Anxiety in Health Behaviors and Physical Illness (Series in Anxiety and Related Disorders)

Anxiety in Health Behaviors and Physical Illness SERIES IN ANXIETY AND RELATED DISORDERS Series Editor: Martin M. Ant...

Author: Michael J. Zvolensky | Jasper A. J. Smits

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Anxiety in Health Behaviors and Physical Illness

SERIES IN ANXIETY AND RELATED DISORDERS Series Editor: Martin M. Antony, Professor, Department of Psychology, Ryerson University, Toronto, Ontario, Canada ACCEPTANCE AND MINDFULNESS-BASED APPROACHES TO ANXIETY Conceptualization and Treatment Edited by Susan M. Orsillo and Lizabeth Roemer CONCEPTS AND CONTROVERSIES IN OBSESSIVE-COMPULSIVE DISORDER Edited by Jonathan S. Abramowitz and Arthur C. Houts SOCIAL ANXIETY AND SOCIAL PHOBIA IN YOUTH Characteristics, Assessment, and Psychological Treatment Christopher A. Kearney TREATING HEALTH ANXIETY AND FEAR OF DEATH A Practitioner’s Guide Patricia Furer, John R. Walker, and Murray B. Stein TREATING TRICHOTILLOMANIA Cognitive-Behavioral Therapy for Hairpulling and Related Problems Martin E. Franklin and David F. Tolin ANXIETY IN HEALTH BEHAVIORS AND PHYSICAL ILLNESS Edited by Michael J. Zvolensky and Jasper A. J. Smits

A Continuation Order Plan is available for this series. A continuation order will bring delivery of each new volume immediately upon publication. Volumes are billed only upon actual shipment. For further information please contact the publisher.

Anxiety in Health Behaviors and Physical Illness Michael J. Zvolensky University of Vermont Burlington, Vermont, USA

Jasper A. J. Smits Southern Methodist University Dallas, Texas, USA

Michael J. Zvolensky, Ph.D. Department of Psychology University of Vermont John Dewey Hall 2 Colchester Avenue Burlington, VT 05405-0134 USA [email protected]

ISBN 978-0-387-74752-1

Jasper A. J. Smits, Ph.D. Department of Psychology Southern Methodist University 6424 Hilltop Lane Dallas, TX 75205 USA [email protected]

e-ISBN 978-0-387-74753-8

Library of Congress Control Number: 2007935078 © 2008 Springer Science+Business Media, LLC All rights reserved. This work may not be translated or copied in whole or in part without the written permission of the publisher (Springer Science+Business Media, LLC, 233 Spring Street, New York, NY 10013, USA), except for brief excerpts in connection with reviews or scholarly analysis. Use in connection with any form of information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed is forbidden. The use in this publication of trade names, trademarks, service marks, and similar terms, even if they are not identified as such, is not to be taken as an expression of opinion as to whether or not they are subject to proprietary rights. Printed on acid-free paper. 9 8 7 6 5 4 3 2 1 springer.com

Preface

Research has been accumulating on the prevalence and nature of the cooccurrence between various forms of anxiety disorders and problematic health behaviors as well as physical illness. This research has significant implications for both those interested and affected by anxiety as well as physical health factors. Yet, it is striking that there has been little systematic integration of this health-oriented research in contemporary science and practice on anxiety and its disorders. This relative neglect is unfortunate given that the co-occurrence of anxiety and health problems is a major public health priority when measured both in human and financial terms. The overarching aim of this book is to provide a single resource that offers current theoretical perspectives and cutting eZdge reviews of scientific research on health behaviors and physical illness in relation to anxiety and its disorders. A critical analysis of this emerging literature is needed to help move this field forward, making this proposed volume timely. The specific objectives of this edited book are to (1) provide a review of the literature on the link between anxiety and certain health behaviors and processes as well as physical illness; (2) present contemporary theories of their co-occurrence and interplay (e.g., onset, maintenance, and relapse); and (3) provide an analysis of recent research in regard to therapeutic models for targeting these problems. The book is organized into two general sections. In the first part of the book, prototypical health behaviors – smoking, alcohol, illicit substance use, exercise, and sleep – are discussed in relation to anxiety and its disorders. In the second part of the book, the association between anxiety psychopathology and physical health conditions – chronic pain, cardiovascular disease, asthma, HIV/ AIDS – and their treatment are covered. In this same section, the potential role of puberty and the menstrual cycle in the onset and maintenance of anxiety psychopathology are discussed. Inspection of the excellent and comprehensive works has yielded a number of broad-based conclusions relevant to informing research and practice for anxiety disorders. First, there is consistent empirical evidence that medical problems and poor health behaviors are overrepresented among persons with anxiety disorders, and vice versa. Thus, there is a pressing need to marshal information on anxiety-health processes to better serve this population. Second, as each v

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contribution makes clear, there is uniform evidence that both health behaviors and physical illness can, and do, affect the nature of anxiety psychopathology. Yet, the exact nature of these associations depends on the specific disorder and health factor in question. And finally, a variety of the chapters make clear that persons suffering from anxiety psychopathology and poor health behaviors or medical illnesses may need specialized interventions to prompt clinical change. That is, traditional interventions may not be ideally suited or maximize clinical benefit for this population. For us, the present book offers the opportunity to appreciate the importance and complexity involved with the study of anxiety disorders. For many years, health behaviors and medical illnesses have been a neglected facet of anxiety disorder research and practice. The contributions in this book help drive home the message that such neglect is unwarranted, and that by working to better understand the enigmas between health status and functioning and anxiety psychopathology, significant clinically-relevant strides can likely be achieved. We hope the present book helps move such work forward and bring a better quality of life and reduced morbidity to persons with anxiety disorders in the future. We owe gratitude to many people who have helped us complete this project. First among these are the experts who authored the chapters. We would like to thank them for their hard work and dedication. We also appreciate the comments and suggestions of Dr. Martin Antony, the editor of the Series in Anxiety and Related Disorders, and the assistance of Anna Tobias of Spinger with the publishing of this book. Lastly, we continue to be appreciative of our respective family members, Heidi and Jack Zvolensky and Jill and Stella Smits, for their love and support. April 2007

Michael J. Zvolensky, Ph.D. University of Vermont Jasper A. J. Smits, Ph.D. Southern Methodist University

Contents

Preface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Contributors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Part I: Health Behaviors and Anxiety Disorders Tobacco Use and Panic Psychopathology: Current Status and Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Michael J. Zvolensky, Theresa Leyro, Amit Bernstein, Matthew T. Feldner, Andrew R. Yartz, Kimberly Babson, and Marcel O. Bonn-Miller Alcohol Use and Anxiety Disorders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Brigitte C. Sabourin and Sherry H. Stewart Illicit Drug Use Across the Anxiety Disorders: Prevalence, Underlying Mechanisms, and Treatment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Matthew T. Tull, David E. Baruch, Michelle S. Duplinsky, and C. W. Lejuez The Promise of Exercise Interventions for the Anxiety Disorders . . . . . . . . Jasper A. J. Smits, Angela C. Berry, Mark B. Powers, Tracy L. Greer, and Michael W. Otto

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Anxiety and Insomnia: Theoretical Relationship and Future Research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105 Thomas W. Uhde and Bernadette M. Cortese Part II: Physical Conditions and Anxiety Disorders Anxiety Disorders and Physical Illness Comorbidity: An Overview . . . . . . 131 Tanya Sala, Brian J. Cox, and Jitender Sareen

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Contents

The Relation Between Puberty and Adolescent Anxiety: Theory and Evidence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155 Ellen W. Leen-Feldner, Laura E. Reardon, Chris Hayward, and Rose C. Smith Anxiety, Anxiety Disorders, and the Menstrual Cycle . . . . . . . . . . . . . . . . 181 Sandra T. Sigmon and Janell G. Schartel Pain and Anxiety Disorders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 207 Gordon J.G. Asmundson, Murray P. Abrams, and Kelsey C. Collimore Asthma in Anxiety and Its Disorders: Overview and Synthesis . . . . . . . . . . 237 Lisa S. Elwood and Bunmi O. Olatunji Cardiovascular Disease and Anxiety . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 279 Kamila S. White HIV and Anxiety. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 317 Conall O’Cleirigh, Trevor A. Hart, and Carolyn A. James Physical Illness and Treatment of Anxiety Disorders: A Review . . . . . . . . . 341 Norman B. Schmidt, Meghan E. Keough, Lora Rose Hunter, and Ann P. Funk Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 367

Contributors

Murray P. Abrams, B.A., Anxiety and Illness Behaviours Laboratory, University of Regina Gordon J.G. Asmundson, Ph.D. Anxiety and Illness Behaviours Laboratory, University of Regina Kimberly Babson, B.A., Department of Psychology, University of Arkansas David E. Baruch, Center for Addictions, Personality, and Emotion Research and the University of Maryland Amit Bernstein, Ph.D., Veterans Affairs Palo Alto Health Care System and University of Vermont Angela C. Berry, M.A., Department of Psychology, Southern Methodist University Marcel Bonn-Miller, B.A., Department of Psychology, University of Vermont Kelsey C. Collimore, B.S., Anxiety and Illness Behaviours Laboratory, University of Regina

Bernadette M. Cortese, Ph.D., Department of Psychiatry, Penn State College of Medicine and Hershey Medical Center Brian J. Cox Ph.D., Department of Community Health Sciences and Department of Psychiatry, University of Manitoba Michelle S. Duplinsky, Center for Addictions, Personality, and Emotion Research and the University of Maryland Lisa S. Elwood, M.A., Department of Psychology, University of Arkansas Matthew T. Feldner, Ph.D., Department of Psychology, University of Arkansas Ann P. Funk, M.A., Department of Psychology, Florida State University Tracy L. Greer, Ph.D., Department of Psychiatry, University of Texas Southwestern Medical Center at Dallas

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Contributors

Trevor A. Hart, Ph.D., Department of Psychology, York University

Mark B. Powers, Ph.D., Department of Psychology, University of Amsterdam

Chris Hayward, M.D., M.P.H., Department of Psychiatry and Behavioral Sciences, Stanford University

Laura E. Reardon, M.A., Department of Psychology, University of Arkansas

Lora Rose Hunter, B.A., Department of Psychology, Florida State University

Brigitte C. Sabourin, B.A., Department of Psychology, Dalhousie University

Carolyn A. James, M.A., Department of Psychology, York University, Toronto

Tanya Sala, M.D., FRCPC, Department of Psychiatry, University of Manitoba

Meghan E. Keough, M.S., Department of Psychology, Florida State University

Jitender Sareen B.Sc., M.D., FRCPC, Department of Community Health Sciences and Department of Psychiatry, University of Manitoba

Ellen W. Leen-Feldner, Ph.D., Department of Psychology, University of Arkansas

Janell G. Schartel, M.A., Department of Psychology, University of Maine

Carl W. Lejuez, Ph.D., Center for Addictions, Personality, and Emotion Research and the University of Maryland

Norman B. Schmidt, Ph.D., Department of Psychology, Florida State University

Teresa Leyro, B.A., Department of Psychology, University of Vermont

Sandra T. Sigmon, Ph.D. Department of Psychology, University of Maine

Conall O’Cleirigh, Ph.D., Massachusetts General Hospital/ Harvard Medical School and Fenway Community Health

Rose C. Smith, B.A., Department of Psychology, University of Arkansas

Bunmi O. Olatunji, Ph.D., Department of Psychology, Vanderbilt University

Jasper A. J. Smits, Ph.D., Department of Psychology, Southern Methodist University

Michael W. Otto, Ph.D., Center for Anxiety and Related Disorders, Boston University

Sherry H. Stewart, Ph.D., Departments of Psychiatry and Psychology, Dalhousie University

Contributors

Matthew T. Tull, Ph.D., Center for Addictions, Personality, and Emotion Research and the University of Maryland

Thomas W. Uhde, M.D. Department of Psychiatry, Penn State College of Medicine and Hershey Medical Center

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Kamila S. White, Ph.D., University of Missouri-Saint Louis Andrew R. Yartz, Ph.D., Department of Psychology, University of Vermont Michael J. Zvolensky, Ph.D., Department of Psychology, University of Vermont

Part I

Health Behaviors and Anxiety Disorders

Tobacco Use and Panic Psychopathology: Current Status and Future Directions Michael J. Zvolensky, Teresa Leyro, Amit Bernstein, Matthew T. Feldner, Andrew R. Yartz, Kimberly Babson, and Marcel O. Bonn-Miller

Recently, there has been increased effort to better understand linkages between tobacco use and the anxiety disorders (Feldner, Babson, & Zvolensky, 2007; Morissette, Tull, Gulliver, Kamholz, & Zimering, 2007; Morrell & Cohen, 2006; Zvolensky, Bernstein, Marshall, & Feldner, 2006; Zvolensky, Feldner, Leen-Feldner, & McLeish, 2005; Zvolensky, Schmidt, & Stewart, 2003). These efforts are theoretically and clinically important because substance use problems frequently co-occur with anxiety psychopathology, and anxiety-related factors often play a role in tobacco use and dependence (Morissette et al., 2007; Morrell & Cohen, 2006; Zvolensky, Bernstein et al., 2006). However, our understanding of the explanatory nature of these comorbid relations is only beginning to emerge. The purpose of the present chapter is to provide a current review of extant empirical work pertaining to the inter-relations between tobacco use and panic psychopathology. We expressly and specifically focus on panic psychopathology, rather than anxiety disorders more broadly, as most of the work on tobacco and anxiety relations to date has focused on panic. This chapter is organized into four sections. First, we briefly describe panic psychopathology. Second, we review risk factor terminology developed by Kraemer, Kazdin, and Offord (1997), in order to establish a nomenclature for conceptualizing interrelations between tobacco and panic psychopathology. Third, we describe tobacco use and common patterns of use. Fourth, we discuss the nature of comorbidity between tobacco use and panic psychopathology and review and evaluate the related empirical evidence. We focus both on the role of tobacco use in the onset and maintenance of panic psychopathology, and the role of panic factors and processes in the onset and maintenance of smoking. Within each of these sections, we identify gaps in the existing literature and highlight formative questions for future research.

Michael J. Zvolensky University of Vermont, John Dewey Hall, Burlington, VT 05405-0134, Tel: 802-656-8994, Fax: 802-656-8783 [email protected]

M. J. Zvolensky, J. A. Smits (eds.), Anxiety in Health Behaviors and Physical Illness. Ó Springer 2008

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Panic Psychopathology The term ‘‘panic psychopathology’’ is used in this chapter to denote panic attacks, panic disorder, and agoraphobia (with or without panic disorder). Panic attacks are a subjective sense of extreme fear or impending doom accompanied by an autonomic nervous system surge and a strong flight-or-fight action tendency (Barlow, Brown, & Craske, 1994). Recent estimates of unexpected (‘‘out of the blue’’) panic attacks in representative samples suggest that approximately 20% of individuals experience such attacks at one point in their lives and 11.2% in the past 12-months (Kessler, Chiu, Jin, Ruscio, Shear, & Walters, 2006). Thus, panic attacks are a relatively common psychological experience and many people experience panic attacks without necessarily developing panic disorder (i.e., nonclinical panic attacks; Norton, Cox, & Malan, 1992). Typically, individuals who experience nonclinical panic attacks do not experience these attacks as ‘‘spontaneous’’ or ‘‘uncued’’ (as is generally the case in panic disorder), but rather in certain contexts such as stressful or threatening social situations (Norton, 1989). Panic attacks also occur among those with other types of psychopathology (i.e., beyond panic disorder; Bryant & Panasetis, 2005). Panic attack onset can occur across the lifespan, but early onset tends to first occur between the ages of 12–13 years (Hayward et al., 1992; Warren & Zgourides, 1988; please see ‘‘Developmental Course’’ section below for further details). Panic disorder involves recurrent unexpected panic attacks and anxious apprehension about the possibility of experiencing future panic episodes (American Psychiatric Association, 2000). Lifetime estimates of panic disorder without agoraphobia are 3.7% and 1.1% for panic disorder with agoraphobia (Kessler et al., 2006). Twelve-month estimates for panic disorder (with or without agoraphobia) are approximately 2.8% (Kessler et al., 2006). Thus, panic disorder is a relatively common psychiatric disorder both in terms of lifetime and 12-month prevalence rates. This clinical condition is generally regarded as a disorder of adulthood with a median age of onset of 24 (Burke, Burke, Regier, & Rae, 1990), although emerging research has noted that another possible ‘‘peak onset period’’ may be between ages 45–54 years (Burke et al., 1990). Panic disorder with and without agoraphobia is associated with a chronic, fluctuating course and high rates of both psychiatric comorbidity and substance use disorders (Zvolensky, Bernstein et al., 2006). Although not all persons with panic disorder will meet diagnostic criteria for agoraphobia, individuals with panic disorder often show signs of avoiding potentially threatening situations in which a panic attack might occur (Feldner, Zvolensky, & Leen-Feldner, 2004). Agoraphobia reflects a pattern of behavior characterized by consistent avoidance of threatening situations where a panic attack or high anxiety is perceived to be likely (e.g., limited options to escape), or experiencing marked emotional distress when in such situations. Avoidance behavior can be multifaceted, with a wide range of stimuli that are perceived as

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threat-relevant (e.g., anything from being in crowds to certain substances like caffeine; Feldner et al., 2004). Although agoraphobia does not necessarily require the presence of panic attacks or panic disorder (Fava, Grandi, & Canestrari, 1988), researchers frequently conceptualize agoraphobia as a complication of (severe) panic disorder (Barlow, 2002). However, it is noteworthy that this approach has been increasingly called into question in recent years, as research indicates that there may be differing forms of agoraphobic avoidance (Hayward & Wilson, in press). Regardless, agoraphobia with or without panic disorder often is related to higher rates of clinically significant life impairment and severity of illness (Kessler et al., 2006). The onset of agoraphobia with or without panic disorder is not as firmly established as that of panic attacks and panic disorder; though research suggests it likely occurs later in life than the onset of panic attacks and panic disorder (Lindesay, 1991).

Vulnerability Nomenclature Explicit delineation of terminology facilitates efforts to understand the nature of associations between tobacco use and panic psychopathology. Led by the work of Kraemer and colleagues, groundbreaking conceptual strides have created a clearer understanding of various risk processes (Kazdin, Kraemer, Kessler, Kupfer, & Offord, 1997; Kraemer et al., 1997; Kraemer, Lowe, and Kupfer, 2005; Kraemer, Stice, Kazdin, Offord, & Kupfer, 2001). Specifically, as is reviewed in this section, Kraemer and colleagues have worked to standardize operational definitions for risk processes to increase the clarity and consistency with which these factors are communicated across studies. Risk factors. A risk factor is a variable that is related to, and temporally precedes, an unwanted outcome (Kraemer et al., 1997). Causal risk factors reflect variables that, when modified in some way (e.g., through an intervention), produce change (increase or decrease) in the dependent variable of interest (Kraemer et al., 1997). Controlled research designs are necessary to document causal effects because they can rule out competing alternative explanations (e.g., ‘‘confounding variables’’). Proxy risk factors are variables that are related to an outcome of interest, but this association is due to the proxy risk factor’s relation with another causal risk factor (Kraemer et al., 2001). Thus, change in a proxy risk factor would not yield corresponding systematic change in an outcome variable; accordingly, a proxy risk factor may ‘‘mark’’ risk, but not explain or account for such risk. Due to the importance of the ability to change a risk factor, both risk and proxy risk factors often are further categorized on the basis of whether or not they are malleable (i.e., can be changed or altered). When a risk factor cannot be changed, it can be classified as a fixed marker, whereas when it can be changed, it can be classified as a variable risk factor (Kraemer et al., 2005).

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A risk factor also can be contrasted with a maintenance factor. A maintenance factor is a variable that predicts the persistence of an existing condition over time among individuals already demonstrating the outcome (Stice, 2002). In theory, the same categorization scheme could be applied to maintenance factors in terms of whether or not they are causal or proxy maintenance factors (Kazdin et al., 1997). Moreover, a risk factor also may subsequently function as a maintenance factor. Qualifying conditions for risk factor effects. Clarifying relations between vulnerability processes and outcomes represents only the ‘‘first step’’ in a larger process of risk factor research. That is, this step represents a focus on ‘‘main effects,’’ but does not explicate how, when, or among whom a specified risk process unfolds (see Zvolensky, Schmidt, Bernstein, & Keough, 2006). We do not delve fully into these explanatory processes within the present chapter, as extant work has largely focused on questions of main effects at this early developmental stage of this area of study.

Tobacco Use: Definition, Nature, and Prevalence Cigarette smoking. Cigarette smoking is widely recognized as the most popular form of tobacco use and as a major public health problem (Windle & Windle, 1999). Indeed, cigarette smoking remains a leading preventable cause of death and disability in the United States (Centers for Disease Control and Prevention [CDC], 1994). Smoking is considered a key factor in various types of medical illness, including heart disease, a variety of pulmonary diseases (e.g., chronic obstructive pulmonary disease), and many types of cancer (CDC, 1994, 2002). For instance, smoking is responsible for almost 31% of all cancer-related deaths (American Cancer Society [ACS], 2006a). Although smoking increases one’s risk for developing many of these lethal medical diseases, quitting smoking decreases the risk of developing such problems and may increase the survival time among persons who have already developed such medical problems (Samet, 1992). Despite a reduction in smoking prevalence over the past 25 years, approximately 45–48 million (approximately 22% to 25%) adults in the U.S. currently smoke (CDC, 1996). Though nearly 70% of these smokers are motivated to quit (CDC, 2002), approximately 90–95% of smokers who do try to quit smoking on their own (Cohen et al., 1989), and 60–80% who attend treatment programs, relapse to smoking (CDC, 2002). Additional work suggests that 64% of youth (adolescents) report having tried cigarettes and 14% have smoked frequently in the past month (i.e., 20 out of the past 30 days; CDC, 2002). Thus, there is evidence that smoking is not only a major source of death and disability, but that once started it is often difficult to stop. Smokeless tobacco use. Although cigarettes are the most common type of tobacco use, there also is a significant population of smokeless tobacco

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users in the U.S. and other regions of the world (e.g., India; ACS, 1999). Epidemiological data in the U.S., for example, suggest that approximately 3% of individuals have used some form of smokeless tobacco – either snuff (finely ground, shredded tobacco) or chewing tobacco – in the past month (ACS, 1999). These rates of use are elevated among young Caucasian males compared to females, and among those in southeastern and north central states compared to other regions, as well as rural compared to urban settings (Hatsukami & Severson, 1999). For example, past work suggests that the highest rates of current use (16.6%) are among Caucasian males 18–25 years of age (CDC, 1994). In general, rates of smokeless tobacco use are noteworthy because smokeless tobacco contains carcinogens (e.g., tobacco-specific nitrosamines [TSNAs]; National Cancer Institute and National Institute of Health (NCI/NIH), 2006) known to be causal agents in lung, oral, esophageal, liver, and pancreatic cancer (About: Smoking Cessation, 2006b). In addition, smokeless tobacco use is associated with greater nicotine absorption and for longer periods of time (e.g., stays in the bloodstream for greater durations of time) than cigarette smoking (ACS, 2006; NCI/NIH 2006b). Similar to cigarettes, smokeless tobacco use can lead to increased rates of physical disease (e.g., oral cancer, gum disease) and nicotine addiction (ACS, 1999). Whereas the risks associated with cigarette use have become well-publicized in the U.S., public awareness about the dangers of smokeless tobacco remains limited. Indeed, many perceive smokeless tobacco as a ‘‘risk-free alternative’’ to cigarette smoking (CDC, 1994). Although as many as 50% of smokeless tobacco users report wanting to quit (ACS, 2006a), as with cigarettes, rates of relapse remain high (Hatsukami, Jensen, Allen, Grillo, & Bliss, 1996). In a recent review of smokeless tobacco treatment programs, Hatsukami and Severson (1999) estimated a 3–6 month abstinent rate of 12%–30% with intensive behavioral treatments fairing better than other intervention options. Thus, similar to cigarette use, smokeless tobacco use is an addictive behavior that is difficult to quit and more intensive care appears to yield relatively better outcomes.

Prevalence of Comorbid Tobacco Use and Panic Psychopathology There have been both representative surveys and community-based studies focused on addressing the extent of the co-occurrence between tobacco use and panic psychopathology. To date, this work has largely centered on cigarette smoking rather than smokeless tobacco. Additionally, from a historical perspective, the vast majority of early work in this domain did not focus on panic or other specific anxiety conditions, but rather, addressed anxiety disorders as a single ‘‘class of problems’’ (e.g., Breslau, 1995; Brown, Lewinsohn, Seeley, & Wagner, 1996; Costello, Erkanli, Federman, & Angold, 1999; Degenhardt, Hall, & Lynskey, 2001; Hughes, Hatsukami, Mitchell, & Dalgren, 1986;

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Kandel, Huang, & Davies, 2001; Kandel et al., 1997; Merikangas et al., 1998; Tilley, 1987). Although such work has importantly directed scientific attention to tobacco-anxiety relations at the broadest level, it is limited in demarcating specific rates of co-occurrence for (particular) disorders of interest, such as panic. Thus, for the sake of explanatory specificity, we focus our summary on investigations that expressly distinguished panic psychopathology from other anxiety disorders. Comorbidity prevalence. The majority of studies have focused on documenting rates of smoking among persons with panic psychopathology. The criteria for smoking behavior has varied across investigations. Moreover, treatmentbased recruitment strategies have been most commonly employed, perhaps making these data somewhat less generalizable to the overall smoking population. Nonetheless, among treatment-seeking adults, several studies have reported that current daily smoking among patients with panic psychopathology (either panic disorder or agoraphobia or both) ranged from 19% Panic (Baker-Morissette, Gulliver, Wiegel, & Barlow, 2004) to 57% (Himle, Thyer, & Fischer, 1988), with the vast majority of investigations falling between 30% to 50% (Amering et al., 1999; Lopes et al., 2002; McCabe et al., 2004; Pohl, Yeragani, Balon, Lycaki, & McBride, 1992). These rates of daily smoking are typically higher than comparison groups involving persons without psychiatric problems and typically higher, or as high as, rates among persons with other anxiety or mood disorders (McCabe et al., 2004). Thus, these data collectively suggest that smoking is a relatively common unhealthy behavior among treatment-seeking individuals with panic psychopathology. Studies focused on non-treatment seekers are currently limited. Of the available work, one study focused on youth (Hayward, Killen, & Taylor, 1989; 95 9th graders in public schools) and the other on college students (Valentiner, Mounts, & Deacon, 2004, n = 337). In both investigations, individuals with panic attacks, but not necessarily panic disorder or agoraphobia, had higher rates of cigarette use on a ‘‘regular basis’’ (Hayward et al., 1989; Valentiner et al., 2004). For example, Hayward et al. (1989) reported that of those with a lifetime history of panic attacks, 77% had engaged in ‘‘experimental’’ or ‘‘regular’’ cigarette use compared with 48% of adolescents without a lifetime history of panic attacks. These results, albeit highly limited in overall scope, generally parallel those of the treatment-oriented investigations noted earlier in terms of documenting elevated use prevalence among individuals with panic problems. Another set of investigations has utilized representative sampling methods to explore the nature of tobacco use among those with panic psychopathology (Covey, Hughes, Glassman, Blazer, & George, 1994; Farrell et al., 2001; Lasser et al., 2000). In perhaps the most comprehensive and well-known of these investigations, Lasser et al. (2000) examined smoking status according to psychiatric diagnoses using data from the National Comorbidity Survey (NCS), a nationally representative study that used structured clinical interviews to document mental illness (Kessler et al., 1994). Participants were 4,411 individuals aged

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15 to 54 years. Among individuals diagnosed with panic attacks, panic disorder, and agoraphobia in their lifetime, 38%, 35%, and 38% were current smokers, respectively. These rates were significantly greater than rates of current smoking among individuals without mental illness. By comparison, 36% of individuals with a lifetime history of major depression and 49% of individuals with a lifetime diagnosis of drug abuse or dependence were current smokers. Rates of lifetime smoking among persons with a lifetime history of panic psychopathology (i.e., panic attacks, panic disorder, or agoraphobia) ranged from 58% to 61%. When diagnostic status in the past month was used as the grouping variable, current rates of smoking were 46% among persons with panic attacks, 42% among persons with panic disorder, and 48.1% among persons with agoraphobia. It is noteworthy that as number of mental diagnoses increased (ranging from 0 to 4 or more), the percentage of heavy (i.e., peak consumption exceeding 24 cigarettes a day) compared to relatively lighter (i.e., peak consumption less than 24 cigarettes per day) smokers increased. Overall, these data, coupled with the treatment-seeking data noted earlier, suggest that smoking occurs at relatively higher rates among those with panic psychopathology compared to those with no mental illness. Whereas the studies just reviewed focused on smoking among those with panic psychopathology, other investigations have sought to evaluate rates of panic psychopathology among smokers (Black, Zimmerman, & Coryell, 1999; Breslau, Kilbey, & Andreski, 1991; Goodwin, Zvolensky, & Keyes, 2007; Nelson & Wittchen, 1998). All of these investigations except that by Black and colleagues (1999), which involved community-based recruitment, involved some sort of representative sampling strategy. In contrast to the studies reviewed earlier, these investigations attempt to understand panic within the context of tobacco dependence and severity. Here, across studies, results indicate that among those persons meeting criteria for more addictive use of cigarettes (e.g., nicotine dependence), there is a greater prevalence of panic psychopathology (Breslau et al., 1991). For example, Breslau and colleagues (1991) found that 6.6% of persons meeting criteria for moderate dependence, 4.8% of those with mild dependence, and 2.4% of those with no dependence had a lifetime diagnosis of panic disorder. Nelson and Wittchen (1998) similarly found that among participants endorsing a lifetime history of smoking (yes/no), 7.6% met lifetime diagnostic criteria for panic attacks, 2% for panic disorder, and 4.4% for agoraphobia. These rates of panic psychopathology were significantly greater than those reported among nonsmokers; 2.4% had a panic attack history, 0.7% had panic disorder, and 1.6% had agoraphobia. Smokers with a lifetime nicotine dependence diagnosis compared to smokers without such a diagnosis evidenced greater rates of panic attacks (11.3% versus 4.0%), panic disorder (2.2% versus 1.8%), and agoraphobia (6.4% versus 2.5%). It should be noted that a similar, albeit not uniform, pattern of findings was apparent for individuals with other psychiatric disorders (e.g., alcohol dependence, drug dependence).

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In the only study to focus on cigarette and smokeless tobacco use, Goodwin and colleagues (2007) found that among a representative sample from the U.S., rates of past-year panic attacks (with or without agoraphobia) were greatest among smokers with nicotine dependence (6.7%), followed by cigarette use with no dependence (2.2%), both of which were greater than among those with no past year cigarette or smokeless tobacco use (1.5%). Being dependent on smokeless tobacco (1.9%) was largely comparable to no past year tobacco use, both of which were greater than smokeless tobacco use without nicotine dependence (0.6%). Overall, the extant literature suggests that heavier rates of cigarette use (greater degrees of dependence) are associated with a greater rate of comorbidity with panic psychopathology. Although limited, this pattern of findings does not yet seem to be apparent for smokeless tobacco use, suggesting that factors related to the ‘‘mode of administration’’ may be an important domain to further understand in tobacco-panic linkages. Future directions. Though there are many avenues for future inquiry into the nature of tobacco-panic comorbidity, here we highlight a few domains of primary importance based upon the gaps in the existing literature. Before specific recommendations are made, it is striking to point out that, to the best of our knowledge, none of the past work focused on comorbidity issues has been a priori oriented on tobacco-panic relations. Thus, it is, perhaps, not surprising that some of the assessment approaches used in past work may not be fully comprehensive or geared towards maximizing information about the nature of the co-occurrence of these specific behavioral problems. As such, a first-step in improving research in this domain would be to design evaluations specifically focused on better understanding tobacco-panic comorbidity. Beyond this general issue, there are at least three specific points within this domain that would be particularly useful to address. First, only one study has provided data on smokeless tobacco and panic comorbidity. Thus, to foster further empirical knowledge in this domain, it is necessary to complete investigations wherein multiple forms of tobacco use are assessed to provide information on both cigarette use and smokeless tobacco. Aside from providing much needed data on smokeless tobacco and psychopathology, this type of work would help to define the parameters of tobacco-panic relations more generally. In this same context, it would be advisable to clarify the extent to which the observed co-occurrence rates between tobacco use and panic psychopathology are similar to, or different from, other health behaviors (e.g., alcohol use, physical exercise). In general, research suggests smoking is strongly positively related to alcohol and other substance use and negatively related to exercise (Zvolensky & Bernstein, 2005). This work is necessary because it would further explicate the degree to which tobacco use is or is not unique to the co-occurrence of panic psychopathology. As the present book illustrates, research in the health-anxiety linkage is only now emerging.

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Second, there are a number of issues central to the generalizability of the reviewed investigations. The large majority of these studies have nottilized representative samples and therefore selection biases may be operative. It also is noteworthy that only one study (Hayward et al., 1989) focused exclusively on youth. Therefore, it is not possible to generalize the present tobacco-panic relations to other segments of the lifespan (e.g., adolescents) or the various stages of tobacco use (e.g., initiation, maintenance) that would presumably be apparent across different age ranges. Additionally, there are very limited data on tobacco-panic psychopathology linkages from a cross-national perspective. As factors that govern tobacco use may vary across communities and cultures, and in conjunction with the world-wide public health impact of both smoking and panic problems, it is important to extend work in this area to more diverse global populations. Finally, existing work has largely utilized limited assessments of smoking and panic psychopathology. Due to the focus on the ‘‘presence or absence of daily smoking,’’ little is known about the nature or topography of smoking behavior in terms of its association with panic psychopathology (e.g., age of onset, age of daily use, amount used when smoking the heaviest). This work would be improved by broadening smoking assessments to include a more detailed account of smoking history. It also may be productive to incorporate a multidimensional approach that takes into consideration theoretically-relevant motivational processes underlying cigarette use (Piper et al., 2004). This type of approach could be particularly valuable when examining linkages between smoking and panic psychopathology, whereby motivation to smoke to avoid negative affect might be a formative psychological process (Zvolensky, Schmidt, Antony et al., 2005).

Nature of the Associations Between Tobacco Use and Panic Psychopathology Developmental course. As a basis for understanding the nature of the relations between tobacco use and panic psychopathology, it is important to first clarify their developmental course. Representative data on the age of onset of panic attacks and smoking provide a means to evaluate temporal sequence. Research suggests that the onset of daily smoking typically occurs between the ages of 15 and 20 and rarely after age 25 (Breslau, Johnson, & Hiripi, 2001). For example, the CDC reports that in the United States, approximately 3,900 adolescents between the ages of 12 and 17 years initiate cigarette smoking each day (CDC, 2004), and an additional 1,500 become daily cigarette smokers each day (Substance Abuse and Mental Health Services Administration, 2005). Early studies of smokeless tobacco use indicate a mean age of onset between 10 and 12 years (i.e., Gottlieb, Pope, Rickert, & Hardin, 1993).

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Studies examining the typical age of onset for panic attacks also suggest that such problems often first occur in adolescence. For example, Goodwin and Gotlib (2004) reported that the mean age of panic attack onset was 13.4 years (n = 1,285; age range 9–17). Other studies based on community or school samples have found similar results, with the modal age of onset of panic attacks being 12 years old (Hayward et al., 1992; Warren & Zgourides, 1988), and clinical samples report a slightly younger age of panic attack onset (Alessi & Magen, 1988; Black & Robbins, 1990). These data suggest that, across studies, panic attack onset tends to first occur between the ages of 12–13 years. One important interpretative caveat to these investigations is that they focus exclusively on youth and expressly do not sample from a larger age range. Thus, it is possible that the ‘‘average’’ age of onset of panic attacks may be different if the sampling strategy incorporated adults. Based on available indirect data from smoking and panic attack age of onset studies, it appears that in many instances the typical age of onset of panic attacks precedes the typical age of onset of smoking. However, retrospective reports of smokers with ‘‘active panic problems’’ are not entirely consistent with this perspective. For example, Amering and colleagues (1999) examined 102 consecutive panic disorder patients with or without agoraphobia attending an academic treatment clinic in Austria. Participants were diagnosed using the SCID-III-R (First, Spitzer, Gibbon, & Williams, 1995) and interviewed about their smoking status. Individuals presenting with ‘‘severe somatic illness’’ and comorbid depression and other psychiatric illnesses were excluded from the study. Amering and colleagues (1999) reported that the onset of smoking preceded the onset of panic disorder (cf. panic attacks) by 12.3 years (SD = 9.4) in a community sample of individuals with the condition (n = 102). Bernstein, Zvolensky, Schmidt, and Sachs-Ericsson (2007) directly evaluated onset patterns among 4,409 adults (Mage = 33.1, SD = 10.7, females = 2,221) from the NCS (Kessler et al., 1997). Results indicated that among cases with a lifetime history of comorbid daily smoking and panic attacks (n = 167), the onset of daily smoking (M = 16.0 years, SD = 3.0) preceded the onset of panic attacks (M = 27.8 years, SD = 7.6) in the majority, but not among all, of the comorbid cases (63.7%, n = 106). A relatively large minority of comorbid cases (33%; n = 55) reported that panic attacks (M = 11.4 years, SD = 5.2) preceded the onset of daily smoking (M = 18.2 years, SD = 4.7). The concurrent (same year) onset of these two problems appeared rarely (3.3%, n = 6). Also, as the pattern of ages of onset above illustrate, daily smoking demonstrated a relatively consistent mean age of onset (mid to late adolescence) across comorbid sub-samples and the uni-morbid sub-sample of smokers (age 18.5 years). In contrast, the mean ages of onset of panic attacks differed markedly between the comorbid sub-samples and the uni-morbid sub-sample of nonsmokers with panic attacks (age 20.3 years). Overall, while data focused expressly on developmental course and smoking-panic psychopathology is limited, extant studies suggest that the majority of cases may involve smoking preceding panic attacks.

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Future directions. Again, it is important to highlight that work in this domain, although important for illuminating basic facets of tobacco-panic relations, is currently limited. First, to the best of our knowledge, no studies have examined the developmental course for smokeless tobacco. Future prospective work is therefore needed to expand this area of knowledge. Second, future study is needed to more carefully examine the putative smoking-to-panic and panic-to-smoking developmental courses. Third, smoking often occurs in a context of other substance use patterns. Thus, it may be useful to understand the developmental relations of tobacco and panic within the larger developmental context of panic-substance use comorbidity. In this sense, understanding the relative degree of ‘‘specificity’’ of initial findings vis a vis other substance use patterns and problems as well as health behaviors (e.g., physical exercise) may be a fruitful next research step. Current knowledge regarding tobacco use and panic psychopathology. Cross-sectional studies that have utilized interview and self-report methods have uniformly indicated that smoking, compared to non-smoking, is associated with more panic-relevant symptoms and impairment among nonclinical (Zvolensky, Forsyth, Fuse, Feldner, & Leen-Feldner, 2002) and clinical (McCabe et al., 2004; Zvolensky, Eifert, Feldner, & Leen-Feldner, 2003) samples. For example, Zvolensky, Schmidt and McCreary (2003) found that treatment-seeking smokers with panic disorder compared to nonsmokers with panic disorder reported more severe and intense anxiety symptoms, greater interview-based overall severity ratings of panic symptoms, and more social impairment. In these investigations, effects did not vary by gender, age, or other forms of substance use. Moreover, there is emerging evidence that these types of effects are relatively specific to panic disorder and psychopathology that frequently co-occurs with panic (e.g., posttraumatic stress disorder; Feldner et al., 2007). For example, Morissette and colleagues (2006) found that smokers with anxiety disorders, as compared to their non-smoking counterparts, reported higher levels of anxiety sensitivity (i.e., fear of anxiety and bodily-related sensations; McNally, 2002), anxiety symptoms, and agoraphobic avoidance. However, this association was specific to panic disorder and not evident for any of the other studied anxiety disorders, which did not include posttraumatic stress disorder (Morissette et al., 2006). Laboratory studies, although less common, have yielded similar findings. Zvolensky and colleagues (2004), for example, employed a voluntary hyperventilation paradigm to examine associations between smoking and panic-relevant fearful responding to bodily sensations. Results indicated smokers with panic disorder reported greater levels of anxiety than smokers without panic disorder at baseline, and also showed greater increases in anxiety during the post-challenge assessment and recovery periods. Although smokers with, versus without, panic disorder did not differ on baseline or post-challenge anxiety, smokers with, compared to without, panic disorder, demonstrated slower affective recovery from the challenge. These results indicate that smoking compared to not smoking is related to greater affective distress in response to

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panic-relevant cues even among those with panic disorder. Less attention has been focused on determining the relation between smoking rate and level of affective distress or impairment. Yet, a number of studies, some involving prospective measurement (discussed in greater detail below), have found that smoking rate is related to greater degrees of panic-specific emotional symptoms (e.g., panic-relevant avoidance; Breslau & Klein, 1999; Goodwin, Lewinsohn, & Seeley, 2005; Johnson et al., 2000; McLeish, Zvolensky, & Bucossi, 2007; Zvolensky, Kotov, Antipova, & Schmidt, 2003). Thus, there is empirical evidence that both smoking status and rate are related to increased risk for panic-relevant emotional vulnerability. Cross-sectional tests also have helped to clarify factors that may affect the smoking-panic relation. In one study of epidemiologically-defined (i.e., representative) adult residents of Moscow (n = 95 daily smokers from a larger sample of about 400 persons; Zvolensky, Kotov et al., 2003), anxiety sensitivity moderated the effects of cigarettes smoked per day (m = 15) on level of agoraphobic avoidance. This significant interaction accounted for approximately 10% of unique variance after controlling for their respective main effects and the theoretically-relevant factors of problematic alcohol use and negative affectivity. No interaction, however, was found for panic attacks, potentially due to the fact that assessment of this factor was restricted to the past (most recent) week to enhance the validity of panic reports (but probably truncating variability). Similar moderating effects have been evident for perceived health among young adult daily smokers (McLeish, Zvolensky, Bonn-Miller, & Bernstein, 2006), and for neuroticism among a representative sample of adult smokers (Zvolensky, Sachs-Ericsson, Feldner, Schmidt, & Bowman, 2006). Overall, these findings suggest smokers are not a homogeneous group in regard to their risk for panic problems and that individual differences in anxiety sensitivity (or other cognitive-affective factors like perceived health or neuroticism) may be key factors in accounting for such differences. Moderating effects for anxiety sensitivity also have been evident in between-group tests involving smokers and nonsmokers. For example, the combination of high levels of anxiety sensitivity and a positive current smoking status predicted panic symptoms and somatic complaints, but not depressive symptoms in a biological challenge test (Leen-Feldner et al., 2007). Again, such findings suggest that anxiety sensitivity (and possibly other factors) may moderate the relation between smoking and prototypical panic psychopathology variables (panic attacks and somatic complaints) even after controlling for gender and negative affectivity. Moreover, these associations are specific to panic-relevant processes. In a re-analysis of the Russian epidemiological study reported earlier, Zvolensky and colleagues extended this smoking and anxiety sensitivity effect (Zvolensky, Kotov, Bonn-Miller, Schmidt, & Antipova, in press). Here, anxiety sensitivity, again, moderated the association of smoking status with indices of anxiety symptoms; effects were evident after controlling for the variance accounted for by alcohol use problems, environmental stress (past month), and gender.

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Although cross-sectional data are informative in the study of tobacco-panic psychopathology relations, their utility also is limited. Prospective studies offer unique insight into the nature of the observed relations over time, and by extension, the order or temporal sequence of the associations. Researchers have evaluated the association between smoking and risk of panic psychopathology in a number of studies. Breslau and Klein (1999) tested the association between daily smoking and risk for panic attacks and panic disorder. Participants were drawn from two separate epidemiologically-defined data sets. Across both data sets, results indicated that there was a significant lifetime and prospective association between daily smoking and onset of panic attacks and panic disorder; daily smokers were almost 4 times more likely to experience panic attacks and 13 times more likely to develop panic disorder after controlling for major depression and gender. Additionally, among individuals who continued to smoke, compared to those who had quit, there was a significantly increased risk for experiencing a panic attack and panic disorder. Johnson and colleagues (2000) also found that anxiety disorders during adolescence were not significantly related to smoking in young adulthood. However, smoking in adolescence increased the risk for developing agoraphobia and panic disorder during early adulthood. These effects were observed above and beyond the variance accounted for by temperament, family history of psychopathology, drug/alcohol use and other theoretically-relevant factors. Specifically, adolescents who were heavy smokers were 15.6 times more likely to develop panic disorder in early adulthood than non-smokers. Interestingly, adolescents who smoked fewer than 20 cigarettes per day were not at elevated risk for the development of (later) anxiety disorders, potentially suggesting, once again, that heavier smoking levels impart greater panic-related risk. In another prospective study recently completed in Germany, 2,500 participants (ages 14–24 years at baseline) were evaluated over 4 years (Isensee, Wittchen, Stein, Ho¨fler, & Lieb, 2003). Compared with all other levels of smoking, dependent regular smokers at baseline were significantly more likely to develop panic attacks and panic disorder, and a similar pattern was observed for agoraphobia. Similarly, Breslau, Novak, and Kessler (2004) evaluated daily smoking and subsequent onset of psychiatric disorders. Results indicated that the onset of panic disorder (odds ratio = 2.6) and agoraphobia (odds ratio = 4.4) were associated with pre-existing daily smoking after controlling for age, gender, ethnicity, and educational level. Additionally, after controlling for pre-existing psychiatric disorders and sociodemographic characteristics, current nicotine dependent smokers were significantly more likely to have panic disorder compared to current non-dependent smokers and former smokers. Importantly, the likelihood of panic disorder and agoraphobia was significantly reduced as time since quitting increased; these effects were specific to these conditions and not other psychiatric disorders (e.g., major depressive disorder), suggesting quitting smoking likely decreases the risk of developing panic problems, an issue that is discussed in greater detail

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later in the chapter. More recently, Goodwin and colleagues (2005) replicated the results of Breslau and Klein (1999), Johnson et al. (2000), and Isensee et al. (2003) by finding that daily smoking during adolescence was associated with an increased risk for panic attacks and panic disorder in young adulthood. Moreover, the observed effects were no longer evident after controlling for parental smoking and anxiety disorder status, suggesting that these family history characteristics may be formative in the linkages between smoking and panic psychopathology. Prospective tests examining moderating factors in the tobacco use-panic relation are very limited. In the only study to date on this topic, McLeish and colleagues (2007) evaluated the moderating role of anxiety sensitivity in the relation between smoking rate and panic vulnerability variables among a community-based sample of 125 daily smokers (60 females; Mage = 26.02 years). Findings indicate that the interaction between anxiety sensitivity and smoking rate significantly predicted concurrent agoraphobic avoidance (3.2% of unique variance) and change in levels of anticipatory anxiety about bodily sensations during the 3-month follow-up period (4.7% unique variance). Smokers high in anxiety sensitivity who also smoked at greater rates reported the highest levels of avoidance and greatest increase in anticipatory anxiety. These data, in accord with cross-sectional findings (LeenFeldner et al., 2007; Zvolensky, Kotov et al., 2003), once again suggest that anxiety sensitivity is an important individual difference factor that, when coupled with higher rates of smoking, is associated with greater levels of avoidance and anticipatory anxiety among daily smokers, both of which contribute to the development of panic psychopathology. Overall, research co-addressing smoking and panic psychopathology suggests that smoking can be considered a variable risk factor for panic problems. Indeed, existing work provides evidence regarding relations with panic problems based on cross-sectional and prospective studies, but it is noteworthy that this work is rarely multi-method in its approach. To have more confidence in smoking-panic psychopathology relations, the incorporation of multi-method assessment protocols would be an important next research step. Additionally, evidence from cross-sectional, and to a lesser extent, prospective studies indicates that fears of internal sensations (anxiety sensitivity) and perhaps other ‘‘affect-amplifiers’’ (e.g., perceived health, neuroticism) may moderate smoking-panic processes. Future directions. There is a rapidly developing empirical literature on tobacco-use and panic psychopathology relations. Such scientific interest in this work underscores its public health relevance and potential clinical implications (see Zvolensky, Bernstein, Yartz, McLeish, & Feldner, in press, for an expanded discussion of treatment implications of tobacco-panic relations). At the same time, this literature remains relatively under-developed and there are a number of key areas in need of future study. First, as in the area of comorbidity prevalence studies reviewed earlier, there is a dearth of data on smokeless tobacco-panic relations. Virtually no scientific

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data exists on this important topic, making it a fertile area for future exploration. Second, available data suggest daily smoking tends to precede the onset of panic attacks in the majority of cases, although direct evaluations with panic disorder and agoraphobia have not been completed. Given that smoking can be changed via intervention (Abrams et al., 2003), there is evidence of its potential malleability, and hence, possible application to prevention programs for panic psychopathology. Overall, then, evidence that changing cigarette smoking rate or smoking cessation will alter the future risk of panic psychopathology from a preventative standpoint is lacking. Thus, it is currently not clear if smoking represents a variable marker or a variable causal risk factor for panic psychopathology. To clarify this issue, it is important for future research to examine changes in smoking prospectively following experimental manipulation (e.g., smoking cessation intervention; Zvolensky, Schmidt, Bernstein, & Keough, 2006). Third, research has yet to examine the possibility that shared or common risk factors may further explain the development of comorbid tobacco use and panic. It is theoretically possible that certain biological, psychological, and social factors may partially underlie the etiology and maintenance of these behavior problems. And finally, while there is a growing literature on moderating factors, there has been little scientific attention to mediators of smoking-panic associations and therefore almost no empirical knowledge exists pertaining to the putative causal mechanisms of interest. Intensifying the focus on mediators of smoking-panic relations is a clinicallyrelevant and timely task. Specifically, clarification of key mechanisms through which smoking achieves its panicogenic effects will stimulate the development of targeted interventions focused on therapeutic processes, and help to establish such processes (e.g., emotional reactivity) as important in the etiology and/or maintenance of panic-related problems. Only Breslau and Klein (1999) conducted exploratory analyses of possible mediators by evaluating the role of lung disease. Although medical illness is one useful process to better understand, other factors such as perceived health, affect tolerance, various trajectories of emotional distress (e.g., delayed recovery), withdrawal symptoms, and avoidance-oriented smoking patterns are all examples of theoretically-relevant factors deserving of future study (see Zvolensky & Bernstein, 2005, for an expanded discussion). Current knowledge regarding the relation between panic psychopathology. pre-morbid panic risk variables, and tobacco use. Although much of the most highly publicized work on smoking and panic psychopathology pertains to the potential role of smoking in the onset or maintenance of panic problems, panic vulnerability characteristics, broadly encompassing both pre-morbid variables and full-blown panic problems, may conversely impact smoking behavior (Zvolensky & Bernstein, 2005). Work in this domain has focused on empirical evidence related to smoking cessation outcome, expression of withdrawal symptoms, and motivational and cognitive processes related to smoking behavior (e.g., outcome expectancies). A major strength of work in this domain is that study of smoking has involved measurement of various facets of

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smoking-related problems and processes (i.e., motivational processes) as opposed to focusing more narrowly on rates of tobacco use. This multidimensional conceptualization and measurement of smoking behavior is central to theoretical and clinical advances relevant to tobacco-panic relations. Moreover, it provides Moreover, it provides a means by which to further examine the role of panic-specific, and other anxiety factors (e.g., traumatic event exposure, negative affectivity), in smoking initiation (Bernstein, Zvolensky et al., 2007; Feldner et al., 2007; Isensee et al., 2003). Research has shown that affective vulnerability factors like panic psychopathology may be related to problems in quitting smoking. Lasser et al. (2000), for example, reported quit rates (i.e., proportion of lifetime smokers who were not current smokers) in relation to psychiatric diagnosis among a representative sample from the U.S. Using 1-month diagnostic status as a criterion point, the quit rate was 29% for persons with panic attacks, 32% for those with panic disorder, and 23% for persons with agoraphobia. Individuals with both panic attacks and agoraphobia in the past month were significantly less successful in quitting smoking compared to individuals with no mental illness (42%). Covey and colleagues (1994) reported conceptually similar findings that panic psychopathology may be related to poorer success in quitting, although it is not clear whether this effect is more robust than the types of association(s) between psychiatric disorders more generally and quit success. Other cross-sectional field and laboratory work using a community sample has found that daily smokers with a history of panic attacks, but no axis I histories, reported significantly shorter average quit attempt histories, measured in days, compared to smokers without panic (Zvolensky, Lejuez, Kahler, & Brown, 2004). Similar results have been observed in laboratory investigations (Zvolensky, Feldner, Eifert, & Brown, 2001). Although limited by cross-sectional design, and by extension, possible reporting errors (e.g., recall biases), these data provide evidence of a relation between panic psychopathology variables and problems in quitting. A related line of work has focused on anxiety sensitivity and success in quitting smoking. Anxiety sensitivity tends to be elevated among individuals who fear anxiety and arousal-related sensations such as panic disorder (Bernstein & Zvolensky, 2007). In the earliest study in this domain, Brown, Kahler, Zvolensky, Lejuez, and Ramsey (2001) examined a subset of data from a randomized controlled clinical trial comparing standard smoking cessation treatment versus standard smoking cessation plus cognitive-behavioral treatment for depression in smokers with past major depressive disorder. In this investigation, the association between anxiety sensitivity and relapse during the early stages of a quit attempt (e.g., first week), when individuals are most apt to experience symptoms of anxiety (Hughes, Higgins, & Hatsukami, 1990), was examined. Anxiety sensitivity was significantly associated with increased odds of lapsing during the first week after quit day (odds ratio = 2.0). Subsequent work has conceptually replicated and extended the results of Brown and colleagues (2001). For example, Zvolensky, Bonn-Miller, Bernstein, and

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Marshall (2006) found anxiety sensitivity was significantly associated with increased risk of early smoking relapse among a community sample of daily smokers; these effects were evident above and beyond smoking rate and negative affectivity. Such work has recently been extended to low-level smokers from Mexico, adding cross-national empirical support (Zvolensky, Bernstein, et al., in press). Collectively, there is a growing amount of empirical evidence suggesting that panic psychopathology or pre-morbid panic-relevant variables such as elevated anxiety sensitivity is related to early relapse problems, and possibly, lower rates of overall success in quitting. Here again, controlled, prospective studies are an important next research step, as they would remove concerns that observed effects to date are attributable to reporting biases. A closely related line of inquiry has suggested that anxiety sensitivity is related to motivation to quit, barriers to quitting, and reasons for quitting. For example, Zvolensky, Baker and colleagues (2004) found anxiety sensitivity was related to higher levels of current motivation to quit smoking among adult daily smokers (Mage = 20.4], Mcigarettes per day = 10.2); effects were not attributable to other theoretically-relevant factors (e.g., gender, smoking rate; Zvolensky, Baker et al., 2004). These findings may at first seem counterintuitive in that it seems logical that individuals with high levels of anxiety sensitivity would be less likely to express interest or motivation in quitting due to the feared negative consequences related to quitting (e.g., withdrawal symptoms, emotional dyscontrol). Yet, related work suggests that smokers who worry about the negative health-related effects of smoking may engage in more quitting behavior (Dijkstra & Brosschot, 2003). From this perspective, high anxiety sensitivity smokers may be more apt to perceive a personal vulnerability to the negative effects of smoking (e.g., health risks), and as such, express greater motivation to quit (Zvolensky & Bernstein, 2005) despite their greater difficulty in successfully doing so (Brown et al., 2001). In line with this reasoning, Zvolensky, Vujanovic and colleagues (2007) more recently examined the relations between anxiety sensitivity and (1) motivation to quit smoking, (2) barriers to smoking cessation, and (3) reasons for quitting smoking among 329 (160 females; Mage = 26.08 years, SD = 10.92) adult daily smokers. After covarying for theoretically-relevant variables (negative affectivity, gender, axis I psychopathology, non-clinical panic attack history, number of cigarettes smoked per day, and current levels of alcohol consumption), anxiety sensitivity was significantly incrementally related to level of motivation to quit smoking, as well as perceived barriers to quitting smoking. Additionally, after accounting for the variance explained by other theoretically relevant variables, anxiety sensitivity was significantly associated with self control reasons for quitting smoking (intrinsic factors) as well as immediate reinforcement and social influence reasons for quitting (extrinsic factors). These results provide empirical evidence that anxiety sensitivity is uniquely related to level of motivation to quit smoking, perceived barriers to quitting, and certain intrinsic and extrinsic reasons for quitting.

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Panic psychopathology or pre-morbid risk factors also appear to be related to severity of acute nicotine withdrawal. In an early study in this domain, Breslau, Kilbey, and Andreski (1992) found tobacco withdrawal symptoms in a sample of young adults were significantly elevated among smokers with ‘‘any anxiety disorder’’ compared to individuals without a history of such disorders; however, specific anxiety diagnoses were not provided, rendering unclear the specificity of such results to panic psychopathology per se. Zvolensky and colleagues (2004) found that daily smokers with a history of panic attacks reported significantly more intense anxiety-related withdrawal symptoms (anxiety, restlessness, difficulty concentrating, and irritability) compared to smokers without such a history; no differences were evident for the other tobacco withdrawal symptoms (e.g., increased appetite). In another study, Zvolensky, Baker et al. (2004) tested whether anxiety sensitivity predicted the intensity of withdrawal symptoms during the first week of daily smokers’ most recent quit attempt. Results indicated that anxiety sensitivity predicted the intensity of nicotine withdrawal symptoms during the first week of smokers’ most recent quit attempt, and this effect was above and beyond variance accounted for by negative affectivity, panic attack history, gender, cigarettes per day, and age of smoking onset, accounting for 16% of unique variance in withdrawal symptoms. This work is promising in suggesting panic-specific factors are related to an enhanced reactivity to nicotine withdrawal symptoms. Experimental work, which is now underway in our laboratory, is necessary to provide an additional degree of confidence in such conclusions. Another facet of evidence in support of a panic-tobacco relation is apparent from motivational and outcome expectancy research. In regard to smokingrelated motivational processes, there is a large empirical literature documenting that smokers often attribute their smoking, at least in part, to its mood-regulating functions and believe that smoking will reduce negative affect states (Parrott, 1999). Due to their affective vulnerability, smokers with panic-relevant vulnerabilities (i.e., high anxiety sensitivity) may be particularly motivated to smoke to escape from emotional distress elicited by acute nicotine withdrawal or non-withdrawal states (e.g., anticipatory anxiety; Zvolensky & Bernstein, 2005). A number of cross-sectional studies support this theory. Specifically, studies have indicated that anxiety sensitivity is associated with coping-oriented smoking motives among young adults with no history of psychopathology (Novak, Burgess, Clark, Zvolensky, & Brown, 2003; Stewart, Karp, Pihl, & Peterson, 1997; Zvolensky, Bonn-Miller et al., 2006), adolescents (Comeau, Stewart, & Loba, 2001), and individuals with a past history of major depression (Brown, Kahler et al., 2001). Zvolensky, Feldner, Leen-Feldner et al. (2004) report conceptually similar findings for relations between anxiety sensitivity and negative-reinforcement outcome expectancies for smoking. The Comeau et al. (2001) investigation, in particular, is noteworthy in that anxiety sensitivity moderated the relation between trait anxiety (frequency of anxiety symptoms) and use of cigarettes to cope with affective distress, reporting a stronger relationship between anxiety and use of cigarettes to cope with negative emotions

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among high anxiety sensitive compared with low anxiety sensitive youth. Using a sample of panic disorder patients, Zvolensky and colleagues (2005) also found that smokers with panic disorder reported higher levels of smoking to reduce negative affect than their counterparts without such a history. These cross-sectional studies are not capable of elucidating the direction of the effects. Theoretically, coping-oriented smoking motives may have bi-directional effects, influencing, and being influenced by, affective vulnerability. An initial investigation exploring this possibility was consistent with such an account (Gregor, Zvolensky, Bernstein, Marshall, & Yartz, 2007), reporting that coping-oriented motives were incrementally related to a variety of negative affective and cognitive factors. Overall, there are a variety of separate, but related, lines of inquiry indicating panic psychopathology and a select number of pre-morbid risk factors are meaningfully related to smoking behavior. These lines of work differ in their focus, but broadly indicate that panic factors (full blown disorders and certain pre-morbid risk factors) are related to abstinence duration during smoking cessation outcome expectancies related to smoking, perceived barriers and reasons for quitting, nicotine withdrawal symptom severity, and motivational bases for smoking. Thus, it is most appropriate to conceptualize many of the studied variables (e.g., anxiety sensitivity) as variable risk factors. Although definitive prospective work has not been conducted to firmly establish temporal precedence in many, if not most, of the investigations, theoretically, panic variables would precede the smoking factors. It also is theoretically possible that panic and panic-relevant risk factors may not necessarily developmentally precede smoking, but nevertheless meaningfully influence the course and nature of smoking behavior over time via many of the processes described throughout this chapter. Further prospective work will delineate the possibility that these panic-smoking relations may be transactional over development. Future directions. As in the earlier sections of this chapter, a first observation and recommendation for future research is to better understand the relations between panic psychopathology and smokeless tobacco use. There is no empirical work completed in this domain to the best of our knowledge, leaving this facet of the tobacco-panic linkage undocumented. Second, essentially all of the existing work on panic psychopathology (and related factors) and smoking behavior is focused on main effects. This approach seems appropriate given the currently limited knowledge in the area, but represents only a ‘‘first step’’ in a larger scientific effort. Future work is needed to increase understanding about linkages among these factors beyond main effects by including moderational and mediational tests of theoretically relevant variables. Similarly, the possibility that shared or common risk factors may underlie panic problems, panic-relevant risk factors, and these smoking-related problems and processes has received little theoretical or empirical evaluation. Third, the generalizability of panic psychopathology and smoking research is limited in that it has focused largely on adults from the U.S. Furthermore, there is very little information on the nature of these relations among youth. Given the early age of onset of these

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behaviors and their health relevance, as well as the international scope of this public health problem, research development in these domains is needed. Finally, little research has directly targeted panic vulnerability factors in smoking cessation interventions. Similarly, there is little work addressing smoking in the context of panic-related treatments. Given the consistent empirical evidence of bi-directional associations between these often comorbid behavioral problems, it is important to develop specialized treatments, as generic interventions may not target the affective vulnerability processes functioning to maintain smoking in this population. For example, it may be useful to integrate interoceptive exposure, cognitive restructuring, and psychoeducation exercises developed for panic prevention and treatment programs with standard smoking cessation strategies and nicotine replacement therapy. These therapeutic tactics may be most effective when they target theoretically-relevant panic risk factors like anxiety sensitivity in order to facilitate cessation. As a second illustration, it may be useful to target smoking cessation as part of evidence-based panicproblem treatment strategies. While there have been some inroads made in this domain, with successful case reports and pilot studies now being reported (Zvolensky, Bernstein et al., in press; Zvolensky, Lejuez, Kahler, & Brown, 2003; Zvolensky, Schmidt et al., 2006), much work is yet to be addressed in this domain.

Summary The present chapter provides an updated review of extant empirical work pertaining to the inter-relations between tobacco use and panic psychopathology. Although a relatively nascent area of research, a recent spate of empirical evidence indicates that theoretically and clinically important associations exist between tobacco use and panic psychopathology. Although promising, there are a multitude of critical gaps in the research literature that need to be addressed in future studies. We hope that such ongoing research may help translate knowledge about basic processes to the development and dissemination of powerful clinical intervention strategies for tobacco users with panic-related vulnerabilities or psychopathology.

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Alcohol Use and Anxiety Disorders Brigitte C. Sabourin and Sherry H. Stewart

The relationship between anxiety and alcohol use is a topic of great theoretical and practical interest for both scientists interested in the nature and causes of psychopathology and practitioners working with anxious and/or alcohol abusing clients. Although it has been clearly established that anxiety disorders and alcohol use disorders are highly ‘‘comorbid’’ or co-occurring conditions (e.g., see Kushner, Abrams & Borchardt, 2000a for a review), the relationship between the symptoms or behaviors involved in each disorder (e.g., feelings of anxiety and levels of alcohol use) has not been as extensively reviewed. This chapter will review recent empirical evidence linking anxiety and alcohol at both the behavioral and disorder level to determine if similar conclusions can be derived regarding their relationship from data at both of these levels of enquiry. We will first briefly describe epidemiological studies linking anxiety disorders and alcohol use disorders. Then we will examine some of the etiological theories of the relationship between anxiety and alcohol use and their disorders, with a review of the empirical evidence supporting each theory. Next, some specific factors moderating and mediating the relationship between anxiety and alcohol use will be explored, with an emphasis on individual differences and specific processes involved in the relationship. A brief discussion of the differences between factors affecting onset, maintenance, and relapse in the anxiety and alcohol relationship will follow. The latest empirical evidence and thoughts about treating both alcohol use and anxiety related problems will also be reviewed. Finally, we conclude the chapter with some remarks about where the field stands and directions that future research in this area might profitably take.

Brigitte C. Sabourin Department of Psychology, Life Sciences Center, Dalhousie University, Halifax, Nova Scotia, Canada, B3H 4J1, Tel: +902 494 3793, Fax: +902 494 6585 [email protected]

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Symptomatic and Syndromal Levels of Enquiry in the Anxiety – Alcohol Relationship Anxiety and alcohol use can both be characterized at two different levels: symptomatic and syndromal. An association at the former level would entail a clear relationship, for example, between feelings of anxiety and drinking behavior. That is, one would expect that higher levels of anxiety would be related to higher quantities and/or frequency of drinking behavior. In a classic paper, Persons (1986) describes the advantages of studying psychological phenomena at the symptomatic level rather than at the diagnostic category (or syndromal) level. The symptom approach allows for study of important phenomena that may be ignored by examining only the diagnostic category in question. For example, level of alcohol consumption is not considered in the diagnosis of alcohol abuse or dependence according to the fourth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV; American Psychiatric Association [APA], 1994), although there have been some recommendations for incorporating heavy drinking behaviors in the diagnostic definitions in future editions (Helzer, Bucholz, & Bierut, 2006). Nonetheless, level of consumption may be an important risk factor for alcohol problems (Dawson & Archer, 1993) and thus may be of interest as a ‘‘symptom’’ when considering the anxiety – alcohol relation from the symptom perspective. Also, the symptom approach recognizes the continuity of clinical phenomena and behaviors with normal phenomena and behaviors. This is a crucial point in the study of both drinking behavior and anxiety. For example, some argue that drinking problems are best viewed as lying on a continuum ranging from normal, non-problematic social drinking on one end to severe and pathological alcohol dependence on the other extreme (Sobell et al., 1996). In addition to the arguments presented above in favor of focusing on symptoms rather than diagnostic categories, Chilcoat and Breslau’s (1998) discussion of criteria for establishing causation between anxiety and alcohol abuse also demands a symptom-focused approach rather than a syndromal- focused approach. According to Chilcoat and Breslau, one of the criteria for causation includes a ‘‘gradient of effect’’, or dose response relationship between the two phenomena of interest. That is, as the level of exposure to the causal agent increases, a resulting increase in the level of the causal outcome should be expected. The gradient of effect relationship can be studied as it pertains to the relation of any anxiety-related symptom (e.g., number of panic attacks; severity of cognitive re-experiencing) with any alcohol-related symptom (e.g., severity of negative consequences resulting from alcohol use; usual number of alcohol beverages consumed per week). The relationship between anxiety and alcohol can also be considered at the syndromal level. At this level, a relationship between alcohol and anxiety would be demonstrated if a diagnosis of one of the two disorders (i.e., anxiety disorder or alcohol use disorder) was associated with an increased likelihood of a diagnosis of the other disorder. The DSM IV (APA, 1994) distinguishes between two distinct types of alcohol use disorders: alcohol abuse and alcohol dependence.

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Alcohol abuse is characterized by ‘‘recurrent and significant adverse consequences related to the repeated use of alcohol’’ (p. 198), whereas alcohol dependence must include ‘‘evidence of tolerance, withdrawal, or compulsive behavior related to alcohol use’’ (p.214). Alcohol dependence is considered more severe than alcohol abuse and always overrides the latter diagnosis. As was mentioned earlier, consumption levels are not considered in the diagnosis of either alcohol abuse or dependence. On the other hand, for anxiety disorders, both symptom levels (e.g., repeated panic attacks in the case of panic disorder) and/or negative consequences of the symptoms (e.g., distress about having another panic attack in the case of panic disorder) are considered in making a diagnosis.

Epidemiological Findings on the Anxiety – Alcohol Relationship The relationship between anxiety and alcohol can be described using the concept of comorbidity, which can be defined as diagnosable, problematic alcohol use and anxiety symptoms that are both present at some point in a person’s lifetime, but not necessarily at the same time (Kushner et al., 2000a). Comorbidity rates can be estimated using either clinical or community samples. Because individuals with more than one disorder are more likely to seek treatment, clinical samples may in fact inflate comorbidity estimates (Berkson, 1949). It is believed that community surveys provide more accurate reflections of the anxiety disorder – alcohol use disorder relationship. We will review the two most recent large-scale community surveys, which are representative of the results of these types of surveys. In this chapter, we will present odds ratios (ORs) to quantify the comorbid relationship between anxiety disorders and alcohol use disorders. An OR reflects the odds that individuals will display a second disorder if a first disorder is present versus if it is not present. An OR of 1.0 reflects a lack of relationship, with higher ORs reflecting more significant relationships between two disorders. ORs of less than 1.0 reflect a decreased probability of having the second disorder given the presence of the first disorder. The National Comorbidity Survey (NCS: e.g., Kessler et al., 1996) reported 12-month ORs for individuals with alcohol dependence and alcohol abuse of also having suffered from panic disorder (1.7 and 0.5 respectively), social phobia (2.8 and 2.3), generalized anxiety disorder (4.6 and 0.4), posttraumatic stress disorder (2.2 and 1.5), and specific phobias (2.2 and 1.2). The 12-month ORs associated with alcohol dependence are significant for all anxiety disorders with the exception of panic disorder (although the lifetime OR of alcohol dependence is significant for panic disorder). On the other hand, although having any anxiety disorder leads to a significant OR of developing alcohol abuse, the only specific anxiety disorder with a significant OR is social phobia. More recently, the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC; e.g., Grant et al., 2004) reported 12-month ORs for individuals with alcohol dependence and abuse to also display any anxiety

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disorder (2.6 and 1.1, respectively), panic disorder with agoraphobia (3.6 and 1.4) and without agoraphobia (3.4 and 0.8), social phobia (2.5 and 0.9), a specific phobia (2.2 and 1.1), and generalized anxiety disorder (3.1 and 0.9).1 The NCS (Kessler et al., 1997) also examined sex differences in comorbidity between alcohol use disorders and anxiety disorders. Anxiety disordered women and men do not differ significantly in their risk of developing alcohol dependence; however, women with social phobia, simple phobias or post traumatic stress disorder hive higher ORs of abusing alcohol than men with these anxiety disorders. Similarly, the NESARC (Smith et al., 2006) reported ORs of alcohol use disorders and anxiety disorders by race/ethnicity. Across all races/ethnic groups, there were significant ORs of any anxiety disorder with alcohol dependence but not with alcohol abuse. However, the pattern of comorbidity across specific anxiety disorders reveals significant racial/ethnic effects. For Whites and Blacks, the ORs for alcohol dependence and anxiety disorders were significant across almost all anxiety disorders. The only exception was that the OR for panic disorder with agoraphobia was significant for alcohol abuse but not for alcohol dependence among Blacks. On the other hand, for Native Americans and Hispanics, only a few of the anxiety disorders were significantly associated with alcohol dependence and none with alcohol abuse. Two general conclusions can be made from the data reported across these large-scale community surveys. First, the relationship between anxiety disorders and alcohol dependence appears to be much stronger than between anxiety disorders and alcohol abuse, with the ORs for dependence much more likely to be significant than those for abuse. In other words, having a comorbid anxiety disorder increases the chances of displaying the more severe type of alcohol use disorder (dependence) moreso than the less severe type (abuse), suggesting a gradient of effect relationship. . Second, the relationship between alcohol use disorders and anxiety disorders differs between sexes and racial/ethnic groups. Although alcohol use is generally more common among men than women (Paavola, Vartiainen, & Haukkala, 2004), alcohol abuse and anxiety disorders are more closely related for women than for men. Furthermore, it appears that for Whites and Blacks, anxiety and alcohol dependence are more closely associated than for Native Americans and Hispanics. The following sections cover etiological models of the relationship between alcohol and anxiety, their maintenance, and their relapse, in an attempt to explicate the high level of comorbidity between anxiety disorders and alcohol use disorders observed in the epidemiologic surveys.

Etiological Models of the Relationship In order to gain a better understanding of the relationship between anxiety and alcohol use, it is important to explore the mechanisms that may affect the etiology of the co-occurrence of symptoms of both of their disorders. There 1

The NESARC did not specify significance of reported 12-month ORs.

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are three main hypotheses that have been put forward, with some evidence supporting each hypothesis. First, there is some evidence that the associations between anxiety and alcohol arise from common underlying variables, such as common genetic or environmental factors, that cause both anxiety symptoms and problematic alcohol use. Second, some believe that certain aspects of problematic alcohol use, such as repeated experiences with alcohol withdrawal, cause anxiety symptoms and ultimately an anxiety disorder. Finally, others argue that anxiety symptoms cause alcohol misuse, culminating in an alcohol use disorder. Evidence examining these three hypotheses is presented below.

Common Underlying Variables There is some evidence, provided by two main lines of research, to support the hypothesis that certain common, underlying factors are causing both anxiety symptoms and problematic alcohol use (Kushner et al., 2000a). First, family and twin studies have provided some evidence of possible common genetic contributions to the correlation between anxiety symptoms and alcohol consumption (e.g., Tambs, Harris, & Magnus, 1997). Family and twin studies have also examined the heritability of common underlying personality traits associated with both anxiety and alcohol use disorders. For example, several crosssectional and longitudinal studies have linked the highly heritable personality trait of neuroticism (Jang, Livesley, & Vernon, 1996) with anxiety and its disorders (e.g., Jorm et al., 2000; Weinstock & Whisman, 2006). Neuroticism has also been linked to alcohol use disorders (Cox, 1987). Another personality dimension that is closely related to neuroticism, negative emotionality, has been associated with alcohol use disorders (Swendsen, Conway, Rounsaville, & Merikangas, 2002). In a study by Swendsen et al. (2002) examining heritability of negative emotionality, non-alcoholic individuals with alcoholic relatives did not differ significantly on scores of negative emotionality than those without alcoholic relatives. If negative emotionality were a heritable risk factor, nonalcoholic individuals with alcoholic relatives would score higher on this trait than those without alcoholic relatives. These findings suggest that negative emotionality may indeed be an individual risk factor rather than a heritable risk factor for alcohol use disorders. The inconsistent results between these two related personality traits (i.e. both associated with negative emotional states) demonstrates that common heritability for some of the personality traits relevant to the anxiety – alcohol relationship is still in need of further investigation. Conversely, another personality risk factor for both anxiety disorders and alcohol use disorders, anxiety sensitivity (i.e. fear of anxiety; Stewart & Kushner, 2001), does have a strong heritable component that accounts for nearly half of the variance in scores on anxiety sensitivity measures (Stein, Lang, & Livesley, 1999). Therefore, it appears that some, but not necessarily all, underlying personality risk factors associated with both alcohol use disorders and anxiety disorders have a shared heritable component.

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Second, results from some prospective studies suggest a possible common ‘‘third variable’’ contribution to the alcohol – anxiety relationship. For example, Zimmerman et al. (2003) found that remitted panic disorder and social phobia were as important as current panic/social phobia diagnoses in predicting future alcohol outcomes. That is, even individuals who were not currently experiencing sufficient symptoms to receive any anxiety disorder diagnosis were at higher risk of developing alcohol problems if they had ever been diagnosed with either panic or social phobia in the past. These findings can be interpreted to suggest that a third underlying factor (such as a common personality vulnerability or genetic predisposition) was driving both the alcohol problem and the past or current anxiety disorder. A 21-year longitudinal study (Goodwin, Fergusson, & Horwood, 2004) found that once other factors were controlled (i.e., prior substance dependence, concurrent major depression, and affiliations with deviant peers), the ability of anxiety disorders to predict the development of alcohol dependence was no longer significant. The study points to a number of possible third variables including prior substance dependence which could contribute both to the development of anxiety disorder (see Norton, Norton, Cox, & Belik, in press) and of alcohol dependence (e.g., alcohol is consumed in larger quantities when combined with other substances; Barrett, Darredeau, & Pihl, 2006). Unfortunately the study did not test which of these factors was most important in explaining the link between anxiety and alcohol dependence. Some factors that have emerged as possible contributors to the increased vulnerability of developing comorbid anxiety and alcohol use problems include either common genetic pre-dispositions (e.g., anxiety sensitivity), biological environment risk factors (e.g., fetal alcohol syndrome), or non-biological environmental risk factors (e.g., disruptive familial environment; Merikangas, Stevens, & Fenton, 1996). Unfortunately, no research has yet confirmed one or more of these candidate factors. More research needs to be conducted exploring these additional underlying mechanisms before one can make conclusions about their influence.

Alcohol Use Causes Anxiety The second hypothesis dealing with the relationship between anxiety and alcohol use posits that prolonged drinking is actually a causal factor in anxiety symptoms and disorders. This alcohol-induced anxiety can occur through either psychosocial or physiological mechanisms. Psychosocially, it is hypothesized that alcohol may interfere with normal adaptation to stressful stimuli or that negative consequences produced by problematic drinking (e.g., loss of job or relational problems) can lead to anxiety symptoms and increased vulnerability of developing anxiety disorders (Kushner et al., 2000a). Physiologically, alcohol withdrawal can often produce anxiety symptoms such as shakiness (see Kushner et al., 2000a) or increased startle, a common symptom of PTSD (Stewart et al., 1998). In addition, neural adaptation occurs

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with frequent and excessive alcohol use over time such that repeated alcohol withdrawals actually sensitize this withdrawal-induced anxiety (Breese, Overstreet, & Knapp, 2005). This has often been referred to as the ‘‘kindling-stress hypothesis’’; that is, repeated withdrawals from chronic heavy drinking are thought to worsen, or ‘‘kindle’’ withdrawal-induced anxiety. A number of studies have also demonstrated increased norepinephrine activity as well as hyperexcitability of the central nervous system, especially of limbic structures, during alcohol withdrawal (Kushner et al., 2000a; Marshall, 1997). These are the same neural systems that have been implicated in panic attacks and panic disorder, providing a possible physiological explanation for the link between panic disorder and alcohol use disorders (Marshall, 1997). A final area of research supporting the hypothesis that alcohol problems cause anxiety involves prospective studies. One such study by Kushner, Sher, and Erickson (1999), for example, found that a diagnosis of alcohol dependence at baseline quadrupled the risk of developing an anxiety disorder three to six years later. Prospective studies have also examined the relationship between PTSD and alcohol abuse to ascertain whether heavy alcohol use can be a risk factor for developing PTSD. It has been hypothesized that physiological and neurochemical changes due to prolonged heavy alcohol use and/or past reliance on alcohol to deal with life stressors at the expense of developing other coping mechanisms may increase an individual’s susceptibility of developing PTSD after a traumatic experience (Brown & Wolfe, 1994; Stewart et al., 1998). A prospective study by Acierno, Resnick, Kilpatrick, Saunders, and Best (1999) found that a history of alcohol abuse increased the risk of developing PTSD in rape victims almost three-fold (OR = 2.65) when compared to the absence of this factor.

Anxiety Causes Alcohol Use It has been hypothesized that anxiety symptoms and anxiety disorders promote alcohol use, as individuals drink to self-medicate their anxiety. The ‘‘self-medication hypothesis’’ (and the related tension reduction hypothesis) as applied to the understanding of the relationship between anxiety and alcohol posits that the pharmacological and/or psychological effects of alcohol lead to decreases in aversive anxiety symptoms, thereby motivating anxious individuals to increase their quantity and/or frequency of alcohol use via the process of negative reinforcement (Kushner et al., 2000a). Although the self-medication and tension reduction hypotheses clearly do not account for all drinking behavior (Greeley & Oei, 1999), there has been a good deal of empirical evidence to support these hypotheses as they apply to the understanding of comorbid anxiety and alcohol use disorders (Kushner et al., 2000a). Anxiety disordered individuals do in fact self-report using alcohol to manage their anxiety (Kushner, Abrams, Thuras, & Hanson, 2000b; Thomas, Randall,

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& Carrigan, 2003; see also Kushner, et al., 2000a for a review). In addition, Thomas and colleagues (2003) found that socially anxious individuals not only reported that they drank to feel more comfortable in social situations, but that they would actually avoid social situations if alcohol were unavailable. As introduced earlier in this chapter, one possible criterion for establishing causation (Chilcoat & Breslau, 1998) is a dose response, or gradient of effect relationship: if anxiety causes alcohol use, one would expect that higher levels of anxiety would be associated with higher levels of alcohol use. Studies have found positive correlations between severity of PTSD arousal symptoms and severity of alcohol use disorder symptoms (McFall, Mackay, & Donovan, 1992; Stewart et al., 1998). Because correlation does not determine causation, one must rely on laboratory-based studies, such as a study by Abrams, Kushner, Medina, and Voight (2002), for evidence that induction of anxiety symptoms causes heavier drinking. The study found that participants with social phobia consumed more alcohol following an anxiety provoking activity (speaking in front of a group) than a control activity (reading a book), presumably in an effort to dampen the anxious feelings caused by the anxiety provoking activity. Prospective research on non-clinical populations also supports a doseresponse relationship between anxiety and alcohol use. In a diary-based study by Swendsen and colleagues (2000), moderate drinkers documented their daily drinking and mood states for a one-month period. The study revealed that only anxious feelings and not sadness or other negative affective states preceded and predicted increased alcohol consumption. As can be observed above, findings from correlational, laboratory-based experimental, and diary-based prospective research conducted with both clinical and non-clinical populations converge to provide some evidence for a relationship between anxiety symptoms and alcohol use where anxiety precedes and contributes to increased alcohol use. Social anxiety appears to have a more complicated relationship with alcohol use than do other types of anxiety, however. Specifically, some studies examining the relationship between social anxiety and alcohol consumption show a positive relationship, whereas other studies show either no linear relationship or even a negative relationship (Ham & Hope, 2005; Stewart, Morris, Mellings, & Komar, 2006; Tran, Haaga, & Chambless, 1997). The negative relationship between social anxiety and alcohol consumption may exist because socially anxious individuals actually avoid the types of social situations that involve drinking because of their social anxiety, thus leading to lower levels of alcohol consumption (Stewart et al., 2006). Nonetheless, social anxiety has been found to predict alcohol dependence, as well as problems caused by alcohol (Gilles, Turk, & Fresco, 2006; Stewart et al., 2006). Thus, social anxiety does appear related to alcohol-related consequences, even if it does not always predict increased alcohol use. Another criterion discussed by Chilcoat and Breslau (1998) as necessary for causation is temporality. If anxiety causes increased or problematic alcohol use, then anxiety symptoms should predate alcohol-related problems, and anxiety

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disorder diagnoses should precede alcohol disorder diagnoses. In the cases of social phobia, panic disorder, and PTSD diagnoses, the anxiety disorder usually preceded the onset of the alcohol use disorder in comorbid individuals (Cox, Norton, Swinson, & Endler, 1990; Kushner, Sher, & Beitman, 1990; Stewart & Conrod, 2002).Furthermore, a cross-national investigation by Merikangas et al. (1998) confirmed that anxiety disorders preceded alcohol use disorders for the majority of participants. Assessing temporality or relative order of onset of symptoms of alcohol use disorders and anxiety disorders among comorbid cases can also help elucidate the anxiety – alcohol causal relationship. For example, a recent study by Bernstein, Zvolensky, Sachs-Ericsson, Schmidt, and Bonn-Miller (2006) found that the symptom of panic attacks predated the onset of heavy drinking behaviors for the vast majority of participants with both panic attacks and heavy drinking in a community sample. Although many anxiety disorders and their symptoms predate alcohol use disorders and heavy drinking, this relationship is normally inverse for individuals with generalized anxiety disorder (GAD). For the majority of individuals with GAD, alcohol use disorder predated the GAD (Kushner et al., 1990), suggesting that, for those cases, anxiety could not have been the cause of the alcohol use disorder. Thus, as can be seen from the findings above, for most comorbid individuals (excluding a majority of GAD individuals), the order of onset supports the possibility that anxiety may play a causal role in the development of alcohol use disorders. And conversely, for those with GAD, the alcohol use may play a causal role in the development of the anxiety disorder. However, Chilcoat and Breslau (1998) clarify that the temporality criterion is necessary but not sufficient for determining a causal association between disorders. Finally, the prospective study by Kushner and colleagues (1999) mentioned earlier in the chapter that found an increased risk of future anxiety disorders for individuals with alcohol dependence also found the converse. That is, having a diagnosis of anxiety at baseline increased the risk three- to five-fold for a new onset of alcohol dependence three to six years later (see also Goodwin et al., 2004). The study demonstrates that the causal relationship between anxiety and alcohol is potentially bi-directional in nature. Overall, the evidence presented above does seem to support the fact that, at least in some instances, anxiety symptoms and anxiety disorders do precede and possibly promote problematic alcohol use.

Moderating and Mediating Variables in the Anxiety – Alcohol Relationship More recent work has focused on finding specific variables that either moderate or mediate the causal relationship between anxiety and alcohol use. A moderator variable is a qualitative (e.g., sex) or quantitative (e.g., anxiety level) variable that affects the direction and/or strength of the relation between two

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other variables (Baron & Kenny, 1986). A mediator variable, on the other hand, explains how or why the relationship between a predictor and given criterion (e.g., between anxiety and alcohol use) exists. That is, the mediator actually accounts for the relationship between the two variables (Baron & Kenny). Alcohol expectancies. A potential moderator variable between anxiety and problematic alcohol use includes certain ‘‘alcohol outcome expectancies’’ (i.e., beliefs about the consequences of drinking alcohol). For anxious individuals who self-medicate to avoid anxiety, an important aspect of the self-medication hypothesis involves the notion that self-medicators anticipate anxiety, and that they expect that alcohol will actually decrease their feelings of anxiety (e.g., Kushner, Sher, Wood, & Wood, 1994; Tran et al., 1997). Studies have shown that tension reduction expectancies predict drinking frequency and quantity in non-alcoholic drinkers with panic disorder (Kushner et al., 2000b) and comorbid problem drinking in women with PTSD (Ullman, Filipas, & Townswend, 2005). These results support the role of tension reduction alcohol expectancies as a moderator: increased or problematic drinking occurs among anxiety disorder patients only when tension reduction alcohol expectancies are present. Another methodology that has been employed to investigate the role of alcohol outcome expectancies in the anxiety – alcohol relationship is the experimental manipulation of expectancies via the placebo-controlled design. If expecting alcohol were to induce a cognitive or placebo-induced anxiety reducing effect among anxious individuals, such an effect would provide additional evidence for the contribution of alcohol expectancies in explaining the anxiety – alcohol relationship. The empirical evidence provided thus far has found mixed results for this placebo anxiolytic effect. Some studies have found that the belief that one was consuming alcohol, even when one was actually consuming a placebo, was enough to lower feelings of anxiety among anxiety-disordered patients (Abrams, Kushner, Lisdahl, Medina, & Voight, 2001; Lehman, Brown, Palfai, & Barlow 2002). On the other hand, research by MacDonald, Stewart, Hutson, Rhyno, and Loughlin (2001) conducted with participants high in anxiety sensitivity did not support a cognitively-mediated tension reduction effect of alcohol. The researchers actually found a ‘‘reverse placebo’’ effect, where high AS participants in a placebo condition, who had expectations of alcohol-induced tension reduction, but did not benefit from alcohol’s physiological tension-reduction properties, appeared to have even higher levels of anxiety than participants in a control condition where they neither received nor expected alcohol. Regardless of the direction of the placebo effect, all of these findings do suggest a role for cognitive expectancy variables in accounting for the effects of alcohol among anxious individuals. A number of studies have examined specific aspects of alcohol expectancies in individuals with social anxiety. For people high in social anxiety, expecting that alcohol would decrease social anxiety or increase social assertiveness was associated with both higher self-reported drinking quantities (Tran et al., 1997) and higher alcohol consumption in a laboratory setting (Kidorf & Lang, 1999). More general tension reduction expectancies, on the other hand, had no effect

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on alcohol consumption. In addition, socially related alcohol expectancies have been associated with higher levels of alcohol dependence in socially anxious individuals (Ham, Carrigan, Moak, & Randall, 2005). These studies demonstrate that different expectancies affect alcohol consumption depending on the particular type of anxiety-related psychopathology involved. For individuals with panic disorder or PTSD, the research until now appears to indicate that general tension reduction expectancies provide sufficient motivation for increasing alcohol consumption. However, for individuals with social anxiety, it appears that specific social-related alcohol expectancies, but not general tension reduction expectancies, tend to motivate these individuals to drink, resulting in greater risk of developing alcohol dependence. As has been done with social anxiety, increasingly directed research in other types of anxiety-related psychopathology is needed to determine more precisely the kinds of expectancies that help explain each group’s increased risk for alcohol problems in order to target these more specifically in treatment. Self-efficacy. Self-efficacy has been defined by Bandura (1977) as the conviction that one can successfully execute a behavior required to produce a certain outcome. Research conducted with socially anxious individuals suggests that self-efficacy may act as a link between alcohol expectancies, social anxiety and heavy drinking behaviors. Positive socially related alcohol expectancies and low self-efficacy to avoid heavy drinking interact with one another in increasing problematic drinking among socially anxious individuals (Burke & Stephens, 1997; Gilles, Turk, & Fresco, 2006). Thus, increasing individuals’ self-efficacy in refusing alcohol or avoiding heavy drinking could be incorporated when developing treatment programs for comorbid individuals, at least in the case of social phobia comorbidity. More research is needed to determine the relevance of the self-efficacy construct to the comorbidity of alcohol use disorders with anxiety disorders other than social phobia. Drinking motives. Problematic drinking can arise because of maladaptive drinking motives (reasons for drinking) even in the absence of particularly elevated levels of alcohol consumption (Stewart et al., 2006). For some individuals who experience fear or anxiety, avoidance behaviors, such as drinking to self-medicate, become negative reinforcement strategies used to attenuate or cope with anxious states. Because such avoidance strategies are negatively reinforcing through their effects in alleviating anxiety, the drinking behavior continues over time and the individual comes to rely on drinking as a primary coping strategy. For example, in many cases, social anxiety is not associated with higher drinking levels (Tran et al., 1997), but it is with problematic reasons for drinking, such as drinking to cope with negative emotional states, as well as with greater risks of developing alcohol problems (Thomas, Randall, & Carrigan, 2003; Stewart et al., 2006). A further problem with coping-related drinking is that, as an avoidance behavior, it may serve to maintain anxiety by preventing habituation of the anxiety response. Research by Cooper (1994; see also Cooper, Russell, Skinner, & Windle, 1992) exploring drinking motives and their relation to problematic drinking

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uncovered four factors explaining motivation for drinking. Two of these motives involve positive reinforcement from drinking: social (i.e. to obtain social rewards) and enhancement (i.e. to enhance positive mood or well being), whereas the other two motives involve negative reinforcement from drinking: coping (i.e. to cope with negative emotions), and conformity (i.e. to avoid negative social consequences such as social rejection). Only the negative reinforcement motives of coping and conformity predict alcohol problems after controlling for quantity and frequency of alcohol use. A study by Stewart and colleagues (2006) also found that for undergraduate students, problem-drinking symptoms were positively associated with the negative reinforcement motives of coping and conformity drinking. The study also found that coping and conformity drinking motives mediated the relationship between social anxiety (specifically, fear of negative evaluation) and drinking problems. That is, individuals with social anxiety experienced drinking problems because they drank either to cope with negative emotions (i.e. coping drinking motives), or to avoid negative social consequences (i.e. conformity drinking motives). In addition, the study found either no association or even a negative direction association between social anxiety measures and drinking quantity and frequency. Together, research by Cooper and her colleagues and Stewart and her colleagues support the notion that drinking to cope with anxiety or to conform with peer pressure confers additional risk for problem drinking over and above the risks associated with level of alcohol consumption. Additional support for coping and conformity drinking motives as important factors in the anxiety – alcohol relationship has been provided by studies conducted with non-clinically anxious participants. For example, Deacon and Valentiner (2000) found a significant association between scores on the Beck Anxiety Inventory (BAI, a widely-used measure of anxiety symptoms) and coping motivated drinking but not social or enhancement motivated drinking. In addition, Thomas et al. (2003) found that socially anxious individuals more often reported drinking before and during social situations in an effort to feel more comfortable (i.e. to cope with their social anxiety) than non-socially anxious individuals. Anxiety sensitivity has been associated with greater drinking levels and argued to be a potential risk factor for alcohol use disorders (Stewart & Kushner, 2001), as we describe in greater detail in the next section. Results from a study by Stewart et al. (2001) supported coping and conformity motives as mediators in the relationship between AS and higher drinking levels. That is, high AS individuals’ greater drinking behavior was at least partially explained by high coping and conformity motive scores. Anxiety sensitivity. Anxiety sensitivity (AS) is an important individual difference that may mediate the anxiety – alcohol relationship. It is possible that anxiety disordered patients are at increased risk of alcohol problems because of their higher levels of AS (i.e., higher levels of fear of anxiety), which, in turn, promote greater motivation and behaviors (e.g., alcohol use) to escape or avoid the feared symptoms (Stewart & Kushner, 2001). Thus, consistent with the

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self-medication hypothesis, it is possible that individuals high in AS use alcohol for its anxiolytic or arousal dampening effects. In fact, high AS individuals have been found to prefer alcohol and other ‘‘depressants’’ over ‘‘stimulant’’ type drugs (DeHaas, Calamari, & Bair, 2002; Norton, Rockman, & Ediger, 1997). Additionally, elevated levels of AS have been associated with increased drinking behavior, including increased typical weekly drinking frequency, and yearly excessive drinking frequency (Stewart, Peterson, & Pihl, 1995; Cox & Klinger, 1988; Stewart, Zvolensky, & Eifert, 2001). Moreover, Stewart, Conrod, Samoluk, Pihl, and Dongier (2000) found evidence for the mediating role of AS in explaining the association between PTSD symptoms and negative reinforcement drinking. Stewart et al. (2001) also examined the relationship between lower-order components of AS and drinking behavior. AS consists of three lower-order factors: AS physical concerns (e.g., worrying that a rapidly beating heart is a sign of having a heart attack), AS psychological concerns (e.g., worrying that not being able to keep one’s mind on a task is a sign of going crazy), and AS social concerns (e.g., worrying about appearing nervous in front of others; see Zinbarg, Mohlman, & Hong, 1999). After controlling for the other two factors, AS social concerns emerged as the only significant predictor for weekly drinking frequency and yearly excessive drinking frequency. Thus, it is possible that AS also plays an important role in the relationship between social anxiety and drinking problems given the elevation of AS social concerns among those with social phobia (Zinbarg et al., 1999). Summary. Although these mediating and moderating variables are typically studied in isolation, as can be seen above, alcohol expectancies, self-efficacy, drinking motives, and anxiety sensitivity may interact with each other or intervene with one another in explaining problematic alcohol use in anxious individuals. For example, people with certain anxiety disorders may be more likely to drink to cope with their anxiety sensations (coping motives) because of their fear of these sensations (anxiety sensitivity), thereby increasing their risk for drinking problems. Additional research exploring the interplay between the different variables affecting the anxiety-alcohol relationship would provide important steps toward creating more effective treatments for comorbid individuals.

Anxiety, Alcohol Use, and Other Health Behaviors Alcohol consumption has been shown to be highly related to risky health behaviors, such as smoking and illicit drug use (Paavola, Vartiainen, & Haukkala, 2004; Tolstrup et al., 2005). In a longitudinal study (Paavola et al., 2004), earlier alcohol use was associated with later smoking, and smoking in adolescence predicted alcohol use in adulthood. Despite this close association between alcohol use and smoking, combining the two behaviors does not

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increase the rate of anxiety disorders above the rate associated with alcohol use only (Kandel, Huang, & Davies, 2001). A diagnosis of an anxiety disorder combined with a drug use disorder constitutes a significant risk factor for developing alcohol dependence (lifetime OR =5.81; Kessler et al., 1997). This increased risk appears to be even higher than the risk associated with being diagnosed with an anxiety disorder alone (i.e. without a drug use disorder; lifetime OR = 1.85). Unfortunately, like many epidemiological surveys, the National Comorbidity Survey does not break drug use disorders down by drug type/class, which could further elucidate the drug – anxiety – alcohol relationship. One possible explanation for this elevated risk for alcohol dependence among those with comorbid anxiety – drug use disorders is that problematic drug use, through the drugs’ potentially anxiogenic effects, exacerbates the need to self-medicate with alcohol, resulting in increased risk for alcohol dependence relative to those with non-comorbid anxiety disorders.

Maintenance of Comorbid Anxiety and Alcohol Problems Empirical findings supporting all three causal hypotheses suggest the possibility of multiple causal pathways involved in the etiology of comorbid alcohol use disorders and anxiety disorders. The specific causal pathway involved may vary across people or across anxiety sub-types. Regardless of the etiology of the comorbid anxiety symptoms and problematic alcohol use, there have been countless studies confirming that, once comorbid, anxiety and alcohol use do, in fact, exert important influences on each other (see Kushner et al., 2000a). Furthermore, processes involved in the initiation of the comorbidity may differ from those involved in the maintenance of problematic alcohol use and anxiety. A feed-forward model has been proposed (Kushner et al., 2000a) in which once both alcohol use and anxiety are present, each promotes the maintenance or exacerbation of the other. For example, anxious individuals may resort to alcohol to decrease feelings of anxiety, which might be an effective strategy in the short term, providing reinforcement for this pattern. However, alcohol, and especially withdrawal from alcohol, increases anxiety-like symptoms in the longer run via physiological mechanisms such as kindling. Alcohol may also worsen anxiety levels because of the negative familial, social or occupational consequences of heavy drinking. Individuals will then increase their drinking behavior in an attempt to alleviate these worsening feelings of anxiety because drinking has become a learned strategy for dealing with these symptoms, especially if there is a failure to recognize that the alcohol may actually be promoting the anxiety in the medium to long term. Finally, in individuals with PTSD, alcohol that is used to cope with anxiety may prevent normal ‘‘habituation’’ of the anxiety symptoms following trauma exposure. On the other hand, for individuals who are not drinking, anxious

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feelings caused by PTSD may naturally remit with time. Thus, when individuals drink in an attempt to numb or avoid these feelings, they may be preventing this natural recovery from taking place, leading to maintenance of the anxiety symptoms in the long run (Stewart et al., 1998).

Treatment Outcome and Relapse When individuals who suffer from both anxiety disorders and alcohol use disorders enter treatment for either disorder, their treatment outcome is often negatively affected by their comorbidity. Alcohol use disorders have been found to predict poorer anxiety disorder treatment outcomes for patients with both PTSD (Forbes, Creamer, Hawthorne, Allen, & McHugh, 2003), panic disorder with agoraphobia, social phobia, and generalized anxiety disorder (Bruce et al., 2005). Comorbid anxiety problems also increase the likelihood of relapse in treated or abstinent alcoholics (e.g., Driessen et al., 2001; Kushner et al., 2005; Willinger et al., 2002). For example, if a comorbid PTSD – alcoholic individual does not know how to cope with flashbacks and nightmares of the traumatic event in ways other than through drinking, then continued reexperiencing symptoms can serve as a major risk factor for return to problem alcohol use following initially effective alcohol abuse treatment. Not all studies have shown this relationship, however. In one study (LaBounty, Hatsukami, Morgan, & Nelson, 1992), alcoholics with comorbid panic disorder did not differ in their rates of relapse to drinking problems from non comorbid alcoholics. However, in a recent review, Bradizza et al. (2006) noted some methodological issues with this paper, including the absence of a valid and reliable diagnostic measure and the failure to define relapse, limiting the conclusions that could be drawn from the study. Moreover, despite the similar relapse rates, the study did find that more comorbid alcoholic and panic disordered patients reported relapsing to cope with negative emotions than non comorbid alcoholics. Thus, these observed differences in the relapse process might be useful for improving treatments for this group. Another study compared relapse rates for alcoholic individuals with comorbid social phobia, or panic disorder with agoraphobia, or agoraphobia without a history of panic attacks to relapse rates for alcoholics without any comorbid anxiety disorder (individuals with other anxiety disorders were excluded) following treatment for alcoholism (Marquenie et al., 2006). The results suggested that the comorbid anxiety disorders did not have a significant impact on either relapse rates or days to relapse. Nonetheless, some methodological problems may account for this study’s failure to support higher alcoholism relapse among treated alcoholic patients with comorbid anxiety disorders. First, the study used a retrospective design. Participants were contacted for the study an average of 20.3 months (and up to 42 months) after baseline assessment, even though the majority of participants who relapsed did so within the first few months post

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baseline, raising issues concerning potential inaccuracy in the self-reports due to retrospective memory bias. Also, compared to the non comorbid group, the comorbid group had less chronic alcoholism and a shorter period between the initial and follow-up assessments, which could have led to underestimates of the rate of relapse in the comorbid group. Although the authors stated the failure to observe group differences in alcoholism relapse persisted when these group differences were statistically controlled in the analyses, statistical control of possible confounds is never definitive, (and in fact may even produce biased parameter estimates) especially when the confounding variables are correlated with the predictor of interest, again limiting any firm conclusions that can be drawn from the Marquenie et al. study. Several studies, on the other hand, have found higher relapse rates in comorbid patients. Driessen et al. (2001) found that treated alcoholic patients with comorbid anxiety had 29% higher alcoholism relapse rates than did alcoholics without comorbid anxiety. Furthermore, a study examining the relationship between trait anxiety and relapse in a sample of abstinent alcohol dependent patients found that higher trait anxiety was significantly predictive of relapse to uncontrolled drinking (Willinger et al., 2002). Finally, in the bestcontrolled study to date, Kushner et al. (2005) found that alcoholic patients with an anxiety disorder (especially those with comorbid panic disorder or social phobia) were significantly more likely to relapse to problem drinking (using multiple criteria for drinking relapse) than alcoholic patients without an anxiety disorder. These finding are particularly convincing given the methodological soundness of the study. For example, the study used a prospective design where all participants were contacted between 90 and 120 days after the beginning of treatment, thus increasing reporting accuracy by reducing reliance on long-term retrospective memory. Also, all participants were given the same standardized treatment and assessed at a consistent time following treatment. Taken together, it appears that comorbid alcohol and anxiety may have a negative effect on treatment outcome and relapse but with some mixed results. The methodologically superior studies do seem to suggest such a negative effect. In addition, although a couple of studies failed to show differences in relapse rates, one of these negative studies did provide some evidence for the self-medication hypothesis through highlighting the importance of coping with anxiety in explaining relapse to alcohol use among patients with comorbid alcohol and anxiety disorders. These differences could be useful in developing specific relapse prevention types of treatments (see Marlatt & Donovan, 2005) for comorbid patients.

Treatments of Comorbid Anxiety and Alcohol Use Disorders Individuals who suffer from both anxiety problems and alcohol use problems present a special and challenging population with regards to treatment. As was shown above, this population often suffers worse anxiety and alcohol treatment

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outcomes than populations experiencing symptoms in only one of the two domains. Although the study of specific treatments for anxiety – alcohol comorbidity is still in its infancy, this area is growing and there are now several promising approaches to treating comorbid anxiety and alcohol use disorders (Stewart & Conrod, in press). There have been mixed findings regarding the effects of pharmacological treatment for anxiety on drinking outcomes with some studies finding improvements in alcohol outcomes and others finding more equivocal results (see review by Kushner et al., 2000a). One study (Randall et al., 2001) found that treating individuals with comorbid social phobia and alcohol use disorder with paroxetine (a selective serotonin reuptake inhibitor) did improve anxiety, but did not result in significant decreases in drinking frequency and quantity. Relative to placebo, paroxetine treatment did, on the other hand, lead to improvements on the Clinical Global Index for alcohol. Other studies have found that successful treatment of anxiety with buspirone was also associated with a reduction in alcohol use (Tollefson, Montague-Clouse, & Tollefson, 1992; Kranzler et al., 1994). These mixed findings are partially consistent with the self-medication hypothesis, although the paroxetine study does suggest that there is more to the maintenance of problematic drinking behavior in anxious individuals than just the self-medication process. There have also been mixed findings for the effectiveness of cognitive behavioral therapy (CBT) to improve anxiety and problematic drinking symptoms in comorbid patients. Thevos et al. (2000) found that, for female patients with comorbid social phobia and alcohol use disorders involved in project MATCH (the largest treatment-matching trial to date), CBT treatment for alcohol was more effective in delaying return to drinking than Twelve-Step Facilitation (TSF). It was hypothesized that TSF, which encourages participation in Alcoholics Anonymous (AA), a group-based treatment modality that heavily involves public speaking as patients share their experiences, may be too intimidating for women with social phobia. Subsequently, Randall, Thomas, & Thevos, (2001) examined whether conducting parallel CBT treatments aimed at decreasing social anxiety and at addressing problematic drinking behaviors would have additional benefits for comorbid patients compared to treatment of the alcohol disorder alone. For patients receiving the parallel treatments, the sessions consisted of CBT treatment for alcohol followed immediately by CBT for social anxiety (i.e. the two treatments are offered simultaneously, but independently of each other). Surprisingly, they found that patients who participated in the parallel treatment had worse drinking outcomes, as assessed by drinking quantity and frequency measures, than did patients who participated in the alcohol only treatment. There are several possible explanations for these unexpected findings. It is possible that clients in the parallel treatment group engaged in more social situations as a consequence of their social phobia treatment, resulting in more opportunities to drink. Additional research needs to be conducted that would include other types of outcome measures that are not specifically linked to frequency or quantity of drinking. As was mentioned

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earlier in the chapter, coping drinking motives and problematic consequences of drinking are useful therapy targets for comorbid individuals, particularly in the case of social phobia. It is also possible that the lack of integration of the two treatments or the excessive demands of combining two already intensive treatments may have affected results. The parallel treatment did in fact lead to somewhat higher drop out rates than the alcohol treatment alone, suggesting that the parallel treatment may have been too much for comorbid patients to handle (Conrod & Stewart, 2005). On the other hand, another study (Bowen, D’Arcy, Keegan, & Senthilselvan, 2000) found that parallel CBT for panic disorder and standard alcohol treatment in a group of comorbid panic disordered and alcoholic patients did not result in significantly different treatment outcomes than standard alcohol treatment alone. Both treatments resulted in significant decreases in anxiety and in drinking behaviors. The authors noted that the relaxation training and stress management components of the standard alcohol treatment might have limited the ability to distinguish between treatments as these components may have been useful in targeting the comorbid anxiety. A recent randomly-controlled study conducted by Schade and colleagues (2005) compared standard alcohol treatment alone to standard alcohol treatment with anxiety treatment consisting of CBT plus optional fluvoxamine (a selective serotonin re-uptake inhibitor) treatment (again, a parallel approach) in patients with a primary diagnosis of alcohol dependence and a comorbid diagnosis of panic disorder, agoraphobia, or social phobia. There were no differences in alcohol outcome measures between both groups of patients. The additional anxiety treatment did, on the other hand, improve anxiety symptoms. It can be speculated that improved anxiety scores are significant for this population, as decreased anxiety may serve as a protective factor for longer-term outcomes. The study examined outcome results 32 weeks after initial assessment, but did not look at longer- term outcomes (1 year or later) in these patients. Future studies should examine longer-term treatment outcomes in comorbid anxiety and alcohol patients. Few studies, however, have reported outcomes for truly integrated treatments. Integrated treatment models recognize the complex relationship between anxiety disorders and alcohol use disorders and their possible mutual maintenance (Zahradnik & Stewart, in press). Furthermore, their aim is to create a hybrid of the treatments that work best for each disorder separately, and also include in the treatment strategy an understanding of the reciprocal influences each disorder has on the other (Zahradnik & Stewart). Integrated treatments have been developed and tested for certain anxiety disorder – substance use disorder combinations, but until now only one study (Kushner et al., 2006) has investigated an integrated treatment focusing on comorbidity with alcohol use disorders in particular. The treatment integrated CBT for panic disorder with content focusing on the interaction between alcohol use and panic symptoms. The integrated treatment was provided on top of treatment as usual (TAU) for the alcohol use disorder and compared to a group who received only the TAU.

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The trial was conducted on a sample of comorbid panic disorder – alcoholic patients, with promising results. The group receiving the integrated treatment showed better anxiety and alcohol outcomes than the TAU alcohol only treatment group. It is hoped that integrated treatments will provide a more effective strategy in treating comorbid patients. Integrated treatments appear to be the most recommended by ‘‘expert opinion’’; however few of the recommendations are supported by randomized controlled trials, or even quasi-experimental designs (Watkins, Hunter, Burnman, Pincus, & Nicholson, 2005). More research needs to be conducted to develop and test integrated treatment strategies and to compare them against parallel or sequential approaches.

Prevention and/or Early Intervention Another treatment approach receiving recent research attention involves targeting the vulnerability factors (e.g., AS) associated with problematic drinking in cases with, or at risk for, comorbid anxiety disorders (Conrod, Stewart, Comeau, & MacLean, 2006, Watt et al., 2006). A study by Watt et al. found promising results for brief CBT targeted at reducing AS in a sample of university women. Three 50-minute CBT sessions led to a decrease in the proportion of women with high AS who engaged in negative consequence drinking (based on elevated scores on the Rutgers Alcohol Problem Index; RAPI; White & Labouvie, 1989), as well as a decrease in conformity-motivated drinking (a high-risk drinking motive; Cooper et al., 1992; Cooper, 1994) and in emotional relief alcohol expectancies (i.e. a positive alcohol expectancy similar to tension reduction expectancies described earlier). The treatment also significantly reduced AS levels (Watt et al., 2006). Another similar AS-focused brief CBT delayed drinking onset in young at-risk adolescents (mean age = 14; Conrod, Castellanos, & Mackie, in press). Later drinking onset has been shown to be a factor protecting against the development of later alcohol use problems (Grant, Stinson, & Harford, 2001). The intervention also reduced panic attacks in high AS adolescents (Castellanos & Conrod, 2006). Together, these results suggest that brief CBT focused on reduction or management of AS may be a useful strategy for prevention of or early intervention with anxiety – alcohol use disorder comorbidity.

Conclusion Although there is ample evidence supporting the existence of a strong relationship between anxiety and its disorders, and alcohol use and its disorders, much remains unknown regarding the nature of the relationship. More research examining particular circumstances in which anxious individuals are more

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likely to self-medicate needs to be conducted, with a focus on potential differences in high-risk drinking situations across the various anxiety disorders. In addition, there has been little research about protective factors that can decrease anxious individuals’ needs to self-medicate their anxiety symptoms. For example, a few studies have explored the role of self-efficacy in heavy drinking among individuals with anxiety disorders (Burke & Stephens, 1997; Gilles et al., 2006). Initial results suggest that it might be beneficial for treatments to incorporate specific strategies to increase anxious individuals’ feelings of self-efficacy, especially about avoiding heavy drinking in particular high risk situations (e.g., those involving anxiety). Increased knowledge about this and other potential protective factors may be useful when designing specific treatments for comorbid populations (Burke & Stephens, 1997). It has also been found that alcohol expectancies, drinking motives, and anxiety sensitivity all moderate or mediate the relationship between anxiety and alcohol use/abuse. In addition, these three variables have been found to interact with or intervene with each other when explaining reasons and circumstances for increased and problematic alcohol use in anxious individuals (e.g., Stewart et al., 2001). More research exploring the interplay between these and other moderating and mediating variables would provide deeper and more complete understanding of the precise mechanisms through which anxiety and alcohol use affect one another. Finally, although research on treating and preventing comorbid anxiety disorders and alcohol use disorders is still in relatively early stages, promising approaches are emerging in this growing clinical research area. For example, in prevention/early intervention, recent studies have shown promising results for targeting personality risk factors directly (e.g., AS) in attempts to reduce both emergent problematic drinking (Conrod et al., 2006; Watt et al., 2006) and emerging anxiety disorder symptoms (Castellanos & Conrod, 2006). Recent research aimed at developing truly integrated treatments for comorbid patients that consider the interplay between anxiety symptoms and drinking behaviors (Kushner et al., 2006) has also provided positive preliminary results. Treatment research efforts should continue exploring ways to address the factors discussed in this chapter (e.g., moderating and/or mediating factors) linking anxiety and problematic alcohol use to improve the efficacy of treatments we have available for comorbid patients.

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Stewart, S. H., Zvolensky, M. J., & Eifert, G. H. (2001). Negative-reinforcement drinking motives mediate the relation between anxiety sensitivity and increased drinking behavior. Personality and Individual Differences, 31, 157–171. Swendsen, J. D., Conway, K. P., Rounsaville, B. J., & Merikangas, K. R. (2002). Are personality traits familial risk factors for substance use disorders? Results from a controlled family study. American Journal of Psychiatry, 159, 1760–1766. Swendsen, J. D., Tennen, H., Carney, M. A., Affleck, G., Wilard, A., & Hromi, A. (2000). Mood and alcohol consumption: An experience sampling test of the self-medication hypothesis. Journal of Abnormal Psychology, 109, 198–204. Tambs, K., Harris, J. R., & Magnus, P. (1997). Genetic and environmental contributions to the correlation between alcohol consumption and symptoms of anxiety and depression: Results from a bivariate analysis of Norwegian twin data. Behavior Genetics, 27, 241–249. Thevos, A. K., Roberts, J. S., Thomas, S. E., & Randall, C. L. (2000). Cognitive behavioral therapy delays relapse in female socially phobic alcoholics. Addictive Behaviors, 25, 333–345. Thomas, S. E., Randall, C. L., & Carrigan, M. H. (2003). Drinking to cope in socially anxious individuals: A controlled study. Alcoholism: Clinical and Experimental Research, 27, 1937–1943. Tollefson, G. D., Montague-Clouse, J., & Tollefson, S. L. (1992). Treatment of comorbid generalized anxiety in a recently detoxified alcoholic population with a selective serotonergic drug (buspirone). Journal of Clinical Psychopharmacology, 12, 19–26. Tolstrup, J. S., Heitmann, B. L., Tjonnelands, A. M., Overvad, O. K., Sorensen, T. I. A., & Gronbaeki, M. N. (2005). The relation between drinking pattern and body mass index and waist and hip circumference. International Journal of Obesity, 29, 490–497. Tran, G. Q., Haaga, D. A. F., & Chambless, D. L., (1997). Expecting that alcohol use will reduce social anxiety moderates the relation between social anxiety and alcohol consumption. Cognitive Therapy and Research, 21, 535–553. Ullman, S. E., Filipas, H. H., & Townswend, S. M. (2005). Trauma exposure, posttraumatic stress disorder and problem drinking in sexual assault survivors. Journal of Studies on Alcohol, 65, 610–619. Watkins, K. E., Hunter, S. B., Burnman, S. B., Pincus, H. A., & Nicholson, G. (2005). Review of treatment recommendations for persons with a co-occurring affective or anxiety and substance use disorder. Psychiatric Services, 56, 913–926. Watt, M., Stewart, S., Birch, C., & Bernier, D. (2006). Brief CBT for high anxiety sensitivity decreases drinking problems, relief alcohol outcome expectancies, and conformity drinking motives. Journal of Mental Health, 15, 683–695. Weinstock, L. M., & Whisman, M. A. (2006). Neuroticism as a common feature of the depressive and anxiety disorders: A test of the revised integrative hierarchical model in a national sample. Journal of Abnormal Psychology, 115, 68–74. White, H. R., & Labouvie, E. W. (1989). Towards the assessment of adolescent problem drinking. Journal of Studies on Alcohol, 50, 30–37. Willinger, U., Lenzinger, E., Hornik, K., Fischer, G., Schonbeck, G., Aschauer, H. N., et al. (2002). Anxiety as a predictor of relapse in detoxified alcohol-dependent patients. Alcohol and Alcoholism, 37, 609–612. Zahradnik, M., & Stewart, S. (in press). Anxiety disorders and substance use disorder comorbidity: Epidemiology, theories of interrelation, and recent treatment approaches. In M. Antony & M. Stein (Eds.), Handbook of anxiety and the anxiety disorders. Oxford, UK: Oxford University Press. Zimmermann, P. Wittchen, H. U., Hofler, M., Pfister, H., Kessler, R. C. & Lieb, R. (2003). Primary anxiety disorders and the development of subsequent alcohol use disorders: A 4-year community study of adolescents and young adults. Psychological Medicine, 33, 1211–1222.

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Zinbarg, R. E., Mohlman, J., & Hong, N. N. (1999). Dimensions of anxiety sensitivity. In S. Taylor (Ed.), Anxiety sensitivity: Theory, research, and treatment of the fear of anxiety. (pp. 83–114). Mahwah, NJ: Lawrence Erlbaum.

Illicit Drug Use Across the Anxiety Disorders Prevalence, Underlying Mechanisms, and Treatment Matthew T. Tull, David E. Baruch, Michelle S. Duplinsky, and C. W. Lejuez

An increasing number of studies are beginning to recognize the heightened risk for the development of substance use disorders among individuals with an anxiety disorder diagnosis, and the possible interplay between these disorders is receiving more attention in theoretical, clinical, and empirical spheres (e.g., Goodwin et al., 2002; Morissette, Tull, Gulliver, Kamholz, & Zimering, 2007; Stewart, 1996; Zvolensky & Schmidt, 2004; Zvolensky, Schmidt, & Stewart, 2003). As the majority of this attention has been focused on nicotine or alcohol use, the goal of this chapter is to review the extant work specific to illicit drug use across the anxiety disorders. In keeping with this focus, we will consider only illicit drugs and refer interested readers to chapters 4 and 5 in this volume for reviews specific to nicotine and alcohol. We begin by providing a brief list of the drugs that would fall under the larger category of illicit drugs, as well as prevalence rates of illicit drug use within the general population. We then move to discuss prevalence rates of illicit drug use within the anxiety disorders and among individuals with anxiety-disorder relevant symptoms (e.g., non-clinical panic attacks). Of note, this chapter will focus primarily on illicit drug use within the anxiety disorders as opposed to anxiety disorder diagnoses among individuals who use illicit drugs. Next, we present theories and data pertaining to the temporal progression of illicit drug use and anxiety disorders. The chapter then concludes with a brief review of treatments that specifically address comorbid anxiety and illicit drug use.

Illicit Drugs The term illicit drug is used here in reference to any substance that is illegal, with the distinction of illegal being specific to the United States.1 Such drugs, as recognized by the Diagnostic and Statistical Manual of Mental Disorders, Matthew T. Tull Department of Psychology, University of Maryland, College Park, MD 20742, Tel: 301-4053281, FAX: 310-405-3223 [email protected] 1

Due to space limitations we do not consider legal drugs used in an illegal manner (e.g., pain medications used without a prescription).

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4th Edition (DSM-IV; American Psychiatric Association [APA], 1994), include opioids (e.g., heroin, morphine), cocaine and its variants (e.g., crack), amphetamines (e.g., crystal methamphetamine), hallucinogens (e.g., LSD, PCP), inhalants, and marijuana. Drug use diagnoses include abuse and dependence. Abuse refers to a pattern of drug use leading to significant functional impairment, as evidenced by one of the following within a 12 month period: 1) recurrent use leading to failures to fulfill major obligations at work, school, or home; 2) recurrent use in situations where it may be physically hazardous to do so; 3) legal problems resulting from use; or 4) continued use even when the drug use results in social or psychological problems (APA, 1994). Dependence refers to a history of drug use marked by: 1) substance abuse; 2) continued use despite problems associated with that use; 3) drug tolerance; and 4) withdrawal symptoms (APA, 1994). Specific reference to use, abuse, and dependence often differ across studies, which can limit more broad conclusions across studies. Therefore, throughout this chapter we refer more broadly to use and will refer specifically to abuse and dependence when appropriate. In regard to rates of illicit drug use within the general population, the National Comorbidity Survey (NCS; Kessler et al., 1994), a nationally representative household survey of 8,098 adults aged 15–54 in the United States, found that 4.4% (5.4% of men and 3.5% of women) of respondents met criteria for lifetime drug abuse and 7.5% (9.2% of men and 5.9% of women) met criteria for lifetime drug dependence. In regard to 12-month prevalence, 0.8% (1.3% of men and 0.3% of women) met criteria for 12-month drug abuse and 2.8% (3.8% of men and 1.9% of women) met criteria for 12-month drug dependence. Data from the NCS Replication (NCS-R; Kessler, Chiu, Demler, & Walters, 2005), a nationally representative household survey of adult English-speaking individuals in the United States, provides more recent 12-month prevalence rates. Specifically, the NCS-R found that 1.4% and 0.4% of 5,692 respondents met criteria for drug abuse or dependence (respectively) in the past 12 months (prevalence rates as a function of gender were not provided). A limitation of the majority of epidemiological surveys is the examination of prevalence rates across drugs, with limited specificity to particular drugs. As a notable exception, the Epidemiological Catchment Area (ECA) study, a representative household survey of 20,291 adults in the United States, provides 6-month and lifetime prevalence rates for drug use disorders, as well as rates for specific illicit drug use disorders (rates are collapsed across abuse or dependence)(Reiger, et al., 1990). In particular, 2% and 6.1% of the sample met criteria for a 6-month or lifetime drug use disorder respectively. In regard to specific drug use disorders, prevalence rates were provided for marijuana dependence-abuse (1.2% 6-month, 4.3% lifetime), cocaine dependence-abuse (0.0% 6-month, 0.2% lifetime), opiate dependence-abuse (0.1% 6-month, 0.7% lifetime), amphetamine dependence-abuse (0.2%

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6-month, 1.7% lifetime), and hallucinogen dependence-abuse (0.0% 6-month, 0.3% lifetime) (Reiger et al., 1990). The National Epidemiological Survey on Alcohol and Related Conditions (NESARC; Conway, Compton, Stinson, & Grant, 2006), a representative household and group quarters survey of 43,093 adults in the United States, provides a more recent estimate of lifetime prevalence rates of drug use disorders, as well as rates for specific illicit drug use disorders, than the ECA. Within their sample (which over-sampled for minorities and young adults between 18–24 years of age), 7.74% (10.6% for men and 5.1% for women) met criteria for lifetime drug abuse and 2.59% (3.3% for men and 2.0% for women) for lifetime drug dependence. In regard to specific illicit drug use disorders: 1.08% (1.6% men, 0.6% women) and 0.34% (0.4% men, 0.3% women) met criteria for lifetime opioid abuse and dependence respectively, 1.40% (1.9% men, 0.9% women) and 0.60% (0.6% men, 0.6% women) met criteria for lifetime amphetamine abuse and dependence respectively, 1.45% (2.1% men, 0.9% women) and 0.24% (0.4% men, 0.1% women) met criteria for lifetime hallucinogen abuse and dependence respectively, 1.83% (2.7% men, 1.0% women) and 0.98% (1.2% men, 0.7% women) met criteria for lifetime cocaine abuse and dependence respectively, 7.16% (10% men, 4.5% women) and 1.30% (1.7% men, 0.9% women) met criteria for lifetime marijuana abuse and dependence respectively, and 0.30% (0.5% men, 0.1% women) met criteria for lifetime inhalant/solvent abuse (Conway et al., 2006). In terms of racial/ethnic differences in drug use disorders, Smith et al. (2006) found in the NESARC that, in general, Native Americans evidenced the highest 12 month prevalence rates of drug abuse or dependence as compared to all other racial/ethnic groups. Rates of drug use disorders across racial/ethnic groups were as follows: White (1.93%), Black/African-American (2.39%, significantly different from rates for White participants), Native-American (4.91%, significantly different from rates for White and Black/African-American participants), Asian/Asian-American (1.39%, significantly different from rates for Black/African-Americans and Native-Americans), and Latino (1.74%, significantly different from rates for Black/African-Americans and NativeAmericans). Not surprisingly, illicit drug use is associated with a variety of health compromising behaviors including risky sexual behavior (Brook et al., 2004; Loxley, Bevan, & Carruthers, 1998), licit substance use such as smoking (Zvolensky, Bonn-Miller et al., 2006) and alcohol abuse or dependence (Stinson et al., 2005), and poor self-care including poor dietary (Benedict, Evans, & Calder, 1999; Morabia et al., 1989) and sleep patterns (Pace-Schott et al., 2005). Combined with an anxiety disorder (which may develop independently of, prior to, or as a result of a drug use disorder), the interactive effects of a co-morbid drug use and anxiety disorder may place an individual at risk for more severe and extensive health consequences than those with either disorder alone.

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Illicit Drug Use in the Anxiety Disorders A number of studies have demonstrated that prevalence rates of anxiety disorder diagnoses among illicit drug users are generally higher than what has been found among individuals from the general population (e.g., Kessler, Berglund, Demler, Jin, & Walters, 2005; Grant et al., 2004). For example, Kessler, et al. (1996), in examining the 1-year prevalence of anxiety disorders among 5,877 individuals with a substance use disorder from the NCS, found that 24% of individuals with drug use without dependence also met criteria for some anxiety disorder and 45.5% of individuals with an illicit drug use disorder met criteria for an anxiety disorder. Beyond evidence of anxiety disorders among substance users, a growing literature focuses on illicit drug use among those with an anxiety disorder.

General Relationships Between Anxiety Disorders and Illicit Drug Use Reiger et al. (1990), in analyzing data from the ECA study, found that individuals with any anxiety disorder (as determined by DSM-III criteria) were 2.5 times as likely to also exhibit a comorbid drug use disorder (Odds Ratio [OR] = 2.4 for drug dependence and OR = 2.3 for drug abuse). Specifically, 11.9% of participants with any anxiety disorder diagnosis also met criteria for a drug use disorder, and this rate was significantly greater than that found among participants without an anxiety disorder diagnosis. Grant et al. (2004) found slightly higher ORs in examining data from the NESARC. Individuals with any anxiety disorder were 4.58 times as likely to also exhibit a comorbid drug use disorder (OR = 2.15 for drug abuse and OR = 2.43 for drug dependence). In another large scale study of comorbidity, Merikangas et al. (1998) analyzed data from six international epidemiological study sites (Germany, Mexico, Netherlands, Ontario, and two sites in the United States). They found that, across all sites, approximately 24.9% of individuals with any lifetime DSM-III-R anxiety disorder diagnosis also exhibited lifetime drug use (e.g., marijuana, opioids, stimulants, sedatives, or inhalants, but not alcohol), 35.8% exhibited lifetime drug problems (met at least one DSM-III-R abuse criteria for any drug), and 45.8% met criteria for lifetime DSM-III-R drug dependence. Lopez, Turner, and Saavedra (2005) analyzed data from 1,747 young adults (92% aged 19–21) from Miami-Dade county (Florida) public schools, and examined drug dependence among individuals with pure anxiety disorder diagnoses (i.e., the occurrence of one or more anxiety disorders that is not accompanied by any additional psychiatric disorder) or an anxiety disorder that

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was comorbid with some other psychiatric disorder (depression, dysthymia, conduct disorder, or attention deficit/hyperactivity disorder) (DSM-IV diagnostic criteria was used for disorder classification). Of the 4.9% with a pure anxiety disorder diagnosis (75.3% met diagnostic criteria for posttraumatic stress disorder [PTSD], 16.5% for social anxiety disorder [SAD], 5.9% for panic disorder [PD], and 3.5% for generalized anxiety disorder [GAD]), 13.9% also exhibited drug dependence. Further, more men (20.8%) than women (10.9%) with a pure anxiety disorder diagnosis also met criteria for drug dependence. Among the 10.2% with a comorbid anxiety disorder diagnosis (76.4% met criteria for PTSD, 18% for PD, 15.7% for SAD, 12.4% for GAD, and in terms of non-anxiety disorder comorbid psychiatric diagnoses, 62.9% met criteria for depression/dysthymia, 53.5% for conduct disorder, 36.5% for antisocial personality disorder, and 28.1% for attention deficit hyperactivity disorder), 29.2% met criteria for drug dependence. Again, more men (33.3%) than women (26.9%) with a comorbid anxiety disorder diagnosis also met criteria for drug dependence. Studies have also been conducted among adolescent populations and produced similar findings regarding high prevalence of drug use disorders among adolescents with anxiety disorder diagnoses. For example, Swadi and Bobier (2003) examined 62 adolescent patients (Mage=16.35) from an inpatient mental health facility in New Zealand. Of the 16% of these patients who had a diagnosable anxiety disorder, 63% also exhibited a drug use disorder (primarily marijuana, stimulants, and hallucinogens). Goodwin, Fergusson, and Horwood (2004) examined DSM-IV anxiety disorder and illicit drug dependence comorbidity among 1265 16–18 year-olds from the New Zealand Christchurch Health and Development Study (CHDS). Of the 175 participants who met criteria for an anxiety disorder at the age of 16–18, 12% also met criteria for illicit drug dependence, compared to 3.4% among those without an anxiety disorder diagnosis. Participants were then assessed again at age 18–21. Of the 130 who met criteria for an anxiety disorder within this age range, only 9.2% met criteria for illicit drug dependence. Interestingly, this rate was not significantly different from rates obtained among participants without an anxiety disorder diagnosis (7%).

Relationships Between Specific Anxiety Disorders and Illicit Drug Use In addition to examining general relationships between anxiety and drug use disorders, studies have also focused their attention on examining the relationship between specific anxiety disorders or anxiety disorder-related symptoms (e.g., non-clinical panic attacks) and the use of specific drugs. Although these studies are limited, more focused attention on the relationship between specific anxiety disorder diagnoses and drugs of abuse may further our understanding

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of the functional relationship between disorders. That is, depending upon the type of anxiety disorder present, an individual may be at risk for the development of a particular drug use disorder. We will first present data from the NESARC that provides an overview of 12-month and lifetime prevalence rates of various illicit drug use disorders among individuals with specific anxiety disorder diagnoses. We will then direct more focused attention on additional research that examines illicit drug use within specific anxiety disorders. The National Epidemiological Survey on Alcohol and Related Conditions. Conway et al. (2006) have recently presented data from the NESARC on lifetime prevalence rates of illicit drug use disorders across the DSM-IV anxiety disorders (with the exception of PTSD and obsessive-compulsive disorder [OCD]). In doing so, Conway et al. (2006) have provided the most comprehensive overview of anxiety disorder-illicit drug use disorder comorbidity to date2. Among respondents with PD with agoraphobia, 6.2% met criteria for a lifetime opioid use disorder, 9.2% for amphetamine use disorder, 8.1% for hallucinogen use disorder, 25.6% for marijuana use disorder, 11.5% for cocaine use disorder, and 0.8% for inhalant/solvent abuse. Among respondents with PD without agoraphobia, 4.9% met criteria for a lifetime opioid use disorder, 5.8% for amphetamine use disorder, 4.3% for hallucinogen use disorder, 17.7% for marijuana use disorder, 7.6% for cocaine use disorder, 1.1% for inhalant/ solvent abuse. Of respondents with SAD, 3.6% met lifetime criteria for an opioid use disorder, 5.5% for amphetamine use disorder, 4.1% for hallucinogen use disorder, 17.8% for marijuana use disorder, 6.3% for cocaine use disorder, and 0.7% for inhalant/solvent abuse. In regard to specific phobia, 2.8% of respondents with a lifetime diagnosis of specific phobia also met lifetime criteria for an opioid use disorder, 4.9% for amphetamine use disorder, 3.9% for hallucinogen use disorder, 14.9% for marijuana use disorder, 4.8% for cocaine use disorder, and 0.5% for inhalant/solvent abuse. Finally, among respondents with GAD, 3.7% also met lifetime criteria for an opioid use disorder, 6.2% for amphetamine use disorder, 4.6% for hallucinogen use disorder, 18.5% for marijuana use disorder, 7.1% for cocaine use disorder, and 0.7% for inhalant/solvent abuse. Conway et al. (2006) also examined gender differences in the ORs of illicit drug use disorders across the anxiety disorders. Few differences were observed. However, women with SAD (OR = 4.4) were significantly more likely than men with SAD (OR = 2.3) to exhibit comorbid lifetime opioid use disorder. In addition, men with PD with agoraphobia (OR = 8.7) were significantly more likely than women with PD with agoraphobia (OR = 6.5) to exhibit comorbid lifetime cocaine dependence. Grant et al. (2004) also provide 12-month anxiety disorder-illicit drug use disorder co-morbidity prevalence data from the NESARC, although 2

Due to space limitations, only data pertaining to drug use disorders in general will be presented. Readers interested in data pertaining to rates of drug abuse or dependence separately across the anxiety disorder diagnoses are referred to Conway et al. (2006).

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prevalence rates pertaining to specific illicit drug use disorders were not examined. Among respondents who met 12-month criteria for a DSM-IV anxiety disorder of PD with agoraphobia, 10.58% also exhibited a 12-month drug use disorder (4.65% drug abuse and 5.94% drug dependence). Rates of 12-month drug use disorders for other anxiety disorders were: 6.32% (2.17% drug abuse and 4.16% drug dependence) for PD without agoraphobia, 5.52% (2.59% drug abuse and 2.94% drug dependence) for SAD, 4.08% (2.13% drug abuse, 1.95% drug dependence) for specific phobia, and 8.06% (2.82% drug abuse, 5.24% drug dependence) for GAD. Finally, data from the NESARC has been used to examine differences in racial/ethnic background across comorbid anxiety and drug use disorders. Specific to abuse, Smith et al. (2006) found significant 12-month associations between drug abuse and all anxiety disorders (with the exception of PD without agoraphobia). No other significant 12-month associations between drug abuse and anxiety disorders were found for any other racial/ethnic group, with the one exception of a significant 12-month association between drug abuse and specific phobia among Native American respondents. A greater number of significant associations were found when examining the relationship between drug dependence and specific anxiety disorders across racial/ethnic groups. Significant associations were found for drug dependence and all anxiety disorders examined (PD with and without agoraphobia, SAD, specific phobia, GAD) among White respondents. Significant associations were found for drug dependence and all anxiety disorders with the exception of specific phobia for Black/African American respondents. Among Native American respondents, significant associations were found for PD without agoraphobia and SAD. Asian/AsianAmerican respondents demonstrated significant associations between drug dependence and PD without agoraphobia, SAD, and GAD, and Latino respondents exhibited significant associations between drug dependence and PD with agoraphobia, SAD, specific phobia, and GAD. As mentioned previously, the NESARC is the first to provide comprehensive data on the co-occurrence of specific anxiety disorders and illicit drug use disorders. In general, though, limited data is available that examines drug use within specific anxiety disorders. The one exception, however, may be PTSD, as a number of studies have examined the co-occurrence of PTSD and illicit drug use (for a review, see Chilcoat & Menard, 2003). We now move to a review of this literature, followed by a review of the literature pertaining to drug use within other anxiety disorders besides PTSD. Posttraumatic stress disorder. Data from the ECA found that compared to men and women without a diagnosis of PTSD, men with PTSD were 5 times more likely to also exhibit a drug use disorder and women with PTSD were 1.4 times as likely to exhibit a drug use disorder (overall odds ratio of 2.2; Helzer et al., 1987). In the NCS, Kessler, Sonnega, Bromet, Hughes, and Nelson (1995) found that compared to men and women without a diagnosis of PTSD, men with PTSD were approximately 2.97 times as likely and women 4.46 times as likely to exhibit a drug use disorder. Giaconia and colleagues (1995, 2000)

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collected data from 384 18-year-olds as part of The Early Adulthood Research Project (EARP) and found that compared to individuals without a history of traumatic exposure, individuals with a lifetime diagnosis of PTSD were 8.8 times as likely to also meet criteria for a lifetime drug dependence diagnosis and 14.14 times as likely to meet criteria for past year drug dependence. Calhoun et al. (2000) assessed drug use among a sample of 341 veterans with PTSD seeking treatment for PTSD. Opiate and marijuana use was reported by the largest number of patients (23% and 20% respectively). Benzodiazepine use was reported by 11% of patients, cocaine use by 8% of the patients, barbiturates by 5% of the patients, amphetamines by 3% of the patients, psilocybin by 3% of the patients, LSD by 1% of the patients, and PCP by 1% of the patients. Other studies have produced similar findings in regard to the use of specific drugs. For example, Saxon et al. (2001) found that incarcerated veterans with PTSD were more likely to report a greater degree of cocaine and heroin use as compared to individuals without a PTSD diagnosis. Tarrier and Sommerfield (2003) assessed 120 civilians seeking treatment for chronic PTSD on their drug use histories. Of the 120 participants, 17 used marijuana, 6 used sedatives, 4 used stimulants, 2 used a psychedelic, and 1 used cocaine. Further, in regard to rates of drug use disorders among younger individuals with PTSD, Kilpatrick, et al. (2000) collected data from a national sample of 4,023 adolescents (between the ages of 12 and 17). They found that PTSD was significantly associated with illicit drug use, including marijuana abuse and dependence and ‘‘harder’’ drug abuse and dependence (e.g., stimulants). Panic disorder and panic disorder-related symptoms. Moving beyond PTSD, a number of studies have examined illicit drug use among individuals with PD or PD-related symptoms, such as the experience of non-clinical panic attacks. Biederman et al. (2005) examined the rates of comorbid disorders among 23 individuals with PD and found that 8% exhibited a comorbid psychoactive substance use disorder. Among individuals with PD and major depression, 21% exhibited a comorbid psychoactive substance use disorder. Further, Zvolensky, Bernstein et al. (2006) examined lifetime associations between marijuana use, abuse, and dependence and panic attacks in a representative sample of 4,745 individuals. They found a positive association between lifetime panic attack occurrence and marijuana use, even when controlling for the effect of polysubstance use, alcohol abuse, and demographic variables (e.g., age, gender, etc.). Bonn-Miller, Bernstein, Sachs-Ericsson, Schmidt, and Zvolensky (2007) also examined the relationship between psychedelic (e.g., PCP, LSD, mescaline, peyote, psilocybin, DMT) use, abuse, and dependence and lifetime panic attack history within this same sample. Psychedelic abuse and dependence (although not use) were significantly associated with a heightened risk for the experience of lifetime panic attacks, controlling for demographic variables, polysubstance use, alcohol abuse, and a history of major depressive disorder. Deacon and Valentiner (2000) examined the relationship between panic attacks and substance use within a sample of 279 college students. Students with non-clinical panic attacks (n = 25) were significantly more likely than

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students without panic (n = 222) to report the use of drugs, such as sedatives (not alcohol), cocaine, and stimulants. Further, among non-clinical panickers, sedative use was not found to be related to distress about panic attacks, panic attack frequency, the occurrence of unexpected attacks, or general anxiety or depression symptoms. Valentiner, Mounts, and Deacon (2004) also investigated the relationship between panic attacks and illicit drug use in a sample of 399 incoming college freshman. Similar to Deacon and Valentiner (2000), they found that non-clinical panickers (n = 47), compared to non-panickers (n = 290), were significantly more likely to report lifetime use of sedatives, stimulants, and opioids, but not tobacco, alcohol, cocaine, or hallucinogens. In regard to specific rates of drug use among panickers, 12.8% reported lifetime use of sedatives (not alcohol), 6.4% reported lifetime use of cocaine, 55.3% reported lifetime use of marijuana, 34% reported lifetime use of stimulants, 21.3% reported lifetime use of opioids, and 23.4% reported lifetime use of hallucinogens. Additional analyses were conducted by Valentiner et al. (2004) to determine whether the relationships between panic and substance use differed as a function of gender or racial/ethnic background. Gender only served as a moderator in the relationship between panic and cocaine use. In particular, male panickers were significantly more likely to use cocaine than males without panic. In addition, among non-clinical panickers, substance use was not due to the number of panic attacks in the past year, panic attack symptom severity, and the experience of unexpected panic attacks. Other anxiety disorders. There is a dearth of studies on the relationship between specific drug use disorders with SAD, GAD, OCD, and specific phobia. More research is needed, especially given extant evidence that these anxiety disorder diagnoses may be associated with heightened risk for the development of illicit drug use disorders. For example, using data from the ECA Study, Reiger et al. (1990) found that 18.4% of respondents with lifetime OCD also exhibited a lifetime drug use disorder (11% for drug dependence and 7.4% for drug abuse). Further, this rate was significantly greater than what was found among individuals without a diagnosis of OCD. In regard to SAD, Kessler et al. (1996), in examining data from the NCS, found that respondents with SAD were significantly at greater risk to exhibit a 12-month co-occurrence of drug dependence (OR = 3.2) and lifetime drug dependence (OR = 2.6). Kessler et al. (1996) also provide data on GAD and specific phobia. Respondents with GAD were at significantly greater risk to exhibit lifetime drug dependence (OR = 3.8). Respondents with specific phobia were at significantly greater risk to exhibit co-occurring 12-month (OR = 1.8) or lifetime (OR = 2.5) drug dependence. Fewer studies have specifically examined the relationship between specific drug use and SAD; however, of note, several studies have also found evidence of an association between SAD and marijuana use (Buckner, Mallott, Schmidt, & Taylor, 2006; Buckner, Schmidt, Bobadilla, & Taylor, 2006; Lindquist, Lindsay, & White, 1979; Lynskey et al., 2002).

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Anxiety and illicit drug use disorder comorbidity in the context of a mood disorder. It is important to recognize that anxiety disorders are also likely to cooccur with other disorders, especially mood disorders. Therefore, it will be important for future studies to begin to examine the impact of mood-anxiety disorder comorbidity on drug use behavior. Speaking to this potential impact of mood-anxiety disorder comorbidity on drug use, Goodwin et al. (2002) examined the relationship between anxiety and drug use disorders among a sample of 130 individuals with a severe affective disorder (recurrent major depression, bipolar disorder) to examine whether the presence of a comorbid anxiety disorder diagnoses increases risk for the presence of a drug use disorder. They found that, in general, among individuals with a severe affective disorder, having an anxiety disorder was associated with a significantly increased risk of a cocaine, sedative, stimulant, or opioid use disorder. In examining specific anxiety disorders, they found that a) the experience of panic attacks increased the likelihood of having a cocaine, sedative, stimulant, or opioid use disorder; b) the presence of an OCD diagnosis increase the likelihood of stimulant use disorder; c) a diagnosis of SAD increased risk for a sedative use disorder; and d) and a specific phobia diagnosis was associated with increased risk for a cocaine, sedative, stimulant, and opioid use disorder.

Temporal Order of Anxiety Disorders and Illicit Drug Use Many of the studies discussed above are cross-sectional in nature, and therefore, it is impossible to determine the temporal progression of the disorders. In regard to the specific relationship between anxiety and drug use disorders, three temporal paths are possible. First, the use of specific drugs may increase the risk for the onset of an anxiety disorder. Second, illicit drug use may follow the development of an anxiety disorder diagnosis, consistent with a self-medication model of illicit drug use. Finally, there may be an underlying third factor that increases the risk for both anxiety disorders and illicit drug use. That is, there may be a common underlying mechanism for the comorbid development of these disorders (Goodwin et al., 2002).3 3

It is of note that a fourth possibility also exists. Specifically, anxiety disorder and drug use disorder diagnoses may develop through a completely independent process. Goldenberg et al. (1995) examined 181 participants in the Harvard Anxiety Research Project who had a history of substance use disorders and anxiety disorders in order to test hypotheses pertaining to the chronology of substance use-anxiety disorder comorbidity. They found, among individuals with a primary anxiety disorder diagnosis, the anxiety disorder diagnosis was present for, on average, 11.6 years before the onset of the substance use disorder. Further, substance use tended to occur a mean of 9.6 years before the onset of a secondary anxiety disorder diagnosis. Given the amount of time between the onset of the diagnoses, the authors concluded that there is not an etiological connection between the disorders, but instead, the onset of these disorders are guided by independent processes.

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Illicit Drug Use Precedes Anxiety Disorder Onset In regard to the first hypothesis, Zvolensky, Bernstein et al. (2006) found that a lifetime history of marijuana dependence was significantly associated with an increased risk for panic attacks, even when controlling for polysubstance use, alcohol abuse, and relevant demographic variables. Further, Cottler, Compton, Mager, Spitznagel and Janca (1992) found evidence for the high-risk hypothesis of comorbid PTSD-substance use disorder development. This hypothesis essentially states that drug use increases the likelihood of traumatic exposure (due to the high risk behaviors drug use is often associated with), thereby increasing risk for PTSD. Using data from the St. Louis Epidemiologic Catchment Area study, Cottler et al. (1992) examined the order of onset of PTSD and drug use within the 2,663 respondents. Cottler et al. (1992) found that drug use tended to precede the development of PTSD. However, it is important to note, that rates of PTSD in this sample were low (1.35% overall). In another study, Compton, Cottler, Phelps, Abdallah, and Spitznagel (2000) examined the temporal relationship of drug dependence and DSM-IIIR psychiatric diagnoses among 425 individuals in drug treatment. In the majority of cases (90%), drug dependence was found to follow the onset of a phobic disorder (the authors did not indicate whether this referred to SAD, specific phobia, or both). However, among individuals with a diagnosis of GAD, in 65% of the cases, the onset of the anxiety disorder followed the onset of the drug dependence, suggesting that, at least with GAD, the diagnosis may be secondary to drug dependence.

Illicit Drug Use Follows Anxiety Disorder Onset Studies have also provided support for the hypothesis that illicit drug use follows an anxiety disorder diagnosis. This hypothesis has most extensively been studied in PTSD. For example, Chilcoat and Breslau (1998) found that a PTSD diagnosis greatly increased the risk for the subsequent development of a SUD; however, traumatic exposure not resulting in PTSD did not have this effect, suggesting that the relationship between traumatic exposure and substance use is unique to those individuals who develop PTSD. They also found that substance abuse/dependence did not increase risk for traumatic exposure or PTSD (thus not providing support for the high-risk hypothesis). Consistent with a self-medication model of illicit drug use where drug use develops in an attempt to alleviate anxiety disorder symptoms, it has been demonstrated that exposure to trauma cues among PTSD-SUD patients is associated with substance craving, suggesting that the experience of PTSD-related symptoms may increase motivation to use substances in an attempt to relieve those symptoms (Coffey et al., 2002; Saladin et al., 2003).

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Additional support for the hypothesis that the presence of an anxiety disorder increases risk for illicit drug use comes from findings of Lopez et al. (2005) who found that, within their sample of 1747 young adults, the mean age of onset for an anxiety disorder diagnosis was consistently lower than that for substance dependence. In addition, an anxiety disorder diagnosis tended to occur before the onset of substance dependence 80% of the time.

Common Third Variables that may Underlie Both Illicit Drug Use and Anxiety Disorders Much less research has examined the third hypothesis of third variables that may function as a common underlying mechanism for both anxiety disorders and illicit drug use, especially in regard to the identification of common neurobiological and psychological mechanisms for the relationship between anxiety and drug use disorders. Two variables that are worthy of strong consideration are neurobiology and individual difference variables, which we will review below. First, however, it is also important to note that another important third variable for future consideration is gene by environment interactions. Although no current research has directly examined shared genetic transmission of anxiety and illicit drug use disorders, this is likely an important area for further pursuit. Specifically, the interaction between life stress and a polymorphism in the regulatory region of the serotonin transporter gene may be a particularly promising area of study. Indeed, although the preponderance of the work in this area has focused on the development of depression, some emerging research has separately identified the role of this interaction in the development of anxiety (Kendler, 1996) and illicit drug use (see Kreek, Nielsen, Butelman, & LaForge, 2005). Neurobiology. One aspect of neurobiology that may be potentially relevant to the development and maintenance of both anxiety disorders and illicit drug use involves the hypothalamic-pituitary-adrenal (HPA) axis, which controls the secretion of hormones for the pituitary and adrenal cortex. The HPA axis plays a central role in mediating the body’s response to stress and anxiety and is extremely sensitive to inputs from the limbic system and prefrontal cortex, two brain areas that are important in modulating reinforcement and motivational processes. The activity of the HPA axis is reflected in changes in serum or salivary cortisol levels (de Kloet & Reul, 1987), and has been found to account for differences in stress reactivity to physical and psychological laboratory challenges (Kaye et al., 2004; Wetherell et al., 2006). Neurobiological models of drug addiction hypothesize that dysregulated HPA axis functioning contributes to a state of chronic deviation of the regulatory system from its normal operating level, resulting in increased reinforcing effects of illicit drugs (Koob & Le Moal, 2001). More specifically, the HPA and brain stem stress circuits are hypothesized to be recruited in feed forward loops during response to stress,

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such that the corticotrophin releasing factor (CRF) in the extended amygdala drives norepinephrine systems in the pons-medulla of the brain stem, which in turn drives CRF in the extended amygdala. The extended amygdala is thus hypothesized to play a key role in regulating the HPA axis (i.e., stress response) and subsequent recruitment of negative reinforcement behavior (Koob & Le Moal, 2006), which may be especially relevant if substances are used for self-medication of anxiety symptoms. As much of this work is focused more on the relationship between stress and illicit drug use, as opposed to anxiety disorders specifically, it will be important for additional work to target the relationship between anxiety disorders and illicit drug use specifically. It is important to note, though, that dysregulation of the HPA axis has been found to play a role in the anxiety disorders (for a review, see Risbrough & Stein, 2006) and especially in PD (e.g., Erhardt et al., 2006) and PTSD (e.g., de Kloet et al., 2006; Yehuda, 2001) – two anxiety disorders that have been found to frequently co-occur with illicit drug use, suggesting that dysregulated functioning of the HPA axis may be common pathway at least for PD or PTSD and illicit drug use. However, further research is needed to test this hypothesis. Anxiety sensitivity. Anxiety sensitivity (AS) is an individual difference variable representing the tendency to fear anxiety-related sensations (e.g., increased heart rate, shortness of breath) due to beliefs that they will have negative somatic, cognitive, or social consequences (Reiss, 1991). Reiss (1991) originally proposed AS as a predisposing personality factor for the pathogenesis of the anxiety disorders, and research supports this, as demonstrated through the finding of elevated levels of AS across the anxiety disorders, with the exception of specific phobia (see Cox, Borger, & Enns, 1999). Although AS was originally proposed as a vulnerability factor for the anxiety disorders in general, its role as a specific vulnerability factor for PD has been examined most extensively. Studies consistently find higher levels of AS among individuals with PD, compared to individuals with other anxiety disorders (with the exception of PTSD) and healthy controls (see Cox et al., 1999). Further, AS has been predictive of the later development of spontaneous panic attacks (e.g., Schmidt, Lerew, & Jackson, 1997, 1999), as well as fearful responding to biological challenge tasks, such as hyperventilation and CO2 inhalation (Donnell & McNally, 1990; Harrington, Schmidt, & Telch, 1996; Rapee & Medoro, 1994; Schmidt & Telch, 1994; Telch, Silverman, & Schmidt, 1996; see also Zvolensky & Eifert, 2001, for a review). Similarly, successful treatment of PD has been found to be associated with corresponding reductions in AS following a cognitive behavioral group for PD (Telch et al., 1993) and individual cognitive behavior therapy (CBT) for anxiety medication discontinuation (Bruce, Spiegel, Gregg, & Nuzzarello, 1995). Research exploring AS as an underlying vulnerability for psychopathology in general has also been conducted, producing evidence that AS may underlie other psychiatric conditions as well, including depression (e.g., Otto, Pollack, Fava, Uccello, & Rosenbaum, 1995; Taylor, Koch, Woody, & McLean, 1996; Tull & Gratz, in press; Tull, Gratz, & Lacroce, 2006), borderline personality

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disorder (Gratz, Tull, & Gunderson, in press), and certain types of drug use patterns (see Lejuez, Paulson, Daughters, Bornovalova, & Zvolensky, 2006; Otto, Safren, & Pollack, 2004; Stewart & Kushner, 2001; Zvolensky & Schmidt, 2004). In regard to AS and drug use in particular, across the substance use disorders, McNally (1996) predicted that those individuals high in AS should specifically be at risk for drugs that include anxiolytic or depressive psychopharmacological effects as opposed to those with arousal properties (i.e., stimulants). However, research examining the role of AS in drug use is in its infancy, and across substances, alcohol and tobacco use have been most extensively studied (see chapters in this book; for reviews, see also Stewart, Samoluk, & MacDonald, 1999; Zvolensky et al., 2003). Few studies have been conducted that specifically examine the relationship between AS and other drug use. However, there is some evidence to suggest that elevated levels of AS may be associated with certain drug classes (besides tobacco and alcohol). Consistent with the relationship between arousal dampening drugs and AS, individuals reporting both chronic back pain and high AS report greater use of analgesic medications (Asmundson & Norton, 1995), and heightened AS has been found to be associated with elevated use of anxiety medications in general (Telch, Lucas, & Nelson, 1989). Bruce et al. (1995) examined successful benzodiazepine (Alprazolam) medication discontinuation in individuals receiving treatment as usual or the same procedure together with CBT treatment. While CBT significantly decreased anxiety and depression compared to control at 6-month follow-up, across both groups successful drug discontinuation was predicted by AS reduction from baseline to post-treatment. While McNally’s prediction has been generally supported regarding arousal dampening effects (but see Forsyth, Parker, & Finlay, 2003), the prediction that individuals with high AS should avoid arousal related drugs have not been confirmed to date. No differences have been found in preferences for illicit stimulants (e.g., cocaine or amphetamines) between high and low AS individuals (Norton et al., 1997; DeHaas, Calamari, Bair, & Martin, 2001; Forsyth et al., 2003) or for other stimulants such as caffeine (Stewart, Karp, Pihl, & Peterson, 1997). These findings suggest that while AS may act as a risk factor for drugs with arousal dampening effects, it does not act as a prophylactic against arousal producing self-medication. Research investigating the role of AS in marijuana use has provided mixed results. Whereas marijuana use has been reported to correlate with high AS in adolescents (Comeau, Stewart, & Loba, 2001), the opposite was found among adults in which low AS correlated with marijuana use (Norton et al., 1997; Stewart et al., 1997). In a recent investigation into adult tobacco users, marijuana users high in AS were at increased risk for more severe anxiety-related symptoms (Zvolensky, Bonn-Miller et al., 2006), controlling for the effects of cigarettes per day, alcohol use, and negative affectivity. In addition, AS has been found to predict the severity of marijuana withdrawal symptoms among young adult marijuana smokers, controlling for frequency of past 30-day marijuana use, number of cigarettes smoked per day, alcohol consumption,

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anxious arousal, and anhedonic depressive symptoms. These conflicting results indicate that future research is needed to better clarify the interactions between AS, marijuana, and other variables such as age and co-occurrence with other addictive substances. This research will aid in determining potential confounding factors, as well as facilitate the identification of more complex relationships between factors associated with vulnerability for illicit drug use and anxiety disorders. Further, given evidence that AS may be associated with the severity of marijuana withdrawal symptoms (Bonn-Miller, Zvolensky, Marshall, & Bernstein, 2007), it will be important for future research to examine whether AS may function to maintain drug use (due to fears of withdrawal symptoms) and/or increase risk for relapse for certain drugs during periods of attempted abstinence. Limited research has also been conducted that investigates the relationship between AS and heroin use. Lejuez et al. (2006) investigated AS among primarily African-American inner city substance users receiving treatment in a residential treatment facility. Specifically, measures of AS were collected among heroin users, crack/cocaine users, users of both heroin and crack/cocaine, and those that used neither. It was found that even when controlling for demographic variables, depressive symptoms, and the use of other drugs (e.g., alcohol, marijuana), primary heroin users evidenced higher levels of AS than all other groups, suggesting a unique relationship between heroin use and AS. Elevated AS has also been found to be a risk factor for worse treatment outcomes among heroin users in residential substance use treatment. Specifically, Lejuez, et al. (2007) examined AS as a predictor of residential substance use treatment drop-out among heroin and crack/cocaine users. Heightened levels of AS were found to predict residential substance use treatment dropout among heroin users but not crack/cocaine users. Prospective studies are needed to determine the specific role AS may play in the concurrent development of both anxiety and drug use disorders, as well as to identify the particular mechanisms through which AS may lead to these disorders. In regard to the pathogenesis of an anxiety disorder such as PD, heightened AS may be associated with attempts to avoid anxiety-related physical symptoms, thereby preventing functional exposure to the feared stimulus and maintaining anxious responding. Likewise, in regard to the pathogenesis of drug use, motivational models acknowledge the influence of positive consequences factoring into substance use yet posit a special role for the removal or avoidance of negative internal invents especially among chronic users (Cooper, 1994; Simons, Correia, Carey, & Borsari, 1998; Simons, Gaher, Correia, Hansen, & Christopher, 2005; Tate, Pomerleau, & Pomerleau, 1994). Baker, Piper, McCarthy, Majeskie, and Fiore (2004) comprehensively reviewed the basic experimental learning literature and concluded that negative reinforcement remains the primary mechanism behind addiction. Of utmost interest to the role of AS in addiction, Baker et al. (2004) argue that addiction is maintained by the avoidance and or escape of negative affect and other associated interoceptive cues (i.e. cognitive processes) that signal withdrawal symptoms.

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This is consistent with Hayes and colleagues proposal to reconceptualize psychopathology, including substance use, as a behavior that serves an experientially avoidant function. Experiential avoidance (defined as attempts to alter the form or frequency of internal experience such as thoughts, emotions, and bodily sensations; Hayes, Wilson, Gifford, Follette, & Strosahl, 1996) may be a particularly useful construct to examine in attempting to understand the pathway through which heightened AS leads to both the pathogenesis of anxiety disorders and illicit drug use. Experiential avoidance has been found to be associated with AS (e.g., Zvolensky & Forsyth, 2002), as well as a variety of anxiety disorder diagnoses and anxiety disorder-related symptoms (for reviews, see Hayes, Luoma, Bond, Masuda, & Lillis, 2006; Salters-Pedneault, Tull, & Roemer, 2004), as well as substance use behaviors (Hayes et al., 1996; Stewart, Zvolensky, & Eifert, 2002). Impulsivity (delay discounting). Impulsivity, defined as delay discounting, may also provide a useful framework for considering the concurrent development of anxiety disorders and illicit drug use. Traditionally, delay discounting has served as a behavioral operationalization for understanding the construct of impulsivity, which was developed following concern regarding the prevailing trait conceptualizations of the construct. Simply put, a delay discounting perspective considers impulsive behavior to be the choice of a smaller, immediate reinforcer instead of a larger, delayed reinforcer (Ainslie, 1975; Rachlin & Green, 1972). Taking this approach, studies have shown that compared to non-users, illicit drug users are more likely to select smaller amounts of immediate money instead of larger amounts that are delayed (e.g., $5 today over $20 in 30 days; Coffey, Gudleski, Saladin, & Brady, 2003; Kirby, Petry, & Bickel, 1999). In this way, this procedure provides an analogue for real world behavior of illicit drug users where more high impact yet delayed long-term goals (e.g., career development, relationship building) are sacrificed in favor of immediate gain in the form of drug use. Complimenting this approach to reinforcers, delay discounting also may be applied in its reciprocal form to aversive stimuli. In this case impulsivity involves the selection of a larger, delayed aversive stimulus over a smaller, yet immediate aversive stimulus. Said differently, this describes the tendency to put off experiencing an aversive event, even though this delay will result in an exacerbation of the negative consequences. A theoretical account of the relevance of this reciprocal approach to delayed discounting for SAD was provided by McNeil, Lejuez, and Sorrell (2001), describing the tendency of individuals with SAD to avoid potentially uncomfortable social interactions despite acute awareness that this will result in considerably larger long-term consequences. This approach is easily applied to other anxiety disorders as well. For example in the case of PD with agoraphobia, an individual may choose to only leave home with a ‘‘safe’’ person due to fear that of what will happen if alone in public during a panic attack, thereby resulting in the more severe yet delayed consequences associated with a loss of independence in the service of avoiding smaller yet immediate discomfort associated with leaving home alone.

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Combining both the reinforcer and reciprocal aversive conceptualizations of delay discounting provides a unique approach for understanding anxiety disorder-illicit drug use comorbidity. This may be particularly powerful in individuals where drug use is not only positively reinforcing (drug induced euphoria, social interaction) but also highly negatively reinforcing in regard to anxiety (the removal of overwhelming anxiety). It is also of note that although discounting is typically considered in terms of delay as discussed here, it is quite difficult to have a delay without also adding a degree of uncertainty. In this way, the extent to which delayed positive reinforcers and delayed aversives also are not perceived as guaranteed, their impact on keeping an individual from making an impulsive choice is further diminished. For example, while benefits of sobriety participating in exposure-based anxiety treatments seem strikingly powerful (good health, job security, trust, family), the delay to attaining the rewards are often long and relatively uncertain (will trust ever be fully returned? Will employers give you the benefit of the doubt if something goes missing? Will the anxiety ever really go away?), while pain (anxiety, withdrawal) remains immediate and certain. Thus, delayed discounting provides a framework to conceptualize the myriad of environmental factors influencing preference between two alternatives and suggests intervention implications (i.e., increasing the immediacy and certainty of alternative behaviors).

Treatment for Anxiety and Drug Use Disorder Comorbidity Given the high rates of comorbidity between anxiety disorders and substance use disorders, as well as suggestions that comorbid anxiety and substance use disorders may be better characterized as a single unique disorder (Hien, Cohen, Miele, Litt, & Capstick, 2004; Morissette et al., 2007), specialized treatments designed to specifically target this comorbidity are beginning to be developed. Of those treatments that are available, the majority are focused on the comorbidity between PTSD and substance use disorders. Seeking Safety. Najavits (2002) developed Seeking Safety to specifically target comorbid PTSD and substance use disorders. Seeking Safety is a 24-session cognitive behavioral group therapy protocol treatment that teaches individuals with this comorbid symptom presentation a variety of cognitive, behavioral, and interpersonal skills particularly applicable to individuals with both PTSD and substance use difficulties, all of which are designed with the idea that safety is the top priority in recovery from each disorder (Najavits, Weiss, & Liese, 1996). That is, coping skills are focused on maintaining abstinence, reducing self-destructive and high-risk behavior, and establishing support. Seeking Safety has been found to be effective, with patients exhibiting significant reductions in substance use behavior, trauma-related symptoms, suicide risk, suicidal thoughts, depression, and thoughts about substance use, and improvements in social adjustment, family functioning, and problem

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solving (e.g., Hien et al., 2004; Najavits et al., 1996; Zlotnick, Najavits, Rohsenow, & Johnson, 2003). Concurrent Treatment of PTSD and Cocaine Dependence. Another treatment specifically designed for individuals with comorbid PTSD and substance use disorders is Back, Dansky, Carroll, Foa, and Brady’s (2001) Concurrent Treatment of PTSD and Cocaine Dependence (CTPCD). This treatment consists of 16 individual 90-minute sessions. The treatment was designed by integrating previously validated cognitive behavioral treatments for substance dependence (Carroll, 1998) and PTSD (Foa, Rothbaum, Riggs, & Murdock, 1991; Foa & Rothbaum, 1998). CTPCD involves psychoeducation on the link between PTSD and cocaine dependence, coping skills training, relapse prevention skills, and cognitive restructuring. Further, patients undergo in-vivo and imaginal exposure in order to address their PTSD symptoms. In an initial examination of CTPCD, Brady, Dansky, Back, Foa, and Carroll (2001) found that individuals who completed treatment evidenced significant reductions in depressive symptoms, PTSD symptoms, and cocaine use severity. Anxiety Sensitivity Treatment for Heroin Users. Targeting AS, as opposed to any specific disorder, we (Tull, Schulzinger, Schmidt, Zvolensky, & Lejuez, 2007) recently developed an acceptance-based behavioral treatment (the Anxiety Sensitivity Treatment for Heroin Users; AST-H) meant to be used in conjunction with standard substance abuse treatment. Our treatment was designed to have specific relevance for heightened heroin users with heightened AS. Previous research (Lejuez et al., 2006) has demonstrated that heightened AS may increase risk for substance use treatment drop-out among heroin users. In particular, a tendency to fear of and unwillingness to have anxiety-related sensations may prompt individuals to attempt to avoid these sensations through the use of heroin. Therefore, we developed a six session adjunctive treatment where individuals engage in interceptive exposure exercises in order to facilitate acceptance of, and tolerance for, aversive internal sensations, with the goal of preventing the use of heroin for selfmedication of these sensations. In an initial examination of this treatment’s effectiveness, the AST-H was found to result in reductions in AS, heroin cravings, avoidance behavior, and emotion dysregulation (Tull et al., 2007). Improvements were maintained when measured over one month post-treatment. Current efforts are underway to replicate this finding within a randomized controlled trial.

Conclusion Recent years have seen a rise in studies examining the co-occurrence of illicit drug use and anxiety disorder diagnoses, and these studies provide convincing evidence that illicit drug use is prevalent among individuals with anxiety disorder diagnoses. Further, the impact of this co-occurrence on psychological functioning and physical health is clear. Yet, although studies have begun to address the mechanisms underlying this co-occurrence, all anxiety disorders

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and forms of illicit drug use have not been examined equally. Therefore, future research is needed to better understand the functional relationship between all anxiety disorders and forms of illicit drug use, with the goal of informing the development of novel and targeted interventions for this comorbidity, as well as prevention efforts.

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The Promise of Exercise Interventions for the Anxiety Disorders Jasper A. J. Smits, Angela C. Berry, Mark B. Powers, Tracy L. Greer, and Michael W. Otto

Introduction There is consistent evidence for the role of exercise in increasing longevity (Lee & Paffenbarger, 2000; Lee, Hsieh, & Paffenbarger, 1995) and reducing risk for coronary disease (Berlin & Colditz, 1990; Kohl, 2001), stroke (Wannamethee & Shaper, 1992), diabetes (Chipkin, Klugh, & Chasan-Taber, 2001), obesity (Ross & Janssen, 2001) and various cancers (Lee et al., 1995; Lee, Paffenbarger, & Hsieh, 1991; Lee, Paffenbarger, & Hsieh, 1992; Lee, Sesso, & Paffenbarger, 1999). Evidence from a variety of sources also suggests that physical activity benefits mental health (see for review Biddle, 2000; Stathopoulou, Powers, Berry, Smits, & Otto, 2006). Several large cross-sectional population studies have demonstrated that physical activity is associated with fewer symptoms of anxiety and depression (Stephens, 1988), lower levels of stress, anger, and cynical distrust (Hassmen, Koivula, & Uutela, 2000) as well as better social functioning and vitality among persons with anxiety and substance use disorders (Schmitz, Kruse, & Kugler, 2004). Prospective studies have further shown that physical activity is associated with a decreased risk of developing depression (Camacho, Roberts, Lazarus, Kaplan, & Cohen, 1991; Paffenbarger, Lee, & Leung, 1994) even after controlling for age, social economic status and educational level (Farmer, Locke, Mosciki, Larson, & Radloff, 1998). Lastly, there is a growing body of research demonstrating the efficacy of exercise interventions for mental health (Stathopoulou et al., 2006). If effective for the prevention and treatment of anxiety disorders, physical activity interventions would have a significant public health impact. In this chapter, we review the literature on the relationship between physical activity and anxiety. Specifically, we discuss findings from epidemiological, basic and clinical studies, and consider potential mechanisms by which physical activity Jasper A. J. Smits Southern Methodist University, Department of Psychology, 6424 Hilltop Lane, Dallas, TX. Tel: 214-768-4125, Fax: 214-768-0821 [email protected]

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may confer protective or anxiolytic effects. We conclude this chapter with suggested avenues for further research in this area.

Physical Activity Defined Caspersen, Powell, and Christenson (1985) defined physical activity as ‘‘any bodily movement produced by skeletal muscle that results in energy expenditure.’’ As such, physical activity encompasses a variety of activities, including occupational work, leisure activities and exercise, which is defined as a physical activity that is planned for fitness or health purposes (Caspersen et al., 1985). Exercise can be further sub-divided into aerobic or anaerobic exercise. Aerobic exercise includes activities such as walking, swimming, cycling and running, all of which require maintenance of increased heart rate. The American College of Sports Medicine (ACSM, 2005) defines aerobic exercise as a physical activity that lasts longer than three minutes during which glycogen is consumed with oxygen. In contrast, anaerobic exercise, which includes activities such as weight training and sprinting, lasts less than three minutes during which glycogen is consumed without oxygen (ACSM, 2005). Physical fitness has been defined as a set of attributes related to the ability to engage in physical activity (Caspersen et al., 1985). It is a multidimensional construct (President’s Council on Physical Fitness, 2000) that includes skill-related (e.g., agility, balance, speed, reaction time), health-related (e.g., cardiorespiratory endurance, muscular endurance, muscular strength, body composition, and flexibility) and physiologic components (e.g., glucose tolerance, blood lipid and cholesterol profiles, fatness, and bone mass). The latter two components have been more directly linked with physical health and evidence suggests that they can be more easily improved, relative to the other component of physical fitness, by engaging in regular physical activity (ACSM, 2006). Quantifying the level of physical activity involves the determination of energy expenditure, which is typically expressed in kilocalories, or the amount of heat required to increase the temperature of 1 kg of water by 18C. Energy expenditure is best measured by a method called ‘‘doubly labeled water’’ (Schoeller, 1988). This procedure involves several steps, starting with the administration of water labeled with stable isotopes of hydrogen and oxygen. Participants are then subjected to regular urine sampling to track the loss of these isotopes over a 7- to 14-day period. This procedure allows for an estimation of daily carbon dioxide production, which can be converted to total daily energy expenditure in kilocalories. However, instead of determining energy expenditure, most investigations of the relationship between physical activity or exercise and anxiety have relied on less expensive and more practical methods such as self-report questionnaires and interviews.

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These instruments typically assess several dimensions of physical activity including type, intensity, frequency, and duration, thereby allowing researchers to estimate the total expended kilocalories during a given time point (e.g., week, month). Such instruments are also often used merely to categorize participants’ physical activity habits (e.g., engaging in regular exercise versus not engaging in regular exercise, active versus non-active, sedentary versus non-sedentary). Research examining the link between anxiety pathology and fitness has mostly focused on cardiorespiratory fitness, which is operationalized as the volume of oxygen consumed while exercising at maximum capacity (i.e., VO2max). VO2max can be expressed in absolute values (liters/minute) or relative values (ml/kg/min). The values tend to be higher among men compared to women and decline with age. According to the ACSM (2006), mean absolute values for men over age 20 range from 44.2 to 34.6 ml/kg/min, whereas mean absolute values for women in the same age range are between 37.8 to 26.7 ml/ kg/min. VO2max can be measured directly using open-circuit spirometry, or indirectly by means of maximal or submaximal exercise tests. Since open-circuit spirometry and maximal exercise testing require specialized settings, submaximal exercise tests are more commonly employed. One of the most widely used submaximal exercise tests is the Astrand-Ryhming ergometer test (Astrand & Ryhming, 1954). During this 6-minute protocol, participants peddle at 50 rotations per minute at a work rate (i.e., watts) that is determined by the participant’s gender and fitness status. The objective is to reach a steady-state heart rate between 125 and 170 beats per minute. A nomogram is then used to estimate VO2max based on the average heart rate during minutes 5 and 6. Because it provides an index of cardiorespiratory fitness, VO2max can be used to guide the prescription of exercise intensity. Specifically, the intensity of exercise (e.g., very light, light, moderate, vigorous, very hard, maximal) can be Table 1 Physical activity intensity Intensity VO2R (%) HRR (%)

HR Max (%)

RPE

Very Light <20 <50 9 Light 20–39 50–63 11 Moderate 40–59 64–76 13 Hard 60–84 77–93 15 Very Hard 85 94 17 Maximal 100 100 20 Note: VO2R is oxygen reuptake reserve (i.e., the difference between resting VO2 and maximal VO2); HRR is heart rate reserve (i.e., difference between resting heart rate and maximum heart rate, where maximum heart rate is 220-age); HR Max is maximum heart rate; RPE is rating of perceived exertion using a scale from 6 to 20 (Borg, 1998). Table is adapted from ACSM guidelines for exercise testing and prescription (2006)

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anchored to VO2R (i.e., the difference between resting VO2 and maximal VO2) values. As can be seen in Table 1, intensity of exercise prescriptions can also be guided by a person’s heart rate reserve, maximal heart rate, or subjective ratings of perceived exertion (i.e., RPE; Borg, 1998).

Physical Activity in the United States Data from the 2002–2004 National Health Interview Survey (NHIS), which included a representative sample of 93,222 U.S. adults, indicated that 62% of adults engaged in at least in some leisure-time physical activity over the past year (i.e., light, moderate or vigorous activity episodes that last at least 10 minutes; Adams & Schoenborn, 2006). Physical activity status further varies as a function of several demographic factors. For example, physical activity is significantly more prevalent among men compared to women (64% versus 60.2%) and among White and Asian adults (63.7% and 62.1%) compared to Black and Hispanic adults (51.3% and 47.6%). Likewise, physical activity decreases with age and increases with education and family income (Adams & Schoenborn, 2006).

Developmental Stages of Adopting Physical Activity Understanding contributors to the adoption and maintenance of physical activity is critical to the implementation of physical activity interventions (see for review Marcus et al., 2000). The Transtheoretical Model (TTM) or ‘‘Stages of Change’’ (Prochaska & DiClemente, 1983) has been applied to many health-related activities, including physical activity, to describe the process of adopting a new behavior. The model describes five stages as follows: 1) precontemplation, in which there is no intent to change behavior within 6 months; 2) contemplation, in which there is intent to change behavior within 6 months; 3) preparation, in which there are small or inconsistent changes in a behavior; 4) action, in which there is active involvement in a behavior for less than 6 months’ duration; and 5) maintenance, in which a behavioral change is sustained for 6 months or more. Utilization of the stages in intervention management frequently involves assessment of individuals’ readiness to change, evaluation and contributors to stage transition, and stage-targeted strategies that target behaviors and issues specific to that stage. For example, in the PACEþ study (Calfas et al., 2002), behaviors such as targeting a specific exercise behavior (e.g., setting a goal to increase moderate or vigorous physical activity) was associated with a greater likelihood of moving to the next stage of change. Self-efficacy has also been shown to be an important factor in transition to subsequent stages (Plotnikoff, Hotz, Birkett, & Courneya, 2001). Marshall et al. (2003) reported that a stage-targeted physical activity intervention was associated with significantly greater increases in amount of post-baseline

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physical activity (78 minutes) compared to a control group receiving no intervention (12 minutes) after 2 months, although this effect was attenuated by 6 months. In the Project Active study, Dunn and colleagues (1999) showed that interventions based on the Stages of Change model yield comparable benefits to physical activity when utilized as a lifestyle or structured intervention, further supporting the incorporation of the model in intervention strategies. Indeed, research examining the TTM model has led to the development of multi-component approaches to adoption of and adherence to exercise. When assessing the feasibility of a treatment, it is important to consider behavioral factors that may limit the likelihood of treatment compliance. Multi-component interventions have been shown to be more effective than single component interventions because no one strategy is effective for all individuals (Ockene, Hayman, Pasternak, Schron, & Dunbar-Jacob, 2002; Roter et al., 1998). Multi-component strategies include behaviors such as developing a specific action plan for activity and targeting barriers to completion of the activity to increase the likelihood of exercise behaviors. This is particularly true with psychiatric populations, where psychological aspects of the disease process may increase barriers to exercise or create difficulty in moving on to the next stage of behavioral change.

Population-based Studies of the Relationship Between Physical Activity and Anxiety There have been several large-scale studies providing evidence for the negative association between physical activity and anxiety. For example, Stephens (1988) collapsed data from four national health surveys conducted in the United States and Canada between 1971 and 1981 (e.g., the National Health and Nutrition Examination Study, Canada Health Survey, National Survey of Personal Health Practices and Consequences, and the Canada Fitness Survey). This procedure yielded a total sample size of approximately 55,000 persons between ages 10 and 74. Both mental health and level of leisure time exercise were assessed by self-report. The findings supported the hypothesis that physical activity is associated with good mental health, including fewer symptoms of depression and anxiety, even after controlling for education and physical health status. Interestingly, the strength of this relationship varied as a function of age and sex, where a stronger link was observed among women and among those over age 40. Recently, Schmitz and colleagues (Schmitz et al., 2004) extended these findings by showing a link between physical activity and enhanced psychological and health-related well-being among persons suffering from DSM-IV anxiety disorders. They used data from the German National Health Interview and Examination Survey (GHS) which comprised a representative sample of approximately 7,000 persons between ages 18 and 79. Diagnoses (12-month prevalence) were determined by a combination of

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self-report and interviewer measures, while physical activity level and emotional well-being were assessed by self-report. Of those suffering from anxiety disorders (n = 573), 63% indicated that they were inactive. These inactive individuals reported significantly lower quality of life across a number of health and mental health domains relative to anxiety disorder sufferers who reported regular exercise. Further, the associations remained significant after controlling for theoretically-relevant variables, but they did not depend on age or gender. In addition to evidence for the association between physical activity and general emotional well-being, there is also survey data indicating that physical inactivity is related to clinical levels of anxiety. Using data from the National Comorbidity Survey (NCS), which comprised a probability sample of approximately 6,000 individuals between ages 15 and 54, Goodwin (2003) estimated the 12-month prevalence of DSM diagnoses among persons who indicated that they exercised ‘‘regularly’’ (60.3%) and compared the rate to those exercised occasionally, rarely or never. Findings revealed a dose-response relationship between physical activity and the likelihood of having an anxiety disorder. Specifically, physical activity was associated with a significantly decreased likelihood of agoraphobia, panic attacks, generalized anxiety disorder (GAD), specific phobia, and social phobia, even after controlling for comorbid physical illness and demographic variables. Interestingly, the relationship between physical activity and GAD was no longer significant after additionally adjusting for comorbid mental disorders, suggesting that physical inactivity may not be directly linked with GAD.

Clinical Studies of the Relationship Between Physical Fitness and Anxiety The linkage between phobic anxiety and cardiovascular disease and mortality (Coryell, Noyes, & House, 1986; Coryell, Noyes, & Clancy, 1982; GomezCaminero, Blumentals, Russo, Brown, & Castilla-Puentes, 2005; Kawachi et al., 1994; Kawachi, Sparrow, Vokonas, & Weiss, 1994; Kawachi, Sparrow, Vokonas, & Weiss, 1995; Weissman et al., 1990; see also White et al. in Chapter 11 in this volume) has prompted research on physical fitness among individuals suffering from pathological anxiety, and particularly panic disorder. There have been several studies that have employed standardized exercise testing protocols to determine cardiorespiratory fitness among individuals with panic disorder (Broocks et al., 1997; Gaffney, Fenton, Lane, & Lake, 1988; Martinsen, Raglin, Hoffart, & Friis, 1998; Meyer, Broocks, Bandelow, Hillmer-Vogel, & Ruther, 1998; Schmidt, Lerew, Santiago, Trakowski, & Staab, 2000; Taylor et al., 1987). For example, Martinsen and colleagues (1998) subjected 35 patients to a submaximal bicycle ergometer test and found that their VO2max was on average at 82% (1.9 liters/min) of the expected value. Similarly, Brooks and colleagues (1997) reported that, relative to a group of non-psychiatric participants (n = 24), individuals with panic disorder (n = 38) showed significantly

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reduced VO2max. Specifically, the mean relative VO2max values for panic disorder patients was 31.0 ml/kg/min (SD = 9.1) versus 37.6 ml/kg/min (SD = 6.3) for non-psychiatric controls. In a follow-up study, the authors (Meyer et al., 1998) showed that a 10-session exercise training program was associated with significant improvements in VO2max values. To clarify the link between panic disorder and fitness, Schmidt and colleagues (Schmidt et al., 2000) designed a study to determine whether the relatively poor cardiorespiratory fitness estimates among individuals with panic disorder may be biased by elevated levels of anxiety symptoms. To this end, they randomly assigned 27 panic disorder and 27 matched healthy control participants to a submaximal bicycle ergometer test with or without heart rate feedback. This study yielded several important findings. First, panic disorder participants showed reduced cardiorespiratory fitness relative to non-psychiatric participants even after controlling for anxiety responses during the testing protocol (26.4 ml/kg/min (SD = 11.4) versus 34.11 ml/kg/min (SD = 9.8), respectively). Second, although anxiety sensitivity (i.e., fear of anxiety-related sensations), a cognitive disposition that has been implicated in the onset and maintenance of panic disorder (McNally, 2002), was not directly associated with poorer fitness, it appeared to moderate the effects of diagnostic status and heart rate feedback on cardiorespiratory fitness. Specifically, cardiorespiratory fitness was particularly poor among panic disorder suffers with elevated levels of anxiety sensitivity. Similarly, heart rate feedback during testing was only associated with poorer fitness among individuals who reported elevated levels of anxiety sensitivity. Collectively, these findings suggest that cardiovascular conditioning is impaired among individuals with panic disorder, and emphasize the importance of considering anxiety sensitivity in investigations of the relationship between physical activity and anxiety. Indeed, support for the linkage between anxiety sensitivity and physical activity is growing. Recently, McWilliams and Asmundson (2001) observed an inverse relationship between exercise frequency and anxiety sensitivity in a non-clinical sample. Likewise, Smits and Zvolensky (2006) reported that anxiety sensitivity mediated the relationship between physical inactivity and measures of panic severity in a community sample of individuals with panic disorder. Further research regarding the linkage between exercise and anxiety sensitivity will be discussed in the next section on the effects of exercise interventions on anxiety.

Reductions in Anxiety with Exercise Although the studies discussed above support the hypothesis that physical activity plays a role in the etiology, maintenance and treatment of anxiety pathology, the cross-sectional nature of many of these investigations leave open several alternative explanations for the observed relationships. In this section, we will discuss a number of studies that have experimentally manipulated physical activity, providing some evidence for the causal effects of physical activity on anxiety.

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The Effects of Acute Exercise on Anxiety Evaluation of the beneficial effects of single episodes of exercise on anxiety has been the focus of numerous quantitative and qualitative reviews (e.g., Ekkekakis & Petruzzello, 1999; Petruzzello, Landers, Hatfield, Kubitz, & Salazar, 1991; Schlicht, 1994). For example, Petruzzello and associates (1991) conducted a meta-analysis of 119 studies that examined the pre- to post-exercise reductions in self-reported state anxiety. The mean controlled effect size was d = 0.23, although randomized controlled studies yielded smaller effect sizes (d = 0.16). In a more recent review, Ekkekakis and Petruzzello (1999) aptly pointed out that many of the studies examining the effect of acute exercise on anxiety lack the methodological rigor (e.g., adequate sample sizes and control conditions) necessary to significantly advance knowledge regarding the doseresponse relationship. They did, however, observe some robust findings. First, the duration of exercise session is not predictive of anxiety reduction beyond the effects explained by the degree of exercise intensity. Second, the degree of benefit is linked to the degree of fitness; in non-clinical samples, demanding exercise tasks result in greater anxiety reductions among high-fit individuals versus low-fit individuals (Ekkekakis et al., 1999). In addition to fitness level, the participant’s baseline anxiety level appears to be predictive of the degree of benefit. Long and Stavel (1995) reported that effect sizes for studies that employed high-anxious samples were significantly larger than those that employed low anxious samples (d = 0.51 and 0.28, respectively). One implication of this finding is that the degree of benefit from exercise may be much more profound in clinical samples. In addition to reducing state anxiety, single exercise sessions also appear to buffer the effects of social stressor tasks. Using a counterbalanced design, Rajeski and colleagues (Rejeski, Thompson, Brubaker, & Miller, 1992) asked 48 low-to-moderate physically fit women to exercise or rest prior to completing two stressor tasks. The experimental sessions began with either 40 minutes of cycling at 70% heart rate reserve or 40 minutes of rest after which participants rested 30 minutes. Following this 30 minute period, participants completed a Stroop mental challenge and a 3-minute impromptu speech on a controversial topic (e.g., abortion, role of women in society). Relative to rest, exercise was associated with less blood pressure reactivity following psychosocial stress, and reduced anticipatory anxiety prior to speech task. Similar findings have been observed in studies using biological challenge procedures. Biological provocations such as caffeine ingestion, inhalation of carbon dioxide-enriched air, and lactate infusion have been shown to reliably increase bodily and subjective symptoms of anxiety and panic in healthy controls (Zvolensky & Eifert, 2001). A series of recent studies (Esquivel, Schruers, Kuipers, & Griez, 2002; Strohle et al., 2005; Youngstedt, O’Connor, Crabbe, & Dishman, 1998) has demonstrated that emotional responding to these challenges is significantly attenuated when preceded by a single brief

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(e.g., 12–30 minutes) intense exercise session (e.g., 70% of max HR; 60–70% VO2max, >6mm of blood lactate). Together, these findings suggest that single exercise sessions result in anxiolysis in non-clinical participants.

Parameters of Exercise Interventions Petruzzello and colleagues (1991) reviewed 62 studies of exercise interventions that were at least four weeks in length. Most studies involved non-clinical (n = 48) or non-clinical high anxious (n = 11) individuals. Less than half of the studies (n = 25) employed a randomized controlled design; the other 37 studies were non-experimental or quasi-experimental in nature. Comparison groups involved waitlist control, relaxation or motivational control conditions and anxiety was generally measured using the trait version of the State-Trait Anxiety Inventory (STAI-T; Spielberger, Gorsuch, Lushene, Vagg, & Jacobs, 1983). The average controlled effect size for anxiety reduction with exercise training was (d = 0.34). However, post-hoc analyses revealed that the effect size significantly varied as a function of characteristics of study design and the exercise intervention. Specifically, randomized controlled studies yielded larger effects sizes (d = 0.54). Moreover, length of training was significantly associated with the degree of improvement in anxiety; interventions with a minimum length of 10 weeks were associated with greater effect sizes (d =0.36 to 0.90) compared to interventions with a duration of less than 10 weeks (d = 0.14 to 0.17). Similarly, only interventions with session durations between 21 and 30 minutes or greater than 40 minutes yielded significant effect sizes.

Exercise Training Programs for Clinical Anxiety Despite the wealth of studies devoted to the application of exercise interventions to stress and non-clinical anxiety, to our knowledge, there are only two randomized controlled clinical trials of exercise interventions for individuals meeting criteria for anxiety disorders. This limited evidence stands in stark contrast to studies of exercise interventions for major depression. For depression, exercise interventions are associated with reliable benefit. For example, a recent meta-analysis of 11 controlled studies of the efficacy of exercise interventions for depression yielded a controlled effect size of (d = 1.42) (Stathopoulou et al., 2006). For anxiety disorders, the available evidence for the efficacy of exercise interventions is limited to the treatment of panic disorder. Panic disorder is a particularly apt disorder for the application of exercise interventions (see for review Smits et al., 2007) given that fears of somatic sensations of anxiety (i.e., anxiety sensitivity) are central to the etiology and

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maintenance of the disorder (McNally, 2002; Smits, Powers, Cho, & Telch, 2004). Cognitive-behavioral treatments for panic disorder target anxiety sensitivity by prescribing exposure to these feared sensations (i.e., interoceptive exposure) in conjunction with cognitive interventions to help patients eliminate catastrophic interpretations of these symptoms (Margraf, Barlow, Clark, & Telch, 1993). Accordingly, in addition to the general benefits of exercise on anxiety reduction, as documented for nonclinical samples, exercise also has the potential to provide patients with exposure to feared sensations of bodily arousal. Indeed, aerobic exercise induces many of the somatic sensations (e.g., heart racing, rapid breathing, and sweating) that have shown to elicit increased anxiety reactions in panic disorder patients (Rief & Hermanutz, 1996). The notion that exercise can serve as an interoceptive exposure procedure is also consistent with early reports that exercise can be anxiogenic for these patients. For example, Cameron and Hudson (1986) observed significant increases in subjective anxiety during submaximal exercise testing in 31% of patients with panic disorder, but only in 7% of patient and non-patient controls. Similarly, two more recent studies reported that panic disorder patients are more likely to prematurely terminate submaximal exercise testing compared to non-clinical controls (Schmidt et al., 2000; Stein, Tancer, & Uhde, 1992). Consistent with previous evidence that repeated exposure to biological provocation procedures is associated with clinical benefits for panic disorder sufferers (van den Hout, van der Molen, Griez, Lousberg, & Nansen, 1987), Broman-Fulks, Berman, Rabian and Webster (2004) developed a brief exercise intervention to target anxiety sensitivity. The intervention consisted of six 20-minute high-intensity (60–90% maximal heart rate) sessions on a treadmill. This intervention was compared to a similar protocol low-intensity (below 60% of maximal heart rate) level aerobic exercise program. Neither group received a specific treatment rationale or cognitive interventions. Results revealed that the high intensity intervention was associated with significantly greater reductions in anxiety sensitivity compared to the low intensity intervention (pre- to posttreatment raw score mean reductions of 9.14 and 2.88, respectively). Preliminary results from our own laboratories suggest that preceding the interventions with a rationale emphasizing the importance of exposure to reducing anxiety sensitivity coupled with coaching participants during and following exercise sessions (i.e., ‘‘what are you learning from this?’’) may enhance the effect of this exercise intervention on anxiety sensitivity (Smits et al., 2007). In addition to the direct application of exercise as an interoceptive exposure procedure to reduce anxiety sensitivity, exercise may also have general anxiolytic properties for patients with panic disorder. Using a counterbalanced design, O’Connor (2005) asked 10 women with panic disorder to complete a maximal treadmill exercise test, 25 minutes of submaximal treadmill walking (i.e., 65% of VO2 max), and 25 minutes of seated rest during three consecutive sessions. Self-report of state anxiety was assessed 5 and 15 minutes before and after each session. Consistent with hypothesis, patients reported significant

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reductions in anxiety after both maximal and submaximal exercise testing. Importantly, these reductions were evident within 5 minutes following exercise. A much broader study of the efficacy of aerobic exercise for panic disorder was conducted by Broocks et al. (1998). These investigators examined the efficacy of aerobic exercise relative to clomipramine and pill placebo in a sample of patients with panic disorder (N = 46). Patients randomized to clomipramine were prescribed the medication following evidence-based guidelines. Patients in the aerobic exercise condition were medication-free and underwent a 10-week endurance training program. Specifically, patients were asked to find a four-mile route (forest or park) that was easily accessible from their home, and complete this entire route at least three times a week, where walking was allowed during the first six weeks, and running was expected during the last four weeks. Patients also met with a trainer once each week to run together. Exercise led to significantly more benefit than placebo treatment at week 10, and clomipramine yielded significantly greater effects compared to placebo after four weeks. At posttreatment, both active treatments outperformed the placebo condition and were equally effective in reducing anxiety. Additionally, clomipramine yielded greater changes in global improvement ratings compared to aerobic exercise. In discussing the magnitude of the effects observed for exercise in their study, Broocks et al. (1998) hypothesized that additional cognitive interventions would have enhanced the benefits among participants in the exercise condition. Specifically, therapists could have assisted patients in preparing to reappraise some of the feared consequences of exercise-induced sensations. This type of preparation could have potentially prevented avoidance of more intense exercise that was evident in a subset of the patients (Broocks et al., 1998). The findings reported by Broocks and colleagues (1998) comport well with an earlier report (Martinsen, Hoffart, & Solberg, 1989). Martinsen et al. (1998) randomly assigned in-patient participants with panic disorder with agoraphobia (n = 56), social phobia (n = 13), or generalized anxiety disorder (n = 10) to either an aerobic or non-aerobic exercise treatment program. Both programs were conducted in group format, were eight weeks in length, and involved three weekly one-hour sessions, of which thirty minutes were devoted to exercise. The aerobic program involved walking or running at 70% of maximal aerobic capacity, whereas the intensity of the anaerobic program, which comprised muscular strength training, was unspecified. The study attrition rate was 11% and involved only panic disorder patients (n= 9) in the aerobic exercise condition. Although aerobic exercise was associated with greater improvements in physical fitness, both conditions showed comparable significant pre- to post treatment improvements on interviewer and self-report measures of anxiety. Based on these results, the authors concluded that exercise programs are effective for reducing pathological anxiety and that this effect cannot be accounted for by enhanced cardiorespiratory fitness. Initial feasibility data also supports the application of exercise to obsessivecompulsive disorder (OCD). Brown and colleagues (Brown et al., 2007) recently

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completed an open trial of an exercise intervention with 15 patients who were also on a stable dose of cognitive-behavioral treatment, pharmacotherapy, or their combination. The exercise intervention involved a combination of supervised and home-based aerobic exercise at 55 to 69% of age predicted maximal heart rates. Over the course of the 12-week protocol, participants progressed from 20-minute to 40-minute sessions three to four times a week. Prior to each supervised group session, participants participated in a 30-minute meeting with a clinical psychologist and an exercise physiologist to discuss topics related to compliance with the intervention program (e.g., benefits of exercise, goal setting, identifying and overcoming barriers to exercise). Compliance was further stimulated by providing monetary remuneration for adherence. The Cohen’s d effect size for reductions in Y-BOCS scores was d = 1.69 from pre- to posttreatment, and d = 1.11 for pretreatment to 6-month follow-up. Moreover, clinically meaningful changes were observed for 69% and 50% of patients at posttreatment and 6-month follow up, respectively. The initial successes of the application of exercise interventions to the treatment of clinical anxiety problems encourage a more in-depth study of the feasibility and efficacy of exercise protocols for patients with anxiety disorders. In addition to large-scale randomized controlled trials, these efforts should include investigations of the mechanism underlying the effects of exercise on anxiety.

Mechanisms of Exercise Anxiolysis There is little research on the mechanism by which exercise exerts its ameliorative effects on anxiety. In this section, we will discuss several proposed physiological and psychological mechanisms of exercise anxiolysis for which there is some preliminary supporting evidence.

Central Neurotransmitter Function Several animal studies have demonstrated that physical activity results in alterations in many neural systems that are also presumed to underlie the reductions in depression and anxiety with pharmacological treatments. For example, increased release of serotonin has been observed in animals both during (Wilson & Marsden, 1996) and following treadmill running (Dunn & Dishman, 1991; Meeusen & De Meirleir, 1995). Based upon other animal studies showing that physical activity leads to increased serotonin metabolism (Broocks, Schweiger, & Pirke, 1991; Chaouloff, 1997), Broocks and colleagues (Broocks et al., 1999; Broocks et al., 2001; Broocks et al., 2003) posited that physical activity may result in down-regulation of postsynaptic serotonin

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receptors, and specifically the 5-HT2C receptors. In a first study to test this hypothesis, they compared marathon runners to sedentary controls on their responses to meta-chlorophenylpiperazine (m-CPP), a 5-HT agonist that produces anxiogenic symptoms via 5-HT2C receptors (Broocks et al., 1999). Marathon runners showed a diminished cortisol response to m-CPP, providing evidence consistent with the idea that chronic exercise results in a reduced hormonal reaction to m-CPP mediated by postsynaptic 5-HT2C receptors. In a second study, the authors (Broocks et al., 2001) found that untrained participants show a similar blunted cortisol response to m-CPP following a 10-week aerobic exercise program of moderate intensity. The authors concluded that these data collectively suggest that the anxiolytic effects of exercise may be mediated by the downregulation of 5-HT2C receptors. The efficacy of benzodiazepines for reducing anxiety forms the basis of research examining the potential of exercise on -aminobutyric acid (GABA) function. Studies suggest that measuring the amount of time a rat spends in an open field (open field locomotion) with or without treadmill exercise is a useful animal model for studying the anxiolytic effects of exercise (Dishman, Armstrong, Delp, Graham, & Dunn, 1988; Morgan, Olson, & Pedersen, 1982; Royce, 1977). Injections of GABA into the nucleus accumbens septi (NAS) reduces open field locomotion and injections of a GABA antagonist into the NAS increases locomotion in rats (Jones & Mogenson, 1980a; Jones & Mogenson, 1980b; Jones, Mogenson, & Wu, 1981). Since exercise also increases open field locomotion in rats (Tharp & Carson, 1975); (Weber & Lee, 1968), Dishman and colleagues (1996) have posited that exercise may reduce anxiety by the downregulation of GABAa receptor density in the corpus striatum. Consistent with this hypothesis, they found that voluntary exercise in rats increased open field locomotion with a corresponding GABAa downregulation (Dishman et al., 1996). Human studies are needed to test the hypothesis that exercise anxiolysis in humans can be accounted for by GABAa downregulation or other changes in central neurotransmitter function.

Sleep Restoration Improved sleep as a proposed mechanism of change first emerged with the delayed onset hypothesis, or the observation that antidepressant drugs rapidly change plasma levels and sleep parameters (48–72 hours), and that corresponding mood and anxiety changes in the weeks following (Chen, 1979; Ehlers, Havstad, & Kupfer, 1996; Hyttel, 1994; Kupfer et al., 1994; Shipley et al., 1984). There is also evidence that pharmacologic treatment of sleep symptoms improves depression outcomes (Fava et al., 2006). Moreover, several studies have now shown that exercise training programs are associated with significant improvements in self-reported sleep quality (King, Oman, Brassington, Bliwise, & Haskell, 1997; Singh, Clements, & Fiatarone, 1997). Interestingly, some

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findings converge to suggest that changes in slow wave sleep (SWS), which occurs during restorative stages 3 and 4 of the sleep cycle, may be particularly relevant to the anxiolysis following exercise. Specifically, reduced SWS is ubiquitous among anxiety disorder sufferers (Arriaga & Paiva, 1990; Arriaga et al., 1996; Bourdet & Goldenberg, 1994; Fuller, Waters, Binks, & Anderson, 1997) and exercise appears to enhance SWS (Horne, 1981; Shapiro, Griesel, Bartel, & Jooste, 1975). There is some controversy with respect to the mechanism underlying the effects of exercise on SWS. Some studies suggest that it may be the elevation in body temperature created by exercise that may be responsible for sleep effects (Atkinson & Davenne, 2006; Horne & Moore, 1985; Horne & Shackell, 1987; Horne & Staff, 1983). However, other studies show that low intensity activity without a corresponding increase in body temperature can also increase SWS (Naylor et al., 2000). Also, well-controlled studies show that the anxiolytic effects of acute exercise are not solely due to body temperature (Youngstedt, Dishman, Cureton, & Peacock, 1993).

Cognitive Refocusing and Self-efficacy There is some evidence suggesting that exercise may exerts its effect on anxiety by enhancing perceived coping ability. Steptoe and colleagues (Moses, Steptoe, Mathews, & Edwards, 1989) observed parallel decreases in perceived coping and anxiety in anxious individuals who initiated an exercise program. Similarly, Bodin and Martinsen (2004) found that exercise that targeted self-efficacy (e.g., 45 minutes of martial arts) corresponded with significantly greater improvements in positive affect and state anxiety compared to exercise that did not target self-efficacy (e.g., 45 minutes of stationary bike exercise). As an alternative to enhanced self-efficacy, some have suggested that physical exercise may only serve as distraction from ruminations, worries, and anxiety (Bahrke & Morgan, 1978; Leith, 1994). Interestingly, Goode and Roth (1993) found that it is not distraction per se but the content of the distraction techniques in which people engage that is associated with changes in emotional well-being. They found that that runners who focused on nonassociative thoughts (those not related to exercising) showed less fatigue and in some cases decreases in tension and anxiety, compared to runners who focused on associative thoughts (monitoring the body and the exercise itself).

Exposure Recently, Stathopoulou and colleagues (2006) proposed that, among other effects, exercise may exert positive effects on mental health by teaching persistence in the presence of negative somatic or emotional states. Indeed, the modification of some of the self-perpetuating patterns in affective disorder

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(e.g., social withdrawal and inaction in response to feelings of depression, and avoidance in response to feelings of anxiety), by facilitation of adaptive pursuit of goals regardless of the presence of aversive thoughts or emotions, is increasingly being discussed as a general feature of adaptive change in therapy (Barlow, Allen, & Choate, 2004). Accordingly, by training persistence with exercise, despite the presence of the physical and emotional symptoms of exertion, exercise interventions may have more general effects on returning participants to adaptive activity. As we discussed above, this persistence in the presence of symptoms may take on special meaning in the case of panic disorder. We discussed exercise, with its induced array of symptoms that are similar to many of the symptoms of anxious arousal, as a form of interoceptive exposure – exposure to the somatic symptoms of anxiety under controlled circumstances. As suggested by the research to date, inclusion of specific preparation and cognitive coaching for the symptoms to be induced both mimics typical interoceptive exposure procedures used in cognitive behavior therapy (Smits et al., 2007) and appears to lead to more optimal outcomes for exercise interventions (Smits et al., 2005; Broocks et al., 1998).

Conclusions and Future Directions The application of exercise interventions to clinical anxiety is in the early stages of development, but the few trials completed to date, as well as the wealth of evidence for the effects of exercise on non-clinical anxiety, encourage further study. Although most work to date has been completed with persons suffering from panic disorder, preliminary findings with respect to the mechanisms of exercise anxiolysis suggest that exercise of may also offer significant benefits for those suffering from other forms of anxiety psychopathology. This hypothesis awaits testing in large-scale randomized controlled trials. The development of exercise interventions for the anxiety disorders will likely benefit from studies focused on identifying intervention parameters critical to efficacy of exercise. There is evidence from the depression literature suggesting that high intensity exercise provides superior results compared to lower intensity exercise. For example, Dunn and associates (Dunn, Trivedi, Kampert, Clark, & Chambliss, 2005) reported that the public health recommended dose of aerobic exercise (total energy expenditure of 17.5 kcal/kg/week) was more effective in reducing depression relative to low dose aerobic exercise (total energy expenditure 7.0 kcal/kg/week) or flexibility exercise. A public health dose of exercise has also yielded reductions in depressive symptom severity and improvements in quality of life in a preliminary study of exercise augmentation to antidepressant treatment (Trivedi, Greer, Grannemann, Chambliss et al., 2006a) and is currently being investigated in the context of a larger randomized controlled trial (Trivedi, Greer, Grannemann, Church et al.,

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2006b). Other elements of exercise dose that warrant further study are intensity and duration. In addition to exercise dose, it is important to determine the relative importance of exercise type. There is currently a paucity of available data on the effects of anaerobic exercise (resistance training) for anxiety. Findings from the depression literature indicate that resistance training may be equally effective compared to aerobic activity in reducing symptoms of depression (e.g., Doyne et al., 1987; Martinsen et al., 1989). Support for the use of anaerobic exercise for depression was further strengthened by a recent study completed by Singh and colleagues (Singh et al., 2005). They demonstrated that high intensity progressive resistance training (PRT) (80% maximum load) was more effective in treating depression than lower intensity PRT (20% maximum load). Perhaps more important was the finding that the effects of PRT on depression reduction were accounted for by expectancy in the low intensity condition but not in the high intensity condition, suggesting that anaerobic exercise, when prescribed at the higher doses, offers more than a placebo effect. An important implication of these findings is that resistance training may be an alternative for patients for whom aerobic activity may be inappropriate or for those who do not have the initial motivation for aerobic activity. When examining the utility of new interventions, it is important consider issues related to effectiveness in addition to efficacy. It remains to be seen how exercise is best integrated within provider networks. Within specialty care, exercise interventions may emerge as another adjunctive clinical tool that has the advantage of providing a broad spectrum of health benefits in addition to its benefits on mental health (Stathopoulou et al., 2006). In primary care, exercise may emerge as a more fundamental intervention that can be prescribed by the primary care physician or provider team. Specifically, exercise has a potential for targeting many mental and physical health problems simultaneously. In this application, exercise is likely to bring with it all the challenges of any health promotion intervention. Adherence to exercise recommendations has been low in the United States (Schoenborn, Adams, Barnes, Vickerie, & Schiller, 2004); although there is some evidence suggesting that exercise for mental health benefits may fare better than when prescribed for improving physical health. The use of exercise interventions for anxiety disorders has one clear advantage over exercise for general health promotion. Unlike exercise interventions that are prescribed for the prevention of health problems, exercise interventions for treating anxiety disorders are linked with immediate benefits (i.e., acute bouts of exercise are associated with significant changes in anxiety). As reported by Christensen-Szalanski and Northcraft (1985), adherence to recommended health behavior changes is greater when there is direct symptom reduction that is linked with the behavior change. There also appears to be wide acceptance of nontraditional treatment strategies for mental health among individuals suffering from mood and anxiety disorders (Kessler et al., 2001). Indeed, exercise interventions have the potential of avoiding the social stigma associated with other mental health interventions (Sirey et al., 2001). Although

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these data are encouraging, systematic research on issues related to the dissemination and adoption of exercise interventions for the anxiety disorders is needed. From a public health perspective, examining the potential role for physical activity interventions in the prevention of anxiety pathology may be as important as determining its effectiveness for the treatment of anxiety disorders. Certainly, growing evidence for the efficacy of exercise for reducing anxiety sensitivity indicate promise for exercise interventions for preventing panic-related pathology (Schmidt, Lerew, & Jackson, 1997; Schmidt, Lerew, & Jackson, 1999; Wilson & Hayward, 2005). However, there is a need for studies that clarify the role of physical (in)activity in the development of anxiety pathology. When testing the direction of this relationship, it is important to consider the potential interplay between physical activity and other established risk factors of anxiety pathology as well as the potential moderating effects of gender (Stephens, 1988). In this context, it may also be important to assess other health factors (e.g., fitness, nutrition, substance use, sleep) that have shown to be linked to physical activity (Aaron, Dearwater, Anderson, & Olsen, 1995). Similarly, the importance of investigating the impact of exercise on psychosocial function and quality of life should be underscored. Impaired psychosocial function is associated with increased risk of recurrence of anxiety disorders (Rodriguez, Bruce, Pagano, & Keller, 2005), and these symptoms must therefore be addressed in addition to primary symptoms in order to fully manage the anxiety disorders. Finally, we have limited the discussion in this chapter to a unidirectional model. It should be noted, however, that the evidence to date may point to a more complex relationship between physical activity and anxiety and panic psychopathology. Of particular importance to public health would be the investigation of the potential impact of anxiety and mood problems on the adoption and maintenance of physical activity.

References Aaron, D., Dearwater, S., Anderson, R., & Olsen, T. (1995). Physical activity and the initiation of high-risk health behaviors in adolescents. Medicine & Science in Sports & Exercise, 27(12), 1639–1645. Adams, P. F., & Schoenborn, C. A. (2006). Health behaviors of adults: United States, 2002–04. National Center for Health Statistics. Vital Health Statistics, 10, 20, 1–140. American College of Sports Medicine. (2005). ACSM’s guidelines for exercise testing and prescription (6th ed). Philadelphia, PA: Lippincott Williams, & Wilkins. American College of Sports Medicine. (2006). ACSM’s Advanced exercise physiology. Baltimore: Lippincott Williams & Wilkins. Arriaga, F., & Paiva, T. (1990). Clinical and EEG sleep changes in primary dysthymia and generalized anxiety: A comparison with normal controls. Neuropsychobiology, 24(3), 109–114.

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Anxiety and Insomnia Theoretical Relationship and Future Research Thomas W. Uhde and Bernadette M. Cortese

Introduction The major focus of this chapter is to identify future research directions for advancing knowledge about two phenomena, anxiety and insomnia, which are highly prevalent, co-existent problems in humans. Despite this universal observation across different cultures, the medical field has a poor understanding of the pathophysiology and causal relationships between anxiety and insomnia. The physiological and neurobiological relationships between anxiety and insomnia remain one of medicine’s mysteries. Given the prominence and relevance of these co-occurring complaints among individuals seeking medical care, the lack of research is somewhat surprising and may be a by-product of conceptualizing anxiety and insomnia as simply nonspecific manifestations of most systemic diseases. Such attributions impede the development of new treatments that can improve appreciably the health and well-being of not only patients with primary insomnia and anxiety disorders but also individuals with cancer, metabolic, and other multi-system medical diseases. The goal of this chapter is to encourage clinicians and investigators to think about anxiety-insomnia from different theoretical, even highly speculative perspectives, with the hope that new areas of research will be undertaken by the research community. We understand that some ideas regarding future research directions are not necessarily logical ‘‘next step’’ studies, but rather, areas of high-risk investigation that in their own right (and in the opinion of the authors) may lead to an improved, understanding of the anxiety-insomnia coupling.

Thomas W. Uhde Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina (MUSC), 67 President Street, 5 South, Charleston, SC

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Definitions Anxiety and insomnia are multidimensional phenomena that largely rely on impairment criteria to achieve status as a disorder. There are two primary classification systems used by clinicians for the diagnosis of anxiety and sleep disorders: Diagnostic and Statistical Manual (DSM-IV) and Tenth Revision of the International Classification of Diseases (ICD-10). While the Diagnostic and Statistical Manual subdivides the anxiety disorders into a number of subtypes, the essential feature of the anxiety disorders is impairment in work or social function or ongoing distress as a result of the condition. For the purposes of this chapter, unless otherwise indicated by reference to a specific anxiety disorder (e.g. panic disorder), we are referring to the overall category of the anxiety disorders. For the purposes of this chapter (and consistent with the conceptualization of most sleep experts), insomnia refers to the subjective experience of having restless and un-refreshing sleep, including difficulty falling asleep, multiple nocturnal awakenings, or early morning waking. Later in this chapter, we make specific distinctions between the subjective experience of insomnia and absolute sleep restriction (i.e. insufficient amount of objective EEG sleep). The rationale for underscoring this point is that there may be a large gap between subjective experiences of sleep duration versus objective criteria of the hours of sleep per night or sleep efficiency (i.e. the percent of time in bed when the person is actually sleeping). In fact, a characteristic of many individuals suffering from insomnia may be the lack of objective evidence of profound restricted sleep by either polysomnography or multiple sleep latency testing (MSLT), despite the perception of having had little or no sleep. Thus, for the purposes of this chapter, insomnia refers to a subjective experience of poor quality of sleep, which may or may not be associated with an actual decrease in the normal amounts of sleep.

Theoretical Models The high prevalence of co-morbid insomnia in primary anxiety disorders and co-morbid anxiety symptoms in primary insomnia suggest an important underlying relationship between these clinical entities. However, using cross-sectional methods, it is also known that anxiety symptoms, including the cognitive process of worry, and insomnia are not 100% co-existent in all phases of illness in either patients with primary insomnia or any primary anxiety disorder. These observations can be explained on the basis of three theoretical constructs: a) anxiety (or a diagnostic subtype) and primary insomnia represent a single, spectrum disorder with a common diathesis (and predictable evolution of symptoms) (see Fig. 1); b) anxiety and insomnia are separate and distinct pathological conditions, each of which cause, permit, or promote the downstream development of secondary complications (Fig. 2) and c) anxiety and insomnia are each caused by another critical, independent factor (Fig. 3). Each

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Fig. 1 In the single spectrum disorder model, anxiety (or a diagnostic subtype) and insomnia represent the same disorder with a common diathesis and predictable evolution of symptoms. In this model, the common underlying pathological process (i.e., neurobiological abnormality) leads to different symptoms or components (e.g. anxiety or insomnia) of the illness

Fig. 2 In the different disorders with secondary complications model, anxiety and insomnia are separate and distinct pathological conditions with different underlying neurobiological abnormalities. Early stages of the disorder may reflect this distinction, while later stages show increasingly similar symptoms (e.g. anxiety and insomnia) due to the downstream development of secondary complications

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Fig. 3 In the third factor model, anxiety and insomnia are each caused by a critical, independent factor(s) that separately influences each disorder. These third or ‘‘other’’ factors might be psychosocial/environmental, endogenous/neurobiological or familial/genetic in nature, or possibly involve contributions from any or all of these elements

of these theoretical models might explain high co-morbid rates of insomnia and anxiety observed in patients seeking treatment for an anxiety disorder or primary insomnia.

What criteria would support a single (spectrum) versus different disorders versus third factor models for anxiety and insomnia? A. Single-Spectrum Disorder: In a single-spectrum disorder model, there is really just one underlying neurobiological disorder that is characterized by modest variations in clinical presentation. If anxiety (or one of its diagnostic subtypes) and insomnia are the same basic disorder, one should be able to document identical pathological mechanisms or neurobiological abnormalities in each of the two clinical syndromes. Thus, either the anxiety or an anxiety diagnostic subtype (e.g. panic disorder) and insomnia syndromes would share common neurobiological abnormalities. A medical analog of a single-spectrum disorder might be multiple sclerosis, wherein a common underlying pathological process (e.g. demyelization) leads to different symptoms at different phases of illness (Fig. 1). In terms of investigating whether two apparently different clinical syndromes (i.e. anxiety and insomnia) actually represent a single disease entity, one would study and expect to find similar ages of onset of illness, gender distributions, type of symptoms, course of illness, and response to treatment for the two candidate conditions. One would also predict that cultural, education, and related expectancy biases might largely contribute to whether people with the ‘‘same’’ disorder identified themselves as having a ‘‘sleep’’ versus ‘‘anxiety’’ problem. The single-spectrum disorder theory, therefore, suggests that ‘‘insomnia’’ and ‘‘anxiety’’ (or one or more diagnostic subtypes of anxiety) are the same single-spectrum disorder and that non-biological, socio-cultural factors largely determine whether patients self-identify themselves as having an anxiety or sleep disorder.

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B. Different Disorders: In contrast to a single-spectrum disorder, distinctly different disorders would have different underlying abnormalities and be highly likely to reflect dissimilarities in onset and course of illness, medical complications and treatment response. However, depending on the underlying diathesis or etiology of illness, one might anticipate downstream complications that result in overlapping clinical symptoms. If these are truly different disease entities, the initial presentation and associated clinical features would be different. Nonetheless, two different diseases could be associated with increasingly similar symptoms during later stages of illness insofar as secondary complications might recruit common neuro-anatomical substrates or neurobiological systems. Thus, either anxiety or a diagnostic anxiety subtype and insomnia might each increase the likelihood of developing secondary complications, which, when the initial and secondary complications are taken together, produce similar clinical profiles. A medical disease analog might be hypertension leading to impaired renal function which would share many of the same symptoms as primary renal disease associated with secondary hypertension (Fig. 2). To explain high rates of co-morbid anxiety and insomnia wherein each (i.e. anxiety and insomnia) are fundamentally different disorders would suggest that we could identify two syndromes: a) patients presenting with initial insomnia followed by the development of pathological anxiety (or one of its diagnostic subtypes) and b) patients that present initially with anxiety or an anxiety disorder subtypes which is later associated with insomnia. Furthermore, one would predict different (particularly early in the course of illness) but overlapping (especially in later stages of illness) neurobiological abnormalities in the anxiety-insomnia versus insomnia-anxiety syndromes. Moreover, one would predict that these two syndromes would have differential responses to treatment, as well as dissimilarities in age of onset and other demographic variables. C. Third Factor Models: High co- morbid rates of anxiety and insomnia could also be explained on the basis of an unknown third factor or factors that have a direct but independent impact on anxiety and insomnia. In this circumstance, third factor(s) would be necessary or contributory but insufficient alone to produce anxiety and insomnia. Like the single-spectrum and separate diagnoses models, the third factors model could explain high co-rates of insomnia and anxiety, respectively, in people seeking treatment in mental health (or an anxiety subspecialty program) versus sleep medicine clinics. These third or ‘‘other’’ factors might be psychosocial/environmental, endogenous/neurobiological or familial/genetic in nature, or possibly involve contributions from any or all of these elements (Fig. 3). An example of an exogenous-external factor that has an impact on two separate medical but co-morbidly associated disorders is ultraviolet light/sun exposure. Data suggest a higher than expected association between patients with subacute cutaneous lupus erythematosus (SCLE) and polymorphous light eruption (PLE) (Millard, Lewis et al., 2001; Millard, Kondeatis et al.,

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2001). Although thought to be different medical conditions, both are made more evident or severe by sun exposure. Still other third factors (e.g. genetic polymorphisms) (Millard, Kondeatis et al., 2001) may contribute to the co-morbid associations of SCLE and PLE, as has been similarly proposed for apolipoprotein E gene polymorphism in patients with high HDL-cholesterol levels and dermatophystosis (Tursen et al., 2004). Likewise, hypercholesterolemia can be conceptualized as playing a third factor role in the co-morbid association of cardiovascular disease and type 2 diabetes. Such third factors might be hypothesized for insomnia and anxiety disorders, wherein each is a truly separate neurobiological disease entity but both suffer an exacerbation of severity due to external factors (e.g. sleep deprivation) or, in fact, might even share a common genetic polymorphism. If third factor(s) are contributing to the high prevalence of co-morbid anxiety and insomnia, we should be able to identify differences in course of illness and treatment responses in direct relation to the degree to which that outside ‘‘third’’ factor distinctly and separately influences the essential qualities of anxiety and insomnia. It should be noted that an outside factor may affect different components (e.g. symptoms, severity) of anxiety versus insomnia, although the impact of the third factor should have a consistent, predictable, and identifiable role in explaining one or more common and critical feature(s) of anxiety and insomnia.

What Evidence Supports a Single (Spectrum) Versus Different Disorders Versus Third Factor Models for Anxiety and Insomnia? A. Age: Age of onset could help to distinguish anxiety and insomnia as separate and distinct disorders if it was found to be considerably different for these two disorders. Recent data from the World Mental Health Survey (WMH) describes an early age of onset for some anxiety disorders, with a later onset for others. For example, phobias and separation anxiety disorder was found to have a median age of onset in the range of 7–14 years (interquartile range [IQR] = 4–20 years). The age of onset distributions for panic, generalized anxiety, and posttraumatic disorders, on the other hand, ranged from 25 to 53 years (IQR = 15–75 years; Kessler et al., 2007). The NCS-R median age of 11 for the onset for anxiety reported by Kessler et al. (2005) and a 7 year (IQR = 7 years) median age of onset for a first anxiety disorder reported by Johnson, Roth, and Breslau (2006) are consistent with the WMH results and further demonstrate the early age of onset for anxiety. With respect to insomnia, the evidence supports the view that older individuals are most at risk (Morphy, Dunn, Lewis, Boardman, & Croft, 2007). In fact, several studies reveal that nearly half of individuals over the age of 65 report sleeping difficulties and insomnia-like symptoms (Monane, 1992; Foley et al., 1995; Ganguli, Reynolds, & Gilby, 1996).

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Fewer studies have specifically assessed the age of onset for insomnia. In one retrospective analysis of adolescents from the ages 13 to 15 years, Johnson et al. (2006) reported a median age of onset for insomnia at age 11 (IQR = 5 years). Although this study found a relatively young age of onset for children identified specifically with insomnia, most other studies with children assess individuals with unspecified sleep problems that includes insomnia, but could also include numerous other difficulties surrounding sleep (Paavonen, Solantaus, Almqvist, & Aronen, 2003; Gregory & O’Connor, 2002; Johnson, Chilcoat, & Breslau, 2000), making it difficult to draw clear conclusions about age of onset for insomnia. B. Gender: A second factor that could distinguish anxiety and insomnia as a single spectrum disorder versus two separate disorders is gender distribution. With respect to both insomnia and anxiety, data suggest a similar gender distribution for these two disorders. Anxiety, for example, is nearly twice as prevalent in women as in men (Kessler et al., 1994, 2005). Although not as consistent as the anxiety data, most studies report higher prevalence rates for females than males, with female gender as a strong risk factor for insomnia (Ford & Kamerow, 1989; Mellinger, Balter, & Uhlenhuth, 1985; Bixler, Vgontzas, Lin, Vela-Bueno, & Kales, 2002; Zhang & Wing, 2006). C. Symptoms and Sleep EEG: Insomnia, as a subjective sleep complaint, is reported by many patients with anxiety disorders. The report of insomnia is so prevalent among patients with anxiety disorders that it is widely assumed among clinicians, and even by most anxiety disorder specialists, that the treatment of core anxiety symptoms in anxiety disorder patients will be associated with parallel improvement in sleep quality (see discussion). Some anxiety disorders, however, appear to be more commonly associated with insomnia and two specific anxiety disorders, panic disorder and generalized anxiety disorder, deserve special mention insofar as they appear to share important but different symptom characteristics compared with patients with primary insomnia. Patients with generalized anxiety disorder often have subjective complaints that are nearly identical to those reported by patients with primary insomnia. These include worrying about obtaining good quality or sufficient amounts of sleep and problems falling or maintaining sleep. Patients with primary insomnia, essentially by operational criteria, report almost identical sleep complaints, but, for reasons that remain unclear, experience their complaints within the context of a sleep problem, rather than within the context of a mental health problem. Patients with GAD and primary insomnia typically report symptoms of physiological hyperarousal and increased vigilance (‘‘feeling keyed up’’) with intermittent fatigue and disturbances in concentration and memory. There are also nearly identical polysomnographic findings; sleep architecture and REM measures are normal whereas both syndromes have EEG evidence of increased sleep latency and disturbances in maintaining sleep (for reviews, see Papadimitriou & Linikowski, 2005; Uhde, 2000).

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Of interest, patients with GAD, when awakened under experimental conditions after several minutes of EEG-documented stage 2 sleep, report not having been asleep or experiencing any drowsiness whatsoever. These observations, combined with our ongoing studies in patients with recurrent sleep paralysis indicate that some individuals find it nearly impossible to distinguish between awake and sleep states, including REM-stage sleep. We have reported that patients with recurrent sleep paralysis, as well as some patients with GAD and PD (especially those with nocturnal panic attacks) find it difficult to separate at the experiential level the difference between sleep versus wakeful states (Uhde et al., 2006). Thus, the study of sleep in patients with primary insomnia, as well as patients with selective anxiety disorders and recurrent sleep paralysis may be of interest to neuroscientists investigating the neurobiological and theoretical basis of consciousness. In fact, the impressive degree of self-awareness reported by patients with recurrent sleep paralysis during sleep has been described by our research team as ‘‘consciousness intruding upon REM stage sleep’’ or as ‘‘sleep consciousness’’ (Uhde et al., 2006). Taken together, these observations suggest that GAD and panic disorder, particularly patients with nocturnal panic attacks, share many symptomatic and sleep EEG characteristics with chronic insomnia sufferers. On the other hand, certain other anxiety disorders such as social phobia (Brown, Black, & Uhde, 1994) can be easily distinguished from chronic insomnia on a number of clinical and physiological criteria (for review, see Uhde, 2000), largely based on the absence of either impressive clinical or EEG findings. D. Course: Anxiety and insomnia are, in many cases, both disabling and chronic conditions that put a significant number of individuals with these disorders at risk for developing secondary complications. The high co-morbidity between anxiety and insomnia suggests a strong relationship between the two but information on the temporal relationship is lacking. Some research on insomnia and anxiety has assessed the longitudinal course of illness in relation to each other. The findings, however, are limited and inconsistent, with important questions remaining as to whether insomnia typically precedes anxiety or if insomnia more often develops subsequent to anxiety. 1. Insomnia, with secondary anxiety. Some findings suggest that anxiety symptoms/disorders can develop from primary insomnia. For example, longitudinal data from the National Institute of Mental Health Epidemiologic Catchment Area Study (ECA) revealed that adults with uncomplicated insomnia (i.e., defined as insomnia without the lifetime presence of a psychiatric disorder) at baseline were 5 times more likely to experience a panic attack in addition to being at a significant increased risk for developing panic disorder by a follow-up interview, one year later, compared to individuals without baseline insomnia or a psychiatric disorder (Weissman, Greenwald, Nin˜o-Murcia, & Dement,

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1997). Breslau, Roth, Rosenthal, and Andreski (1996) also found that a history of insomnia increased the risk for developing anxiety compared to individuals with no history of insomnia (OR=1.97, 95% CI 1.08–3.60). 2. Anxiety, with secondary insomnia. Other evidence supports the course of illness progression from primary anxiety to secondary insomnia. Ohayon and Roth (2003) retrospectively assessed the temporal relationship between insomnia and anxiety in a large, multinational European, general population study. In this study, current severe insomnia was the strongest predictor of a past psychiatric history (OR=5.8, 95% CI 2.4–14.0). Further evidence demonstrating an illness progression from anxiety to insomnia included the finding that the onset of insomnia preceded the development of anxiety in only 18% of the cases, while the onset of anxiety preceded the insomnia in more than 43% of the cases. In another retrospective analysis of a community-based sample of adolescents from the ages 13 to 15 years, Johnson et al. (2006) sought to assess the directionality of association between insomnia and psychiatric disorders including anxiety and depression. This study reported a high prevalence rate of insomnia in individuals with a history of anxiety that varied between 24% and 43% depending on the specific anxiety disorder. Additionally in 73% of the individuals that were co-morbid for anxiety and insomnia, the anxiety disorder preceded the onset of the insomnia. Risk associated with either anxiety or insomnia by the prior onset of the other disorder was also assessed to evaluate directionality. This analysis revealed that a prior anxiety disorder increased the risk of subsequent insomnia more than 3 fold, but that prior insomnia was unrelated to the later development of an anxiety disorder. E. Neuroanatomy & Pharmacology: Any attempt to examine the relationship between anxiety and insomnia should consider the neuroanatomical substrates and related neurotransmitter-neuromodulatory receptor systems that mediate wake versus sleep states, keeping in mind that ‘‘alarm’’ mechanisms are likely to influence both wakefulness and sleep. This is based on observations that states of fear (Uhde 2000) can take place during sleep and wakefulness. Neither insomnia nor anxiety, therefore, necessarily reflect disturbances in those neurobiological systems that mediate either wakefulness or sleep per se. In fact, neuroreceptor-neurotransmitters that mediate alarm functions might represent a third factor that contributes to the high co-morbidity of chronic insomnia in many anxiety disorders (see Fig. 3). Keeping these theoretical constructs in mind, we briefly review the neuroanatomy of wakefulness-promotion and sleep-promotion in relation to those neurotransmitter and neuropharmacological systems most commonly implicated in anxiety and insomnia. 1. Wakefulness-Promotion versus Sleep-Promotion Wakefulness is mediated in part by midbrain and pontine-acetyl cholinergic, pontine locus ceruleus-noradrenergic, reticular formation system

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(superior)-sertonergic, and posterior hypothalamus (tuberomammillary nucleus)-histaminergic systems whereas sleep-promotion is linked to anterior hypothalamus (ventrolateral preoptic nucleus) and reticular formation (caudal)-GABAergic systems. 2. Anxiety and Insomnia Many of the substrates implicated in sleep- or wakefulness-promotion also have been implicated in either anxiety or insomnia or both. The noradrenergic, GABAergic and serotonergic systems have been particularly associated in the pathophysiology or treatment of both anxiety and insomnia. a) Noradrenergic: Anatomy: The pontine nucleus locus ceruleus (LC) plays a key role in arousal and vigilance in animals and disturbances in this nucleus or its neuronal projections such as the amygdala and related limbic substrates, and nucleus accumbens have been implicated in panic disorder, GAD, PTSD and insomnia (Abelson, Khan, Liberzon, & Young, 2007; Alttoa, Eller, Herm, Rinken, & Harro, 2007; Charney & Redmond, 1983; Charney et al., 1990; DeViva, Zayfert, & Mellman, 2004; Sullivan, Coplan, Kent, & Gorman, 1999; Uhde & Singareddy, 2002). The locus ceruleus likely mediates its wakefulness-promoting effects, and possibly insomnia, via a number of actions including direct activation of the cortex and pedunculopontine tegmental nucleus and inhibitory inputs to the ventral lateral preoptic nucleus (VLPO), a galanin-related structure implicated in insomnia associated with aging (Gaus, Strecker, Tate, Parker, & Saper, 2002). Drug Action: Clonidine, an 2 adrenergic agonist, has short-term but not long-term anti-anxiety actions (Uhde et al., 1989), which theoretically parallels the inhibition and then tolerance to clonidine’s direct application via iontophoresis onto the LC in animals. Likewise, it is likely that the sedating and anti-anxiety effects of other 2 adrenergic agonists such as dexmedetomidine and lofexidine are mediated via locus ceruleus inhibition. Similarly, the 1 adrenergic antagonist, prasozin, has been recently reported to have beneficial effects in the treatment of the hyper-arousal, anxiety, and sleep-related problems in PTSD, including insomnia and nightmares (Raskind et al., 2003). b) GABAergic: Anatomy: The neurotransmitter pathway most widely implicated in both anxiety and insomnia is the GABAergic-benzodiazepine-chloride (GBC) system, with the ionotropic GABAA receptor that regulates chloride channels being particularly relevant for the biological functions of alarm, arousal and sedation. The role of the GABAergic system in animal fear is well-established (Zorumski & Isenberg, 1991). Alterations in GABAergic receptor function also are linked to arousal states, involving the full-range of

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sedation-drowsiness to alertness-hypervigilence and alarm states in humans. However, there is no known specific or final common pathway disturbance known to be associated with insomnia, anxiety or any anxiety disorder. Extrapolating from observations largely obtained in panic disorder patients using flumazenil, a pure benzodiazepine-receptor antagonist, there are few consistent data to support the idea that pathological anxiety states are directly mediated by either an excess or deficiency, respectively, of an endogenous benzodiazepine inverse agonist or pure agonist (Coupland, Bell, Potokar, Dorkins, & Nutt, 2000; Nutt et al., 1990). It remains possible, however, that disturbances in benzodiazepine receptor distribution, location or sensitivity or secondary GABAergic influences could play a role in the pathophysiology of anxiety or insomnia (Kalueff & Nutt, 1997; Kaschka, Feistel, & Ebert, 1995; Malizia et al., 1998; Mohler, Fritschy, & Rudolph, 2002; Mohler, Fritschy, Vogt, Crestani, & Rudolph, 2005). Consistent with this notion are prevalent decreases in flumazenil and iomazenil binding throughout the brains of panic and generalized anxiety disorder patients, respectively, as well as decreases in the fear-associated and anxiety-linked orbitofrontal cortex, amygdala and hippocampus regions (Malizia et al., 1998, Tiihonen et al., 1997). Of interest, Buhr and coworkers (2002) recently reported a mutation in the b3 subunit of the GABAA receptor in a person with chronic insomnia from a family with sleep problems. Unfortunately, there was no comprehensive information provided, or available, on the specific qualities of insomnia or anxiety within the individual or family. Nonetheless, these observations, combined with separate lines of evidence in rodents and humans suggest that the GABAA receptors, perhaps particularly 1, 2, 3, and b3 subunits, may play a partial role in the pathophysiology and treatment of insomnia and co-morbid anxiety symptoms (Laposky, Homanics, Baile, & Mendelson, 2001; Mohler et al., 2002, 2005; Rowlett, Cook, Duke, & Platt, 2005; Rush, 1998). It is theoretically possible that some co-morbid anxiety-insomnia syndromes have particular relevance to a specific GABAA subunit(s), although developing such a specific animal co-morbidity model will be a major challenge. Drug Action: Many drugs with direct or indirect actions at the GABAergic-benzodiazepine-chloride (GBC) receptor complex have short-term sedating, sleep-promoting and anti-anxiety profiles. Barbiturates, alcohol, benzodiazepines, and anesthetic agents, which act at different sites of the GBC receptor complex, have both sedating and subjective anxiety-reducing effects in humans, although the behavioral effects of barbiturates, alcohol, and anesthetic agents in patients who meet contemporary DSM-IV diagnostic criteria for anxiety or sleep disorders have not been thoroughly examined. Propofol, an

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anesthetic agent with GABAA receptor actions, is often reported by subjects undergoing colonoscopy to produce the equivalent of a ‘‘fullnight’s restful’’ and restorative sleep (author observations). Traditional hypnotic benzodiazepine drugs such as flurazepam, estazolam, temazepam, triazolam and quazepam, which have FDA indications for the short-term treatment of insomnia, produce anxiolysis but are generally considered impractical for such off-label use due to short half-life pharmacokinetics. Benzodiazepine hypnotics administered to patients with insomnia as target symptoms have been shown to improve insomnia as well as reduce co-morbid daytime anxiety (Fontaine, Beaudry, Le Morvan, Beauclair, & Chouinard, 1990) and improve a sense of physical well-being (Roth, Walsh, Krystal, Wessel, & Roehrs, 2005). It is widely appreciated among clinicians that benzodiazepine compounds and so-called Z drugs reduce anxiety and subjective insomnia. These observations are consistent with the notion that anxiety and insomnia share overlapping neuroanatomical substrates, at least in terms therapeutic response patterns to drugs that act at the GBC receptor complex. These observations, however, contribute to the possible misperception that a critical, or even requisite, ingredient of drug-mediated anxiolysis and especially sleep-promotion is the induction of drowsiness or sedation. Drug properties of drowsiness and sedation may not only be unnecessary for the effective treatment of anxiety or insomnia or co-morbid anxiety-insomnia conditions, but, theoretically may actually reduce the overall effectiveness of sedating drugs in the treatment of selective anxiety disorders, which require vigilance to monitor threat during sleep (Singareddy, Uhde, & Commissaris, 2006). c) Serotonergic: Anatomy: The reticular formation has long been associated with functions of wakefulness. Moruzzi and Magoun (1949) conducted studies demonstrating that the transection of the reticular formation above the pons in the face of intact sensory inputs to higher brain regions are associated with behavior and EEG patterns consistent with sleep, whereas lesions of the reticular formation below the pons are associated with a reduction in sleep. These classic studies and subsequent research indicate that different neural networks within and impinging onto the reticular formation mediate wakefulness and arousal functions, including serotonergic projections and activation of 5HT2A receptors at the level of the cerebral cortex and possibly hypothalamus. The serotonergic receptor system is strongly implicated in fearful animal behaviors and human anxiety disorders, particularly panic and obsessive-compulsive disorders (for review, see Uhde & Singareddy, 2002). Knock-outs of 5-HT1A receptors are associated with increased fear behaviors in animal models including, but not limited to, the elevated plus maze and foot shock (Heisler et al., 1998), forced swim (Ramboz et

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al., 1998), and open field (Parks, Robinson, Sibille, Shenk, & Toth, 1998) tests. In humans, fenfluramine, a 5-HT releasing agent, induces both anxiety and increases in blood cortisol. Of interest, over-activity of the hypothalamic-pituitary-adrenal (HPA) axis is associated with some types of severe insomnia (for review, see Roth, Roehrs, & Pies, 2007). Drug Action: Similar to benzodiazepines, selective serotonin reuptake inhibitors (SSRI) are widely used by clinicians to treat most of the anxiety disorders. And, trazodone, a tetracylic SSRI with 5-HT2 antagonist effects, may be the most frequently prescribed medication for the treatment of insomnia by psychiatrists and primary care physicians. There are limited data regarding the secondary improvement in insomnia following the targeted treatment of anxiety (or vice versa). It is known that older patients with anxiety disorders (60 years of age with mainly GAD) show decreased change scores on the Pittsburgh Sleep Quality Index (PSQI), suggesting that quality of sleep improves after the targeted treatment of anxiety in elderly patients (Blank et al., 2006). Not all anxiety disorders (e.g. PTSD), however, show convergent and parallel improvements in anxiety symptoms and insomnia (or sleep efficiency on polysomnography) when treated with SSRI’s; moreover, responses to some SSRI’s may be either ineffective or actually induce insomnia in PTSD, people with primary insomnia or healthy subjects (Davis, Frazier, Williford, & Newell, 2006; Winokur et al., 2001). Thus, while the SSRI’s play a crucial role in the treatment of many anxiety disorders, including those wherein sleep problems are a core feature, the effects of these same agents on the treatment of insomnia appear to be less predictable. F. Other ‘‘Third’’ Factors: An important question that remains to be answered is whether sleep deprivation is a contributing factor to insomnia and/or anxiety. Contrary to popular belief, there is a lack of good evidence for significant sleep loss in insomnia. Despite the fact that insufficient sleep is a hallmark feature of insomnia, there is little data demonstrating actual sleep loss or sleep restriction in individuals reporting insomnia. Sleep polysomnography (PSG) documents this lack of relationship between subjective reports of insomnia and objective measures of poor sleep including reduced sleep time. In general, individuals with insomnia underestimate sleep time compared to actual sleep time recorded by PSG. For example, Rosa and Bonnet (2000) reported no relationship between the subjective experience of insomnia and poor EEG sleep, defined by increased sleep latency or decreased efficiency. Specifically, chronic insomniacs reported significantly worse laboratory sleep compared to controls, while objective EEG-assessed sleep revealed little difference between the groups. Means, Edinger, Glenn, and Fins (2003) who also assessed individuals with insomnia and compared them to normal sleepers corroborate the findings of Rosa and Bonnet (2000) and go further to describe that insomniacs show a wide range of sleep misperception, from considerable underestimation to both

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accurate and overestimation of sleep time. In all, these studies suggest that insomnia is a complex condition associated with factors that extend beyond reduced sleep time. Recent findings from our anxiety, stress and trauma laboratory also suggest a difference between subjective reports of sleep duration (i.e., sleep quantity) and subjective experience of sleep quality. We administered the Pittsburgh Sleep Quality Index (PSQI) to a small group of individuals with motor vehicle accident-related PTSD. The PSQI is a widely used, valid and reliable instrument designed to measure sleep disturbance through seven components including sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, use of sleeping medications, and daytime dysfunction (Buysse, Reynolds, Monk, Berman, & Kupfer, 1989). To achieve a pure score for sleep quality (i.e., score that excludes sleep quantity) we eliminated the two components of the sleep efficiency domain (i.e., sleep duration and habitual sleep efficiency) from the overall PSQI score (Cole et al., 2006). We then correlated this modified score (i.e., sleep quality) with subjective reports of average sleep duration (i.e., amount of sleep in minutes) and found no relationship between these two variables (r = 0.20; F1,26=1.04, p=0.32). Our findings in this small group of anxious individuals demonstrate an apparent distinction between sleep quantity and quality and suggest that individuals suffering from anxiety who report poor sleep may not have a reduction in sleep duration (i.e., restriction/deprivation). Although limited data exists concerning the effects of sleep deprivation on insomnia and anxiety, the available evidence suggests that sleep deprivation or restriction could have opposing effects on insomnia or anxiety, findings that support a clear distinction between these 2 disorders. On one hand, sleep deprivation/restriction has shown positive results in people with insomnia, while no consistent benefits have been shown for sleep deprivation in individuals diagnosed with anxiety. Specifically, sleep deprivation is associated with an increase in anxiety symptoms in healthy individuals and has been shown to worsen anxiety in patients with some but not all anxiety disorders. Roy-Byrne, Uhde, and Post (1986) assessed depression and anxiety levels after one night of total sleep deprivation in patients with panic disorder who were not currently depressed. Individual responses of panic patients to sleep deprivation varied, with a subset of panic patients (7/12 [58%]) demonstrating a worsening of anxiety and 4 of the 12 panic patients (33%) experiencing a spontaneous panic attack the day following the sleep deprivation procedure. Labbate et al. (1997) also assessed the effects of sleep deprivation on anxiety and reported a worsening of anxiety symptoms after sleep deprivation in a small sample of panic (n=5) patients. In this study, 3 of the 5 panic patients experienced at least one panic attack the morning after sleep deprivation, while none of the control subjects experienced sleep deprivation-induced panic. With respect to other anxiety subtypes, one night of sleep deprivation revealed inconsistent, and for some negative, effects in patients with primary OCD (Joffe & Swinson,

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1988; Labbate et al., 1997), social phobia (SP) and generalized anxiety disorder (GAD; Labbate et al., 1998). Several studies describe the positive effects of sleep deprivation/ restriction on insomnia and suggest its potential utility in treating this disorder. In one study (Stepanski, Zorick, Roehrs, & Roth, 2000), sleepiness and total sleep time for primary insomniacs was significantly increased, compared to baseline, during the recovery night following one night of total sleep deprivation. In addition, post-deprivation sleep measures in the insomniacs were comparable to the age- and sex-matched normal sleeper controls.

Discussion Certainly, the collective data reviewed in the aforementioned sections argue against the idea that anxiety and insomnia are entirely separate disorders with distinctly different neurochemical disturbances. However, it is impossible without prospective studies, conducted in at-risk populations, to ascertain whether these neurobiological findings represent different phases of a common diathesis (Fig. 1), different disorders with coupled downstream abnormalities (Fig. 2), or the consequence(s) of unknown ‘‘other’’ endogenous and/or external/exogenous factors (Fig. 3). Given the prevalence of insomnia reported by patients with anxiety disorders (Brown & Uhde, 2003; Craske & Tsao, 2005; Hoehn-Saric, 1981; Mellman & Uhde, 1989, 1990; Saletu et al., 1997; Uhde, 2000), the portfolio of polysomnography and related sleep research studies in patients with anxiety disorders is fairly modest in number. The greatest amount of polysomnography and related sleep research has been conducted in panic disorder (PD), post-traumatic stress disorder (PTSD), generalized anxiety disorder (GAD) and, to a lesser extent, obsessive-compulsive disorder (OCD) (Dow, Kelsoe, & Gillin, 1996; Engdahl, Eberly, Hurwitz, Mahowald, & Blake, 2000; Hurwitz, Mahowald, Kuskowski, & Engdahl, 1988; Papadimitriou & Linkowski, 2005; Mellman, 1997; Ross et al., 1994; Sheikh, Woodward, & Leskin, 2003; Uhde et al., 1984; Uhde, 2000). While sleep disturbances are a ‘‘core’’ and distinguishing feature of PTSD, the anxiety disorders of GAD and PD, especially those patients with sleep-nocturnal panic attacks (Craske & Tsao, 2005; Cortese & Uhde, 2006; Mellman & Uhde, 1989), appear to share particularly poignant characteristics with primary insomnia patients in terms of symptomatology, co-morbidity, pharmacologic treatment response, and, sleep EEG measures. Because symptoms of ‘‘psychic distress’’, worry, difficulty concentrating, feelings of jitteriness, agitation, and muscle tension are almost universally reported in part or whole by patients with generalized anxiety disorder and primary insomnia, it is not surprising that GAD was found to be the most prevalent co-morbid anxiety

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disorder assessed in a large general population study of individuals with insomnia complaints (Ohayon, Caulet, & Lemoine, 1998). Taken together, these observations suggest that any attempt to further dissect the theoretical models in a prospective manner should give priority to the systematic investigation of patients with primary insomnia versus generalized anxiety disorder. The convergence of symptoms and their robust treatment response to benzodiazepines are particularly compelling from a clinical perspective. If GAD and primary insomnia represent different phases of the same disorder (Fig. 1) or different conditions whose neurobiology significantly converge over time (Fig. 2), one would predict that at later stages of illness both GAD and primary insomnia would respond favorably to not only the same pharmacologic treatments but also the same non-pharmacological interventions. Thus, one might predict that cognitive behavioral treatments specifically designed to target the cognitive distortions of worry would be useful in both syndromes. In an important preliminary investigation, Be´langer, Morin, Langlois and Ladouceur (2004) administered group CBT to GAD patients based on targeting GAD-related worries (Dugas & Ladouceur, 2000), wherein sleep complaints were not specifically addressed as part of the treatment. In this study, 86.5% of the GAD patients reported that they had never experienced insomnia without worry and the majority reported difficulties maintaining sleep; indeed, 25% reported suffering from all phases of insomnia (i.e. early, middle, and late). Additionally, group CBT was associated with a significant improvement on the Insomnia Severity Index (Morin, 1993). One cannot help but speculate that cultural or socioeconomic factors might largely influence whether one self-identifies anxiety-insomnia as a medical (i.e. sleep) versus mental health problem (i.e. anxiety), which in the case of GAD and primary insomnia might lead to the conclusion that major difference in primary insomnia versus GAD patients are mainly related to help-seeking strategies.

Future Research To validate any of the theoretical models, future research must investigate patients with primary insomnia and anxiety disorders using both cross-sectional and retrospective (Uhde, Boulenger, Roy-Byrne, Vittone, & Post, 1985) lifecharting as well as prospective methods. Prospective studies in patients whose initial presentation is anxiety versus insomnia or, in well-defined at-risk populations, would be particularly desirable. Assessment tools must be developed, validated and employed in a systematic fashion. The conduct of such studies will be particularly challenging due to pragmatic considerations, which will necessitate that such investigations be conducted across different institutional sites and specialty clinics (i.e. sleep medicine clinics versus anxiety disorder clinics). Ideally, it is desirable to conduct such studies within department(s) or

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institution(s), which have research expertise in both sleep and anxiety disorder research in order to minimize internal and external sources of variation. To investigate the convergent, co-morbid relationship between anxiety and insomnia, priority might be given to the study of patients who a) meet DSM-IV criteria for GAD plus seek treatment at anxiety disorder clinics versus b) patients meeting ICD-10 criteria for insomnia plus seek treatment from sleep clinics. Other than these entry criteria, we recommend that there be few, if any, exclusion criteria in designing such comparator studies. Specifically, we would not include or exclude on the basis of sleep misperception or, perhaps, even the degree or duration of subjective insomnia. Such differences or similarities across groups seeking treatment for anxiety versus insomnia might themselves be markers that distinguish group differences. A particular problem for clinicians is the lack of information on the impact of long-term pharmacological treatments or the comparative efficacy of drug versus cognitive behavioral interventions. Such studies are time-intensive but necessary to advance knowledge about the validity of any of the proposed three theoretical models but also to develop evidence-based treatment packages for the long-term treatment of anxiety-insomnia syndromes. Even more problematic is the lack of information on the course of anxiety and insomnia after treatment discontinuation. It is beyond the scope of this chapter to review and recommend the behavioral, physiological, and neuroimaging studies, which might be conducted to best characterize the relationship between insomnia and anxiety. Clearly, neuroimaging strategies would be useful, although current MRI, MRS and fMRI imaging strategies have resolution limitations that make it difficult to define with precision the neuroanatomical substrates and functional circuits underlying anxiety, insomnia, and mixed anxiety-insomnia syndromes. Nonetheless, the emerging field of sleep neuroimaging (Nofzinger, 2004) may ultimately provide tools for understanding fundamental constructs such as ‘‘time perception’’ or ‘‘sleep consciousness’’ (Uhde et al., 2006). Such hypothesized third factors (Fig. 3) might be amenable to investigation with imaging strategies, which are not conducive to examination with traditional polysomnography or even spectral analysis methods (Nofzinger et al., 1999, 2002, 2004). An examination of the comparator effects of sleep deprivation under laboratory-controlled conditions would be of interest to better differentiate the behavioral, cognitive, MSLT and neuroendocrine effects of sleep restriction. Likewise, caffeine is an ideal chemical model of anxiety (Lin, Uhde, Slate, & McCann, 1997; Uhde, 1995) and has been recently proposed as a tool to study primary insomnia (Drake, Jefferson, Roehrs, & Roth, 2006). Studying the behavioral (including sleep perception and polysomnographic measures), neuroendocrine, and physiological effects of caffeine in primary insomnia and GAD would provide useful information. Disturbances in hypothalamic-pituitary-adrenal axis function remain a focus of much anxiety (Uhde & Singareddy, 2002) and insomnia research (Drake, Roehrs, & Roth, 2003; Vgontzas & Chrousos, 2002); yet, the

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specific origin, maintenance, and neuroanatomical impact of putative glucocorticoid disturbances in the anxiety disorders and insomnia remain unknown. The most exciting area of future research is the theoretical possibility that designer drugs might be developed with non-sedating anxiolysis or, even, cognitive enhancing, pro-vigilance, anxiolytic properties. As reviewed elsewhere (Dawson, Collinson, & Atack, 2005; Mohler et al., 2002, 2005), the development of a compound that binds to 2 GABAA and/or 3 GABAA sites, which are located primarily in the fear-related substrates (i.e. amygdala) and cortex, but without binding to the sedation-associated 1 GABAA binding site, would theoretically have non-sedating anxiolytic properties. Such a drug would be particularly useful for patients who wish to maintain alertness or who experience increased anxiety as a result of increasing relaxation or sedation (e.g. patients with nocturnal panic attacks). Even more speculative, but equally provocative, is the idea that drugs with hypocretin agonist actions might also be useful in the treatment of nocturnal panic attacks or patients whose insomnia is related to a fear of sleeping (Uhde, 2000; Singareddy et al., 2006).

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Part II

Physical Conditions and Anxiety Disorders

Anxiety Disorders and Physical Illness Comorbidity: An Overview Tanya Sala, Brian J. Cox, and Jitender Sareen

Introduction There has been a considerable body of research exploring associations between physical illness and depressive disorders, but similar research examining a possible association of physical illness with anxiety disorders has lagged behind. More recently, research into the association of anxiety disorders with physical illness has also been expanding, prompted in part by large epidemiologic survey data revealing a high prevalence of anxiety disorders in community samples (Kessler et al., 2005). Some studies have reported an association with anxiety disorders as strong as or stronger than that with mood disorders (McWilliams, Cox, & Enns, 2003; McWilliams, Goodwin, & Cox, 2004; Von Korff et al., 2005). Some studies examining associations between anxiety disorders and specific illnesses, including thyroid disease, cancer, diabetes, cardiac disease, gastrointestinal disease, respiratory disease, and chronic pain, have found levels of anxiety disorders among patients seeking treatment for medical conditions to be higher than expected compared to the general population. Attempts to explore and clarify associations between anxiety disorders and physical disorders have focused on two main sources of data: clinical samples and community samples. Within these two broad categories, sample size and methodology of studies vary considerably. Many studies offer intriguing findings, but are challenging to interpret due to inconsistencies in nosological terminology, psychometric measurements, and methodology. This overview chapter is designed to be selective rather than exhaustive, and attempts to

Tanya Sala Department of Psychiatry, University of Manitoba. PsycHealth Centre, PZ430-771 Bannatyne Avenue, Winnipeg, MB, Canada, R3E 3N4, Tel: 204-787-7078, Fax: 204-787-4879 [email protected] Acknowledgements Dr. Sareen is supported by the Canadian Institutes of Health Research New Investigator Award. Dr. Cox is supported by the Canada Research Chair Award. The authors thank Natalie Mota for her assistance in manuscript preparation.

M. J. Zvolensky, J. A. Smits (eds.), Anxiety in Health Behaviors and Physical Illness. Ó Springer 2008

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focus on large epidemiologic and clinical studies where available in the existing literature. However, the relative lack of such studies mandates some consideration of research that falls outside these parameters. The majority of currently available studies in this area are cross-sectional in nature. To avoid unnecessary repetition, unless otherwise specified, all studies referred to are cross-sectional. The chapter is organized into sections for each anxiety disorder, with subsections by system of disease where warranted by available literature. For the purposes of this literature review, searches of PubMed and PsycInfo were performed using the general term anxiety disorder as well as each specific anxiety disorder (e.g. panic disorder), in combination with the general terms medical condition, physical illness, and medical illness as well as terms for individual systems of disease (e.g. cardiovascular). Searches included studies published from 1985 to 2007. For a discussion of associations between pain and anxiety disorders, please refer to the chapter by Asmundson et al.

Possible Explanations for Observed Relationships The cross-sectional design of the majority of existing studies of anxiety psychopathology and physical illness precludes any firm conclusions about the exact nature of the observed associations. However, if a true association exists, possible explanations can be understood within three basic types of relationships. Although intriguing, it must be emphasized that these relationships remain speculative and are not yet convincingly supported by empirical evidence. 1. Direct causal relationship – The presence of an anxiety disorder may directly increase the risk of suffering from a physical illness. For example, it has been postulated that chronically high levels of anxiety may produce changes in physiological functioning, which may in turn increase risk for physical illness (e.g. Kubzansky, Koenen, Spiro, Vokonas, & Sparrow, 2007). Conversely, the presence of a physical illness may directly increase the risk of having an anxiety disorder, a possibility explored in studies of asthma and anxiety disorders, especially panic disorder (e.g. Goodwin, Jacobi, & Thefeld, 2003; Goodwin & Pine, 2002). An interesting related concept is the model of mutual maintenance (Sharp & Harvey, 2001), which refers to the phenomenon of physical symptoms and anxiety symptoms each exacerbating and perpetuating the other. 2. Indirect causal relationship – An anxiety disorder may indirectly increase the risk of having a physical illness through some intermediate factor, such as smoking, obesity, physical exercise, or substance abuse. Alternatively, having a physical illness could indirectly increase the risk of suffering from an anxiety disorder, such as when the use of a particular medication has an adverse effect on anxiety symptoms. In individuals being treated for respiratory disease, use of bronchodilators has been suggested as a possible exacerbating factor for anxiety symptoms.

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3. Shared risk factors – There may be no causal relationship between anxiety disorders and physical illness. Rather, they may share risk factors, such as genetic, environmental (e.g. poverty), or personality characteristics. It is also possible, although unlikely, that the reported associations are not true associations, but the result of another process. Some studies have found anxiety disorders to be associated with high utilization of medical services (e.g. Calhoun, Bosworth, Grambow, Dudley, & Beckham, 2002; Hoge, Terhakopian, Castro, Messer, & Engel, 2007; Richardson, Elhai, & Pedlar, 2006). Increased frequency of medical attention, and possibly increased somatic complaints, may lead to increased detection of physical illness in individuals with anxiety disorders. This explanation may be particularly important to exclude for those physical illnesses that are typically asymptomatic in the early stages, such as Type II diabetes and hypertension. A possible link between anxiety disorders and health behaviors such as obesity (Simon et al., 2006), physical exercise, and smoking remains understudied. Although some studies have adjusted for health behaviors such as smoking (Sareen, Cox, Clara, & Asmundson, 2005), the majority of studies have not adjusted for important health behaviors. Given the well-known impact of lifestyle and health choices on risk for physical illness, this remains an issue for interpretive caution. However, debate exists about the utility of adjusting for relevant health behaviors. Some authors argue that if health behaviors are intermediate factors along a causal pathway, rather than confounding variables, these adjustments could potentially obscure an indirect causal relationship as described above.

Anxiety Symptoms in General Sareen et al. (2005) examined the relationship between anxiety disorders and a range of physical disorders in the US National Comorbidity Survey (NCS), a large nationally representative dataset. This study found that among respondents with one or more physical disorders, a comorbid anxiety disorder diagnosis was associated with an increased likelihood of disability even after adjusting for severity of pain, comorbid mood, and substance use disorders. Interestingly, adjusting for smoking did not affect these associations. Using German Health Survey data, Sareen et al. (2006) again examined these associations. Advantages of this study included both a large sample size and the fact that the presence of physical illness was based on physician assessment and not individual self-report, thus increasing reliability. Unfortunately, this study did not include PTSD. After adjusting for sociodemographic factors and other common mental disorders, the presence of an anxiety disorder was significantly associated with thyroid disease, respiratory disease, gastrointestinal disease, arthritis, migraine headaches, and allergic conditions. The presence of a comorbid anxiety disorder with one or more physical disorders was significantly

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associated with poor quality of life and disability in this study. Important clinical implications of these associations exist, including the possibility that the co-occurrence of physical disorders and anxiety disorders may confer a more disabling condition. Method of assessment of anxiety and physical illness varies considerably between studies. Some have assessed anxiety as a unified entity, rather than distinguishing amongst anxiety disorders (Anderson et al., 2002; Engum, 2007; Engum, Bjoro, Mykletun, & Dahl, 2002; Hermanns, Kulzer, Krichbaum, Kubiak, & Haak, 2005; Kruse, Schmitz, & Thefeld, 2003; Shaban, Fosbury, Kerr, & Cavan, 2006), adding to the challenge of interpretation and clinical application.

Posttraumatic Stress Disorder (PTSD) Editions of the Diagnostic and Statistical Manual of Mental Disorders (DSM) prior to the DSM-IV explicitly excluded life-threatening illness as a stressor that could be considered a traumatic precipitant of PTSD. With the publication of DSM-IV, individuals could receive a diagnosis of PTSD as a direct result of being traumatized by the experience of a life-threatening illness. This development has contributed to interest in the association between PTSD and physical illness. Much of the early work examining the co-occurrence of PTSD with physical disorders involved studies of war veterans. Higher scores on measures of posttraumatic stress symptoms have been linked with increased medical care utilization and lower ratings of general health (Calhoun et al., 2002; Hoge et al., 2007; Richardson et al., 2006). Frayne et al. (2004) reported that female veterans with PTSD had a greater number of physical illnesses and poorer physical health functioning than female veterans with either depression alone or neither diagnosis. Within the general population of the United States, Sareen et al. (2005) reported that, among DSM-IV anxiety disorders, PTSD had the greatest number of significant associations with chronic physical disorders, including neurological, cardiovascular, gastrointestinal, metabolic/autoimmune, and bone or joint conditions. A study of primary care patients found PTSD to be a stronger predictor of a reported number of medical problems than trauma history, physical injury, lifestyle factors, or comorbid depression (Weisberg et al., 2002). Studies have not been limited to adult populations. A descriptive epidemiologic case-control analysis of Medicaid service-use data in the United States found PTSD to be associated with adverse health outcomes in female children and adolescents (Seng, Graham-Bermann, Clark, McCarthy, & Ronis, 2005), and significant associations with PTSD were found across a wide range of disease categories. The importance of PTSD diagnosis as a predictor of having

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a physical illness appeared to increase with age. Studies of different ethnic groups have also identified PTSD as being significantly associated with cardiovascular disease, even after controlling for major depression and traditional cardiovascular risk factors including age, sex, education, diabetes, high blood pressure, and smoking (Sawchuk et al., 2005). Efforts to understand the biological pathways through which PTSD and physical illness might be linked have included examination of the hypothalamic-pituitary-adrenal and sympathetic-adrenal-medullary axes. Findings of lower cortisol, higher catecholamine levels, and increased circulating T-lymphocytes in individuals with PTSD support the possibility of biological underpinnings (e.g. Yehuda et al., 1995).

Cardiovascular Disease A link between PTSD or trauma and cardiovascular disease has been suggested by a number of studies. A recent prospective study of community-dwelling US military veterans found a significant association between PTSD symptoms at baseline and subsequent development of coronary heart disease, even after controlling for depressive symptoms (Kubzansky et al., 2007). A study of Korean War and World War II veterans reported increased rates of physician-diagnosed cardiovascular disease among veterans with PTSD (Schnurr, Spiro, & Paris, 2000). Studies demonstrating increases in basal cardiovascular activity in PTSD sufferers offer a potential biological pathway (Buckley & Kaloupek, 2001). One important possible consequence of PTSD secondary to a medical condition or medical treatment is the potential for lower levels of adherence to medical treatment. Shemesh et al. (2001, 2004, 2006) examined the hypothesis that symptoms of MI-related PTSD were linked to nonadherence to medical follow-up. The authors hypothesized that patients who experience myocardial infarction as a traumatic event may not take medications as prescribed, with nonadherence representing part of the avoidance dimension of PTSD. In these studies, PTSD symptoms were significantly associated with nonadherence to medical treatment. In support of these findings, others have reported that alleviation of PTSD symptoms in a series of burn patients could improve adherence to treatment (Countermanche & Robinow, 1989).

Neurological Disease A number of studies have sought to determine whether PTSD diagnosis is associated with psychogenic nonepileptic seizure (PNES), also referred to as pseudoseizure and psychogenic seizure. Fiszman, Alves-Leon, Nunes, D’Andrea, and Figueira (2004) recently conducted a review of studies on the

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prevalence of traumatic events and/or PTSD in patients with PNES. Among the 17 studies included in this review, ten analyzed the PTSD diagnosis in PNES patients. Although the prevalence rates reported in these ten studies varied considerably, rates of PTSD were consistently higher than those found in the general population. However, when compared with control groups who had epilepsy, only two studies found a significant difference in rates of PTSD. Limitations acknowledged by the authors include the fact that all 17 studies were hospital-based, and many had small sample sizes. The authors speculate that PNES, which has been traditionally thought of as a dissociative phenomenon, might be understood as a severe form of PTSD that includes prominent dissociative features. There is currently too little information to warrant conclusions on this premise.

Endocrine/Metabolic/Autoimmune Disease Among the significant associations with PTSD in the study by Sareen et al. (2005), metabolic/autoimmune conditions showed the most robust association (AOR 3.32, CI 1.96-5.62). A number of studies have supported an alteration in thyroid function in individuals with PTSD, both in chronic combat-related PTSD (Mason et al., 2004; Wang & Mason, 1999; Wang et al., 1995) and in survivors of childhood sexual abuse (Friedman, Wang, Jalowiec, McHugo, & McDonagh-Coyle, 2005). In both studies by Wang et al., alterations in thyroid function were specifically associated with increased hyperarousal symptoms. Through promotion of ongoing noradrenergic transmission, elevations in triiodothyronine (T3) have been proposed by some authors as a possible underlying biological mechanism perpetuating arousal features in PTSD (Prange, 1999), although this hypothesis remains speculative at this stage. Using data from a large national sample of Vietnam veterans, Boscarino (2004) tested the hypothesis that chronic sufferers of PTSD may be at increased risk for certain autoimmune diseases, including rheumatoid arthritis, thyroid disease, insulin-dependent diabetes, and psoriasis. After adjusting for a variety of factors, including age, alcohol and drug abuse, and history of cigarette smoking, the authors noted significant associations between chronic PTSD and all the above-mentioned illnesses. In a large study of US male veterans with diabetes, Trief, Ouimette, Wade, Shanahan, and Weinstock (2006) noted significantly higher cholesterol, LDL, weight, and BMI in subjects with PTSD and depression, compared to depression alone, PTSD alone, or neither. Goodwin and Davidson (2005), using the NCS dataset, examined the association between self-reported diabetes and PTSD in a community sample of adults. In this study, self-reported diabetes was found to be significantly associated with an increased likelihood of PTSD, but not with an increased likelihood of any other mental disorder. This study not only provides evidence for

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generalizability of previous findings to adults in the community, it also suggests some specificity for the association with PTSD compared to other mental disorders.

Cancer The majority of studies assessing incidence or prevalence of PTSD in individuals with cancer have involved cross-sectional assessment of individuals with breast cancer following completion of primary treatment, and have reported rates ranging from 0 to 32% (e.g. Andrykowski, Cordova, Studts, & Miller, 1998). Several studies (Andrykowski, Cordova, McGrath, Sloan, & Kenady, 2000; Mehnert & Koch, 2007) also included a longitudinal component in the form of either a 12 or 6-month follow-up assessment for PTSD. Analysis of data from a large US community sample (Honda & Goodwin, 2004) found no significant association between cancer and PTSD. A variety of factors have been reported to be predictive of PTSD in individuals with cancer, including increased emotional distress following diagnosis, female gender, a history of negative life stressors, prior psychological disturbance, lower socioeconomic status, poor social support, and reduced physical functioning (e.g. Jacobsen et al., 2002). Some have reported an association between more severe PTSD symptoms and a more advanced stage of disease (Jacobsen et al., 1998), while other studies have found no association between medical variables of the illness and risk of PTSD (Alter et al., 1996; Green et al., 1998). With respect to the predictive value of any specific medical variable, studies have been mixed. In summary, challenges exist in the interpretation of existing PTSD literature, one of which is the predominance of cross-sectional methodology in evaluating associations of PTSD with physical illnesses. Research examining PTSD related to discrete trauma may not generalize to the experience of a significant physical illness. Clarifying the precise event or events that represent trauma can be difficult but clinically relevant, as some evidence exists that prolonged or multiple traumatic events may result in greater severity or chronicity of PTSD symptoms. The relative contributions of the diagnosis itself, treatment, side effects, prognosis, disrupted physical, social and occupational functioning, and risk of exacerbation or recurrence cannot be examined within a cross-sectional design. Diagnostic validity using current DSM-IV criteria also presents special challenges in this population. Divergent definitions of the stressor may increase variability in the diagnosis of PTSD in the context of physical illness. The utility of specific symptoms within DSM-IV criteria for PTSD needs to be assessed in this population. For example, ‘‘sense of a foreshortened future’’ may be a realistic concern in individuals with more serious physical illnesses such as cancer. Arousal symptoms may overlap considerably with side effects of

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treatment. PTSD also needs to be distinguished from reactive stress to ongoing medical issues, or a grief reaction when the diagnosis is a terminal or significantly disabling illness. There is good evidence supporting cognitive-behavior therapy (CBT) for treatment of PTSD. However, solid research supporting CBT for treatment of PTSD co-occurring with physical illness is lacking. The relative benefits of cognitive vs. behavioral components of CBT may also vary in this population.

Panic Disorder (PD) Adding to the complexity of the relationship between panic disorder and physical illness, both for individuals suffering from these disorders and for the professionals who provide them with care, is the high degree of overlap between symptoms of panic and certain physical illnesses, particularly cardiac and respiratory disease.

Cardiovascular Disease Given the high level of symptom overlap, it is not surprising that an association between panic disorder and cardiac disease has been relatively well studied. Of the 13 symptoms of a panic attack listed in DSM-IV, many could also represent cardiovascular disease. Many patients with panic disorder present first to the emergency room requesting medical assessment (Huffman & Pollack, 2003). Data from the NIMH ECA study suggested that individuals who present with numerous medically unexplained symptoms have 200 times increased odds of having panic disorder, compared with 17 for major depression (Simon & Von Korff, 1991). A strong relationship has been reported between panic attacks and hypertension diagnosed by physical exam in a primary care sample (Davies et al., 1999). Similarly, myocardial infarction has been associated in at least two studies with increased likelihood of new-onset panic attacks. Physiological mechanisms such as decreased heart rate variability, increased platelet activity, and increased sympathetic tone have been implicated in the relationship between anxiety and cardiac disease (Kawachi, Sparrow, Vokonas, & Weiss, 1995). In a retrospective study of a large random community sample, Weissman, Markowitz, Ouellette, Greenwald, and Kahn (1990) examined the association between PD and cardiovascular/cerebrovascular disorders. After adjusting for a number of demographic factors, participants with PD were at higher risk of reporting high blood pressure, heart attack, and stroke than a group of respondents with no psychiatric disorder, but when compared with other psychiatric disorders, only stroke remained significant. One limitation of this study is that existence of cardiovascular or cerebrovascular disease was based on self-report.

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Kawachi et al. (1994) reported on a prospective study of phobic anxiety and the risk of coronary artery disease (CAD) in a sample of 34,000 male health professionals. Although not a DSM-IV disorder, phobic anxiety likely most closely resembles panic symptoms, and these findings are therefore discussed here. Subjects were initially free of cardiovascular disease at baseline. A significant difference was found in the age-adjusted relative risk of fatal coronary artery disease when groups with the highest and lowest anxiety scores were compared. The excess risk was confined to sudden death. A more recent prospective study examined the relationship between phobic anxiety and coronary artery disease among women participating in the Nurses’ Health Study over 12 years of follow-up (Albert, Chae, Rexrode, Manson, & Kawachi, 2005). In this sample of over 72,000 women with no history of cardiac disease at baseline, a higher anxiety score was associated with an increased risk of sudden cardiac death and fatal coronary artery disease, but not of nonfatal MI. After adjusting for possible intermediaries (hypertension, diabetes, and elevated cholesterol), only a trend toward increased risk persisted for sudden cardiac death.

Respiratory Disease Chronic obstructive pulmonary disease (COPD) and asthma are featured most prominently in the literature, although a smaller number of studies examine an association between panic disorder and allergic reactions in both children and adults (Goodwin, 2002; Kovalenko et al., 2001). As with cardiovascular disease, the high level of symptom overlap presents unique challenges in understanding repeatedly observed associations. Given the early age of onset of asthma, many have speculated that it could be a contributor to the development of panic disorder, although there is evidence supporting a bidirectional influence of the disorders (Hasler et al., 2005), as well as studies questioning whether both may be due to a third variable (Goodwin, Fergusson, & Horwood, 2004). Lifetime rates of respiratory disease have been reported to be as high as 47% in individuals with panic disorder (Zandbergen et al., 1991). Rates of panic disorder in individuals with respiratory illness have also been found to be increased above those reported in general population studies, not only within clinical samples of adults, but also in community samples and within child and adolescent populations (Goodwin & Eaton, 2003; Goodwin, Jacobi, et al., 2003; Goodwin, Olfson, et al., 2003; Goodwin, Pine, & Hoven, 2003). In a community sample of more than 4000 individuals with current severe asthma, 10% also had panic disorder (Goodwin, Jacobi, et al., 2003). Using the NCS dataset, Sareen et al. (2005) did not find a relationship between panic attacks and respiratory disease, as previous studies have reported (Goodwin & Eaton, 2003; Goodwin, Jacobi, et al., 2003; Goodwin et al., 2003; Goodwin, Pine, et al., 2003; Ortega, McQuaid, Canino, Goodwin, & Fritz, 2004). A possible explanation suggested by the authors is that the discrepancy

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may be related to severity. The NCS did not distinguish severity of physical disorders, but in a German community sample, severe asthma diagnosed by a physician was associated with panic attacks while non-severe asthma was not (Goodwin, Jacobi, et al., 2003). Special considerations arise in the treatment of comorbid asthma and panic disorder. Treatments for asthma, in particular short-acting b2 agonists, may exacerbate anxiety symptoms as a side effect of their use, presenting a dilemma both for the individual and health care provider. If symptoms are attributed to asthma and a short-acting b2 agonist is used, symptoms may worsen if related to panic rather than respiratory causes. Some evidence exists that patients with comorbid panic disorder and asthma may make greater use of short-acting b2 agonists than asthma-only patients, independent of pulmonary function, asthma medication class, and sociodemographic status (Feldman, Lehrer, Borson, Hallstrand, & Siddique, 2005). Several studies have reported an increased risk of panic disorder in individuals with COPD (e.g. Karajgi, Rifkin, Doddi, & Kolli, 1990). A recent review by Brenes (2003) noted consistently increased rates of panic disorder and GAD across studies, but commented on the lack of evidence to guide treatment decisions in this population.

Neurological Disease Studies examining associations with neurological illness have focused mainly on epilepsy or vestibular dysfunction. The majority of those involving epilepsy have concentrated on the diagnostic challenges in differentiating partial seizure epilepsy involving pre-ictal or ictal fear from panic attacks or panic disorder, and available literature is limited mainly to case reports (e.g. Bernik, Corregiari, & Braun, 2002; Thompson, Duncan, & Smith, 2000). Some authors have speculated on the existence of a subgroup of panic attacks, in which panic constitutes symptoms of simple partial seizures with primarily psychic content (Alvarez-Silva, Alvarez-Rodriguez, Perez-Echeverria, & Alvarez-Silva, 2006). Patients with partial seizures may have symptoms similar to panic attacks – prodromal tension, fear, and autonomic disturbances, including changes in blood pressure, heart rate, and skin color. This category of overlap once again highlights the importance of treatment providers maintaining an index of suspicion to rule out physical illness as an etiologic factor in the presentation of anxiety symptoms. Possible indications for neurological investigations include atypical symptoms or age at onset, non-response to standard treatments, abnormalities in routine physical exam or laboratory investigations, or family history. With respect to vestibular dysfunction, a two-year prospective study examining the role of cognitions in the development of panic disorder after the experience of vestibular neuritis (Godemann, Schabowska, Naetebusch,

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Heinz, & Strohle, 2006) reported that although fear arising on the first day of an acute vestibular episode did not predict the development of panic, fear of vertigo one week after the dysfunction was a significant predictor. After six weeks, persistent fear of vertigo remained a significant predictor. Results of a small clinical study suggested that subclinical vestibular dysfunction might contribute to symptoms of panic disorder, (Jacob, Furman, Durrant, & Turner, 1996). Although the majority of studies assessing vestibular function in individuals with panic disorder report a high prevalence of abnormal results of vestibular testing, no consistent pattern of vestibular dysfunction has been observed across studies. Similarly, although results of studies examining psychiatric symptoms in patients with vestibular dysfunction in general show increased levels of anxiety symptoms, especially panic, no consistent pattern of association has yet been described.

Gastrointestinal (GI) Disease The majority of studies within this system of disease have focused on associations of anxiety disorders with ‘‘Functional’’ GI symptoms. Functional refers to symptoms reported by an individual that do not correlate to any tissue pathology detectable by medical testing. In a nationally representative survey of over 13,000 individuals in the United States, Lydiard et al. (1994) found that individuals with panic disorder had the highest rate of unexplained GI symptoms (7.2%) compared with other diagnostic categories. Respondents who reported two gastrointestinal symptoms had significantly higher lifetime prevalence rates for panic disorder and agoraphobia than those who reported no GI symptoms. In patients with severe irritable bowel syndrome (IBS), panic disorder has been associated with impaired functioning (Creed et al., 2005). In a longitudinal study of a representative cohort of Swiss adults by Hochstrasser and Angst (1996), subjects were assessed for functional GI symptoms and anxiety and depressive disorders. Cross-sectionally, a significant relationship was found between functional GI complaints and panic disorder, subthreshold panic disorder, agoraphobia, social phobia, simple phobia, and GAD. However, those who reported functional GI complaints at younger ages were not at increased risk for subsequent development of an anxiety disorder. The authors concluded that functional gastrointestinal complaints reflect a non-specific concomitant vegetative disturbance associated with anxiety disorders, not a risk factor for the development of a specific anxiety disorder. Data from a large-scale, nationally representative sample of Japanese subjects was analyzed for comorbidity of IBS with panic disorder and agoraphobia (Kumano et al., 2004). Significantly higher rates of PD and agoraphobia were observed in subjects with IBS than in

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non-IBS subjects. Although IBS was more prevalent in females, comorbidity did not differ between males and females.

Endocrine/Metabolic Disease Within this category, thyroid disease and diabetes have received the most attention from researchers. A recent review of studies examining associations between thyroid dysfunction and anxiety disorders found significantly elevated rates for panic disorder in patients with a history of thyroid disease, and concluded that inquiring about thyroid symptoms and screening for thyroid disease is warranted in patients with panic disorder (Simon et al., 2002). However, of the 12 studies included in this review, only six were controlled, and the findings of studies varied considerably. Results from larger studies have been mixed. Analyzing a community sample, Sareen et al. (2005) did not find an association between panic attacks and self-reported diagnosis of metabolic/endocrine disease. Analysis of a different community sample also did not find a significant association between panic disorder/agoraphobia and self-reported thyroid disease (Patten, Williams, Esposito, & Beck, 2006). However, analysis of a large clinical sample showed an association between panic disorder and thyroid disease (Rogers et al., 1994).

Cancer A review of studies between 1980 and 1994 examining psychological disturbances in cancer patients (van’t Spijker, Trijsburg, & Duivenvoorden, 1997) found no significant differences from the general population with respect to anxiety and psychological distress. In fact, in comparison with other medical patients, cancer patients showed significantly less anxiety in this review. In contrast, Honda and Goodwin (2004) used NCS data to examine the association between cancer and mental disorders, adjusting for sociodemographic characteristics. Among other reported findings, cancer was associated with increased risk of agoraphobia, although this finding barely reached statistical significance. There was no significant association in this study with panic disorder. The findings of Honda and Goodwin have been criticized on a number of grounds (Coyne & Palmer, 2005), including the low prevalence of cancer diagnosis in the NCS (n=45, 0.76%), making it possible for small sampling biases to have large effects. It has also been suggested that diagnoses made in the NCS may have been less valid when a significant medical comorbidity was present, as distinguishing between psychiatric symptoms and physical symptoms could pose an even greater challenge for lay interviewers than clinicians.

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Generalized Anxiety Disorder (GAD) Cardiovascular Disease Barger and Sydeman (2005), using data from a large US community sample of adults aged 25–74, found that independently of depression, subjects with GAD were more likely to have coronary artery disease risk factors, as measured by self-reported smoking status, body mass index, and recent medication use for hypertension, hypercholesterolemia, and diabetes.

Gastrointestinal Disease Goodwin and Stein (2002) examined a possible link between GAD and peptic ulcer disease (PUD) among adults in a community sample. After controlling for differences in sociodemographic characteristics, psychiatric comorbidity, and physical comorbidity, the authors found a significantly increased risk of self-reported PUD in subjects with GAD. A dose-response relationship was also found between number of GAD symptoms and higher likelihood of PUD. A review of a number of smaller studies (Lydiard, 2001) reported a consistent link between irritable bowel syndrome and GAD. In the NCS sample, Sareen et al. (2005) found GAD to be associated exclusively with gastrointestinal disease after adjusting for sociodemographic factors, other anxiety disorders, and depression. See the section on Panic Disorder and gastrointestinal disease for discussion of a relevant study by Hochstrasser and Angst (1996).

Endocrine/Metabolic/Autoimmune Disease Studies of this body system have primarily examined associations with either thyroid disease or diabetes mellitus. In a small study of a clinical sample, Carta et al. (2005) found that subjects with Hashimoto disease showed higher frequencies of GAD compared to subjects with euthyroid goiter and controls. See the section on Panic Disorder and endocrine/metabolic disease for discussion of a relevant review by Simon et al. (2002). Studies in clinical samples have also supported an association between GAD and diabetes (Kovacs, Goldston, Obrosky, & Bonar, 1997). However, both studies of diabetes and studies of thyroid disease typically involve smaller numbers of individuals and are subject to the sampling bias that accompanies studies of treatment-seeking populations. In a recent review of anxiety in adults with diabetes (Grigsby, Anderson, Freedland, Clouse, & Lustman, 2002), the authors concluded that 14% of diabetic subjects in the included studies also had GAD, well in excess of the prevalence reported in community surveys (Kessler, Chui, Demler,

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Merikangas, & Walters 2005). However, of the 18 studies included in this review, only 5 included a non-diabetic control group, and most of the subjects were drawn from clinical populations. In contrast, an analysis of general population data (Sareen et al., 2005) found no significant association between metabolic/endocrine or autoimmune diseases and GAD.

Obsessive-Compulsive Disorder (OCD) The bulk of the research exploring a link between obsessive-compulsive disorder and physical illness has focused on a possible etiologic link between Group A b-Hemolytic Streptococcus (GABHS) and the onset and subsequent exacerbations of OCD. Allen, Leonard, and Swedo (1995) published an early description of cases in which the onset of obsessive-compulsive symptoms and tics appeared to follow streptococcal infection. Based on the first 50 cases described, Swedo et al. (1998) defined five inclusion criteria for this postulated subgroup of OCD cases, referred to as PANDAS – pediatric autoimmune neuropsychiatric disorders associated with streptococcus infection: (1) presence of OCD and/or a tic disorder (meeting DSM-IV criteria); (2) pediatric symptom onset (between 3 years and the beginning of puberty); (3) episodic course characterized by abrupt onset of symptoms or dramatic symptom exacerbations; (4) temporal relationship between GABHS infections and symptom exacerbations; (5) neurological abnormalities (e.g. choreiform movements, motoric hyperactivity, and/or tics) present during symptom exacerbations. The postulated biological mechanism for PANDAS is referred to as molecular mimicry, a process by which pathogens attempt to evade host immune defenses designed to distinguish between host and foreign antigens. In the case of PANDAS, the mimicry is thought to exist between surface antigens of the streptococcus bacterium and neuronal antigens in the basal ganglia, resulting in neuropsychiatric symptoms. The majority of studies examining PANDAS are limited by small sample size, and there is a strong bias in the literature towards samples from specialty clinics. Although a robust association was reported in a large, population-based casecontrol study (Mell, Davis, & Owens, 2005), another recent prospective study found no association between OCD or tic symptom exacerbations and GABHS infections beyond that expected based on chance alone (Luo et al., 2004). The presence of anti-basal ganglia antibodies (ABGA) in the peripheral blood of patients with tics and/or OCD may be an important clue to the involvement of autoimmunity in these disorders (Dale, Heyman, Giovannoni, & Church, 2005). However, it is important to note that the presence of ABGA does not prove autoimmunity as a causal mechanism. Autoantibodies against a variety of tissue antigens are present in healthy individuals, and therefore, the presence of these antibodies does not by itself prove pathological significance. In fact, a recent study did not detect differences in antineuronal antibody

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profiles between children with Tourette’s syndrome, PANDAS, or age-matched controls (Singer, Hong, Yoon, & Williams, 2005). Efforts to elucidate a possible autoimmune mechanism have included a number of treatment studies. A pilot study of antibiotic prophylaxis for prevention of symptom exacerbations, analogous to penicillin prophylaxis in rheumatic fever, revealed no difference in number of infections or obsessivecompulsive or tic symptom severity between antibiotic and placebo groups (Garvey et al., 1999). A study of 29 patients fulfilling proposed PANDAS criteria reported sustained benefits after both intravenous immunoglobulin and plasma exchange, compared to placebo (Perlmutter et al., 1999). However, this small study had significant methodologic problems, and its findings have not been convincingly replicated. Other authors have reported rapid diminution of OC symptoms in cases fulfilling PANDAS criteria following treatment with antibiotics (Murphy & Pichichero, 2002), and positive correlations between streptococcal titers and obsessive-compulsive severity rating changes in subjects with large symptom changes (Murphy et al., 2004). Despite a large body of literature in this area, the existence of a PANDAS subgroup of OCD sufferers remains controversial. There is a clear need for longitudinal studies aimed at delineating the precise relationships between GABHS infections, OC symptom exacerbations, and alterations in immune parameters. It remains uncertain whether an association, if it truly exists, refers to a specific subgroup of patients with OCD or tics (PANDAS), to tic disorders and OCD in general, or to a broader range of diagnostic entities perhaps encompassing eating disorders and impulse control disorders such as trichotillomania. Based on the evidence so far, some argue for routine throat culture and antistreptolysin-O titres in children with an abrupt onset or exacerbation of OCD or tic disorder, although others dispute this recommendation. In summary, there is ample evidence to warrant further research in this area, but insufficient data to definitively describe the PANDAS subgroup or any treatments specific to such a group.

Social Anxiety Disorder Gastrointestinal Disease See the section on Panic Disorder and gastrointestinal disease for discussion of a relevant study by Hochstrasser and Angst (1996).

Endocrine/Metabolic Disease Results of smaller studies examining an association between social anxiety disorder and thyroid disease have been mixed, with some authors reporting significant associations (e.g. Carta et al., 2005), and others finding no increased prevalence compared to the general population (Simon et al., 2002). Studies

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using larger community samples have generally supported a significant association. Analysis of NCS data by Sareen et al. (2005) revealed a strong association between social phobia and metabolic/autoimmune disorders. Using data from a Canadian general population sample, Patten et al. (2006) reported that after adjusting for sex, age, and other chronic conditions, social phobia remained associated with thyroid disease.

Autoimmune Disease Lindal, Thorlacius, Steinsson, and Stefansson (1995), in an analysis of all known individuals with lupus in Iceland, reported that social phobia was more common in persons with lupus than in the general population. Reasons for this association are unclear, although the authors speculated that the occurrence of disfiguring facial rashes in certain lupus sufferers could be related to increased social anxiety.

Specific or Simple Phobia Respiratory Disease Goodwin, Jacobi, et al. (2003) reported a strong association between physiciandiagnosed severe asthma and specific phobia in a German community sample, which included assessment by a physician rather than self-report by study participants. This finding is consistent with analysis of NCS data by Sareen et al. (2005), which found a significant association between specific phobia and respiratory disease.

Gastrointestinal Disease See the section on Panic Disorder and gastrointestinal disease for discussion of a relevant study by Hochstrasser and Angst (1996).

Endocrine/Metabolic Disease As part of an examination of the epidemiology of blood-injection-injury phobia in the Baltimore ECA Follow-up Study, Bienvenu and Eaton (1998) found no

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strong, broad general health ramifications of this subtype of specific phobia. However, individuals with diabetes and blood-injection-injury phobia had higher than expected rates of macrovascular complications. This finding supports those from a previous study reporting that phobic symptoms are frequent in patients with Type I diabetes, and that the intensity of blood and injury fears negatively correlated with number of blood glucose measurements per day and metabolic control (Berlin et al., 1997). These findings together suggest the possibility that decreasing blood-injury fears could lead to improved metabolic control.

Cancer See the section on Panic Disorder and cancer for discussion of relevant studies by van’t Spijker et al. (1997) and Honda and Goodwin (2004).

Concluding Comments Conclusions Examination of the relationship between anxiety disorders and physical illness is a limited but expanding area of the scientific literature. The prevalence of both anxiety disorders and many physical illnesses in the population argues convincingly for the clinical relevance of this area of research. In addition to informing screening and detection of both mental and physical disorders, early evidence suggesting an impact on risk of death and disability underscores the importance of extending our understanding of these relationships. The impact of this comorbidity on treatment for either condition remains largely unexplored. Results of an analysis of primary care patients with panic disorder (Roy-Byrne et al., 2005) suggest that patients with a higher burden of physical illness responded equally well to CBT and pharmacotherapy targeted at panic symptoms, but more research in this area is needed to provide support for these findings and to explore treatment implications for other anxiety disorders. Although an impressive number of studies support associations between anxiety disorders and physical illness, the variety among reported findings is equally striking. This variety represents the current state of the literature: sufficient evidence exists to argue convincingly that associations between anxiety disorders and physical illness exist, but the precise nature of the relationships remains elusive, and a number of important methodological concerns limit conclusions. Which anxiety disorders are associated with which physical illnesses, and the exact nature of these associations, is a task for future research efforts.

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An essential caveat accompanying any discussion of associations between mental and physical disorders is the necessity of ruling out a physical illness masquerading as an anxiety disorder by virtue of overlapping symptomatology. In order for this very real possibility to be reliably distinguished from comorbidity, a thorough history and physical exam is required in any patient presenting for the first time with symptoms of an anxiety disorder, in any patient with markedly altered nature or severity of symptoms, and in any patient whose symptoms are resistant to standard treatments. Only when any existing physical illness is diagnosed and optimally treated can associations with mental disorders be accurately and safely explored.

Limitations and Future Directions Within the currently available literature, a number of methodological issues limit our understanding of associations between anxiety disorders and physical illness. The relative lack of large clinical or epidemiological studies, and relative preponderance of smaller studies, is one of the primary limiting factors. In addition, much of the available research still relies heavily on self-report in assessment of physical illness. In a population of individuals shown to be sensitized to perception of physical symptoms, reliance on self-report is particularly problematic. The lack of understanding of the role of other health behaviors, such as physical exercise and substance use, must also be highlighted as an issue for interpretive caution. It remains to be discovered whether health behaviors play a significant role in the observed associations between anxiety disorders and physical illness, and if so, whether they represent confounding variables or intermediate factors in an indirect causal pathway. The majority of studies in this area are cross-sectional, precluding any causal inferences. The scarcity of longitudinal data is a major limitation of existing research, and the need for more prospective, longitudinal epidemiologic data with objective measures of both physical and mental health status stands out as a clear mandate for future research efforts. Despite the limitations in available studies, existing research is compelling and argues convincingly that further attention to this area is warranted.

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The Relation Between Puberty and Adolescent Anxiety: Theory and Evidence Ellen W. Leen-Feldner, Laura E. Reardon, Chris Hayward, and Rose C. Smith

The Role of Puberty in Adolescent Anxiety: Theory and Evidence Anxiety disorders are among the most prevalent forms of psychopathology affecting youth, with recent estimates ranging from 3% to 18% for particular disorders (Albano, Chorpita, & Barlow, 1996). These rates are alarming, in light of the fact that anxiety psychopathology negatively impacts functioning across multiple domains (e.g., McGee & Stanton, 1990), maintains a chronic course for a significant proportion of youth affected (Orvaschel, Lewinsohn, & Seeley, 1995), and increases the risk for other types of disorders (Cole, Peeke, Martin, Truglio, & Seroczynski, 1998; Goodwin & Hamilton, 2002a, 2002b). The period of adolescence appears to be a particularly ‘‘high-risk’’ epoch in terms of the onset and intensification of anxiety problems; for instance, panic attacks (Macaulay & Kleinknecht, 1989; Warren & Zgourides, 1988), social phobia (Inderbitzen & Hope, 1995; Liebowitz, Gorman, Fyer, & Klein, 1985) and obsessive-compulsive disorder (Rasmussen & Eisen, 1990) commonly emerge during this developmental stage. Furthermore, traumatic event exposure is common among youth, with estimates indicating 16%–47% of youth ages 12–17 years have been exposed to at least one traumatic event (Giaconia, Reinherz, Silverman, & Stashwick, 1995; Perkonigg, Kessler, Storz, & Wittchen, 2000; Kilpatrick et al., 2000). Overall, adolescence represents a critical period during which anxiety vulnerability may be transformed into psychopathology. Efforts to develop sophisticated and comprehensive etiological models of adolescent anxiety psychopathology must necessarily consider the role of puberty, conceptualized as the most significant milestone of this period (Hayward & Sanborn, 2002). In addition, a growing body of literature links various aspects of puberty to clinical problems (Graber, Lewinsohn, Seeley, & Brooks-Gunn, 1997; Graber, Seeley, Brooks-Gunn, & Lewinsohn, 2004), including depression Ellen W. Leen-Feldner University of Arkansas, Department of Psychology, 216 Memorial Hall, Fayetteville, AR 72701, Tel: 479-575-5329, Fax: 479-575-3219 [email protected]

M. J. Zvolensky, J. A. Smits (eds.), Anxiety in Health Behaviors and Physical Illness. Ó Springer 2008

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(Angold, Costello, & Worthman, 1998), eating disorders (Killen, et al., 1992), and substance use problems (Patton et al., 2004). With this backdrop, researchers have begun to consider the potential role that puberty and its associated parameters (e.g., timing) may play in the development and maintenance of anxiety problems among adolescents. Indeed, a number of empirical articles have been published on this topic in the past decade; nonetheless, the literature is still in its relative infancy. Accordingly, the overarching objective of the current chapter is to stimulate additional research in this important domain; our specific goals are to 1) discuss methodological and conceptual issues pertinent to the study of puberty, 2) present an overview of the empirical literature focused on the association between puberty and anxiety, and 3) provide some conceptually-driven suggestions for future work in the area.

Operationalizing and Assessing Puberty: Methodological and Conceptual Issues Puberty is a period of profound biopsychosocial development; in a relatively short time-span (i.e., two to four years), youth experience extensive physical development, including reaching skeletal maturity (i.e., growth spurt), developing primary and secondary sexual characteristics (e.g., breast and penis growth), and attaining reproductive capability (Rogol, Roemmich, & Clark, 2002; Sheehy, Gasser, Molinari, & Largo, 1999). Although the experience can be exciting and relatively positive for many youth, puberty also is characterized by potentially undesirable bodily events, such as spontaneous erections, nocturnal emissions, gynecomastia, as well as onset of menses and irregularity of initial menstrual cycles (Kipke, 1999). Indeed, some youth report feeling under-prepared for the events of puberty, potentially contributing to a sense of ‘‘unexpectedness’’ or dyscontrol around these somatic events (Forest, Strange, Oakley, & The RIPPLE Study Team, 2004; Omar, McElderry, & Zakharia, 2003). In addition, puberty is associated with increased susceptibility to negative affectivity (Brooks-Gunn, Graber, & Paikoff, 1994; Susman, Dorn, & Chrousos, 1991), sleep deprivation (Carskadon et al., 2002), conflict in parent-child relationships (Paikoff & Brooks-Gunn, 1991), and enhanced emotional lability (Buchanan, Eccles, & Becker, 1992; Spear, 2003). Collectively, these data suggest puberty may be a difficult experience, at least for some adolescents. Indeed, puberty may be associated with the onset or exacerbation of clinically meaningful symptomatology among vulnerable youth (Caspi, & Moffitt, 1991, 1993). As the field endeavors to construct developmentally sensitive models of the etiology and maintenance of anxiety psychopathology among youth, it has become apparent that puberty deserves theoretical and empirical attention. However, operationalizing and assessing the complex construct of puberty is a challenging task.

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Because puberty is a multifaceted and dynamic process, there is no ‘‘gold standard’’ for its assessment (Hayward, 2003). When considering the mechanisms by which puberty may confer risk for psychopathology, researchers typically highlight three aspects of puberty: pubertal status, timing, and hormones, all of which are conceptualized to be in dynamic relation with one another and the larger social context (Graber, Brooks-Gunn, & Warren, 2006). A brief overview of each, including assessment approaches, is provided in the next section. For more comprehensive discussions of methodological approaches to the study of puberty, the reader is referred to reviews by Graber, Petersen, and Brooks-Gunn (1996) as well as Dorn, Dahl, Woodward, and Biro (2006). Finally, it is important to note in this context that, despite a significant correlation between the two variables, puberty is not redundant with chronological age. For example, age does not necessarily reflect pubertal status because the age at which the events of puberty occur vary across individuals (e.g., female breast development typically begins anywhere from ages 8 to 13; Tanner, 1962). In addition, a number of studies have shown that during early adolescence, puberty, and not age, is related to clinical problems such as eating disorders (Killen et al., 1992) and depression (Angold et al., 1998). Therefore, it is important to consider how age and puberty, both independently and in concert, alter risk over time for the development of specific clinical outcomes (Hayward, 2003). Pubertal Status. Pubertal status refers to an adolescent’s current level of morphologic development (Dubas, Graber, & Petersen, 1991) and can be indexed by asking participants to self-report their development in terms of specific physical indicators (e.g., height, pubic hair growth, skin changes; Petersen, Crockett, Richards, & Boxer, 1988) or experience of particular pubertal events such as spermarche (first emission of spermatozoa) or menarche (first menstrual period or bleeding). One of the most commonly used indices of pubertal status is the Tanner Staging System (Tanner, 1962; Morris & Udry, 1980), a five-stage classification system based on maturation of secondary sexual characteristics (i.e., breasts and pubic hair for females; genitalia and pubic hair for males) ranging from Tanner stage I (immature) to Tanner stage V (mature). Tanner stage can be self- or parent-reported (by asking respondents to select from a series of schematics), or directly evaluated by a practitioner. The Tanner staging system is a standard assessment of pubertal status in the literature; however, some limitations of the instrument include 1) inconsistent reliability between self report and practitioner evaluation, 2) concerns about the generalizability of the Tanner schematics across ethnic groups, and 3) the degree to which perceptions of status may affect adolescents’ self ratings of physical development (Dorn, Dahl et al., 2006). Pubertal Timing. Pubertal timing refers to the timing of pubertal onset relative to peers (i.e., early, on-time, or late). Timing can be objectively indexed by classifying participants on the basis of established standards of physical development (e.g., Todd standards of skeletal maturity) or comparing participants’ status on conceptually-relevant indicators, such as breast/pubic hair development (Wilson et al.,

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1994), menarche/spermarche (Kaltiala-Heino, Marttunen, Rantanen, & Rimpela, 2003), or age at peak height velocity (Dubas et al., 1991) with sample- or epidemiologically-defined norms. The timing of puberty also can be indexed via subjective self-report (e.g., ‘‘do you think your development is (was) any earlier or later than most other boys/girls your age?’’ Petersen et al., 1988). Although such reports evidence modest associations with objective measures (r’s range from 0.28 to 0.56; Dubas et al., 1991), puberty researchers conceptualize adolescents’ interpretation of pubertal development as reflecting meaningful variance in participants’ affective response to pubertal events. In other words, tapping into adolescents’ sense of their experience of puberty, irrespective of the degree to which it maps onto actual development, is theoretically important, as it is indicative of the broader psychosocial context in which the youth is developing. As an illustrative example, Michael and Eccles (2003) found that objectively indexed early timing (i.e., self-report of onset of menarche) was not associated with psychological distress (e.g., depressive symptoms; anger problems) among a sample of 266 African American females ages 13–14 years. However, when perceptions of pubertal timing were evaluated, females who viewed their maturation as early or late relative to on-time peers evidenced elevated depressive, eating, anger, and problem behavior symptoms. Maternal report corroborated these adolescent self report data. These findings suggest that subjective indices tap conceptually-relevant processes that may be important in terms of risk for psychopathology during puberty (cf., Silbereisen, & Kracke, 1997). Indeed, assessing perceptions of timing is recommended in studies where outcome variables are theorized to vary as a function of individual differences in the experience of puberty (e.g., perceptions of pubertal timing may be more relevant if self-perception is related to the outcome variable [self-esteem; anxiety; body image] whereas objective indices are indicated if research questions are focused on the effect of actual physical development on a particular outcome [aggression; muscle strength]; Dorn, Dahl et al., 2006). Pubertal Hormones. The two primary hormonal processes that drive pubertal development are adrenarche and gonadarche (Fechner, 2002). The first phase of puberty, adrenarche, commences between ages five and nine years in girls (approximately one year later in boys; Grumbach, & Styne, 2003). Activation of the adrenal axis results in the release of the adrenal hormones including cortisol, dehydroepiandrosterone (DHEA), its sulfate (DHEAS), and androstendione (4-A; Parker, 1999). The second phase of puberty, gonadarche, commences around age 9–10 years in females and is characterized by the release of leutinizing hormone (LH) and follicle stimululating hormone (FSH) by gonadotropes in the anterior pituitary (Johnson & Everitt, 2000). These hormones stimulate the enlargement of the gonads, which in turn release testosterone (T) and estrogen (E)/estradiol (E2) that promote the development of breasts and genitalia. Hormone concentrations typically are measured via blood serum or salivary sample assay. Salivary samples are less invasive and typically more cost effective, with professional assay services offered by well-respected companies such as Salimetrics, Inc. Moreover, there is evidence of adequate inter-correlations between the two assessment approaches

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(e.g., r =0.91 [cortisol]; r = 0.86 [DHEAS]; Salimetrics, LLC). However, salivary assay may not be sensitive enough to detect some hormones (e.g., estradiol; Shirtcliff, Reavis, Overman, & Granger, 2001) and can be affected by multiple variables, including contraceptive use, teeth brushing, medication, as well as recent meals and exercise (e.g., Bhagwager, Hafizi, & Cohen, 2002; Kirschbaum, Kudielka, Gaab, Schommer, & Hellhammer, 1999). Therefore, blood serum assessments may be preferable, particularly if researchers have access to the appropriate personnel and testing services (e.g., affiliations with a medical school). Regardless of the approach however, rigorous assessment (e.g., multiple assessments within- and across- days; Goodyer, Park, & Herbert, 2001) is critical to ensure valid hormone indices because hormones evidence significant fluctuation (e.g., ultradian; circadian; monthly rhythms; Cauter, 2001). Puberty as a ‘‘Risk Factor.’’ A necessary first step toward theoretical and empirical integration of puberty into models of etiology and maintenance of anxiety psychopathology is to clarify how the various aspects of puberty fit into contemporary conceptualizations of risk. Specifically, Helena Kraemer and her colleagues (Kazdin, Kraemer, Kessler, Kupfer, & Offord, 1997; Kraemer, Stice, Kazdin, Offord, & Kupfer, 2001; Kraemer et al., 1997) have developed a standardized nomenclature for operationalizing risk factor processes in which a risk factor is defined as characteristic, experience, or event that indicates the relative likelihood of a given outcome among individuals within a population (e.g., if the entire population is exposed to the variable in question, it is not a risk factor). The authors suggest that a characteristic can be classified as a risk factor (i.e., a characteristic that temporally precedes, and is correlated with, an outcome) or a causal risk factor (i.e., a characteristic that temporally precedes and, when manipulated, produces systematic change in an outcome). Risk factors can be further categorized according to whether they are malleable; if the characteristic changes spontaneously (e.g., age) or can be manipulated (e.g., skill set) is it classified as a variable risk factor, whereas if the characteristic is non-modifiable (e.g., gender), it is referred to as a fixed marker. According to the Kraemer model, puberty per se (i.e., an individual’s pubertal status; hormonal changes characteristic of puberty) is not a risk factor; all youth are exposed to puberty and as such it does not designate sub-populations of youth more or less likely to evidence a given outcome. A more accurate conceptualization of puberty generally is as a ‘‘critical period,’’ reflecting a high-risk phase for youth who are otherwise vulnerable. Indeed, the unparalleled physical, cognitive, and psychosocial changes associated with puberty can be stressful for some adolescents, making it an important time for screening and intervention. Pubertal timing, on the other hand, is a facet of puberty that reflects individual differences in an otherwise universal human experience. Accordingly, pubertal timing more readily lends itself to classification within the Kraemer model. Specifically, pubertal timing characterizes specific sub-groups of youth at risk for a number of psychiatric outcomes (e.g., early-maturing females evidence increased risk of substance use problems;

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Dick, Rose, Viken, & Kaprio, 2000). Although the timing of puberty has changed in the past two decades (earlier onset), given the current state of our knowledge, altering the timing of puberty is not currently conceptualized as a reasonable target of intervention. Therefore, pubertal timing is considered non-malleable and classified as a fixed marker. Importantly, pubertal timing is non-specific in nature as it has been linked to an array of clinical sequelae, including problematic health behaviors (e.g., excessive dieting and exercise [McCabe & Ricciardelli, 2004]; alcohol, cigarette, and marijuana use [Lanza & Collins, 2002; Wichstrom, 2001; Weisner & Ittel, 2002]) as well as elevated risk of clinical symptomatology and diagnoses (e.g., depressive-type problems [Graber, Seeley, Brooks-Gunn, & Lewinsohn, 2004; Kaltiala-Heino, Kosunen, & Rimpela, 2003); eating-related pathology [Kaltiala-Heino, Rimpela, Rissanen, & Rantanen, 2001]). As highlighted by the current volume, the important link between health behaviors and anxiety is just beginning to be fully appreciated. As these two outcomes, anxiety and unhealthy behaviors, both increase at puberty, it will become increasingly important to untangle both pubertal status and pubertal timing effects associated with health behaviors in addition to unraveling the potential interaction between onset of anxiety and initiation of unhealthy behaviors in the peripubertal period.

Overview of Findings from the Empirical Literature – Differentiating Pubertal Status and Timing Effects The available empirical literature focused on the puberty-anxiety association is briefly reviewed in this section, addressing anxiety in relation to each of the aspects of puberty discussed above. In light of the marked gender differences in the process and experience of puberty (Hayward, 2003), findings among males and females are presented separately. Finally, in light of space limitations, more detailed descriptions are presented for studies that, relative to others in the literature, are characterized by greater methodological rigor (e.g., sample size; prospective assessments) thereby allowing for more confidence in the observed findings. Pubertal Status and Anxiety. In terms of the main effects of pubertal status, findings are mixed. Among females, for instance, a significant positive relation was observed in two large samples of non-clinical youth conducted in the United States (Hayward et al., 1992) and Australia (Patton et al., 1996). Specifically, Hayward and colleagues found, after controlling for age, a two-fold increase in the likelihood of having had a panic attack for each one-point change in self-reported Tanner stage among 754 ethnically diverse 6th and 7th grade females. Interestingly, none of the females at Tanner stages I or II reported having had a panic attack. Similarly, in a sample of more than 2,000 adolescents, Patton and colleagues reported a positive association

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between psychiatric symptoms (including anxiety) and pubertal status (self-reported age at menarche) after controlling for chronological age. Indeed, females for whom menarche had occurred more than 36 months prior to the study were more than twice as likely to evidence psychiatric morbidity. Studies also have demonstrated an association between advancing pubertal status and trait anxiety among females (Huerta & Brizuela-Gamino, 2002) but others have found either a weak negative association or no relation at all (Canals,Marti-Henneberg, Fernandez-Ballart, Cliville, & Domenech, 1992; Laitinen-Krispijn, van der Ende, & Verhulst, 1999; Susman et al., 1991; Stone & Barker, 1939). Among males, Ge, Conger, and Elder (2001) reported a positive association between ‘‘internalized distress’’ (i.e., summary measure of self-reported depressive, anxious, somatization, and eight additional symptoms) and self-reported pubertal status among 202 adolescent males between the ages of 12 and 14 assessed annually over a four year period. However, the association did not persist, suggesting this effect may be short-term in nature. Specifically, pubertal status indexed in grade 7 predicted internalized distress at grades 8 and 10, but pubertal status assessed at grades 8, 9, and 10 was unrelated to internalized distress at any other assessment point. Similarly, Susman and colleagues (1991) found that physician assessed pubertal status related positively to interviewassessed depressive and anxiety symptoms 12 months later among 56 males aged 10 to 15 years (age was entered simultaneously into the model). However, inconsistent with these two studies, other work has found no association between pubertal status and anxious symptoms (Patton et al., 1996), a decrease in anxious-depressed symptoms as a function of advancing pubertal stage (Laitinen-Krispijn et al., 1999), or mixed findings (i.e., elevated state anxiety at the beginning and end of puberty; Canals et al., 1992). One reason that the literature is mixed may be that key constructs that might influence or moderate the pubertal status-anxiety association have received limited attention. This relative degree of neglect is unfortunate, particularly because, as discussed above, puberty per se is a normative developmental process (Rosenfeld & Nicodemus, 2003). Therefore, the characteristic changes of puberty would only be expected to increase risk for psychopathology under certain conditions (e.g., among psychologically vulnerable adolescents; Buchanan et al., 1992). This conceptualization is in line with the idea that puberty in and of itself is a ‘‘critical period,’’ or a period of high risk for youth who are otherwise vulnerable. Specifically, the accentuation hypothesis (Caspi & Moffitt, 1991, 1993) postulates that the changes associated with puberty amplify pre-existing vulnerability, thereby resulting in psychopathology among at-risk youth. Consistent with this perspective, panic-relevant (anxiety sensitivity; Leen-Feldner, Reardon, et al., 2006; LeenFeldner, Reardon, & Zvolensky, 2007) and biological (seratonergic dysfunction; Twitchell, Hanna, Cook, Fitzgerald, & Zucker, 2000), individual difference vulnerability variables have been found to moderate the association between advancing pubertal status and anxiety outcomes. For instance,

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among 123 psychologically healthy adolescents aged 12–17 years, Leen-Feldner and colleagues (2006) found that more mature youth who also were high in anxiety sensitivity [AS], a cognitive vulnerability factor reflecting a tendency to fear the consequences of anxiety (Reiss & McNally, 1985), reported the most fearful reactivity in response to a panic-relevant voluntary hyperventilation challenge. That is, advancing pubertal status was associated with panic-relevant reactivity only among those youth who were vulnerable to such reactivity by virtue of elevated cognitive vulnerability (i.e., AS). These effects were significant above and beyond age, gender, and pre-experimental anxiety. These data highlight the utility of investigating potential moderators of the pubertal status-anxiety association. Indeed, a number of conceptually relevant diatheses may be important in terms of enhancing anxiety vulnerability during pubertal development, including behavioral inhibition (Hirshfeld et al., 1992), negative affectivity (Craske, 2003), anxiety sensitivity (Schmidt, Zvolensky, & Maner, 2006), and traumatic event exposure (Caffo, Forresi, & Lievers, 2005). With the exception of AS, no empirical work has addressed these questions, and thus they represent important future directions (please see the Suggestions for Future Research section for additional recommendations). Pubertal Hormones and Anxiety. Perhaps due to the complexities of hormone research described earlier, the literature focused on the link between anxiety and pubertal hormones is quite limited, precluding integrative conclusions. Prior to reviewing the available literature, it is worth noting that several studies conducted with adolescents have investigated the general association between anxiety and specific hormones that are present during puberty (e.g., cortisol; Gerra et al., 2000). For instance, in a study of 131 adolescents, Terleph, Klein, and Roberson-Nay (2006) reported a positive association between mean cortisol levels before and during a biological challenge procedure and panic attacks elicited by the challenge, suggesting elevated cortisol may represent a panic-relevant vulnerability variable. Although these findings are theoretically interesting in their own right, without an index of pubertal status, it is difficult to extrapolate their relevance in terms of the puberty-anxiety association because observed associations could be due to other variables that are confounded with hormone levels, such as the social consequences of hormonally-driven secondary sex characteristic development (Slap, Khalid, Paikoff, & Brooks-Gunn, 1994). Therefore, studies reviewed below included an index of pubertal status. In a seminal study, Olweus, Mattsson, Schalling, and Low (1980) reported no association between blood serum testosterone and both trait and state anxiety elicited by the blood draw among 58 Swedish males aged 15 to 17 years. In a more fine-grained analysis of the role of testosterone, Granger and colleagues (2003) found, in a mixed gender study of over 200 youth aged 11–17 years, a negative association between testosterone and concurrent anxious/depressed symptomatology. In addition, anxious/depressed symptoms were related to diurnal variation such that those males who exhibited less of a

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decrease in testosterone across the course of the day evidenced elevated symptomatology. No relation was observed among females. Nottelmann and colleagues (1987) measured LH, FSH, DHEA, DHEAS, T, E2 4-A, and internalizing-type symptoms among 108 youth aged 9 to 14 years. The only associations observed were among males; a positive correlation between 4-A and an index of obsessive-compulsive symptoms and a negative correlation between ‘‘emotional tone’’ (combined sadness/anxiety ratings) and a T/E2 ratio. Finally, in a one-year prospective study of more than 100 youth (ages–years), Susman and colleagues (1991) measured cortisol in addition to the hormones indexed in the Nottelmann et al. study. Among females, cortisol and T relatepositively to concurrent anxious symptoms and emotional tone, respectively. DHEAS related negatively to concurrent maternal report of internalizing symptoms. Prospective analyses with females indicated LH (positive association) and DHEAS (negative association) predict anxiety symptoms assessed one year later. Among males, T and E2 (negative associations) as well as 4-A (positive association) related concurrently to emotional tone. In addition, LH and cortisol related negatively to maternal report of internalizing symptoms 12 months later; DHEA and 4-A also prospectively predicted anxious symptoms (positive associations). As noted above, it seems premature to draw integrative conclusions about the role of hormones in potentiating anxiety, although there is some evidence that T and 4-A are related to anxious symptomatology among males; reliable associations among females have not been observed across studies. There are multiple empirical questions to address in this domain (please see the Suggestions for Future Research section). From a conceptual perspective, it is useful to highlight the fact that hormones represent a ‘‘piece of the puzzle’’ as they exhibit reciprocal effects on other hormones, behavior, and pubertal development (Nelson, 2000). Therefore, the role of pubertal hormones in anxiety development will likely be understood only if studied within the context of a larger, biopsychosocial model (Brooks-Gunn et al., 1994; Booth, Johnson, Granger, Crouter, & McHale, 2003). Pubertal Timing and Anxiety. Although the literature is not uniform, compared to pubertal status and hormones, pubertal timing evidences the most consistent and robust associations with anxiety psychopathology, particularly among females. Specifically, early-maturing females report elevations in anxious symptoms (Dorn, Hitt, & Rotenstein, 1999; Graber et al., 2006; Kaltiala-Heino et al., 2003; Silbereisen & Kracke, 1997; Sonis et al., 1985), psychological distress (including anxiety symptoms; Ge, Conger, & Elder, 1996; Hayward et al., 1997), panic attacks (Hayward et al., 1997) and anxiety disorders when prospectively assessed (Graber et al., 2004). As an illustrative example, in one of the most comprehensive studies completed to date, Graber and colleagues examined perceptions of pubertal timing in relation to psychiatric symptoms and interview assessed diagnoses among an epidemiologically-defined mixed gender sample of 1,709 adolescents aged 14–18 years. Concurrent analyses (adjusted for chronological age) indicated

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early maturing females evidenced elevated depressive symptoms as well as disruptive behavior, eating, and major depressive disorders (but not anxiety disorders). These associations were significant (with the exception of eating disorders) at the follow-up assessment (approximately 10 years after the initial evaluation). In addition, there appeared to be a ‘‘sleeper effect’’ for anxiety; compared to their on-time counterparts, early maturing females were almost twice as likely to meet criteria for an anxiety disorder (lifetime). There is no evidence that late maturation is associated with anxiety among females. Among males, the pattern is somewhat less consistent; studies have found early maturation is associated with increased anxiety symptoms (Ge, Brody, Conger, & Simons, 2006), state anxiety (i.e., a single question on which participants self-reported the ease with which they became anxious or distressed; Kaltiala-Heino et al., 2003), observations of manifest anxiety (i.e., trained interviewers’ ratings of participants’ anxiety (e.g., tendency to worry) based on direct observation and interviews with family and teachers, taken yearly between the ages of 5 and 16; Peskin, 1967), and ‘‘internalized distress’’ (i.e., a self-report of depression, anxiety, somatization, and other complaints such as poor appetite, trouble sleeping, and overeating, as measured on the SCL-90-R; Ge et al., 2001). In contrast, other reports suggest late maturation relates positively to self-reported internalizing-type symptoms (including anxiety; Graber et al., 1997) and observer rated social anxiety (Jones & Bayley, 1971). In the studies conducted by Graber and colleagues discussed above, the follow up study indicated that the positive association between late maturation and internalizing symptoms does not persist among males and, in contrast to females, pubertal timing does not prospectively predict anxiety diagnoses (although late maturation was associated with current substance use and lifetime disruptive behavior diagnoses at the follow-up assessment). There are a number of individual and contextual factors that appear to influence the association between pubertal timing and anxiety. For instance, significant interactions have been observed between early maturation and life stress (Ge et al., 2001), as well as early maturation and pre-pubertal internalizing symptoms (Hayward et al., 1997) in the prediction of anxious symptomatology. Specifically, early maturing youth who also reported elevated life stress and internalizing symptoms, relative to all other variable combinations, evidenced the most anxiety. In a more fine-grained analysis, Ge and colleagues (2001) examined pubertal timing as indexed by age at menarche in a four-year longitudinal study of 216 females (7th through 10th grade). These authors found evidence for the idea that early maturation exacerbates vulnerability to psychological distress and that this process is influenced by a number of variables. Specifically, among early maturing females only (cf., on-time and late developers), early psychological distress relates positively to later psychological distress, suggesting early maturation increases susceptibility to continued emotional problems. In addition, early maturing females were more likely to associate with deviant peers, which in turn predicted later psychological distress. Finally, peer group composition moderated the timing-distress

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association such that, compared to on-time and late developers, early maturing females who also were associated with mixed (as opposed to same-sex) peer groups in the 7th through 9th grades were more likely to evidence psychological distress in the 10th grade. This study highlights the complex inter-relations that characterize the association between pubertal timing and anxiety, and furthermore suggests that negative effects of off-time maturation may not be transient, but rather persist over time. Overall, pubertal timing appears to be an important fixed marker in the development and maintenance of anxiety-type symptoms, particularly among females. Interestingly, not only does the timing of puberty alter psychiatric risk but psychological factors may alter the timing of puberty (reviewed in more detail below). Thus, in theory, pubertal timing is malleable. However, from an intervention standpoint, understanding how pubertal timing affects outcomes may be a more feasible goal than attempting to alter the timing of puberty itself. Therefore, at this stage of research development, we consider pubertal timing to be non-malleable (i.e., fixed marker). In addition, as noted earlier, the association between pubertal timing and psychiatric outcomes is non-specific in nature. For both these reasons (non-malleability; non-specificity) identification of mediators and moderators of the pubertal timing-anxiety association is critical. In particular, it will be important for researchers to consider gender-specific characteristics that may mediate or moderate the timing-anxiety association, as the link between timing and anxiety appears to differ across males and females. For instance, sexual assault exposure (Hayward & Sanborn, 2002) and body image and weight concerns (Richards, Boxer, Petersen, & Albrecht, 1990) may be particularly important among females, whereas risk-taking activities (e.g., substance use; Andersson & Magnusson, 1990) may be important to consider among males. Temporal Dimensions of the Pubertal Timing-Anxiety Association. As mentioned above, a complicating facet of the putative link between pubertal timing and anxiety pertains to the chicken-and-the-egg issue. Specifically, two pathways are viable. First, the timing of maturation may potentiate anxiety for some youth (e.g., early maturing females develop anxiety-related problems; Graber et al., 2004). However, it has also been posited that the direction of the association may be from contextual ‘‘stress’’ in the early environment to pubertal timing. Both neurobiological (e.g., changes to the HPA-axis secondary to childhood stress; Meschke, Johnson, Barber, & Eccles, 2003) and sociobiological (Belsky, Steinberg, & Draper, 1991) mechanisms have been theorized. For instance, Belsky and colleagues highlight the utility, from an evolutionary perspective, of commencing reproductive activities as soon as possible if an organism is reared in a stressful environment where the viability of progeny is questionable. Therefore, children reared in a stressful environment are predicted to experience the hormonal and physical changes of puberty earlier than youth from stable home environments. There is a relatively large body of work examining the role of early stress in relation to pubertal timing. For instance, among females, dysfunctional family background (e.g., parental

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divorce; alcoholism; Hulanika, 1999) and childhood sexual abuse (HermanGiddens, Sandler, & Friedman, 1988) have been found to predict earlier menarche. Similarly, familial conflict in the childhood environment has been shown to predict early spermarche (Kim & Smith, 1998). Conflicting findings also have been observed, however, with some studies suggesting childhood stress predicts later maturation (e.g., Malo & Tremblay, 1997) and others reporting no association at all (see Kim, Smith, & Palermiti, 1997, for a review). With regard to anxiety symptoms specifically, the literature is similarly mixed, with some studies reporting that anxious symptomatology in childhood is associated with earlier menarche (Kim & Smith, 1998) and spermarche (Kim & Smith, 1999), others suggesting it is linked with later spermarche (Malo & Tremblay, 1997), and still others indicating it is unrelated to maturational timing (Graber, Brooks-Gunn, & Warren, 1995). In addition, at least one study calls attention to the importance of the type of anxiety being assessed. Specifically, Meschke and colleagues (2003) found, among males, economic and school anxieties predicted earlier and later puberty, respectively. These studies represent a useful first step toward specifying the role of early-life anxiety in affecting pubertal onset. However, the mixed findings, due at least in part to methodological issues (e.g., reliance on retrospective recall) make it difficult to draw definitive conclusions about issues of temporal order. Nevertheless, these data suggest that interventions designed to reduce anxiety early in life might also ‘‘secondarily’’ alter the timing of puberty. This is a critical area for future work. Summary of the Empirical Literature Focused on the Puberty-Anxiety Association. Although the available research is promising, there is a great deal of work to be done to fully understand the association between puberty and anxiety. Much of the early work was characterized by significant methodological limitations, including small sample size, assessment of only one aspect of puberty, one-time hormone assessments, analyses with males and females combined, and utilization of non-specific measures of anxiety. Indeed, in drawing conclusions from the extant work, greater weight should be placed on those studies (e.g., Ge et al., 1996, 2001; Graber et al., 1997, 2004; Hayward et al., 1992, 1997) where some of these limitations are addressed. Accordingly, three tentative conclusions can be drawn at this stage of research development. First, anxiety symptomatology appears to increase as youth traverse puberty; the more methodologically rigorous studies suggest a positive association between pubertal status and anxiety that cannot be explained by chronological age (e.g., Patton et al., 1996). From a conceptual perspective, however, it makes sense to continue exploring mechanisms that may explain this association, as puberty itself is not considered to be pathological in its own right (Graber, 2003); examination of individual-difference variables that might be expected to influence the association is an exemplar of an important next step in this literature. Second, the hormone literature is too under-developed to draw any firm conclusions at this point; additional work is needed to cull out the main, additive, and interactive effects of pubertal hormones on anxiety

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symptomatology. Finally, pubertal timing, particularly early maturation among females, appears to be a fixed marker for anxiety (e.g., Graber, 2003); there is less compelling evidence for the effects of early or late maturation on anxiety among males. As with pubertal status, our understanding of the effects of off-time maturation will be most comprehensive when other variables, such as the role of concomitant life stress, are considered. In addition, there is at least some evidence indicating that early-life anxiety predicts early maturation, suggesting the association between anxiety and pubertal timing is complex and likely bi-directional, at least for some youth. Despite the overarching promise of the emerging literature in this domain, the direction, magnitude, and nature of the puberty-anxiety association have yet to be fully explicated. Building on the suggestions for future research proposed in previous sections, the next section offers additional ideas within the context of the overarching limitations of the extant work.

Moving this Literature Forward: Conceptually-Driven Suggestions for Future Research We have three specific suggestions for future research, aimed at increasing the methodological and conceptual sophistication of the literature. First, there is a general need for more comprehensive and integrated assessments of puberty. For instance, it will be important to replicate and extend findings from the hormone literature suggesting a main effect of specific hormones on anxious symptomatology (Granger et al., 2003). Here, methodologically innovative approaches that involve multiple assessments across the course of puberty will be critical for addressing questions related to the short-term (e.g., rapidly escalating hormones; Apter, 1980) and long-term effects of hormonal changes during puberty. In addition, because hormones affect each other in complex ways (Johnson & Everitt, 2000) it will be important for researchers to obtain indices of several different hormones and examine their independent and combined effects on anxiety. Although expansion of the hormone-anxiety literature would fill an important empirical gap, perhaps a more pressing challenge is to evaluate the combined (additive and interactive) effects of pubertal status, timing, and hormones on anxiety, as well as the impact of childhood anxiety on pubertal maturation. An integrated approach to pubertal assessment is critical here, as these aspects of puberty are fundamentally inter-related (Brooks-Gunn et al., 1994). As an illustrative example, consider breast development among females. This process is driven by gonadal hormones, which may have an independent effect on anxious reactivity (Susman et al., 1991). However, personal and social (e.g., parents; peers) reactions to a female’s status on this relatively visible pubertal event may also contribute to anxiety (Brooks-Gunn, 1984), particularly if she is ‘‘off-time’’ with respect to her contemporaries (Brooks-Gunn & Warren, 1985). Of course, some of the

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greatest yield in terms of improving our conceptual understanding of the puberty-anxiety association will come from prospective assessments of the inter-relations between the two across the course of puberty, beginning, ideally, as young as five or six years so that the early stages of puberty are studied (e.g., awakening of the adrenal glands; Dorn, Dahl et al., 2006) and questions of the temporal association can begin to be addressed. In addition, advanced statistical techniques, aimed at delineating the associations among childhood anxiety, early puberty, and subsequent anxiety, are needed. Overall, multi-modal, integrated, and longitudinal assessments of puberty will be necessary to cultivate a comprehensive understanding the puberty-anxiety association. Related to this first point, the literature would also benefit from more fine-grained assessments of anxiety. For instance, with some important exceptions (e.g., Graber et al., 1997, 2004; Hayward et al., 1992, 1997), the majority of available studies focus on associations among pubertal indices and non-specific anxiety-relevant outcomes (e.g., anxiety as a part of a larger internalizing construct). Although this approach yields useful information in terms of the role of puberty in terms of general risk trajectories (e.g., internalizing versus externalizing), it does not speak to the aspects of puberty that may potentiate fearful reactivity to distinct classes of stimuli (e.g., social; bodily; mental; Craske, 2003) or the development of specific types of anxiety psychopathology (e.g., social anxiety disorder; post-traumatic stress disorder). In addition to the conceptual utility of such tests, data pertinent to the role of puberty in the development of specific anxiety disorders would be useful for the development of tailored preventative interventions (e.g., Mrazek & Haggerty, 1994; Zvolensky, Schmidt, Bernstein, & Keough, 2006). To this end, investigators could explore pubertal processes in the context of specific anxiety outcomes, including symptom checklists that correspond to specific anxiety disorders (e.g., generalized anxiety disorder subscale of the Screener for Child Anxiety and Related Disorders; Birmaher et al., 1997) and diagnostic status across the anxiety disorders as indexed via structured clinical interview. These data would be extraordinarily useful in clarifying the nature and magnitude of the puberty-anxiety association and would furthermore position researchers to examine whether and how pubertal processes affect anxious symptomatology across disorders (e.g., is puberty more likely to potentiate social anxiety as compared to obsessive compulsive disorder?). As a complement to this approach, there may be significant merit in integrating laboratory-based assessments of anxiety processes (e.g., are aspects of puberty related to changes in social anxiety as indexed via distress elicited by a laboratory-based social evaluative task?; Ferrell, Beidel, & Turner, 2004). Laboratory-based methodology has the advantage of allowing for the evaluation of ‘‘real-time’’ emotional responding, thereby delimiting recall biases other types of reporting errors common to affective processing (Zvolensky, Lejuez, Stuart, & Curtin, 2001). Finally, the extant literature can be described as largely descriptive in nature, focusing on whether a relation exists between puberty and anxiety. Building on

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this foundation will require systematic testing of the putative ‘‘mechanisms of action’’ underlying the link between puberty and anxiety. The broad-based questions that need to be addressed include 1) precisely how does puberty contribute to anxiety psychopathology (and vice versa)? 2) what individual difference and social-contextual variables increase the explanatory power of puberty-anxiety models? and 3) what types of ‘‘process variables’’ mediate the puberty-anxiety association? Given the multi-faceted nature of both puberty and anxiety, there are multiple systematic research programs that will converge to address these questions. Consistent with our suggestion to develop the literature on the role of puberty in the development and maintenance of specific anxiety-relevant outcomes, we will utilize panic disorder (PD) as the outcome of interest to exemplify this issue. However, because pubertal timing is a non-specific fixed marker, it is our hope that investigators with expertise in other types of anxiety psychopathology (e.g., post-traumatic stress disorder; social anxiety disorder) will extrapolate ideas relevant to their own programs of research from the current discussion. Panic disorder is a common, severe, and chronic condition associated with substance use disorders, poor physical health outcomes, social/occupational disability, and high rates of healthcare utilization (APA, 2000; Greenberg et al., 1999). Importantly, adolescence is a critical developmental period during which panic problems first manifest, making it an important stage to study in terms of panic-related problems (e.g., Ollendick, Mattis, & King, 1994; Von Korff, Eaton, & Keyl, 1985). The hallmark characteristic of PD is fearful reactivity to bodily sensations, which is posited to result, at least in part, from interoceptive learning (Craske, 2003). Specifically, the repeated pairing of somatic cues and personal threat/anxiety results in bodily arousal becoming a phobic stimulus (Bouton, Mineka, & Barlow, 2001). Puberty may be a ‘‘critical period’’ for such interoceptive learning. Specifically, puberty is replete with bodily oriented changes, some of which, as discussed earlier, may be conceptualized as unpredictable, uncontrollable, and undesirable bodily events (e.g., spontaneous erection; Omar et al., 2003). Importantly, an array of studies using diverse methodological procedures have demonstrated that uncontrollable and unpredictable aversive events are associated with heightened anxiety states and bodily arousal (Maier & Seligman, 1976; Mineka & Kihlstrom, 1978; Sanderson, Rapee, & Barlow, 1989; Sapolsky, 1990; Sapolsky, Alberts, & Altman, 1997; Zvolensky, Eifert, & Lejuez, 2001). As youth traverse puberty, they are increasingly exposed to somatic events that may result in panic-relevant interoceptive learning. This hypothesis predicts that puberty, reflective of adolescents’ relative degree of exposure to such learning trials, will be associated with elevated panic symptomatology. However, because puberty per se is not a malleable risk factor (all youth experience puberty, but not all youth develop clinical problems [Graber, 2003]), investigators are tasked with identifying other variables that may explain the puberty-panic association. To identify risk factors that are malleable and therefore subject to intervention it is necessary to identify the specific mediators and moderators of the

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puberty panic association. Specifically, identification of mediators/moderators will 1) elucidate the causal chain that links pubertal effects to panic outcomes, 2) point researchers toward modifiable factors that will aid in the prevention of panic, and 3) increase model specificity (e.g., anxiety-relevant mediators and moderators such as fear of negative evaluation may improve the prediction of anxiety problems, whereas depression-relevant mediators/moderators such as dysfunctional attitudes will likely aid in the prediction of depressive outcomes). Discussions of some candidate mediators and moderators of the puberty-panic association are provided below. Mediators temporally follow and are correlated with a risk characteristic (in this case, pubertal effects), and attenuate the association between the risk characteristic and the outcome (i.e., anxiety; Kraemer et al., 2001). One potential mediator may be the fear-relevant somatic learning that occurs during the course of puberty (see Fig. 1).This hypothesis requires an assessment of the posited mediating process. To this end, it would be helpful to design a psychometrically sound self-report index of fear-relevant experiences with puberty-related bodily sensations (e.g., ‘‘I was scared when I first started having menstrual cramps’’). With a valid and reliable index, researchers would be well positioned to address questions such as whether fear-relevant learning changes across the course of puberty and whether such learning accounts for observed associations between puberty and panic. Another class of conceptually interesting mediators, given their effects on neurotransmitter systems hypothesized to be involved in mood regulation (McEwen, 1991), are the gonadal steroids associated with puberty. For instance, estrogen modulates the serotonin neurotransmitter system in a number of ways, including effects on serotonin synthesis and receptor density (Biegon et al., 1990). Animal research suggests puberty ushers in changes in the serotonin system reaction to stress, particularly among females. For instance, following separation, post-pubertal female rhesus monkeys, compared to males, evidence higher levels of 5-Hydroxyindoleacetic acid (5-HIAA), a primary metabolite of serotonin and an index of the organism’s level of serotonin (Higley, Suomi, & Linnoila, 1990). This difference is not apparent prior to puberty, suggesting gonadal steroids may potentiate the stress response among pubertal females (Sanborn & Hayward, 2003). Time Puberty

Panic-Related Problems

Mediators (e.g., fear-relevant learning; gonadal steroids)

Fig. 1 Mediators of the puberty-panic association

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It also is important to identify potential moderators of the puberty- panic association. These variables precede and are uncorrelated with aspects of puberty (Kraemer et al., 2001). An important potential individual-difference factor that could moderate the puberty panic association is anxiety sensitivity (AS), or the fear of anxiety and anxiety-related sensations (Reiss & McNally, 1985), which has been theoretically (Barlow, 2002) and empirically (Hayward, Killen, Kraemer, & Taylor, 2000) supported as a key cognitive vulnerability factor involved in the development of anxious responding to bodily sensations – a hallmark characteristic of panic attacks. From a conceptual perspective, AS might be expected to amplify the panic-relevant learning that occurs during puberty. That is, compared to low AS youth, adolescents with elevated AS may perceive the bodily events that occur during puberty (e.g., early breast development; menstrual discomfort/accidents; autonomic arousal secondary to hormonal shifts) as more threatening. Across the course of puberty, vulnerable youth (i.e., high AS youth) may more readily learn that physical sensations are aversive and anxiety-relevant, possibly resulting in a panic attack. In contrast, adolescents low in AS may be less susceptible to panic-relevant interoceptive learning during puberty because they are less fearful of bodily sensations (see Fig. 2). In addition to individual-difference characteristics, there are a number of panic-relevant social/contextual moderators that would be theoretically interesting to investigate. For instance, there is emerging evidence for the role of parenting behavior in increasing the ‘‘threat value’’ of bodily sensations via direct (e.g., informational transmission), or indirect (e.g., modeling) reinforcement of fearful responding to somatic cues (Craske & Rowe, 1997; Ehlers, 1993; Muris, Merckelbach, & Meesters, 2001; Watt & Stewart, 2000). Thus, a parent

Time Moderator (e. g., youth HIGH in anxiety sensitivity)

Puberty

Presence of PanicRelated Problems Absence of PanicRelated Problems

Moderator (e. g., youth LOW in anxiety sensitivity)

Fig. 2 Moderators of the puberty-panic association

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who communicates fear in the context of bodily arousal (e.g., dizziness secondary to a childhood fever) may inadvertently facilitate the child’s pairing of fear and interoceptive experiences. Subsequently, the bodily perturbation characteristic of puberty (particularly when such experiences are off-time compared to peers) may be experienced as panic-relevant. In this example, the moderating effect of specific parenting behaviors would be expected to increase the likelihood of panic-relevant learning during puberty. Another conceptuallyrelevant social-contextual moderator is pre-pubertal traumatic event exposure, such as childhood sexual abuse. A number of studies suggest a link between significant stress and changes (e.g., hypersecretion of corticotropin-releasing hormone) to the hypothalamic-pituitary-adrenal (HPA) axis (e.g., Miller, Chen, & Zhou, 2007). Such changes are thought to directly increase vulnerability to psychopathology; this outcome may be more likely among females because of the role estrogen plays in enhancing the HPA stress response. When this vulnerability is combined with the normative HPA axis changes that occur during puberty, Sanborn and Hayward (2003) suggest that impairments in HPA functioning may reach a threshold, thereby putting trauma-exposed, pubertal females at particular risk for anxiety psychopathology (including panic). Together, although the discussion was focused on panic-related problems, the third general suggestion is for researchers to complement the available descriptive research and work toward identifying key mediators and moderators of the puberty-anxiety association. Understanding the processes that influence the association between puberty and anxiety will be critical from a public health perspective. For instance, if research bears out the prediction that panic-relevant learning mediates the association between puberty and panic, high risk youth (e.g., early maturing females) could be identified in a primary care setting and presented with a brief intervention focused on reducing fear of bodily sensations and encouraging interoceptive exposure to attenuate the effects of subsequent panic-relevant leaning trials (e.g., latent inhibition; Bouton et al., 2001). However, at this stage of research development, the key tasks relate to clarifying the nature of the puberty-anxiety association. To this end, the role of individual-difference and social-contextual factors, as well as variables that may mediate the puberty-anxiety relation need to be systematically and comprehensively addressed, irrespective of what type of anxiety serves as the outcome variable.

Conclusions The period of adolescence is characterized by both puberty and an increase in anxiety-related psychopathology, prompting researchers to examine the relation between the two. The available literature suggests there is a meaningful association between puberty and anxiety; for some youth (particularly females),

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the process of puberty appears to enhance anxiety-related symptoms, although there are a number of important gaps in the research base on which researchers could focus their investigative efforts, including improved methodological approaches and more sophisticated and comprehensive conceptual models. Nonetheless, this is a promising area of research; we hope the suggestions presented here will stimulate what we conceptualize as important future work aimed at clarifying the association between puberty and anxiety among youth.

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Anxiety, Anxiety Disorders, and the Menstrual Cycle Sandra T. Sigmon and Janell G. Schartel

Fluctuations in mood, bodily sensations, and behavior have long been associated with the premenstrual phase of the menstrual cycle. Research has found that women with psychological disorders often experience symptom exacerbation and psychiatric admission rates are increased during the premenstrual phase (e.g., Hendrick, Altshuler, & Burt, 1996). There are a few studies focusing on the follicular or intermenstrual phase of the menstrual cycle but the majority has focused on the premenstrual phase. This chapter covers the empirical research on the relationship between anxiety, anxiety disorders and the premenstrual phase of the menstrual cycle; however it is not an exhaustive review of the literature on menstrual cycle effects. There is a significant premenstrual literature on depression and other mood states; however this chapter focuses on anxiety. The complex relationship between anxiety and menstruation is presented by (1) identifying the continuum of experience of premenstrual anxiety, (2) addressing issues in assessment and treatment, (3) reviewing the literature on the premenstrual experience of normal and clinical samples of women, (4) discussing current models used to explain this relationship, and (5) briefly reviewing how health behaviors are influenced by the menstrual cycle. Anxiety is discussed both as a common symptom of menstrual distress and as clinical disorders that are influenced by the menstrual cycle. Limitations of the current literature and suggestions for future research are also presented.

The Menstrual Cycle Phases of the normal menstrual cycle are typically based on a 28-day timeline that corresponds to changing hormone levels in a woman’s body (e.g., Hillard & Deitch, 2005). The normal range of women’s cycles varies from 24–35 days. The Sandra T. Sigmon University of Maine, 5742 Little Hall, Orono, ME 04469-5742, Tel: 207-581-2049, Fax: 207-581-6128 [email protected]

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uterus, ovary, and pituitary play a large role in menstrual cycle functioning with the hypothalamus playing a central control function. Research in the menstrual literature has typically delineated 3 distinctive phases: follicular (days 1–13), ovulation (days 13–14), and luteal (days 15–28). Days 1–7 represent menses and days 21–28 are generally considered the premenstrual or late luteal phase of the cycle.

Premenstrual Symptoms and Disorders Premenstrual Symptoms. Menstrual cycle fluctuations in mood and behavior have been addressed for over 2500 years (e.g., Hippocrates [600 B.C.] described premenstrual complaints) in Western and non-Western cultures (e.g., Chrisler & Caplan, 2002; Hylan, Sundell, & Judge, 1999). Epidemiological surveys suggest approximately 75% of menstruating women experience premenstrual symptoms each month (APA, 2000). Approximately 40% of women experience premenstrual and menstrual symptoms of a mild nature with only 2–10% reporting severe symptoms (e.g., Logue & Moos, 1986). Over 150 symptoms have been identified with the premenstrual phase of the menstrual cycle, the most common domains being affective (e.g., depression, anxiety, irritability, mood lability), somatic (e.g., bloating, breast tenderness), and behavioral (e.g., difficulty concentrating, overeating). Symptoms of anxiety include physiological sensations, emotional and cognitive symptoms, as well as behavioral symptoms. Typical anxiety symptoms associated with the premenstrual phase include muscle tension, stomach pain, feeling restless or irritable, difficulty concentrating, and avoidance behaviors. Premenstrual Syndrome. There are no universal or uniform definitions for premenstrual syndrome [PMS] (e.g., Johnson, 2004), but the defining factor is typically presence of symptoms exclusively during the late luteal phase. To assist researchers and foster more uniformity in PMS research, the American College of Obstetricians and Gynecologists (ACOG, 2000) proposed the following criteria: symptoms must only occur five days prior to menses onset, remit by day 4 of menses and symptoms must be absent during the follicular phase (or symptom free for at least one week). These criteria also require prospective reporting for 2 consecutive cycles to document the pattern. There are two consistent aspects of PMS examined in the literature; (1) the timing of the symptoms, and (2) the symptoms must be distressing and interfere with normal functioning. Premenstrual Dysphoric Disorder. A controversial debate ensued when Late Luteal Phase Dysphoric Disorder (LLPDD) was included in the DSM-III-R in 1987 and continued with the inclusion of Premenstrual Dysphoric Disorder (PMDD) in DSM-IV (APA, 1994). Women with LLPDD reported greater affective symptoms during the premenstrum than controls; however anxiety symptoms do not reach the level of severity reported by women diagnosed with

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anxiety disorders such as panic disorder (Veeninga, de Rutter, & Kraaimaat, 1994). Although the estimates for women experiencing PMS symptoms are somewhat high, research indicates that only 3–8% of women may meet diagnostic criteria for PMDD (e.g., APA, 1994; Halbreich, Borenstein, Pearlstein, & Kahn, 2003). However, subsyndromal levels that may also result in severe impairment are estimated to occur in 13–18% of women. Currently, PMDD is diagnosed under ‘‘Depressive Disorder Not Otherwise Specified’’ and appears under ‘‘Criteria Sets and Axes Provided for Further Study’’ (APA, 2000). There are four major criteria for a diagnosis of PMDD to be assigned. First, at least 5 of 11 identified symptoms must meet the same criteria used for PMS. There are four core affective symptoms (depressed mood, anxiety, affective lability, and persistent irritability or anger), at least one of which must be present for diagnosis. This symptom pattern must occur in most menstrual cycles for at least one year. The second criterion for PMDD requires that the symptoms cause marked interference with work, school, social activities or relationships. Third, the symptoms cannot be an exacerbation of another diagnosable disorder. For example, a diagnosis of PMDD would exclude the many women with panic disorder who experience an exacerbation of their panic symptoms premenstrually. And finally, the symptom pattern must be verified by at least two consecutive cycles of prospective daily symptom ratings for two symptomatic cycles.

Issues and Methods of Assessment Retrospective versus Prospective Reporting. The research that exists on pmenstrual cycle effects in general has yielded inconsistent results. One reason may be that early research on menstrual cycle effects relied almost exclusively on women’s retrospective self-reports. Women often overestimate the exacerbation of their anxiety symptoms when asked to recall their symptoms retrospectively (e.g., Endicott & Halbreich, 1982; Rubinow, 1985). Indeed, many of the retrospective studies on anxiety and the menstrual cycle have found strong cyclic effects in that anxiety symptoms worsen during the premenstrum (Breier, Charney, & Heninger, 1986; Cameron, Kuttesch, McPhee, & Curtis, 1988; Williams & Koran, 1997). Retrospective accounts of the premenstrual experience have been hypothesized to reflect a reliance on stereotypical and cultural biases regarding the menstrual cycle (e.g., McFarland, Ross, & DeCourville, 1989; Ruble, 1977). Prospective assessment of menstrual symptoms has addressed some of the concerns stemming from retrospective measures, yet has simultaneously presenting challenges to retrospective results, often finding no significant fluctuations premenstrually (e.g., Stein, Schmidt, Rubinow, & Uhde, 1989). Prospective studies that have shown menstrual fluctuations in anxiety disorder symptomatology suggest much smaller fluctuations than have been found in retrospective studies (Cameron et al., 1988; Cook et al., 1990). In the discussion

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of anxiety that follows, research will be discussed in terms of retrospective versus prospective methodologies. Assessment Measures. The gold standard for assessing any symptom across the menstrual cycle is prospective monitoring. Thus, fluctuations in anxiety across the cycle can be tracked by having women repeatedly complete any statedependent measure of anxiety or visual analogue scales focused for specific symptoms (e.g., frequency of panic attacks or obsessive-compulsive rituals). As one of the core symptoms of PMS and PMDD, anxiety and anxiety fluctuations across the menstrual cycle are often assessed within that context. There are several empirically supported measures for PMS and PMDD, all of which include items assessing anxiety (see Table 1). Readers are encouraged to see Haywood, Slade, and King (2002) for a review of retrospective and prospective measures of symptoms across the menstrual cycle. On retrospective measures, women are asked to consider either several recent menstrual cycles or to report on their typical experience across the menstrual cycle. Prospective measures typically take the form of a ‘‘daily diary,’’ asking women to indicate if a symptom did or did not occur or rate on a Likert scale the severity of individual symptoms each day. Some measures, such as the Premenstrual Tension Rating Scale (Steiner, Haskett, & Carroll, 1980) include both a self and observer rating form. Researchers and clinicians need to be aware of the format and the intended purpose of the assessment, as not all assessment measures are diagnostic in nature. A major difficulty with requiring prospective analysis over two months is time and effort to complete the measures. Many women are unable to complete daily ratings over several months’ time and many of the rating forms are

Table 1 Sample of measures used in assessing symptoms across the menstrual cycle Retrospective Measure Purpose (PMS/PMDD) or Prospective Premenstrual Tension Rating Scale, self and observer forms (Steiner et al., 1980) Daily Rating Form (Endicott et al., 1986) Premenstrual Symptom Diary (Thys-Jacobs et al., 1995) Calendar of Premenstrual Experiences (Mortola et al., 1990) Menstrual Distress Questionnaire (Moos, 1968) Menstrual Distress Questionnaire – Today version (Blake et al., 1998) Premenstrual Assessment Form (Halbreich et al., 1982) Daily Record of Severity of Problems (Endicott et al., 2006) Daily Symptom Rating Scale (Taylor, 1979)

Diagnostic and Treatment Response – PMS Assess Symptoms – PMS Diagnostic – PMS

Both

Diagnostic – PMS

P

Assess Symptoms – Both

R

Diagnostic – PMS; Treatment response

P

Assess Symptoms – Both

R

Diagnostic – PMDD

P

Assess Symptoms – Both

P

P P

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lengthy. Researchers have made efforts to validate short forms of empirically supported measures with limited success (Haywood et al., 2002). As such, it is common clinical practice for these forms to be adapted or for clinicians to create unique versions of these forms to suit the needs of their individual clients. However, clinicians should take several things into consideration when reformatting assessment measures. First, because of validity issues noted above, it is recommended to rate symptoms on a severity scale rather than in yes/no format (Freeman, 2003). Symptoms most relevant or most distressing to the client should be the focus of monitoring. Consolidating information into as few pages as possible increases compliance, reduces errors and minimizes data. One common way to do this is to have a monthly page, much like a calendar, rather than daily pages to record information (Freeman, 2003). Most importantly, women must make note of the first day of bleeding so that ‘‘menstrual time’’ can be established and accurate comparisons made between the follicular and luteal phases. Co-morbidity versus Premenstrual Exacerbation. With regard to assessment of menstrual-related symptoms, three options need to be considered: (1) is anxiety manifesting as a primary symptom of a menstrual problem, (2) are symptoms of an anxiety disorder worsening premenstrually, or (3) are symptoms consistent with a comorbid menstrual problem and anxiety disorder. Differentiating between comorbidity and premenstrual exacerbation (PME) may be one of the most difficult challenges facing researchers and clinicians. Anxiety disorders and menstrual difficulties are highly comorbid (see below). Specifically, Kim and colleagues (2004) found that panic disorder occurs in 25% of PMDD samples, social phobia in 19–23%, OCD 11–13% and GAD in 4–38% across studies. Moreover, many women with anxiety disorders report premenstrual exacerbation (PME) of their symptoms. Previous research has found that women with Generalized Anxiety Disorder (GAD), Panic Disorder (PD), and simple phobia (SP) report premenstrual worsening of their anxiety symptoms (e.g., Busch, Costa, Whitehead, & Heller, 1988). Moreover, 45–50% of psychiatric admissions for women occur during the premenstrual phase (e.g., Targum, Caputo, & Ball, 1991). Distinguishing PME from comorbidity presents challenges for women with PMS. Stout and colleagues (1986) found that in a sample of 223 women seeking treatment for PMS, 81% of the women had at least one psychiatric diagnosis lifetime with 65% meeting criteria for phobia and 16% meeting criteria for OCD. Hsiao, Hsiao, and Liu (2004) examined the prevalence of PMS and premenstrual exacerbation (PME) in 200 Chinese women and found that 78% of the women with GAD and 68 % of the women with PD met criteria for PMS. In addition, 52% of the women with GAD and 36% of the women with PD reported PME of their anxiety symptoms. The distinction between comorbidity and PME might stem from controversy surrounding the diagnostic validity of PMS and PMDD. Some researchers argue that PMDD is a distinct disorder with irritability and mood lability as defining features (e.g., Lande´n & Eriksson, 2003) rather than a subtype of

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depression or anxiety. Hartlage and Gehlert (2001) suggest the problem is that symptoms of PMDD overlap significantly with other affective disorders and argue for phase specificity in diagnosing PMDD (i.e., symptoms occur solely during the premenstrum). They propose that PME can be distinguished from PMDD if clinicians consider one symptom at a time. This leaves unresolved the possibility of some symptoms of an anxiety disorder occurring across the entire cycle while others do not. How many of the symptoms of PMDD must be distinct from the symptoms of the ongoing anxiety disorder remains unclear. The criteria of five symptoms has also been challenged as being arbitrary and too restrictive to accurately assess the impact of symptoms on women’s functioning (Smith et al., 2003; Freeman, 2003). Yonkers (1997) suggests that premenstrual complaints can vary in severity, degree of comorbidity with other psychological disorders and level of impairment. For example, a woman may only demonstrate two out of five symptoms, but they may be severe enough to cause significant interference with her day to day functioning. Researchers have also questioned the validity of defining and measuring the ‘‘absence’’ of a symptom. The requirement of symptom absence is unique to PMS/PMDD, and there are currently no good assessment measures that reliably measure this criterion. Furthermore, most criteria require symptoms be absent for the duration of the follicular phase. This requirement has been challenged as being unrealistic due to the natural fluctuations in mood and occurrence of life events over the course of the cycle (Freeman, 2003; Smith et al., 2003). For example, Bailey and Cohen (1999) assessed the number of women seeking treatment for premenstrual symptoms who experienced symptoms across the menstrual cycle. Over 60% of their sample met criteria for either a mood or anxiety disorder or both, indicating they experienced symptoms diagnostic of PMS across all phases of the cycle. Instead, researchers like Freeman (2003) suggest we would be better served to look at changes in symptom severity or overall frequency (i.e., degree of change). Although suggestions have been made (e.g., Smith et al., 2003), no conclusion has yet been reached regarding what would represent a clinically significant change from one menstrual cycle phase to the next phase. There is a significant amount of variability both between and within individual women’s symptoms from cycle to cycle. Bloch, Schmidt, and Rubinow (1997) looked at the stability of premenstrual symptoms in 16 women with PMS (defined as 30% increase in symptom frequency during the luteal phase) for 3 or more cycles. Results indicated that symptom presentation from cycle to cycle varied considerably, with anxiety (83%), irritability (85%), and mood lability (77%) exhibiting the most stability across the 3 cycles. Freeman (2003) also notes that the timing of symptom appearance/remission varies between women. Some women experience PME for only a few days of the premenstrual phase at either the beginning or end and some symptoms are experienced on nonconsecutive days. Thus, the literature suggests that in well-defined PMS samples, symptoms persist across time and can cause significant impairment in women’s

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lives even if two consecutive symptomatic cycles are not established during the diagnostic period.

Research on Premenstrual Anxiety Normal Samples. Normal samples of women have been studied extensively to ascertain the level of distress associated with the premenstrual phase. It should be noted that although most studies indicate a normal sample, typically no assessment has been made of pre-existing levels of trait anxiety or anxiety disorders. Studies utilizing retrospective methodology have demonstrated increases in negative affect (depressed mood and anxiety in particular) and increases in severity of physical symptoms during the premenstrual phase compared to the intermenstrual phase of the cycle (e.g., Boyle & Grant, 1992). Some prospective studies of menstrual cycle fluctuations in affective and somatic symptoms in normal populations have shown premenstrual effects (e.g., Gallant, Hamilton, Popiel, Morokoff, & Chakraborty, 1991) whereas others have failed to find increased symptoms during the premenstrual phase (e.g., Slade, 1984). When normal women report more anxiety during the premenstrual phase, the level of anxiety appeared to be more comparable to women who are mildly stressed, not to a clinical sample (Golub, 1976). This equivocal pattern was not clarified whether or not participants were informed of the true purpose of the study (e.g., Gallant et al., 1991). Although the majority of individuals who seek treatment for PMS are typically in their mid 20’s to mid 30’s, Hillard and Deitch (2005) found that 75% of older adolescents who visited a health care provider perceived a problem with menstruation. However, Golub and Harrington (1981) found no significant differences between premenstrual and menstrual physical or mood symptoms in 158 15–16 year old females. Moreover, they did not significantly differ from comparisons to same-age males during the same time period. In a prospective study (Layton, 1989), adolescent females reported elevated rates of state anxiety during the premenstrual phase compared to the menstrual phase. Although the findings for premenstrual worsening of mood symptoms vary in adolescent samples, it appears that premenstrual complaints are common across different age samples. Large community surveys have also been conducted to determine if women experience greater distress during the premenstrual phase of the menstrual cycle (e.g., Strine, Chapman, & Ahluwalia, 2005). As part of the 2002 National Health Survey, over 11,000 women from ages 18–55 completed a computerassisted personal interview. Approximately 19% of the sample indicated menstrual difficulties over the past year with white non-Hispanic women reporting more difficulties than Hispanic women and 16% reported interference from menstrual problems. In addition, women who reported menstrual problems were more likely to report psychological distress including anxiety, sleep

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difficulties, and negative health behaviors (e.g., smoking, drinking, obesity). Unfortunately, no associations between distress and cycle phase were assessed. A growing area of research on menstrual cycle effects examines physiological differences in normal women during phases of the menstrual cycle. Researchers have found phase differences in hypothalamic pituitary axis (HPA) functioning, specifically related to cortisol and DHEA (i.e., dehydroepiandrosterone) levels (Symonds, Gallagher, Thompson, & Young, 2004). Cortical activity has also been found to fluctuate across menstrual cycle phase in samples of normal women (Asso & Braier, 1982; Protopopescu et al., 2005). It has been suggested that varied levels of estrogen and progesterone across the menstrual cycle may affect neuronal circuitry (Protopopescu et al., 2005). Asso and Braier (1982) found increased skin conductance during the premenstrual phase compared to the intermenstrual phase in a normal sample of women. It is clear that more research needs to be conducted regarding normal menstrual cycle psychophysiology in order to inform how such processes may be impaired in women with anxiety disorders. Premenstrual Anxiety in PMS Samples. Similar to the findings in normal samples, there are mixed results in women self-reporting PMS with retrospective and prospective methods. Women with PMS retrospectively report higher levels of state (e.g., Haskett, Steiner, & Carroll, 1984; Mira, Vizzard, & Abraham, 1985) and trait anxiety (e.g., Giannini, Price, Loiselle, & Giannini, 1985; Watts et al., 1980) during the premenstrum. However, prospective self-reports of premenstrual changes have yielded inconsistent results (e.g., Sampson & Jenner, 1977; Taylor, 1979). In a sample of 69 undergraduate and community women, Kessel (2000) found women who experienced significant premenstrual changes (>30%) reported higher levels of anxiety compared to women who did not report severe changes. Christensen and Oei (1989) found that women with PMS prospectively reported more anxiety, depression, and automatic negative thoughts than controls during the premenstrual phase. Magos, Brincat and Studd (1986) found that retrospective and prospective reports of women seeking treatment for PMS were similar, with 61–85% reporting symptoms consistent with PMS. In contrast, Hardie (1997) found that none of the retrospective reports of PMS from their sample of 101 women were confirmed by 2 prospectively monitored cycles. Fluctuations in mood were better predicted by interpersonal relationship quality and stress level than cycle phase. Thus, anxiety fluctuations across the menstrual cycle in PMS populations are just as inconclusive as those in normal samples. Other research has focused on assessing attributions for PMS symptoms (e.g., Veeninga & Kraaimaat, 1995). For example, women with PMS were more likely than controls to attribute symptoms to their cycle when in the premenstrual phase than when they were in the intermenstrual phase. Women with PMS also reported more menstrual symptoms both premenstrually and during the intermenstrual phase (Veeninga & Kraaimaat, 1995). However, a large number of the women with PMS also met criteria for an anxiety disorder and thus this study

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could not distinguish between women with PMS alone or women with PMS who also met criteria for an anxiety disorder. Cross-cultural research in Western societies seems to parallel the results obtained in the United States. A study on women in the United States, United Kingdom, and France (N = 1045) revealed considerable impairment at home, in social relationships, and work. Across countries, more than 60% of women reported increases in anxiety, fears and tension premenstrually, and less than 25% had sought treatment for their symptoms (Hylan et al., 1999). Premenstrual Dysphoric Disorder. Researchers have estimated that the impact and burden associated with PMDD to be similar to that of other affective disorders (e.g., Halbreich et al., 2003). Wittchen, Becker, Lieb, and Krause (2002) contend that PMDD can persist for the duration of a woman’s reproductive years. In their research, depression was the first ranked symptom (91%) and anxiety was noted by 67% of the sample, with 47% of women with PMDD meeting criteria for a comorbid anxiety disorder. Several studies have found that comorbid anxiety disorders may be found in as many as 59% of women diagnosed with PMDD (Fava et al., 1992; Pearlstein, Frank, Rivera-Tovar, Thoft, et al., 1990). Research has also indicated that women with PMDD report more stressors and experience more distress premenstrually than intermenstrually compared to controls (e.g., Fontana & Badawy, 1997) and also report more state anxiety than controls (e.g., Christensen & Oei, 1989).

Menstrual Cycle Effects on Anxiety and Anxiety Disorders Anxiety Sensitivity. Anxiety sensitivity (AS; i.e., fear of symptoms of anxiety and its consequences; Reiss & McNally 1985) has been well-studied as a vulnerability to anxiety disorders, panic disorder in particular (e.g., Schmidt, Lerew, & Trakowski, 1997; Weems, Hayward, Killen, & Taylor, 2002) and gender differences in anxiety sensitivity may account for some of the gender differential in anxiety disorder prevalence rates. In a series of studies, Sigmon and colleagues have investigated the relationship between AS, self-reports of menstrual symptoms, gender roles, somatic beliefs, and psychophysiological reactions to anxiety stimuli across the menstrual cycle (Sigmon, Dorhofer, Rohan, & Boulard, 2000; Sigmon, Fink, Rohan, & Hotovy, 1996; Sigmon, Rohan, Boulard, Dorhofer, & Whitcomb, 2000). In the first study (Sigmon et al., 1996), women high or low in anxiety sensitivity were assessed during either the intermenstrual or premenstrual phase. Results indicated that women high in AS reported more severe premenstrual symptoms, more state and trait anxiety, and exhibited greater skin conductance responses to auditory anxiety-provoking stimuli than women low in AS, regardless of current cycle phase. Researchers proposed that women high in anxiety sensitivity are more likely to focus on internal stimuli, have a higher nonspecific arousal level, and negatively interpret normal bodily sensations. In addition to

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confirming greater premenstrual distress reported by women high in AS, two subsequent studies (Sigmon, Rohan et al., 2000; Sigmon, Dorhofer, et al., 2000) suggested that women high in AS may demonstrate more gender specificity (endorsing more feminine and less masculine characteristics), illness attitudes, and may be more vigilant to bodily sensations than women low in AS. The above results led Sigmon and colleagues to propose the menstrual reactivity hypothesis (Sigmon, Dorhofer, et al., 2000) which states that certain women (e.g., high in AS, women with asthma) are more likely to report greater menstrual distress due to accurate reports of symptoms, expectations about the meanings of symptoms, hypervigilance to bodily sensations, and increased psychophysiological responding in response to anxiety stimuli. The menstrual cycle may represent a cyclical stressor that provides increased opportunities for self-focus, symptom attribution and interpretation. The authors suggest that researchers should routinely assess for AS and for gender-related variables that could add to a more complete account of the relationship between the menstrual cycle and anxiety. Although existing research on menstrual effects and anxiety sensitivity has focused on AS as a continuous variable, recent research has found support for a latent structure that is taxonic (i.e., categorical in nature; e.g., Schmidt, Kotov, Lerew, Joiner, & Ialongo, 2005; Bernstein et al., 2005). In general, the taxon accounts for more variance than variables such as body sensations and body vigilance and possesses incremental validity in predicting future panic attacks. Bernstein and colleagues (2005) suggest that taxon criteria may differ across gender and population, pointing to the need for more research to determine if AS has a latent taxonic structure for women experiencing PME of an anxiety disorder and women for whom anxiety is the core symptom of a menstrual disorder. It is possible that taxon identification may be useful in identifying women who are vulnerable to menstrual cycle influences on anxiety and formulating successful treatment strategies.

Premenstrual Symptoms and Anxiety Disorders Anxiety represents a prominent premenstrual symptom for some women and comorbidity between premenstrual and anxiety disorders is high (e.g., Fava et al., 1992), however the course of specific anxiety disorders across the menstrual cycle is less clear. Few studies have investigated if and how specific anxiety disorders are affected by the menstrual cycle and that which does exist is complicated by issues surrounding retrospective and prospective recording. Panic Disorder. Although evidence suggests that panic disorder symptoms can be exacerbated premenstrually (e.g., Klein, 1993; Cameron et al., 1988), retrospective and prospective self-reports of menstrual symptoms are inconsistent. Given the similarity between certain premenstrual symptoms (e.g., muscle tension, hot flashes, increases in breathing rates, anxiety) and symptoms of panic, the ability to distinguish between the exacerbation of panic symptoms or the

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experience of premenstrual symptoms is complicated, regardless of the methodology used. Research on PME of panic symptoms assumes that women are able to accurately distinguish the causes of their symptoms, and symptom misattribution has been cited as a contributor to inconsistent findings as well as a significant component of panic disorder (Stein, Schmidt, Rubinow, & Uhde, 1989). Retrospective assessments suggest that a large proportion of women experience an increase in panic symptoms premenstrually. For example, Breier and colleagues (1986) found that more than half of women reported PME of their symptoms. Women in other studies have reported increases in severity of symptoms (Cameron et al., 1988), overall anxiety, frequency of panic attacks and phobic avoidance (Cook et al., 1990). Prospective studies have yielded mixed results with respect to PME of panic disorder. Cameron et al. (1988) found that women reported all symptoms as more severe retrospectively, but only muscle tension was statistically significant prospectively. Similarly, other researchers have failed to find premenstrual increases in overall levels of anxiety (e.g., Stein et al., 1989; Cook et al., 1990) or frequency of panic attacks (Cook et al., 1990). Women have also rated symptoms as more severe during the premenstrual phase. For example, Cook and colleagues (1990) found that approximately half of their sample prospectively rated one out of two menstrual cycles with a greater than 30% increase in panic symptom severity. In contrast, Kaspi, Otto, Pollack, Eppinger and Rosenbaum, (1994) found that panic attack frequency increased premenstrually whereas panic severity, avoidance, and anticipatory anxiety did not. Half of the participants in this study experienced twice as many panic attacks during the premenstrual phase compared to only 5 women who retrospectively reported symptom worsening. Unsubstantiated retrospective reports of premenstrual worsening only occurred in four out of twelve participants. Several reasons for these inconsistencies have been suggested. The experience of negative life events, fatigue, or other stressors may affect women’s experience of anxiety from one cycle to the next and assuming consistency across consecutive cycles may be inappropriate (Cook et al., 1990). The influence of beliefs about menstruation, social expectations or social roles may also play a part in women’s symptom expression (Sigmon, Dorhofer, et al., 2000). Memory biases (Cameron et al., 1988) and symptom misattribution during different phases have also been suggested. Natural fluctuations in anxiety might be mistakenly attributed to the menstrual cycle because it is a salient anchor point for women (Stein et al., 1989). Obsessive-Compulsive Disorder. Retrospective studies have suggested a significant portion of women with OCD experience premenstrual worsening of their symptoms (Labad et al. 2005; Williams & Koran, 1997). Interestingly, many of the women reporting premenstrual worsening also reported significant premenstrual mood symptoms indicative of PMS or PMDD (Williams & Koran, 1997). No studies utilizing daily prospective symptom monitoring have been conducted; however Vulink, Denys, Bus, and Westenberg (2006) assessed women at three time points concordant with menstrual, premenstrual,

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and intermenstrual phases of their cycles. Results indicated that half of the women reported PME of OCD symptoms. Generalized Anxiety Disorder. Only one study has investigated menstrual cycle relationships with GAD (McLeod, Hoehn-Saric, Foster, & Hipsley, 1993) and PTSD (Perkonigg, Yonkers, Pfister, Lieb, & Wittchen, 2004). McLeod and colleagues (1993) recruited women with GAD with and without comorbid PMS. Results indicated that women who had both GAD and PMS reported significant PME of anxiety symptoms during the luteal phase. Unfortunately, assessment points were not consistent between groups, making comparisons difficult. PTSD. Perkonigg and colleagues (2004) followed women with PTSD over a span of 42 months, assessing for predictors of PMDD at three time points. The best predictor of PMDD diagnosis was subthreshold PMDD symptoms at the initial interview. However, the experience of traumatic events and anxiety disorder presence both significantly predicted subsequently meeting diagnostic criteria for PMDD. PMDD symptoms were only assessed retrospectively and interviews were conducted without respect to menstrual cycle phase; however their results do suggest that trauma and anxiety may impact women’s experience of symptoms across the menstrual cycle. Although results across different disorders, populations, and methods of reporting have been inconsistent, there is nonetheless some evidence to suggest that for some women, menstrual cycle phase may have a significant impact on their experience, or at least the reporting of symptoms. Symptom patterns may also vary from cycle to cycle and may be related to life events, stress, fatigue, interpersonal or relationship problems. Many authors have suggested that this heterogeneity both between and among women may interfere with accurate diagnosis and interpretation of effect sizes in treatment studies (Vulink et al., 2006). Given recent advances in statistical methods for prospective data and in general understanding of anxiety disorders, more research investigating menstrual cycle effects on women’s experience of anxiety is warranted.

Models of Anxiety-Premenstrual Cycle Phase Interaction Feminist Views. Chrisler and Caplan (2002) provide an excellent overview of the evolution of scientific thought regarding PMS. The authors discuss the implications surrounding the medicalization of the menstrual cycle and the promulgation of ‘‘the belief that the (menstrual) cycle itself is a problem to be solved’’ (p. 283). Ussher (2003) also discusses hegemonic truths that need to be carefully scrutinized: ‘‘PMDD as a thing that can be objectively defined and measured; PMDD is pathology to be eradicated; PMDD is caused and treated by one factor; PMDD as a bodily phenomenon, and PMDD causes women’s symptoms’’ (p. 131). In a similar vein, Clare (1983) argues that it may be unrealistic to assume that women would be symptom free during any given menstrual cycle given that the symptoms that are most reported are ubiquitous

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to humans. To study any aspect of the menstrual cycle without the contexts of stress and lifestyle will result in incomplete assumptions (e.g., Koeske, 1983). Thus, feminist views about the menstrual cycle mirror similar concerns that have been raised in other approaches. Biological Explanations. Reproductive hormones play a significant role in mood symptom fluctuation across the menstrual cycle; however, the exact mechanisms involved are not well understood (e.g., Hendrick, Altshuler, & Burt, 1996). Progesterone metabolites and estrogen levels typically decrease during the premenstrual phase and remain low through the early follicular phase. These hormones modulate neurotransmitter levels (e.g., serotonin, GABA, dopamine, norepinephrine) that are hypothesized to play an important role in the development and maintenance of psychological disorders, in particular anxiety and depression (e.g., Dubrovsky, 2006; Le Melle´do & Baker, 2002). This area of research is relatively new and is hampered by the use of small samples, retrospective methodology, and lack of precision in determining menstrual cycle phase. Biological explanations of PMS typically begin with a discussion of hormonal control of the menstrual cycle. The development of premenstrual symptoms is purported to be linked to the rapid decrease in progesterone during the late luteal phase (e.g., Poromaa, Smith, & Gulinello, 2003). However women with and without PMS often do not show differences in absolute levels of progesterone across the menstrual cycle (e.g., Rubinow et al., 1988; Hammarba¨ck, Damber, & Ba¨ckstro¨m, 1989). Thus, researchers have proposed that there may be differences in sensitivity to the changing hormone levels (e.g., Poromaa et al., 2003; Halbreich, 2003). In addition, because progesterone metabolites enhance GABA (i.e., gamma-aminobutyric acid) activity (e.g., Olsen & Sapp, 1995) and GABA has been implicated in anxiety symptoms (e.g., Ninan et al. 1982), researchers have proposed models of complex hormonal interactions that may link premenstrual symptoms and anxiety disorders (e.g., Facchinetti, Tarabusi, & Nappi, 1998). However, more research is needed to determine the mechanisms affecting sensitivity to these interactions (Roy-Byrne, Cowley, Greenblatt, Shader, & Hommer, 1990). Research has also demonstrated several biological links between menstrual disorders and anxiety disorders. Women diagnosed with PMS and LLPDD (i.e., Late Luteal Phase Dysphoric Disorder) report increased in panic symptoms, negative interpretations of sensations, and state anxiety in response to a lactate challenge (e.g., Facchinetti et al., 1998; Kent et al., 2001). Further, approximately 60–70% of women with panic disorder and with LLPDD experience panic attack in response to lactate infusion and inhaled carbon dioxide. Panicogenic responding to challenge tasks was previously thought to be specific to panic disorder, and the similar rates of responding may suggest a shared biological vulnerability and account for the high levels of anxiety reported by LLPDD patients (for a review see Vickers & McNally, 2004). Other evidence to support a link between PMS and anxiety disorders comes from the responsiveness to alprazolam in women with PMS (e.g., Facchinetti et al., 1998). Although

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these findings are preliminary, they do suggest intriguing links between anxiety symptoms and PMS. Biological links between PMDD and anxiety have also been explored. For example, symptoms disappear or decrease in women diagnosed with PMDD when they do not ovulate, when ovaries are removed, or when they take medications that inhibits ovulation (e.g., Steiner, 2000). Biopsychosocial Models. More complex models of menstrual distress incorporating social and psychological processes are surfacing as it has become clear that biological explanations alone cannot suffice (e.g., Anson, 1999). A woman’s experience of premenstrual symptoms is influenced by socialization practices and environmental contextual factors (e.g., Anson, 1999). Menstrual attitudes and beliefs that develop from interactions with peers, family, and the media (e.g., Aubuchon & Calhoun, 1985; Woods, Mitchell, & Lentz, 1995) may play a significant role in the reporting and experience of premenstrual symptoms. Reports of premenstrual complaints vary depending on retrospective reports (e.g., Marva´n & Corte´s-Imiestra, 2001; Rapkin, Chang, & Reading, 1988), number and severity of daily and life stressors (e.g., Fontana & Palfai, 1994), use of maladaptive coping strategies (Sigmon, Whitcomb-Smith, Rohan, & Kendrew, 2004), complex role conflicts (e.g., Ross & Steiner, 2003), and history of sexual abuse (e.g., Ross & Steiner, 2003). These represent but a few of the factors proposed to play a contributory role in the experience and reporting of premenstrual difficulties. Researchers have also examined the role that the perception of stress and interference with functioning might play in the reporting of increases in anxiety during the premenstrual phase. Davydov and colleagues (2004) assessed anxiety symptoms during the luteal and follicular phases in nurses, who reported higher levels of anxiety on working days during the luteal phase than during days off during the luteal phase or during the follicular phase. Studies examining menstrual interference in college samples (e.g., Brooks-Gunn & Ruble, 1986) have found that perceived interference, menstrual pain, and premenstrual pain were the best predictors of emotional distress. The menstrual cycle itself has been conceptualized as a stressor (e.g., Logue & Moos, 1986). Elliott and Harkins (1992) found that for normal women menstrual and premenstrual pain and perception of interference were the strongest predictors of emotional distress. According to the authors, results provided support that how individuals appraise or perceive interference from a particular condition or stressor (e.g., menstrual cycle) may represent an important component in stress and coping processes.

Treatment Approaches for Premenstrual Anxiety There are several treatment options available for women who experience significant levels of anxiety either as a result of PME or as a core symptom of PMS or PMDD. Efficacious treatments include lifestyle changes, medications,

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hormone supplements, and psychotherapy. Researchers have suggested that when there are questions of comorbidity, patients should be treated first for the primary anxiety disorder, as many premenstrual symptoms will resolve with its effective treatment and additional treatment for residual premenstrual symptoms can then be provided (e.g., Steiner & Born, 2000). Lifestyle changes, stress management and/or dietary supplements (e.g., Clayton, 2003; Steiner & Born, 2000) are often recommended as the first step in treatment. Establishing and maintaining a regular sleep-wake cycle (Clayton, 2003) and regular exercise may reduce the severity and impact of both physical symptoms and anxiety during the premenstrum (e.g., Kirkby & Linder, 1998; Hightower, 1997). Studies have found particular positive effects of exercise on anxiety disorders such as OCD (Lancer, 2005) and PTSD (Manger, 2005). Various forms of psychotherapy have been found to be helpful in alleviating menstrual difficulties and may have implications for anxiety symptoms. Although random controlled trials on psychotherapeutic interventions for menstrual-related problems are few, the existing research is promising. Relaxation training has been shown to be superior to a distracting activity such as leisure reading and to symptom monitoring (Goodale, Domar, & Benson, 1990) and coping skills groups have demonstrated superior efficacy to relaxation and hormone therapy (Morse, 1999). Cognitive-behavior therapy for PMS has demonstrated effectiveness in both group and individual format (Morse, 1999; Slade, 1984) when compared to placebo treatments (Kirkby, 1994) and wait list control (Blake, Salkovskis, Gath, Day, & Garrod, 1998). Educational groups have demonstrated effectiveness when compared to CBT groups (Christensen & Oei, 1995). As with most forms of CBT, it is critical that a strong, collaborative therapeutic alliance between patient and therapist be established. Most women who experience menstrual-related problems typically adhere to medical explanations for their problems (Hunter, Ussher, Cariss, Browne, Jelley, & Katz, 2002). Thus, it is important for therapists to explain the biopsychosocial model (presented in next section) as an alternative, more complete framework from which women can understand their symptoms and their impact on their lives (Blake et al., 1998). When presented with a biopsychosocial model, most women find it an acceptable alternative to traditional medical explanations and subsequently report more active cognitive and behavioral coping strategies (Hunter et al., 2002). Specific components of CBT for PMS typically consist of teaching coping skills, identifying symptom triggers and maintaining factors, identifying and challenging cognitive distortions, and implementing behavior change strategies (Blake et al., 1998). Other therapies include cognitive restructuring and assertiveness training (Christensen & Oei, 1995). Women receiving CBT for PMS have shown greater reductions in symptoms and irrational thinking compared to placebo control therapy through 9-month follow up (Kirkby, 1994) and reductions in impairment, depressive symptoms, and prospective ratings of both physical and mood symptoms when compared to

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a wait-list control condition (Blake et al., 1998). However, CBT may be more effective for managing depressive symptoms than anxiety symptoms, as some studies have found no reduction in anxiety scores following treatment (Blake et al., 1998). CBT has demonstrated equal efficacy to medication (i.e., fluoxetine) in treating PMDD with better maintenance after one year (Hunter et al., 2002 ). A combination of medication and psychotherapy did not demonstrate any additional benefits to each alone. It is interesting to note, that women treated with fluoxetine reported greater improvement in anxiety than those who received CBT. The authors attributed this to either the known anxiolytic effects of the medication or the tendency for CBT to focus on depressive symptoms and not anxiety. Selective serotonin reuptake inhibitor (SSRI) anti-depressants have been found to be effective for alleviating symptoms of PMS and PMDD (see Kornstein & Smith, 2004). Only two controlled trials have demonstrated efficacy for intermittent dosing of anxiolytic medication for treating PMS (e.g., Freeman, Rickels, Sondheimer, & Polansky, 1995). However, treatment with SSRIs can result in decreases in both anxiety and depression symptoms, with the option to add anxiolytics if residual anxiety symptoms remain (Rapkin, 2003). Several reviews of the existing literature on antidepressant treatment of PMS and PMDD are available (e.g., Kornstein & Smith, 2004; Dimmock, Wyatt, Jones, & O’Brien, 2000). Clearly, more research is needed on what components of psychological and biological treatments are effective for anxiety symptoms across the menstrual cycle.

Health Behaviors and the Menstrual Cycle Health behaviors seem to be significantly impacted by anxiety and menstrual distress. It is well-established that anxiety problems are associated with negative health behaviors such as drug and alcohol use (e.g., Strine, Chapman, Kobau, & Balluz, 2005). Unfortunately, very little research has been done with specific regard to anxiety across the menstrual cycle and health behavior, thus this brief section is intended to provide an overview of how general symptoms associated with menstrual distress influence women’s behavior. Results of the National Health Interview Survey indicated that women reporting menstrual problems were more likely to report frequent anxiety, nervousness, restlessness and were also more likely to engage in health risk behaviors (e.g., smoking, drinking, overeating) than women reporting no menstrual problems (Strine, Chapman, & Ahluwalia, 2005). Both physical and affective menstrual symptoms have been positively associated with smoking (e.g., Sloss & Frerichs, 1983), alcohol use (e.g., Tobin, Schmidt, & Rubinow, 1994), and caffeine intake (e.g., MacKay, 1985). Affective symptoms may be more strongly associated with negative health behaviors (Woods et al., 1992).

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There is some evidence to suggest that negative health behaviors may increase during the premenstrum. Smoking in particular may be likely to increase during the premenstrual phase both for women without menstrual disorders (Kritz-Silverstein, Wingard, & Garland, 1999) and for women with PMDD (Pomerleau, 1996). In addition, women may experience more cravings or have a more difficult time quitting during the premenstrum (see Carpenter, Upadhyaya, LaRowe, Saladin, & Brady, 2006 for a review). However, women may be more likely to relapse during menses (Frye, Ward, Bliss, & Garvey, 1992 as cited in Carpenter, Upadhyaya, LaRowe, Saladin, & Brady, 2006). Some research has found that women who quit during the luteal phase rated withdrawal symptoms worse than those who quit during the follicular phase and shown positive correlations between withdrawal distress and menstrual distress (O’hara, Portser, & Anderson, 1989). Alcohol consumption has been shown to increase premenstrually by both retrospective (e.g., Harvey & Beckman, 1985) and prospective (e.g., Epstein, Rhines, Cook, Zdep-Mattocks, Jensen, & McCrady, 2006) reports. However such increases might only be related to those suffering from severe premenstrual distress (Griffin, Mello, Mendelson, & Lex, 1987), as results have not been consistent (e.g., Abraham & Mira, 1989). In contrast, Tobin and colleagues (1994) found that women with PMS prospectively reported more alcohol use than controls over the course of the menstrual cycle, not just the premenstrum. Physical activity is a positive health behavior that is supported as a protective factor both for physical and mental health problems including anxiety (e.g., Petruzello, Landers, Hatfield, Kubitz, & Salazar, 1991). Kirkby and Lindner (1998) found that increases in trait anxiety from mid-cycle to premenstrum were common in sedentary women with a history of PMS; however there were no changes in self-reported anxiety among women who exercised. Adolescent girls who reported severe menstrual symptoms also reported the least amount of physical activity (Teperi & Rimpela, 1989). Menstrual distress and health behaviors are thus closely associated; however it has been difficult for researchers to determine causation. One reason may be that women are attempting to self-medicate through the use of substances or through decreasing the amount of physical activity in which they engage. Conversely, negative health behaviors may make women more vulnerable to a wide array of health conditions including menstrual distress (Teperi & Rimpela, 1989). In addition, research in this area to needs to distinguish between the impact of the physical and affective symptoms of menstrual distress.

Summary of Research on Anxiety and the Menstrual Cycle Inconsistencies abound in the literature on anxiety and the menstrual cycle. Different definitions and different methodologies used by researchers contribute to equivocal results. In general, it may be safe to conclude that a significant

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number of normal women and those suffering from menstrual or clinical anxiety disorders may experience increased anxiety symptoms during the premenstrual phase. Prospective assessment of at least 2 months is necessary to determine if the anxiety symptoms only increase during the premenstrual phase. Such a determination is crucial given that different treatment options may be warranted. If anxiety symptoms persist across all phases of the menstrual cycle, then treatment may be focused more on anxiety than phase-specific effects. Thus, assessment and treatment decisions are crucial given the possible complex relationships between anxiety and the premenstrual phase.

Limitations in Existing Research In this review, several issues have been delineated that make the literature on anxiety, its disorders and menstrual cycle phases difficult to summarize. Retrospective and prospective methods of reporting anxiety symptoms across the menstrual cycle reveal many inconsistent findings. Researchers are often unclear about whether they are discussing anxiety as a symptom caused by the premenstrual phase of the menstrual cycle or the exacerbation of a pre-existing anxiety disorder. The menstrual literature is replete with differing definitions of premenstrual complaints, menstrual cycle timing, and premenstrual exacerbation of existing pathologies. Conceptually, researchers need to reach consensus on diagnostic criteria for premenstrual difficulties and premenstrual exacerbation of psychological disorders. In addition, researchers need to be more consistent in definitions and lengths of menstrual cycle phases. It may be time for researchers to conduct more translational research in which both camps agree on these matters.

Future Research Although anxiety is often associated with premenstrual complaints and premenstrual exacerbation of anxiety disorders has been documented, more research needs to be conducted that distinguishes between the symptoms of anxiety disorders and premenstrual disorders. The complex interactions of steroidal hormones with neurotransmitters associated with the development and maintenance of anxiety and its disorders deserves more attention. Following the tenets of the biopsychosocial approach to understanding premenstrual difficulties may prove useful in research that attempts to disentangle some of the complexities of these relationships. In addition, prevention research in adolescence that targets emotional vulnerability factors, such as anxiety sensitivity may be helpful. There continues to be a great need for more basic research on furthering our understanding of the physiological and psychological bases of how menstrual

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cycle phases and anxiety interact. More information is also needed to increase our understanding of how beliefs, expectations, cultural ‘‘knowledge’’, and personal experiences influence the experience, reporting, and attribution of symptoms as well as the perception of control over them. A taxometric approach may also be helpful in investigating emotional vulnerability factors in the prediction of premenstrual anxiety. Finally, measurement issues need to be addressed. The use of prospective monitoring over longer periods of time coupled with agreement over definitions of premenstrual concepts needs to standardized. In general, the relationship between menstrual cycle effects and anxiety symptomatology needs further refinement.

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Pain and Anxiety Disorders Gordon J. G. Asmundson, Murray P. Abrams, and Kelsey C. Collimore

Introduction There is growing evidence that chronic pain, typically that which is associated with the musculoskeletal system (e.g., arthritis, low back pain, fibromyalgia), frequently co-occurs with the anxiety disorders. This co-occurrence is often overlooked in practice because it is neither standard protocol nor obvious that clinicians consider pain experiences in the context of screening or assessment of anxiety disorders. Yet, people with both an anxiety disorder and chronic musculoskeletal pain typically present with greater distress and functional impairment compared to those with only one of these conditions. As a result, both assessment and treatment can be complicated. The goals of this chapter are several. First, we review the core characteristics of acute and chronic pain, and present data regarding the extent of its co-occurrence with the anxiety disorders. Second, we summarize models that have been offered to explain the co-occurrence of these conditions. Third, we review evidence supporting the postulates of these models. Fourth, we discuss practical issues that are intended to improve assessment, treatment, and outcomes for people who present with an anxiety disorder accompanied by clinically significant pain. Much of the discussion focuses on the relationship between chronic musculoskeletal pain and posttraumatic stress disorder (PTSD), as it is the anxiety disorder that has received the most empirical attention in this context. We conclude with a brief outline of issues that warrant future research attention.

Gordon J. G. Asmundson Anxiety and Illness Behaviours Laboratory, University of Regina, Regina, Saskatchewan, S4S 0A2, Tel: (306) 347-2415, Fax: (306) 585-4854 [email protected]

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Understanding Pain Pain was once conceptualized strictly as a sensory experience resulting from stimulation of specific noxious receptors, such as might occur at the time of physical injury or from progressive disease. We now understand that pain is more than sensation. Contemporary models of pain recognize that it is a complex perceptual experience that is determined by sensory as well as psychological (i.e., thinking, emotions, behaviors) and social influences (Asmundson & Wright, 2004). Generally speaking, we experience pain in order to adapt to and survive in our environment; that is, pain alerts us that potential or actual tissue damage may be pending, and it motivates us to take action to limit damage and recover from it (Wall, 1978). Compelling evidence for the adaptive significance of pain comes from observations of people who have a rare autosomal recessive genetic disease called congenital analgesia. These individuals do not experience pain and, as a consequence, often die in childhood from the effects of undetected (i.e., painless) life threatening injuries or disease (for review, see Nagasako, Oaklander, & Dworkin, 2003). For most people, physical injury or disease is accompanied by pain. This pain typically abates with recovery. However, for some people pain becomes chronic (i.e., persists for three months or more; International Association for the Study of Pain, 1986), losing its adaptive qualities and, instead, causes considerable emotional distress and impairment of social and occupational abilities. Many people with chronic pain make frequent physician visits, sometimes undergo inappropriate medical evaluations, and miss work and other important activities because of their symptoms and associated suffering (e.g., Gureje, Von Korff, Simon, & Gater, 1998). As a result, chronic pain has become one of the most common chronic health conditions in North America. Estimates from the US indicate that approximately 7% of the general population has experienced chronic pain in the past 12 months (McWilliams, Cox, & Enns, 2003) at a cost of about $100 billion annually (Weisberg & Vaillancourt, 1999). While chronic pain is often associated with these negative outcomes, it is important to note that some people with chronic pain cope effectively with the pain, and adapt to it in a manner that does not impose limitations on their wellbeing. In recent years it has become increasingly evident that a substantive number of people who have an anxiety disorder also have chronic pain symptoms. Likewise, people with chronic pain frequently report significant expressions of fear and anxiety, often at levels and with impacts that warrant diagnosis of an anxiety disorder. Fear and anxiety specific to pain, while prevalent in some people with chronic pain, are not the focus of this chapter; these constructs are discussed in detail elsewhere (e.g., Asmundson, Vlaeyen, & Crombez, 2004). Below we review the available data on the epidemiology of co-occurring clinically significant pain and anxiety disorders in both community and treatmentseeking samples. It is noteworthy that chronic musculoskeletal pain has

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received the vast majority of theoretical and empirical attention with regard to co-occurrence with the anxiety disorders; thus, unless otherwise indicated, it will be the focus of much of the discussion that follows.

Epidemiology Prevalence of Anxiety Disorders in Pain Samples Investigators have consistently observed that rates of some anxiety disorders are elevated in people with chronic musculoskeletal pain. Table 1 and Table 2 show the 12-month prevalence of various anxiety disorders in people reporting primarily chronic musculoskeletal or migraine headache pain in community and treatment seeking samples, respectively. In community samples, the most prevalent past 12-month anxiety disorders were specific phobia (formerly simple phobia; ranging from 12.5% to 15.7%), social anxiety disorder (SAD; ranging from 8.3% to 11.8%), and PTSD (ranging from 7.3% to 10.7%). This pattern of findings is consistent with, but higher than, the general US population 12-month prevalence rates (i.e., specific phobia, 8.7%; SAD, 6.8%; PTSD, 3.5%; Kessler, Chiu, Demler, & Walters, 2005). In a large (N=85,088) survey of community dwelling adults from 17 countries, Demyttenaere et al. (2007) most recently reported pooled results indicating that those with back or neck pain, compared to those without, were approximately two times more likely to have had past 12-month panic disorder (PD)/agoraphobia and SAD, and almost three times more likely to have had generalized anxiety disorder (GAD) or PTSD. Raphael, Janal, Nayak, Schwartz, and Gallagher (2006) have likewise reported that community-dwelling women with fibromyalgia were five times more likely than others to have had a lifetime diagnosis of obsessive-compulsive disorder (OCD), four times more likely to have had PTSD, and more than four times as likely to have had GAD. In treatment seeking samples the most prevalent past 12-month anxiety disorders were phobic disorders (including SAD; ranging from 9% to 13%), followed generally by GAD (ranging from 0% to 13.4%) and PD (ranging from 1% to 7.2 %). Twelve-month prevalence of any anxiety disorder was 26.5% to 35.1% in community samples with chronic pain, and 8 to 28.8% in treatment seeking samples with chronic pain, both elevated relative to the general population (18.1%; Kessler, Chiu, et al., 2005). Lifetime prevalence of various anxiety disorders reported by patients with chronic musculoskeletal pain, as illustrated in Table 2, have been elevated relative to the general population (Kessler, Berglund, Demler, Jin, & Walters, 2005) in some (Atkinson, Slater, Patterson, Grant, & Garfin, 1991), but not all (Kinney, Gatchel, Polatin, Fogarty, & Mayer, 1993; Polatin, Kinney, Gatchel, Lilio, & Mayer, 1993), studies. It is noteworthy that the 12-month and lifetime prevalence rates for PTSD in the treatment seeking chronic pain samples described in Table 2 were neither

Nationally representative sample of the U. S. population (n = 3032)

Nationally representative sample of the U. S. population (n = 5692)

McWilliams et al. (2004)

Von Korff et al. (2005)

DSM-III-R

National Comorbidity Survey Replication (NCS-R)

DSM-IV

Midlife DSM-III-R Development in the United States Survey (MIDUS)

National Comorbidity Survey Part II (NCS)

Arthritis (n = 588) Panic attacks GAD Migraine (n = 340) Panic attacks GAD Back pain (n = 614) Panic attacks GAD 13.0 6.2

17.4 9.1

11.2 5.6

Chronic pain (arthritis; n = 382) Any anxiety disorder 35.1 PD 6.5 AWHPD 8.4 SP 11.8 SiP 15.7 PTSD 10.7 GAD 7.3 No arthritis Panic attacks GAD No migraine Panic attacks GAD No back pain Panic attacks GAD

5.3 2.5

5.5 2.5

5.8 2.7

General population (n = 5495) Any anxiety disorder 18.1 PD 1.9 AWHPD 3.3 SP 7.8 SiP 8.3 PTSD 3.3 GAD 2.6

Chronic spinal pain (n = 2397) Any anxiety disorder 26.5 PD 4.8 AWHPD 1.3 SP 8.3 SiP 12.5 PTSD 7.3 GAD 6.4 Note: PD = Panic Disorder; AWHPD = Agoraphobia Without History of Panic Disorder; SP = Social Phobia (also called social anxiety disorder); SiP = Simple Phobia; PTSD = Posttraumatic Stress Disorder; GAD = Generalized Anxiety Disorder; Not all studies evaluated all anxiety disorders; All studies based on 12-month prevalence.

Nationally representative sample of the U. S. population (n = 5877)

McWilliams et al. (2003)

Table 1 Prevalence of anxiety disorders among persons with pain (community samples) Study Participants Data set Diagnostic criteria % Meeting criteria for an anxiety disorder

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Chronic low back pain patients (n = 97)

Chronic back pain patients (n = 90)

DSM-III

Mixed chronic pain patients (n = 283)

Fishbain et al. (1986) Atkinson et al. (1991)

Kinney et al. (1993)

DSM-III

Mixed chronic pain patients (n = 50)

Large (1986)

DSM-III-R

DSM-III

DSM-III

Mixed chronic pain patients (n = 37)

Katon et al. (1985)

DSM-III

Mixed chronic pain patients (n = 43)

Reich et al. (1983)

Table 2 Prevalence of anxiety disorders among pain patients (clinical samples) Diagnostic Study Participants Criteria

Any anxiety disorder Generalized disorder PD OCD Any anxiety disorder PD Phobic disorders OCD PTSD GAD

-

-

-

-

PD OCD Any anxiety disorder PD Phobic disorders OCD PTSD GAD

3.0 17.0 3.0 2.0 4.0

Generalized disorder

Any anxiety disorder

Any anxiety disorder (PTSD only) Any anxiety disorder (PD only) Any anxiety disorder GAD PD PTSD Any anxiety disorder

Current prevalence (%)

8.2 13.4 29.0

22.7

37.9

Lifetime prevalence (%)

3.0 13.0 3.0 2.0 4.0

7.2 8.2 25.0

13.4

28.8

8.0 4.0 2.0 2.0 19.4

16.2

7.0

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Chronic low back pain patients (n = 200)

Polatin et al. (1993)

DSM-III-R

Diagnostic Criteria Any anxiety disorder PD Phobic disorders OCD PTSD GAD 3.0 11.0 2.0 1.0 2.0

19.0

Lifetime prevalence (%)

Current prevalence (%) Any anxiety disorder

17.0

PD 3.0 Phobic disorders 9.0 OCD 2.0 PTSD 1.0 GAD 2.0 Asmundson et al. Chronic musculoskeletal pain patients DSM-IV Any anxiety disorder 17.0 (1996) (n = 200) PD 2.1 SP 11.0 SiP 2.7 OCD 0.0 PTSD 2.1 GAD 0.0 Note: PD = Panic Disorder; OCD = Obsessive-Compulsive Disorder; PTSD = Posttraumatic Stress Disorder; GAD = Generalized Anxiety Disorder; SP = Social Phobia (also called social anxiety disorder); SiP = Simple Phobia; Not all studies evaluated all anxiety disorders.

Participants

Study

Table 2 (continued)

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remarkable nor elevated relative to the general population. This may be a product of the nature of structured assessments employed in these studies; specifically, the PTSD module may have been skipped if the participant did not respond affirmatively to introductory questions regarding exposure to traumatic experiences, examples of which do not often include accidental or painful injury. Contrary to these unremarkable findings, several comprehensive reviews of the literature indicate that 10% to 50% of patients receiving rehabilitation services for chronic musculoskeletal pain and related conditions have PTSD (Asmundson, Coons, Taylor, & Katz, 2002; Otis, Keane, & Kerns, 2003). Moreover, the available data indicate that up to 45% of patients with pain subsequent to burn-related injury exhibit significant posttraumatic stress symptoms (Saxe et al., 2001). Overall, it appears that there is a high prevalence of some anxiety disorders in people with conditions characterized by chronic musculoskeletal pain. The most common appear to be PTSD, SAD, GAD, and possibly PD. However, there are notable limitations in the scope of inquiry to date. Additional investigation in samples seeking treatment for various chronic pain conditions, using structured and comprehensive assessment of current and lifetime occurrence of each anxiety disorder, is warranted.

Prevalence of Pain in Anxiety Disorder Samples A growing number of studies have assessed the prevalence of clinically significant pain conditions in people with anxiety disorders. Two of these studies have focused on pain reports in patients with PD. Kuch, Cox, Woszczyna, Swinson, and Shulman (1991) reported that nearly 40% (54 of 141) of their sample of consecutively referred patients with PD reported chronic pain, most commonly in the head, shoulders, and lower back. Almost 10% of those in the sample were using analgesic medications on a daily basis. Similarly, in a study of 71 patients with PD, Schmidt and Telch (1997) identified a variety of comorbid physical conditions, including chronic back problems (46%), arthritis (22%), irritable bowel syndrome (17%), heart conditions (13%), and other conditions such as migraine, cancer, and diabetes (24%). A substantial number (35%) had seen a physician in the last month, and most (89%) in the last year; however, only 6% had been hospitalized in the past six months. These studies provide preliminary evidence that chronic pain, particularly that of the musculoskeletal system, is prevalent in patients seeking treatment for PD. Acute and chronic pain are reported with striking frequency in people with PTSD (for review, see Asmundson et al., 2002). Upwards of 20% to 30% of those with PTSD seeking outpatient treatment from community and mental health clinics report chronic pain (e.g., Hubbard, Realmuto, Northwood, & Masten, 1995). Prevalence estimates of current chronic pain have, in most cases, been even higher in military veterans and volunteer firefighters with PTSD,

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ranging from 50% to 80% (for recent reviews, see Asmundson et al., 2002; Otis et al., 2003). Recent findings from a sample of female veterans using the Veterans Administration (VA) Health Care System confirm that these finding generalize across gender (Asmundson, Wright, & Stein, 2004). Road traffic collisions, work-related injury, and service in combat and emergency theatres are the most common events precipitating the development of PTSD accompanied by chronic pain (Asmundson, Norton, Allerdings, Norton, & Larsen, 1998; Beckham et al., 1997; Blanchard & Hickling, 2004). Sareen, Cox, Clara, and Asmundson (2005) recently used data from the US National Comorbidity Survey Part II to evaluate associations between the anxiety disorders and diagnoses of general medical conditions, including those for which pain is often a significant component. After controlling for socio-demographic variables and other common mental disorders, robust associations were found amongst PTSD, panic attacks, and agoraphobia and the physical disorders. Most strikingly, individuals with PTSD were more than twice as likely as others to have a past-year neurological disorder (e.g., multiple sclerosis), roughly twice as likely to have a past-year gastrointestinal disorder (e.g., ulcer, hernia), more than three times as likely to have a past-year metabolic or immune disorder (e.g., diabetes, lupus), two and one half times as likely to have a past-year bone or joint conditions (e.g., arthritis, rheumatisms, other bone/joint disease), and almost twice as likely as others to have one or more past-year physical disorders. Overall, it appears that conditions characterized by some degree of persistent pain are prevalent in people with anxiety disorders, particularly PTSD and panic-related conditions. This avenue of inquiry is in its infancy; thus, further investigation geared toward replication of findings in community and treatment-seeking samples, using comprehensive pain assessment batteries, is warranted.

Course Few studies have systematically investigated the extent to which anxiety disorders exist prior to the onset of pain, or vice versa. There is some evidence to suggest that anxiety disorders precede the onset of pain. In a sample of injured workers with chronic musculoskeletal pain, Asmundson, Jacobson, Allerdings, and Norton (1996) found that in all but one case, the anxiety disorder preceded the pain complaint. Kinney et al. (1993) found that among 90 chronic low back pain patients, 23% had a preexisting anxiety disorder. In the only prospective study to date, we recently demonstrated that PTSD symptoms measured prior to surgery made a unique contribution to the prediction of post-surgical pain disability in chronic pain patients undergoing general surgery (Martin, Dzyuba, Halket, Asmundson, Katz, 2007); thus, PTSD symptoms may be important in the development and/or maintenance of pain disability. There is also evidence

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that the probability of onset of an anxiety disorder before versus after pain onset is comparable. In a study of 97 chronic back pain patients, 30 of whom had a comorbid anxiety disorder, 46.7% reported onset of anxiety before pain, and 53.3% reported onset after pain (Atkinson et al., 1991). Additional research, particularly that which uses prospective methods, is needed to delineate the temporal sequence of co-occurring anxiety disorders and chronic pain.

Theoretical Overview The substantial degree of co-occurrence of the anxiety disorders and clinically significant pain experiences suggests that these conditions are related in some way. Yet, establishing co-occurrence provides neither an understanding of the nature of the associations between the conditions nor an understanding of the mechanisms by which they are linked. There are several possible scenarios that might explain the relationship. For any two variables (or, in this case, conditions), possible relationship scenarios are as follows: (1) one causes the other (i.e., the anxiety disorder causes pain or vice versa), (2) they influence one another in some mutually maintaining way (e.g., pain exacerbates symptoms of the anxiety disorder and vice versa), or (3) some third factor (e.g., a common predisposition, a shared environmental event) increases vulnerability to both. The second and third possibilities are not mutually exclusive. There are, to the best of our knowledge, no theoretical positions that explicate the first of the possibilities noted above; nor are there data to support the position that one condition causes the other. Several models, rooted in the second and third possibilities, have been recently posited to explain the relationship between the anxiety disorders and chronic pain. For the most part, they have been developed in the context of efforts to understand mechanisms underlying co-occurring PTSD and chronic musculoskeletal pain, and are based on tenets of empirically supported cognitive-behavioral models of each of these conditions (e.g., Ehlers & Clark, 2000; Foa & Rothbaum, 1998; Norton & Asmundson, 2003; Vlaeyen & Linton, 2000). Below we review these models and speculate on their value in explaining the association between the other anxiety disorders and chronic musculoskeletal pain.

Mutual Maintenance Model The mutual maintenance model (Sharp & Harvey, 2001) holds that certain components of PTSD (e.g., physiological arousal, absence of positive emotions, avoidance of trauma stimuli) maintain or exacerbate symptoms of pain and, similarly, that certain components of chronic musculoskeletal pain (e.g., physiological arousal, catastrophizing about pain, avoidance of physical exertion) maintain or exacerbate symptoms of PTSD. The model predicts, for

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example, that pain sensations experienced by a person with chronic musculoskeletal pain will be persistent and arousal-provoking reminders of the trauma that precipitated the pain. Physiological arousal in response to recollection of the trauma will, in turn, promote avoidance of pain-related activities and (over time) physical deconditioning, which makes the experience of pain more likely. The person thereby becomes trapped in a vicious cycle whereby the symptoms of PTSD and chronic musculoskeletal pain interact to produce self-perpetuating distress and functional disability.

Shared Vulnerability (Diathesis)/Stress Models We (Asmundson et al., 2002; Asmundson, & Taylor, 2006) and others (Otis et al. 2003; Turk, 2002) have extended the idea of mutual maintenance, suggesting that some maintenance factors may actually denote a shared vulnerability, or diathesis, for developing both conditions. The shared vulnerability model (see Fig. 1) holds that there are individual difference factors, possibly genetically influenced, that predispose people to develop PTSD and chronic musculoskeletal pain when exposed to certain environmental conditions. Specifically, the model suggests that the interaction of individual difference characteristics – a psychological vulnerability for feelings of loss of control (and anxiety), and a lowered physiological threshold for alarm reactions (i.e., activation of physiological processes that prepare one to fight or flee) to stressors – and instigating

Psychological Vulnerability (e.g., high injury sensitivity, high anxiety sensitivity) Autonomic Nervous System and Muscular Responsivity

Life Event (e.g. traumatic incident, injury)

Emotional Response (e.g. fear, anxiety, worry, agitation)

Avoidance of situations or activities perceived as negative

Hypervigilance and Cognitive Biases

Low Threshold for Alarm (e.g., sympathetic disregulation, hyperalgesia)

Fig. 1 Shared vulnerability model

Disabling Condition (specific or co-occurring)

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stressful events (e.g., traumatic incident, injury) explain the development of PTSD, chronic musculoskeletal pain, and their co-occurrence. To illustrate, PTSD is likely to occur in trauma-exposed people who are predisposed to react to traumatic stressors with alarm and feelings that the situation, and their emotional response to it, are beyond their control. Similarly, chronic musculoskeletal pain is most likely to develop in injured people who believe that the pain they are experiencing, and their emotional responses (e.g., anxiety, worry, fear, agitation) to it, are uncontrollable. The shared vulnerability model further predicts that co-occurring PTSD and chronic musculoskeletal pain are most likely to develop in cases where vulnerable people are exposed to an event that is both traumatic and painful, and that both reminders of the trauma and sensations of pain can serve as triggers for further alarm reactions. The latter is consistent with postulates of the mutual maintenance model and further illustrates how predisposing factors can contribute to maintenance of these conditions. Our understanding of co-occurring PTSD and chronic pain might apply to other anxiety disorders that frequently co-occur with chronic pain. Symptoms of physiological arousal and lack of positive emotions – both general characteristics of the anxiety disorders – may maintain or exacerbate symptoms of pain. Likewise, one or more aspects of the pain experience (e.g., physiological arousal, pain-related catastrophizing, avoidance of physical exertion) may maintain or exacerbate clinically significant symptoms of anxiety. For example, avoidance of physical exertion in persons experiencing persistent pain may result in avoidance of specific social environments (e.g., fitness center, sporting complex) which may, in turn, contribute to the maintenance of symptoms of social anxiety through rewards (i.e., anxiety reduction) derived from behavioral avoidance. Likewise, physiological arousal in these social environments may promote muscle tension, avoidance of pain-related activities, physical deconditioning, and an associated increase in muscle pain. As with PTSD, persons with other anxiety disorders may become trapped in a cycle wherein symptoms of anxiety and pain interact to promote clinically significant distress or impairment.

Summary It is plausible that postulates of the mutual maintenance and shared vulnerability models will prove useful in delineating why some, if not all, of the anxiety disorders are often accompanied by conditions characterized by chronic pain (and vice versa). Efforts to understand the mechanisms of co-occurrence are only just beginning; however, as summarized below, there is a growing body of support for these postulates emerging from investigations of co-occurring PTSD and chronic musculoskeletal pain.

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Overview of Empirical Support Evidence supporting the postulates of the mutual maintenance and shared vulnerability models has been culled in the context of pain that accompanies PTSD (or vice versa). Below we review this literature, with specific focus on symptom overlap, anxiety sensitivity (AS), selective attention for threat, and lowered threshold for alarm. These models have not heretofore been applied in the context of understanding the co-occurrence of chronic musculoskeletal pain and the other anxiety disorders. While it is likely that the models will prove useful in this regard, direct empirical evaluation of the model postulates in these contexts remain a direction for future consideration.

Symptom Overlap There is considerable symptom overlap between PTSD and chronic musculoskeletal pain. Both are characterized by somatic hypervigilance and (possibly) biases in attention toward threatening stimuli, heightened startle, emotional numbing (e.g., absence of positive emotion), avoidance, and dysregulations in stress response and pain modulation (for review, see Asmundson et al., 2002). These findings indicate that PTSD and chronic musculoskeletal pain share similar response patterns in the cognitive, behavioral, and physiological domains. There is also evidence to suggest that particular PTSD symptom clusters are more closely associated with certain aspects of the pain experience; for example, re-experiencing symptoms are uniquely associated with pain severity, self-report of physical symptoms, and limitations in functional ability (Asmundson, Wright, et al., 2004; Beckham et al., 1997; Zoellner, Goodwin, & Foa, 2000), whereas hyperarousal is associated with detection of pain (Asmundson, Wright, McCreary, & Pedlar, 2003).

Anxiety Sensitivity AS (i.e., fear of anxiety based on the belief that it may have harmful consequences) is one of several individual difference factors that increase sense of danger and fearful responding. AS is elevated in patients with PTSD (Taylor et al., 2001, 2003) and in some patients with chronic musculoskeletal pain (for review, see Asmundson, Wright, & Hadjistavropoulos, 2000), is positively correlated with the severity of PTSD symptoms (Fedoroff, Taylor, Asmundson, & Koch, 2000), increases the risk of pain-related avoidance and disability following physical injury (for review, see Keogh & Asmundson, 2004), and is partly influenced by genetic factors (Stein, Jang, & Livesley, 1999). Consequently, it has been postulated that AS is responsible for the extreme emotional

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responses to trauma and pain associated with injury, and that it denotes the specific vulnerability that predisposes people to develop both PTSD and chronic musculoskeletal pain (Asmundson et al., 2002; Asmundson & Taylor, 2006; Turk, 2002). It has yet to be established that elevated AS precedes the development of PTSD and chronic musculoskeletal pain; thus, it remains a possibility that AS becomes elevated as a consequence of PTSD and chronic musculoskeletal pain and thereafter serves to maintain symptoms (see Sharp & Harvey, 2001). Longitudinal studies are needed to assess these possibilities. Additional study of other potential vulnerability factors (e.g., illness/injury sensitivity, fear of pain) is also warranted.

Selective Attention to Threat Cognitive models suggest that people with various forms of psychopathology or general medical conditions tend to selectively attend to threat-related stimuli that are representative of the core concerns of their specific disorder; that is, they direct attention towards objects or situations that they fear. This increases state anxiety and, according to some, makes one vulnerable for emotional disorders (e.g., Mathews & MacLeod, 2002). Evidence for syndrome-specific attentional biases is, with few exceptions, robust across various anxiety disorders (see Williams, Mathews, & MacLeod, 1996). This has been consistently demonstrated in patients with PTSD using emotional Stroop colour-naming and fear-potentiated startle tasks (e.g., Paunovic, Lundh, & O¨st, 2002) but not with the dot-probe task (e.g., Elsesser, Sartory, & Tackenberg, 2005). The findings from chronic musculoskeletal pain patients have been mixed and there is no clear consensus amongst modified Stroop and dot-probe investigations as to whether patients with chronic musculoskeletal pain do or do not selectively attend to pain-related stimuli. A recent meta-analysis of five modified Stroop investigations suggests that chronic pain patients, compared to healthy participants, have an attentional bias to both sensory and affect pain words (Roelofs, Peters, Zeegers, & Vlaeyen, 2002); however, scrutiny of the findings from the individual investigations used in the meta-analysis as well as findings from controlled investigations (Andersson & Haldrup, 2003) fail to provide convincing evidence for this conclusion. The results of dot-probe investigations, with some exceptions, also fail to provide clear evidence that chronic pain is associated with a pain-specific bias in attentional processing (Asmundson, Carleton, & Ekong, 2005; Asmundson, Kuperus, & Norton, 1997, Asmundson, Wright, & Hadjistavropoulos, 2005; Roelofs, Peters, Fassaert, & Vlaeyen, 2005). Most recently, fear-potentiated startle has been employed as a means of potentially resolving the mixed findings yielded using other cognitive tasks. Some of these studies have indicated increased startle to pain-related stimuli (Flor, Knost, & Birbaumer, 1997) while others have not (Carleton, Asmundson, Collimore, & Ellwanger, 2006;

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Kronshage, Kroener-Herwig, & Pfingsten, 2001); however, strong associations between startle responses to pain-related stimuli and fear-based individual difference constructs (e.g., AS, fear of pain) were noted in both studies that assessed the latter (Carleton et al., 2006; Kronshage et al., 2001). The assumption underlying this area of research is that patients with chronic musculoskeletal pain are generally fearful of pain and, thus, will selectively attend to pain-related stimuli; however, it is plausible that investigators have not identified the specific objects or situations that are feared by these individuals (for detailed discussion of objects of fear in pain conditions, see Morley & Eccleston, 2004). That is, pain-related stimuli may not be the object of fear for the majority of patients with chronic musculoskeletal pain. There is evidence to suggest that trauma-related stimuli may be the most relevant object of fear for many patients with chronic musculoskeletal pain. Specifically, we (Asmundson, Bonin, Frombach, & Norton, 2000) and others (Beck, Gudmundsdottir, & Shipherd, 2003) have demonstrated that when the heterogeneous nature of chronic musculoskeletal pain is considered, those patients classified as dysfunctional are far more likely to have co-occurring PTSD (70%) than those classified as interpersonally distressed (35%) or as adaptive copers (20%). The empirically-derived system for making these classifications – the Multiaxial Assessment of Pain (MAP; Turk & Rudy, 1987) – is described in detail in the Assessment section below. There is also preliminary evidence that patients with co-occurring PTSD and pain show attentional biases (on a modified Stroop task) for both pain and accident words (e.g., crash), whereas those with pain and no PTSD are biased only toward pain words (e.g., throbbing; Beck, Freeman, Shipherd, Hamblen, & Lackner, 2001). While the latter findings await replication, they suggest that the object of fear in some chronic pain patients (i.e., those classified as dysfunctional) may be associated with prior traumatic and painful injury. Confirmation of these findings may explain the lack of robustness observed in efforts to identify attentional biases in patients with chronic musculoskeletal pain and may shed light on cognitive mechanisms underlying the co-occurrence of these conditions.

Lower Threshold for Alarm Pain and anxiety are both associated with physiological arousal (e.g., accelerated heart rate, elevated blood pressure, increased respiration, decreased gastrointestinal activity, increased muscular tension, increased blood flow to skeletal muscles; Hoehn-Saric & McLeod, 1993). The bodily changes stemming from arousal serve a protective function, promoting escape and withdrawal, but can have detrimental effects if prolonged. Physical injury and traumatic experiences also initiate other complex neural and hormonal processes (e.g., release of cytokines, b-endorphin, 5-HT-moduline) that, while designed to promote tissue healing and reinstate homeostasis, can be destructive to muscle, bone,

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and neural tissue when prolonged (e.g., Kiecolt-Glaser, McGuire, Robles, & Glaser, 2002; Melzack & Katz, 2004). In short, prolonged physiological arousal and activation of neural and hormonal processes, whether initiated by pain or anxiety, act as a stressor (i.e., they are perceived as threatening and uncontrollable) that can have detrimental effects on various body systems (McEwen, 1998). Illustrating these effects, and as noted in our discussion of epidemiology of co-occurrence, Sareen et al. (2005) found strong associations between anxiety disorders, particularly PTSD, and general medical conditions characterized by pain. We have been particularly interested in the role that autonomic nervous system (ANS) dysregulation may play in anxiety disorders and in chronic musculoskeletal pain. This interest is predicated on the notion that chronic arousal is, in part, responsible for the symptoms of both conditions. One of the most robust findings reported in the PTSD literature over the past two decades is that sympathetic activity is increased and parasympathetic activity decreased, both in general and in response to trauma-related stimuli. This pattern of findings has been observed across a wide variety of measures of cardiovascular reactivity in both traumatized adults (Keane et al., 1998) and children (Scheeringa, Zeanah, Myers, & Putnam, 2004). Although ANS dysregulation in chronic musculoskeletal pain has received little empirical scrutiny, available findings suggest a pattern similar to that observed in PTSD. Rainville, Bao, and Chretien (2005), for example, used hypnosis to alter mood, perceived pain unpleasantness, and severity of pain induced in healthy participants, showing that increases in negative mood and pain unpleasantness were positively associated with changes in heart rate variability. This suggests that pain-related emotion impacts ANS responsivity. We recently completed an investigation of patients with chronic musculoskeletal pain (n=33), acute musculoskeletal pain (n=12), and healthy controls (n = 30) using tasks designed to evoke measurable, bi-directional ANS responses. Preliminary analyses indicate no betweengroup differences with regard to tasks that augment vagal tone; however, the chronic pain patients exhibited increased sympathetic activity compared to controls on tasks designed to induce rapid vagal withdrawal followed by sympathetic discharge (i.e., dysregulated sympathetic discharge). Collectively, these data indicate both PTSD and chronic musculoskeletal pain are characterized by labile sympathetic responsivity. The literature regarding pain threshold (i.e., the point at which a stimulus is detected as being painful) and pain tolerance (i.e., the length of time that a pain stimulus can be endured) in each of PTSD and chronic musculoskeletal pain may also provide some clues as to the mechanism of association; however, the findings are mixed and complex. There is, for example, a body of evidence indicating that hyperalgesia (i.e., reduced pain threshold and tolerance or, in other words, exaggerated pain perception) is induced by elevations in state and trait anxiety (e.g., Carter et al., 2002; James & Hardardottir, 2002). Since elevations in state and trait anxiety are central features of PTSD and chronic musculoskeletal pain, it is plausible that PTSD and chronic musculoskeletal

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pain may induce hyperalgesia. On the other hand, there is a body of literature indicating that conditioned stress-induced hypoalgesia/analgesia (i.e., increased pain threshold and tolerance or, in other words, attenuated pain perception) plays an important and potentially causal role in both chronic musculoskeletal pain (e.g., Flor, Birbaumer, Schulz, Gru¨sser, & Mucha, 2002) and PTSD (e.g., Foa, Zinbarg, & Rothbaum, 1992). This literature suggests that dysregulation of the endogenous opioid system – perhaps functioning to deactivate fear structures in the short term through heightened release of endogenous opioids – may play a role in blunting pain perception (e.g., higher pain threshold and tolerance), reducing avoidance behavior, and increasing emotional numbing associated with chronic musculoskeletal pain and PTSD. It is noteworthy that pain tolerance, but not threshold, is affected by naloxone (a drug that blocks opioid receptors) only when pain levels are high, suggesting only partial mediation by the endogenous opioid system. These mixed findings are intriguing when placed in the context of evidence showing that AS does not impact pain tolerance or threshold, but is associated with pain intensity (for review, see Keogh & Asmundson, 2004). It is possible that different mechanisms may be operating at different levels of the stimulusresponse range (i.e., from just noticeable sensation through intolerable pain) and that their operations are partially regulated by individual difference factors that influence processing of pain sensation as alarming. Given recent observations that unpredictable and predictable pain are associated with hyperalgeisa and hypoalgesia/analgesia, respectively (Ploghaus, Becerra, Borras, & Borsook, 2003), it is equally possible that different mechanisms are operative depending on whether pain evokes anxiety (i.e., response to unpredictable, future threats) or fear (i.e., response to an immediate threat). Chronic dysregulation of the ANS and endogenous opioid system appears to play important, possibly interactive roles in reducing the threshold for alarm in PTSD and chronic musculoskeletal pain and, in part, may account for their substantive co-occurrence. This remains to be evaluated in direct comparisons between those with PTSD, chronic musculoskeletal pain, both PTSD and chronic musculoskeletal pain, and healthy as well as clinical control participants. This, combined with evidence that the serotonergic system – an aminergic neurotransmitter system responsible for maintaining homeostasis via modulation of the release of 5-HT from serotonergic neuron terminals – may be dysregulated in both PTSD and chronic musculoskeletal pain (e.g., Davidson & Connor, 2001), provides clues as to the peripheral and central physiological mechanisms underlying the suggestion of a lower threshold for alarm.

Summary There exists a small and growing body of empirical support for postulates of the mutual maintenance and shared vulnerability models of co-occurring PTSD

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and chronic musculoskeletal pain. However, given that empirical scrutiny of these models is in its infancy, we remain at a stage where there are more questions than answers. With regard to the applicability of these models to understanding, explaining, and guiding treatment for those with other anxiety disorders that are accompanied by clinically significant pain, even less is known. Notwithstanding, these models provide a foundation on which to make recommendations for assessment and treatment planning for these potentially complicated cases.

Assessment and Treatment As noted above, clinically significant pain often goes unnoticed when assessing and planning treatment for a patient with an anxiety disorder. When overlooked, pain can make treatment of the anxiety symptoms complicated at best, and frustrating and ineffective at worst. There is little information available on assessment and treatment planning for anxiety disorder patients who present with co-occurring pain symptoms. In order to facilitate clinical and research efforts, we provide a brief overview of tactics for assessment and treatment in this context.

Assessment Comprehensive assessment of pain requires delineation of pain severity or intensity, pain location and distribution, attitudes and beliefs about pain and its effects, ways of coping with pain, pain-specific emotional distress (i.e., fear, anxiety, mood changes), and pain-related functional abilities and limitations (Asmundson, 2002; Tait, 1999). Below we highlight specific assessment methods that may be useful in the context of assessing pain in patients with anxiety disorders. We assume that (a) a comprehensive assessment of the anxiety disorders and related Axis I and Axis II psychopathology has been conducted, (b) individual difference factors pertinent to the anxiety disorders and relevant in the context of mutual maintenance and shared vulnerability, particularly AS, have been assessed (see Taylor, 1999), and (c) appropriate steps will or have been taken to identify and medically address organic pathology or other identifiable physical factors that might account for the patient’s presenting pain symptoms. Assessment methods include reviewing hospital medical records (in order to chart the course of the patient’s problems), clinician-administered structured clinical interviews, clinician observation techniques (e.g., pain behaviors, facial action coding), prospective monitoring forms, and self-report questionnaires. In the context of patients presenting for treatment of an anxiety disorder, and for future research efforts, we recommend brief semi-structured interviewing

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accompanied by select self-report measures as an easy and time efficient means of getting essential information. Use of semi-structured interviews can provide a wealth of information regarding pain origins, its impact on current beliefs and assumptions, its impact on behavior, as well as associated complications (e.g., marital conflict, depression, substance abuse). Therapist guided inquiries may facilitate identification of the patient’s conceptualization of his or her problem. Specific questions (e.g., What makes your pain worse?) can provide valuable information regarding pain triggers, patterns of avoidance, and the patient’s treatment goals. Where self-report measures are administered in advance of interviews, the direction of interviews can be guided to some extent by information gained from these measures; conversely, information gained from interviews may guide the choice of instruments. We recommend that assessment batteries provide maximal information with minimal overlap. The following measures meet this criterion (also see Mikail, DeBreuil, & d’Eon, 1993). Multidimensional Pain Inventory (MPI; Kerns, Turk, & Rudy, 1985). The MPI assesses physical, psychological, and social factors related to the pain experience. It is comprised of 52 items and is a reliable, valid self-report measure. To classify pain patient subgroups, responses on the MPI can be submitted to the MAP (Turk & Rudy, 1987), an empirically-based and computerized application. Patients can be classified as dysfunctional (i.e., higher than average pain severity, interference, and distress, and lower levels of self-efficacy and activity), interpersonally distressed (i.e. lower levels of perceived social support), or minimizers/adaptive copers (i.e., lower than average pain severity, interference, and distress, and higher levels of self-efficacy and activity). Asmundson, Bonin, et al., (2000) found that a substantial proportion of dysfunctional and interpersonally distressed patients were classified as having PTSD (71.4 and 42.9%, respectively) when compared to minimizers/adaptive copers (21.3%). These findings suggest that MAP subgroups differ with regard to their likelihood of having PTSD. Additional research is needed to determine if they differ with regard to other anxiety disorders. Short Form McGill Pain Questionnaire (SF-MPQ; Melzack, 1987). The SF-MPQ is used to measure dimensions of the pain experience. It comprises 15 adjectives describing sensory (e.g. throbbing) and affective (e.g., sickening) dimensions of pain, a visual analogue scale (VAS) and present pain index [PPI; based on a scale of 0 (no pain) to 5 (excruciating)]. The SF-MPQ has been widely used to measure pain experiences in many different types of patients (e.g., low back pain, fibromyalgia, rheumatoid arthritis), and as a measure of treatment efficacy (e.g., Frost et al., 2000). A more comprehensive assessment of the pain experience can be achieved by using the full length MPQ (MPQ; Melzack, 1975). Pain Anxiety Symptoms Scale (PASS; McCracken, Zayfert, & Gross, 1992). For assessing pain-related anxiety, the 40-item PASS, and a shorter 20-item version (PASS-20; McCracken & Dhingra, 2002) are commonly used. The PASS and the PASS-20 both assess four theoretically distinct components of

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pain-related anxiety, including cognitive anxiety (e.g., I find it hard to concentrate when I hurt), fearful appraisal of pain (e.g., Pain sensations are terrifying), escape and avoidance behavior (e.g., I try to avoid activities that cause pain), and physiological anxiety associated with pain (e.g., Pain seems to cause my heart to pound or race). Individuals rate each item on a 6-point Likert scale ranging from 0 (never) to 5 (always). The PASS and PASS-20 have been found to have good psychometric properties. While both versions of the PASS are widely used, several other measures of pain-related anxiety are available; for a detailed discussion see Asmundson and Carleton (in press). Chronic Pain Coping Inventory (CPCI; Jensen, Turner, Romano, & Strom, 1995). The 65-item CPCI, and its abbreviated 42-item short form (Romano, Jensen, & Turner, 2003), measure cognitive and behavioral strategies that people might use while experiencing or trying to prevent pain. Eight coping strategies are assessed, including positive coping self-statements, guarding, resting, asking others for assistance, seeking social support, relaxing, task persistence, and exercising. Use of past-week coping strategies is measured on an 8-point scale expressed in number of days. The CPCI provides a comprehensive and psychometrically valid assessment of pain-related coping strategies (Hadjistavropoulos, MacLeod, & Asmundson, 1999).

Treatment Cognitive-behavioural therapy (CBT) is a highly effective treatment for both anxiety disorders (Butler, Chapman, Forman, & Beck, 2006) and chronic pain (Morley, Eccleston, & Williams, 1999). Therefore, treatment of clinically significant pain in patients with an anxiety disorder may effectively incorporate elements of CBT for both the anxiety disorder and chronic pain. While the specific application of CBT for managing pain in patients with anxiety disorders is still in its infancy it is, nonetheless, very promising. Several features of CBT for managing pain can be used in the context of CBT for the anxiety disorders. These include psychoeducation, relaxation training, attention diversion strategies, cognitive restructuring, graded activity, and one or more of several exposure techniques. Psychoeducation. Patients experiencing pain often desire to be pain-free. This goal is somewhat unrealistic. Accordingly, education can be used to help the patient reformulate his or her view of pain as a signal of impending catastrophe (e.g., permanent disability, disease, reinjury) to one of pain as a common experience that can be self-managed. A basic understanding of the typical course of pain (and, if appropriate, healing), combined with appreciation of the premise that hurt does not always equal harm, can ameliorate reservations about making pain worse and thereby encourage activity participation. A key advantage of psychoeducation is that it is simple to administer and can be delivered in groups.

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Relaxation Training. We recommend a modified version of the method described by Taylor and Asmundson (2004). This includes systematic education about and practice doing release-only relaxation, rapid relaxation, and diaphragmatic breathing. Implementation of these strategies may help the patient to control muscle tension and associated pain, and provide general skills that can be used in everyday living to become more relaxed. In patients with chronic musculoskeletal pain or headache we typically omit tense-release relaxation as the process of repeatedly tensing and releasing certain muscle groups can, rather than providing relief, increase muscle tension or cramping. Cognitive Strategies. Cognitive strategies may further enhance pain management. Cognitive restructuring strategies involve identification of catastrophic cognitions about pain (e.g., Hurt equals harm) followed by teaching the patient strategies to challenge and change their catastrophic thoughts (e.g., My pain is not harmful, and I can function despite it). Attention diversion strategies may include focusing attention on external stimuli (e.g., pictures of landscapes), focusing on neutral (e.g., an instructor attending a lecture) or pleasant (e.g., sitting comfortably in a chair) imagery, dramatized reconstruction of the context in which pain occurs (e.g., imagining pain due to an injury in a sports game), repetitive or systematized cognitive strategies (e.g., counting backwards from 100 by 3), and pain acknowledging (e.g., reappraisal of pain in terms of objective sensations). A meta-analysis of 61 studies showed that these strategies enhanced pain tolerance and reduced pain ratings more than 85% of the time relative to no treatment (Fernadez & Turk, 1989). Imagery strategies were most effective. Graded Activity. The purpose of graded activity is to counter the effects of painpromoting deconditioning that might occur due to inactivity and pain-related behavioral avoidance. When applied in the context of patients with an anxiety disorder and co-occurring chronic pain we recommend a variant of graded activity that specifically targets exercise and fitness training. The premise is similar to that of graded activity – exercise and fitness training may serve to promote activity pacing, recommencement of previous activity levels, and physical reconditioning in patients with a variety of chronic pain conditions (for review, see Wright & Sluka, 2001). Because exercise can also serve to ameliorate anxiety symptoms, particularly panic-related symptoms (Smits, Powers, Berry, & Otto, in press; Stathopoulou, Powers, Berry, Smits, & Otto, 2006), it is an attractive consideration for the patient with both anxiety and chronic pain symptoms. Exposure. Many patients with chronic musculoskeletal pain avoid situations or activities based on the fear that these will provoke further pain or re-injury. Accordingly, clinicians have used various forms of exposure therapy to reduce fear of pain and increase involvement in leisure and work activity. Exposure is conducted within treatment sessions and as homework assignments. Recent data from studies using replicated single-case experimental (e.g., de Jong et al., 2005; Vlaeyen, de Jong, Leeuw, & Crombez, 2004) and randomized controlled (Woods & Asmundson, in press) designs indicate that graded in vivo exposure – exposure to specific pain-related activities that are feared or avoided – is more effective than graded activity in reducing fear of pain, avoidance behaviors, and

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reports of pain severity. In vivo exposure is explained in detail elsewhere (Vlaeyen et al., 2004). In vivo exposure may be an effective strategy to incorporate when a patient with an anxiety disorders reports significant fear and avoidance of pain-related situations or activities; however, this may require substantial time (e.g., two weekly session of 45 mins for approximately 8 weeks) and divergence from standard treatment. Interoceptive exposure (i.e., exposure to anxiety provoking bodily sensations) is an interesting alternative to in vivo exposure; it is an empirically-supported intervention often included as part of CBT for anxiety disorders (e.g., Taylor, 1999) and, more recently, has been shown effective in reducing both PTSD symptoms (Wald & Taylor, in press) and fear of pain (Watt, Stewart, Lefaivre, and Uman, 2006). Other Treatment Considerations. While we have emphasized CBT in our discussion of treatment options for co-occurring chronic musculoskeletal pain and anxiety disorders, there are other promising approaches. Pharmacotherapy can be effective in alleviating pain associated with various conditions (e.g., Portenoy, 2000); thus, combining analgesics with CBT may prove particularly effective in cases where an anxiety disorder and clinically significant pain co-occur. Combined pharmacotherapy and CBT is, in fact, recommended in current expert consensus guidelines for comorbid PTSD and chronic pain (Foa, Davidson, & Frances, 1999). Moreover, recent developments in pharmacotherapy suggest that some pharmacologic agents may be particularly effective for alleviating co-occurring PTSD and pain. Specifically, results from two small, randomized trials indicate that propranolol, a beta-blocker with analgesic effects, reduces PTSD symptoms (Pitman et al., 2002; Pitman & Delahanty, 2005). Speculations of effectiveness of combination treatments across the anxiety disorders do, however, await systematic empirical scrutiny. Acceptance and mindfulness-based interventions (e.g., Kabat-Zinn, 1990; Hayes, Wilson, & Strosahl, 1999) have also been found to be effective for a range of medical and psychological problems that include pain syndromes and anxiety disorders (for reviews, see Baer, 2003; Bishop, 2002; Melbourne Academic Mindfulness Interest Group, 2006). It is plausible that these interventions may prove effective, either on their own or as adjuncts to CBT, for the treatment of anxiety disorders that co-occur with chronic pain. On the other hand, while standard physical treatments of chronic musculoskeletal pain (e.g., electrotherapy, muscle manipulation) are potentially therapeutic, there is a lack of substantive empirical evidence supporting their effectiveness (Wright & Sluka, 2001); thus, we do not recommend their use in treating a patient with co-occurring anxiety disorder and chronic musculoskeletal pain.

Outstanding Issues and Conclusion Generally speaking, relatively little is known about the mechanisms that underlie the co-occurrence of the anxiety disorders and conditions characterized by clinically significant pain. The majority of evidence comes from

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investigations of the co-occurrence of PTSD and chronic musculoskeletal pain. Examination in the context of the other anxiety disorders may serve to identify mechanisms of co-occurrence (e.g., mutual maintenance, shared vulnerability) that are common to each. Systematic inquiry may also allow further development, refinement, and empirical validation of treatments geared specifically toward those patients who have both an anxiety disorder and chronic pain. As noted at the outset of this chapter, the co-occurrence of an anxiety disorder and chronic pain does not bode well for assessment or treatment outcome. It remains undetermined whether co-occurrence negatively influences health compromising behaviors and, if so, how this will affect treatment. However, given that the anxiety disorders and chronic pain syndromes present with a strikingly similar cluster of health compromising behaviors (e.g., heavy smoking, increased alcohol and substance consumption, poor sleep, increased depression and suicidal ideation, avoidance of leisure activities and exercise), it seems reasonable to speculate that co-occurrence will, at minimum, be associated with reduced likelihood that such patients will present with a well developed arsenal of adaptive health behaviors. This, in turn, may complicate or, at minimum, prolong treatment. Below we highlight a number of specific research directions that await investigation. For those investigators who pursue one or more of these directions, we urge careful attention to the heterogeneous nature of chronic pain (e.g., as illustrated by the MAP categories of minimizers/adaptive copers, interpersonally distressed, dysfunctional; Turk & Rudy, 1987), as failure to do so may significantly reduce power to detect mechanisms at play. We also urge that efforts are made to evaluate aspects of both mental and physical health. First, further elaboration of current and lifetime prevalence of various pain conditions in each of the anxiety disorders, in community and treatmentseeking samples, using comprehensive pain assessment batteries is warranted. Second, and of particular importance, investigation of the temporal sequence of co-occurring anxiety disorders and chronic pain are required to determine whether one condition is more likely to precede the other, and whether sequencing of onset is consistent across the anxiety disorders. Third, further empirical exploration of the mechanisms of co-occurrence, as posited in the mutual maintenance and shared vulnerability models, for various chronic pain conditions and each of the anxiety disorders will improve our understanding of cooccurrence. Further empirical scrutiny may also serve to guide treatment for those with anxiety disorders accompanied by clinically significant pain. The preliminary research regarding the application of each of propanolol and interoceptive exposure in this context is promising. Finally, there are a number of specific studies related to shared vulnerability factors that will advance the field, including (a) longitudinal studies to examine whether elevated AS precedes the development of anxiety disorders and chronic musculoskeletal pain, or whether it becomes elevated as a consequence of these conditions, (b) additional study of other potential vulnerability factors (e.g., trait negative affectivity, illness/injury sensitivity, fear of pain) in understanding the

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association between anxiety disorders and chronic musculoskeletal pain, (c) further examination of the object of fear in chronic musculoskeletal pain patients with and without a co-occurring anxiety disorder (e.g., whether they are associated with prior traumatic and painful injury), and (d) examination of the possible interactive roles of ANS dysregulation and the endogenous opioid system in reducing threshold for alarm in PTSD (and other anxiety disorders) and chronic musculoskeletal pain. The aforementioned research directions are neither exhaustive nor presented in order of importance. There are, instead, ideas that may stimulate research in this emerging but currently underdeveloped area. Ultimately, the outcomes of studies targeting theses avenues of inquiry may serve to inform assessment and treatment that, in turn, will increase the probability that clinicians can positively impact the mental and physical health of their patients who present with an anxiety disorder accompanied by clinically significant pain.

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Asthma in Anxiety and Its Disorders: Overview and Synthesis Lisa S. Elwood and Bunmi O. Olatunji

Asthma is a respiratory disease with symptoms including reversible airway obstruction, airway inflammation, and hyperactive airways that affects approximately 6% to 9% of the U.S. population (Carr, 1998; Turkeltaub & Gergen, 1991). Asthma is one of the most chronic respiratory disorders and the cost of caring for asthma is estimated to be higher than that of AIDS/HIV and tuberculosis combined (World Health Organization, 2000). Furthermore, the economic impact of asthma is considerable, with total US expenditures for 1990 in excess of $6 billion (Weiss, Gergen, & Hodgson, 1992). Individuals with asthma appear to be at an increased risk for psychological difficulties, and report high prevalences of anxiety, depressive, and substance disorders (Scott et al., 2007). Although asthma is a treatable condition, morbidity and mortality due to asthma have increased (Afari, Schmaling, Barnhart, & Buchwald, 2001; Sly, 1988; Weiss, Gergen, Wagener, 1993). The availability of efficacious interventions for the management of asthma suggests that some proportion of poor outcomes is preventable (Greineder, Loane, & Parks, 1995). This conclusion has prompted health care providers to give special attention to risk factors for poor asthma outcomes. Psychological difficulties may increase the distress associated with asthma symptoms and may be linked with poor asthma management (Katon, Richardson, Lozano, & McCauley, 2004; Lavoie et al., 2005). The current chapter reviews literature examining the relation between asthma and anxiety symptoms and disorders. The chapter will begin with a brief description of asthma symptomatology, assessment, treatment, and non-psychological risk factors. The general association between asthma and anxiety disorders in children and adults will then be reviewed followed by a more in depth examination of the relation between asthma and panic disorder. Next, the chapter will review studies that examine the link between anxiety and asthma severity, control, and quality of life. The relation between psychological vulnerabilities to anxiety and asthma will then be discussed. The chapter will then Lisa S. Elwood National Crime Victims Research and Treatment Center, Medical University of South Carolina, 165 Cannon Street, P.O. Box 250852, Charleston, SC 29425, Tel: 843-792-2366, Fax: 843-792-3388 [email protected]

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consider the specificity of the relation between asthma and anxiety. Finally, cognitive behavioral models of the asthma and anxiety relation will be provided and the efficacy of cognitive behavioral treatments for individuals with asthma will be reviewed.

Asthma During an acute asthma attack, a stimulus initiates an airway response that includes inflammation, bronchospasm, and increased mucus production (Sims, 2006). Additional asthma symptoms include coughing, wheezing, shortness of breath, and tightness in the chest. An individual’s asthma symptoms can be classified as mild intermittent, mild persistent, moderate persistent, or severe persistent (Banasiak, 2007). Although the diagnosis and classification of asthma varies, three factors are typically taken into consideration when classifying the severity of asthma: frequency of daytime symptoms, frequency of nighttime symptoms, and lung functioning. Lung functioning is assessed using peak flow rates and forced expiratory volume in 1 second (FEV1). The FEV1 is the amount of air the individual is able to forcibly exhale in 1 second. FEV1 is measured using spirometry, with a lower number indicating increased severity (Sims, 2006). Peak expiratory flow (PEF) rates compare the individual’s pulmonary functioning to what is normal for his or her height, age, weight, and sex. Normal peak flow rates range from 80% to 100%, while severe asthma attacks yield peak flow rates of less than 60% (Sims, 2006). An individual with mild intermittent asthma endorses daytime symptoms less than twice a week, nighttime symptoms less than twice a month, FEV1 or PEF greater than 80% of the predicted amount, and PEF variability of less than 20%. Mild persistent asthma includes daytime symptoms greater than two times a week, nighttime symptoms greater than two times a month, and FEV1 or PEF rates greater than 80% with 20–30% variability. Criteria for moderate persistent asthma include daily daytime symptoms, nighttime symptoms more than once a week, and FEV1 or PEF greater than 60–80% predicted with PEF variability of greater than 30%. Finally, severe persistent asthma describes persistent daily symptoms, frequent nighttime symptoms, and FEV1 or PEF less than 60% of the predicted value with PEF variability greater than 30% (Banasiak, 2007). Asthma is often treated using bronchodilators, corticosteroids, and leukotriene antagonists (Sims, 2006). Research has revealed that there is a considerable amount of variability in the course of asthma. It has been suggested that asthma should be conceptualized as a syndrome, with many etiologies that may result in different presentations and outcomes (Reed, 2006). Different asthma etiologies may include intermittent wheezing with respiratory infection in infants, Immunoglobulin E (IgE; related to allergic responses) mediated asthma, intrinsic asthma, and asthma associated with other chronic lung diseases (Reed, 2006). While frequent wheezing in infancy is associated with an increased likelihood of chronic

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asthma symptoms; infants with infrequent wheezing typically do not continue to display asthma symptoms as they mature. Allergic asthma commonly develops during the second decade of life when individuals become exposed to allergens they did not have contact with as children. Allergic asthma is typically not severe and does not progress over time. Intrinsic asthma appears to develop frequently in middle-aged and older adults, but can begin at any age. Intrinsic asthma tends to be persistent, is likely to increase in severity over time, and may become irreversible.

Non-psychological Risk Factors for Asthma Research examining risk factors for asthma have identified sex, race, weight, timing of birth, smoking, environmental factors, and atopy (i.e., allergic responses) as potential risk factors for the development of asthma. The relationship between sex and asthma appears to fluctuate over time. Studies have found that asthma appears to be more prevalent in males in childhood (van Merode, Maas, Twellar, Kester, & van Schayck, 2007), but in females in adulthood (Apter, 2007; Wenzel & Busse, 2007). Members of ethnic minority groups, with the exception of Mexican Americans, appear to be at an increased risk for asthma when compared to Caucasians (Apter, 2007, McCoy et al., 2006). Specifically, within the US, asthma appears to be most prevalent in Puerto Rican Americans, followed by Native Americans, African Americans, and then by Caucasians. In addition, members of minority groups and individuals with low socioeconomic status (SES) appear to be at an increased risk for not receiving appropriate medical care for asthma, resulting in higher rates of medical visits and death related to asthma (Apter, 2007; Joseph, Williams, Ownby, Saltzgaber, & Johnson, 2006). However, one study found support for chronic stress as a mediator between low SES and decreased immune processes and asthma symptoms (Chen, Hanson et al., 2006). A meta-analysis examining the relation between weight and asthma indicated that both high weight at birth and at middle childhood appear to be related to increased risk for future asthma (Flaherman & Rutherford, 2006). The article suggests that diet, gastroesophageal reflux, mechanical effects of obesity, atopy, and hormonal influences may serve as links between body weight and asthma symptoms. The link between overweight status and asthma has also been supported in adolescents (OR 1.4, 95% confidence interval (CI) 1.1–1.6; Jones, Merkle, Fulton, Wheeler, & Mannino, 2006). Research suggests that obesity in adulthood is associated with the presence of asthma symptoms in females, but not males (McLachlan et al., 2007). A separate meta-analysis revealed that premature birth may also serve as a risk factor for asthma (Jaakkola et al., 2006). However, the strength of the association varied across studies, with cross-sectional design, broad outcome criteria, small sample size, young sample, and more recent publication displaying the strongest associations between pre-term birth and asthma symptoms.

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Atopy has consistently been supported as a risk factor for asthma (Shapiro, 2006). Atopy describes an allergic response which frequently affects parts of the body that are not in contact with the allergen. Atopic responses include eczema, allergic rhinitis, and allergic conjunctivitis. Both the presence of atopy in the child and parental atopy or asthma appear to serve as risk factors for the development or maintenance of asthma symptoms in children (Shapiro, 2006). Studies have consistently shown a high comorbidity between asthma and rhinitis (i.e., irritation and inflammation of the nose) and have posited that rhinitis serves as a risk factor for asthma (Bousquet, van Cauwenberge, & Khaltaev, 2001). It has been proposed that rhinitis and asthma may be two expressions of a common mucosal susceptibility and may affect and amplify each other (Jani & Hamilos, 2005). For individuals with both rhinitis and asthma, there is some evidence that treatment of rhinitis may improve coexisting asthma symptoms (Bousquet et al., 2001). Other medical conditions that have been associated with asthma include heartburn and acid regurgitation (Hancox et al., 2006). Studies suggest that smoking or being exposed to second hand smoke serves as a strong risk factor for the development of asthma (McCoy et al., 2006; Shapiro, 2006). In fact, a recent study found that the risk of developing asthma was significantly higher among current smokers with an adjusted odds ratio (OR) of 1.33 (95% CI 1.00–1.77) and among ex-smokers with an adjusted OR 1.49 (CI 1.12–1.97) compared with never-smokers (Piipari, Jaakkola, Jaakkola, & Jaakkola, 2004). Similarly, a prospective cohort study among 2,609 children with no lifetime history of asthma or wheezing found that regular smoking was associated with increased risk of new-onset asthma and the increased risk from regular smoking was greater in nonallergic than in allergic children (Gilliand et al., 2006). A third study which assessed individuals over a eight year period reported that smokers reported a higher frequency of new onset asthma than non-smokers, OR 2.14 (95% CI 1.30–3.00; Frank, Hazell, Morris, Linehan, & Frank, 2007). A study examining poor asthma control, based on patient diaries over a 4 week period, in individuals being treated for asthma revealed that smoking, along with lung function and ethnicity, was associated with the presence of asthma episodes (McCoy et al., 2006). Smoking has been shown to be a unique and independent predictor of the development of asthma. The smoking-asthma relation may be largely attributable to airway narrowing and hyperresponsiveness secondary to emphysema and chronic bronchitis.

Asthma and Mental Health Many studies have outlined how immunological and physiological factors moderate asthma outcomes (e.g., Grupp-Phelan, Lozano, & Fishman, 2001; Watson, Becker, & Simons, 1993). However, the potential influence of psychological

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factors on asthma has received relatively less attention (Katon et al., 2004). The available literature does suggest that approximately 40% of individuals with asthma present with clinically elevated levels of psychological distress (Mullins, Chaney, Pace, & Hartman, 1997) with 21% to 25% reporting depressive symptoms (Badoux & Levy, 1994; Chaney et al., 1999). Furthermore, it has been shown that asthma is longitudinally associated with a significant increase in suicidal ideation and suicide attempt, independent of major depression (Goodwin & Eaton, 2005). These findings highlight the importance of psychological distress in the conceptualization of the etiology, maintenance, and treatment of asthma. Recent research has shown that a wide range of mental health problems are common among patients with asthma (Goodwin, Messineo, Bregante, Hoven, & Kairam, 2005). However, data from epidemiologic samples suggest that anxiety disorders, relative to other mental health problems, are especially prevalent among patients with asthma (e.g., Ortega, McQuaid, Canino, Ramirez, Fritz, & Klein, 2003).

The Intersection of Anxiety and Asthma Prevalence and Impact of Anxiety Disorders Anxiety disorders have the highest overall prevalence rate among psychiatric disorders, with a 12-month rate of 18.1% and a lifetime rate of 28.8% (Kessler, Berglund, Demler, Jin, Merikangas, & Walters, 2005; Kessler, Chiu, Demler, & Walters, 2005). The estimated costs associated with anxiety disorders has been reported to be over $45 billion, accounting for over 30% of total expenditures in mental health (DuPont et al., 1996). Anxiety disorders also have a substantial negative impact on quality of life (Mendlowicz & Stein, 2000; Olatunji, Cisler, & Tolin, 2007).

Anxiety in Children and Adolescents with Asthma Asthma is the most common medical disorder among adolescents and is associated with increased functional impairment and lost days at school (Weitzman, Gortmaker, Sobol, & Perrin,1992). There is also evidence that the presence of asthma increases the risk for the development of an anxiety disorder. As outlined in Table 1, the presence of asthma in children and adolescents has been linked with anxious disorders and symptoms in clinical (Butz & Alexander, 1993; Gupta, Mitchell, Giuffre, & Crawford, 2001; Vila, Nollet-Clemencon, de Blic, MourenSimeoni, & Scheinmann, 2000) and non-clinical samples (Goodwin, Pine, & Hoven, 2003; Goodwin, Fergusson, & Horwood, 2004; Ortega et al., 2003; Ortega,

Sample

Children 7–12, Recruited from pediatric ER, Diagnosis of acute asthma

Data drawn from an epidemiology study

Data collected during the course of a longitudinal study of an unselected birth cohort; at ages 18 and 21 participants were asked about asthma

Study

Butz and Alexander (1993)

Goodwin et al. (2003)

Goodwin, Fergusson, & Horwood (2004) Classified as presence of absence of asthma during age 16–18 and 18–21. Presence was determined by reported diagnosis and symptoms during the

Parents report of child asthma symptoms and hospitalization for asthma

Self-reported number and type of symptoms, number of hospital and ER visits, limitation of activity, medication

Asthma Measurement

Items from CIDI; asked for the previous two years; Assessed GAD, social phobia, specific phobia, and agoraphobia; assessed panic attacks and

DISC; Child global assessment scale

State-Trait Inventory for Children, reported emotion at the beginning of an asthma attack

Anxiety Measurement

None

Asthma to no asthma

None

Comparison group

Table 1 Findings of studies examining the relation between asthma and anxiety in children and adolescents

65% reported feeling ‘‘panic’’ at the beginning of an asthma attack, feeling panic at the beginning of an attack significantly predicted trait, but not state, anxiety Asthma was associated with an increased likelihood of panic attacks; severe asthma was associated with an increased likelihood of panic attacks and disorder; Number of panic symptoms was associated with an increased likelihood of asthma and severe asthma Asthma was related to anxiety prior to (OR=1.6 (CI 1.2–2.2)), but not after controlling for adverse childhood experiences (e.g., SES, abuse,

Main Findings

242 L. S. Elwood, B. O. Olatunji

Sample

Children recruited from an asthma clinic, a cardiology clinic

Study

Gupta et al. (2001)

Table 1 (Continued)

time period; also obtained self-report of number of asthma related medical consultations in past year, number of asthma attacks in past year, frequency of medication, and current frequency of symptoms Diagnosis, needed change of 15% in FEV, severity determined by number of breakthrough attacks

Asthma Measurement

Both groups scored sig higher on medical fears, fear of injury and small animals than norms; both groups scored sig higher than norms on the internalizing T score on the CBCL and on the anxiety/depression factor of the CBCL; both groups scored higher on the physiological anxiety subscale of the RCMAS than norms

Children: Fear Survey Schedule-Revised; RCMAS; Parents: CBCL, STAI

Main Findings parental conflict) OR = 1.2 (CI .5–2.9); suggested a third common factor

Compared to cardiology patients

Comparison group

symptoms but not disorder

Anxiety Measurement

Asthma and Anxiety 243

Sample

Community sample, sample based on island-wide probability household sample of children

Community sample, sample based on island-wide probability household sample of children

Study

Ortega et al. (2003)

Ortega et al. (2004)

Table 1 (Continued)

Parental reports of an asthma diagnosis and parental reports of the child ever having an asthma attack

Parent report of asthma symptoms, diagnosis, or asthma related hospitalization

Asthma Measurement

DISC; anxiety disorders included: panic disorder, separation anxiety disorder, social phobia, PTSD, and GAD

DISC, used diagnostic categories of anxiety, affective, and disruptive disorders; diagnoses of separation anxiety, social phobia, major depression, conduct disorder, oppositional defiant disorder, and ADHD

Anxiety Measurement

Children with and without reported histories of asthma

Asthma to no asthma

Comparison group

After controlling for maternal mental health, income, and education asthma diagnosis was associated with having any psychiatric disorder, any affective disorder, having more than one disorder, and ADHD; Asthma attack associated with most disorders, but not social phobia or conduct disorder; hospitalization was associated with separation anxiety disorder. Children with a history of asthma attacks had higher prevalence of any anxiety disorder; however, separation anxiety disorder was the only individual anxiety disorder that was significantly different between groups

Main Findings

244 L. S. Elwood, B. O. Olatunji

Sample

Adolescents with and without asthma; with asthma recruited from general and lung physicians

Adolescents with mild to severe stable asthma and healthy participants without asthma

Outpatients from pediatric allergology and pneumology department compared to healthy community participants recruited from schools

Study

Rietveld (2000)

Rietveld et al. (2000)

Vila et al. (2000)

Table 1 (Continued)

Moderate to severe persistent asthma

Severity of asthma classified from one to five; class 1 (if needed bronchodilator) to class 5 (oral corticosteroids) Severity of asthma was classified based on prescribed medicine: severe, moderatesevere, moderate, moderate-mild, mild

Asthma Measurement

Revised Schedule for Affective Disorders and Schizophrenia for School-aged children; CBCL; Anxiety and Fears Behavioral Scale

STAI

STAI

Anxiety Measurement

Asthmatic children to controls

Compared asthmatics to healthy controls

With asthma to healthy controls

Comparison group

Average threshold for breath holding did not differ between groups; state anxiety of participants with asthma was sig higher than those without; No sig differences in trait anxiety 35% of the asthmatic children had at least one DSM-IV anxiety disorders (29% GAD, 16% separation anxiety disorder, 10% social phobia, 1% panic); children with asthma reported significantly higher levels of anxiety than controls

No sig differences in state or trait anxiety

Main Findings

Asthma and Anxiety 245

Children aged 7–19 were recruited from asthma related summer camps and an inpatient unit; both children and a parent participated

Wamboldt et al. (1998) Severity was determined by a pediatric pulmonologist and allergist/immunologist by reviewing medical records. Asthma rated as mild, moderate, or severe. Parent report of number of days missed from school, number of hospitalizations, number of days hospitalized, and number of emergency visits for asthma.

Asthma Measurement RCMAS; CBCL (parent report)

Anxiety Measurement None

Comparison group

Neither child-reported anxiety nor parentreported internalizing symptoms were significantly elevated

Main Findings

Note. ADHD = Attention Deficit Hyperactivity Disorder, CBCL= Child Behavior Checklist, CIDI = Composite International Diagnostic Interview, DISC = Diagnostic Interview Schedule for Children; GAD = Generalized Anxiety Disorder PTSD = Posttraumatic Stress Disorder, RCMAS = Revised Children’s Manifest Anxiety Scale, STAI = State-Trait Anxiety Interview, Sig. = p < 0.05.

Sample

Study

Table 1 (Continued)

246 L. S. Elwood, B. O. Olatunji

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247

McQuaid, Canino, Goodwin, & Fritz, 2004) samples. The association between asthma and anxiety in children has been reported by studies using a variety of methodologies, including cross-sectional (Butz & Alexander, 1993; Gupta et al., 2001; Vila et al., 2000), epidemiological (Goodwin et al., 2003; Ortega et al., 2003; Ortega et al., 2004), and longitudinal (Goodwin et al., 2004). However, it should be noted that some studies have failed to find a relation between asthma and anxiety in children (e.g., Wamboldt, Fritz, Mansell, McQuaid, & Klein, 1998). While one study reported that children suffering from asthma report higher levels of general anxious symptoms than healthy controls (Gupta et al., 2001), two studies failed to find significant differences between children with asthma and healthy controls on trait anxiety (Rietveld, 2000; Rietveld, Everaerd, & van Beest, 2000). A detailed review of the literature suggests that the discrepancy between studies may partially be accounted for by methodological differences. When relations between asthma and specific anxiety disorders are examined, asthma has been linked specifically to panic disorder (Goodwin, Pine, et al., 2003), separation anxiety disorder (Ortega et al., 2003; Ortega et al., 2004; Vila et al., 2000), and generalized anxiety disorder (Vila et al., 2000) in children. The inconsistent findings regarding the relationship between asthma and anxiety in children highlights the importance of considering sampling approaches as well as the source of data. For example, Wamboldt and colleagues (1998) found that child and parent ratings of the child’s psychological symptoms displayed inconsistent patterns. While the child’s reported level of anxiety failed to be significantly related to asthma severity, asthma severity was significantly related to parent’s ratings of the child’s internalizing symptoms. In addition, parental ratings of the child’s internalizing symptoms were significantly related to the parent’s personal level of physical symptoms, suggesting that parental reports of child symptoms may be biased by their own distress (Wamboldt et al., 1998).

Anxiety in Adults with Asthma Although asthma is commonly observed during childhood, the majority of the research examining the relations between anxiety and asthma has been conducted using adult samples. As outlined in Table 2, studies examining the relations between asthma and anxiety disorders in adults have linked asthma with diagnoses of panic disorder (Afari et al., 2001; Goodwin, Jacobi, & Thefeld, 2003; Brown, Khan, & Mahadi, 2000; Goodwin & Eaton, 2003; Goodwin, Olfson, et al., 2003; Goodwin & Pine, 2002; Lavoie et al., 2005; Nascimento et al., 2002; Perna Bertani, Politi, Colombo, & Bellodi, 1997; Pollack et al., 1996; Shavitt, Gentil, & Mandetta, 1992; Yellowlees, Alpers, Bowden, Bryant, & Ruffin, 1987), social phobia (Afari et al., 2001; Brown et al., 2000; Goodwin, Jacobi, et al., 2003; Nascimento et al., 2002; Perna et al., 1997), generalized anxiety disorder (Goodwin, Jacobi et al., 2003; Goodwin, Olfson et al., 2003; Goodwin & Pine, 2002; Heaney, Conway,

Adult patients with diagnosis of mild to moderate asthma recruited from an asthma clinic

Recruited participants using medication regularly scheduled to receive prednisone at an asthma clinic, Evidence of asthma, recruited from an asthma clinic

COPD patients were recruited from a respiratory unit and controls were recruited from annual check-ups

Afari et al. (2001)

Brown et al. (2000)

Di Marco et al. (2006)

Davis et al. (2002)

Sample

Study

diagnosis of COPD; FEV1 values; Italian versions of the modified Medical Resource Council dyspnea scale and the St. George’s Respiratory Questionnaire

‘‘objective evidence of asthma based on the Canadian Consensus Guidelines’’

Completed a methacholine inhalation challenge test to confirm airway reactivity; FEV1/ FVC FEV1

Asthma Measurement

None

COPD patients compared to healthy controls

Italian version of the STAI

None

SCID-IV

ASI, Sheehan Patient Rated Anxiety Scale (SPRAS), ADIS

Compared to prevalence rates

Comparison group

DIS-III-R

Anxiety Measurement

Table 2 Findings of studies examining the relation between asthma and anxiety in adults

59% met criteria for at least one anxiety disorder; 28% specific phobia, 19% PTSD, 15% PD, 13% social phobia 37% received an anxiety disorder; 11% PD, 6% PTSD, 16% GAD, 3% social phobia, 2% specific phobia a greater percentage of asthma participants endorsed high levels of anxiety (28%) than the control participants (6%).

Participants endorsed PD, agoraphobia, and social phobia at higher rates than general population prevalence rates

Findings

248 L. S. Elwood, B. O. Olatunji

Sample

Respiratory unit clinic

Data was collected as part of the Epidemiologic Study

Adult participants of an epidemiological study

Study

Erhabor & Mosaku (2004)

Goodwin & Eaton (2003)

Goodwin, Jacobi, et al. (2003)

Table 2 (Continued)

Self-report of current and past asthma diagnosis, method of assessment by physician, type of asthma, treatment

Self-report of asthma and treatment of asthma

Diagnosis of asthma,

Asthma Measurement

German National Health Interview and Examination Survey-Mental Health Supplement

DIS, assessed panic attacks

General Health Questionnaire, STAI 1 and 2

Anxiety Measurement

Community individuals without asthma

Individuals with asthma compared to those without

Orthopedic and healthy controls

Comparison group

Asthma patients reported a significantly higher level of state anxiety than orthopedic and healthy participants; No sig differences in trait anxiety; Asthmatic patients scored significantly higher on the General Health Questionnaires (indicating higher psychiatric symptoms) Individuals with asthma were sig more likely to report PAs at baseline, OR= .75 (CI 1.08–2.84), and continued PAs at time 2, but not incident PAs at time 2. Reported treated asthma was associated with higher number of symptoms during PA Current severe asthma was associated with any anxiety disorder, specific phobia, PD, and PAs. Lifetime severe asthma was associated with any anxiety

Findings

Asthma and Anxiety 249

Sample

Adult community sample

Study

Goodwin & Pine (2002)

Table 2 (Continued)

Self-report. Assessed both respiratory disease (asthma, chronic bronchitis, and emphysema) and lung disease (other lung disease).

sought, and severity of attacks. Rated as current if present in the last 4 weeks. Categorized as severe or nonsevere

Asthma Measurement

CIDI short form

followed by Munich CIDI

Anxiety Measurement

Community individuals without respiratory & lung disease

Comparison group

disorder, PD, PAs, social phobia, specific phobia, GAD, bipolar, and any severe mental disorder. Current nonsevere asthma was associated with any affective disorder, any severe mental disorder. Lifetime nonsevere asthma was associated with any anxiety disorder, anxiety NOS, any somatoform disorder, and any severe mental disorder. PAs, OR = 2.2 (CI 1.7–3.0) and GAD, OR = 1.5 (CI .6–2.2) were associated with respiratory disease, lung disease, and comorbid respiratory and lung disease. When comorbid mental disorders and physical problems were controlled for, only PAs were associated with respiratory disease and lung disease.

Findings

250 L. S. Elwood, B. O. Olatunji

Sample

Adult primary care patients at an internal medicine clinic

Adult participants of an epidemiological study, data collected over 20 yrs

Study

Goodwin, Olfson, et al. (2003)

Halser et al. (2005)

Table 2 (Continued)

Self-report of asthma symptoms and selfreport of physician diagnosis

Asthma diagnoses obtained from billing encounter data

Asthma Measurement

SCL-90-R, Structured Psychopathological Interview and Rating of the Social Consequences for Epidemiology; assessed for the presence of panic disorder, any panic, and childhood anxiety

PRIME-MD; Patient Health Questionnaire; panic attack and panic disorder were collapsed into one group

Anxiety Measurement Compared patients with and without diagnoses of asthma

Comparison group

Participants with asthma were sig more likely to report PA and GAD than those without; PA remained sig after controlling for sociodemographic characteristics the association PAs remained sig., OR = 1.8 (CI 1.2–2.7), but GAD did not, OR = 1.4(CI = .9–2.2) Cross-sectional results: 21% of individuals with asthma met criteria for PD, 33% met criteria for any panic symptoms; 20% of individuals with PD met criteria for asthma, 12% of individuals with any panic met criteria for asthma; asthma was more strongly associated with PD than any panic; Longitudinal results: asthma and panic were not associated at baseline; asthma was predictive of

Findings

Asthma and Anxiety 251

Participants were recruited if they had 1) persisting refractory symptoms prompting referral, 2) minimal maintenance therapy of long acting b2 agonists, and inhaled steroids 3) at least 1 course of systematic steroids in preceding 12 months

Heaney et al. (2005)

Jonas et al. (1999)

Sample

Study

Table 2 (Continued)

HADS; psychiatric interview offered to participants

Examined difficult to control asthma; Asthma defined on the basis of symptom with documented reversible airflow obstruction (FEV1 of > 12%), skin prick testing to 12 inhalant allergens, chest x-ray, and spirometric testing; Asthma related quality of life assessed using the Juniper scale Self-report of doctor diagnosed asthma General Well Being Schedule, relaxed

Anxiety Measurement

Asthma Measurement

None

Compared treatment (for asthma) responders to treatment non responders

Comparison group

For non-smokers, increasing asthma incidence rates were

subsequent PD and any panic, although when demographic data was included the only held up for women and smokers; PD, but not any panic, was a significant predictor of later asthma; childhood anxiety also predicted subsequent asthma GAD was the most common anxiety disorder (16%), also found PTSD, acute stress reaction, and specific phobia (no mention of PD, Anxiety did not sig decrease across treatment and was not sig different between treatment responders and treatment nonresponders

Findings

252 L. S. Elwood, B. O. Olatunji

Lavoie et al. (2005)

Study Spirometry was measured as 65% FEV1, 65%, or no best trial. Respiratory symptoms were coded as present or absent: 1) a cough in morning or winter or, 2) in the summer, 3) any phlegm from chest in the morning in the winter, or 4) the summer, 5) a period of increased cough and phlegm lasting for 3 weeks þ during the past 3 years, 6) shortness of breath, and 7) wheezy or whistling sounds in chest Primary diagnosis of asthma; Asthma Control Questionnaire and Asthma Quality of

Adults 25 to 74 at baseline and received a medical examination.

Adult patients presenting to asthma clinic

Asthma Measurement

Sample

Table 2 (Continued)

PRIME-MD

versus anxious scale.

Anxiety Measurement

Compared asthma patients with and without

Comparison group

25% met criteria for one or more anxiety disorder, PD most common (12%); 36% reported a lifetime history of PAs

found for increasing anxiety. When split between presence and absence of early asthma symptoms, similar pattern for no early symptom nonsmokers.

Findings

Asthma and Anxiety 253

Sample

Outpatients presenting to an anxiety disorders specialty clinic, met criteria for a principal diagnosis of PD with or without agoraphobia

Study

Meuret et al. (2005)

Table 2 (Continued) Anxiety Measurement

ADIS-IV-L

Asthma Measurement Life Questionnaire asthma diagnoses confirmed by chart evidence of a 20% fall in FEV1 after metacholine challenge and/or bronchodilator reversibility in FEV1 of 20% predicted; severity rated based on clinical symptoms, medication usage, and pulmonary functioning Self report anxiety disorders

Comparison group

13% of the sample reported current asthma, which was stated as being higher than in the general population; patients with a current diagnosis of asthma reported significantly higher levels of the cardiorespiratory symptom group but no difference in the other symptom groups

Findings

254 L. S. Elwood, B. O. Olatunji

Sample

Outpatients from an asthma unit (age range 13–80, mean 50.2)

Outpatients recruited from Allergology Clinic; diagnosis of asthma

Study

Nascimento et al. (2002)

Perna et al. (1997)

Table 2 (Continued)

asthma defined by recurrent episodes of dyspnea with diffuse wheezing and either a 20% improvement in FEV1 following a nebulized b2 agonist bronchodilator or a 20% decrease in FEV1 after the metacoline bronchoprovocation test Age and onset of use of beta-agonists by inhalation obtained from medical files. severity of asthma scored as mild, moderate, or severe based on criteria defined by National Asthma Education Program.

Asthma Measurement

DIS-R. Asked to rate the similarity between an asthma attack and a panic attack. Family history of anxiety disorders obtained using a modified Family History Method for Research Diagnostic Criteria

MINI

Anxiety Measurement

None

None

Comparison group

19.6% prevalence of PD, 9.8% prevalence of social phobia, 45% experienced at least one unexpected sporadic PAs. 96% described their PAs as ‘‘completely different’’ than their asthma attacks. 54% indicated that asthma occurred before panic, compared to 23% that indicated panic before asthma. Participants with PD had higher rates of family history of PD.

52% met criteria for at least one current anxiety disorder; PD 14%, agoraphobia without PD 27%, social anxiety 9%, and GAD 24%; concluded the prevalence of PD, social anxiety, and GAD were higher than found in the general population

Findings

Asthma and Anxiety 255

Sample

Patients presenting for pulmonary function testing

Recruited from asthma outpatient clinic (age range from 14–58, mean 26.8)

Study

Pollack et al. (1996)

Shavitt et al. (1992)

Table 2 (Continued)

Used a computerized grading system developed by the hospital

Asthma Measurement

Screening questionnaire asking about the presence of panic/ anxiety symptoms in association with troubled breathing or subjective anxiety, previous experience of panic, agoraphobic fears, and a question about whether or not they considered themselves to be anxious; SCID

SCID

Anxiety Measurement

None

None

Comparison group

41% reported PAs and 11% reported PD. 67% of participants with COPD met criteria for PD. Participants with PAs or disorder were significantly more likely to complain of dyspnea at rest and irritable bowel syndrome. No sig. differences in pulmonary functioning abnormalities or severity 13% indicated agoraphobia without panic, 6.5% indicated PD; 6% simple phobias, 5% social phobia; concluded found greater than expected prevalence rates of agoraphobia and panic when compared to general population

Findings

256 L. S. Elwood, B. O. Olatunji

Sample

Adult patients recruited from an asthma outpatient clinic, a hospital, psychiatrists, and a department store

Relatives of individuals receiving treatment at an anxiety clinic

Study

Sreedhar (1989)

van Beek et al. (2005)

Table 2 (Continued)

Lifetime prevalence of respiratory disorder was assessed using a questionnaire that distinguishes between asthma, bronchitis, emphysema, and other respiratory disorders; each was rated as past and present

Diagnosis at clinic

Asthma Measurement

MINI

Manifest Anxiety Scale

Anxiety Measurement General hospital outpatients, ‘‘neurotic’’ psychiatry patients, and controls (no physical or mental disorder) Relatives of individuals diagnosed with panic disorder were compared to relatives of individuals diagnosed with other anxiety disorders

Comparison group

Family members of individuals with PD were sig more likely to report lifetime prevalence of a COPD and of asthma specifically than family members of individuals diagnosed with other anxiety disorders

Females experienced higher levels of anxiety than males, but the sexes demonstrated similar patterns of findings. Asthma patients endorsed significantly higher levels of anxiety than general outpatients and controls, but were not significantly different than ‘‘neurotic’’ psychiatry patients

Findings

Asthma and Anxiety 257

Adult patients recruited to a lung function laboratory for a histamine challenge test for clinical diagnosis

Adult patients recruited from a respiratory unit, patients were required to have chronic airflow obstruction from due to bronchitis, emphysema, or asthma

van PeskiOosterbaan et al. (1996)

Yellowlees et al. (1987)

Physician diagnosis based on chart review; International Union Against Tuberculosis and Lung Disease Questionnaire; Borg scale to assess breathlessness; spirometry; FEV1 Pulmonary function tests- FEV1, PaO2, PaCO2

Asthma Measurement Participants given diagnosis of asthma compared to those not given diagnosis of asthma None

Interview assessing DSM-III criteria

Comparison group

ADIS-R, STAI, Agoraphobic Cognitions Scale, Body Sensations Questionnaire, Panic Attack Questionnaire

Anxiety Measurement

36% met criteria for an anxiety disorder; 24% PD, 10% GAD, 2% PTSD

In individuals with asthma, 9% met criteria for current PD and 12.8% in past year, In non-asthma participants, 9% current and 11% in past 12 mos. No sig. differences in PD. Also no sig. differences in pulmonary functioning.

Findings

Note: ASI = ADIS = Anxiety Disorders Interview Schedule, Anxiety Sensitivity Inventory, COPD = Chronic Obstructive Pulmonary Disorder, DISR = Diagnostic Interview Schedule- Revised, FEV1 = Forced Expiratory Volume in the first second of exhalation, FVC = Full Vital Capacity, GAD = Generalized Anxiety Disorder, HADS = Hospital Anxiety and Depression Scale, MINI = Mini International Neuropsychiatric Interview, PAs = Panic attacks, PD = Panic Disorder, PTSD = Posttraumatic Stress Disorder, SCID = Structured Clinical Interview for DSM-III-R, SCL-90-R = Symptom Checklist 90-R, STAI = State Trait Anxiety Inventory. Sig. = p < 0.05.

Sample

Study

Table 2 (Continued)

258 L. S. Elwood, B. O. Olatunji

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259

Kelly, & Gamble, 2005; Nascimento et al., 2002; Yellowlees et al., 1987), posttraumatic stress disorder (Brown et al., 2000), specific phobia (Brown et al., 2000; Goodwin, Olfson, et al., 2003), and anxiety not otherwise specified (Goodwin, Jacobi et al., 2003). The association between anxiety and asthma in adults has been supported in clinical (Afari et al., 2001; Brown et al., 2000; Davis, Ross, & MacDonald, 2002; Di Marco et al., 2006; Erhabor & Mosaku, 2004; Goodwin, Olfson, et al., 2003; Heaney et al., 2005; Lavoie et al., 2005; Nascimento et al., 2002; Perna et al., 1997; Pollack et al., 1996; Shavitt et al., 1992; Sreedhar, 1989; Yellowlees et al., 1987) and non-clinical samples (Goodwin & Eaton, 2003; Goodwin, Jacobi et al., 2003; Goodwin & Pine, 2002; Halser et al., 2005; Jonas et al., 1999). The relation has been reported by cross-sectional (Afari et al., 2001; Brown et al., 2000; Davis et al., 2002; Di Marco et al., 2006; Erhabor & Mosaku, 2004; Goodwin & Pine, 2002; Goodwin, Olfson, et al., 2003; Heaney et al., 2005; Lavoie et al., 2005; Meuret, White, Ritz, Roth, Hofmann, & Brown, 2005; Nascimento et al., 2002; Perna et al., 1997; Pollack et al., 1996; Shavitt et al., 1992; Sreedhar, 1989; Yellowlees et al., 1987), epidemiological (Goodwin & Eaton, 2003; Goodwin, Jacobi, et al., 2003; Halser, et al., 2005), and longitudinal (Halser et al., 2005; Jonas, Wagener, Lando, & Feldman, 1999) studies. Recently, the World Mental Health Survey examined the relation between psychopathology and asthma (Scott et al., 2007). Participants from 17 different countries provided information about whether or not they had ever been diagnosed with asthma and completed a structured interview to assess for the presence of selected psychological disorders (GAD, panic disorder, PTSD, social phobia, dysthymia, major depressive disorder, and alcohol use and dependence) in the past year. The pooled estimate of the OR for the anxiety disorders fell within the 1.3–1.8 (all anxiety disorders exhibited an OR greater than 1) and the pooled estimate of the OR for any anxiety disorder was 1.5 (95% CI 1.4–1.7, Scott et al., 2007). When the individual surveys were examined, all but one survey fell within the 95% confidence interval. Both depressive disorders and alcohol use disorders were also significantly associated with asthma and similar strengths of association were evidenced across the mental disorders (Scott et al., 2007). Although it is clear that the experience of asthma and anxiety share many overlapping features, research attempting to highlight the specific nature of this overlap in adults has yielded inconsistent findings. For example, some studies have found that individuals with asthma display higher levels of general anxious symptoms than healthy controls (Di Marco et al., 2006; Sreedhar, 1989). However, another study found significant differences in state, but not trait, anxiety (Erhabor & Mosaku, 2004). One study differentiating between airway obstruction specific anxiety and trait-like anxiety also failed to find a significant relation between levels of airway obstruction anxiety and baseline measures of anxiety (Spinhoven, van Peski-Oosterbaan, Van der Does, Willems, & Sterk, 1997). However, a recent longitudinal study found that the onset of anxiety was significantly associated with the development of asthma nine years later, OR = 3.53 (CI 1.03–12.1; Neuman et al., 2006).

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Specificity of Panic Disorder in Asthma Panic disorder has been suggested to be the anxiety disorder that most frequently co-occurs with asthma and has been more frequently studied in relation to asthma than other anxiety disorders. Indeed, studies have consistently shown that individuals with asthma report higher levels of both panic attacks and panic disorder than found in the general population (Goodwin & Eaton, 2003; Goodwin, Jacobi et al., 2003; Perna et al., 1997; Pollack et al., 1996). Butz and Alexander (1993) reported that 65% of their sample of children diagnosed with acute asthma reported feeling ‘‘panic’’ at the beginning of an asthma attack, and the presence of panic feelings accompanying asthma attacks significantly predicted trait anxiety. The relation between asthma and anxiety is supported when individuals with anxiety are examined as well. Meuret and colleagues (2005) found that 13% of participants seeking treatment for panic disorder reported current asthma. Those with co-occurring asthma and panic also reported higher cardio-respiratory symptoms than participants with panic alone but did not differ in severity on other types of panic symptoms (i.e., autonomic/somatic and cognitive symptoms; Meuret et al., 2005). In an attempt to examine the association between asthma and anxiety in families, van Beek, Schruers, and Griez (2005) recruited family members of individuals receiving treatment for an anxiety disorder and obtained information about their pulmonary health. Results revealed that family members of individuals with panic disorder were significantly more likely to report a lifetime prevalence of asthma than family members of individuals diagnosed with other anxiety disorders. Panic attacks and asthma attacks have similar symptom presentations including sensations of being smothered, choking, and hyperventilation (Feldman, Giardino, & Lehrer, 2000; Perna et al., 1997). However, studies have shown that asthma and panic can be differentiated by specific processes. For example, Schmaling and Bell (1997) recruited participants suffering from either panic disorder or asthma who completed the Asthma Symptom Checklist (ASC; Kinsman, Luparello, O’Banion, & Spector, 1973) for a relevant attack. The findings showed that the panic fear, OR = 0.5, and hyperventilation/hypercapnia, OR = 0.70, subscales of the ASC significantly predicted panic disorder, while the airway obstruction scales, OR =1.73 (dyspnea and congestion) predicted asthma. There is also some evidence suggesting that individuals suffering from asthma and panic are able to differentiate between the two. Indeed, one study found that 96% of participants, outpatients receiving treatment for allergy at a specialized clinic, described their panic attacks as ‘‘completely different’’ than their asthma attacks (Perna et al., 1997). When the temporal nature of the two conditions is examined, participants typically report experiencing asthma attacks before panic attacks (Feldman, Lehrer, Borson, Hallstrand, & Siddique, 2005; Perna et al., 1997). Studies that have compared patients with asthma and panic to those with asthma alone suggest that individuals with co-occurring asthma and panic

Asthma and Anxiety

261

suffer from additional consequences. For example, individuals with asthma and panic have been found to endorse increased dyspnea at rest, irritable bowel syndrome, and global distress (Dorhofer & Sigmon, 2002; Pollack et al., 1996). Feldman and colleagues (2005) found that individuals with asthma (physician diagnosed) and panic disorder (based on results of a structured interview) reported more frequent visits to their primary care providers, lower overall quality of life, greater restriction of activities, and greater emotional difficulties than individuals with asthma alone. In addition, women with asthma and panic exhibited significantly greater skin conductance responses and anxious mood than individuals with asthma alone after being exposed to both neutral and asthma related scenes (Dorhofer &, Sigmon 2002). Taken together, these findings suggest that individuals with comorbid asthma and panic disorder display lower levels of functioning across various domains than individuals with asthma alone. Longitudinal examinations may provide valuable information about the temporal nature of the comorbidity of asthma and panic. In a longitudinal epidemiological study, Goodwin and Eaton (2003) found that the presence of asthma was significantly associated with the presence of panic attacks one year later. A recent 20 year longitudinal epidemiological study found a bidirectional relationship between panic disorder and asthma (Halser et al., 2005). Asthma served as a significant predictor of future panic disorder, OR = 4.5 (CI 1.1–20.1), and panic disorder served as a significant predictor of future asthma, OR = 6.3 (CI 2.8–14.0). When the criteria were expanded to include any panic symptoms, panic symptoms predicted future asthma but asthma failed to predict future panic symptoms. Interestingly, when demographic variables were controlled for, asthma remained a predictor of future panic disorder in women, OR = 2.9 (CI 1.1–8.6), and smokers, OR = 3.5 (CI 1.0–13.4), but not for men, OR = 1.9 (CI .2–19.6), and nonsmokers, OR = 2.1 (CI .5–8.5). Family history of allergy, OR = 1.8 (CI 1.1–2.9), smoking, OR = 1.6 (CI 1.0–2.5), and childhood anxiety, OR = 0.6 (CI .3–1.3), demonstrated the strongest relations with the development of panic disorder and appear to be the strongest confounds of the panic-asthma relation (Halser et al., 2005). Although more recent research has begun to address processes that underlie the comorbidity between asthma and panic disorder, the specificity of the asthma-panic relation remains somewhat unclear. For example, one study failed to find significant differences in the diagnosis of panic disorder between the asthma and non-asthma groups among patients referred for a histamine challenge test (van Peski-Oosterbaan, Spinhoven, van der Does, Willems, & Sterk, 1996). In addition, no differences in asthma symptom severity were found between those with and without panic disorder. The authors concluded that panic disorder was unlikely to be specifically related to asthma, but rather was likely to be generally related to illness and medical attention seeking behaviors (van Peski-Oosterbaan et al., 1996).

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Anxiety and Asthma Symptom Severity One explanation of the relation between asthma and anxiety is that individuals experience anxiety in response to their asthma symptoms (Katon et al., 2004). In support of this notion, two studies (Hommel, Chaney, Wagner, & McLaughlin, 2002; Hommel, Chaney, Wagner, White, Hoff, & Mullins, 2003) have reported significant correlations between objective asthma illness severity (peak flow rates) and self-reported anxiety (using the Beck Anxiety Symptom Inventory; BAI). However, several studies have also failed to find significant relations between asthma severity and/or pulmonary functioning and levels of anxiety (Di Marco et al., 2006; Feldman et al., 2005; Kinsman, Dirks, & Jones, 1980; Lavoie et al., 2005; Pollack et al., 1996; Rimington, Davies, Lowe, & Pearson, 2001; Rushford, Tiller, & Pain, 1998; Sa´ndez, Va´zquez, Romero-Frais, BlancoAparicio, Otero, & Verea, 2005). Furthermore, no significant relationship has been observed between self-reported (both questionnaire and diagnostic interview) baseline anxiety and respiratory symptom severity perception during histamine induced bronchoconstriction in patients with asthma (Spinhoven et al., 1997). Individuals with life-threatening asthma also do not appear to endorse significantly higher levels of anxiety disorders, based on responses to diagnostic interviews, than those with less severe asthma (Yellowlees, Haynes, Potts, & Ruffin, 1988). In a study that compared asthmatics with and without panic disorder, results of a histamine challenge test indicated that patients did not differ in overall pulmonary functioning as measured by FEV1 (van Peski-Oosterbaan et al., 1996). However, asthmatic patients with panic disorder reported higher levels of perceived breathlessness after completing the histamine challenge test than asthmatic patients without panic disorder (van Peski-Oosterbaan et al., 1996). Although the findings are equivocal, there does not appear to be a strong relation between asthma severity and anxiety symptoms. An alternative explanation for the relation between anxiety and asthma is that the presence of anxiety could potentially influence the individual’s interpretation of and reaction to his or her asthma symptoms. In a recent study by Chen and collogues (Chen, Hermann, Rodgers, Oliver-Welker, & Strunk, 2006), eighty-six children with mild or moderate asthma had symptom perception and pulmonary function measured throughout methacholine challenge (to induce bronchoconstriction). Higher trait anxiety was associated with heightened symptom perception and greater asthma severity was associated with blunted symptom perception and with a slower rate of increase in symptom perception across the methacholine challenge. These results suggest that anxiety may only play a role when symptoms are mild, whereas medical variables, such as asthma severity, play a role in perception of changes in asthma symptoms as bronchoconstriction worsens. Past studies have failed to find a significant relation between anxiety and subjective severity of symptoms, suggesting that the interpretation of the symptoms themselves may not be different between those with and without

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anxiety (Hommel et al., 2002, Hommel et al., 2003). Rather, the influence of anxiety may result in behavioral changes such as increased treatment seeking, increased avoidance of situations perceived as threatening, and decreased selfefficacy which may reduce the individual’s quality of life.

The Effects of Anxiety on Asthma Related Quality of Life There is evidence suggesting that increased levels of anxiety are associated with poorer quality of life in individuals with asthma (Di Marco et al., 2006; Feldman et al., 2005; Hommel et al., 2002; Lavoie et al., 2005; Rimington et al., 2001). The co-occurrence of anxiety and asthma may also be related to worse asthma medication usage (Lavoie et al., 2005). For example, individuals with asthma and comorbid psychiatric disorders (as diagnosed through a structured interview) have reported greater use of bronchodilators than individuals with asthma alone (Lavoie et al., 2005). High scores on the Minnesota Multiphasic Personality Inventory (MMPI) scale Pt, indicative of general anxiety, have been associated with arbitrary use of bronchodilators (Mawhinney, Spector, Heitjan, Kinsman, Dirks, & Pines, 1993). An association has also been found between high levels of self-reported anxious symptoms and low inhaled steroids treatment adherence (Cluley & Cochrane, 2001). However, the demonstrated negative impact of anxiety on asthma-related quality of life has not been a consistent finding in the literature. For example, some studies have failed to find a significant relation between anxiety and asthma control. One study failed to find a significant association between the presence of an anxiety disorder in adults being treated for asthma, as indicated by a structured interview, and overall physical, role, and social functioning (Afari et al., 2001). A second study found that self-reported levels of anxious symptoms were not related to overall functional morbidity, including number of days missed from school, number of hospitalizations, number of days hospitalized, and number of emergency visits for asthma in children (Wamboldt et al., 1998). Studies have also failed to find significant relations between self-reported anxiety and treatment compliance with inhaled corticosteroids and beta-agonists (Bosley, Fosbury, & Cochrane, 1995), overall health care use (i.e., primary care visits, hospital visits, and oral steroids; Kullowatz, Kanniess, Dahme, Magnussen, & Ritz, 2007) and emergency room visits (Nouwen, Freeston, Labbe´, & Boulet, 1999; Wamboldt et al., 1998). These findings suggest that anxiety in individuals with asthma may influence some domains of quality of life more than others. In addition, there may be moderating variables that predict when anxiety results in poorer quality of life in patients with asthma.

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Anxiety Vulnerabilities in Asthma Anxiety and asthma share common symptoms and are often comorbid, perhaps reflecting a shared pathophysiological vulnerability (Smoller & Otto, 1998). The construct of ‘‘panic-fear’’ (P-F) has been proposed as a potential vulnerability that may account for the occurrence of excessive anxiety in patients with asthma (Kinsman et al., 1973). P-F refers to subjective panic and anxious feelings associated with asthma episodes and the perception of bronchoconstriction. Individuals high in P-F react to asthma symptoms by emphasizing their distress in an anxious, dependent, and ineffective way (Kinsman et al., 1980). P-F was originally assessed as a subscale of the Asthma Symptom Checklist (Kinsman et al., 1973), however Dirks and colleagues later developed a 15-item MMPI subscale to assess the construct (Dirks, Jones, & Kinsman, 1977). The MMPI scale uses original MMPI questions and was created by selecting items that significantly differentiated between individuals that scored low, moderate, and high on the ASC’s P-F scale. One study found that while the ASC P-F scale significantly predicted the diagnosis of panic disorder in participants with asthma, the MMPI P-F scale did not (Carr, Lehrer, & Hochron, 1995). This suggests that items that assess physical symptoms specifically (i.e., the ASC) may be more strongly related to panic disorder. High levels of P-F have been linked with poorer asthma-related quality of life (Va´zquez, 2000), particularly in the physical (e.g., limitations in self-care, physical and social role activities, bodily pain, and poor physical health) domain (Sa´ndez et al., 2005). Individuals with high P-F have also been found to be more pessimistic about their ability to cope with and master their asthma, feel more stigmatized and psychologically different from others, feel more anxiety about their asthma attacks, and feel more frequent irritation, worry, isolation, and hyperventilation (Kinsman et al., 1980). Finally, levels of P-F have differentiated between individuals with asthma that frequently visit the emergency room and those without emergency room visits (Nouwen et al., 1999). Anxiety sensitivity (AS) has also been examined as a potential vulnerability that may account for the link between asthma and anxiety. AS is the fear of anxiety and anxiety related sensations based on the belief that the symptoms have harmful consequences (Reiss, 1991). AS is a stable, trait-like characteristic that functions as a vulnerability to the development and maintenance of anxious symptoms, particularly panic disorder (Taylor, Koch, & McNally, 1992). AS also has been found to significantly predict levels of panic fear among individuals with asthma (Carr et al., 1995). Carr, Lehrer, Rausch, and Hochron (1994) conducted a study examining the role of AS in individuals with asthma and found that endorsement of panic symptoms was significantly related to level of AS. Thirty-six percent of participants that endorsed high levels of AS met criteria for panic disorder, while none of the individuals that endorsed low levels of AS met criteria for panic disorder. In addition, the mean AS scores of the participants with asthma and panic disorder were higher than

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those without panic disorder (Carr et al., 1994). A similar study found that women with asthma alone, panic alone, and asthma and panic endorsed higher levels of AS than controls (Dorhofer & Sigmon, 2002). However, one study did fail to find a significant relation between severity of asthma and level of AS (Asmudson & Stein, 1994). The precise nature of the relation between AS and asthma is unclear. However, a review of the available literature did lead to a tentative conclusion that that there may not be a direct relation between asthma and AS, but instead that the relation may be mediated by their common association with panic disorder (Asmundson, Wright, & Hadjistavropoulos, 2000).

Smoking and Anxiety Vulnerability in Asthma There is also evidence that smoking is a risk factor for, and may serve to maintain, some anxiety conditions, particularly; panic attacks and panic disorder (see Zvolenksy & Bernstein, 2005). However, few studies have examined how smoking and anxiety interact in the context of asthma. In a populationbased cohort study of 5,231 participants (Jonas et al., 1999), non-asthmatic persons aged 25 to 74 were followed for 13 years. For nonsmokers and persons without respiratory symptoms, a high level of anxiety was a predictor of increased asthma incidence rates. For the smokers, the relative risks for high anxiety were not significantly elevated and there was no clear pattern between anxiety symptoms and risk for the development of asthma. Although research has also shown a robust association between anxiety and asthma, preliminary findings highlight the possibility that the presence of smoking may suppress the effects of anxiety symptoms on the subsequent development of asthma.

Specificity of the Anxiety-Asthma Relation Although the extant research literature suggests that individuals with asthma are at an increased risk of developing anxiety disorders, and panic disorder in particular, when compared to healthy controls (Goodwin, Jacobi, et al., 2003; Goodwin & Eaton, 2003; Goodwin & Pine, 2002), comparing individuals with asthma to healthy controls does not provide information about the specificity of the relation between asthma and anxiety. Consequently, some studies have taken the approach of including an additional non-asthmatic medical group as a comparison condition. Such studies are particularly helpful in determining if increased anxiety is related to the presence of a medical condition or a reflection of an effect that is unique to asthma. In an early study, Sreedhar (1989) compared participants with asthma to general hospital outpatients, ‘‘neurotic’’ psychiatry patients, and controls (with no physical or mental disorder). Results revealed that participants with asthma endorsed significantly higher levels of

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anxiety than the general outpatients and controls, but were not significantly different on anxiety than the psychiatric participants (Sreedhar, 1989). Similarly, Erhabor and Mosaku (2004) found that patients with asthma reported higher levels of state anxiety and other psychiatric symptoms than orthopedic participants and controls, but failed to find significant group differences for trait anxiety. However, there is evidence that children with asthma endorse higher levels of trait anxiety than children with diabetes (Vila et al., 1999). Asthma patients have also been found to report higher levels of trait anxiety than patients with peptic ulcers and controls (Shanmugam & Kaliappan, 1982). Children with asthma and those with congenital heart disease have been found to score significantly higher than the general population on multiple measures of anxiety (Gupta et al., 2001). However, asthmatic children were found to score higher than children with congenital heart disease only on medical fears (Gupta et al., 2001). These findings generally suggest that individuals with asthma endorse greater levels of anxiety than individuals with other medical conditions.

Towards a Cognitive-Behavioral Model of the Co-occurrence of Anxiety and Asthma Asthma and symptoms of anxiety share many similar symptoms and often cooccur, suggesting that perhaps both conditions share a common underlying vulnerability. It has been suggested that respiratory distress may be the common pathophysiology between asthma and anxiety symptoms, particularly the experience of panic and panic disorder (Smoller, Pollack, Otto, Rosenbaum, & Kradin, 1996). Respiratory distress as a common pathophysiology may also be observed as exaggerated increases in respiratory drive. There is research evidence that increases in respiratory drive (typically assessed by introducing occlusion of breathing during inhalation through a tube) can be easily induced in asthmatics (Kelsen, Fleeger, & Altose, 1979). Respiratory distress may lead to episodes of hyperventilation, particularly in the absence of increases of a physiological need for ventilation (Lehrer, 1998). The physical sensations associated with episodes of hyperventilation may give rise to panic and anxiety. Feldman and colleagues (2000) have suggested that the experience of respiratory distress (e.g., dyspnea) in asthma and anxiety-related conditions may also be mediated by CO2 hypersensitivity. As a consequence of bronchoconstriction in asthma, medullary chemoreceptors and/or the locus coeruleaus may be stimulated. Repeated stimulation of the chemoreceptors may result in a low ‘‘suffocation alarm’’ threshold (Klein, 1993). This process may serve as the developmental context for a vulnerability for anxiety/panic vulnerability in patients with asthma. Although biological models based on CO2 hypersensitivity and a low ‘‘suffocation alarm’’ threshold are consistent with the clinical description of anxiety/panic symptoms observed in patients with asthma, the

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underlying processes articulated by these modes have not consistently been supported in basic laboratory research (see Smoller et al., 1996 for review). A cognitive-behavioral approach that emphasizes dysfunctional beliefs about bodily symptoms may also have utility in better understanding how the experience of anxiety is reinforced and subsequently maintained in the context of asthma (Smoller et al., 1996). AS, the fear of bodily sensations derived from beliefs that such sensations have harmful consequences, had been shown to be a risk factor for the development of anxiety-related conditions, especially panic disorder. AS is proposed to arise from the combination of genetic predispositions (Stein, Jang, & Livesley, 1999) and learning experiences that result in the acquisition of beliefs about potential harmful effects of autonomic arousal (e.g., Stewart et al., 2001). Previous longitudinal research has shown that asthma occurs first thus possibly serving as a risk factor for the development of anxiety-related problems (Goodwin & Eaton, 2003; Perna et al., 1997). A risk factor is a variable that is related to, and temporally precedes, an undesirable outcome. At some level, asthma may be regarded as non-malleable in that it is chronic and when a risk factor is non-malleable (cannot be changed); it may be classified as a fixed marker (see Zvolensky, Schmidt, Bernstein, & Keough, 2006 for review). However, negative attributions and beliefs that derive from asthma can be classified as variable risk factors for anxiety in that they can be changed. Although the identification of asthma may prove to be important for identifying individuals who may be at risk for the development of anxiety conditions, negative attributions and beliefs that derive from asthma will ultimately be the target of preventative interventions. Asthma and associated beliefs may serve as a context in which vulnerable individuals learn to fear bodily sensations because such sensations could potentially have harmful consequences (i.e., AS). Fig. 1 graphically depicts a cognitive-behavioral model that may be used as a heuristic for conceptualizing excessive anxiety that may be experienced in patients with asthma. This model is adapted from available models that stress the importance of the misinterpretation of physical symptoms in the etiology and maintenance of anxiety-related conditions (Abramowitz, Deacon, & Valentiner, in press). The perceived severity of past asthma attacks may increase the perceived severity and consequences of future attacks (Ten Thoren & Petermann, 2000). According to this cognitivebehavioral model, mistaken beliefs about the likelihood and severity of having an asthma attack among those predisposed towards being fearful of bodily sensations may be the foundation for the development of anxiety pathology. Such beliefs also include the assumption that the experience of respiratory symptoms always indicate that something is seriously wrong (i.e., hurt equals harm). Given that asthma episodes are often unpredictable and may be perceived as uncontrollable, asthma-related dysfunctional beliefs may be mobilized to deal with the uncertainty. However, chronic perceptions of unpredictability and uncontrollability have a strong negative impact on functioning and have been implicated in the development of anxiety-related disorders (Mineka & Zinbarg, 1996).

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Asthma-related dysfunctional beliefs among those fearful of bodily sensations may then motivate vigilance for respiratory cues. For example, it has been shown that asthma patients with panic disorder tend to perceive more symptoms of dyspnea during a histamine challenge than asthma patients without panic disorder, although the two groups did not differ with regard to the effects of histamine on pulmonary function (van Peski-Oosterbaan et al., 1996). Excessive respiratory vigilance among asthmatics increases the likelihood of noticing and misinterpreting respiratory and other bodily sensations. Indeed, there is evidence that asthmatic who are also high in anxiety symptoms mislabel nonrespiratory sensations (i.e., feelings of fatigue) as symptoms of asthma (Dirks, Schraa, & Robinson, 1982). These beliefs increase the risk of developing catastrophic cognitions when individuals are exposed to ambiguous (benign) bodily symptoms. For example, someone who believes they are at high risk of having an asthma attack might become anxious if he or she notices even a slight feeling of tightness in the chest (‘‘this symptom means I am having an asthma attack’’). Catastrophic cognitions about benign symptoms may increase feelings of worry, anxiety, and panic in individuals with asthma. Feelings of uncertainty about respiratory symptoms may also contribute to the development of clinical anxiety among individuals with asthma. Indeed, it has been shown that uncertainty contributes unique variance to anxiety symptoms among patients with asthma when controlling for demographic, disease, and psychological variables (Hommel et al., 2003). The cognitive-behavioral model also suggests that anxiety symptoms are maintained by the very strategies individuals with asthma use to cope with their symptoms, such as attempts to prevent or regulate the experience of bodily sensations. For example, anxiety symptoms in patients with asthma are associated with excessive use of as-needed medications (Kinsman, Dahlem, Spector, Staudenmayer, 1977) and more hospital readmissions (Dirks, et al., 1977) even when controlling for asthma disease severity (Wamboldt et al., 1998). These safety-seeking behaviors function to prohibit individuals with asthma from acquiring information that would disconfirm their dysfunctional beliefs.

Cognitive-Behavioral Treatment of Anxiety in Asthma Although asthma may be a fixed marker, specific interventions derived from the cognitive behavioral model may have clinical utility for the treatment and prevention of anxiety among patients with asthma (Smoller et al., 1996). Such interventions directly target catastrophic cognitions and the preoccupation and fear of bodily sensations that may have specific links with anxiety, as such symptoms appear to differentiate asthma patients who develop an anxiety disorder, particularly panic, from asthma patients that do not develop an anxiety disorder (Carr et al., 1994). However, it should be noted that the experience of anxiety among patients with asthma is not necessarily

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Dysfunctional Beliefs Overestimating the likelihood/severity of having an asthma attack prevents acquisition of disconfirmatory evidence

selective attention to signs of asthma

Safety-Seeking Behaviors

Respiratory Vigilance increase likelihood of noticing benign respiratory sensations

motivation to avoid sensations and perceived harm

Uncertainty/Anxiety/Panic

Perception of Airway Symptoms misinterpretation of ambiguous symptoms

activate respiratory fear

Catastrophic Cognitions About Symptoms Fig. 1 Cognitive-behavioral model of excessive anxiety in patients with asthma

problematic. Thus, the across-the-board application of cognitive behavioral treatment for anxiety reduction in asthma is not indicated (Kinsman, Dirks, Jones, & Dahlem, 1980). Among some patients, the experience of anxiety may improve self-care by motivating patients with asthma to seek treatment. In fact, there is evidence that the experience of low generalized anxiety and panic is associated with a lower risk of rehospitalization among patients with asthma (Jones, Kinsman, Dirks, & Dahlem, 1979). Although some degree of anxiety regarding asthma is adaptive in motivating self care, there is evidence that morbidity tends to be higher among asthmatic patients who experience symptoms of panic disorder (Baron et al., 1986). Cognitive behavioral interventions aimed at anxiety management may be useful adjunctive treatments for asthma patients who are particularly fearful of bodily sensations. Feldman and colleagues (2000) have outlined a cognitive behavioral treatment of panic that has been adapted for patients with asthma. This intervention highlights specific treatment components including: 1) Treatment Rationale and Education (Sessions 1–2); 2) Asthma Self-Management (Sessions 3–4); 3) Panic Attack Management (Sessions 5–6); 4) Asthma and Panic Differentiation (Sessions 7–8); and 5) Imagery Exposure, Problem Solving, and Relapse Prevention. An important component of this treatment is teaching patients to discriminate asthma and panic symptoms in order to correctly address excessive fear of bodily sensations. Patients are also introduced to interoceptive exposures as a method of confronting feared bodily sensations. The patient is encouraged to practice the exposures (without engaging in safety behaviors) that produces his or her most feared bodily sensations with the goal

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of habituating to these sensations. Respiratory-related exposure is limited to pursed lips breathing in this treatment, pending further evaluation, because of possible iatrogenic effects in patients with asthma. Interoceptive exposure exercises for panic control (e.g., spinning) may be applied if nonrespiratory symptoms (e.g., dizziness) are present. Physical exercises designed to increase heart rate and induce shortness of breath may be integrated into treatment for anxiety among patients with asthma. However, integration of interoceptive exposures that my cause respiratory distress should be done in consultation with the patient’s internist or pulmonologist (Smoller et al., 1996). Although there are well-validated treatments for anxiety-related disorders based on empirically supported principles that may inform the development of efficacious treatments for anxiety and panic in patients with asthma, very little research on treatment development has been conducted along these lines. In a recent review of the literature, Deshmukh and colleagues (Deshmukh, Toelle, Usherwood, O’Grady, & Jenkins, 2007) concluded that the asthma research literature is lacking in randomized controlled trials applying cognitive behavioral techniques to patients with co-morbid asthma and clinical anxiety manifestations. The available studies that have examined the efficacy of psychological treatments, broadly defined, in individuals with asthma are also characterized by relatively poor methodology with small sample sizes (Deshmukh, Toelle, Usherwood, O’Grady, & Jenkins, 2007; Yorke, Fleming, & Shuldham, 2007). There is some preliminary evidence that cognitive-behavioral therapy leads to improvements in quality of life among individuals with asthma (Yorke et al., 2007). However, no conclusions could be reached regarding the effectiveness of cognitive therapy in reducing anxiety symptoms. Overall, the paucity of research highlights the need for additional studies examining the effectiveness of psychological interventions for excessive anxiety among individuals with asthma.

Conclusion Summary of Extant Research The presence of asthma may induce the clinical expression of anxiety and panic in those that may already be genetically vulnerable. Indeed, many studies have shown that asthma and anxiety, specifically panic disorder, are often comorbid with the onset of anxiety-related conditions occurring after the onset of asthma. However, there is evidence that the association between asthma and anxiety and its disorders is not necessarily causal and the high rate of comorbidity may reflect common factors/diathesis that are related to both conditions (Goodwin et al., 2004). Indeed, there is little evidence suggesting individuals with comorbid asthma and anxiety display more impaired pulmonary functioning than those with asthma alone. Furthermore, other chronic medical problems that share symptoms with anxiety presentations (e.g., cardiac problems) display a

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similar pattern of relations with anxiety and its disorders. Thus, the specificity of the asthma-anxiety relation remains relatively unclear. However, what is clear is that the comorbidity between asthma and anxiety may influence interpretations of and reactions to respiratory symptoms. The consequences of this comorbidity appear to be largely observed in poorer asthma related quality of life, worse asthma control, and increased treatment seeking. Attempts to address these poor outcomes have appealed to the identification of common factors/diatheses that are related to both asthma and anxiety conditions. The tendency to fear physical symptoms due to their perceived harmful consequences (i.e., panic-fear, AS) may function as the underlying vulnerability for the development of excessive anxiety among patients with asthma.

Limitations and Future Directions Previous research has succeeded in identifying a link between asthma and the experience of anxiety, both generally and with specific disorders. However, much of the past research has focused on examining the frequency of the comorbidity of asthma and anxiety, without providing information about the nature or strength of the relation. Many non-psychological risk factors have been identified for asthma, some of which (e.g., smoking habits) have also been previously identified as risk factors for anxiety. Initial research suggests that the relation between asthma and anxiety remains even when controlling for risk factors, but that the relation may vary between individuals with and without prominent risk factors (Halser et al., 2005). Future research should improve assessment and consideration of non-psychological risk factors. Findings also suggest that the prevalence of anxiety disorders and symptoms is higher in individuals with asthma than in individuals with other medical conditions. However, there is evidence to suggest that additional medical conditions with similar presentations to anxiety symptoms (e.g., cardiac problems) may be also be associated with anxiety. Continued use of medical control groups is needed to determine if general factors related to illness are linked with anxiety, or if the asthma-anxiety relation is unique. Future research explicating the relation between asthma and anxiety may benefit from appeal to a cognitive behavioral model. This model highlights the importance of dysfunctional beliefs based on misinterpretations of benign respiratory symptoms and excessive asthma-related safety-seeking. This model offers components that are amenable to basic laboratory research and identification of moderators (variables that alter the strength or direction of the relation between asthma and anxiety) and mediators (mechanism that explains the association between asthma and anxiety) of the cognitive behavioral model inform effective treatment and prevention of excessive anxiety among patients with asthma. Moderators in this context may consist of important individual difference characteristics (i.e., high AS, chronic stress) that, in the presence of

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asthma, increase the risk of the development of clinical anxiety. Research on mediators or explanatory process linking asthma and anxiety symptoms would benefit from the examination of the potential role of perceived uncontrollability and unpredictability. Importantly, additional studies examining the efficacy of cognitive behavioral treatments and other psychosocial treatment interventions for asthma patients with excessive anxiety are clearly needed. Such treatments have the potential of improving the quality of life of asthma patients as well as potentially minimize unnecessary health care costs.

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Goodwin, R. D., Jacobi, F., Thefeld, W. (2003). Mental disorders and asthma in the community. Archives of General Psychiatry, 60, 1125–1130. Goodwin, R. D., Messineo, K., Bregante, A., Hoven, C. A., & Kairam, R. (2005). Prevalence of probable mental disorders among pediatric asthma patients in an inner-city clinic. Journal of Asthma, 42, 643–647. Goodwin, R. D., Olfson, M., Shea, S., Lantigua, R. A., Carrasquilo, O., Gameroff, M. J., & Weissman, M. M. (2003). Asthma and mental disorders in primary care. General Hospital Psychiatry, 25, 479–483. Goodwin, R. D., & Pine, D. S. (2002). Respiratory disease and panic attacks among adults in the community. Chest, 122, 645–651. Goodwin, R. D., Pine, D. S., & Hoven, C. W. (2003). Asthma and panic attacks among youth in the community. Journal of Asthma, 40, 139–145. Greineder, D. K., Loane, K. C., & Parks P. (1995). Reduction in resource utilization by an asthma outreach program. Archives of Pediatric and Adolescent Medicine, 149, 415–420. Grupp-Phelan, J., Lozano, P. & Fishman, P. (2001). Health care utilization and cost in children with asthma and selected comorbidities. Journal of Asthma, 38, 363–373. Gupta, S., Mitchell, I., Giuffre, R. M., & Crawford, S. (2001). Covert fears and anxiety in asthma and congenital heart disease. Child: Care, Health, and Development, 27, 335–348. Halser, G., Gergen, P. J., Kleinbaum, D. G., Ajdacic, V., Gamma, A., Eich, D., et al. (2005). Asthma and panic in young adults: A 20-year prospective community study. American Journal of Respiratory and Critical Care Medicine, 171, 1224–1230. Hancox, R. J., Poulton, R., Taylor, D. R., Greene, J. M., McLachlan, C. R., Cowan, J. O., et al. (2006). Associations between respiratory symptoms, lung function and gastro-esophageal reflux symptoms in a population based birth cohort. Respiratory Research, 7, 142. Heaney, L. G., Conway, E., Kelly, C., & Gamble, J. (2005). Prevalence of psychiatric morbidity in a difficult asthma population: Relationship to asthma outcome. Respiratory Medicine, 99, 1152–1159. Hommel, K. A., Chaney, J. M., Wagner, J. L., & McLaughlin, M. S. (2002). Asthma-specific quality of life in older adolescents and young adults with long-standing asthma: The role of anxiety and depression. Journal of Clinical Psychology in Medical Settings, 9, 185–192. Hommel, K. A., Chaney, J. M., Wagner, J. L., White, M. M., Hoff, A. L., & Mullins, L. L. (2003). Anxiety and depression in older adolescents with long-standing asthma: The role of illness uncertainty. Children’s Health Care, 32, 51–63. Jaakkola, J. J. K., Ahmed, P., Ieromnimon, A., Goepfert, P., Laiou, E., Quansah, R., et al. (2006). Pre-term delivery and asthma: A systematic review and meta-analysis. Journal of Asthma and Clinical Immunology, 118, 823–830. Jani, A. L., & Hamilos, D. L. (2005). Current thinking on the relationship between rhinosinusitis and asthma. Journal of Asthma, 1, 1–7. Jonas, B. S., Wagener, D. K., Lando, J. F., & Feldman, J. J. (1999). Symptoms of anxiety and depression as risk factors for development of asthma. Journal of Applied Biobehavioral Research, 4, 91–110. Jones, E. J., Merkle, S. L., Fulton, J. E., Wheeler, L. S., & Mannino, D. M. (2006). Relationship between asthma, overweight, and physical activity among U.S. high school students. Journal of Community Health, 31, 469–478. Jones, N. F., Kinsman, R. A., Dirks, J. F., & Dahlem, N. W. (1979). Psychological contributions to chronicity in asthma: Patient response styles influencing medical treatment and its outcome. Medical Care, 17, 1103–1118. Joseph, C. L. M., Williams, L. K., Ownby, D. R., Saltzgaber, J., & Johnson, C. C. (2006). Applying epidemiological concepts of primary, secondary, and tertiary prevention to the elimination of racial disparities in asthma. Journal of Allergy and Clinical Immunology, 117, 233–240. Katon, W. J., Richardson, L., Lozano, P., & McCauley, E. (2004). The relationship of asthma and anxiety disorders. Psychosomatic Medicine, 66, 349–355.

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Cardiovascular Disease and Anxiety Kamila S. White

Introduction A broken heart is a common metaphor used when a human being suffers an emotional or physical loss, to the extent that it begins to cause them physical or physiological pain. This condition is known as heartbreak. – Wikipedia

Despite the age-old and virtually universal idea that emotions stem from the heart, science has only recently begun to understand why a stressed, sad, or anxious heart is unhealthy. Speculation about the role of psychological factors in the etiology of heart problems dates back to the early 19th century (irritable heart) (Da Costa, 1871). Systematic study of the association between heart and mind began in the late 1950s with the pioneering work of Meyer Friedman and Ray Rosenman, two cardiologists who coined the term Type A behavior pattern. Since that time, increasing clinical attention and empirical research has been focused on both biomedical and psychosocial influences on coronary heart disease (CHD). CHD is the leading cause of death and disability in the United States (American Heart Association, 2006) and in much of the Western world, especially among industrialized nations (Zevallos, Chiriboga, & Herbert, 1992). CHD claims more lives each year than the next five causes of death combined. Psychosocial factors that may be important to the presentation and clinical course of CHD include: Psychological stress, job strain, vital exhaustion, social isolation and lack of social support, hostility and anger, depression, and anxiety. Negative emotions exert a harmful influence on CHD outcomes and quality of life. Relative to the sizeable, persuasive literature linking the negative emotions of depression and hostility and CHD morbidity and mortality, less is known about how anxiety may influence CHD. Failure to Kamila S. White University of Missouri-Saint Louis, Department of Psychology, One University Boulevard, 212 Stadler Hall, Saint Louis, MO 63121. Tel: 314.516.7122, Fax: 314.516.5392 [email protected]

M. J. Zvolensky, J. A. Smits (eds.), Anxiety in Health Behaviors and Physical Illness. Ó Springer 2008

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understand and address some of these more upstream psychological risk factors including anxiety may be one explanation for why CHD morbidity and mortality remain so high. Chest pain is one of the most common, frightening medical complaints. And anxiety is one of the first, most powerful psychological responses to a cardiac event. Sudden, strong emotion is one of the two most common precipitating events experienced prior to sudden cardiac death (SCD); exercise is the other event (Lampert et al., 2005). Considerable epidemiological evidence implicates the emotion of anxiety in the development of CHD and SCD. This chapter reviews the empirical literature on the emotion of anxiety and its relation with cardiovascular illness. First, epidemiological evidence that points to anxiety (particularly phobic anxiety) as a risk factor for CHD morbidity and mortality is reviewed. Several prospective studies are described, and a number of methodological challenges to the interpretation of this research are noted. Considering the apparent comorbidity of anxiety and depression, studies encompassing the construct of negative affectivity which includes the underlying structure of both anxiety and depression are also described. Next, research on the comorbidity of anxiety disorders and CHD are highlighted. Included is a discussion of patients with non-cardiac chest pain (NCCP), a sizable segment of the population referred for cardiological workup and a group worthy of psychological study. Second, pathophysiological mechanisms or pathways by which negative emotions (i.e., anxiety, depression, and anger/ hostility) are thought to influence CHD development and progression are discussed. Several possible mechanisms for the anxiety-CHD link include connections with behavior, with the atherosclerotic process, and with cardiac instability. Third, treatment studies designed to reduce negative emotion and its impact on CHD endpoints are reviewed. Finally, the chapter ends with a discussion of the limitations of past research and highlights of a number of exciting future directions in understanding the anxiety-CHD association.

Some Terminology and Background The field of cardiac psychology or psychocardiology uses a number of important medical terms to describe facets related to heart disease (Jordan, Barde, & Zeiher, 2007). Although many terms are quite specific (e.g., myocardial infarction [MI] or heart attack), other terms are more general. First, the terms coronary artery disease (CAD) and CHD are often used synonymously, with the understanding that CHD does not exist in the ICD-10 Classification of Diseases (i.e., chronic ischemic heart disease) (World Health Organization, 2006). In this chapter, these terms are used interchangeably. Second, nearly all indications of CHD including angina pectoris (i.e., CHD-related chest pain), MI, and SCD are the product of atherosclerosis. The term atherosclerosis comes from the Greek words athero (meaning paste) and sclerosis

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(meaning hardness) and generally refers to the process of fatty substances (i.e., cholesterol, cellular waste product, calcium, and fibrin) building up in the inner lining of an artery (American Heart Association, 2006). This buildup that results is termed plaque. Atherosclerosis then is the general term for the thickening and hardening of the arteries. The precise nature of onset is not known, however, theories posit that atherosclerosis is set in motion because the innermost layer of the artery (the endothelium) becomes damaged. Three likely causes of this damage are elevated cholesterol and triglyceride in the blood (hypercholesterolemia), high blood pressure (hypertension), and cigarette smoke. Cigarette smoke aggravates and hastens atherosclerosis in the coronary arteries, the aorta, and the arteries of the legs. As a result of this damage and the accumulation of substances deposited in the artery wall, the endothelium thickens. If the artery wall is amply thickened, the diameter of the artery is reduced resulting in less blood flow and decreased oxygen supply. If the oxygen supply to the heart is reduced sufficiently, a heart attack can occur. Similarly, reduced oxygen flow to the brain and legs may result in stroke and peripheral vascular disease, respectively. Atherosclerosis is thought to result from a number of risk factors. Extensive research has documented the heritable (sex, age, race, family history) and modifiable risk factors (tobacco use, obesity, hypertension, physical inactivity, diabetes mellitus) associated with an increased risk for CHD (American Heart Association, 2006). Each or a combination of these risk factors may combine synergistically to contribute to CHD. Traditional risk factors are thought to account for roughly 40% of CHD incidence (Marmot & Winkelstein, 1975), and CHD has a genetic component independent of these risk factors (Shiffman, Rowland, Sninsky, & Devlin, 2006). Incidence and severity of some of these established risk factors are affected by behavioral factors – and, in fact, each of the major modifiable risk factors has a behavioral component. In addition, psychosocial risk appears to influence CHD including: Social support/social isolation, job strain, vital exhaustion, depression, stress, hostility, and anxiety. This chapter critically explores the current knowledge concerning anxiety in CHD. Research has accumulated over the years establishing anxiety as a possible risk factor in CHD development, progression, and outcome; however, a number of important factors need to be considered in our contemporary analysis of past studies.

Anxiety and Increased Risk for CHD: Prospective Evidence Anxiety is a cognitive-affective process that is commonly exemplified by a perceived inability to predict, control, or obtain desired results (Barlow, 2002). The emotion of anxiety is universally experienced and is seldom pathological except when it becomes persistent. Anxiety disorders are among the most prevalent psychiatric disorders in the general population afflicting

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roughly 40 million American adults in a given year (Kessler, Chiu, Demler, & Walters, 2005). Relative to other negative emotions (i.e., depression, anger/ hostility), far less empirical research has been paid to the impact of anxiety and its possible cardiotoxic influences in CHD development, progression, and outcome. Most research to date on the anxiety-CHD link has examined the role of a construct defined as phobic anxiety. Increasing evidence from several prospective studies has implicated phobic anxiety as a risk factor for CHD, and considerable retrospective and correlational research has consistently found a link between anxiety and CHD. Indeed, the relationship between anxiety disorders and other forms of subclinical anxiety symptoms and CHD have not been studied systematically. Correlational and prospective studies with both healthy and ill populations are reviewed here, and some important methodological challenges to interpretation of this research are highlighted.

Prospective Epidemiological Studies Perhaps the most compelling support for a link between anxiety and CHD has arisen from longitudinal studies conducted with initially healthy samples that have controlled for the effects of known cardiovascular risk factors in the prediction of subsequent disease. In the recent two decades, large-scale community-based studies have established a significant relationship between anxiety and subsequent death due to cardiac pathology in men (Haines, Imeson, & Meade, 1987; Kawachi, Colditz et al., 1994; Kawachi, Sparrow, Vokonas, & Weiss, 1994) and women (Eaker, Pinsky, & Castelli, 1992). Support from these studies is bolstered because each study examined the anxiety-CHD link in samples free of CHD at baseline, controlled for some known cardiovascular risk factors, and predicted follow-up at time periods of up to 20 years. First, one of the earliest prospective studies to systematically examine the anxiety-CHD link was the Northwick Park Heart Study. The Northwick study followed 1,457 initially healthy men across 10 years (Haines et al., 1987). After controlling for a set of cardiovascular risk factors, elevated phobic anxiety, as assessed by the Crown-Crisp Index (Crown & Crisp, 1966), was associated with fatal CHD in this initially healthy sample of men. In a second study also conducted exclusively with males, the Health Professionals Follow-up Study (Kawachi, Colditz et al., 1994), Kawachi and colleagues followed a large sample (N = 33,999) of health professionals free of CHD at baseline. Results revealed that over the two-year follow-up period, the age-adjusted relative risk of fatal CHD among men with the highest levels of phobic anxiety was three times that compared to men in the lowest levels of anxiety. Risk for fatal CHD increased with mounting phobic anxiety even after controlling for risks conferred by other major cardiovascular risk factors (e.g., family history of heart disease, smoking, blood pressure); notably, the excess risk conferred by phobic anxiety was confined to SCD, defined as death within 1 hour of symptom onset, rather

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than non-sudden CHD death. Nonfatal MI was not significantly associated with phobic anxiety in this study. Similar results were also found in the Veterans Administration Normative Aging Study conducted with a sample of largely white males (Kawachi, Sparrow et al., 1994). The Normative Aging study assessed anxiety symptoms using a 5-item scale from the Cornell Medical Index. The association between anxiety and CHD was only marginally significant after adjusting for other risk factors. Likewise in another set of analyses using Normative Aging data, the risk of disease was examined with regard to worry, a cognitive component of anxiety (Kubzanksy et al., 1997). Study outcome showed that males with the highest levels of worry were 2 ½ times more likely to suffer nonfatal MI; men with moderately elevated worry were also at increased risk. At follow-up (M follow-up = 10.9 years), Kubzansky and colleagues found that anxiety and shared general distress were independently associated with the development of CHD (Kubzansky, Cole, Kawachi, Vokonas, & Sparrow, 2006). In this case, the anxiety-CHD link was independent of shared general distress, anger, and depression associations. Although anxiety was only weakly associated with the development of angina, it was strongly associated with both fatal and nonfatal MI. Another recent study again conducted with veterans demonstrated a prospective association between post-traumatic stress disorder (PTSD) symptoms and CHD. Researchers studied 1,946 male veterans of World War II and Korea and found that veterans with symptoms of PTSD are at greater risk of heart attacks as they age (Kubzansky, Karestan, Spiro, Vokonas, & Sparrow, 2007). This association was significant even after controlling for depressive symptoms. Although this study warrants replication, results suggest that symptoms of post-traumatic stress increase CHD incidence in older men. Importantly, each of these prospective cohort studies established a dose-response gradient for the anxiety-CHD relation. Although the prevalence of anxiety (Wittchen, Zhao, Kessler, & Eaton, 1994) and phobic disorders (Magee, Eaton, Wittchen, McGonagle, & Kessler, 1996) is known to be twice as high among women, less is currently known about the relationship between anxiety and CHD among women. In one study examining 20-year follow-up of women participating in the Framingham Heart Study, multivariate analyses showed that symptoms of anxiety and tension in 749 subjects were independent predictors of CHD after controlling for a set of cardiovascular risk factors (Eaker et al., 1992). Significant associations were found for anxiety-MI and anxiety-coronary death among homemakers, but not among employed women. Indeed, these researchers found a 6 fold increase in CHD risk for women who self-reported any symptoms of ‘‘tension’’ after controlling for known risk factors. In this case, anxiety was assessed by self-ratings on a social strain scale developed for the study. In a recently published 12-year prospective study conducted with women, the Nurses’ Health Study, Albert and colleagues found that among women without a history of cardiovascular disease, high levels of phobic anxiety were associated with an increased risk of fatal CHD, particularly from SCD. Notably, some but

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not all of this risk was accounted for by CHD risk factors (i.e., hypertension, diabetes, and elevated cholesterol) associated with phobic anxiety (Albert, Chae, Rexrode, Manson, & Kawachi, 2005). Similar to results with male-only samples, findings suggest that phobic anxiety is prospectively associated with increased risk of fatal CHD among females (Albert et al., 2005). In sum, these prospective epidemiological studies using initially healthy samples provide compelling evidence that anxiety contributes to subsequent CHD. Both the strength and consistency of the claim that anxiety contributes to CHD risk and outcomes beyond the traditional CHD risk factors are evident across the studies. Moreover, in each of these studies, varied but valuable efforts were made to control for the effects of known risk factors, and at least one or multiple hard endpoints (i.e., documented MI, cardiac mortality) were investigated.

Prospective Studies in Samples with Known CHD In addition to studies conducted with initially healthy samples free of CHD at baseline, important published reports have examined anxiety and subsequent documented CHD and cardiac death in prognostic samples. To date, the association between anxiety and cardiac death or documented CHD in samples with known CHD at baseline has been examined in over 10 prospective studies using independent patient samples (sample sizes ranging from 86 to over 5,000; with follow-up periods from 6 months to 10 years). For a complete review see (Suls & Bunde, 2005). Taken as a whole, the published research linking anxiety and CHD in prognostic samples is mixed. Moreover, this research is complicated by interpretation challenges and causal limitations. Although several studies demonstrate a positive association between initial anxiety and later cardiac morbidity and/or mortality (even after controlling for known risk factors), still others have not found this relationship to be present in patients with known CHD. Based on data from several prognostic samples, anxiety appears to relate to subsequent CHD, cardiac events, and cardiac death. Frasure-Smith and colleagues followed 222 patients for 1 year post-MI and found that higher scores on a self-report measure of state and trait anxiety were related to the occurrence of new cardiac events (i.e., unstable angina admissions, recurrent fatal and non-fatal MI) (Frasure-Smith, Lesperance, & Talajic, 1995). Notably, the influence of anxiety was independent of other predictors (i.e., depression, other cardiac risk factors), and it was the only variable studied that was coupled with recurrent MI. Consistent findings were reported in another study by this group conducted with 896 post-MI patients (Frasure-Smith & Lesperance, 2003). In a study examining patients 48 hours after acute MI, higher anxiety levels (assessed via brief, self-report symptom checklist) conferred an almost 5 times increased likelihood of experiencing

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in-hospital cardiac complications or death (i.e., 19.6% high-anxiety group versus only 6% in lower anxiety), independent of cardiac risk factors (Moser & Dracup, 1996). More than two thirds of patients suffered anxiety levels considered above normal, and 26% reported levels of anxiety equivalent to or above those reported by psychiatric inpatient samples. Other studies have shown that over and above the effects of depression, anxiety appears to have a negative influence on outcomes following ischemic coronary events. In a study of 913 patients with unstable angina and MI, anxiety predicted recurrent cardiac events at 6 months and one year follow-up (Grace, Abbey, Irvine, Shnek, & Stewart, 2004). Anxiety was assessed using the self-rated Crown-Crisp index and the Anxiety subscale of the PRIME-MD (Spitzer et al., 1994). Hermann and colleagues studied CHD patients who were referred for exercise testing and found that anxiety (measured by the Hospital Anxiety and Depression Scale) was associated with cardiac mortality at 5-year follow-up (Hermann, Brand-Driehorst, Buss, & Ruger, 2000). Finally, one study that examined the relative contribution of both anxiety and depression found that anxiety was an independent predictor of both cardiac events and increased health care consumption. In this study, anxiety symptoms wholly accounted for the depression-cardiac prognosis association (Strik, Denollet, Lousberg, & Honig, 2003). A related line of research shows that the tendency to suppress emotional distress may be coupled with both cardiac and non-cardiac mortality, irrespective of disease severity and irrespective of disease biomedical risk factors of mortality. In one study conducted with patients with established CHD, individuals who scored high on the trait scale of the Speilberger State-Trait Anxiety Inventory and who endorsed high social inhibition (i.e., termed Type D personality style) showed a four-fold increase in cardiac death as compared to those who did not have this personality style at 6–10 years follow-up (Denollet et al., 1996). In a more recent study by this same group, Denollet and colleagues found that the Type D personality distinction was useful in predicting cardiac events at 5-years follow-up even after controlling for concurrent symptoms and psychological stress (Denollet, Pedersen, Vrints, & Conraads, 2006). These prospective studies conducted with documented CHD patients indicate that anxiety appears to have a negative impact on disease course and outcome (i.e., disease severity, mortality, recurrent cardiac events), and this influence appears to be independent of the effects of depression. However, it is important to report that this conclusion is not without some contradictory evidence. For instance, Ahern and colleagues examined anxiety in 502 patients following MI and arrhythmia, and they concluded no relationship between anxiety and cardiac arrest or death at 1 year follow-up after controlling for known risk factors (Ahern et al., 1990). Similar null findings were reported by others including Lane and colleagues (Lane, Carroll, Ring, Beevers, & Lip, 2001) and Mayou and colleagues who both examined anxiety in post-MI patients (Mayou et al., 2000) at 1-year follow-up.

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Studies in Psychiatric Samples Although truly prospective studies of the anxiety-CHD association have not been conducted with patients suffering anxiety disorders, a number of retrospective reports establish that anxiety (and panic disorder in particular) is a risk factor for CHD. Specifically, psychiatric inpatients and outpatients with initial diagnoses of anxiety conditions have shown a greater-than-expected mortality rate. One early study suggested a link between anxiety disorders and CHD mortality by examining psychiatric inpatients diagnosed with panic disorder (PD) over the course of a 35-year follow-up. Coryell and colleagues found that the risk of cardiovascular mortality was twice as high in this anxiety group (i.e., anxiety neurosis, a panic-like form of anxiety that is similar to current criteria for DSM-IV PD) as compared with the general population; this excess risk was not found in patients with other psychiatric disorders (Coryell, Noyes, & Clancy, 1982). A trend toward similar findings was reported for men but not women in an age- and sex-matched sample of surgical control patients but these findings did not quite reach traditional indications of statistical significance, p < .07 (Coryell, Noyes, & House, 1986); as such, excess mortality due to CHD in these studies was limited to males with PD, and CHD death rates among females with anxiety were in the expected range. The authors concluded that the increased mortality in general was largely ascribed to CHD and suicide. Still other studies by Allgulander and Lavori found that ‘‘heart deaths’’ among men with ‘‘pure’’ anxiety neurosis were higher than expected (Allgulander & Lavori, 1993) and predictive of fatal CHD at 14-year follow-up (Allgulander & Lavori, 1991); however, the extent of this association with suicide and CHD remains unknown. Although these studies have been often cited as prospective evidence that PD is a CHD risk factor (Kubzansky, Kawachi, Weiss, & Sparrow, 1998; Suls & Bunde, 2005), these results must be interpreted with vigilance. Unfortunately, both of the above studies used suboptimal designs and were not truly prospective by comparison with age- and sex-matched controls. Moreover, in some cases, the relatively small sample sizes lacked the statistical power to render significance. Further, diagnoses were derived from chart review, and cardiovascular ‘‘causes’’ of death were not definitive (e.g., ‘‘circulatory disease’’) (Coryell et al., 1982). Because of these reasons, it is not possible to exclude other biomedical, behavioral (i.e., smoking, sedentary behavior), or psychological factors as the cause of the CHD-related mortality. As a result, it can be concluded that while anxiety disorders, and PD in particular, is associated with increased incidence of cardiovascular morbidity, the direction of this causality remains unclear (Chignon, 1993; Fleet, Lavoie, & Beitman, 2000). Equally important, contrary to the above studies, another albeit smaller body of published research with follow-up time periods ranging from 7–14 years conducted with psychiatric samples (some identified as outpatients with anxiety neurosis) who were initially free of CHD (Hippisley-Cox, Fielding, & Pringle,

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1998; Martin, Cloninger, Guze, & Clayton, 1985) have not found a significant prospective anxiety-CHD association. The extent to which publication bias has influenced the availability of negative findings is also uncertain.

Summary Drawing from these prospective studies, the available evidence appears to conservatively point to support for an anxiety-CHD relationship. However, the directionality of this relationship is less certain. Although data has accumulated across different study samples (i.e., initially healthy, individuals with CHD, individuals with anxiety conditions), the anxiety-CHD relationship appears to be most compelling and consistent in the epidemiological prospective studies. And the claim that self-reported anxiety confers CHD risk appears to be most persuasive in studies with initially healthy samples; this is particularly true in light of the fact that the studies highlighted herein often controlled for possible confounds and used hard endpoints for disease (e.g., MI, cardiac mortality). One interpretive caveat to these studies, however, is that the extent to which comorbid health behaviors (e.g., exercise) and addictive behaviors (e.g., smoking) were controlled for across studies was variable. Nevertheless, these findings are noteworthy in light of the fact that most studies to date have found these associations using less than optimal and possibly diluted measures of anxiety. Findings with prognostic samples (i.e., known CHD, in- and out-patients with psychiatric illness) are less persuasive. Indeed, it may be that anxiety confers a stronger role in CHD development than in the disease progression (Suls & Bunde, 2005), or it may be that difficulties with distinction between anxiety and declaration of CHD have lead to weaker findings among the groups studied.

Prevalence of Anxiety Disorders in Patients with CHD Although the experiences of anxiety and fear are universal, research examining the incidence of clinically significant anxiety in CHD has received considerably less attention. Accumulating data support a high rate of comorbid anxiety disorders in patients with CHD. Although strictly prospective research examining anxiety disorders as risk factors for CHD is absent, correlational and retrospective research supports an anxiety disorder-CHD association. Incidentally, the prevalence of anxiety disorders in CHD appears to at least parallel the high rate of depressive disorders in this group (Gonzalez et al., 1996; Hance, Carney, Freedland, & Skala, 1996). A high proportion of patients with estabshed CHD suffer from anxiety disorders (Fleet et al., 2000; Goldberg et al., 1990). One of the first systematic studies of anxiety disorders in cardiology outpatients was conducted by

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Beitman and colleagues, who examined the prevalence of PD in patients with documented CAD (Beitman, Basha, & Flaker, 1987). In this study, 53% of patients with documented CAD met criteria for PD assessed by a validated structured clinical interview; and this percentage may be an underestimate as the majority of patients (36 out of the 47) did not undergo coronary arteriography to determine the presence of CAD. In a subsequent study conducted by this same group (Basha et al., 1989), the authors found support for this increased rate of PD in CAD patients and concluded that this association may be more common in patients with atypical chest pain. In a more recent cohort study examining the association between PD and CHD using a large national managed care database, researchers found that patients with PD showed a nearly 2-fold increase in their risk for CHD, even after controlling for CHD risk factors (Gomez-Caminero, Blumentals, Russo, Brown, & Castilla-Puentes, 2006). In addition to increased prevalence of PD, other anxiety disorders occur at an increased rate in CHD patients including generalized anxiety disorder and PTSD (Bankier, Januzzi, & Littman, 2004). Despite the fact that most research in this area has been restricted in scope to only one disorder at a time, one particularly persuasive study systematically examined a set of psychological disorders (assessed using the Structured Clinical Interview for the Diagnostic and Statistical Manual of Mental Disorders [SCID]) in outpatients with CHD (Bankier et al., 2004). In addition to an increased rate of depressive disorders, current anxiety disorders including GAD (24%) and PTSD (29%) were identified at a high rate. Indeed, among nonclinical and representative samples, elevated CHD risk (as indicated by self-reported smoking status, body mass index, and medication use for hypertension, hypercholesterolemia, and diabetes) has been associated with GAD (Barger & Sydeman, 2005). Though the generalizability of past research is nearly exclusive to cardiology settings, some research has explored the anxiety disorder-CHD connection in other settings. Fleet and colleagues examined this prevalence in consecutive patients presenting to the emergency department; these researchers found that 34% of patients with documented CAD (i.e., determined by previous MI, bypass surgery, angioplasty, an angiogram indicating 50% stenosis in one major coronary artery or positive nuclear stress test) met criteria for current PD (Fleet et al., 1996). Because many CHD patients also experience atypical chest pain and are referred for gastroenterological evaluation, Kane and colleagues retrospectively examined the prevalence of anxiety disorders in patients with CAD referred to a digestive disease laboratory. These researchers found that among patients with known CHD more than 70% of these patients met criteria for Generalized Anxiety Disorder, 49% met criteria for PD, and 31% who met criteria for Major Depression (Kane, Strohlein, & Harper, 1991). Notably, though findings of this study suggest an increased prevalence of Axis I disorders in patients with CAD, results need to be interpreted with some caution because ‘‘diagnoses’’ were established through a mailed questionnaire and it is not known how ‘‘known heart disease’’ was determined in this group of patients.

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Other correlational studies show that anxiety, particularly PD, is prevalent in individuals with CHD. In the 1990s, Weissman and colleagues showed PD and CHD were significantly associated using data from the Epidemiological Catchment Area database (Weissman, Markowitz, Ouellette, Greenwald, & Kahn, 1990). Falger and colleagues reported that veterans exposed to war-related traumatic events in World War II showed not only increased incidence of PTSD but also increased medical morbidity including cardiovascular disease (Falger et al., 1992). In short, these studies conducted with psychiatric samples seem to indicate that anxiety and anxiety disorders may precipitate or exacerbate CHD.

Anxiety in Patients with Non-Cardiac Chest Pain One diagnostic category of patients that often present to cardiology settings but whom are less well understood is those experiencing non-cardiac chest pain (NCCP). In contrast to patients who have a detectible cardiovascular cause for their chest pain, the majority of patients who experience recurrent chest pain are found to have normal coronary angiograms and show no other identifiable medical condition (Fleet & Beitman, 1997). It has been estimated that more than 6 million people present annually to US emergency departments with chest pain suggestive of MI (American Heart Association, 2006), however, the majority of these individuals do not receive an organic explanation for their chest pain (Kroenke & Mangelsdorff, 1989). Ten to 13 billion dollars is spent annually to care for patients who are admitted with suspected ischemic symptoms but who do not sustain acute MI (Roberts & Kleinman, 1994). Despite their apparently favorable cardiac prognosis, patients with NCCP show poor outcomes that are comparable to patients who are diagnosed with CHD (Eifert, Hodson, Tracey, Seville, & Gunawardane, 1996). In fact, when compared to cardiac patients, surgical patients, and normal controls, individuals with NCCP (i.e., often accompanied by subjective heart-focused anxiety) experience more physical symptoms and are as equally fearful of these physical sensations as cardiac patients (Eifert et al., 1996). This attention to and fear of heart-related problems (often termed heart-focused or cardiac anxiety) has been shown to be predictive of the severity of the chest pain as well (Zvolensky, Eifert, Feldner, & Leen Feldner, 2003). Heart-focused anxiety, as assessed via the Cardiac Anxiety Questionnaire (Eifert, Thompson et al., 2000), is thought to be conceptually distinct from trait anxiety, anxiety sensitivity, and other forms of health anxiety (Eifert, Zvolensky, & Lejuez, 2000) and shares only moderate zero-order correlations with the ASI. For example, trait anxiety taps into anxiety-based negative affect generally, heart-focused anxiety relates to specific fears of cardiac-related events, physical sensations, and functioning. Research has demonstrated the prevalence and costs associated with NCCP, however, factors associated with its onset, severity, and persistence are not

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well-understood (Eifert, Zvolensky et al., 2000; Fleet et al., 1996; White & Raffa, 2004). Theoretical conceptualizations of NCCP generally assert that the etiology of the pain is multi-causal and interactive (Eifert, Zvolensky et al., 2000; Mayou, 1998; White & Raffa, 2004). It has been hypothesized that the functional syndrome of NCCP may partially result from psychological vulnerabilities (i.e., greater awareness of internal bodily sensations, somatic hypervigilance) that focus on circumstances associated with threat or danger (e.g., heart disease, death) (White & Raffa, 2004). Although most cases of NCCP are thought to be benign, unrecognized CAD and microvascular angina (i.e., cardiac syndrome X, a condition characterized by apparent vasospasm of the arteries that nourish the heart but that are not visible on cardiac catheterization) may explain an unknown portion of NCCP cases in the general population (Allan & Scheidt, 1999). Recent reviews have suggested that the clinical prognosis of patients with NCCP may not be as benign as is commonly thought (Bugiardini & Bairey Merz, 2005). Moreover, identification of heart disease risk factors in this patient group may help to determine optimal methods for identification and prevention of clinical events through risk factor management (White, Malone, & Gervino, 2006). In light of the extensive research that has documented the heritable (e.g., sex, age, race, family history) and modifiable risk factors (e.g., tobacco use, obesity, hypertension, physical inactivity, diabetes mellitus) associated with an increased risk for heart disease (American Heart Association, 2006), a systematic examination of cardiac risk in patients with NCCP may have important implications for identification, risk stratification, or intervention. One study conducted by our research group found that patients with NCCP endorsed on average 4 CHD risk factors (SD = 1.6) (White, Malone et al., 2006). The most common risk factors endorsed included a family history of CHD (46%), physical inactivity (42%), and obesity (34%). This elevated risk was associated with elevated anxiety (both in general and heart-focused anxiety), and hierarchical regressions showed that risk factor incidence, general anxiety, and heart-focused anxiety all predicted significant variance in chest pain interference (45%; large effect size f 2 = .81). These findings indicated that not only are CHD risk factors present and appear to exacerbate chest pain in patients with NCCP, but that the subjective anxiety may be well-founded and perhaps prematurely related to later CHD. Ongoing longitudinal research by our group and others may help to disentangle this important question. Considerable research has investigated the relationship between psychiatric illness and NCCP. Bass and colleagues conducted a series of studies and concluded that two-thirds of patients with normal or near-normal coronary arteries have predominantly psychiatric, as opposed to cardiac disorders; anxiety neurosis was the most common diagnosis in this patient group (Bass & Wade, 1984; Bass, Wade, Hand, & Jackson, 1983). Indeed, research by our group has explored the prevalence of anxiety and mood disorders in patients with NCCP and found that almost half of patients (47%) with NCCP also were

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assigned an Axis I anxiety disorder; the most common anxiety disorders assigned were PD, social phobia, and generalized anxiety disorder. Mood disorders were present in 17% of patients. In other studies comparing chest pain patients with and without CAD, the presence of psychiatric diagnosis has been significantly higher among patients without CAD (Cormier et al., 1988; Katon et al., 1988). Several studies have documented the greater prevalence of PD in patients with NCCP as compared to those with cardiac chest pain (Beitman & Basha, 1992; Dammen, Arnesen, Ekeberg, & Friis, 2004; Fleet et al., 1996) with few exceptions (Yingling, Wulsin, Arnold, & Rouan, 1993). Unfortunately, this research signifying an increased rate of anxiety disorders in patients with NCCP has been used to suggest that the etiology and clinical presentation of NCCP is psychological in nature (Beitman et al., 1991; Yingling et al., 1993). Although these diagnostic studies are informative, it may be premature to conclude that NCCP is entirely psychological in the absence of a systematic investigation of cardiac risk factors in this patient group (White, Raffa et al., in press) and more longitudinal work. Recent reviews showing less favorable outcomes (Bugiardini & Bairey Merz, 2005) combined with findings from recent studies showing a high incidence of CHD risk factors in patients with NCCP (White, Malone et al., 2006) indicate that this group of patients warrants more investigation. It may be that NCCP patients who show increased CHD risk are worried prematurely for current heart disease but may be ideal for risk factor modification given the high incidence of risk factors that has been demonstrated in this population. The importance of this question is underscored by the recent studies showing that anxiety may be an independent risk factor for CHD. Research by GomezCaminero and colleagues (2006) found that the presence of anxiety (i.e., PD) increased the risk of CHD (Gomez-Caminero et al., 2006), and others have found that general anxiety (Kubzansky et al., 2006) and phobic anxiety are associated with an increased risk of fatal CHD in both men (Kawachi, Colditz et al., 1994; Kawachi, Sparrow et al., 1994), and women (Albert et al., 2005). It may be that the occurrence of NCCP presents a potential ‘‘teachable moment’’ to engage patients in CHD risk factor management (i.e., smoking cessation, weight management). Patients with chest pain that is not of cardiac origin may be uniquely open to considering options to modify and lessen their risk of developing CHD (White, Malone et al., 2006).

Some Caveats in the Interpretation of Past Studies Descriptive epidemiological studies have generally revealed that anxiety is predictive of CHD morbidity and mortality, even after controlling for traditional CHD risk factors (Booth-Kewley & Friedman, 1987; Gallo & Matthews, 2003; Hemingway & Marmot, 1999; Kubzansky & Kawachi, 2000; Matthews, 1988; Rugulies, 2002). At first blush, these findings appear to be

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persuasive and undeniably indicate that anxiety plays a part in CHD; however, some qualifications need to be considered when interpreting this research. A number of factors influence how robust these findings are including: 1) factors associated with study outcome (i.e., type of research design, method of assessment), 2) factors associated with construct definition (i.e., fear, anxiety, the panic spectrum, anxious arousal, worry) and construct validity (i.e., type of anxiety or anxiety disorder assessed, construct overlap among negative emotions), and 3) factors associated with assessment (i.e., diagnostic structured clinical interviews, self-report symptom rating scales). Relevance to current conceptualizations of anxiety and their psychometric acceptance, construct definition overlap (i.e., the co-occurrence, intersection of anxiety and other negative emotions), and the directionality of anxiety and CHD may be vital.

Conceptualizations of Anxiety Anxiety occurs along a continuum from adaptive to maladaptive. Emotion theorists have long distinguished between basic emotions, such as fear, and more invasive cognitive-affective processes, such as anxiety and worry (Ekman, 1992; Izard, 1992). Unlike the basic emotion of fear, anxiety represents a higher-order cognitive elaboration that is considered by many to be a related but distinct construct (Barlow, 2002; Craske, 1999; White & Barlow, 2002). Much of the research examining the anxiety-CHD connection predates contemporary conceptualizations of anxiety, and studies to date have yet to explore empirically supported models of anxiety and panic in CHD. Research on the panic spectrum (e.g., fear, anxious arousal, anxiety sensitivity, PD) – including the recurrent, intense, and often private experience of panic attacks which is a common comorbidity of anxiety and mood disorders – may be the most potent aspect of fear and anxiety (White & Barlow, 2002) to influence CHD. Interpreting the research on anxiety and CHD begs consideration of the varied conceptualizations of anxiety (i.e., ‘‘phobic anxiety’’, general anxiety, worry, panic, fear) and the domains assessed in past research. Nearly all studies to date have relied primarily on self-report measures of anxiety symptoms rather than anxiety diagnoses. And little research has explored the clinically significant end of the anxiety continuum with regard to the presence of anxiety disorders, panic attacks, and the available research is limited with regard to ‘‘pure’’ anxiety and CHD. In fact, of the studies demonstrating an anxiety-CHD connection, most have used scales that may serve to dilute the assessment of anxiety (e.g., Framingham Tension scale, STAI, Crown-Crisp). With few exceptions, research conducted on anxiety in heart disease has been conducted using scales that are not generally considered both gold-standard and empirically-based measures of anxiety (Antony, Orsillo, & Romer, 2001). For instance, most research to date on the

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anxiety-CHD link has examined a self-reported construct of ‘‘phobic anxiety’’ measured by the 8-item Crown-Crisp experiential index. This scale appears to be particularly predictive of mortality (risk ratios = 3.0 to 3.8) (Haines et al., 1987; Kawachi, Colditz et al., 1994). Scores range from 0–16, with higher scores indicative of more phobic anxiety, and the majority of items are related to symptoms of agoraphobia (e.g., concerns about going out alone, concerns about crowds) and simple phobias (e.g., fear of heights) with some association with generalized worry (e.g., concerns when relatives are late coming home). Although this may indicate that the plain presence of anxious symptoms is a risk factor for CHD, this also may indicate that the assessment was less than optimal, necessitating other problems in interpretation (Kubzansky et al., 1998). Importantly, validity studies provide some reassurance and show that elevated scores on the phobic anxiety subscale can successfully discriminate phobic disorders from other diagnostic groups in psychiatric patients (Crisp, Jones, & Slater, 1978; Mavissakalian & Michelson, 1981). How this scale relates to the broader domains of anxiety and panic, including anxiety sensitivity, remains to be seen. Moreover, how phobic anxiety relates to other negative emotions (e.g., fear, anxiety, hostility, depression) and related disorders is unclear. It is noteworthy that past research that has found significant anxiety-CHD associations, even when most studies have not used gold-standard measures of anxiety or anxiety disorders (e.g., Anxiety Disorders Interview Schedule for DSM [ADIS], Structured Clinical Interview for the DSM [SCID]). And even when an anxious individual does not meet diagnostic criteria for a clinical disorder, they still often suffer from multiple difficulties (Kessler et al., 2003) and may show comparable functional impairment to those with clinical anxiety disorders (Fifer et al., 1994). Future research is needed to clarify some of these basic issues of construct definition and psychopathology including diagnosis and comorbidity. Little research has explored the extent to which current diagnoses, current comorbidities, and lifetime/past diagnoses influence the anxiety-CHD relation. For instance, it may be that the comorbidity of a PD and Major Depressive Disorder is particularly lethal, resulting in a synergistic or more weighty influence on CHD morbidity and mortality. Future research examining the clinical experience of anxiety may help improve our understanding of the anxiety-CHD connection.

Construct Definition Overlap Unequivocal evidence that ‘‘pure’’ anxiety plays an independent role in CHD has yet to be broadly determined or accepted. Few studies have considered the independent and combined contributions of these negative emotions and CHD. Many studies have examined only one psychological construct at a time making it ‘‘impossible to compare the prognostic importance of the different concepts in

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the same individuals. . . to know whether any apparent prognostic importance relationships are due to a specific psychological construct or one or more hidden underlying dimensions’’ (p. 627) (Frasure-Smith & Lesperance, 2003). One particularly revealing recent study examined the shared and unique contributions of anger, anxiety, and depression to CHD using data from the Normative Aging study. Kubzansky and colleagues found that each of the emotions was associated with CHD risk. However, when considered simultaneously, only anxiety and the shared general distress factor were uniquely associated with the occurrence of CHD (Kubzansky et al., 2006). Although some of the newest research has been acutely attuned to these issues and distinctions (Kubzansky et al., 2006), future research studies designed to deal with issues of construct overlap as well diagnostic comorbidity in CHD are needed. As has been recently speculated by Suls and Bunde, it may that inconsistent findings are the result of a failure to distinguish between state and trait anxiety in CHD patients (Suls & Bunde, 2005). Or another possibility, in light of the apparent comorbidity of anxiety and depression, is that it may be that it is exclusively depression rather than anxiety that is relevant to CHD. The construct of negative affectivity which may encompass the underlying structure of both anxiety and depression may be a more complete reflection of the emotional factors associated with CHD. Theoretical and empirical distinctions can be made between the constructs of depression and anxiety, and these two negative emotions can be assessed as unique emotional states. Nevertheless, when discussed among clinicians and researchers alike, the constructs of depression and anxiety are not always separated, and it is not clear to what extent this distinction is necessary or meaningful in practice.

Directionality Although critical reviews of the anxiety-CHD association have concluded that anxiety, and perhaps PD in particular, is associated with increased incidence of cardiovascular morbidity, the absolute direction of this causality remains unclear (Chignon, 1993; Fleet et al., 2000). Moreover, individuals experiencing anxiety and anxiety disorders commonly use medication, and the extent to which psychotropic medication use is causally associated with CHD risk is not fully known (Thorogood, Cowen, Mann, Murphy, & Vessey, 1992). In short, it may be too preliminary to conclude any definite causal directions in the anxiety-CHD relationship. Research using truly prospective designs measuring anxiety with gold-standard measures of anxiety and negative affect that are conducted with initially healthy samples of both men and women are needed to more completely document onset of anxiety, other negative emotions, risk factor initiation, and CHD onset would resolve many of these questions.

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Potential Mechanisms in the Anxiety-CHD Association Anxiety may manifest in CHD through a number of pathways. In response to the growing evidence supporting the anxiety-CHD connection accumulated over the past few decades, the field has evolved toward a greater focus on the mechanisms and pathophysiological pathways by which negative emotions influence disease onset, development, and progression. A sizable body of both animal and human research has supported the long held belief that psychological factors contribute to CHD and SCD (Kamarck & Jennings, 1991; Niaura & Goldstein, 1992; Rozanski, Blumenthal, Davidson, Saab, & Kubzanksy, 2005; Rozanski, Blumenthal, & Kaplan, 1999). Research has identified behavioral, biological, and physiological pathways that may account for how these emotional processes may give rise to CHD development and progression (Fleet et al., 2005; Grippo & Johnson, 2002; Krantz & Manuck, 1984). Naturally, because psychological factors and behavioral stresses tend to occur and change in tandem together over time, it is a challenge to study the independent mechanisms and their effects. Research examining the mechanisms connecting anxiety and CHD is still in the early stages and is far from definitive conclusions. Nevertheless, several potentially important interconnected mechanisms have been put forward to explain why negative emotions in general, and anxiety in particular, are implicated in CHD occurrence and progression (Everson-Rose & Lewis, 2005; Kubzansky et al., 1998; Rozanski et al., 1999; Smith & Ruiz, 2002). Anxiety may exert its influence on CHD through vulnerability toward health-compromising behavior. Other possible mechanisms put forward have ranged from direct effects (e.g., anxiety may directly influence the progression of atherosclerosis) to more indirect effects (e.g., anxiety may lower the threshold for ventricular arrhythmia and SCD). Several of the more promising possibilities are reviewed here.

Anxiety and Health-Compromising Behaviors First, one possible mechanism that may mediate the anxiety-CHD link is via health-compromising behaviors. Specifically, it may be that anxiety gives rise to health-compromising behaviors (e.g., physical inactivity, smoking, caloric intake, lack of sleep, poor diet, alcohol consumption, drug use, and lack of compliance with medications). Perhaps initially providing some temporary relief, these negative health behaviors may grow to become habitual and mediate the anxiety-CHD relationship. Although a sizable research has examined and shown positive correlational associations between anxiety and health-compromising behaviors (Breslau, Kilbey, & Andreski, 1991; Fisher, Schneider, Pegler, & Napolitano, 1991; Hayward, 1995), truly prospective

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designs with initially healthy samples with documentation of onset of both anxiety, health-compromising behaviors, and CHD risk factors are scarce. That said, individuals with anxiety and anxiety disorders are prone to more unhealthy lifestyle behaviors (Kawachi, Colditz et al., 1994; Kawachi, Sparrow, Vokonas, & Weiss, 1995). For example, cross-sectional studies have demonstrated that 1 out of every 4 cases of obesity are associated with a mood or anxiety disorder (Simon et al., 2006), and anxiety is elevated among those individuals with obesity (Tuthill, Slawik, O’Rahilly, & Finer, 2006). Although the causal relationship and complex interplay between anxiety and CHD risk factors is still unclear, the available research seems to indicate that obesity is associated with increasing rates of psychiatric comorbidity, including major depression and PD. To this end, perhaps even low levels of anxiety may serve to hasten CHD risk course. As another example, strong evidence shows that psychiatric illness in general is associated with cigarette smoking, and this is true for increased anxiety, particularly the panic-spectrum (e.g., panic attacks, anxiety sensitivity, panic disorders) among smokers (Haines, Imeson, & Meade, 1980). Indeed, a disproportionate number of individuals with PD smoke cigarettes (Zvolensky, Schmidt, & McCreary, 2003), and anxiety sensitivity may be an important individual difference variable in this relationship (Zvolensky et al., 2006). It may be that there are higher rates of smoking and other CHD health-compromising behaviors (e.g., hypertension, hypercholesterolemia, physical inactivity) among individuals with anxiety disorders. This may result in a fatal confluence of risk.

Anxiety and Atherosclerosis Another possible mechanism by which anxiety has its effect on CHD is through the progression of atherosclerosis. Using a broadly-defined condition of anxiety neurosis, Sims and Prior found a higher death rate from atherosclerotic disease among those with anxiety neurosis (Sims & Prior, 1982). Several factors are thought to contribute to atherosclerosis including elevated cholesterol and triglyceride in the blood (hypercholesterolemia), high blood pressure (hypertension), and cigarette smoking. Elevated cholesterol levels have been documented among patients with anxiety disorders (Huang, Wu, Chiang, & Chen, 2003; Peter, Goebel, Muller, & Hand, 1999; Peter et al., 2002); indeed, Peter and colleagues found that patients with anxiety disorders have elevated or high cholesterol levels almost three times as often as control subjects, even after controlling for anxiety-specific avoidance of physical exercise and special dietary habits (Peter et al., 1999). With regard to hypertension, one study that specifically examined predictors of blood pressure changes in middle-aged women found that women experiencing anxiety showed greater increases of systolic blood pressure over a 3-year follow-up period (Markowitz, Matthews, Wing, Kuller, & Meilahn, 1991). Several more studies of anxiety (as assessed by

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the Framingham Tension Scale) showed that anxiety is associated with hypertension among initially normotensive men (but not women) (Markovitz, Matthews, Kannel, Cobb, & D’Agostino, 1993). In a cohort study of 2,992 normotensive individuals over a followed-up period of 7 to 16-years, researchers found that both anxiety and depression were predictive of subsequent hypertension and prescription treatment for hypertension (Jonas, Franks, & Ingram, 1997). In addition to research with initially normotensive subjects, other research on anxiety and hypertension has been derived from studies with psychiatric samples. An increased incidence of hypertension has been found among patients with anxiety disorders (Noyes, Clancy, Hoenk, & Slymen, 1978; Wells, Golding, & Burnam, 1989). Matthews, Owens, Kuller, Sutton-Tyrrell, and Jansen-McWilliams (1998) followed 200 healthy women prospectively, and measures of atherosclerosis were obtained using ultrasound of carotid arteries to measure intima-media thickness (IMT; a marker of atherosclerosis) at 10-year follow-up (Matthews, Owens, Kuller, Sutton-Tyrrell, & Jansen-McWilliams, 1998). After controlling for risk factors (e.g., smoking, triglycerides, and pulse pressure), early anxiety (and hostility) was predictive of atherosclerotic disease symptoms. In another interesting line of research examining psychosocial risk and atherosclerosis, researchers worked with non-human primates, cynomolgus monkeys. Primates were assigned a stressed living condition (i.e., high or low) and were fed a diet high in fat, intended to mimic the diet consumed in North America (Kaplan et al., 1996; Manuck, Marsland, Kaplan, & Williams, 1995). After two years, dominant primates living in the stressed condition showed more than twice the amount of atherosclerosis than dominant primates residing in the low stress condition. Along these lines, some researchers have speculated that it is acute anxiety rather than more-trait-like anxiety that triggers ruptures of atherosclerotic plaques in the coronary arteries leading to SCD or other acute cardiac events (Davies & Thomas, 1984; Falk, 1983). Empirical research is needed to examine this possibility.

Anxiety and Altered Cardiac Function Anxiety is one of several psychosocial stressors that may bring about chronic autonomic imbalance with sympathetic predominance. Altered cardiac autonomic tone is a credible explanation for why anxiety may be associated with increased CHD risk. This possible mechanism could involve amplified sympathetic stimulation (that is associated with the occurrence of arrhythmias and SCD) or impaired vagal control (that is also associated with CHD mortality) (Farrell et al., 1987; Lown, Verrier, & Corbalan, 1973; Rich et al., 1988). Evidence supporting these hypotheses includes findings that individuals with anxiety disorders have a reduced HRV (Kawachi et al., 1995), consequently, indicating an alteration in autonomic tone.

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Reduced Heart-Rate Variability (HRV). The healthy heart displays beatto-beat variations that result from fluctuations in autonomic nervous system (ANS) activity at the sinus node. HRV decreases with stress (emotional or physical) and increases with rest. Therefore, HRV is considered a noninvasive marker of ANS function (Hayano, Sakakibara, & Yamada, 1991; Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology, 1996) and it is a commonly used means of studying sympathetic tone and inadequate parasympathetic tone. Greater autonomic dysfunction, as indicated by decreased HRV has been proposed as a plausible mechanism linking anxiety to increased cardiac mortality in post-MI patients. Increased sympathetic or decreased parasympathetic nervous system activity predisposes patients with CHD to ventricular tachycardia, ventricular fibrillation, and SCD (Podrid, Fuchs, & Candinas, 1990; Pruvot et al., 2000). Specifically, low HRV is indicative of excessive sympathetic and inadequate parasympathetic tone (Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology, 1996). Moreover, low HRV is a robust, independent predictor of post-MI mortality (Bigger et al., 1992; Kleiger, Miller, Bigger, & Moss, 1987; Sudhair, Stevenson, Marchant, & al., 1994), and it has been linked to increased risk of CHD (Dekker et al., 2000), atherosclerosis (Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology, 1996), MI (Bigger, Fleiss, Rolnitzky, & Steinman, 1993), cardiac events (Liao et al., 1997; Tsuji et al., 1996), and mortality (Dekker et al., 2000). Decreased HRV is associated with anxiety (Kawachi et al., 1995) and PD in particular (Yeragani et al., 1998). Using power spectral analysis of heart rate, Yeragani found that patients with PD had lower amplitudes of respiratory sinus arrhythmia during paced breathing and elevated levels of mid-frequency power during spontaneous breathing compared with normals (Yeragani et al., 1993). In a later study, these researchers studied beat-to-beat QT interval variability (QTV), identified as a predictor of SCD, and found that QTV is indeed elevated in patients with anxiety and depression. Interestingly, individuals with PD showed higher QTV at nighttime than controls (Yeragani, Pohl, Balon, Jampala, & Jayaraman, 2002). Findings from HRV studies suggest that the decreased vagal tone and increased sympathetic tone may contribute to increased risk for cardiac mortality in patients with anxiety, with some exceptions. One contradictory study conducted with 42 CAD patients with and without PD found that patients suffering both PD and CAD showed lower sympathetic modulation (Lavoie et al., 2004). These results suggest that alterations in HRV may not be the underlying mechanism for the increased morbidity and mortality among CAD patients with PD. One particular challenge in interpreting this research is that HRV has also been proposed as a marker of less favorable health in general (Dekker et al., 2000). Moreover, similar to studies with anxiety, decreased HRV has been linked with depression. Mean 24-hour HRV is lower in depressed than in medically similar nondepressed patients with stable CHD (Carney et al.,

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1995; Krittayaphong et al., 1997; Stein et al., 2000) and decreased HRV is generally accepted as one mechanism linking depression to increased cardiac mortality in post-MI patients (Carney et al., 2001). Failure to consider overlap and co-occurrence among the negative emotions may have influenced some of the conclusions that can be drawn from the HRV research to date. Susceptibility to Ventricular Arrhythmia. A related possible mechanism that may explain the harmful effects of anxiety on CHD and CHD-related mortality is through a susceptibility to ventricular arrhythmias. Ventricular arrhythmias occur when a group of heart cells in the lower two chambers of the heart (i.e., the ventricles) trigger contractions out of sync with the normal rhythm established by the sinus node; in short, arrhythmias are abnormal rhythms of the heart that cause the heart to pump blood less effectively. Blood is pumped through the heart in a controlled sequence of muscular contractions; these contractions are controlled by bundles of cells which control the electrical activity of the heart. When this sequence is disturbed, heart arrhythmias occur. Arrhythmias are abnormal rhythms of the heart, and many types of heart disease are associated with ventricular arrhythmias. Some researchers have posited that anxiety may be related to an increased risk of CHD and CHD-related mortality through the altered electrical stability of the heart including ventricular arrhythmias. Evidence of an association between psychological factors and ventricular arrhythmias is mixed (Follick et al., 1990; Follick et al., 1988; Freeman, Cohen-Cole, Fleece, Waldo, & Folks, 1984; Orth-Gomer, Edwards, Erhardt, Sjogren, & Theorell, 1980). Support for anxiety in particular as an arrhythmic mechanism is demonstrated by the known relationship between anxiety and increased sympathetic and parasympathetic cardiac control (Kawachi et al., 1995; Thayer, Friedman, & Borkovec, 1996; Watkins, Blumenthal, & Carney, 2002) and by findings that phobic anxiety increases the risk of SCD (Kawachi, Colditz et al., 1994). One particularly revealing study lends support to the premise that the increased risk in SCD observed in individuals with phobic anxiety may be due to ventricular arrhythmias. Watkins and colleagues directly examined the relationship between phobic anxiety and ventricular arrhythmias (Watkins et al., 2006) and found that phobic anxiety (and depression) predicted subsequent ventricular arrhythmias in 940 patients with CAD during a 3-year follow-up. The phobic anxiety-arrhythmia association was independent of comorbid depression; however, the composite (of anxiety and depression) resulted in a larger effect size than either construct independently. The most common type of ventricular arrhythmia (in both healthy and diseased individuals) is the ventricular premature beat (VPB). VPBs increase with psychological stress (Taggart, Carruthers, & Somerville, 1973; Taggart, Gibbons, & Somerville, 1969), and VPBs have also been identified as risk factors for electrical instability of the heart and SCD (Lown & Graboys, 1977; Lown & Ruberman, 1970). Kubzansky and colleagues summarized much of this research and theorized that anxiety (characterized as both an intense and acute psychological state) may be one psychological state which predisposes individuals to VPBs (Kubzansky et al., 1998). Indeed, one study found that

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compared to age- and sex-matched controls, patients with cardiac arrhythmia were significantly more anxious; assessment of anxiety was based on the Multiple Affect Adjective Checklist Anxiety Scale and the Psychasthenia Scale of the Minnesota Multiphasic Inventory (MMPI) (Katz, Martin, Landa, & Chadda, 1985). Based on these findings, it is conceivable then that increased risk of CHD and CHD-related mortality may be associated with anxiety through altered electrical stability of the heart.

Related Pathophysiological Mechanisms Emotionally stressful events have been shown to trigger onset of MI (Mittleman et al., 1995). Laboratory studies of mental stress (commonly defined by the acute experience of negative emotions including anxiety, depression, and anger) can induce MI in 50–70% of patients with positive nuclear exercise tests (Jiang et al., 1996; Rozanski et al., 1988), and this may be particularly important for personally relevant tasks. Laboratory mental stress tasks commonly include challenges associated with arithmetic, public speaking, gaming challenges, or other stressful tasks. Indeed, mental-stress induced ischemia has been shown to be a more potent predictor of cardiac events at long-term (> 3 years) follow-up than exercise-induced ischemia; patients with mental-stress induced ischemia showed markedly higher rates of cardiac events (both fatal and nonfatal) even after controlling for other risk factors (e.g., age, previous MI, initial left ventricular ejection fraction) (Jiang et al., 1996). In fact, even among individuals without any coronary disease, severe and sudden emotional distress can precipitate reversible left ventricular dysfunction (or ‘‘stress cardiomyopathy’’) (Wittstein et al., 2005), however, the mechanism for this is unknown (Grawe, Katoh, & Kuhl, 2006). It stands to reason then that the recurrent, intense, and often private experience of panic attacks, a common comorbidity of anxiety and mood disorders, may serve as a more potent stressor than laboratory-based mental tasks. Panic attacks can be considered acute psychological stressors and are accompanied by increased heart rate and blood pressure, as described more completely elsewhere with respect to PD (Fleet et al., 2000). It may be that patients with CHD and clinically significant anxiety or mood disorders (and/or panic attacks in particular) may experience more substantial and/or potent stress associated with induced myocardial ischemia. One study using 35% carbon dioxide challenge tests found that panic attacks preferentially provoked myocardial perfusion defects in CAD patients with PD compared to those without PD (Fleet et al., 2005). More controlled studies to determine the relative risk and underlying mechanisms supporting this possibility are needed. Because persistent overactivity of the SNS increases cardiovascular workload and hemodynamic stress, anxious individuals may be predisposed to experience a number of other adverse cardiovascular effects including

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endothelial dysfunction, coronary spasm, left ventricular hypertrophy, dysrhythmias, platelet activation, and thrombosis (Curtis & O’Keefe, 2002; Das & O’Keefe, 2006). One study found reduced baroreflex cardiac control (a particularly important risk factor for sudden death) in anxious patients (Watkins, Grossman, Krishnan, & Sherwood, 1998). In addition, platelets play an important role in hemostasis and also in the pathophysiology of CAD (Camacho & Dimsdale, 2000). Because platelets are affected by diverse stressors, including psychological ones, platelets offer an interesting vantage point for understanding the neurophysiology of various psychiatric disorders (Camacho & Dimsdale, 2000). Also, studies have demonstrated that stress-induced sympathetic activation and increased cortisol production can predispose individuals to hypertension and the metabolic syndrome (a possible precursor to coronary disease) (Brunner et al., 2002). Both elevated SNS activity and dysregulation of the hypothalamic pituitary-adrenal (HPA) axis have been found in medically healthy patients with major depression, as indicated by elevated plasma and urinary catecholamines and their metabolites (Esler et al., 1982; Roy, Pickar, De Jong, Karoum, & Linnoila, 1988; Veith et al., 1994) and by elevated plasma and urinary cortisol (Roy et al., 1988). These symptoms have been linked to arterial damage and risk for CHD. Similar studies with anxiety are needed. In addition, research examining other possible pathophysiological mechanisms purported in the stress and depression-CHD link may be beneficial in understanding the link with anxiety including increases in inflammatory proteins (i.e., C-reactive protein, interleukin-6) (Anisman & Merali, 2002) and a hyperactive 5-hydroxytryptamine (5-HT) transporter2A receptor signal system (Schins, Honig, Crijns, Baur, & Hamulyak, 2003). In one study, Kamarck and colleagues demonstrated the broad impact of daily life stress (i.e., psychological demands) and their association with CHD. Using carotid IMT assessed via ultrasonography, healthy older adults who reported higher daily life task demands showed larger IMT, after adjusting for covariates (Kamarck et al., 2004). Carotid IMT is used as a marker for atherosclerosis (Lorenz, Markus, Bots, Rosvall, & Sitzer, 2007). In another study conducted over 4 years, sustained anxiety increased carotid IMT (Paterniti et al., 2001). Other research has demonstrated that a history of major depressive disorder is related to low-grade systematic inflammation, which promotes the process (Danner, Kasl, Abramson, & Vaccarino, 2003). Anxiety may assist in this process via the anxiety-depression comorbidity and CHD (Grippo & Johnson, 2002). Notably, Brydon and colleagues found that inflammatory cytokine expression (i.e., interleukin-1b, interleukin-6) is positively associated with both cardiovascular responses and anxiety symptoms (Brydon et al., 2005); IL-1b and IL-6 are inflammatory cytokines that play an essential role in atherosclerosis. The definitive causal direction of these relationships remains to be seen. Even though depression has been extensively investigated, additional prospective work is needed to examine the mechanisms underlying cardiovascular morbidity and mortality among patients with anxiety and anxiety

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disorders. Studies examining how the negative emotions (e.g., anxiety, depression) have their direct and combined pathophysiological effects may be most revealing.

Therapeutic Approaches Targeting the Anxiety-CHD Association Cardiac rehabilitation is a medically supervised program designed to help patients recover from a cardiac event and to reduce the risk of another cardiac event or to keep an already present cardiac condition from worsening. Comprehensive programs offer health education, exercise program development, and assistance with cardiac risk factor modification (i.e., hypertension, hypercholesterolemia, smoking, obesity, diabetes, physical inactivity). Behavioral and psychosocial interventions are increasingly included in comprehensive cardiac rehabilitation programs partly due to the fact that the long-term success of these secondary prevention programs depends heavily on patient compliance. Moreover, in light of the increasing evidence revealing the negative impact of depression and other psychological factors on cardiac morbidity and mortality, truly comprehensive programs include psychological interventions (Skala, Freedland, & Carney, 2005). The psychological interventions often include stress management programs that are designed to reduce stress as a single endpoint or to reduce cardiac risk further in CHD patients. The stress management component tends to be skills-based and includes relaxation techniques alone or in combination with other more potent cognitive-behavioral strategies, including problem-solving skills, coping strategies, cognitive restructuring, and behavioral activation. A complete review of secondary and psychological interventions for coronary heart disease is beyond the scope of this chapter; for a more complete discussion see (Clark, Hartling, Vandermeer, & McAlister, 2005; Rees, Bennett, West, Davey Smith, & Ebrahim, 2004; Skala et al., 2005). Overall, psychosocial interventions for CHD (broadly-defined) have demonstrated that these often wide-ranging interventions do produce small reductions in anxiety in CHD patients but do not have an effect on subsequent cardiac morbidity or mortality. Anxiety (assessed by various measures) has been reported in fewer than 10 published clinical trials with mixed intervention results (Lewin, Robertson, Cay, Irving, & Campbell, 1992; Oldenburg, Martin, Greenwood, Bernstein, & Allan, 1995; Stern, Gorman, & Kaslow, 1983), and pooled results suggest that reductions in anxiety are associated with intervention effects (Rees et al., 2004). Composite measures of anxiety and depression are reported by other clinical trials and showed similar beneficial reductions (Black, Allison, Williams, Rummans, & Gau, 1998; Brown, Munford, & Munford, 1993; Rees et al., 2004). Published studies to date have not exclusively or independently targeted anxiety or anxiety disorders in patients with CHD, however, important findings

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regarding depression may be helpful in approaching treatment of anxiety in CHD. The first study to show that an antidepressant is safe for treating depression early after an acute event is the SADHART trial, Sertraline Antidepressant Heart Attack Randomized Trial (Swenson et al., 2003). Unfortunately, sertraline was only modestly effective in treating major depression. Partly due to drug-drug interactions that may be problematic and the modest findings, researchers have attempted to more fully integrate other empirically supported treatments for mood in patients with CHD (Skala et al., 2005). Inclusive reviews of psychological interventions with CHD patients have indicated that overall, such programs appear to have a modest effect on anxiety, depression, and non-fatal reinfarction; no effect on total or cardiac mortality is evident from the available data (Jordan et al., 2007; Rees et al., 2004). Perhaps the most weighty results for the impact of psychosocial interventions on reinfarction are reported in the large multicenter randomized controlled trial conducted with patients recovering from MI, Enhancing Recovering in Coronary Heart Disease (ENRICHD) trial (Berkman et al., 2003; Carney et al., 2004). The ENRICHD trial examined whether a cognitive-behavioral intervention for depression or low social support would reduce mortality and reinfarction in 2,481 patients post-MI. The treatment consisted of 11 individual sessions of cognitive behavior therapy, with group treatments when possible, over the course of 6 months; patients who experienced a less than 50% reduction in depression (as assessed by the Beck Depression Inventory) after 5 weeks also received medication. Results indicated that the intervention had important and significant impact on reducing depression and increasing social support, however, the hard endpoints of total mortality and non-fatal MI were not significantly different between the treated and usual care groups. Interestingly, patients in the usual care condition showed ‘‘substantial improvement’’ (p. 3106) and as result, group differences were less than expected (Berkman et al., 2003). Both assessment and treatment research on negative emotions and CHD has tended to focus on one negative emotion at a time, however, in light of the independent role of anxiety, symptoms of anxiety may need to be considered in risk stratification and treatment of emotionally distressed patients with CHD. Early recognition and treatment of anxiety in patients with CHD may minimize risk for future cardiac events.

Future Directions Cardiovascular disease remains the leading cause of preventable mortality in the Western world. Some 16 million Americans suffer from CHD, the most common form of heart disease and the leading cause of death (American Heart Association, 2006). Recent results of two large prospective studies have found that 80–90% of patients who developed clinically significant CHD and more than 95% of patients who experienced a fatal CHD event had at least on major

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modifiable risk factor (i.e., smoking, diabetes, hypertension, and hypercholesterolemia) (Greenland et al., 2003; Khot et al., 2003). These results have focused renewed attention on the prevention of CHD. Future research therefore must be on examining the upstream psychosocial instigators (e.g., anxiety, mood, physical inactivity, overeating) of the CHD epidemic. Unlike other negative emotions, less empirical research has explored anxiety and its possible cardiotoxic influences in CHD development, progression, and outcome. Failure to address anxiety and other psychological risk factors may be one reason that CHD-related morbidity and mortality remain high. The potential public health impact of preventing the development and progression of CHD is high if the nature of the association between anxiety and CHD is appreciated and investigated. The explanatory strength of anxiety as a psychosocial factor influencing CHD development and progression may be underestimated because most past studies have used suboptimal assessments tapping selective domains of anxiety. Symptom screenings are necessary but not sufficient in the place of more extensive diagnostic and structured clinical interviews that may help to identify this important emotional factor in CHD patients. Understanding CHD risk in patients suffering from anxiety disorders may be one line of inquiry to identify those most in need of prevention and intervention efforts. Issues of construct definition and overlap and diagnostic classification have hampered scientific knowledge to date, and ultimately research applying contemporary models of anxiety is needed to understand how anxiety may or may not influence CHD development and progression. Research is needed to more broadly investigate the current and lifetime incidence of Axis I anxiety and mood disorders and the underlying dimensions of emotionality (including negative affect) in the impact these anxiety conditions may or may not have on CHD. Similarly, research examining incidence of psychopathology and the course of subclinical psychiatric concerns (i.e., those conditions that do not surpass the threshold for sufficiently impairing and distressing or those conditions that do not reach full DSM-IV diagnostic criteria) may prove advantages toward identifying those individuals more at-risk who may be targeted for intervention. Comprehensive research examining anxiety (including worry, anxious apprehension), the panic spectrum, and the other negative emotions in CHD development and progression is warranted. In particular, the CHD-fear (e.g., panic attacks, the panic spectrum) association seems important. Also, perhaps there is a threshold at which anxiety begins to wield its cardiotoxic effects. Moreover, there are relatively little data regarding the additive yield of ‘‘pure’’ anxiety over that of other negative emotions. Methods used for diagnostic evaluation of cardiac diagnoses (and therefore group composition) have come under scrutiny, particularly with regard to missed diagnoses in women (Buchthal et al., 2000; Bugiardini & Bairey Merz, 2005), and comparative studies tell us little about within group variability. Studies examining psychological factors associated with the broad range of cardiac symptoms including NCCP are needed to explore possible means

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of intervention. With regard to directionality, the most compelling evidence for directionality can be drawn from studies that examine the anxiety-CHD link using the continuum of anxiety (i.e., ranging from low, subclinical to clinical anxiety disorders), the spectrum of health-compromising behaviors (i.e., ranging from overeating to obesity), and CHD. Future research using sophisticated research designs are needed to unravel these issues of directionality. In light of the strong psychosocial influences on CHD, risk reduction programs will continue to be developed, particularly for secondary prevention of CHD. If anxiety continues to show independent association with CHD, there will likely be less resistance from the medical community to such programs. It may be particularly rewarding to evolve treatments to fit with these empirical associations. Controlled intervention studies targeting individuals with these factors for proven risk-reduction therapies, or specifically treating these factors with available therapies, are few. One particularly interesting line of recent inquiry is designed to examine the extent that positive psychological factors (i.e., optimism, gratitude, altruism) may reduce physiological hyperresponsiveness that may in turn reduce clinical events (Rozanski & Kubzanksy, 2005). Finally, the wealth of scientific knowledge in our understanding of the role psychosocial factors may have in CHD could not have been accomplished without the tremendous interdisciplinary cooperation and coordination spanning many disciplines. Future collaborative research examining the risk and protective factors that contribute to anxiety and CHD may provide information to better understand the experience of anxiety in CHD and begin to identify the individuals most in need of intervention.

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HIV and Anxiety Conall O’Cleirigh, Trevor A. Hart, and Carolyn A. James

Introduction There is a growing body of literature that identifies the psychosocial and behavioral factors that increase individuals’ vulnerability to Human Immunodeficiency Virus (HIV) infection and that adversely impact HIV disease management and progression among HIV-infected individuals. In this chapter we consider the evidence that anxiety and its disorders negatively impact susceptibility to HIV infection and interfere with adaptive disease management. It is plausible, for example, that the presence of anxiety disorders may interfere with an individual’s ability to negotiate safer sex or increase the likelihood of injection drug use thereby increasing the risk of HIV infection. HIV disproportionately affects men who have sex with men (MSM), communities of color, and minority women (Centers for Disease Control and Prevention, 2005). We consider the evidence that higher levels of anxiety disorders in these risk groups may, in part, account for the higher HIV prevalence observed in these groups. It is also possible that the presence of anxiety disorders or high levels of anxious affect may contribute to poorer disease course in people already living with HIV. We review the existent research to consider several pathways by which anxiety may compromise optimal disease management by interfering with individuals’ ability to adhere to their anti HIV medications, by increasing substance and alcohol use, or by negatively impacting physical functioning and underlying pathophysiology. The first section of the chapter provides an overview of HIV disease course and treatment. The second section considers the prevalence of anxiety disorders in people living with HIV and reviews the evidence that particular anxiety Conall O’Cleirigh Massachusetts General Hospital, Psychiatry Department, Department of Psychiatry, Behavioral Medicine Massachusetts General Hospital, 1 Bowdoin Square BS-07B, Boston, MA 0211 [email protected] This research was supported in part by the National Institute of Health, National Institute on Drug Abuse (NIDA) grant R01-DA018603, PI. Steven Safren, Ph. D.

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disorders may be over-represented in particular HIV risk groups. Thirdly, we examine the role of anxiety in sexual risk for HIV infection and transmission among HIV-negative and positive individual respectively. We next review the literature on the role of anxiety symptoms and disorders in the management of HIV with reference to medication adherence and substance use. Finally we examine the relationship between anxiety and functional impairment and consider some of the neurobiological mechanisms common to anxiety and the pathophysiology of HIV. We conclude with some specific recommendations for directed clinical research.

An Overview of HIV HIV is an infectious disease that is spread predominantly through sexual exposure but also through contaminated blood products, injection drug use, or occupational exposures. It is estimated that more that 40 million adults and children are infected with HIV worldwide and approximately two-thirds of these cases are in Sub-Saharan Africa. Since the beginning of the epidemic, more than 18 million people have died of AIDS. It is estimated that in the United States close to 1 million people are living with HIV. Men who have sex with men (MSM) continue to represent the largest group of new infections in North America and AfricanAmericans comprised 49% of all new U.S. infections in 2005. Approximately 40% of all U.S. HIV cases diagnosed in 2004 progressed to AIDS within 12 months of diagnosis (Centers for Disease Control and Prevention (CDC), 2005). HIV is a retrovirus whose principal targets of infection are CD4þ cells (t-helper cells), which play a major part in regulating immune response (Gallo & Montagnier, 1988). The clinical presentation of acute HIV infection (e.g., fever, muscle weakness, and fatigue, (Boyle, McMurchie, Tindall, & Cooper, 1993) can manifest shortly following infection and persist for several weeks during which time the immune system mounts an initial response to HIV infection. This period is also associated with high initial rates of CD4þ cell decline and is followed by a prolonged asymptomatic phase during which the individual remains healthy. During this phase gradual CD4þ cell decline continues and in the absence of antiretroviral treatment HIV viral load increases. CD4þ cell number and HIV viral load are the principal biological measures of disease progression and predict clinical outcomes and survival. As the CD4þ cells fall to less than 500 cells/mm2, the susceptibility to infection increases and initial presentation of Category B symptoms are observed (e.g. night sweats, peripheral neuropathy, shingles, fatigue). When CD4þ cell number falls below 200 cells/mm2 an AIDS diagnosis is made and the risk of developing Category C (AIDS defining) symptoms or neoplasias increases (e.g., Kaposi’s Sarcoma, HIV wasting syndrome, lymphoma) as the immune system becomes seriously compromised. The insidious depletion of CD4þ cells results in inverted CD4þ/CD8þ ratios and the functional capacity of T-lymphocytes and

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proliferative responses are progressively impaired and natural killer cell cytotoxicity (NKCC) decreases (Klimas, Baron, & Fletcher, 1991). The average time between infection and progression to AIDS can vary as a function of antiretroviral medication regimen (Fischl, 1995) or route of infection and a range of psychosocial characteristics (see Leserman, 2003). The clinical care of HIV infected individuals has improved dramatically over the last decade. In fact, the disease course has changed from a virtual death sentence via progressive deterioration of the immune system to a manageable chronic condition. Treatment began with the introduction of the first antiretroviral agent, zidovudine (AZT) in 1987. With the advent of combination therapies that include newer reverse transcriptase inhibitors and HIV-specific protease inhibitors (PI), referred to as highly active antiretroviral therapy (HAART), significant further improvement has been made in delaying AIDS and mortality (Lima, Hogg, Harrigan, et al., 2007). The success of HAART has greatly increased HIV survival with recent estimates greater than 24 years post HIV diagnosis (Schackman, Gebo, Walensky, et al., 2006). As life expectancy increases so also does the cost of HIV-related medical care. The life time cost of HIV medical care has been estimated at between $385,200 and $618,900 depending primarily of the discounts available for antiretroviral medication (Schackman, Gebo, Walensky, et al., 2006) constituting a significant public health expense and identifying prevention of future cases of HIV infection as a continued public health concern.

Prevalence of Anxiety Disorders in People Living with HIV In the U.S., estimates of lifetime anxiety disorders among HIVþ individuals range from 3.6% to 19% (e.g., Johnson, Williams, Rabkin, Goetz, & Remien, 1995; Sewell, Goggin, Rabkin, Ferrando, McElhiney, & Evans, 2000). These estimates appear to be somewhat lower than in the general population where prevalence of lifetime anxiety disorders is estimated to be approximately 29% (Kessler, Chiu, Demler, & Walters, 2005). Estimated rates of current anxiety disorders among HIVþ individuals range widely from less than 1% to 43% (e.g., Chandra, Ravi, Desai, & Subbakrishna, 1998; Johnson et al., 1995; Perretta et al., 1996;Perkins et al., 1994; Savard, Laberge, Gauthier, Ivers & Bergeron, 1998; Sewell et al., 2000). This wide variability in prevalence estimates is likely due to several factors, one of which is the variation in measures used to assess anxiety. Higher prevalence rates (36–43%)have been found in studies using clinical cutoffs on screening measures such as the Hospital Anxiety and Depression Scale (HADS; Zigmond & Snaith, 1983) as opposed to a diagnosis based on the Structured Clinical Interview for the Diagnostic and Statistical Manual (DSM) (under 20%) (SCID; Spitzer Williams, Gibbon et al., 1995). Additionally, the variability in prevalence estimates likely results from the small sample sizes that have been used to assess the prevalence of any anxiety disorder. Among the studies noted above, the largest sample size was 442 (Brown et al., 1992) with the remainder having sample sizes below 200 (Chandra et al., 1998; Perretta et al., 1996).

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There may also be variation in the prevalence of any anxiety disorders by subgroup of HIVþ individuals, although the extent of this variation is difficult to determine because studies have focused primarily on MSM. Based on the available literature, rates of any anxiety disorders by subgroups of HIVþ individuals seem comparable. The prevalence of any current anxiety disorder is approximately 1–12% for MSM (Johnson et al., 1995; Perkins et al., 1994; Rosenberger et al., 1993; Sewell et al., 2000), and 12% for men in general (Brown et al., 1992), which seem similar to rates among HIVþ individuals in general (6.6–12%; Holmes, Bix, Meritz, Turner, & Hutelmyer., 1997; Perretta et al., 1996). Unfortunately, no known research has examined the prevalence rates of overall anxiety disorders among HIVþ women. The evidence is equivocal as to whether or not the prevalence of current anxiety disorders is higher among those who are HIVþ compared to the general population. A study of 442 HIVþ male U.S. Air Force personnel found that nearly 12% met criteria for a current anxiety disorder, which was significantly higher than rates among age-matched men in the community, who had a prevalence of 4.7% (Brown et al., 1992). However other studies have reported no difference in rates of current anxiety disorders among HIVþ and HIV-negative individuals (e.g., Rosenberger et al., 1993; Sewell et al., 2000). Given inconsistencies in findings and given that many of the studies were conducted over ten years ago when the HIV epidemic was significantly less associated with heterosexual sex in Western societies than it is currently, it is unclear whether rates of anxiety disorders differ from those in the general population. However, specific anxiety disorders may be more common among HIVþ individuals than in the general population. HIV and Post Traumatic Stress Disorder (PTSD). Much of the research examining the rates of anxiety disorders among individuals with HIV has focused on PTSD. Estimates of the rates of PTSD among HIVþ individuals vary widely, and seem to depend on the patient population under examination. For example, although studies report prevalence rates of PTSD ranging from approximately 10% to 54% (e.g., Kelly et al., 1998; Kimerling, Calhoun, Forehand et al., 1999; Olley, Zeier, Seedat, & Stein, 2005; Smith, Egert, Winkel, & Jacobson, 2002; Tsao, Dobalian, Moreau, & Dobalian, 2004a) rates may be higher among specific populations such as MSM (e.g., Kelly et al., 1998), minority women (e.g., Kimerling et al., 1999) and those with persistent pain (e.g., Smith et al., 2002) compared to those in nationally representative samples (e.g., Tsao et al., 2004a). Overall, rates of PTSD among HIVþ individuals seem to be higher than in the general population (Kessler et al., 2005) and may be higher than among other medical patient groups (Tedstone & Tarrier, 2003). As is found in the general population, among those with HIV, rates of PTSD seem to be higher among women than men (Olley et al., 2005).

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Among HIVþ individuals, PTSD is frequently comorbid with other psychiatric diagnosis, particularly major depression, substance abuse and other anxiety disorders. In a study using a nationally representative probability sample of over 1400 HIVþ individuals, Tsao and colleagues (2004a) found that among those with a PTSD diagnosis, 36.5% had comorbid Major Depressive Disorder (MDD) and 28.9% had comorbid panic disorder (PD). In a sample of individuals recently diagnosed with HIV, those with PTSD were significantly more likely to have comorbid MDD, suicidality and social anxiety disorder (Olley et al., 2005). It is possible that the trauma associated with receiving a diagnosis of HIV may contribute to PTSD symptoms. In fact, approximately one third of HIVþ individuals with PTSD attribute the onset of their PTSD specifically to their HIV diagnosis (Kelly et al., 1998; Olley et al., 2005). The higher rates of PTSD in certain subgroups of HIVþ individuals, particularly minority women, also may be attributable to both higher rates of stressful life events and childhood sexual abuse in these groups (e.g., Kimerling et al., 1999). HIV and Panic Disorder (PD). Estimates of the PD prevalence in HIV are fairly consistent, ranging from 11–16% across several large-scale studies (Bing et al., 2001; Orlando, Burnam, Beckman, et al., 2001; Sherbourne et al., 2000; Tsao, Dobalian, & Naliboff, 2004b). PD is highly comorbid with other psychiatric disorders among HIVþ persons, with some research indicating that over half of those with PD have an additional diagnosis, the most common of which are MDD and PTSD (Tsao et al., 2004b). HIV and Generalized Anxiety Disorder (GAD). Reported rates of GAD among HIVþ individuals generally range between 6.5% and 20% (Bing et al., 2001; Haller & Miles, 2003; Sherbourne et al., 2000; Tsao et al., 2004b; Tucker et al., 2003; Wilkins et al., 1991), with the highest prevalence rate found among individuals attending outpatient mental health clinics. In general, these rates seem higher than that reported in a large-scale national survey, where the 12month prevalence of GAD was 3.1% (Kessler et al., 2005). Moreover, there is some evidence that the prevalence of GAD decreases over time. In a sample of over 2800 HIVþ individuals, Tsao and colleagues (2004b) found that the prevalence of GAD decreased significantly over a six-month period from 16% to 11%. HIV and Other Anxiety Disorders. There is little research examining the prevalence of other anxiety disorders among HIVþ individuals. In a sample of 190 HIVþ individuals attending a HIV mental health clinic, 9% were found to have simple phobia (Haller & Miles, 2003). To our knowledge, there are no studies examining prevalence rates of other anxiety disorders such as social anxiety disorder and obsessive-compulsive disorder among HIVþ individuals. HIVþ MSM and Anxiety Disorders. Studies focusing on anxiety disorders among HIVþ MSM have yielded inconsistent results in terms of prevalence rates, with rates of current and lifetime anxiety disorders ranging from 3–12% to 7–19% respectively (Perkins et al., 1994; Rosenberger et al., 1993; Sewell et al., 2000). Several studies have reported no differences in rates of

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anxiety disorders between HIVþ and HIV-negative MSM (Perkins, et al., 1994; Rosenberger et al., 1993; Sewell et al., 2000). For example, a two-year longitudinal study of HIVþ and HIV-negative MSM who were non-intravenous drug users found that the two groups did not differ in their rates of either lifetime or current anxiety disorders (Sewell et al., 2000). HIVþ Women and Anxiety Disorders. PTSD appears to be over-represented in HIV-infected women, likely because of increased exposure to traumatic stressors such as physical violence and sexual assault (Kimerling et al., 1999). In a study of 67 inner-city African-American women beyond the initial stages of HIV infection, it was found that over a third of the sample met DSM-IV criteria for PTSD. More elevated rates have been reported in higher-risk samples. For instance, in a sample of 81 HIVþ incarcerated women, Lewis (2005) found that nearly three quarters of the sample met criteria for lifetime PTSD. Not only do these rates appear higher than among community samples of women (10.4%; Kessler, Sonnega, Bromet, Hughes, & Nelson, 1995) but are also higher than among incarcerated females in general (30–42%; Jordan, Schlenger, Fairbank, & Caddell, 1996; Teplin, Abram, & McClelland, 1996). Although high-risk HIVþ women appear to be at greater risk for anxiety disorders, particularly PTSD, this risk may not apply to HIVþ women in general. A study comparing HIVþ and –negative women without current substance abuse found that the two groups did not differ in their rates of anxiety disorders, although the HIVþ women were more likely to have depression (Morrison et al., 2002). Conclusions. Based on the current literature, it is difficult to determine whether anxiety disorders in general are more prevalent among HIVþ individuals compared with normative samples. This is due to the fact that no known large-scale studies have examined the prevalence of overall rates of anxiety disorders in people living with HIV. Smaller studies have yielded inconsistent results likely due to subgroup and measurement variation. However, there is evidence that particular anxiety disorders, (i.e., PTSD and GAD) may be more prevalent among those with HIV. Higher prevalence of PTSD may be indicative of traumatic responses to HIV diagnoses and co-occurrence of other traumatic stressors. Additionally, there is evidence that prevalence of anxiety disorders may be elevated among groups with higher HIV prevalence rates than the general population, particularly MSM and high-risk women.

Anxiety and Risk for HIV Infection or Transmission Few studies specifically examine the role of anxiety in risk for contraction or transmission of HIV. Most research examining the role of psychological distress in HIV risk investigates other phenomena such as depression or substance use (e.g., Johnson, Cunningham-Williams, & Cottler, 2003; Stall et al., 2003). Further, the research is limited by methodological problems regarding the

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measurement of anxiety. Earlier HIV risk studies discussing fear or anxiety actually appear to not to have assessed anxiety per se, but related constructs such as negative and stereotypic attitudes about AIDS (Tashakkori & Thompson, 1992) or intent to avoid contracting a sexually transmitted disease (Katz, Gipson, Kearl, & Kriskovich, 1989). More recent research on HIV risk has employed measures of general emotional distress containing anxiety-related items (e.g., Heckman, Anderson, Sikkema, Kochman, Kalichman, & Anderson, 2004), or screening measures such as the anxiety subscales of the Brief Symptom Inventory (Derogatis & Melisatatos, 1983). A meta-analysis of the literature found extremely weak associations between anxiety measures and unprotected sex (r = 0.03; Crepaz & Marks, 2001). However, the lack of anxiety-specific measures may have led to false conclusions regarding the possible influences of anxiety on HIV risk and prevention. It has therefore been suggested that more sensitive and specific anxiety measures be used in future studies of examining HIV risk cognition and behavior (Kalichman & Weinhardt, 2001). Few studies have found an association between anxiety and HIV risk behavior, defined here as either 1) drug use where blood contact between an HIVþ and an HIV-negative person may take place, such as in injection drug use or sharing of other drug paraphernalia where blood droplets may be present, or 2) unprotected female-male or male-male sexual intercourse (Centers for Disease Control and Prevention, 2005). General emotional distress measures combining anxiety and depression have not been reliably associated with HIV risk behaviors among MSM or adolescent females (e.g., Dudley, Rostosky, Korfhage, & Zimmerman, 2004; Ethier, Kershaw, Lewis, Milan, Niccolai, & Ickovics, 2006). Studies using the anxiety subscale of the Brief Symptom Inventory have not had reliable associations with HIV sexual risk behavior. For example, some research has found no association between anxiety and unprotected sex among HIVþ individuals (e.g., Kalichman, 1999), other work have found a negative association between anxiety and unprotected sex among HIVþ women but not among HIVþ men (e.g., Kennedy et al., 1993), and yet another study suggested an association between scores on the anxiety scale and unprotected insertive and unprotected receptive anal intercourse in the past three months among HIVþ MSM (e.g., O’Leary, Purcell, Remien, & Gomez, 2003). Trait Anxiety and HIV Risk. High trait anxiety scores, especially in the context of high sexual inhibitions due to threat of sexual performance failure, were associated with a reduced profile regarding unprotected anal intercourse in a sample of over 550 gay and bisexual men (Bancroft, Janssen, Strong, Carnes, Vukadinovic, & Long, 2003). Similarly, higher trait anxiety has also been associated with greater risk behavior in a group of 557 Puerto Rican injection drug users, including sharing injection drug paraphernalia and unprotected vaginal sex (Reyes et al., 2007). Social Anxiety and HIV Risk. In a recent study among over 100 gay and bisexual youth Hart and colleagues reported a positive association between social anxiety about being observed by others or performing a task, or social

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performance anxiety, and prevalence of unprotected insertive anal intercourse over the past six months (Hart & Heimberg, 2005, Hart, Purcell, & Farber, 2004). Other studies that have not formally assessed social anxiety also seem to suggest a direct effect of social anxiety on unprotected anal intercourse. For example, using content analysis on focus groups of 41 gay men, Offir and colleagues (1993) found that individuals often modified their sexual behavior because of concerns about AIDS, but their safer sex behaviors remained inconsistent. Social anxiety may also be implicated in other risk factors for engaging in unprotected sex such as embarrassment discussing or using condoms as reported among small samples of heterosexual youth (Abel & Fitzgerald, 2006; Hingson et al., 1990), or crystal methamphetamine use among MSM (Green & Halkitis, 2006; Halkitis, Parsons, & Wilton, 2003; Semple, Patterson, & Grant, 2002). Recent studies of both HIVþ and HIV-negative gay men suggest that men with greater fears of offending a sexual partner have greater difficulty asserting condom use and/or safer sex (Adam, Husbands, Murray, & Maxwell, 2005; Murray & Adam, 2001; Seal et al., 2000). In another study, 32% of gay men reported being less likely to use condoms when they did not wish to offend their partner or if they were concerned their partner would react negatively (Offir et al., 1993). Fears of rejection appear to be greater when one perceives a partner to be more sexually desirable. Although other factors have been identified in cross sectional studies of small cohorts of HIV-infected men and women that may influence perceptions of sexual desirability including physical attractiveness (Murray & Adam, 2001), and fear being rejected because of their HIV serostatus (Klitzman, 1999; Siegel & Schimshaw, 2003). PTSD and HIV Risk. Controlling for cocaine or heroin dependence, current HIV status, and demographic variables, lifetime prevalence of PTSD was associated with a 1.7 times greater likelihood of engaging in anal sex and a 1.6 times greater likelihood of engaging in prostitution (Hutton et al., 2001). These findings may partially explain why PTSD might have a higher prevalence among HIVþ individuals. However, PTSD has not consistently been associated with unprotected sex among adolescent girls (Smith, Leve, & Chamberlain, 2006) or adult HIVþ women (Myers et al., 2006). It is therefore unclear that PTSD is a risk factor for unprotected sex, or if it is fact a proxy variable for having experienced traumatic events that are also associated with risky sex among both MSM and heterosexual samples, such as childhood sexual and physical abuse (Smith et al., 2006; O’Leary et al., 2003). In fact, the documented relationships between childhood sexual abuse and risky sexually behavior appear to be similar for HIV negative (Kalichman, Gore-Felton, Benotsch, Cage, & Romapa, 2004; Stall et al., 2003) and positive (O’Leary et al., 2003) men. Other Anxiety and HIV Risk. Consistent with Snell (2001), physiological symptoms of anxiety also were associated with recent sexual activity among HIV-infected adolescents (Murphy et al., 2001). Health anxiety, or feelings of anxiety related to the possibility of becoming ill, also was associated with recent sexual activity in this sample. Murphy et al. (2001) posit that health anxiety may

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increase sexual behavior paradoxically by increasing attempts to reduce anxiety via alcohol and drug use in this population. Worries about vulnerability to HIV infection are associated with reducing frequency of sexual activity and increasing condom use because of AIDS (Zimet et al., 1992). Similar to findings regarding anxiety about romantic attachments and HIV-related beliefs, among high-risk, young pregnant U.S. women recruited from urban prenatal clinics, anxiety about romantic attachments is associated with greater HIV risk behavior. Specifically, anxiety about romantic attachments was associated with a lower percentage of condom use in the past six months and ever having unprotected sex with a risky partner (e.g., a partner with a history of a sexually transmittednfection or with HIV) in the past six months (Kershaw et al., 2006). Mechanisms of Anxiety-related HIV Sexual Risk. It has been suggested that high awareness that one can contract HIV through sexual behavior may have paradoxical effects (McKirnan, Ostrow, & Hope, 1996) because of its anxiogenic effects. In this model, HIV risk awareness may increase anxiety, which may in turn increase cognitive disengagement, an avoidant coping strategy. Avoidance of anxious thoughts through pleasurable activities (e.g., sexual activity, substance use) may well interfere with safer sex negotiation and condom use. As both PTSD and childhood sexual abuse have been associated with unprotected sexual intercourse, anxiety has also been suggested as a mediator of the relationship between childhood sexual abuse and sexual risk behavior (e.g., O’Leary et al., 2003). This is particularly relevant as the prevalence of PTSD and childhood sexual abuse are significantly higher among MSM (e.g., Kelly et al., 1998) and minority women (e.g., Wyatt et al., 2002; Kimerling et al., 1999), two groups at increased risk for HIV infection. In addition to anxiety, hostility and suicidality (O’Leary et al., 2003), low selfesteem, substance abuse (Rosario, Scrimshaw, & Hunter, 2006), depression (Miller 1999; O’Leary et al., 2003) and dissociation (Kalichman et al., 2001) have been identified as mediators of the relationship between childhood sexual abuse and sexual risk behavior. In combination, anxiety, hostility and suicidality mediated the relationship between childhood sexual abuse and unprotected receptive anal intercourse among HIVþ MSM (O’Leary et al., 2003), although among gay and bisexual youth (Rosario et al., 2006), childhood sexual abuse had a direct association with unprotected receptive anal intercourse. These results suggest that anxiety may play a more significant role in the pathway from childhood sexual abuse to sexual risk taking among MSM who are HIVþ compared with those who are not. Conclusions. Among women, the evidence seems to suggest that severity of the abuse history (Wyatt et al., 2002) is associated with increased risk for HIV and increased HIV sexual risk behavior (Bensley, Eenwyk, & Simmons, 2000). Generally, the consequences of childhood sexual abuse or adult sexual assault appear to have more consistent associations with HIV sexual risk behavior than diagnostic measures of PTSD or other anxiety measures. Recent studies using more specific measures of anxiety have had somewhat greater success in identifying anxiety-related risk factors for HIV risk behavior. However, conclusions

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are limited by the wide range of samples and method for measuring anxiety. Research studies also vary in choice of dependent variables, such as unprotected intercourse (e.g., Hart & Heimberg, 2005) and behaviors associated with unprotected intercourse such as number of sexual partners (Rosario, Scrimshaw, & Hunter, 2006). Measures of emotional stress that incorporate anxiety items and screening measures of anxiety have demonstrated conflicting associations with HIV risk behavior. Future research examining when anxiety exerts risky versus protective effects, and for whom it exerts these effects, is therefore warranted. Lastly, it would be beneficial to examine the effects of more specific types of anxiety, as some appear to be associated with less risk (e.g., trait anxiety; Bancroft et al., 2003) and some with more risk (e.g., social performance anxiety; Hart & Heimberg, 2005)

Anxiety and HIV Disease Management There is considerable variation in HIV disease progression and there is a compelling body of research identifying the psychosocial (e.g., depression, life stress) and behavioral (e.g., medication adherence, substance use) factors that account for some of this variation (see Leserman, 2003 for a review). The presence of a pre-existing anxiety disorder in HIVþ patients or the emergence of anxiety in response to HIV may impair the patient’s ability to approach the distress associated with was variety of disease related stressors (e.g., diagnosis, access to health care, medication adherence, symptom onset). Anxious avoidance of HIV-related distress can interfere with the individual’s ability to effectively manage his or her disease (Antoni, 2003). In addition, the relationship between anxiety and physical functioning in HIV is particularly relevant as the physical symptoms of anxiety overlap with many of the symptoms of advancing HIV disease (e.g., fatigue, disturbances of sleep and appetite) and with side effects of antiretroviral therapy (e.g., abdominal pain, reduced appetite, chills, constipation, diarrhea, dizziness, fatigue, insomnia) (Hofman & Nelson, 2006). There is limited longitudinal research linking anxiety disorders to accelerated disease course in HIV. However, several studies have reported significant predictive relations between avoidant coping (a coping response to stress consistent with anxious responding) and accelerated HIV disease progression (e.g., Ironson, O’Cleirigh, Fletcher, et al., 2005; Leserman, Petitto, Golden, et al., 2000). Similarly, Boarts, Sledjeski, Bogart and Delahanty (2006) reported that diagnostic levels of PTSD symptoms in 57 HIVþ men and women were significantly associated with increased plasma RNA viral load at 3-month follow-up. It is plausible that anxiety may exert its influence on HIV disease progress through its relationship with health behaviors or physical functioning. The relationships between anxiety and medication adherence, substance use and health-related quality of life are examined below.

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HIV, Anxiety, and Health Behaviors Anxiety and Medication Adherence in HIV. Adherence to antiretroviral medications is critical for suppression of viral replication (< 50 viral copies/mL), the goal of antiretroviral therapy (ART). It has been estimated that 90% adherence or greater is necessary to achieve this goal (Paterson, Swindells, Mohr, 2000; Bartlett, 2002). There is a large and growing body of literature identifying the psychosocial and behavioral barriers to medication adherence in HIV (for review see Ammassari et al., 2002). The relationship with medication adherence in HIV and anxiety has been examined with anxiety generally assessed and with specific anxiety disorders. Ammassari, et al. (2002) examined the relationship between anxiety as measured by the Mental Health Index-5 (Wu, Rubin, Mathews, et al., 1991) and self-reported adherence among a diverse cohort of 358 Italians living with HIV. In multivariate analysis, they found that anxiety symptoms were independently associated with non-adherence to antiretroviral medication in the past three days. Similarly, Van Servellen, Chang, Garcia and Lombardi (2002) found that HADS anxiety score was significantly related to both self-reported non-adherence and clinician evaluated adherence based upon patient chart review. Anxiety, assessed through the anxiety subscale of the Brief Symptom Inventory, was the only measure related to sub-optimal adherence in a non-psychiatric sample of patients receiving primary HIV care at outpatient clinic (Scho¨nnesson, Williams, Ross, Bratt & Keel, 2006). Interestingly, severity of intrusion and avoidance symptoms associated with trauma, was associated with better adherence to medication schedule. Several studies have examined the impact of disorder specific anxiety symptoms on medication adherence in patients with HIV. As part of the HIV Cost and Services Utilization Study (Tucker, Burnam, Sherbourne, Kung & Gifford, 2003) using a probability sample of 1,910 adults with HIV, those meeting diagnostic criteria for generalized anxiety disorder and panic disorder (Composite International Diagnostic Interview-Short Form; CIDI-SF, World Health Organization, 1998) were more than twice as likely to be non-adherent than those without a psychiatric disorder. Non-adherence was also significantly associated with depression, substance use and heavy alcohol use. Screening positive for any anxiety disorder (by CIDI-SF) was positively associated with taking medication as directed, whereas social phobia was significantly associated with running out of medications (Ingersoll, 2004). The evidence for a relationship between PTSD symptom severity and medication adherence is mixed. Boarts, Sledjeski, Bogart and Delahanty (2006) reported that severity of depression but not PTSD predicted self-reported adherence at 3-month follow-up in a small group of HIVþ patients. Although the severity of PTSD avoidance and intrusion symptoms related to receiving an HIV diagnosis were both related to estimates of skipped medications and offschedule doses assessed for various time frames during the previous 3 months (Delahanty, Bogart, & Figler, 2004).

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The results of these studies provide some evidence that anxiety, generally assessed, is associated in with sub-optimal medication adherence in diverse samples of patients with HIV. The results of these studies suggest also that symptoms of social phobia, panic, and GAD are associated with medication non-adherence. The largest effects were observed for GAD and panic symptoms. PTSD symptoms of avoidance and intrusion specifically related to HIV were significantly associated with multiple measures of adherence but measures based on diagnostic criteria of PTSD produced only weak associations. All but one of the studies reviewed here used cross-sectional designs creating difficulties specifying the direction of the significant effects. It is possible that the severity of anxious symptoms interferes with adherence but it is also plausible that adherence violations (typically assessed with in the past week) contribute to anxious affect and other symptoms of anxiety. Anxiety and Substance Use in HIV. Substance use in patients with HIV confers multiple disadvantages. Substance use has been associated with both accelerated disease progression and with poorer adherence to antiretroviral medication (e.g., Arnsten et al., 2001; Lucas et al., 2002), with delayed response to ART (Palepu, Tyndall, Yip, et al., 2003) and with failure to achieve HIV viral suppression for those initiating HAART (Lucas, Cheever, Chaisson, et al., 2001). Injection drug use in HIV has also been associated with poorer immune (Wood, Montaner, Yip, et al., 2004) and clinical disease (Moore, Keruly, & Chiasson, 2004) outcomes. Although the co-occurrence of substance use and anxiety disorders has been widely studied in the general population (e.g., Kessler et al., 2005) there is a paucity of research examining this co-morbidity in people with HIV (Chander, Himehoch & Moore, 2006). A recent study estimates the 1 year prevalence rates of comorbid substance use and anxiety/mood disorder in HIV is greater than 8% (Pence, Miller, Whetten, Eron, & Gaynes 2006). Most dramatically, alcohol and substance use disorders were 2.5 and 7.5 time more prevalent than in the general population. These findings are broadly consistent with earlier estimates (Bing et al., 2001) although rates of GAD (15.8%) and panic (10.5%) were higher and drug dependence and heavy alcohol use predicted the presence of mood or anxiety disorders. In a large sample (n = 1168) of HIVþ MSM, Ibnanez, Purcell, Stall, Parsons and Gomez (2005) reported higher rates of anxiety, childhood sexual abuse, and hostility among injection drug users (IDUs) compared to non-IDUs and higher rates of sexual transmission risk behavior than those reporting no drug use. Among 355 African-American crack abusing women, general measures of anxiety and PTSD symptom severity were significantly associated with multiple sexual partners (Roberts, Wechsberg, Zule, & Burroughs, 2003). More recently, among a group of 198 HAART naı¨ ve HIVþ patients, the probability of mood/ anxiety and substance use disorders predicted a slower rate of viral suppression and a faster rate of overall virologic failure after suppression. Alcohol and substance abuse/dependence also predicted faster overall virologic failure (Pence, Miller, Gaynes, & Eron, 2007).

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In summary, there is good evidence from large and nationally representative samples of HIVþ patients identifying the comorbidity of anxiety and substance use disorders. In these samples the prevalence substance use disorders are dramatically higher than in the general population and the presence of substance use disorders appears to be positively associated with the presence of mood/anxiety disorders. There is initial evidence that anxiety symptom severity among HIVþ substance users is associated with increase sexual risk behavior and that substance use and anxiety disorders are associated with poorer response to antiretroviral treatment. Although substance use impediments to adaptive HIV disease management have been well described, it is likely that comorbid anxiety and substance use disorders interact to create unique pathways to HIV sexual transmission risk (O’Cleirigh & Safren, 2007) and elucidating these mechanisms may help to specify targets to support both anxiety treatment and HIV prevention efforts.

HIV, Anxiety and Health-Related Quality of Life The success of highly active antiretroviral therapy (HAART) in containing HIV viral replication, delaying symptom onset and extending life has focused increased attention on health-related quality of life (HQOL) in people living with HIV. In addition, higher HRQOL has been shown to be predictive of improved survival in patients with advanced HIV (Jacobson, Wu, & Feinberg, 2003). In HIV/AIDS, there is little research examining the relationship between anxiety disorders and HRQOL and much of it is limited by cross-sectional designs. Orlando and colleagues (2005) constructed a probability sample of 2,864 HIV-infected adults representing 231,400 patients in care in the United States in 1996. HQOL measures of general health and lack of pain significantly predicted less generalized anxiety and panic symptoms severity at 8-month follow-up. However, baseline anxiety was not significantly related measures of HRQOL at follow-up although depressive symptoms were. In the only other examination of these relationships over time Sewell, et al. (2000), found that, among a group of HIVþ MSM, general measures of anxiety and anxiety disorders assessed through Structured Clinical Interview Diagnostic (SCID: Spitzer et al., 1995) were significantly related to fatigue, physical limitations and to current HIV symptoms at each of the six-month assessments over 2 years. These results maintained when the physical symptoms of anxiety were removed from the anxiety measures. Anxiety was not significantly related to either CD4 cell count or to HIV viral load. Two separate studies reported significant cross-sectional relationships between PTSD symptom severity and health related measures of physical functioning. Leserman et al. (2005) reported that PTSD symptoms were significantly associated with more pain and poorer physical and role functioning

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and with increased utilization of health care services in the previous 9 months. In fact, PTSD symptom severity, trauma history and stressful life events accounted for 27% of the variance in health related functioning controlling for CD4 cell count and HIV-viral load. Smith et al. (2002) reported that PTSD was significantly associated with greater pain intensity and impairment. Also within a cross-sectional design, Holmes et al. (1997) reported that the presence of Axis 1 disorder was significantly associated with lower HRQOL domain scores for health perceptions and mental health. General measures of anxiety have also been related to physical functioning in HIV controlling for HIV disease severity among men (McDaniel, Fowlie, Summerivlle, Farber, and Cohen-Cole, 1995), women (Tostes, Chalub, & Botega, 2004), and intravenous drug users (Lipsitz, et al., 1994). The results of the research reviewed above provide good evidence for a relationship between symptoms of anxiety and HRQOL and other measures of physical functioning. Measures of anxiety based upon diagnostic criteria appear to provide the most consistent evidence for a relationship with health-related functioning and the strongest evidence (replication in a large representative sample) appears to exist for the relationship between PTSD and health-related physical functioning. The relative paucity of longitudinal research in this area makes it difficult to specify the directionality of these relationships. It is possible that HIV disease related decrements in physical functioning might lead to the onset of anxiety symptoms and disorders or exacerbate existing symptoms as the results reported by Orlando et al. (2005) may suggest. It is also plausible that the presence of anxiety disorders may either contribute to decrements in physical functioning (as Leserman et al., 2005 suggest) or at least incline people living with HIV to lower their estimates of their own physical health. In any event there is sufficient evidence reported here to conclude that diagnostic assessment of anxiety may well help inform patients’ HIV symptom reports and reports of physical functioning. The application of randomized trials of cognitive-behavioral therapy to treat anxiety disorders in people with HIV would allow for an examination of treatment related changes in physical functioning and HIV-symptom burden. The results of these studies would help characterize the relationship between anxiety and HRQOL more fully.

HIV and the Pathophysiology of Stress Hormones in Anxiety The neurobiology of anxiety disorders is complex and our understanding of the mechanisms is limited. However, there is a growing body of research that points to disruption of the hypothalamic pituitary adrenocortical (HPA) and sympathetic adrenal medullary (SAM) systems in the pathophyisology of anxiety with associated dysregulation of cortisol and norepinephrine respectively. These are the two core systems that modulate the biological response to stress. For

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example elevated norepinephrine reactivity to stressors has been shown in patients with PD, GAD, and social anxiety disorder (Brawman-Mintzer et al., 1997; Tancer et al., 1993; Abelson et al., 1991) and elevated baseline levels of norepinephrine in patients with PTSD (van der Kolk, 1994). Similarly disruption of cortisol and its precursor, corticotropoin releasing factor (CRH), have been observed in patients with social anxiety disorder, GAD and PTSD (Resnick, Yehuda, Foy, & Pitman, 1995; Abelson et al., 1991). The dysregulation of the HPA and SAM systems in people with anxiety disorders who are also living with HIV is of critical importance as elevated levels of both norepinephrine and cortisol have been independently linked to accelerated disease progression in HIV (Ironson et al., 2006; Leserman, Petitto, Golden, et al., 2000). It has been suggested that the stress hormones cortisol and norepinephrine (NE) may represent potential pathways linking psychological stress response to health outcomes in HIV (Schneiderman, Ironson, & Siegel, 2005). Specifically, cortisol, has been associated with down regulation of the immune system (Munck & Guyre, 1991) and increased HIV infection of lymphocytes (Markman, Salahuddin, Veren, Orndorff, & Gallo, 1986) and elevated levels of norepinephrine enhance viral entry into target lymphocytes and increase HIV viral replication (Cole, Korin, Fahey, & Zack, 1998; Cole, Kemeny, Fahey, Zack, & Naliboff, 2003). In addition, higher levels of autonomic nervous system activity have also been associated with impaired response to HAART (Cole, Naliboff, Kemeny, et al., 2001). Efficacious treatments for anxiety disorders may well allow people living with HIV to reap the physiological benefit of treatment related regulation of the stress hormones cortisol and norepinephrine. In summary, the presence of anxiety disorders may place people living with HIV at a physiological disadvantage through dysregulation of the stress hormones norepinephrine and cortisol. Elevated levels of these hormones are associated with down regulation of the immune system, more rapid HIV viral replication, and impaired response to HAART which may well be the pathways linking elevated levels of stress hormones to poorer HIV disease course.

Directions for Future Research There is a lack of focused and programmatic research on HIV and anxiety. We present some general recommendations to highlight some of the gaps in the scientific knowledge base. Although there is evidence that PTSD and GAD may be more prevalent in people with HIV (particularly among MSM and high risk women) than in the general population, a comprehensive picture of the prevalence rates of anxiety disorders in people living with HIV is unavailable. Studies examining these rates are hampered by inadequate sample sizes and wide spread variation in the measurement of anxiety. Large scale, epidemiological studies are needed to

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reliably estimate the prevalence of anxiety disorders in HIV particularly if useful estimates of the prevalence across HIV risk groups is to be obtained. A preliminary and emerging picture of the relationships between anxiety and outcomes important in HIV is presented in Fig. 1. The model depicts two putative pathways from anxiety to health outcomes, one mediated through health behaviors and the other physiologically mediated though stress hormones. Although there is evidence for many of the direct relationships depicted here the mediated relationships await empirical verification. In general programmatic research elucidating the relationships depicted here will help improve our understanding of the role of anxiety in HIV. In particular, it is apparent that the relationship between anxiety and risk of HIV infection or transmission is complex, with some evidence suggesting that social performance anxiety is associated with increased risk. Further, higher levels of anxiety appear to combine with substance use disorders to increase sexual risk behavior and substantially interfere with HIV treatments. Certainly, additional research more fully elucidating the relationship between anxiety and sexual risk behavior is needed. However, recent research has articulated the need to address comorbid psychosocial issues in HIV prevention (Stall et al., 2003; Koblin et al., 2004) and the adaptation of traditional HIV prevention interventions to address anxiety (e.g., social anxiety disorder) and substance use issues may improve prevention intervention outcomes and help illuminate these relationships.

Behaviors Medication Adherence Substance Use Transmission Risk Behavior (STIs, superinfection) Individual Resources (e.g., trauma history, time since HIV diagnosis, access to care, etc)

Anxiety Profile Anxiety Disorder Anxious Symptoms

Stress Hormones Norepinephrine Cortisol

Biological Markers of HIV Disease CD4+ cells HIV Viral Load

Clinical Disease Outcomes Survival Clinical Progression Development of AIDS

Health-Related Quality of Life (HQOL)

Fig. 1 A Depiction of the direct and mediated relationships between anxiety and health and disease outcomes in HIV Note: The above model describes some of the pathways by which anxiety and its disorders may impact the disease process and health outcomes in HIV. This model is not intended to describe all possible relationships but to suggest potential mechanisms for which there is some initial evidence in the literature reviewed. In the model, anxiety has two main pathways by which it exerts its impact on HIV. In the behavioral pathway the presence of anxiety disorders negatively influence behaviors (adherence, substance use, transmission risk behavior) which in turn can negatively impact immune control of the HIV virus and lead to poor survival and accelerated clinical progression of the disease. In the second pathway the presence of anxiety disorders directly impacts underlying physiology through higher levels of stress hormones which down regulate the immune system leading to poorer immune control of HIV and less favorable disease course.

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The most conspicuous gap in the research on HIV and anxiety is the absence of psychosocial or psychopharmacological clinical intervention research designed to treat anxiety disorders in people with HIV. There is some evidence of the efficacy of broad based coping and stress management group interventions that have been associated with reductions in intrusion and avoidance symptoms of anxiety in HIVþ patients with CSA histories (Sikkema Hansen, Kochman et al., 2007), and with reductions in anxious mood in MSM (Antoni, et al., 2000; Chesney, Chambers, Taylor, Johnson, & Folkman, 2003). Most critically, there is an unmet need for efficacious and effective interventions to treat the full range of anxiety disorders in people with HIV. The success of adapted CBT interventions in the treatment of depression in HIV (for review see Olatunji, Mimiaga, O’Cleirigh, & Safren 2006) augurs well for the generalizability of CBT procedures to treat anxiety in HIV. It seems from this review that the development of efficacious treatments for PTSD is a priority. In particular, the development of psychosocial interventions, or the adaptation of existing technologies, with specific application in HIV for women and MSM with CSA histories is warranted. PTSD and related symptoms are over represented in these groups, and are associated with increased risk for transmission risk behavior, accelerated disease progression, increased symptom burden, poorer medication adherence, and cortisol dysregulation. There is some evidence that psychosocial intervention related changes in anxiety have been associated with changes in norepinephrine in patients with HIV (Antoni et al., 2000) and with reductions in HPA dysregulation in patients with GAD (Tiller, Biddle, Maguire, & Davies 1988). The incorporation of biological measures of disease progression (CD4þ cell and HIV viral load) and stress hormones as secondary outcomes into randomized clinical trials to treat anxiety disorders could help to specify the physiological pathways by which anxiety exerts its influence on disease and health outcomes in HIV.

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Physical Illness and Treatment of Anxiety Disorders: A Review Norman B. Schmidt, Meghan E. Keough, Lora Rose Hunter, and Ann P. Funk

Physical Illness and Anxiety Psychopathology Anxiety psychopathology represents one of the most prevalent and debilitating forms of mental illness (Kessler, Chiu, Demler, & Walters, 2005; Weissman, Markowitz, Ouellette, Greenwald, & Kahn, 1990). Extrapolating from epidemiological studies, it may be conservatively estimated that 25% of the population will suffer from clinically significant anxiety at some point in their lives with a 12-month prevalence rate of approximately 18% (Kessler et al., 2005). Anxiety disorders generally maintain a chronic course when untreated (Pine, Cohen, Gurley, Brook, & Ma, 1998) and result in substantial impairment across the lifespan (Ferdinand & Verhulst, 1995). In addition to the immense personal suffering created by anxiety psychopathology, these disorders create a considerable public expense that includes treatment costs, lost work time, and mortality. In addition, anxiety psychopathology is associated with increased utilization of non-psychiatric medical services (Greenberg et al., 1999). The issue of increased medical utilization indirectly speaks to the topic at hand since it appears that one reason for medical utilization in these patients includes the high co-occurrence of physical illness with anxiety disorders. For example, there are well-established associations between panic disorder and cardiorespiratory disorders such as asthma, chronic obstructive pulmonary disease, and mitral valve prolapse (Gorman, Goetz, Fyer, & King, 1988; Karajgi, Rifkin, Doddi, & Kolli, 1990; Weissman et al., 1990; Zandbergen et al., 1991). Epidemiological reports indicate that chronic medical conditions are more prevalent in those with a lifetime history of an anxiety disorder (Wells, Golding, & Burnam, 1989). Longitudinal evaluation of anxiety patients has indicated an increased risk for chronic medical conditions (e.g., hypertension, migraine headaches, ulcer, thyroid disease) compared to the general population (Rogers, White, Warshaw, & Yonkers, 1994). Norman B. Schmidt Department of Psychology, Florida State University, Tallahassee, FL 32306-1270, Tel: (850) 644-1707, Fax: (850) 644-7739 [email protected]

M. J. Zvolensky, J. A. Smits (eds.), Anxiety in Health Behaviors and Physical Illness. Ó Springer 2008

341

Panic Disorder

Panic Disroder

Panic Disorder

Panic Disorder

Panic Disorder

Panic Disorder

CCAP Roy-Byrne, Stein et al., 2005

CCAP Roy-Byrne, Craske et al., 2005

CCAP Craske et al., 2005

Schmidt & Telch, 1997

Schmidt et al., 2003

Klein et al., 2006

Study

Primary Diagnosis Evaluated

Table 1 Summary of cited studies

Health Perceptions

Health Perceptions Chronic Health Condition Health Perceptions

Medical Disability

Medical Disability

Medical Illness burden

Primary Medical Comorbidity Treatment

CBT (delivered via the

CBT-G

CBT-G

CBT plus Medication vs. Medication

CBT plus Medication Management vs. Usual Care CBT plus Medication Management vs. Usual Care

Randomized Control

Randomized Waitlist Control

Combined Analysis from Control and Treatment Groups No Control

Randomized Control

Randomized Control

Design (groups)

-ADIS-IV

46

55

-SCID-NP

111 (subsample of study total) 71

-CIDI

-CIDI -Fear Questionnaire -Anxiety Sensitivity Index -CIDI -Fear Questionnaire -Anxiety Sensitivity Index -SCID-NP

232

232

Sample Size

Primary Diagnostic Tools used to Assess Psychopathology

-General Health Survey -Physical Health Rating Form -Self-reported number of visits to physician

-General Health Survey

-WHO Disability Scale

-WHO Disability Scale

-RxRisk-V score

Primary Diagnostic Tools used to Assess Physical Illness

342 N. B. Schmidt et al.

Primary Diagnosis Evaluated

Panic Disorder

Anxiety Depression

PTSD Acute Stress Disorder

PTSD

Anxiety Depression

Study

Ross et al., 2005

Kissane et al., 2003

Bryant et al., 2003

Shemesh et al., 2006

Kennedy et al., 2003

Table 1 (continued)

Spinal Cord Injury

Myocardial Infarction

Mild Traumatic Brain Injury

Breast Cancer

Medical Usage Asthma

Primary Medical Comorbidity

Cognitive Effectiveness Training

CBT plus Education vs. Education

internet or manual) CBT-G plus Asthma Education CognitiveExistential Group Therapy plus Relaxation vs. Relaxation CBT vs. Supportive Counseling

Treatment

NonRandomized Matched Historic Control

NonRandomized

Randomized Control

Randomized Waitlist Control Randomized Control

Design (groups)

85

14

24

303

25

Sample Size

-Acute Stress Disorder Inventory -Clinician Administered PTSD Scale -Impact Event Scale -PTSD Diagnostic Scale -SCID-P -STAI -BDI

-HADS -Affect Balance Scale

-ADIS-IV

Primary Diagnostic Tools used to Assess Psychopathology

-Physician Diagnosis

-Physician Diagnosis confirmed by study Cardiologist

-Glasgow Coma Scale

-Physician Diagnosis confirmed by Histology reports

-Self-rating of physical health -Physician Diagnosis

Primary Diagnostic Tools used to Assess Physical Illness

Physical Illness and Treatment of Anxiety Disorders: A Review 343

Anxiety Depression

Mood disturbance Stress

Range of Anxiety and Mood diagnoses

Anxiety Depression

Range of Anxiety and Mood diagnoses Range of Anxiety and Mood diagnoses MDD GAD Panic Disorder

Study

Craig et al., 1998

Speca et al., 2000

Anson & Ponsford, 2006

Suh et al., 2002

Gothelf et al., 2005

Creed et al., 2005

Massand et al., 2002

Primary Diagnosis Evaluated

Table 1 (continued)

Severe Irritable Bowel Syndrome

Irritable Bowel Syndrome

Childhood Cancer

End-Stage Renal Disease

Traumatic Brain Injury

Cancer

Spinal Cord Injury

Primary Medical Comorbidity Treatment

Psychodynamic Interpersonal Therapy vs. SSRI Paroxetine vs. usual medical cares

SSRI Paroxetine

SSRI Fluvoxamine

Regular Exercise

Mindfulness MeditationBased Stress Reduction program CBT-G

CBT-G

257

20

No Control

Randomized Control

15

14

31

90

58

Sample Size

No Control

No Control

Randomized Waitlist Control

NonRandomized Control Randomized Waitlist Control

Design (groups)

-SCAN -clinician administered HDRS

-Profile of Mood States -Symptoms of Stress Inventory -HADS -Sickness Impact Profile -Rosenberg SelfEsteem -Self-rating Depression Scale -STAI -K-SADS-PL -CDI -BDI -SCARED -SCID

-STAI -BDI

Primary Diagnostic Tools used to Assess Psychopathology

-Gastroenterology Clinic Patients Rome I Criteria SF36 scores

-Current pediatric hematologyoncology center patients -IBS Rome I criteria -confirmed by flexible sigmoidoscopy

-Current hemodialysis treatment

-TBI rehailitation patient

-Past cancer diagnosis

-Physician Diagnosis

Primary Diagnostic Tools used to Assess Physical Illness

344 N. B. Schmidt et al.

GAD

Migraine Disorder

Primary Medical Comorbidity Treatment Selective Serotonin Agonist – Buspirone

Randomized DoubleBlind Placebo Controlled

Design (groups) 74

Sample Size -DSM-IV GAD Criteria -HAM-A

Primary Diagnostic Tools used to Assess Psychopathology

l

l

Anxiety Disorders Interview Schedule (ADIS-IV) Beck Depression Inventory (BDI) l Cognitive Behavioral Group Therapy (CBT-G) l Children’s Depression Inventory (CDI) l Composite International Diagnostic Inventory (CIDI) l State Trait Anxiety Inventory (STAI) l Hamilton Depression Rating Scale (HDRS) l Hospital Anxiety and Depression Scale (HADS) l Structured Clinical Interview for DSM-IV-TR Axis I Disorders (SCID) l Schedules for Clinical Assessment in Neuropsychiatry (SCAN) l Schedule for Affective Disorders and Schizophrenia for School-Age Children, Present and Lifetime Version (K-SADS-PL) l Hamilton Anxiety Rating Scale (HAM-A) l Screen for Child Anxiety Related Emotional Disorders (SCARED) l World Health Organization (WHO) l Short Form-36 (SF36) l Major Depressive Disorder (MDD) l Generalized Anxiety Disorder (GAD) l Post Traumatic Stress Disorder (PTSD)

Lee et al., 2005

Study

Primary Diagnosis Evaluated

Table 1 (continued)

-International Headache Society criteria -Migraine Disability Asessment Score (MIDAS)

Primary Diagnostic Tools used to Assess Physical Illness

Physical Illness and Treatment of Anxiety Disorders: A Review 345

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The relationship between anxiety disorders and non-psychiatric medical illness is complex. It appears that anxiety psychopathology can contribute to the development of physical conditions and/or exacerbate existing physical conditions (Karajgi et al., 1990; Kawachi, Sparrow, Vokonos, & Weiss, 1994). In addition, non-psychiatric medical conditions can contribute to the development of anxiety disorders (Kahn, Drusin, & Klein, 1987; Raj, Corvea, & Dagon, 1993) and/or exacerbate anxiety disorder symptoms (McCue & McCue, 1984). Alternatively, the mechanisms that account for comorbidity may be completely independent. Determining whether concurrent non-psychiatric medical conditions are a cause, consequence, or independent of an anxiety disorder is often difficult, but currently held psychological models of anxiety provide an explanatory framework for some of these linkages. Consider some of the prominent psychological theories of anxiety psychopathology (Barlow, 1988; Clark, 1986). These models describe two mechanisms for the generation and/or maintenance of anxiety and panic including: (1) cognitive misappraisal that may often involve the misappraisal of benign bodily sensations and, (2) interoceptive conditioning that links bodily cues with sympathetic arousal. Bodily perturbations are a common and necessary element for the generation of fear in each of these mechanisms. In the context of these mechanisms, it is apparent that the presence of physical conditions that create perceivable bodily perturbations will necessarily place an individual at greater risk for both catastrophic misappraisal of sensations and an interoceptively mediated fear response. In line with these psychological models of anxiety and panic, non-psychiatric medical morbidity may contribute to or maintain anxiety problems when the physical condition produces bodily sensations that are likely to be misattributed. Whatever the relationship, the interplay between the anxiety disorder and physical conditions is likely to influence response to treatment.

Treatment of Anxiety Psychopathology Despite the high prevalence and impairment created by anxiety psychopathology, the evolution in psychological and pharmacological treatments has made tremendous strides in the past 20–30 years. Fortunately, efficacious treatments for anxiety are available including several types of pharmacotherapy as well as cognitive behavioral therapy (CBT; Schmidt, Koselka, & Woolaway-Bickel, 2001). Antidepressants such as monoamine oxidase inhibitors (MAOIs), tricyclic antidepressants (TCAs), and serotonin selective reuptake inhibitors (SSRIs) are among the psychotropic medications that have demonstrated the highest levels of efficacy in the treatment of anxiety disorders (see Sammons & Schmidt, 2001, for a review). Antidepressants have become the medication of choice in the pharmacological treatment of anxiety problems, reducing anxiety symptoms without causing the withdrawal and dependency that can occur with

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benzodiazepines. Yet, benzodiazepines are appealing in that they provide more rapid anxiolytic effects and therefore continue to also serve as a common treatment for certain anxiety disorders. In terms of psychotherapy, research has consistently demonstrated that CBT is one of the most efficacious treatments for most forms of anxiety (see Nathan & Gorman, 1998, for a review). CBT for anxiety disorders is a highly structured, skill-based treatment in which the therapist works with patients to modify thinking and behaviors that maintain anxiety. Techniques utilized in CBT include education, cognitive reappraisal, anxiety management procedures such as progressive muscle relaxation and breathing control skills, as well as various exposure-based interventions. These include interoceptive exposure (i.e., repeated exposure to bodily sensations associated with a fear response), in vivo exposure (i.e., exposure to external situations connected to fear) and imaginal exposure (i.e., exposure to feared internal thoughts and cues). The high rates of comorbidity evident for anxiety disorders have naturally led to evaluation of the effects of co-occurring conditions on treatment outcome. In the case of psychiatric comorbidity, Mellman and Uhde (1987) found poorer response to pharmacotherapy in patients with panic disorder and comorbid obsessive-compulsive disorder. Pollack, Otto, Rosenbaum, and Sachs (1992) reported poorer outcome for panic disorder patients with comorbid Axis II disorders. However, Brown, Antony, and Barlow (1995) found that co-occurring Axis I diagnoses did not differentially affect treatment outcome. While we are beginning to appreciate some of the complications arising from treating patients with anxiety plus other psychiatric conditions, there is very little work exploring the comorbidity of anxiety with physical illness. The focus of this chapter is to review studies that have evaluated treatment effects for those with comorbid anxiety and physical illnesses. In regard to inclusion and exclusion criteria for this review, there are many studies that include some assessment of anxiety in the context of physical illness (see Table 1). However, we excluded a good number wherein anxiety assessment was not a primary focus of the paper, and was not particularly relevant to our understanding of the treatment of Axis I anxiety problems. Generally this occurred when the anxiety symptom outcomes were based on brief, self-report instruments; the symptoms themselves were most likely attributable to a threatening medical condition or procedure (e.g., receiving a cancer diagnosis or undergoing chemotherapy); the study did not adequately assess for clinically significant anxiety; or the treatment of physical illness was the primary focus. We did, however, include and briefly summarize a few studies where these limitations existed, because the investigations raised interesting points. Due to the general lack of research in this area, there is not a well-defineliterature on specific sets of anxiety condition and physical illness. As a result, definitive conclusions about specific pairings of conditions are necessarily limited. In the first review section, we consider available research assessing all forms of anxiety and physical illness comorbidity in the context of psychosocial treatments. Because there are a number of studies varying significantly in methodology, this

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section is organized by the strength of the research design. In the second section we focus on comorbidity in the context of pharmacological treatments. This section is organized according to the issues explored in the limited relevant literature. For each study, our goal is to give a sense of the nature of both the anxiety condition and the physical illness including how adequately each was assessed. In addition, we clarify the nature of the intervention that was used in the trial. Finally, we give a sense of the level of effect in terms of the outcomes that were assessed (e.g., changes on anxiety symptoms, changes in physical illness). As the reader will note, there are relatively few studies that have utilized strong methodologies (e.g., large samples randomized to active treatment and control conditions for psychological treatments, double-blind placebo controlled trials for pharmacological interventions). As a result, we felt that we should include weaker designs that could be informative since the state of knowledge in this area is so nascent.

Psychosocial Treatment of Physical Illness and Anxiety Randomized with Treatment Comparison Group The Collaborative Care for Anxiety and Panic study (CCAP) (Craske et al., 2005; Roy-Byrne, Craske et al., 2005; Roy-Byrne, Stein et al., 2005) sought to investigate the effectiveness of CBT and medication combined versus usual care in the treatment of patients with panic disorder in primary care settings. This was a multi-site study involving six clinics from three different cities. Participants were recruited through brief screenings in the clinic waiting room or referrals from medical providers. Eligibility was determined over the telephone using the Composite International Diagnostic Interview (CIDI; World Health Organization, 1997). Patients met DSM-IV criteria for panic disorder and were randomly assigned to care as usual or to the combined CBT and medication treatment condition. In the treatment condition, participants were assigned to a health care specialist who delivered six in-person sessions of CBT along with six brief booster sessions via the telephone. The CBT techniques employed were relaxation, exposure to feared situations, homework, provision of information about panic attacks, identification of cognitive errors, challenge of cognitive errors and modification of behavioral response to feared bodily sensations. The health care specialist also coordinated the medication management for each participant. Published reports from CCAP study have indicated that the combination of CBT plus medication outperformed usual care in terms of number of remitters and responders as well as greater improvement in functional status and health related quality of life (Roy-Byrne, Craske et al., 2005). Further comparison of individuals who received CBT plus medication versus medication alone, regardless of randomized condition, also revealed an advantage to the combined treatment (Craske et al., 2005). Of particular interest to the current review,

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a medical illness burden score was calculated based on the number and type of prescription medications participants reported taking along with their selfreports of chronic disease (Roy-Byrne, Stein et al., 2005). Based on this calculation, the participants were split into those below and above the median score for burden of medical illness. Individuals above the median reported more anxiety symptomatology, psychiatric comorbidity and disability than their counterparts. However, CBT and pharmacotherapy produced comparable response rates in both groups. The authors cautioned that although both groups responded at a similar rate, the medically burdened group continued to exhibit more symptomatology at follow-up due to their higher baseline symptoms. Thus, the medically burdened group might require a longer intervention to reach the same level of symptomatology as the less medically burdened group. In another report relevant to health ratings, number of medical visits, and anxiety symptoms, Klein, Richards, and Austin (2006) assessed the effectiveness of different CBT delivery methods for individuals with panic disorder (Klein et al., 2006). Participants’ diagnoses were established via the clinician administered anxiety disorders interview schedule (ADIS-IV; Brown, DiNardo, & Barlow, 1994). Participants were randomly assigned to one of three conditions; internet based CBT, CBT manual, or information only control group. The internet condition was composed of one introductory module, four learning modules, and a relapse prevention module. Techniques included controlled breathing instruction, cognitive restructuring, and interoceptive and situational exposure. Each participant was instructed to complete one module a week for six weeks and received support and feedback from a therapist via e-mail. Individuals in the manual condition were mailed a copy of Mastery of Your Anxiety and Panic: MAP-3 (Barlow & Craske, 2000). This manual included the same CBT information as the internet modules but differed in presentation and organization. In addition, the manual group received support and guidance from a counselor who contacted them weekly via the telephone. The information only group was given psychoeducation regarding the nature, causes, effects and treatment options for panic disorder. They were also contacted weekly via the telephone by a study therapist who provided minimal support, checked their symptoms, and encouraged them to reread the informational material. A number of standardized anxiety measures were conducted at each assessment point (pretreatment, post-treatment and follow-up). Participants’ health ratings were established during each assessment point by asking patients how many times they had seen their general practitioner in the past month and also asking them to rate their physical health on a scale from 0 (extremely poor) to 10 (extremely good). The two CBT groups showed greater improvement than the control group on all dependent variables including panic disorder symptomatology, panic related cognitions, negative affect, number of general practitioner visits, and physical health ratings. The gains on all of these variables were maintained or further improved at the 3-month follow-up screening. The internet group outperformed the manual group on health ratings at follow-up and general

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practitioner visits at both post and follow-up. Analyses were not conducted to determine whether health status moderated treatment outcome. Kissane et al., (2003) investigated whether cognitive-existential group psychotherapy (CEGT) among women with breast cancer improved their mood and mental attitude toward cancer. Previous investigations have reported that anxiety and depression are quite common among women recently diagnosed with breast cancer (Burgess et al., 2005). Participants were recruited from nine metropolitan hospital oncology departments and all had been diagnosed with early stage breast cancer confirmed through histology reports. The 303 participants were randomly assigned to receive relaxation classes or CEGT plus relaxation. During three relaxation sessions, participants were taught progressive muscle relaxation with guided imagery. CEGT was manualized and had six goals: promoting a supportive environment, facilitating grief over losses, reframing negative thoughts, enhancing problem solving and coping, fostering hope, and examining priorities for the future. The CEGT was conducted in small groups by two therapists over 20 weekly 90-minute sessions. The therapists were trained in this therapy through a series of workshops and came from the professional fields of psychology, psychiatry, social work, occupational therapy, and oncology nursing. Participants were assessed at baseline and follow-up using the Hospital Anxiety Depression Scale (Zigmond & Snaith, 1983) and the Affects Balance Scale (Derogatis, 1992), a self-report measure designed to assess a range of positive and negative affective states. CEGT group therapy exhibited a trend toward reducing anxiety (d = 0.217) yet failed to significantly impact negative mood (d = 0.254). Psychologists were more successful at decreasing both negative mood and anxiety, with a moderate effect size of d = 0.515. Analyses were not conducted to determine whether pretreatment anxiety moderated treatment effects. Bryant, Moulds, Guthrie, and Nixon (2003) evaluated whether PTSD could be prevented among mild traumatic brain injury patients experiencing acute stress disorder. All patients were injured through a motor vehicle accident or a nonsexual assault within the two weeks prior to study enrollment. Mild brain injury was operationalized as posttraumatic anterograde amnesia of less than 24 hours and a Glasgow Coma Scale score between 13 and 15. Participants also met criteria for Acute Stress Disorder as assessed by the Acute Stress Disorder Interview (Bryant, Harvey, Dang, & Sackville, 1998). Patients were randomly assigned to receive CBT or supportive therapy. Both therapies were administered individually in five weekly 90-minute sessions. CBT techniques included: education about traumatic reactions, progressive muscle relaxation training, imaginal exposure to traumatic memories, cognitive restructuring, and graded in vivo exposures to avoided situations. Supportive therapy provided education about trauma and problem-solving skills. At post-treatment and 6-month follow-up, participants were assessed for PTSD using the clinician administered PTSD Scale (Blake et al., 1995). Individuals in the CBT group exhibited substantially lower rates of PTSD development at both post-treatment (d = 1.16) and at 6-month follow-up (d =0.87).

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Randomized with Waitlist Individuals with panic disorder frequently report a comorbid nonpsychiatric medical illness. While there is extensive support of CBT’s effectiveness in treating the anxiety condition in such persons, few have investigated whether CBT would also improve concommitant physical health. Schmidt et al. (2003) studied panic disorder and general health. After diagnosis via a clinical interview (SCID-NP; First, Spitzer, Gibbon, & Williams, 1994), participants were randomly assigned to 12 weeks of group CBT or to a waitlist condition. The group CBT was a structured, manualized treatment that focused on four main objectives: education and feedback regarding the development and maintenance of panic disorder, identification and alteration of faulty panic related appraisals, interoceptive exposure, and exposure to feared external situations. The Panic Disorder Severity Scale (PDSS; Shear et al., 1997), Sheehan Patient-Rated Anxiety Scale (SPRAS; Sheehan, 1983), General Health Survey (GHS; McHorney, Ware, & Raczek, 1993) and Physical Health Rating Form (PHRF; Orts et al., 1995) were administered to all participants at baseline and post-treatment. Fifty-six percent reported at least one chronic health condition at baseline on the GHS. The treatment group reported both a significant reduction in anxiety symptoms and an improvement in their physical health. Analyses of clinical significance showed that being in the CBT group accounted for 13% of the change in the PHRF scores, 18% of the change in the SPRAS, and 27% of the change in the PDSS. Further, mediational analysis indicated that the gains in physical health were independent of improvement in anxiety symptoms. Ross, Davis, and MacDonald (2005) focused on individuals with comorbid panic disorder and asthma and assessed the combined treatment of CBT and asthma education. Asthmatics report a higher rate of panic disorder than the general population. In this study, individuals with panic disorder were identified using the Anxiety Disorders Interview Schedule for DSM-IV (ADIS-IV; Brown et al., 1994). Participants diagnosed with panic disorder were randomized to either a treatment or waitlist condition. Treatment included twelve 90-minute sessions administered in small groups over eight weeks. The CBT protocol focused on four main objectives: education and corrective feedback regarding the nature, etiology and maintenance of panic disorder; identification and alteration of faulty anxiety and panic related appraisals; and training in slow diaphragmatic breathing and interoceptive exposure. Asthma related indices were attained using the Asthma Quality of Life Questionnaire (Juniper, Guyatt, Ferrie, & Griffith, 1993) and the Asthma Symptoms Diary (Ross et al., 2005). At post treatment, the treatment group evidenced significant decreases in panic frequency, general anxiety, anxiety sensitivity, as well as increases in morning peak-flow expiratory rate and asthma-related quality of life. Anxiety related gains were maintained at 6 months, whereas the pulmonary function gains were not.

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Nonrandomized with Control Group Shemesh et al. (2006) reported on individuals who met PTSD threshold on the Impact Event Scale (IES; Horowitz, Wilner, & Alvarez, 1979) following a myocardial infarction (MI). Original MI diagnoses based on symptoms, electrocardiogram changes and enzymes changes were confirmed by a study cardiologist. All participants received an informational session regarding the importance of following medical advice after an MI. Additionally, a self-selected subset also participated in four to five sessions of CBT focused on their traumatic symptoms. All self-selected participants also met criteria for PTSD on the Structured Clinical Interview for DSM-IV (First, Spitzer, Gibbon, & Williams, 2001). The abbreviated CBT administered in this study was manualized, provided by a psychiatrist and focused on relaxation, exposure and cognitive reprocessing. The psychological measures were the IES, the Posttraumatic Stress Disorder Diagnostic Scale (PDS; Foa, Cashman, Jaycox, & Perry, 1997), the Beck Depression Inventory (BDI; Beck, Ward, Mendelson, Mock, & Erbough, 1967), and the SCID-IV. Participants in the information only group showed significant improvement only in adherence to aspirin treatment. Those in the CBT group exhibited significant improvement in aspirin adherence, several medical risk factors (reduced high blood pressure, smoking and cholesterol) and anxiety symptoms (reduced PDS scores by 57% and IES scores by 22%). Kennedy, Duff, Evans, and Beedie (2003) evaluated inpatients from a rehabilitation unit who had suffered a recent traumatic spinal cord injury (SCI). This group was of particular interest because of their previously reported increased risk for developing psychopathology, particularly anxiety and depression. Anxiety and depression were assessed using the state portion of the State Trait Anxiety Inventory (Spielberger, Gorsuch, Lushene, Vagg, & Jacobs, 1983) and the BDI (Beck et al., 1967). Patients were invited to participate in coping effectiveness training, which was based on Lazarus and Folkman’s cognitive theory of stress and coping (1984) as well as CBT techniques. Sessions were devoted to normalizing stress reactions; assessing typical appraisal and coping techniques; developing appraisal and coping skills; examining the connections and distinctions between thoughts, feelings and behaviors; increasing pleasant activities and relaxation; and challenging negative thoughts. The intervention consisted of seven 60- to 75-minute small group sessions. For analyses, participants were matched with an archival sample of SCI patients. When compared to the control group, the intervention group showed a significant reduction in anxiety and depression symptoms but no improvement in coping strategies as assessed by the COPE (Carver, Scheier, & Weintraub, 1989). Another study among spinal cord injury patients was designed to immunize participants against depression and anxiety (Craig, Hancock, Chang, & Dickson, 1998). Previous work indicates that approximately 30% of individuals with an SCI exhibit elevated levels of depression and anxiety up to two years following the injury (Craig, Hancock, & Dickson, 1994). Participants were

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receiving standardized hospital rehabilitation following an acute spinal cord injury at the time of study enrollment. Depression and anxiety were assessed at pretreatment, post-treatment, 1 year follow-up and 2 year follow-up using the Beck Depression Inventory (Beck et al., 1967) and the trait portion of the State Trait Anxiety Inventory (Spielberger et al., 1983). Treatment consisted of 10 weekly sessions of CBT delivered in a small group format. CBT components included relaxation techniques (progressive muscle relaxation, visualization and self-hypnosis), cognitive restructuring, attentional distraction, pain reinterpretation, education regarding sexuality after an SCI, assertiveness training, social skills training and increased pleasant activities. All participants including the nonrandomized control group were followed for two years. The treatment group did not experience a significant decrease in anxiety or depression. However, more focused analyses examining only those participants with elevated anxiety or depression scores at baseline indicated larger reductions in symptoms for the treatment group.

No Comparison Group Schmidt and Telch (1997) directly examined whether health status and health perception affected participants’ response to CBT for panic disorder. Patients (N = 71) diagnosed with panic disorder through a diagnostic interview (SCIDNP; First et al., 1994) received 12 sessions of CBT over eight weeks. The CBT protocol included four main components: education regarding the etiology and maintenance of panic disorder, cognitive therapy, respiratory control techniques and interoceptive exposure. Medical comorbidity and physical health perceptions were assessed with the General Health Survey. Both were related to poorer outcomes post treatment, though participants’ perceptions proved to be a better indicator of treatment outcome than medical status. Participants were considered to have met PD recovery criteria if they fell within normal range on measures of anxiety and phobic avoidance, and were no longer experiencing panic attacks. Following treatment, 35% of participants who viewed their health as poor met recovery criteria, whereas 71% of those who perceived their health as good met recovery criteria. As noted in the introduction, we generally excluded articles involving treatment of comorbid physical illness and anxiety when the latter was assessed secondarily. Typically, they did not contribute to our understanding of the treatment of Axis I anxiety problems. Yet we briefly summarize a few such studies that highlight some relevant points. Holmberg, Karlberg, Harlacher, Rivano-Fischer, and Magnusson (2006) evaluated the effects of CBT for individuals with phobic postural vertigo (PPV) which is characterized by dizziness, avoidance and anxiety often caused by a vestibular disorder (Holmberg et al., 2006). All study participants received education regarding the disorder and were shown how to perform self-administered vestibular exercises, which they

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were encouraged to perform twice daily for fifteen minutes. Half of the participants also received CBT. Participants in the CBT group reported significantly greater gains on anxiety as measured by the Hospital Anxiety and Depression Scale (Zigmond & Snaith, 1983). This study illustrates the application of CBT in a patient population typically not considered in collaborative health efforts. Psychotherapy also yielded gains when Speca, Carlson, Goodey, and Angen (2000) investigated the effects of a mindfulness meditation-based stress reduction group program on a variety of psychological symptoms among cancer patients. Individuals in the treatment condition exhibited large to medium reductions in anxiety, depression, anger, confusion, and stress subscales of the Profiles of Mood States (McNair, Lorr, & Droppelman, 1971). Yet results were mixed in another severe patient population. Anson and Ponsford (2006) studied CBT’s effectiveness in improving traumatic brain injury patients’ coping strategies and emotional adjustment. PParticipants reported improved competency and understanding of emotional issues and adaptive coping strategies; however, there were no significant changes in depression, anxiety, self-esteem or psychosocial functioning. Together these studies illustrate the issue that less specific anxiety assessment may make it hard to distinguish the clinical significance of any improvements. Suh, Jung, Kim, Park, and Yang (2002) evaluated individuals with end stage renal failure being maintained on hemodialysis, to determine if regular exercise would affect their level of anxiety, depression and quality of life. Participants exhibited a significant improvement in anxiety symptomatology and quality of life but not depression following the exercise program. Exercise is one of several typical components in behavioral health therapy. This study raises the issue that improvements–even in more impaired populations–may accrue from fewer components, shorter durations, or smaller doses. Although much research remains to be conducted, this review provides a promising look at the effects of psychotherapy, particularly CBT, on comorbid physical illness and anxiety. CBT was shown to improve health perceptions, decrease anxiety symptoms, and reduce doctor visits among individuals with panic disorder (Klein et al., 2006; Roy-Byrne et al., 2005; Schmidt et al., 2003). CBT also significantly reduced both medical and anxiety symptoms for asthmatics who had panic disorder (Ross et al., 2005). Patients with PTSD as a result of a myocardial infarction reported both decreased medical risk factors and anxiety symptomatology following CBT (Shemesh et al., 2006). Individuals with comorbid traumatic brain injury and acute stress disorder were less likely to develop PTSD when they received CBT (Bryant et al., 2003). Similarly, a trend toward decreased anxiety symptoms for spinal cord injury and breast cancer patients existed following cognitive therapy, particularly when anxiety was higher at baseline or treatment was delivered by psychologists (Craig et al., 1998; Kissane et al., 2003). While improvements in physical and mental health status have been demonstrated, the potential mechanisms for change are largely unclear. Very few studies investigated the moderating effect of health status on the relationship

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between treatment and anxiety outcome. Schmidt and Telch (1997) reported that poor health perception had a clearly negative impact on response to CBT among panic disorder patients. Roy-Byrne et al. (2005) indicated the medical burden did not affect rate of response to CBT among panic disorder patients but that due to their more severe symptomatology they would require longer treatment duration to be considered remitted. Further investigation into the moderational role of health status on treatment response is warranted to determine what impact it has on the different medical-anxiety illness comorbidities.

Pharmacological Treatment of Physical Illness and Anxiety Medication side effects are a major concern in the pharmacological treatment of comorbid chronic physical illness and anxiety disorders. Psychological benefits must be weighed against the physical tolerability of the psychotropic drugs. Recently, Gothelf et al. (2005) preliminarily investigated the physical and psychological correlates of fluvoxamine treatment in youth cancer patients who also suffered from comorbid depression, anxiety, or both. Gothelf et al. (2005) recruited patients from a pediatric cancer hospital for their open trial study of fluvoxamine tolerability. The diagnosis of psychological disorders was based on recommendations of the American Academy of Pediatrics, and quite thorough. First, healthcare providers specially instructed in the identification of mood disorders identified 74 potential candidates age 7 to 20 years old. The second tier screening asked patients to fill out self-report measures; children aged 7–13 completed the Children’s Depression Inventory (CDI; Kovacs, 1992), and adolescents aged 14–20 completed the BDI. All participants completed the Screen for Child Anxiety Related Emotional Disorders (SCARED; Birmaher et al., 1997). Based on cutoff scores for the CDI (10), BDI (10), and SCARED (15), patients were referred for more comprehensive psychiatric evaluation involving structured clinical interviews of the child, the child’s parents, and the child’s primary nurse. All of the interviews were completed by a psychiatrist specializing in children and adolescents. The psychiatrist used the affective and anxious items of the Schedule for Affective Disorders and Schizophrenia for School-Age Children, Present and Lifetime Version (K-SADS-PL; Shanee, Apter, & Weizman, 1997). For our purposes we will focus on only those diagnosed with anxiety or mixed anxiety and depression. Sixty-three subjects received psychiatric evaluation; of those 9 (14.3%) met DSM-IV criteria for an anxiety disorder, and 8 (12.7%) met criteria for comorbid MDD and an anxiety disorder. Because the K-SADS-PL includes a retrospective report section, the researchers were able to identify two patients who had anxiety disorders prior to their cancer diagnoses. Anxiety disorder diagnoses included generalized anxiety disorder, PTSD, and separation anxiety disorder.

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The nature of each child’s illness and treatment was well documented. Most were inpatients at the start of the study (9 out of 15), most were receiving chemotherapy (14 out of 15), and most had a poor prognosis, which was defined as a less than 30% chance of survival. Patients did not alter the other medications they were receiving during the trial. The safety, tolerability, and benefits of fluvoxamine were assessed using biological assays, self-report measures, and clinician ratings. Measures were taken at baseline, four weeks, and eight weeks. Blood levels of liver enzymes, blood urea nitrogen, and creatinine were taken to assess organ response to fluvoxamine. Patients completed the Children’s Depression Rating ScaleRevised (CDRS-R; Pozananski & Mokros, 1995) and the Pediatric Anxiety Rating Scale (PARS; Research Unit on Pediatric Psychopharmacology Anxiety Study Group, 2001). Additionally, the child and adolescent psychiatrist rated Clinical Global Impressions (CGI; National Institute of Mental Health, 1985) of severity at baseline and improvement at four and eight weeks. Response to treatment for individuals with anxiety disorders was assessed by PARS scores changes. Four out of five patients diagnosed with an anxiety disorder showed over 50% improvement in total PARS scores. Decreases in the scores were significant at four weeks, but there was no further decrease by eight weeks. Moreover, none of the patients experienced adverse physical consequences. While three patients reported fleeting side effects including abdominal pain and dry mouth, none of them were lasting or required dose reduction. The Gothelf et al. (2005) study provided preliminary evidence that anxiety disorders can be safely treated with psychotropic medications in children with chronic physical illnesses. The thorough assessments of anxiety psychopathology as well as physical condition were particular strengths. However, as a preliminary investigation there was no placebo control group with which to compare results. Moreover, patients were only receiving active treatment for eight weeks. The long-term effects of fluvoxamine on children with cancer could not be determined. In addition to the safety of using psychotropic medications in severely ill populations, another consideration when treating individuals with comorbid physical illness and anxiety disorders is whether the medical illness adversely affects responses to treatment. The CCAP conducted by Roy-Byrne et al. (2005) and mentioned in the previous section was a randomized effectiveness trial investigating responses to combined CBT and medication treatment versus medication alone. One goal was to investigate treatment collaborations by community behavioral health specialists and primary care physicians. Consequently, the specific pharmacological intervention was less restricted than other studies reviewed in this chapter. The physicians were given a one-hour didactic about recognizing panic disorder in their patients, as well as information about options and delivery of psychotropic medication. In both groups, the intervention consisted of six weeks of SSRIs with dose titration. However, if a participant had already had two unsuccessful trials of treatment with SSRIs, other

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medications including benzodiazepines and tricyclic antidepressants were tried first. The results suggest combined CBT and pharmacotherapy is most effective. In addition, both high and low physical illness groups had comparable response rates at the end of treatment. However, at follow-up the high physical illness participants experienced more symptoms than their low counterparts. This study suggests physical illness comorbidity does not necessarily affect responses to pharmacological interventions, though it may impact duration. Collaboration between care-givers in medical and psychological fields is in the best interest of patients. Irritable bowel syndrome (IBS) is a medical condition that causes significant abdominal pain, discomfort, and bowel irregularities. In addition, IBS is frequently comorbid with anxiety disorders. Studies have shown that 37% to 41.9% of individuals with anxiety disorders have comorbid IBS, as compared to only 2.5% to 11% of age and sex-matched controls (Noyes, Cook, Garvey, & Summers, 1990; Tollefson, Tollefson, Pederson, Luxenberg, & Dunsmore, 1991). Moreover, researchers have found that the serotonin pathways implicated in IBS are the same as those acted upon by SSRIs (Read & Gwee, 1994). There is significant data supporting the treatment of IBS using SSRIs. Clouse, Lustman, Geisman, and Alpers (1994) found that 89% of individuals with IBS treated with antidepressants reported improvement and 61% reported complete remission. Because of the evidence for shared etiology, high rates of comorbidity, and treatment of IBS using SSRIs, Masand et al. (2002) conducted an open-trial to investigate whether outcomes from treating IBS with paroxetine were different in individuals with versus individuals without a comorbid anxiety disorder. In the Masand et al. (2002) open label study, 10 IBS patients with a history of an anxiety disorder and 10 IBS patients without it were compared. Anxiety disorders were assessed at baseline by clinician-administered SCID, an empirically supported structured interview. The diagnoses included specific phobia, panic disorder without agoraphobia, panic disorder with agoraphobia, social anxiety disorder, and PTSD. Three patients had comorbid psychological disorders including major depressive disorder, dysthymia, and adjustment disorder. IBS was diagnosed using the Rome I criteria, which is the medical profession standard. In addition, patients underwent physical testing to confirm the diagnosis as well as to rule out other conditions. The examination included a blood count, blood chemistry test, fecal occult blood tests, and a flexible sigmoidoscopy. Both the physical and anxiety conditions were determined using structured interview criteria. However, the IBS diagnosis also benefited from additional objective symptom measurement. The intervention consisted of 12 weeks of a 20 mg/day dose of paroxetine. If patients showed a partial response after 4 weeks, their dose was increased to 40 mg/day. The average dose received overall was 31 mg/day. One of the strengths of this study was the use of an interactive telephone interviewing system for daily monitoring of symptoms. Patients provided self-ratings over the phone for the Hamilton Rating Scale for Depression (Hamilton, 1967), the

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CGI (National Institutes of Mental Health, 1985), and specific symptoms of IBS including the frequency and severity of abdominal pain, constipation, diarrhea, incomplete emptying, and bloating. In general, both groups responded well to paroxetine. Symptoms decreased in frequency and severity across the domains of IBS physical symptoms. Individuals with anxiety disorders experienced somewhat greater alleviation of symptoms than the group without anxiety, however the differences were not statistically significant. For example, the criteria for full remission, greater than 70% improvement of symptoms, was met by 7 of 10 patients with anxiety disorders as opposed to 2 of 10 patients without anxiety disorders (p=.07). While the small number of participants limited the power of analyses, these tentative findings suggested a fairly dramatic difference across comorbidity groups. This potentially underscores a significant relationship between anxiety disorders and IBS, perhaps suggesting not only shared etiology, but that IBS can sometimes be a physical symptom of anxiety. On the other hand, several researchers have demonstrated that in the absence of anxiety conditions, SSRIs are still relatively effective in treating IBS (Creed et al., 2003; Creed et al., 2005; Masand et al., 2002). In an initial effectiveness study, Creed and colleagues (2003) compared psychotherapy, antidepressants, and routine gastroenterologist care for patients with severe IBS. They found patients with severe IBS responded significantly better to either psychotherapy or pharmacotherapy. In a follow-up study designed to target anxiety, Creed et al. (2005) compared responses of severe IBS patients with and without psychological comorbidity on psychodynamic interpersonal therapy, paroxetine, or routine IBS care from a gastroenterologist and a general practitioner. Anxiety disorders were diagnosed using the Schedules for Clinical Assessment in Neuropsychiatry (SCAN; World Health Organization, 1994), a clinical interview that was administered by a psychiatrist. In general, patients in both treatment groups experienced significant improvement in their IBS symptoms; whereas, those in the treatment as usual condition did not. For those in the active treatment conditions, there were no differences between patients with and without psychological comorbidity in improvements in physical symptoms. Despite a moderate correlation between improvement in physical symptoms and improvement in psychological symptoms, the researchers concluded that the health-related outcomes in IBS resulting from paroxetine or psychotherapy were better accounted for by factors beyond just improvements in psychological functioning. Similar to IBS, serotonin is believed to play a role in migraine disorders. 5-HT agonists have been found to be effective in reducing the occurrence of migraines, called migraine prophylaxis (Pascual & Berciano, 1991). In order to investigate the primary prophylactic effects of buspirone, Lee, Park, and Kim (2005) conducted a randomized, double-blind, placebo-controlled study. Seventy-four individuals were diagnosed with both GAD and migraine disorder. Anxiety disorders were diagnosed according to the Diagnostic and Statistical Manual, fourth edition (DSM-IV) criteria for GAD, in combination with a

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score of 18 or more on the Hamilton Anxiety Rating Scale (HAM-A; Hamilton, 1967), however there are several concerns about assessment adequacy. It was not clear whether structured clinical interviews were used to diagnose anxiety disorders. In addition, there was little rationale for the exclusion and differential diagnosis of anxiety disorders other than GAD. According to the DSM-IV, GAD frequently co-occurs with not only stress conditions including IBS and migraine disorder, but also with other anxiety disorders including panic disorder, social phobia, and specific phobia. The effective assessment of GAD requires a thorough process of differential diagnoses, which was not mentioned in this study. Migraine disorder without aura was diagnosed according to the criteria of the International Headache Society (IHS; Headache Classification Subcommittee of the International Headache Society, 2004). Patients were screened using the Migraine Disability Assessment Score (MIDAS; Stewart, Lipton, Kolodner, Liberman, & Sawyer, 1999) and completed several self-report measures including the Headache Self-Efficacy Scale (HMSE; Martin, Holroyd, & Rokicki, 1993) and the Headache Disability Inventory (HDI; Jacobson, Ramadan, Aggarwal, & Newman, 1994). Additionally, patients kept a diary in which they recorded headache frequency and intensity during the two-week baseline period and six weeks of treatment. These two variables were used to calculate the headache index (HI) every two weeks. When patients came to the lab biweekly, they also filled out the HAM-A and the headache self-report measures. The buspirone group showed a significant decrease in headache frequency after the six weeks of treatment and at three-month follow up (of 26 patients). Headache intensity and scores on the HDI did not differ between the two groups. HAM-A scores in the buspirone condition were significantly lower than the placebo group. The researchers also considered the emotional component of the HDI, which was significantly reduced in the buspirone condition. Bivariate correlation analysis showed no significant correlation between HI reduction and HAM-A improvement. The researchers (Lee et al., 2005) suggested these results were indicative of the specificity of buspirone effects on the frequency of migraines and this effect was independent, not secondary to, the anxiolytic effects of the drug. Lee et al. (2005) investigated the usefulness of a psychotropic medication on a physical illness and mental disorder with purported similar neurological substrates that appear to contribute to the expression and severity of one another. While it was impossible in this study to clearly separate the anxiolytic effects of buspirone from the prophylactic effects on migraine, it suggests psychotropic treatment may be useful not only because it limits the exacerbation of physical illness by anxiety, but also because psychotropic drugs can directly affect aspects of the physical illness. In sum, this limited literature suggests pharmacological treatments for anxiety disorders can be safe and effective in individuals with even severe comorbid physical illnesses (Gothelf et al., 2005; Roy-Burne et al., 2005). In some cases,

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specifically, IBS and Migraine disorder, pharmacological treatments for anxiety disorders not only alleviate symptoms of anxiety, but also have an additional and potentially separate effect on physical symptoms of comorbid conditions (Lee et al., 2005). It has been speculated that these dual effects may occur because both the physical illness and the anxiety disorder share the same biological substrates.

Future Directions Given the limited research in this area, our conclusions must certainly be tempered. Much research remains to be conducted to fully examine the treatment implications of the various comorbidities between medical illnesses and the anxiety disorders. However, it appears that we can make some preliminary statements about the treatment of patients presenting with both physical illnesses and anxiety. First, people with a wide range of physical illnesses (cardiopulmonary, brain injury, cancer) that are treated for their anxiety problems appear to benefit from empirically supported treatments like CBT or certain classes of psychotropic medications. Moreover, these patients appear to benefit in terms of their anxiety and to an extent, their physical health as well. Some limited data hint that this physical improvement may occur directly (i.e., as a result of the intervention) as well as indirectly (i.e., through changes in anxiety symptoms). Although some data suggest that comorbid patients may not benefit quite as much as those without physical illness, these patients do show some gains. Unfortunately, there are few studies or even speculation about how to handle comorbid patients differently to improve responsiveness. One idea is to simply provide them with more treatment, though ‘‘dose response’’ studies in the anxiety literature are not clear that more is always better. We would suggest that clinicians consider incorporating interventions within existing CBT protocols that are specific to the comorbid physical illness. For example, treating asthmatics with panic disorder could involve specific discussions of the respiratory physiology of asthma and how anxiety affects asthma symptoms, specialized interoceptive techniques designed to assess and tease apart asthma and panic symptoms, and evaluation and discussion of potential medical safety aids such as carrying inhalers. Stanley et al. (2005) created such a protocol by designing CBT-RADAR, an integrated cognitive behavioral treatment for reducing anxiety and depression among patients with Chronic Obstructive Pulmonary Disease (COPD). They noted that differential assessment and treatment is complicated by symptom overlap between medical and mental health symptoms, such as shortness of breath, chest pain, weakness, sleep disturbance, decreased energy, fatigue,. As a result, they integrated two intervention models with documented efficacy and potential utility for medical patients. The first model is CBT-GAD/PC: an approach targeting treatment of generalized anxiety in later life consisting of education/awareness,

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relaxation training, cognitive therapy, problem-solving skills training, and sleep management skills. The second is CBT-BA: the creation of a behavioral activity hierarchy to both increase pleasure (a key component in treating depression) and provide exposure to anxiety producing situations. Treatment involves eight (onehour) weekly group sessions, and includes discussion relevant to how managing anxiety, depression, and somatic symptoms may interrelate, complementing or conflicting. For example, starting an exercise program may increase shortness of breath thereby increasing anxiety in the short term but decreasing it in the long run as interoceptive fears diminish. Exercise may also increase physical fatigue in the short run but decrease fatigue over the long term due to lessened depression and improved cardiopulmonary functioning. Though efficacy trials for these interventions are ongoing, they appear to be very promising.

Future Methodological Considerations One method of considering these studies is to put them into the context of what might be considered ideal designs for the evaluation of treatment outcome in comorbid physical illnesses and anxiety. The first criterion that should be considered involves standardized, clinical assessments of both conditions. An ideal study should have comprehensive medical determination of illness conducted by physicians. Many of the studies reviewed relied on patient self-reports of physical illness. Although there are data suggesting that people can validly report physical conditions, medical evaluation should be considered the gold standard for future work. Similarly, the assessment of anxiety psychopathology should be determined by a structured diagnostic interview and conducted by trained clinicians. It may be fruitful to simply assess anxiety symptoms, as was done in a number of the reports reviewed. Certainly self-report assessments of symptoms can complement diagnostic assessments. However, the evaluation of clinical syndromes is compelling not only in terms of public health significance, but because Axis I conditions may yield different treatment results if they are discontinuous from subclinical or nonclinical expressions of anxiety (Kotov, Schmidt, Lerew, Joiner, & Ialongo, 2005; Schmidt et al., 2007). Moreover, the symptom overlap between certain physical illnesses and anxiety problems is considerable. These comprehensive assessments are needed to ensure accuracy of differential diagnoses (i.e., between physical and psychiatric diagnoses). In addition, standardized medical and psychiatric interviews should be repeated at posttreatment and follow-up. This will allow researchers to ascertain whether the intervention yielded any changes in terms of the medical as well as the psychiatric problems. In this review, very few reports implemented this standard. A second criterion needed for clarification of the effects of comorbidity on outcomes involves the implementation of standardized, empirically supported treatments. In this regard, our review suggests that the literature has done a fairly good job of utilizing empirically supported treatments. However,

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these studies have largely focused on treatments aimed at the psychiatric condition. As we noted in the introduction, very few studies using empirically supported medical treatments that are designed to intervene on a physical illness appear to be concerned with the co-occurrence of Axis I anxiety psychopathology. This is certainly a fertile ground for future work. The final consideration is analytic. We suggest that researchers should consider: (1) treatment effects on both physical illness and anxiety, (2) moderator effects, and (3) mediator effects. Our review found that often studies failed to measure changes in both physical illness and anxiety domains, which is certainly unfortunate since changes in both arenas are of considerable interest. A few studies assessed for moderator effects, for example, whether having a certain physical illness influenced how anxious patients responded to the treatment. Evaluation of such effects is very important for the identification of individuals who may not respond well to standard treatment protocols. Mediator effects are useful in determining whether changes in one domain (e.g., anxiety) are responsible for changes in the other domain (e.g., physical illness). Such analyses have been conducted in only a small minority of the studies evaluated but could be very important in beginning to identify mechanisms that are critical to change among patients with comorbidity. We hope that this review will inspire additional work in this area. Despite highly efficacious treatments for anxiety, there is room for improvement and there are some suggestions that patients respond less optimally because of comorbid physical illnesses. In sum, much can be done to improve our understanding of the interplay between physical illnesses and anxiety and how this impacts treatment interventions.

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Index

Acute exercise, effects on anxiety, 88–89 Acute pain, in PTSD patients, 213, 214 ADIS, see Anxiety disorders interview schedule (ADIS) Adolescent anxiety and puberty anxiety problems, 155 future perspectives, 167, 168 puberty operationalization and assessment, 156–160 researches, 166, 167 See also Puberty, role in adolescent anxiety: theory and evidence Adolescents asthma with, anxiety in, 241, 247 relation between, 242–246 HIV-infected, sexual activity among, 324 Adrenal hormones, in puberty, 158 A2 and 1adrenergic agonist, treatment of anxiety and sleep-related problems, 114 Adulthood, with asthma symptoms, obesity in, 239 Adults asthma and anxiety in, 247, 259 relation between, 248–258 Agoraphobia, 139, 140 as complication of panic disorder, 5 diagnostic criteria for, 4 panic disorder and anxiety disorder with, DSM-IV for diagnosis of, 61 AIDS, casualties since beginning, 318 Alcoholics Anonymous (AA), group-based treatment modality, 45 Alcohol-induced anxiety, 34 Alcohol use, 317 among asthma patients, 259 anxiety and other health behaviors, 41 cognitively-mediated tension reduction effect of, 38

disorders involving, 35 effects of pharmacological treatment for1 anxiety on, 45 among HIV patients, prevalence of, 328 psychological effects of, 35 symptoms of alcohol use disorders, 37 Allergic asthma, 239 Amnesia, 350 Anaerobic exercise, effects of, 96 Anal intercourse, 323, 324 Angina development of, 283 microvascular, 290 Anhedonic depressive symptoms, 69 Anti-basal ganglia antibodies (ABGA), 142 Antiretroviral therapy (ART) goal of, 327 side effects of, 326 viral replication, suppression of, 327 Anxiety in asthma cognitive behavioral model, 269 cognitive behavioral treatment, 268–270 in asthmatic adults, see Asthma and anxiety in asthmatic children/adolescents, see Asthma and anxiety and CHD, see Coronary heart disease (CHD), and anxiety and depression in cardiac events, effects of, 285 in CHD, comorbidity of, 294 comorbidity of, 280 as predictive of hypertension, 297 STAI and BDI for, 352, 353 and HIV, see HIV (Human immunodeficiency virus), and anxiety

367

368 Anxiety (cont.) and hostility, as predictive of atherosclerotic disease, 297 and its disorders in asthma, see Asthma and anxiety disorders in NCCP patients, 289–291 and physical illness, see Physical illness and anxiety and risk for HIV infection or transmission, 322–326 role in CHD, 292 role in HIV, 332 See also HIV (Human immunodeficiency virus), and anxiety and sleep disorder, primary classification for diagnosis, 106 Anxiety and insomnia criteria for support different disorders, 109 single-spectrum disorder, 108 third factor models, 109–110 evidence supports to models age of onset, 110–111 course, 112–113 gender distribution, 111 neuroanatomy and pharmacology, 113–117 symptoms and sleep EEG, 111–112 Anxiety and menstrual cycle disorders anxiety sensitivity, 189, 190 assessment measures, 184, 185 and biological factors, 193 health behaviors, 196, 197 premenstrual exacerbation and comorbidity, 185, 186 premenstrual symptoms and disorders, 182, 183, 190–192 researches on, 197–199 retrospective and prospective studies, 183 treatments and therapies, 194–196 Anxiety and physical illness link, method of assessment generalized anxiety disorder (GAD), 141–142 obsessive-compulsive disorder (OCD), 142–143 panic disorder (PD), 136–140 posttraumatic stress disorder (PTSD), 132–136 social anxiety disorder, 143–144 specific or simple phobia, 144–145 See also Physical illness and anxiety

Index Anxiety disorders alcohol role in development of, 37 and alcohol use disorders, odds ratios (ORs) to quantify relationship between, 31 and alcohol use, etiological theories of relationship between, 29 anxiety symptoms and increased vulnerability of developing, 35 in CHD patients, prevalence of, 281, 282, 287–289 and chronic pain assessment methods, 223–225 associations, 215–217 course of, 214, 215 issues and researches on treatment, 227–229 physiological arousal, 220–222 prevalence of, 209–214 treatment and therapies, 225–227 comorbid anxiety, 329 in context of mood disorder, 64 diagnosis of, 42 exercise role in, 81 GAD, prevalence of, 321 HADS anxiety score, 327 health anxiety and sexual behavior, 324–325 and health behaviors, link between, 131 and HIV infection risks, 322–326 in HIV patients, prevalence of, 319, 332 generalized anxiety disorder (GAD), 321 MSM and anxiety disorder, 321 panic disorder (PD), 321 PTSD, 320–321 women, anxiety disorders in, 322 illicit drug use comorbidity, 71 panic disorder, prevalence of, 321 pathophysiology of stress hormones in, 330–331 and physical illness comorbidity, 129 treatment of, see Physical illness and anxiety in prediction of development of alcohol dependence, 34 prevalence and impact among asthmatic patients, 241 prevalence in HIVþ individuals, 319 HIVþ MSM, 320–322 programmatic research in, importance of, 331–333

Index PTSD, 324 prevalence rates of, 320–321 relationship between anxiety and alcohol, 31 relationships with illicit drug use, 58 screening measures, 319 semi-structured interviews, 223, 224 social anxiety, 323–324 specific rates of co-occurrence for, 8 stress hormones, dysregulation of, 331 symptomatic and syndromal levels of enquiry in, 29–31 temporal order of, 64 tobacco use on, 3 trait anxiety, 323 treatment outcome and relapse in, 43 Anxiety disorders and specific illnesses, 129 observed relationships, explanations for direct and indirect causal relationship, 130 shared risk factors, 131 Anxiety disorders interview schedule (ADIS), 293 for DSM-IV, 351 Anxiety management, in asthma treatment, 269 Anxiety neurosis, 286 atherosclerosis among, 296 Anxiety-premenstrual cycle phase interaction models, 192–194 Anxiety psychopathology assessment of, 361 and physical illness, 341, 346 studies on, 342–345 treatment of, 346–348 Anxiety-related HIV sexual risk, mechanisms of, 325 Anxiety sensitivity (AS), 40, 67 and adolescent anxiety, 171 in asthma-anxiety association, 264–265 in chronic musculoskeletal pain and PTSD patients, 218, 219 in premenstrual disorder, 189–190 treatment for heroin users, 72 Anxiety symptoms, 131–132 Anxiolysis, 116 Arrhythmias anxiety in, examination of, 285 occurrence of, 297 ventricular anxiety in, 295 susceptibility to, 299 Aspirin treatment, for improved PTSD, 352

369 Asthma, 341 adults with, anxiety in, see Asthma and anxiety anxiety-asthma relation, specificity of, 265–266 and anxiety disorders, 237 prevalence and impact of, 241 anxiety in, CBT for, 268–270 anxiety vulnerabilities on, 264–265 Atopy syndrome in, 240 bronchoconstriction, 262, 264, 266 children/adolescents with anxiety in, see Asthma and anxiety classification, 238 dysfunctional beliefs, 267–268 and mental health, 240–241 non-psychological risk factors for, 239–240 occurrence and symptoms, 237, 238 and panic differentiation in asthma treatment, 269 panic disorder in, specificity of, 260–261 P-F levels in, 264 and psychopathology, relation between, 259 related QoL, effect of anxiety on, 263 self management, in asthma treatment, 269 symptom severity, and anxiety, 262–263 Asthma and anxiety in adults, 247, 259 outcomes of various studies, 259 relation between, 248–258 in children/adolescents, 241, 247 relation between, 242–246 cognitive-behavioral model of cooccurrence of, 266–268, 269 extant research, 270–271 limitations, and future directions, 271–272 Asthma Symptom Checklist (ASC), 260, 264 Astrand-Ryhming ergometer test, 83 Atherosclerosis in anxiety-CHD association, 296–297 anxiety for progression of, 295 cause of, 281 inflammatory cytokines in, role of, 301 product of, 280 risk factors of, 297 Atopy syndrome, in asthma, 240 Autonomic nervous system (ANS) dysregulation, in PTSD and chronic pain, 221, 222

370 Average sleep duration, 118 Axis I anxiety disorder in NCCP, 291 Beck Anxiety Inventory (BAI), 40 Beck depression inventory (BDI), for depression and anxiety, 352, 353 Benzodiazepines, 347, 357 efficacy of, 93 Blood pressure changes, as symptom of partial seizures, 138 elevated, in pain and anxiety, 220 high as cardiovascular risk factor, 133, 282 endothelial damage in atherosclerosis due to, 281 as factor contributing to atherosclerosis, 296 influence of CBT over, 352 in panic disorder patients, 136, 300 Brain injury, 354, 360 Breast cancer, 354 CEGT for, 350 Breathing, diaphragmatic, 351 Bronchitis, chronic, 240 Buspirone, effects on migraine disorder, 358, 359 CAD, see Coronary artery disease (CAD) Cancer, 360 breast, 354 CEGT for, 350 in youth, fluvoxamine for treatment of, 355 Cardiac anxiety, in NCCP, 289 Cardiac death, and anxiety, association between, 284 Cardiac function, altered, in anxiety-CHD association, 297–300 Cardiac morbidity, negative impact of depression on, 302 Cardiorespiratory disorders, 341 Cardiovascular disease (CVD) and anxiety, 279 future directions, 303–305 increased risk for CHD, 281–287 See also Coronary heart disease (CHD), and anxiety past studies on, caveats in interpretation of, 291 conceptualizations of anxiety, 292–293 construct definition overlap, 293–294 directionality, 294

Index patients with NCCP, anxiety in, 289–291 terminology and background in, 280–281 Causal risk factor, and puberty, 159 CBT, see Cognitive behavioral therapy (CBT)/ Cognitive-behavioral treatment (CBT) CCAP study, see Collaborative care for anxiety and panic study (CCAP), for effectiveness of CBT CD4þ cell and HIV infection, 318 CDI, see Children’s Depression Inventory CEGT, see Cognitive-existential group psychotherapy (CEGT) Central nervous system (CNS), hyperexcitability of, 35 Central neurotransmitter function, 92 CHD, see Coronary heart disease (CHD) Chest pain (CP), 279 non-cardiac (NCCP), anxiety in patients with, 289–291 Childhood sexual abuse among IDUs, rates of, 328 and PTSD, prevalence of, 325 Children, with asthma and anxiety disorder, relations between, 241, 242–246, 247 Children’s Depression Inventory, 355 Chronic insomniacs, 117 Chronic musculoskeletal pain and anxiety disorders, 208–212 exposure therapy and graded activities, 226, 227 Chronic obstructive pulmonary disease (COPD), 137, 138, 341, 360 patients with anxiety and depression, CBT for, 360 Chronic Pain Coping Inventory (CPCI), in anxiety disorder assessment, 225 Chronic pain, in PTSD patients, 213, 214 Cigarette smoke, 281 See also Smoking Clinical anxiety, exercise training programs for, 89–92 Clinical Global Index, 45 Cognitive behavioral therapy (CBT), 136 for anxiety, 346 anxiety disorder and pain treatment, 225 for depression, efficacy of, 333 for improved QoL among individuals with asthma, 270 for PMS treatment, 195, 196

Index randomized trials for anxiety disorders in HIV patients, 330 to improve anxiety and problematic drinking symptoms in comorbid patients, 45 Cognitive-behavioral treatment (CBT) for anxiety disorders, 346, 347 in HIV patients, 330 of anxiety in asthma, 268–279 CBT-RADAR for reducing anxiety and depression among COPD patients, 360 CCAP for effectiveness of, 348 for depression in HIV, 333 for depression in smokers, 18 for GAD and primary insomnia, 120 for obsessive compulsive disorder, 92 for panic disorder, 349 for panic disorder target anxiety sensitivity, 90 for PPV and panic disorder, 353 for PTSD, 350 for substance dependence, 72 Cognitive-existential group psychotherapy (CEGT), 350 for women with breast cancer, 350 Cognitive refocusing and self-efficacy, 94 Cognitive strategies in anxiety, and pain treatment, 226 Collaborative care for anxiety and panic study (CCAP), for effectiveness of CBT, 348 Concurrent treatment of PTSD and cocaine dependence (CTPCD), 72 Confidence interval (CI), 239 Congenital analgesia, 208 Conjunctivitis, allergic, 240 COPD, see Chronic obstructive pulmonary disease (COPD) Coronary artery disease (CAD), 137, 280 pathophysiology of, 301 patients with PD morbidity and mortality among, 298 myocardial perfusion defects in, 300 prevalence of, 288 Coronary heart disease (CHD) family history of, 290 morbidity predictive of, 291 weighty influence on, 293 occurrence of, 294 patients with, prevalence of anxiety disorders in, 287–289

371 psychosocial influences on, 279 risk factors in, 281 NCCP patients, 291 ventricular arrhythmia, 299–300 Coronary heart disease (CHD), and anxiety association between, potential mechanisms in altered cardiac function in, 297–300 atherosclerosis in, 296–297 health-compromising behaviors in, 295–296 pathophysiological mechanisms of, 300–302 increased risk for, 281 epidemiological studies on, 282–284 studies in psychiatric samples, 286–287 studies in samples with known CHD, 284–285 pathophysiological mechanisms of, 300–302 therapeutic approach for targeting of, 302–303 Corticotrophin releasing factor (CRF), 67 Cortisol dysregulation of, 331 role in HIV, 331 Dehydroepiandrosterone (DHEA), 158, 188 Depression in asthma, prevalence of, 237 on cardiac morbidity, negative impact of, 302 in HIV, CBT for, 333 sertraline for, 303 severity of, 327 Depression and anxiety in cardiac events, effects of, 285 in CHD, comorbidity of, 294 comorbidity of, 280 as predictive of hypertension, 297 STAI and BDI for, 352, 353 Depressive disorders, in CHD, rate of, 287 Dermatophystosis, 110 Diabetes mellitus, 281, 288, 290, 304 Diabetes, type, 2, 110 Drugs properties of drowsiness and sedation, 116 use in diagnoses, 56 Z, for reducing anxiety, 116 DSM-IV (Diagnostic and Statistical Manual of Mental Disorders, fourth edition)

372 DSM-IV (cont.) ADIS for, 351 anxiety disorder of PD with agoraphobia, 61 anxiety disorders, 59, 60, 85 as classification system for diagnosis of anxiety and sleep disorders, 106, 116 criteria for GAD, 120, 358, 359 diagnosis of alcohol abuse or dependence according to, 30 diagnosis of PTSD, 132, 135, 322 diagnostic criteria for CHD, 304 for disorder classification, 59 on illicit drugs, 55, 56 inclusion of PMDD in, 182 for PD, 286, 348 structured clinical interview (SCI) for, 352 symptoms of a panic attack listed in, 136 Dysthymia, asthma with, 259 Early Adulthood Research Project (EARP), 62 Eczema, 240 EEG-assessed sleep, 117 Emotional stress, measures of, 326 Emphysema, 240 Enhancing Recovering in Coronary Heart Disease (ENRICHD), 303 Epidemiological Catchment Area (ECA), 56 Epilepsy, 138 Exercise anxiolysis, mechanisms of, 92 Exercise interventions, parameters of, 89 Exposure therapy in PTSD and pain treatment, 226, 227 Fluvoxamine safety and benefits of, 356 in youth cancer, treatment of, 355 Follicle stimulating hormone (FSH) in puberty, 158 Forced expiratory volume in 1 second (FEV1), 238 Framingham heart study of anxiety-CHD link, 283 GABAergic-benzodiazepine-chloride (GBC), 115 GABAergic systems, for biological functions, 114, 115 GAD, see Generalized anxiety disorder (GAD)

Index Generalized anxiety disorder (GAD) assessment of, 359 with asthma diagnoses of, 247 presence of, 259 cardiovascular and gastrointestinal disease, 141 diagnostic criteria for, 327 endocrine/metabolic/autoimmune disease, 141–142 in HIV, prevalence of, 321 in menstrual cycle, 185, 191, 192 NE reactivity in patients with, 331 obsessive-compulsive disorder (OCD), 142–143 in pain patients, 209–212 in risk of CHD, presence of, 291 Group A -Hemolytic Streptococcus (GABHS), 142, 143 HAART, see Highly active antiretroviral therapy (HAART) HADS, see Hospital anxiety and depression scale Headache index (HI), 359 Headaches, migraine, 341 Health behaviors, and HIV and anxiety, 327–329 Health-compromising behaviors in anxiety-CHD association, 295–296 spectrum of, 305 Health Professionals Follow-up Study of anxiety-CHD link, 283 Health-related quality of life (HRQOL), and HIV and anxiety, 329–330 Heart attacks, PTSD symptoms as risk of, 283 Heart deaths, 286 Heart disease, anxiety in, 292 Heart-focused anxiety, in NCCP, 289 Heart problems, psychological factors in, 279 Heart-rate variability (HRV), reduced, in anxiety disorder, 298 Highly active antiretroviral therapy (HAART) anxiety and substance use, 328 autonomic nervous system activity response to, 331 health-related quality of life (HQOL), 329 and HIV survival, 319, 329 Histamine, role in asthma, 262 HIV (Human immunodeficiency virus) and anxiety, 317

Index disease management, 326 disorder specific anxiety symptoms, impact of, 327–328 future research in, 331–333 health and disease outcomes in, direct and mediated relationships between, 332 and health behaviors, 327–329 and HRQOL, 329–330 management of, 326 medication adherence in, 327–328 overview of, 318–319 prevention, comorbid psychosocial issues in, 332 prevention interventions, traditional, 332 psychosocial and behavioral factors, 326 risk of infection or transmission, 322–326 and self-reported adherence, relationship between, 326 stress hormones in, pathophysiology of, 330–331 substance use and disease progression, 328 anxiety disorders in HIV patients, prevalence of, 319–322 See also Anxiety disorders in HIV patients, prevalence of association with heterosexual sex, 320 CD4þ cell decline in, 318 clinical presentation of, 318 disease management, 326 and GAD, 321 infection risks, role of anxiety in emotional stress, 326 PTSD, 324 social anxiety, 323–324 trait anxiety, 323 and panic disorder (PD), 321 programmatic research in, importance of, 331–333 and PTSD, 320 retrovirus, 318 screening measures, 319 sexual risk behavior abuse history associated with, 325 anxiety, 323 stress hormones in, 330–331 HIVþ MSM and anxiety disorders, 321–322 HIV wasting syndrome, 318 Hospital anxiety and depression scale

373 HADS anxiety score, 327 HIV screening measures, 319 Hospital anxiety and depression scale (HADS), for anxiety disorders in HIV patients, 319 Hostility, 279, 325 HPA systems, see Hypothalamic pituitary adrenocortical systems, dysregulation of HRQOL, see Health-related quality of life (HRQOL), and HIV and anxiety 5-Hydroxyindoleacetic acid (5-HIAA), 170 5-Hydroxytryptamine (5-HT), 301 Hypercholesterolemia, 110, 281, 288, 304 Hypertension, 281, 288, 290, 304, 341 anxiety and depression as predictive of prescription treatment in normotensive individuals, 297 Hypothalamic pituitary adrenocortical systems, dysregulation of, 331 Hypothalamic pituitary axis (HPA), 188 in depression, dysregulation of, 301 IBS, see Irritable bowel syndrome (IBS) ICD-10 (International Classification of Diseases, tenth edition), as classification system for diagnosis of anxiety and sleep disorders, 106 IDUs, see Injection drug users (IDUs), childhood sexual abuse among, rates of IgE role in asthma, 238 IHD, see Ischemic heart disease (IHD), chronic Illicit drugs categories of, 56 in context of mood disorder, 64 factors associated with vulnerability for, 69 lifetime prevalence rates of, 60 reinforcing effects of, 66 relationships with specific anxiety disorders, 59 temporal order of, 64 usage relationships with anxiety disorders, 58 Imagery exposure, problem solving, and relapse prevention in asthma treatment, 269 Immune system response, HIV infection, 318 Immunoglobulin E (IgE), mediated asthma, 238 Injection drug users (IDUs), childhood sexual abuse among, rates of, 328

374 Insomnia age of onset for, 111 risk factor, gender distribution, 111 with secondary anxiety, 112–113 Intercourse, anal, 323, 324 Irritable bowel syndrome (IBS), 139, 140 and asthma, individuals with, 261 SSRIs for treatment of, 357, 358 Ischemic heart disease (IHD), chronic, 280 Kaposi’s Sarcoma, 318 Kindling-stress hypothesis, 35 Late Luteal Phase Dysphoric Disorder (LLPDD), 182, 183 biological factors, 193, 194 biopsychosocial factors, 194 Leutinizing hormone (LH), in puberty, 158 Locus ceruleus (LC), 114 Lung functioning assessment, in asthma, 238 Lymphoma, 318 Major depressive disorder (MDD) with asthma, presence of, 259 comorbidity of, 293 in HIV, prevalence of, 321 for psychiatric comorbidity, 296 MAOIs, see Monoamine oxidase inhibitors (MAOIs) Marijuana withdrawal symptoms, 68 MDD, see Major depressive disorder (MDD) Medical illness, burden of, 349 Medical utilization, 341 Medication adherence, 326 in HIV, anxiety and, 327 Menstrual cycle and anxiety disorders, 181 anxiety sensitivity, 189, 190 assessment measures, 184, 185 biological factors, 193 biopsychosocial factors, 194 health behaviors, 196, 197 premenstrual exacerbation and comorbidity, 185, 186 premenstrual symptoms and disorders, 182, 183 researches on, 197–199 retrospective and prospective assessments, 183 treatments and therapies, 194–196 Menstrual distress and health behaviors, 196, 197 Menstrual reactivity hypothesis, 190 Mental disorders, DSM for, 30

Index See also DSM-IV (Diagnostic and Statistical Manual of Mental Disorders, fourth edition) Mental health and asthma, 240, 241 Mental illness, forms of, 341 Methamphetamine, use among MSM, 324 Migraine disorders buspirone effects on, 359 role of serotonin in, 358 Migraine headaches, 341 Minnesota Multiphasic Personality Inventory (MMPI), 263, 300 MI-related PTSD, 133 Mitral valve prolapse, 341 Monoamine oxidase inhibitors (MAOIs), 346 Mood disorders comorbidity of, 292, 300 in NCCP patients, prevalence of, 290 Mood symptom fluctuation in women, reproductive hormones role, 193 MSM (men who have sex with men), 317 HIVþ, and anxiety disorders, 321 methamphetamine use among, 324 prevalence of anxiety disorder, 320 Multiaxial Assessment of Pain (MAP), 220 Multidimensional Pain Inventory (MPI) in anxiety disorder assessment, 224 Multiple sclerosis, single-spectrum disorder, 108 Multiple sleep latency testing (MSLT), 106 Mutual maintenance model for pain and anxiety disorders, 215, 216 Myocardial infarction (MI), 280, 352, 354 anxiety in, examination of, 285 anxiety with, 283 chest pain suggestive of, 289 trigger onset of, 300 NAS, see Nucleus accumbens septi National Comorbidity Survey (NCS), 131 National Epidemiological Survey on Alcohol and Related Conditions (NESARC), 57, 60 NCCP, see Non-cardiac chest pain (NCCP) anxiety in patients, 289–291 axis I anxiety disorder, 291 risk factors, 290 Neurobiological disorder, 108 Neurobiological models, of drug addiction, 66 Neuropathy, peripheral, 318 Neurotransmitter-neuromodulatory receptor systems, 113

Index Night sweats, 318 Non-cardiac chest pain (NCCP), 280 CVD patients with, anxiety in, 289–291 Non-psychiatric medical services, utilization of, 341 Norepinephrine (NE) in patients with HIV, changes in, 333 in patients with PTSD, levels of, 331 Normative aging study of anxiety-CHD link, 283 Northwick study of anxiety-CHD link, 282 Nucleus accumbens septi, 93 Nurses’ health study of anxiety-CHD link, 283 Obesity in adulthood with asthma symptoms, 239 for psychiatric comorbidity, 296 Obsessive compulsive disorder (OCD), 347 CBT for, 92 in menstrual cycle, 190 in pain patients, 209–212 Pain and anxiety disorders assessment methods, 223–225 associations, 215–217 course of, 214, 215 issues and researches on treatment, 227–229 physiological arousal, 220–222 prevalence of, 209–214 treatment and therapies, 225–227 concept of, 208, 209 prevalence in anxiety disorder patients, 213, 214 -related emotion and ANS responses, 221 -related stimuli, attention, 219, 220 Pain Anxiety Symptoms Scale (PASS), in anxiety disorder assessment, 224, 225 Panic attack management in asthma treatment, 269 Panic disorder (PD), 341, 347 in adolescent anxiety, 169 mediators of, 170 moderators of, 171, 172 with agoraphobia and anxiety disorder, DSM-IV for diagnosis of, 61 application of exercise interventions for, 89 association with cancer, 140

375 cardiovascular disease, 136–137 endocrine/metabolic disease, 140 gastrointestinal (GI) disease, 139–140 neurological disease, 138–139 respiratory disease, 137–138 asthma with, 259 diagnoses of, 247 specificity of, 260–261 CAD patients with morbidity and mortality among, 298 myocardial perfusion defects in, 300 prevalence of, 288 CBT for, 90, 349, 353 in CHD-anxiety association, 286 CHD patients with, prevalence of, 289 comorbidity of, 293 diagnostic criteria for, 327 drinking frequency and quantity in nonalcoholic drinkers with, 38 DSM-IV for diagnosis of, 286, 348 efficacy of aerobic exercise for, 91 in HIV, prevalence of, 321 in incidence of cardiovascular morbidity, 294 NCCP patients with, prevalence of, 291 norepinephrine reactivity in patients with, 331 in pain patients, 209–212 for psychiatric comorbidity, 296 related symptoms for, 62 and symptoms in menstrual cycle, 185, 190, 191 treatment-seeking smokers with, 13 Panic psychopathology addictive use of cigarettes, rates of occurrence in, 9 behavior pattern characterized by consistent avoidance of threatening situations in, 4 current knowledge regarding, 13 development of, 16 diagnostic criteria for agoraphobia, 4 distinction from other anxiety disorders, 8 lifetime estimates of panic disorder, 4 persons with, rates of smoking among, 8 prevention programs for, application to, 17 and tobacco use co-occurrence rates between, 10 nature of associations between, 5, 11 prevalence of, 7–11 Panic-specific emotional symptoms, degrees of, 14

376 PD, see Panic disorder (PD) Peak expiratory flow (PEF), 238 Pediatric anxiety rating scale (PARS), for anxiety disorder, 356 Pediatric autoimmune neuropsychiatric disorders associated with streptococcus infection (PANDAS), 142, 143 Peptic ulcer disease (PUD), 141 Peripheral neuropathy, 318 Pharmacotherapy, in PTSD and pain treatment, 227 Phobias, 110 social phobia, 328 Phobic anxiety, 293 anxiety-CHD for construct of, 293 CHD risk factors associated with, 284, 291 as risk of SCD, 282, 299 Phobic disorders, prevalence of, 283 Phobic postural vertigo (PPV), effects of CBT for, 353 Physical functioning, health-related, relationship between PTSD and, 330 Physical illness and anxiety future directions for, 360–361 future methodological considerations for, 361–362 pharmacological treatment of, 355–360 psychosocial treatment of, 348 no comparison group, 353–355 nonrandomized with control group, 352–353 randomized with treatment comparison group, 348–350 randomized with waitlist, 351 Physiological arousal, in pain and anxiety disorders, 220, 221 Pittsburgh Sleep Quality Index (PSQI), 117, 118 Polymorphous light eruption (PLE), 110 Pontine nucleus locus ceruleus, 114 Poor sleep, 117, 118 Postsynaptic serotonin receptors, downregulation of, 93 Posttraumatic stress disorder (PTSD), 283 association with cancer, 135–136 cardiovascular disease, 133 endocrine/metabolic/autoimmune disease, 134–135 neurologic disease, 133–134

Index asthma with, diagnoses of, 259 in CAD patients, prevalence of, 288 CBT for, 350 and childhood sexual abuse, prevalence of, 325 childhood sexual abuse and, 325 and chronic musculoskeletal pain patients, 207–216 assessment methods, 223–225 hypoalgesia/analgesia in, 222 physiological arousal, 220, 221 symptom overlap and anxiety sensitivity, 218, 219 treatments and therapies, 225–227 concurrent treatment of, 72 depression, substance abuse and anxiety disorders, 321 diagnostic criteria for, 59 drug use disorder, 61 and health-related physical functioning, relationship between, 330 in HIV-infected women, 322 in HIV patients, prevalence of, 320 and HIV risk, 324 in menstrual cycle, 192 NE in patients with, levels of, 331 prevalence rate in HIVþ individuals, 320 symptoms of, 283 treatments for, 333 PPV, see Phobic postural vertigo (PPV), effects of CBT for Premenstrual anxiety health behaviors, 196, 197 research in normal women, 187–188 in women with PMDD, 189 in women with PMS, 188–189 treatments and therapies, 194–196 Premenstrual Dysphoric Disorder (PMDD), 182 assessment measures, 183–186 cognitive-behavior therapy, 195, 196 diagnosis of, 183 research on, 189 selective serotonin reuptake inhibitor, 196 Premenstrual exacerbation (PME), and comorbidity, 185, 186 Premenstrual symptoms, and anxiety disorders assessment measures, 182–186 interaction models, 192–194 OCDs and GADs, 191, 192

Index panic disorder, and symptoms, 190, 191 PTSD, 192 Premenstrual syndrome (PMS), 182 and biological factors, 193 cognitive-behavior therapy, 195, 196 research on women, 188, 189 selective serotonin reuptake inhibitor, 196 Present pain index (PPI), in SF-MPQ, 224 Primary anxiety disorder, observations, 106 Primary insomnia, 106 Progressive resistance training (PRT), 96 Prototypical panic psychopathology, 14 Pseudoseizure, and psychogenic seizure, 133 Psychedelic abuse, and dependence, 62 Psychiatric comorbidity, 349 obesity, PD and MDD for, 296 Psychiatric illness, and NCCP, relationship between, 290 Psychocardiology, 280 Psychoeducation, in anxiety and pain treatment, 225 Psychogenic nonepileptic seizure (PNES), 133, 134 Psychological distress in asthma, importance of, 241 in HIV risk, role of, 322 Psychopathology of anxiety assessment of, 361 physical illness and, 341 treatment of, 346–348 and asthma, relation between, 259 Psychosocial clinical intervention research, importance of, 333 Psychosocial treatment, for physical illness and anxiety, 348 Psychotherapy effects of, 354 in premenstrual anxiety, 195 PTSD, see Posttraumatic stress disorder (PTSD) Pubertal hormones and anxiety, 162, 163 in puberty assessment, 158, 159 Pubertal status and anxiety, 160–162 in puberty assessment, 157 Pubertal timing and anxiety, 163–166 in puberty assessment, 157–159 Puberty and risk factor, 159, 160

377 role in adolescent anxiety: theory and evidence, 155 conceptually-driven suggestions, 167–172 future perspectives, 167 operationalization and assessment, 156–160 psychological problems, 155, 156 pubertal status and timing effects puberty assessment, 156–160 research, 166, 167 undesirable bodily events, 156 Puberty-anxiety association, researches, 166–169 QT interval variability (QTV), 298 Quality of life (QOL) anxiety disorders for negative impact on, 241 asthma related, effect of anxiety on, 263 and HIV, 329–330 Reduced heart-rate variability (HRV), 298–299 Reductions, in anxiety with exercise, 87 Relaxation training in anxiety and pain treatment, 226 Renal failure, 354 Rhinitis, treatment of, 240 Rutgers Alcohol Problem Index (RAPI), 47 SAM systems, see Sympathetic adrenal medullary systems, dysregulation of Schedules for clinical assessment in neuropsychiatry (SCAN), for anxiety disorders, 358 Schizophrenia, 355 Screen for Child Anxiety Related Emotional Disorders (SCARED), 355 Seizure, 138 Selective serotonin reuptake inhibitors (SSRI), 117 in PMS and PMDD treatment, 196 Serotonergic receptor system, 114, 116 Serotonin, role in migraine disorders, 358 Serotonin selective reuptake inhibitors (SSRIs), 346 for treatment of IBS, 357, 358 Sertraline, for depression, 303 Sexual activity, among HIV-infected adolescents, 324 Sexually transmitted disease (STD), 323

378 Shared vulnerability/stress models for pain and anxiety disorders, 216, 217 Shingles, 318 Short Form McGill Pain Questionnaire (SF-MPQ), in anxiety disorder assessment, 224 Simple phobia (SP) in premenstrual anxiety, 185 Single spectrum disorder model, anxiety and insomnia, 107, 108 Sleep deprivation, 110, 117, 118, 156 panic induced by, 118 Sleeping difficulties, and insomnia-like symptoms, 111 Sleep polysomnography (PSG), 117 Sleep restoration, mechanism of, 93–94 Sleep restriction, 118 Slow wave sleep (SWS), 94 Smokeless tobacco, developmental course for, 13 Smoking, 287, 304 for development of asthma, 240 Smoking behavior, conceptualization and measurement of, 18 Smoking cessation, 291 Smoking-panic relations cross-sectional tests to clarify factors affecting, 14 psychopathology of, 12 study of, 15 tests for examining moderating factors affecting, 16 Social anxiety and HIV risk gay and bisexual youth, 323 unprotected sex, 324 impact on drinking behavior of undergraduate student, 40 Social anxiety disorder autoimmune disease, 144 endocrine/metabolic disease, 143–144 gastrointestinal disease, 143 in pain patients, 209–212 Social phobia (SP), 118 asthma with, 259 diagnoses of, 247 Specific anxiety disorders, relationships with illicit drug use, 59 Specific or simple phobia cancer, 145 endocrine/metabolic disease, 144–145 gastrointestinal disease, 144 respiratory disease, 144

Index Spinal cord injury (SCI), 354 with depression and anxiety, 352 Spirometry role, in FEV1 measurement, 238 SSRIs, see Serotonin selective reuptake inhibitors (SSRIs) State trait anxiety inventory (STAI), for anxiety and depression, 352, 353 Stress cardiomyopathy, 300 for low SES and asthma symptoms, 239 Stress hormones in anxiety HIV and pathophysiology of, 330–331 HPA and SAM systems, dysregulation of, 330–331 Structured clinical interview diagnostic (SCID) for assessment of anxiety disorders, 329 for DSM, 293 Subacute cutaneous lupus erythematosus (SCLE), 109 Substance use, 317, 322, 325, 326 in HIV, anxiety and, 328 Substance use disorders (SUD), 71, 328 anxiety and medication adherence, relationships with, 326–327 and anxiety-related HIV sexual risk, 325 in asthma, prevalence of, 237 comorbidity of, 329 in HIV patients, 328 Sudden cardiac death (SCD), 280 anxiety for, 295 emotion of anxiety in development of, 280 occurrence of, 297 due to phobic anxiety, 282, 299 predictor of, 298 Suicidal ideation, in asthma, 241 Suicidality, 325 Sympathetic adrenal medullary systems, dysregulation of, 331 Tachycardia, ventricular, 298 Tanner staging system, in pubertal status assessment, 157 T-helper cells, and HIV infection, 318 Third factor model, anxiety and insomnia, 108, 109 apolipoprotein E gene polymorphism, 110 cardiovascular disease, 110 Threat-related stimuli, attention, 219, 220 Thyroid disease, 341 Tobacco-panic comorbidity, nature of, 10 Tobacco-panic psychopathology linkages, 11

Index Tobacco use, 281, 290 cigarette smoking, 6 co-occurrence rates between panic psychopathology and, 10 current knowledge regarding, 11 effects on persons with a lifetime history of panic psychopathology, 9 lifetime nicotine dependence diagnosis, 9 multiple forms of, 10 nature of associations between panic psychopathology and, 11 nature of association with panic psychopathology, 5 smokeless application, 6–7 See also Smoking Tourette’s syndrome, 142 Trait anxiety, 326 and cardiac events, relation between, 284 in CHD patients, 294 and HIV risk, 323 prediction of, 260 Transtheoretical Model (TTM), 84 Traumatic event exposure, in adolescents, 155 Treatment rationale and education, in asthma treatment, 269 Tricyclic antidepressants (TCAs), 346 Triiodothyronine (T3), arousal features in PTSD, 134 Twelve-Step Facilitation (TSF), 45

379 Ultraviolet light/sun exposure, 109 Variable risk factor, and puberty, 159 Ventral lateral preoptic nucleus (VPLO), 114 Ventricular arrhythmia anxiety for, 295 in CHD, 299–300 Ventricular premature beat (VPB), as risk of SCD, 299 Veterans Administration Normative Aging Study of anxiety-CHD link, 283 Veterans Administration (VA) Health Care System, 214 Visual analogue scale (VAS), in SF-MPQ, 224 Vulnerability nomenclature, risk factors associated with, 5–6 Wakefulness-promotion, 114 Women with breast cancer, CEGT for, 350 HIVþ, and anxiety disorders, 322 increase in CHD risk for, 283 World Mental Health Survey (WMH), 110, 111 on relation between asthma and psychopathology, 259 Worry cognitive process, 106 Z drugs, reducing anxiety, 116

Anxiety in Health Behaviors and Physical Illness (Series in Anxiety and Related Disorders)

Insomnia and Anxiety (Series in Anxiety and Related Disorders)

Anxiety and Related Disorders

Treating Health Anxiety and Fear of Death: A Practitioner's Guide (Series in Anxiety and Related Disorders)

Avoiding Treatment Failures in the Anxiety Disorders (Series in Anxiety and Related Disorders)

Anxiety and Substance Use Disorders: The Vicious Cycle of Comorbidity (Series in Anxiety and Related Disorders)

Acceptance and Mindfulness-Based Approaches to Anxiety: Conceptualization and Treatment (Series in Anxiety and Related Disorders)

Anxiety Disorders

Anxiety Disorders (Psychological Disorders)

Serotonergic Neurocircuitry in Mood and Anxiety Disorders

Anxiety Disorders in Children and Adolescents

Mood and anxiety disorders in women

Anxiety Disorders in Children and Adolescents

Treating Trichotillomania: Cognitive-Behavioral Therapy for Hairpulling and Related Problems (Series in Anxiety and Related Disorders)

Concepts and Controversies in Obsessive-Compulsive Disorder (Series in Anxiety and Related Disorders)

Living with Anxiety Disorders

SSRIs in Depression and Anxiety

Anxiety Disorders in Children and Adolescents: Research, Assessment and Intervention

Anxiety Disorders in Adults: A Clinical Guide

The Anxiety Disorders (Concepts in Clinical Psychiatry)

Pharmacotherapy for Mood, Anxiety, and Cognitive Disorders

Clinical Manual of Anxiety Disorders

Understanding Panic and Other Anxiety Disorders

Postpartum Mood And Anxiety Disorders: A Guide

Anxiety Disorders: Theory, Research and Clinical Perspectives

Anxiety Disorders and Phobias: A Cognitive Perspective

Handbook of Child and Adolescent Anxiety Disorders

Anxiety (Ideas in Psychoanalysis)

Different Views of Anxiety Disorders

Anxiety Disorders Comorbid with Depression

Clinical Manual of Anxiety Disorders

Anxiety in Health Behaviors and Physical Illness (Series in Anxiety and Related Disorders)

Insomnia and Anxiety (Series in Anxiety and Related Disorders)

Anxiety and Related Disorders

Treating Health Anxiety and Fear of Death: A Practitioner's Guide (Series in Anxiety and Related Disorders)

Avoiding Treatment Failures in the Anxiety Disorders (Series in Anxiety and Related Disorders)

Anxiety and Substance Use Disorders: The Vicious Cycle of Comorbidity (Series in Anxiety and Related Disorders)

Acceptance and Mindfulness-Based Approaches to Anxiety: Conceptualization and Treatment (Series in Anxiety and Related Disorders)

Anxiety Disorders

Anxiety Disorders (Psychological Disorders)

Serotonergic Neurocircuitry in Mood and Anxiety Disorders

Anxiety Disorders in Children and Adolescents

Mood and anxiety disorders in women

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