CURRENT OPINION
Sports Med 2011; 41 (8): 613-619 0112-1642/11/0008-0613/$49.95/0
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The Non-Surgical and Surgical Treatment of Tarsal Navicular Stress Fractures John R. Fowler,1 John P. Gaughan,2 Barry P. Boden,3 Helene Pavlov4 and Joseph S. Torg1 1 Temple University Hospital, Department of Orthopaedics and Sports Medicine, Philadelphia, PA, USA 2 Temple University School of Medicine, Biostatistics and Consulting Center, Philadelphia, PA, USA 3 Orthopaedic Cente, Rockville, MD, USA 4 Hospital for Special Surgery, Department of Radiology and Imaging, New York, NY, USA
Abstract
Stress fractures of the tarsal navicular, first described in 1970, were initially thought to be rare injuries. Heightened awareness and increased participation in athletics has resulted in more frequent diagnosis and more aggressive treatment. The vascular supply of the tarsal navicular results in a relatively avascular zone in the central one-third, which experiences severe compressive forces during explosive manoeuvers such as jumping and sprinting. Repetitive activities can result in stress reactions or even fracture. Patients often initially complain of vague midfoot pain localized to the medial border of the foot. The pain is usually exacerbated by activity and relieved with rest. The diagnosis of tarsal navicular stress fracture is challenging because of the high false negative rate of plain radiographs. Additional diagnostic testing with bone scan, CT and MRI are often required for diagnosis. The proper treatment of tarsal navicular stress fractures has become a topic of debate as surgical intervention for these injuries has increased. In a recent meta-analysis, Torg et al. found that 96% of tarsal navicular stress fractures treated with non-weight-bearing (NWB) conservative treatment for 5 weeks went on to successful outcomes. However, only 44% of patients treated with weight-bearing (WB) conservative treatment had successful outcomes. Surgical treatment resulted in successful outcome in 82% of patients. Interestingly, the meta-analysis also found that fracture type did not correlate with outcomes, regardless of treatment. The meta-analysis also found no difference in time to return to activity between patients treated surgically and those who underwent NWB conservative treatment. The recent literature indicates that patients are undergoing surgery or are receiving WB conservative management as a first-line treatment option with the expectation that they will return to their activity more quickly. Although surgical treatment seems increasingly common, the results statistically demonstrate an inferior trend to conservative NWB management. Conservative NWB management is the standard of care for initial treatment of both partial and complete stress fractures of the tarsal navicular. WB conservative treatment and surgical intervention are not recommended.
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1. Introduction The stress fracture of the tarsal navicular was first described in humans in a 1970 case study by Towne et al.[1] Early studies showed that it was a rare injury, accounting for only 0.7–2.4% of all stress fractures.[2] However, as awareness of the injury has increased, so have the reported number of cases, with tarsal navicular stress fractures currently representing up to 25% of stress fractures in some series.[3-7] Diagnosis of tarsal navicular stress fractures is challenging as plain radiographs routinely fail to demonstrate the fracture. One must maintain a high index of suspicion for this injury, especially in athletes with foot pain, given the vague complaints and potential for considerable delay in diagnosis.[8] 2. Anatomy The ‘boat-shaped’ tarsal navicular represents the base of the medial column of the foot, articulating with the talus proximally, and the cuboid and all three cuneiforms distally.[8,9] It has several important ligamentous attachments, including the posterior tibial tendon on the medial tuberosity and the spring ligament on the plantar surface.[8,9] The tarsal navicular derives its dorsal blood supply from a branch of the dorsalis pedis artery, while the plantar surface receives its supply from branches of the medial plantar artery.[9] These branches form a rich anastomosis but leave the central onethird relatively avascular.[8,9] The tarsal navicular is subjected to intense compressive forces over its middle one-third during the foot-strike phase of gait when it is compressed between the talus and the cuneiforms.[10] Torg et al.[11] proposed that repetitive cyclical loading of the tarsal navicular could lead to stress fracture over the central one-third. 3. Clinical Presentation and Physical Examination Patients most often present with dorsal foot pain of insidious onset. Patients may initially describe the pain as soreness or cramping along the dorsomedial border of the foot that is exacerbated with activity.[8,10] As many patients ª 2011 Adis Data Information BV. All rights reserved.
who sustain tarsal navicular stress fractures are athletes, they initially may complain of pain only during sport and not with other activities of daily living.[8,10] Specifically, explosive activities such as jumping, sprinting and rapidly changing direction may exacerbate symptoms.[8,10] Physical examination is often unremarkable. Patients may have tenderness to palpation over the tarsal navicular. Provocative testing includes having the patient hop on the affected foot to determine if it reproduces the symptoms experienced during athletic play.[8,10] 4. Diagnosis The diagnostic work-up should begin with standing plain radiographs of the foot and ankle. The radiographs may demonstrate a visible fracture line; however, several authors have found a high rate of false negative radiographs.[3,11,12] If there remains a high index of suspicion after negative plain radiographs, further work-up with bone scan, CT or MRI is indicated. Although bone scan has been found to have a high sensitivity, it is also non-specific and requires additional diagnostic testing in the event of a positive test, further delaying the definitive diagnosis.[11] Bone scans are unable to differentiate tarsal navicular pathology from other possible aetiologies, including painful accessory tarsal navicular, posterior tibial tendonitis, tarsal coalition, anterior tibial tendonitis and osteochondral defects of the talus.[8] A bone scan examination exposes the patient to ionizing radiation, albeit a low dose, and while a negative result reliably rules out a stress fracture, a positive result is non-specific and requires additional imaging as per clinical symptoms.[10] A CT examination is a sensitive and specific test for diagnosis of a tarsal navicular fracture and can delineate the specific fracture pattern. While CT exposes the patient to ionizing radiation, the foot is a relatively insensitive body part and of low patient risk.[8,11] An MRI examination provides a sensitive method of evaluation with more specificity than a bone scan and has the advantages of no ionizing radiation. It demonstrates soft tissue and cartilage detail as well as a bone oedema pattern, which helps in distinguishing an acute from a Sports Med 2011; 41 (8)
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chronic fracture. The MRI examination can also identify if there is non-union and/or necrosis.[10] Figure 1a demonstrates a partial tarsal navicular stress fracture on CT. Figure 1b and figure 1c show a complete tarsal navicular stress fracture on CT and MRI, respectively. Figure 1d illustrates a delayed union on CT, which progressed to a non-union as seen on MRI (figure 1e). 5. Classification A systematic review of the literature indicates that authors classify tarsal navicular fractures as partial, involving the dorsolateral cortex, or complete, involving both cortices, and further define them as acute, subacute or non-union. 6. Treatment The proper treatment of tarsal navicular stress fractures has been a recent topic of debate. Historically (table I), conservative treatment in a non-weight-bearing (NWB) cast has been the treatment of choice.[1,3,8,11] More recently, authors have described open reduction and internal fixation for tarsal navicular stress fractures.[7,8,12,17,18] Torg et al. reported on 21 cases of tarsal navicular stress fracture and demonstrated that these fractures heal well with conservative treatment.[11] Because routine radiographs failed to show the fracture, the interval between the onset of symptoms and diagnosis ranged from <1 to 38 months (mean of 7 months). Conservative treatment in this series consisted of NWB cast immobilization for 6–8 weeks, followed by gradual weight bearing (WB) in a boot for 2–6 weeks until pain free. The efficacy of this treatment protocol has been confirmed by several authors.[5,12,13] Even in patients for whom treatment in a WB cast has failed, NWB cast treatment compares favourably with surgical treatment.[12] There is strong evidence supporting the effectiveness of proper conservative management for both partial and non-displaced, complete stress fractures of the tarsal navicular. Case series or reports from Ostlie and Simons,[19] Alfred et al.,[20] Murray et al.,[21] Towne et al.,[1] Goergen et al.,[22] Ariyoshi et al.,[23] Miller and Poulos[24] and Ting et al.[25] all reported ª 2011 Adis Data Information BV. All rights reserved.
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a 100% success rate when NWB management of at least 6 weeks was utilized. The data also strongly reaffirms that WB rest or limited activity as a conservative treatment often leads to an unsuccessful outcome, including delayed or non-union, refracture, fracture progression or recurrence of symptoms.[1,5,11-13,26,27] It appears, however, that current management of this injury increasingly utilizes surgical intervention both as a first-line treatment or following failed treatment with WB conservative management because of pressure on both the athlete and the physician to have the athlete return more quickly to competition.[5,13] Saxena et al.[15] suggested that surgical intervention would decrease the amount of time for an athlete to return to their activity level prior to injury. However, the most recently reported data by Saxena et al.[16] demonstrated that there is no significant difference between surgical and conservative management. In support of this view, Burne and colleagues[5] found the clinical outcome of surgical management inferior to that reported for NWB cast immobilization and stated that ‘‘there is limited evidence to support surgical intervention as a first line of management.’’ They suggest that the large variance in different surgical approaches ‘‘may reflect a lack of consistently satisfactory outcomes.’’ In our systematic review of the literature[7] that comprised 30 case series of patients, we did not find any data regarding the incidence of refracture in patients treated with conservative NWB methods. Given the small numbers of patients in many series and the heterogeneity in time to diagnosis and classification, a meta-analysis may be the most appropriate way to study outcomes. In a recent meta-analysis by Torg et al.,[7] 313 tarsal navicular stress fractures were identified in 23 reports in the peer-reviewed literature. The authors created three subsets based on the information contained within each study as follows: (i) subset I included studies that reported fracture types as partial or complete; (ii) subset II included all reports that documented the fracture without defining if it was partial or complete; and (iii) subset III included reports limited to documentation of the fracture and successful/unsuccessful outcomes without including time to return to activity. Sports Med 2011; 41 (8)
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a
b
c
d
e
Fig. 1. (a) CT scan of partial tarsal navicular stress fracture. (b) CT scan of complete tarsal navicular stress fracture. (c) MRI of complete tarsal navicular stress fracture. (d) CT scan of delayed union of complete tarsal navicular stress fracture. (e) MRI demonstrating tarsal navicular non-union.
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Table I. Summary of published studies comparing treatment options for navicular stress fractures Study (y)
No. of
Non-weight bearing
fractures successful outcome with cast for ‡6 wk (n/N)
return to activity (mean; mo)
Torg et al.[11] (1982)
21
3.9
Fitch et al.[13] (1989)
34
Khan et al.[12] (1992)
86
19/22
5.6
Bojanic and Pecina[14] (1997)
18
18/18
6.0
Saxena et al.[15] (2000)
22
Burne et al.[5] (2005)
20
2/2
Saxena and Fullem[16] (2006)
19
6/6
3.7
10/10
Weight bearing successful outcome with cast for <6 wk (n/N)
9/13
return to successful activity outcome (mean; mo) (n/N)
5.8
4/5
Surgery
return to activity (mean; mo)
successful outcome (n/N)
return to activity (mean; mo)
2/9
5.5
2/2
6.0
13/18
10.0
12/16
8.0
9/34
5.8
12/20
5.4
8/13
4.3
9/9
3.1
8/9
4.1
8/13
Others
30
15/15
5.7
4/4
4.2
3/5
3.0
6/6
4.9
Totals [%]
251
70/73 [96]
4.9
17/22 [77]
3.7
43/92 [47]
5.7
54/66 [82]
5.2
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found no statistically significant difference between NWB conservative treatment and surgery (p = 0.6441) in regards to outcome and no difference in time to return to activity. However, the authors did demonstrate a statistical trend favouring NWB management (96% successful outcomes) over surgery (82% successful outcomes). Patients treated with WB protocols had a statistically significant difference in outcomes when
6 5 Months
In subset I, 50 incomplete fractures and 12 complete fractures were treated conservatively, compared with 13 incomplete fractures and 12 complete fractures treated surgically. The fracture type, partial or complete, was not statistically significant when comparing NWB conservative and surgical treatment with regard to a successful outcome (p = 0.994). Having demonstrated that the type of fracture was not a statistically significant variable regarding success of outcome, subsets I and II were combined to yield 251 tarsal navicular stress fractures for analysis. Seventy (96%) of 73 fractures initially treated with NWB cast immobilization for 6 weeks had a successful outcome, with an average return to activity of 4.9 months (figure 2). Only 43 (47%) of 92 patients initially treated with WB rest and/or cast immobilization experienced a successful outcome, with an average return to activity of 5.7 months. Clearly, NWB treatment is favoured over WB treatment. Fifty-four (82%) of 66 fractures initially treated surgically had a successful outcome, with an average return to activity of 5.2 months. Comparing the modes of treatment, the authors
4 3 2 1 0 NWB <6 wk
NWB >6 wk
PWB
Surgery
Average time return to activity Fig. 2. Return to activity for various treatment modalities. NWB = nonweight bearing; PWB = partial weight bearing.
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compared with NWB conservative (p = 0.0001) and surgical treatment (p = 0.0003).[7] The majority of the poor results from surgical intervention were described in two of the initial series documenting the treatment of tarsal navicular stress fractures (table I).[11-13] More recent studies have documented high success rates with both surgery and NWB conservative management.[5,14-16] Improved surgical technique and implants may have contributed to the increased success of operative treatment. Regardless, the increased risk of operative complications (infection, risks related to anaesthesia, etc.), even if minimal, cannot be justified given the high rate of healing in fractures treated non-operatively. 7. Conclusions There is strong evidence supporting the effectiveness of proper conservative management for both partial and non-displaced, complete stress fractures of the tarsal navicular.[1,11,19-21,23-25] A recent meta-analysis by Torg and colleagues[7] demonstrated that the propensity of healing in tarsal navicular stress fractures is independent of fracture type. The recent literature suggests that patients are undergoing surgery or are receiving WB conservative management as a first-line treatment option with the expectation that they will return to their activity more quickly.[5,15,16] Although surgical treatment seems increasingly common, it remains largely under-reported in the literature. Patients treated with NWB cast immobilization for 6 weeks should expect a successful outcome in >90% of cases and a return to activity in approximately 5 months.[7] First-line surgical treatment resulted in successful outcomes in only 82% of cases. A recent meta-analysis demonstrated a statistical trend favouring NWB management over surgical intervention. Interestingly, the fracture type has not been shown to affect outcomes, regardless of the type of treatment. WB conservative treatment is not recommended and often leads to an unsuccessful outcome, including delayed union or non-union, refracture, fracture progression or recurrence of symptoms.[7] Conservative NWB management is the standard of care for initial treatment of both ª 2011 Adis Data Information BV. All rights reserved.
partial and complete stress fractures of the tarsal navicular.[7] Acknowledgements The authors disclose no funding related to this study and no potential conflicts of interest.
References 1. Towne LC, Blazina ME, Cozen LN. Fatigue fracture of the tarsal navicular. J Bone Joint Surg Am 1970 Mar; 52 (2): 376-8 2. Coris EE, Lombardo JA. Tarsal navicular stress fractures. Am Fam Physician 2003 Jan 1; 67 (1): 85-90 3. Khan KM, Brukner PD, Kearney C, et al. Tarsal navicular stress fracture in athletes. Sports Med 1994 Jan; 17 (1): 65-76 4. Brukner P, Bradshaw C, Khan KM, et al. Stress fractures: a review of 180 cases. Clin J Sport Med 1996 Apr; 6 (2): 85-9 5. Burne SG, Mahoney CM, Forster BB, et al. Tarsal navicular stress injury: long-term outcome and clinicoradiological correlation using both computed tomography and magnetic resonance imaging. Am J Sports Med 2005 Dec; 33 (12): 1875-81 6. Bennell KL, Malcolm SA, Thomas SA, et al. The incidence and distribution of stress fractures in competitive track and field athletes: a twelve-month prospective study. Am J Sports Med 1996 Mar-Apr; 24 (2): 211-7 7. Torg JS, Moyer J, Gaughan JP, et al. Management of tarsal navicular stress fractures: conservative versus surgical treatment. A meta-analysis. Am J Sports Med 2010 May; 38 (5): 1048-53 8. Mann JA, Pedowitz DI. Evaluation and treatment of navicular stress fractures, including nonunions, revision surgery, and persistent pain after treatment. Foot Ankle Clin 2009 Jun; 14 (2): 187-204 9. Golano P, Farinas O, Saenz I. The anatomy of the navicular and periarticular structures. Foot Ankle Clin 2004 Mar; 9 (1): 1-23 10. Jones MH, Amendola AS. Navicular stress fractures. Clin Sports Med 2006 Jan; 25 (1): 151-8, x-xi 11. Torg JS, Pavlov H, Cooley LH, et al. Stress fractures of the tarsal navicular: a retrospective review of twenty-one cases. J Bone Joint Surg Am 1982 Jun; 64 (5): 700-12 12. Khan KM, Fuller PJ, Brukner PD, et al. Outcome of conservative and surgical management of navicular stress fracture in athletes: eighty-six cases proven with computerized tomography. Am J Sports Med 1992 Nov-Dec; 20 (6): 657-66 13. Fitch KD, Blackwell JB, Gilmour WN. Operation for nonunion of stress fracture of the tarsal navicular. J Bone Joint Surg Br 1989 Jan; 71 (1): 105-10 14. Bojanic I, Pecina MM. Conservative treatment of stress fractures of the tarsal navicular in athletes. Rev Chir Orthop Reparatrice Appar Mot 1997; 83 (2): 133-8 15. Saxena A, Fullem B, Hannaford D. Results of treatment of 22 navicular stress fractures and a new proposed radiographic classification system. J Foot Ankle Surg 2000 MarApr; 39 (2): 96-103
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16. Saxena A, Fullem B. Navicular stress fractures: a prospective study on athletes. Foot Ankle Int 2006 Nov; 27 (11): 917-21 17. Potter NJ, Brukner PD, Makdissi M, et al. Navicular stress fractures: outcomes of surgical and conservative management. Br J Sports Med 2006 Aug; 40 (8): 692-5; discussion 695 18. Roper RB, Parks RM, Haas M. Fixation of a tarsal navicular stress fracture: a case report. J Am Podiatr Med Assoc 1986 Sep; 76 (9): 521-4 19. Ostlie DK, Simons SM. Tarsal navicular stress fracture in a young athlete: case report with clinical, radiologic, and pathophysiologic correlations. J Am Board Fam Pract 2001 Sep-Oct; 14 (5): 381-5 20. Alfred RH, Belhobek G, Bergfeld JA. Stress fractures of the tarsal navicular: a case report. Am J Sports Med 1992 NovDec; 20 (6): 766-8 21. Murray SR, Reeder M, Ward T, et al. Navicular stress fractures in identical twin runners: high-risk fractures require structured treatment. Phys Sportsmed 2005 Jan; 33 (1): 28-33 22. Goergen TG, Venn-Watson EA, Rossman DJ, et al. Tarsal navicular stress fractures in runners. AJR Am J Roentgenol 1981 Jan; 136 (1): 201-3
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23. Ariyoshi M, Nagata K, Kubo M, et al. MRI monitoring of tarsal navicular stress fracture healing: a case report. Kurume Med J 1998; 45 (2): 223-5 24. Miller JW, Poulos PC. Fatigue stress fracture of the tarsal navicular: a case report. J Am Podiatr Med Assoc 1985 Aug; 75 (8): 437-9 25. Ting A, King W, Yocum L, et al. Stress fractures of the tarsal navicular in long-distance runners. Clin Sports Med 1988 Jan; 7 (1): 89-101 26. Dennis L, Lombardi CM. Stress fracture of the tarsal navicular: two unusual case reports. J Foot Surg 1988 NovDec; 27 (6): 511-4 27. Helstad PE, Ringstrom JB, Erdmann BB, et al. Bilateral stress fractures of the tarsal navicular with associated avascular necrosis in a pole vaulter. J Am Podiatr Med Assoc 1996 Nov; 86 (11): 551-4
Correspondence: Dr Joseph Torg, Temple University Hospital, Department of Orthopaedics and Sports Medicine, 6th Floor Outpatient Building, Zone B, 3401 N Broad St, Philadelphia, PA 19140, USA. E-mail:
[email protected]
Sports Med 2011; 41 (8)
REVIEW ARTICLE
Sports Med 2011; 41 (8): 621-639 0112-1642/11/0008-0621/$49.95/0
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Neuroendocrine-Immune Interactions and Responses to Exercise Maren S. Fragala,1,2,3 William J. Kraemer,1,2 Craig R. Denegar,1 Carl M. Maresh,1 Andrea M. Mastro4 and Jeff S. Volek1 1 2 3 4
Human Performance Laboratory, Department of Kinesiology, University of Connecticut, Storrs, CT, USA Center on Aging, University of Connecticut Health Center, Farmington, CT, USA Department of Child, Family and Community Sciences, University of Central Florida, Orlando, FL, USA Department of Biochemistry and Molecular Biology, The Pennsylvania State University, University Park, PA, USA
Contents Abstract. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1. Neuroendocrine-Immune Interactions/Communication . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1 Neuroendocrine and Immune System Interaction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2 Neuroendocrine and Immune System Communication . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.3 Literature Search Methodology. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2. Exercise-Induced Neuroendocrine Responses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Neuroendocrine Responses to Exercise . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1.1 Catecholamines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1.2 Cortisol . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1.3 Estradiol . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1.4 Testosterone . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Gender Differences in Endocrine Response to Exercise . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3. Exercise-Induced Immune Responses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Immune Responses to Exercise . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Gender Differences in Immune Responses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 Gender Differences in Immune Responses to Exercise. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4. Evidence that Neuroendocrine-Immune Responses Mediate Adaptations to Exercise. . . . . . . . . . . . 4.1 Neuroendocrine and Immune System Communication . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1.1 Glucocorticoid Receptors (Hypothalamic-Pituitary-Adrenal Axis). . . . . . . . . . . . . . . . . . . . 4.1.2 b2-Adrenergic Receptors (the Sympathetic Nervous System) . . . . . . . . . . . . . . . . . . . . . . . 4.1.3 Estradiol and Immune Function . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1.4 Testosterone and Immune Function. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Abstract
621 622 622 622 623 624 624 625 625 625 626 626 627 627 627 628 629 629 629 630 631 632 632
This article reviews the interaction between the neuroendocrine and immune systems in response to exercise stress, considering gender differences. The body’s response to exercise stress is a system-wide effort coordinated by the integration between the immune and the neuroendocrine systems. Although considered distinct systems, increasing evidence supports the close communication between them. Like any stressor, the body’s response to exercise triggers a systematic series of neuroendocrine and immune events
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directed at bringing the system back to a state of homeostasis. Physical exercise presents a unique physiological stress where the neuroendocrine and immune systems contribute to accommodating the increase in physiological demands. These systems of the body also adapt to chronic overload, or exercise training. Such adaptations alleviate the magnitude of subsequent stress or minimize the exercise challenge to within homeostatic limits. This adaptive capacity of collaborating systems resembles the acquired, or adaptive, branch of the immune system, characterized by the memory capacity of the cells involved. Specific to the adaptive immune response, once a specific antigen is encountered, memory cells, or lymphocytes, mount a response that reduces the magnitude of the immune response to subsequent encounters of the same stress. In each case, the endocrine response to physical exercise and the adaptive branch of the immune system share the ability to adapt to a stressful encounter. Moreover, each of these systemic responses to stress is influenced by gender. In both the neuroendocrine responses to exercise and the adaptive (B lymphocyte) immune response, gender differences have been attributed to the ‘protective’ effects of estrogens. Thus, this review will create a paradigm to explain the neuroendocrine communication with leukocytes during exercise by reviewing (i) endocrine and immune interactions; (ii) endocrine and immune systems response to physiological stress; and (iii) gender differences (and the role of estrogen) in both endocrine response to physiological stress and adaptive immune response.
1. Neuroendocrine-Immune Interactions/Communication 1.1 Neuroendocrine and Immune System Interaction
The body’s response to stress is a system-wide effort, in part coordinated by the integration between the immune and the neuroendocrine systems.[1-3] This integration was recognized as early as 1855, when it was discovered that adrenal insufficiency was associated with elevated circulating lymphocytes.[4] The interface between the neuroendocrine and immune systems was further supported in 1924, when investigators removed the anterior pituitary gland from mice and realized that it resulted in atrophy of the thymus (the site of T-cell maturation).[5] Further evidence of this collaboration between the neuroendocrine and immune systems stemmed from findings that mice deficient in prolactin, growth hormones (GHs), and thyroid hormones were also deficient in lymphocyte development[6-8] and administration of these hormones reversed the deficiency.[6-8] Still further evidence of the importance of hormones ª 2011 Adis Data Information BV. All rights reserved.
to the immune response comes from studies that measured peripheral blood lymphocyte responsiveness in rats that had undergone surgical removal of pituitary, thyroid, adrenals or gonads.[9] When subjected to stress, rats that had the thyroid, adrenal or gonads removed had greater lymphocyte responsiveness, while animals without the pituitary gland had reduced lymphocyte responsiveness, implicating the importance of hormones in immune modulation.[9] 1.2 Neuroendocrine and Immune System Communication
The immune and neuroendocrine systems represent an integrated circuit of communication by virtue of sharing common signalling proteins and their affiliated receptors.[2,3,10] Most often cytokines, a specific class of signalling molecules, which can be produced by most cells in the body, including cells of the immune and neuroendocrine systems, are considered responsible for the communication between these two systems.[1] More specifically, lymphokines, a subset of cytokines Sports Med 2011; 41 (8)
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released specifically by lymphocytes, have been demonstrated to influence neuroendocrine tissues.[11] In addition to cytokines, cells of the immune system, including the lymphocytes themselves, are also able to synthesize biologically active neuroendocrine peptide hormones[10-14] including adrenocorticotropin (ACTH),[15] g-endorphin-related substances,[10] immunoreactive GH,[16] and thyrotropin.[17] These neuroendocrine polypeptide hormones are able to modulate lymphocyte and other immunocyte responses,[18-22] such as regulating the numbers of new B lymphocytes that are produced within the bone marrow.[23] Specifically, several hormones, including corticotropin-releasing hormone, ACTH, cortisol, dehydroepiandrosterone, estrogen, progesterone, testosterone, melatonin, prolactin, vasopressin, b-endorphin, other proopiomelanocortin peptides, thyrotropin-releasing hormone, and thyroid-stimulating hormone have been shown to interact with the immune system.[24,25] Since actions of both cytokines and hormones are mediated by receptor expression, only cells expressing the specific receptors deem the influence of the chemical signal. Peripheral and central localized receptors that transmit information through the cell are responsible for the precise regulation and control of these systems. Immune cells are not only able to produce hormones, they also possess target receptors for specific neuroendocrine peptides.[11] For example, lymphocytes have high-affinity receptors for ACTH, endorphins,[3] and high- and low-affinity opiate receptors.[18] Since leukocytes can produce hormones and also express receptors for the same hormones (e.g. ACTH and GH), it is possible that these immunocytes may also influence their own function in an autocrine-like fashion.[11] For example, the presence of both ACTH and its receptor on a B-lymphocytic cell line may demonstrate a possible autocrine function for this neuroendocrine hormone.[26] The evidence that cells of the immune and neuroendocrine systems share receptors implicates that these respective cells are likely targets of the responses. Moreover, a recent study describes the importance of several synergistic factors both locally and systemically, including cytokine, hormones, growth factors and immune cells in mediating physiological adaptations to exercise.[27] ª 2011 Adis Data Information BV. All rights reserved.
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Among the several signalling molecules responsible for communication between these two highly integrated systems, the ‘stress’ hormones, especially the catecholamines and cortisol, appear particularly involved in exercise-induced immune responses.[28] While the concentrations of these hormones elevate during exercise and return to baseline shortly after exercise, they seem to exert mobilizing effects on immune cells during the recovery period from exercise.[29] Catecholamines appear to be responsible for acute exercise effects on lymphocyte subpopulations.[29,30] Cortisol, on the other hand, appears to exert its effects within a time lag of at least 2 hours.[29,30] In addition to these ‘stress’ hormones, ‘sex’ hormones (estradiol and testosterone) also differentially interact with these bidirectional systems of communication in men and women.[31-35] Hence, this review will focus on catecholamines, cortisol, estrogen and testosterone in discussing neuroendocrine-immune interactions and communication. 1.3 Literature Search Methodology
Relevant literature was identified using a number of keyword search strings (contained in subheadings) in the U.S. National Library of Medicine’s PubMed database. The search period spanned from the database’s inception through to December 2010. From these searches, key papers were identified. Reference lists of the key papers were cross-referenced to supplement initial keyword searches. Additionally, investigators with expertise in neuroendocrine or immune responses to exercise and interactions between the neuroendocrine and immune systems were identified and author searches were conducted for additional relevant literature. To be considered, an article that provided evidence regarding one of the subheadings had to address neuroendocrine-immune interactions/communication, exercise-induced neuroendocrine responses, exercise-induced immune responses, or evidence of neuro-endocrine-immune responses mediating adaptations to exercise. Additionally, our search was cognizant to include papers discussing potential gender differences in light of the aforementioned sub-headings. Our review of the literature identified catecholmines Sports Med 2011; 41 (8)
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(epinephrine, norepinephrine), cortisol, estradiol, and testosterone and affiliated endocrine receptors as the most relevant hormones to neuroendocrine-immune interactions and responses to exercise. An EndNote database was developed to manage the search and review process. 2. Exercise-Induced Neuroendocrine Responses 2.1 Neuroendocrine Responses to Exercise
The body’s response to the stress of exercise can be explained by the General Adaptation Syndrome, described by Selye,[36] where the body prioritizes careful regulation of a tightly controlled internal environment. All systems of the human body (including the neuroendocrine and the immune systems) collaborate to maintain this tightly controlled internal environment. Disruptions in tightly regulated limits trigger physiological feedback mechanisms to maintain the constant internal milieu. Exercise presents a unique stress to these homeostatic conditions where the stress is specific to the nature and configurations of the protocol and associated elements (i.e. environmental conditions or nutritional status). During exercise, the neuroendocrine system is vital to maintaining homeostatic control. This system provides a specialized communication system in the body, allowing chemical messages in the form of hormones to be transported systemically to various target organs. The physiological responses of the neuroendocrine system in response to acute exercise are dependent on the intensity and the volume (sets · repetitions · intensity) of the exercise performed.[37] Resistance protocols, moderate to high intensity, high in volume, stressing large muscle mass and using short rest intervals produce the greatest acute hormonal elevations.[38] Despite changes in circulating concentrations, the response to these signals is dependent on the specialized and specific receptors for these hormones. Only cells expressing specific receptors can respond, providing an important means of physiological regulation and control. Thus, the neuroendocrine response to exercise stress is regulated by both the expression of the ª 2011 Adis Data Information BV. All rights reserved.
receptors in or on target cells and the circulating concentration of the hormone. Hormonal mechanisms appear to be involved with both short-term homeostatic control and longterm cellular adaptations to resistance exercise that prepare the body and reduce the magnitude of the stress on the next encounter, as reviewed by Kraemer and Ratamess.[37,38] In response to an acute resistance exercise bout, many specific circulating hormone concentrations elevate (e.g. GH, testosterone [in men], cortisol, epinephrine, norepinephrine).[37,38] Such elevations can be the result of a multitude of factors, including increased secretion, decreased uptake, decreased hepatic clearance, changes in plasma volume or reduced degradation. Regardless of the mechanism, the elevated circulating hormonal concentrations increase the likelihood of their binding to specific receptors on target tissues, triggering a physiological response. Additionally, the number of corresponding available receptors may also increase; further potentiating binding and the consequential initiation of a physiological cascade of events. The acute hormonal responses to resistance exercise, in part, mediate increases in strength, power, hypertrophy and local muscular endurance observed with resistance exercise training.[38] Animal models have demonstrated direct evidence of the endocrine receptor pathway in mediating muscle adaptations to exercise, via androgen receptor antagonist models.[39] Human muscle biopsy studies have also implicated the relevance of muscle steroid hormone receptor protein expression in mediating training adaptations to resistance exercise.[40-42] In addition, mechanicallyinduced signals within the muscle fibres, triggered by resistance exercise, contribute to protein synthesis and muscle hypertrophy.[43,44] Animal models have shown muscle hypertrophy via mechanicallyinduced signalling within muscle fibres, independent of a functioning insulin-like growth factor receptor.[44] It is the accumulation of these repeated physiological responses to acute exercise that cause the subsequent tissue remodelling, resulting in chronic adaptations to exercise training. A variety of resistance exercise protocols result in elevated peripheral hormonal concentrations. Single factor variables such as the intensity (percentage of repetition maximum) of exercise and amount Sports Med 2011; 41 (8)
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of muscle mass utilized in the exercise protocol are important determinants of the magnitude of the hormonal responses.[37] The volume (sets · repetitions · intensity) of exercise is also an important determinant of the hormonal response.[37] Higher volumes of total work as seen in multipleversus single-set resistance exercise protocols produce significantly greater elevations in circulating anabolic hormones (GH, testosterone, and wholeblood lactate) following exercise in men.[45] While several hormones respond to acute resistance exercise, those with evidence supporting their roles in the neuroendocrine-immune interactions in response to exercise stress are focused on in this review. 2.1.1 Catecholamines
The catecholamine (epinephrine, norepinephrine, dopamine) response to acute exercise reflects the acute demands of the exercise protocol.[46] An acute bout of resistance exercise elevates circulating catecholamine concentrations[47,48] to a magnitude dependent on the force of the muscle contraction, amount of muscle stimulated, volume of the resistance exercise and rest intervals.[48-50] During acute exercise, catecholamines are important for generating force, determining the rate of muscle contraction, regulating energy availability and influencing the responses of other hormones.[46] Moreover, an anticipatory rise in catecholamines[51] prior to heavy resistance exercise may be essential for optimal force production at the onset of exercise.[51] The release of catecholamines in response to cognitive (e.g. anxiety, physical discomfort, arousal)[46,52,53] and physical stress (e.g. cardiovascular demand, energy expenditure, H+ accumulation)[48,52] by sympathetic neurons and the adrenal medulla (primarily epinephrine) induces a host of haemodynamic, systemic, and metabolic effects.[54,55] In combination, these physiological responses redistribute blood flow, promote energy availability to support the force-requiring demands of high-intensity resistance exercise, and ultimately facilitate the contractile characteristics of skeletal muscle.[46,53,56,57] 2.1.2 Cortisol
Cortisol is a glucocorticoid released from the adrenal cortex in response to exercise stress. Alª 2011 Adis Data Information BV. All rights reserved.
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though mechanisms are not fully understood, cortisol is believed to play a role in the remodelling of tissue[38] in response to a bout of exercise. Glucocorticoids regulate muscle protein content by inhibiting muscle protein synthesis[58,59] and stimulating protein degradation,[59,60] likely via activation of the ubiquitin pathway.[60] More specifically, glucocorticoids have been shown to inhibit the actin and myosin heavy chain synthesis in all muscle fibre types. Additionally, on a larger scale, glucocorticoids appear to affect overall muscle mass and strength as polymorphisms in the glucocorticoid receptor genotyope have been shown to affect such measures.[61] Accordingly, circulating concentrations of both cortisol and ACTH, a hormone released from the pituitary gland that triggers cortisol release, elevate during an acute bout of exercise.[47,62-64] Resistance exercise protocols that stimulate the greatest lactate response seem to cause the greatest elevations in cortisol.[40,65] Additionally, the metabolic demands of the resistance exercise protocol influences the magnitude of the cortisol response with protocols high in total volume, intensity and short rest intervals eliciting larger responses.[48,62,66] Furthermore, protocols that result in the greatest concentrations of circulating creatine kinase (CK) 24-hours post-exercise, also result in the greatest elevations in circulating cortisol.[67] 2.1.3 Estradiol
Estrogen is an aromatized steroid hormone synthesized predominantly in the gonads and adipose tissue.[68] The most common circulating form is 17b-estradiol.[68] In females, most 17bestradiol is produced by the ovaries, with lesser amounts from the adrenal cortex and from peripheral testosterone aromatization. 17b-estradiol in males is produced from the adrenal cortex and from peripheral testosterone aromatization. Circulating estrogen concentrations do not differ markedly between men and women during the follicular phase of the menstrual cycle, when estrogen levels are lowest. Women, however, have cyclically higher concentrations of estrogen during the ovulatory period of the menstrual cycle and chronically higher concentrations throughout Sports Med 2011; 41 (8)
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pregnancy. While estradiol has been reported to play a protective role in muscle damage, little is known regarding the response of circulating estradiol to acute exercise. Perhaps the reason for this is the difficulty in phasing women during the menstrual cycle, when circulating estradiol concentrations are in flux. Nevertheless, in women, acute elevations in circulating estradiol following resistance exercise protocols have been reported.[69,70] Estradiol has also been reported to decrease post-exercise membrane disruption and structural damage.[71-74] Moreover, estradiol has also been reported to act as an antioxidant and membrane stabilizer in muscle.[75,76] 2.1.4 Testosterone
Testosterone is an important anabolic hormone for the muscle adaptations achieved with resistance exercise and training in men. The physiological actions of testosterone are modulated through the interaction with the intracellular androgen receptor. The elevated endogenous testosterone concentrations potentiate downstream androgen receptor responses to resistance exercise,[41] including the stimulation of protein synthetic pathways. The response of testosterone to acute resistance exercise is largely determined by the muscle mass involved, the intensity and volume of the protocol.[66,77-79] In men, acute resistance exercise results in transient elevations in endogenous testosterone concentrations,[64,78,80-83] which returns to baseline by 2 hours after the exercise.[83] In women, however, most studies report no elevations in circulating testosterone in response to acute resistance exercise.[62,69,77,80,84] Although, some resistance exercise protocols have observed transient elevations in healthy women.[85,86] Endurance exercise, on the other hand, appears to elicit some elevations in circulating testosterone in women.[87,88] Nevertheless, since women have an attenuated testosterone response to resistance exercise, as compared with men, GH appears to compensate for the anabolic requirements stimulated by resistance exercise in women.[77] Hence, testosterone responses to resistance exercise present a major gender difference between men and women. ª 2011 Adis Data Information BV. All rights reserved.
2.2 Gender Differences in Endocrine Response to Exercise
Men and women do not differ in specific strength, which is muscle force production scaled to skeletal muscle mass.[89] However, men and women do exhibit gender differences in exercise performance, fatigue and substrate metabolism during and in response to acute exercise. When matched for muscle strength, women fatigue more slowly and recover more quickly than men.[90,91] Additionally, when muscle damage is similar between men and women, the inflammatory response is attenuated in women.[34] Interestingly, however, under conditions of ischaemia, gender differences in fatigue to maximal voluntary isometric force production are eliminated.[92,93] Such evidence implicates the responsibility of circulating factors (i.e. estrogen and testosterone) in explaining gender differences in physiological exercise responses. Circulating endocrine responses to resistance exercise differ between men and women.[77] Specifically, serum testosterone significantly elevates in response to an acute resistance exercise bout in men,[64,77,78,80-83] while little or no elevations are apparent in women.[62,69,77,80,84] Additionally, during endurance exercise, women oxidize more lipid and less carbohydrate as compared with men.[35] Sex hormones, particularly 17b-estradiol, appear to be partly responsible for the greater fat oxidation seen in women, since administration of 17b-estradiol to men negates most of the sex differences in metabolism.[94] Estradiol has also been attributed for having a protective role in muscle during exercise stress.[74,95] Damage to skeletal muscle caused by certain exercise protocols can result in the efflux of several intramuscular proteins and enzymes into circulation, including CK, lactate dehydrogenase, aspartate aminotransferase and myoglobin,[96] which are measured in circulation. CK is the most commonly measured circulating marker of muscle damage.[97,98] Under resting conditions, women have lower CK activity in the blood as compared with men.[99,100] Additionally, in response to aerobic exercise protocols, women tend to have a lower CK response and less muscle damage than males.[101,102] This attenuation has often Sports Med 2011; 41 (8)
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been attributed to a protective role that estradiol plays as an antioxidant and membrane stabilizer during exercise with a relatively high oxidative stress.[74,95] However, some evidence shows that in response to resistance exercise protocols, women have greater CK responses, as compared with men.[103] Reasons for this discrepancy are unknown, but may be related to the exercise protocol or training status of study participants. 3. Exercise-Induced Immune Responses 3.1 Immune Responses to Exercise
Similar to the endocrine system, the immune system is also highly responsive to acute stressors.[104,105] In fact, the immune system can serve as a sensory organ for pathological states such as infectious diseases and tumours[16] or for external stimuli that cannot be detected by the nervous system.[106] Acute aerobic exercise elicits changes in circulating blood leukocyte counts (mainly lymphocytes and neutrophils).[107,108] The neutrophil concentration in circulation increases during exercise and continues to increase several hours post-exercise.[30] On the other hand, lymphocytes in circulation elevate during exercise, but drop during the recovery phase, with the most pronounced drop in lymphocytes below baseline being 2–6 hours post-exercise.[30] During the recovery period from exercise, the blood concentrations of all lymphocyte subpopulations (CD4+ T cells, CD8+ T cells, CD19+ B cells, CD16+ natural killer (NK) cells, and CD56+ NK cells) decrease. This effect is more pronounced for certain lymphocyte populations (CD8+ and NK).[107-110] The magnitude of such responses is determined by the intensity and the duration of the exercise,[111] where effects are most pronounced with endurance exercise protocols of longer durations (>1.5 hours) and greater intensities (55–75% maximum oxygen consumption).[111] Changes in circulating leukocyte numbers typically return to baseline within 3–24 hours following endurance exercise.[111] Although acute bouts of endurance exercise transiently impact immune function, basal immune function in chronically trained athletes does not appear to differ from non-athletes.[111] ª 2011 Adis Data Information BV. All rights reserved.
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While fewer studies exist examining the immune response to resistance exercise, it appears that in response to an acute resistance exercise bout, circulating leukocyte counts elevate, similar to aerobic exercise protocols.[112,113] Total circulating leukocyte counts have been reported to elevate during and following heavy resistance exercise in men.[112] Similarly, in women, circulating lymphocytes have been shown to elevate by ~62% in response to an intense resistance exercise protocol.[113] Long-term resistance exercise training, on the other hand, has been shown to reduce basal cytokine levels and reduce low-grade inflammation.[114,115] Additionally, animal models have shown that a single bout of resistance exercise can affect lymphoid cell subpopulation distributions in nodes of the immune system and in circulation.[116] In rats, resistance exercise has been shown to elevate the numbers of leukocytes in the thymus, axial and inguinal nodes but not in the blood or spleen.[116] However, the percentage of CD4+ cells increased after exercise in the thymus, spleen and blood.[116] Also, following exercise, leukocytes increase expression of activation markers, interleukin (IL)-2 receptor-a and major histocompatibility complex class II molecules.[116] Such effects are likely attributable to changes in leukocyte trafficking.[116] In addition, other circulating substances such as inflammatory cytokines, antiinflammatory cytokines and acute phase proteins that are known to influence leukocyte function, increase in response to exercise.[111] 3.2 Gender Differences in Immune Responses
Evidence of differences between men and women exist in response to immune challenges. Women generally show higher serum concentrations of the antibody molecule IgM, have a superior ability to form antibodies against infectious agents and experience a lower incidence of viral and bacterial infectious diseases.[117] More specifically, women appear to develop a much stronger immune response than men after infection,[118] which can attenuate the severity of infection (i.e. overall sickness and death).[119] Previous studies suggest that males are generally more susceptible Sports Med 2011; 41 (8)
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to respiratory diseases, viral and some bacterial infections and sepsis,[120-122] whereas females are more susceptible to many autoimmune diseases and have a greater immunoreactivity to particular pathogens.[31,32] For example, the female-to-male susceptibility ratio is 9 : 1 for systemic lupus erythematosus; 3 : 1 for multiple sclerosis; 4 : 1 for rheumatoid arthritis; and 9 : 1 for Sjogren’s syndrome.[123] Moreover, glucocorticoid receptor (GR) binding capacity of mononuclear leukocytes was found to be significantly greater in female children and adolescents than males.[124] Sex hormones are often attributed for such gender differences in the immune system.[31,33] Clinical and animal studies indicate that male hormones may suppress auto-antibody production, whereas female hormones support their production.[117] Gender differences in immune responses may also be due to differences in cytokine production.[125] Women have been shown to present a predominant Th2 (antibody-mediated) peripheral blood lymphocyte immune response as compared with men.[125] While men, on the other hand, show evidence of greater Th1 (cellmediated) cytokine production as compared with women.[125] Testosterone may explain a higher cytokine production in monocytes of men compared with women, since in vitro incubation of women’s monocytes with testosterone has been shown to increase cytokine production.[126] Males and females also differ in infection[127,128] and response to trauma.[129] Sex hormonal status is believed contribute to gender differences in infection, since animal models show reduced severity of infection in prepubertal male and female animals as compared with adult males.[128] Additionally, testosterone treatment to female animals has been shown to increase the severity of infection.[128] Moreover, the increased severity of disease in male compared with female animals was associated with significantly greater expression of cytokines (IL-4, IL-10, and transforming growth factor-b) in the cutaneous lesion.[128] In response to trauma, immune function is also severely depressed in males and aged females as compared with proestrus females.[129] Additionally, animal models reveal sex-related differences in T- and B-lymphocyte proliferative ability in ª 2011 Adis Data Information BV. All rights reserved.
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response to in vivo treatment with the endogenous opioid peptide met-enkephalin.[130] Specifically, met-enkephalin stimulates the proliferative ability of T- and B-cells in male mice, but not in female mice.[130] 3.3 Gender Differences in Immune Responses to Exercise
Although data are limited, some sex-based differences in immune, mainly lymphocyte, responses to endurance exercise have been observed.[131,132] For example, women have shown a 38% greater lymphocyte response to prolonged cycling exercise than men.[132] Additionally, positive correlations have been reported between circulating estrogen and CD19+ (B cells) cells in trained women in response to 1 hour of cycling during the latefollicular menstrual phase.[133] Animal models have also shown that females have a higher immune reactivity (quantified by a greater percentage of peripheral blood lymphocytes) as compared with males after exhaustive swimming.[134] Additionally, some evidence demonstrates that the immune system in female mice recovers to a greater extent following both exercise and a challenge with an infection than male mice, protecting female mice from death.[135] Women also demonstrate an attenuated inflammatory response to muscle damaging exercise than men, even when muscle damage is similar.[34] Some evidence suggests that this gender difference may be specific to women who are physically trained, since gender does not appear to influence lymphocyte apoptosis in response to maximal endurance exercise in untrained subjects.[136] Additionally, lymphocyte proliferation is reduced following acute heavy resistance exercise in women who were classified as ‘stronger’ (performed more work) than ‘weaker’ women.[45] However other evidence shows that lymphocyte proliferation responses appear similar between resistance trained and untrained women during resistance exercise.[137] Resistance training in women has been shown to transiently increase the concentration of circulating NK cells for 3 months.[137] However, elevations in NK cells were no longer present after 6 months of resistance training.[137] Thus, although Sports Med 2011; 41 (8)
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resistance training appears to impact the immune response to resistance exercise, more research is necessary to elucidate the mechanisms of trafficking and proliferation considering differences in the volume of muscle mass trained, the manner of training (power verses hypertrophy) and the time course of training adaptations. 4. Evidence that NeuroendocrineImmune Responses Mediate Adaptations to Exercise 4.1 Neuroendocrine and Immune System Communication
The hormonal changes that occur in response to exercise stress are known to modulate the immune responses.[111] More specifically, two main neuroendocrine pathways are activated in response to exercise stress that influence the immune system, the hypothalamic-pituitary-adrenal (HPA) axis and the sympathetic nervous system.[138] The HPA axis results in the release of glucocorticoids (cortisol), while the sympathetic nervous system, results in the release of catecholamines (epinephrine and norepinephrine). Both catecholamines and cortisol modulate the number, functioning, trafficking, and activity of immune cells.[139] Corresponding to the time frame of exercise-induced increases in circulating catecholamines, which increase in anticipation of exercise,[51] and cortisol, which increases after the onset of exercise,[112] neuroendocrine influences on immune cells appear to follow similar time courses. The early increase in circulating catecholamines mediates the acute earlier effects particularly on neutrophils and NK cells, which act as an early line of defense in muscle tissue inflammatory response to exerciseinduced injury,[140,141] whereas cortisol is more involved in neutrophilia, eosinopenia, lymphopenia, and a suppression of both NK- and T-cell function, all of which occur during recovery from high-intensity exercise.[142-144] The effects are mediated by the variety of immune-derived cells (lymphocytes and monocytes) that possess receptors for specific neuroendocrine-derived peptides and hormones. Leukocytes possess specific receptors for both catecholamines and cortisol.[145,146] These receptors are identical to recepª 2011 Adis Data Information BV. All rights reserved.
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tors present on cells of the endocrine and nervous systems.[147-149] Despite the indirect evidence of exercisestimulated neuroendocrine actions on immune cells, little has been published in regards to direct evidence of exercise-stimulated hormonal responses with simultaneous corresponding neuroendocrine receptor measures on immune cells. However, in a unique study, Dohi and colleagues[150] demonstrated that the receptor expression for prolactin, a peptide hormone, secreted primarily from the anterior pituitary gland, on B-lymphocytes increases in response to exercise in men.[150] Such work provides novel insights into the role of exercise in enhancing the interaction between immune target cells and prolactin, a stress hormone capable of enhancing immune function. However, regardless of evidence supporting the ‘stress’ hormone response to exercise and the stress hormone interactions with immune cells, to date, little is known in regards to responses to exercise and how ‘sex hormones’ potentially mediate such interactions. 4.1.1 Glucocorticoid Receptors (HypothalamicPituitary-Adrenal Axis)
In the HPA axis, corticotrophin releasing hormone is released from the hypothalamus. This hormone stimulates the anterior pituitary gland to secrete ACTH, which induces the adrenal gland to synthesize and secrete glucocorticoids, mainly cortisol.[138] Glucocorticoids exert biological effects on target cells through interacting with specific intracellular (cytosolic) steroid hormone receptors, GRs.[151,152] GRs are located in the cell cytoplasm in almost all nucleated cells,[153] including leukocytes.[145,154] Upon binding, the unit (composed of the hormone and the receptor) translocates to the nucleus and binds to specific acceptor sites on the DNA. The binding to DNA modulates the expression of the target genes, resulting in a cascade of biological events on the target cell.[151,152,155-158] Adrenal glucocorticoid secretion plays an important role in regulating immunological processes by suppressing and regulating inflammation.[159-161] Glucocorticoid hormones (e.g. cortisol) also impact the immune system by affecting immune-cell development, trafficking and functions.[153,162,163] Sports Med 2011; 41 (8)
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The level of GR expressed by lymphocytes is controlled via negative feedback, where elevated levels of glucocorticoids downregulate the GR expression.[154] An age-related decrease in the number of GRs in mononuclear leukocytes has been suggested between individuals younger than 20 years and elderly adults.[145] However, no significant gender differences appear in the number of GRs, although women have shown slightly fewer GRs.[145] Furthermore, GR on leukocytes does not seem to demonstrate seasonal variation.[145] Despite hypotheses based on indirect evidence of the interaction of exercise-induced increases in circulating cortisol on immune-cell function, to our knowledge little direct published evidence exists regarding this interaction. Our recent work[164] provides some insight into the temporal interactions between circulating cortisol and GR on B-lymphocytes in response to acute heavy resistance exercise in men and women. At rest, GR expression on B-lymphocytes was similar between men and women. In response to acute resistance exercise, GR expression on B-lymphocytes was elevated in anticipation of exercise, decreased during exercise, and increased during recovery at 1-hour and 6-hour post-exercise in both men and women, although women demonstrated a somewhat attenuated response. Circulating cortisol was elevated only during the exercise in men, but returned to baseline during recovery. This heavy acute resistance exercise protocol did not result in elevations in circulating cortisol in women, possibly explaining the observed attenuated receptor response in women. Although, we did not evaluate direct cellular interactions in this study, such work provides some valuable insights into the temporal pattern of possible interactions and gender differences in such responses. Further work evaluating direct cellular responses to cortisolGR binding would provide important insights as to how these systems interact to accommodate the stress imposed by exercise. 4.1.2 b2-Adrenergic Receptors (the Sympathetic Nervous System)
Catecholamines are released into the systemic blood supply upon activation of the sympathetic nervous system. They bind to the b2-adrenergic ª 2011 Adis Data Information BV. All rights reserved.
receptors on the plasma membrane of different target tissues. The coupling of cathecholamines (epinephrine, norepinephrine) with b2-adrenergic receptors is mediated through diverse G proteins and G protein-coupled receptor kinases. Such pathways influence physiological events including development, behaviour, cardiac function, smooth muscle tone and metabolism.[165-171] Catecholamines exert their effects on muscle tissue through b2-adrenergic receptors located on the surface the muscle cell. Via these specific receptors they stimulate electrogenic sodium and potassium ion transport and assist in membrane excitability and force generation.[172,173] The acute impact of catecholamines on the immune system is complex when considering Th1, Th2 and inflammatory pathways. In fact, it has been shown that the density of receptors on peripheral mononuclear leukocytes is influenced by health status.[169] Noradrenergic nerve terminals directly innervate tissues where immune cells are produced and reside.[174] Hence, an important effect of catecholamines on the immune system is to pull these leukocytes into circulation from such storage sites.[175] The movement of lymphocytes and neutrophils into circulation is stimulated by increased intracellular cyclic adenosine monophosphate from the binding of epinephrine to b2-adrenergic receptors.[176,177] Despite research supporting the interaction of catecholamines with b2-adrenergic receptors in immune-cell mobilization, the direct exercise effects of such interactions are unknown to date. Our recent work[178] provides some insight into the temporal interactions between plasma epinephrine and norepinephrine and b2-adrenergic expression on circulating leukocytes in response to acute heavy resistance exercise in men and women. In response to acute heavy resistance exercise we found that b2-adrenergic expression on leukocyte subpopulations changes in response to the exercise stress and the temporal pattern of such changes vary by immune-cell population. b2-adrenergic expression was elevated in anticipation of the exercise protocol on monocytes, decreased during the exercise on monocytes and granulocytes, and was elevated during the recovery on lymphocytes. Simultaneously, plasma Sports Med 2011; 41 (8)
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epinephrine and norepinephrine increased during the exercise bout and returned to baseline during recovery. No differences in circulating catecholamines or receptor expression were apparent between men and women. Such findings indicate the complexity of the neuroendocrine interaction in response to exercise stress and implicate little impact of sex hormones on such pathways. However, further work is needed to evaluate direct cellular responses and how such findings translate to other exercise protocols and populations. 4.1.3 Estradiol and Immune Function
While estradiol is considered primarily for its role in reproduction, it also can exert numerous physiological actions on a variety of tissues.[179] In fact, endocrine differences mediated by estradiol may even contribute towards the longer expected lifespan in women as compared with men.[180] Women have an expected lifespan of 4.2 years greater than men, which is projected to increase to 4.8 years by the year 2050.[181] This discrepancy is likely attributed to the delayed incidence of cardiovascular disease in women compared with men,[180] possibly mediated by estradiol. Estradiol also appears to play a mediating role in immune function. However, its effects on the immune system appear to be dichotomous. For example, in mice, estrogen exposure appears to stimulate antibody production[182] but decreases T-cell-mediated delayed-type hypersensitivity,[182,183] granulocyte-mediated inflammation[184] and NKcell-mediated cytotoxicity.[185,186] Sex steroids, including estrogen, participate in normal, steadystate control of the creation of T and B lymphocytes (lymphopoiesis).[187-191] Specifically, certain critical events in lymphopoiesis are negatively regulated by estradiol.[190,191] Additionally, during pregnancy, when estrogen levels are naturally elevated, lymphopoiesis is suppressed.[192] On the contrary, B lymphopoiesis is elevated in conditions of estrogen deficiency.[188] For example, hormone-deficient, hypogonadal or castrated mice were shown to have elevated numbers of B-cell precursors.[187-189] Estrogen replacement to these mice reduced numbers of B-cell precursors to within the normal range.[187-189] Interestingly, changes in reproductive hormones associated with the ª 2011 Adis Data Information BV. All rights reserved.
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menstrual cycle have no appreciable effect on lymphocyte numbers or their response to acute stress.[193] Such findings are possibly attributed to the long-term duration of estrogen’s action, exceeding the window of time afforded by the menstrual cycle.[193] Estrogen has also been shown to modulate B-cell tolerance, development and differentiation.[194] Additionally, sustained exposure to estrogen causes a reduction of IL-7-responsive cells and pre-B cells in the marrow, as well as newly made B cells in the periphery.[190] Moreover, estradiol suppresses IL-2 and its receptor.[195] Many of the biological effects of estrogen are mediated by binding of this steroid hormone to two distinct intracellular receptors,[196] estrogen receptor (ER)-a and ER-b which are members of the nuclear receptor super family of transcription factors.[197,198] Both ER-a and ER-b are present in lymphocytes,[199] with different levels depending on the subtype. CD4+ T cells (helper) express higher levels of ER-a than ER-b, whereas B cells exhibit the opposite pattern and express higher levels of ER-b than ER-a.[199] CD8+ T cells (cytotoxic) express only very low but comparable levels of both.[199] The levels of ER-a and ER-b expression in CD4+ T cells do not appear to be affected by the hormonal status or by the presence of different activation stimuli. Yet, positive correlations have been reported between estradiol and B (CD19+) cells.[133] It is possible that the molecular mechanisms that control ER expression may differ between T-cell subsets (e.g. CD4+ ,CD8+ T, CD4+ T cells ) and other immune cell types (e.g. B cells).[199] Estradiol has also been shown to have an antiinflammatory effect.[200-202] In fact, systemic administration of estradiol has been shown to attenuate both expression of inflammatory mediators and infiltration of leukocytes following vascular injury.[201,202] Estradiol also appears to modulate neutrophil chemotaxis via attenuating expression of cytokine-induced neutrophil chemoattractant.[203,204] Moreover, estrogen appears to modulate tumour necrosis factor (TNF)-ainduced inflammatory responses in rat aortic smooth muscle cells through ER-b activation.[205] Evidence also exists supporting a synergistic role between estrogen with glucocorticoids. For Sports Med 2011; 41 (8)
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example, glucocorticoid sensitivity is increased at higher estradiol concentrations.[206,207] Additionally, synthetic estrogen and oral contraceptive administration results in elevated of cortisol concentrations.[208,209] Moreover, in relation to testosterone, estradiol stabilizes or increases immune stimuli-induced secretion of certain cytokines (TNF, IL-2, IL-4, IL-6, IL-10 and IFN-g) on peripheral blood leukocytes of healthy male subjects in the presence of cortisol.[210] Despite its anti-inflammatory role in other ‘injury’ models, mechanisms as to how estradiol may potentially play a protective role in the immune response to exercise stress remains to be studied. Although the protective role of estradiol in both inflammatory responses and membrane stabilization[71-76] provide interesting hypotheses, its role in the neuroendocrine-immune interactions in response to exercise stress remains to be understood. 4.1.4 Testosterone and Immune Function
Testosterone also appears to impact immune function, as cells of the immune system including macrophages, lymphocytes and vascular smooth muscle cells all possess androgen receptors.[211-213] Evidence of this interaction is apparent in a biofeedback loop where specific cytokines appear to impair synthesis and release of testosterone,[214] while testosterone inhibits the secretion of specific cytokines (IL-2, IL-4, IL-10, TNF, IFNg).[210] Interestingly, this interaction appears to primarily impact cell-mediated immunity, since testosterone has been shown to increase the percentage of IL-12- and IL-1b-producing monocytes,[126] while having no effect on IL-2- and IFNg-producing lymphocytes.[126] Additionally, when comparing male lymphocytes with female lymphocytes, male lymphocytes demonstrate increased type 1 (cellmediated)[215] cytokine (IFN-c and IL-2) production[125] and decreased type 2 (humoral)[215] cytokine (IL-10 and IL-4) production.[125] Moreover, in contrast to estradiol, testosterone inhibits cytokine (IL-2, IL-4, IL-10) production and secretion (TNF, IFNg) on peripheral blood leukocytes of healthy male subjects.[210] Research on how testosterone interacts with the immune system to modulate exercise-induced responses remains to be reported. However, reª 2011 Adis Data Information BV. All rights reserved.
cent research suggesting that expression of steroid hormone receptors could correlate with the presence of inflammation during infection[216] and existing knowledge of the role of testosterone in muscle regeneration[217,218] provide an interesting mechanism to examine in an exercise model in future work. 5. Conclusions While several studies exist in the literature examining neuroendocrine or immune responses to exercise stress, few have examined the neuroendocrine-immune communication in response to exercise. Existing research on immune responses to exercise typically characterizes the number of leukocyte subsets in circulation, but data are sparse in examining function or receptor presence that often dictates how a cell will respond. Further research is needed to identify the factors that trigger the synthesis of neuroendocrine hormones by immune cells and to understand the factors controlling neuroendocrine hormone receptor expression on immune cells.[16] Furthermore, to our knowledge, few studies exist that examine gender differences in neuroendocrine-immune interaction responses to exercise. Since some evidence suggests that immune responses to acute stress differ in men and women, it is hoped that future studies will provide further knowledge on gender differences in immune responses to a challenge. Examining immune parameters to exercise stress is a natural approach to determining possible mechanisms underlying gender differences in other immune challenges and disease risks. Since evidence demonstrates interaction of estrogen and testosterone with immune-cell function, it is feasible to hypothesize that such work will have implications towards understanding differing drug actions and disease progression between men and women. Thus, further studies examining neuroendocrine-immune interactions in response to exercise, with consideration of gender interactions, will not only help us to understand mechanisms of physiological system communication in response to stress, but it may also hold the potential for providing knowledge to aid in the development of drugs and therapies specific to a certain gender. Sports Med 2011; 41 (8)
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Acknowledgements No sources of funding were used to assist in the preparation of this review. The authors have no conflicts of interests that are directly relevant to the content of this review.
References 1. Chrousos GP. The hypothalamic-pituitary-adrenal axis and immune-mediated inflammation. N Engl J Med 1995 May 18; 332 (20): 1351-62 2. Blalock JE, Harbour-McMenamin D, Smith EM. Peptide hormones shared by the neuroendocrine and immunologic systems. J Immunol 1985 Aug; 135 (2 Suppl.): 858s-61s 3. Blalock JE, Smith EM. A complete regulatory loop between the immune and neuroendocrine systems. Fed Proc 1985 Jan; 44 (1 Pt 1): 108-11 4. Addison T. On the constitutional and local effects of the suprarenal capsules. London: Highley; 1855 5. Jaffe HL. The influence of the suprarenal gland on the thymus. III: stimulation of the growth of the thymus gland following double suprarenalectomy in young rats. J Exp Med 1924; 40: 753-60 6. Berczi I, Nagy E, Kovacs K, et al. Regulation of humoral immunity in rats by pituitary hormones. Acta Endocrinol (Copenh) 1981 Dec; 98 (4): 506-13 7. Nagy E, Berczi I. Immunodeficiency in hypophysectomized rats. Acta Endocrinol (Copenh) 1978 Nov; 89 (3): 530-7 8. Nagy E, Berczi I, Friesen HG. Regulation of immunity in rats by lactogenic and growth hormones. Acta Endocrinol (Copenh) 1983 Mar; 102 (3): 351-7 9. Bonnyns M, McKenzie JM. Interactions of stress and endocrine status on rat peripheral lymphocyte responsiveness to phytomitogens. Psychoneuroendocrinology 1979 Jan; 4 (1): 67-73 10. Smith EM, Blalock JE. Human lymphocyte production of corticotropin and endorphin-like substances: association with leukocyte interferon. Proc Natl Acad Sci U S A 1981 Dec; 78 (12): 7530-4 11. Weigent DA, Blalock JE. Interactions between the neuroendocrine and immune systems: common hormones and receptors. Immunol Rev 1987 Dec; 100: 79-108 12. Smith EM, Blalock JE. The hormonal nature of the interferon system. Tex Rep Biol Med 1981; 41: 350-8 13. Smith EM, Blalock JE. A molecular basis for interactions between the immune and neuroendocrine systems. Int J Neurosci 1988 Feb; 38 (3-4): 455-64 14. Blalock JE, Smith EM. Human leukocyte interferon: structural and biological relatedness to adrenocorticotropic hormone and endorphins. Proc Natl Acad Sci U S A 1980 Oct; 77 (10): 5972-4 15. Meyer 3rd WJ, Smith EM, Richards GE, et al. In vivo immunoreactive adrenocorticotropin (ACTH) production by human mononuclear leukocytes from normal and ACTH-deficient individuals. J Clin Endocrinol Metab 1987 Jan; 64 (1): 98-105 16. Weigent DA, Baxter JB, Wear WE, et al. Production of immunoreactive growth hormone by mononuclear leukocytes. Faseb J 1988 Sep; 2 (12): 2812-8
ª 2011 Adis Data Information BV. All rights reserved.
633
17. Smith EM, Phan M, Kruger TE, et al. Human lymphocyte production of immunoreactive thyrotropin. Proc Natl Acad Sci U S A 1983 Oct; 80 (19): 6010-3 18. Johnson HM, Smith EM, Torres BA, et al. Regulation of the in vitro antibody response by neuroendocrine hormones. Proc Natl Acad Sci U S A 1982 Jul; 79 (13): 4171-4 19. Besedovsky H, Sorkin E. Network of immune-neuroendocrine interactions. Clin Exp Immunol 1977 Jan; 27 (1): 1-12 20. Cupps TR, Edgar LC, Fauci AS. Corticosteroid-induced modulation of immunoglobulin secretion by human B lymphocytes: potentiation of background mitogenic signals. J Immunopharmacol 1982; 4 (4): 255-63 21. Hazum E, Chang KJ, Cuatrecasas P. Opiate (Enkephalin) receptors of neuroblastoma cells: occurrence in clusters on the cell surface. Science 1979 Nov 30; 206 (4422): 1077-9 22. Wybran J, Appelboom T, Famaey JP, et al. Suggestive evidence for receptors for morphine and methionineenkephalin on normal human blood T lymphocytes. J Immunol 1979 Sep; 123 (3): 1068-70 23. Kincade PW, Medina KL, Payne KJ, et al. Early B-lymphocyte precursors and their regulation by sex steroids. Immunol Rev 2000 Jun; 175: 128-37 24. Blalock JE. Production of peptide hormones and neurotransmitters by the immune system. Chem Immunol 1992; 52: 1-24 25. Blalock JE, Costa O. Immune neuroendocrine interactions: implications for reproductive physiology. Ann N Y Acad Sci 1989; 564: 261-6 26. Bost KL, Smith EM, Wear LB, et al. Presence of ACTH and its receptor on a B lymphocytic cell line: a possible autocrine function for a neuroendocrine hormone. J Biol Regul Homeost Agents 1987 Jan-Mar; 1 (1): 23-7 27. Malm C, Sjodin TL, Sjoberg B, et al. Leukocytes, cytokines, growth factors and hormones in human skeletal muscle and blood after uphill or downhill running. J Physiol 2004 May 1; 556 (Pt 3): 983-1000 28. Pedersen BK, Bruunsgaard H, Klokker M, et al. Exerciseinduced immunomodulation: possible roles of neuroendocrine and metabolic factors. Int J Sports Med 1997 Mar; 18 Suppl. 1: S2-7 29. Pedersen BK, Rohde T, Ostrowski K. Recovery of the immune system after exercise. Acta Physiol Scand 1998 Mar; 162 (3): 325-32 30. McCarthy DA, Dale MM. The leucocytosis of exercise: a review and model. Sports Med 1988 Dec; 6 (6): 333-63 31. Grossman CJ. Regulation of the immune system by sex steroids. Endocr Rev 1984 Summer; 5 (3): 435-55 32. Gulshan S, McCruden AB, Stimson WH. Oestrogen receptors in macrophages. Scand J Immunol 1990 Jun; 31 (6): 691-7 33. Schuurs AH, Verheul HA. Effects of gender and sex steroids on the immune response. J Steroid Biochem 1990 Feb; 35 (2): 157-72 34. Stupka N, Lowther S, Chorneyko K, et al. Gender differences in muscle inflammation after eccentric exercise. J Appl Physiol 2000 Dec; 89 (6): 2325-32 35. Tarnopolsky MA. Sex differences in exercise metabolism and the role of 17-beta estradiol. Med Sci Sports Exerc 2008 Apr; 40 (4): 648-54 36. Selye H. General Adaptation syndrome and disease adaptation. J Clin Endocrinol Metab 1946 Feb; 6: 117-230
Sports Med 2011; 41 (8)
634
37. Kraemer WJ. Endocrine responses to resistance exercise. Med Sci Sports Exerc 1988 Oct; 20 (5 Suppl.): S152-7 38. Kraemer WJ, Ratamess NA. Hormonal responses and adaptations to resistance exercise and training. Sports Med 2005; 35 (4): 339-61 39. Inoue K, Yamasaki S, Fushiki T, et al. Androgen receptor antagonist suppresses exercise-induced hypertrophy of skeletal muscle. Eur J Appl Physiol Occup Physiol 1994; 69 (1): 88-91 40. Ratamess NA, Kraemer WJ, Volek JS, et al. Androgen receptor content following heavy resistance exercise in men. J Steroid Biochem Mol Biol 2005 Jan; 93 (1): 35-42 41. Spiering BA, Kraemer WJ, Vingren JL, et al. Elevated endogenous testosterone concentrations potentiate muscle androgen receptor responses to resistance exercise. J Steroid Biochem Mol Biol 2009 Apr; 114 (3-5): 195-9 42. Vingren JL, Kraemer WJ, Hatfield DL, et al. Effect of resistance exercise on muscle steroid receptor protein content in strength-trained men and women. Steroids 2009 Nov-Dec; 74 (13-14): 1033-9 43. Hornberger TA, Esser KA. Mechanotransduction and the regulation of protein synthesis in skeletal muscle. Proc Nutr Soc 2004 May; 63 (2): 331-5 44. Spangenburg EE, Le Roith D, Ward CW, et al. A functional insulin-like growth factor receptor is not necessary for load-induced skeletal muscle hypertrophy. J Physiol 2008 Jan 1; 586 (1): 283-91 45. Dohi K, Mastro AM, Miles MP, et al. Lymphocyte proliferation in response to acute heavy resistance exercise in women: influence of muscle strength and total work. Eur J Appl Physiol 2001 Aug; 85 (3-4): 367-73 46. Kraemer WJ, Ratamess NA. Endocrine responses and adaptations to strength and power training. In: Komi PV, editor. Strength and power in sport. 2nd ed. Malden (MA): Blackwell Scientific Publications; 2003: 361-86 47. Kraemer WJ, Fleck SJ, Maresh CM, et al. Acute hormonal responses to a single bout of heavy resistance exercise in trained power lifters and untrained men. Can J Appl Physiol 1999 Dec; 24 (6): 524-37 48. Kraemer WJ, Noble BJ, Clark MJ, et al. Physiologic responses to heavy-resistance exercise with very short rest periods. Int J Sports Med 1987 Aug; 8 (4): 247-52 49. Bush JA, Kraemer WJ, Mastro AM, et al. Exercise and recovery responses of adrenal medullary neurohormones to heavy resistance exercise. Med Sci Sports Exerc 1999 Apr; 31 (4): 554-9 50. Mikkelsen UR, Gissel H, Fredsted A, et al. Excitation-induced cell damage and beta2-adrenoceptor agonist stimulated force recovery in rat skeletal muscle. Am J Physiol Regul Integr Comp Physiol 2006 Feb; 290 (2): R265-72 51. French DN, Kraemer WJ, Volek JS, et al. Anticipatory responses of catecholamines on muscle force production. J Appl Physiol 2007 Jan; 102 (1): 94-102 52. Kraemer WJ, Patton JF, Knuttgen HG, et al. Effects of high-intensity cycle exercise on sympathoadrenal-medullary response patterns. J Appl Physiol 1991 Jan; 70 (1): 8-14 53. Tod D, Iredale F, Gill N. ‘Psyching-up’ and muscular force production. Sports Med 2003; 33 (1): 47-58 54. Mazzeo RS. Catecholamine responses to acute and chronic exercise. Med Sci Sports Exerc 1991 Jul; 23 (7): 839-45
ª 2011 Adis Data Information BV. All rights reserved.
Fragala et al.
55. Richter EA, Sonne B, Christensen NJ, et al. Role of epinephrine for muscular glycogenolysis and pancreatic hormonal secretion in running rats. Am J Physiol 1981 May; 240 (5): E526-32 56. Dienstbier RA. Behavioral correlates of sympathoadrenal reactivity: the toughness model. Med Sci Sports Exerc 1991 Jul; 23 (7): 846-52 57. Fry AC, Kraemer WJ, Stone MH, et al. Endocrine responses to overreaching before and after 1 year of weightlifting. Can J Appl Physiol 1994 Dec; 19 (4): 400-10 58. Dardevet D, Sornet C, Savary I, et al. Glucocorticoid effects on insulin- and IGF-I-regulated muscle protein metabolism during aging. J Endocrinol 1998 Jan; 156 (1): 83-9 59. Hickson RC, Czerwinski SM, Falduto MT, et al. Glucocorticoid antagonism by exercise and androgenic-anabolic steroids. Med Sci Sports Exerc 1990 Jun; 22 (3): 331-40 60. Auclair D, Garrel DR, Chaouki Zerouala A, et al. Activation of the ubiquitin pathway in rat skeletal muscle by catabolic doses of glucocorticoids. Am J Physiol 1997 Mar; 272 (3 Pt 1): C1007-16 61. Peeters GM, van Schoor NM, van Rossum EF, et al. The relationship between cortisol, muscle mass and muscle strength in older persons and the role of genetic variations in the glucocorticoid receptor. Clin Endocrinol (Oxf) 2008 Oct; 69 (4): 673-82 62. Kraemer WJ, Fleck SJ, Dziados JE, et al. Changes in hormonal concentrations after different heavy-resistance exercise protocols in women. J Appl Physiol 1993 Aug; 75 (2): 594-604 63. Kraemer WJ, Fry AC, Warren BJ, et al. Acute hormonal responses in elite junior weightlifters. Int J Sports Med 1992 Feb; 13 (2): 103-9 64. Kraemer WJ, Hakkinen K, Newton RU, et al. Effects of heavyresistance training on hormonal response patterns in younger vs. older men. J Appl Physiol 1999 Sep; 87 (3): 982-92 65. Kraemer WJ, Fleck SJ, Callister R, et al. Training responses of plasma beta-endorphin, adrenocorticotropin, and cortisol. Med Sci Sports Exerc 1989 Apr; 21 (2): 146-53 66. Hakkinen K, Pakarinen A. Acute hormonal responses to two different fatiguing heavy-resistance protocols in male athletes. J Appl Physiol 1993 Feb; 74 (2): 882-7 67. Kraemer WJ, Dziados JE, Marchitelli LJ, et al. Effects of different heavy-resistance exercise protocols on plasma beta-endorphin concentrations. J Appl Physiol 1993 Jan; 74 (1): 450-9 68. Simpson ER, Mahendroo MS, Means GD, et al. Aromatase cytochrome P450, the enzyme responsible for estrogen biosynthesis. Endocr Rev 1994 Jun; 15 (3): 342-55 69. Kraemer RR, Heleniak RJ, Tryniecki JL, et al. Follicular and luteal phase hormonal responses to low-volume resistive exercise. Med Sci Sports Exerc 1995 Jun; 27 (6): 809-17 70. Walberg-Rankin J, Franke WD, Gwazdauskas FC. Response of beta-endorphin and estradiol to resistance exercise in females during energy balance and energy restriction. Int J Sports Med 1992 Oct; 13 (7): 542-7 71. Amelink GJ, Kamp HH, Bar PR. Creatine kinase isoenzyme profiles after exercise in the rat: sex-linked differences in leakage of CK-MM. Pflugers Arch 1988 Sep; 412 (4): 417-21
Sports Med 2011; 41 (8)
Neuroendocrine-Immune Interactions
72. Amelink GJ, Koot RW, Erich WB, et al. Sex-linked variation in creatine kinase release, and its dependence on oestradiol, can be demonstrated in an in-vitro rat skeletal muscle preparation. Acta Physiol Scand 1990 Feb; 138 (2): 115-24 73. Amelink GJ, van der Wal WA, Wokke JH, et al. Exerciseinduced muscle damage in the rat: the effect of vitamin E deficiency. Pflugers Arch 1991 Oct; 419 (3-4): 304-9 74. Bar PR, Amelink GJ, Oldenburg B, et al. Prevention of exercise-induced muscle membrane damage by oestradiol. Life Sci 1988; 42 (26): 2677-81 75. Subbiah MT, Kessel B, Agrawal M, et al. Antioxidant potential of specific estrogens on lipid peroxidation. J Clin Endocrinol Metab 1993 Oct; 77 (4): 1095-7 76. Tiidus PM. Can estrogens diminish exercise induced muscle damage? Can J Appl Physiol 1995 Mar; 20 (1): 26-38 77. Kraemer WJ, Gordon SE, Fleck SJ, et al. Endogenous anabolic hormonal and growth factor responses to heavy resistance exercise in males and females. Int J Sports Med 1991 Apr; 12 (2): 228-35 78. Kraemer WJ, Marchitelli L, Gordon SE, et al. Hormonal and growth factor responses to heavy resistance exercise protocols. J Appl Physiol 1990 Oct; 69 (4): 1442-50 79. Volek JS, Kraemer WJ, Bush JA, et al. Testosterone and cortisol in relationship to dietary nutrients and resistance exercise. J Appl Physiol 1997 Jan; 82 (1): 49-54 80. Hakkinen K, Pakarinen A. Acute hormonal responses to heavy resistance exercise in men and women at different ages. Int J Sports Med 1995 Nov; 16 (8): 507-13 81. Hickson RC, Hidaka K, Foster C, et al. Successive time courses of strength development and steroid hormone responses to heavy-resistance training. J Appl Physiol 1994 Feb; 76 (2): 663-70 82. Weiss LW, Cureton KJ, Thompson FN. Comparison of serum testosterone and androstenedione responses to weight lifting in men and women. Eur J Appl Physiol Occup Physiol 1983; 50 (3): 413-9 83. Jensen J, Oftebro H, Breigan B, et al. Comparison of changes in testosterone concentrations after strength and endurance exercise in well trained men. Eur J Appl Physiol Occup Physiol 1991; 63 (6): 467-71 84. Kraemer WJ, Staron RS, Hagerman FC, et al. The effects of short-term resistance training on endocrine function in men and women. Eur J Appl Physiol Occup Physiol 1998 Jun; 78 (1): 69-76 85. Cumming DC, Wall SR, Galbraith MA, et al. Reproductive hormone responses to resistance exercise. Med Sci Sports Exerc 1987 Jun; 19 (3): 234-8 86. Nindl BC, Kraemer WJ, Gotshalk LA, et al. Testosterone responses after resistance exercise in women: influence of regional fat distribution. Int J Sport Nutr Exerc Metab 2001 Dec; 11 (4): 451-65 87. Consitt LA, Copeland JL, Tremblay MS. Hormone responses to resistance vs. endurance exercise in premenopausal females. Can J Appl Physiol 2001 Dec; 26 (6): 574-87 88. Enea C, Boisseau N, Ottavy M, et al. Effects of menstrual cycle, oral contraception, and training on exerciseinduced changes in circulating DHEA-sulphate and testosterone in young women. Eur J Appl Physiol 2009 Jun; 106 (3): 365-73
ª 2011 Adis Data Information BV. All rights reserved.
635
89. Kent-Braun JA, Ng AV. Specific strength and voluntary muscle activation in young and elderly women and men. J Appl Physiol 1999 Jul; 87 (1): 22-9 90. Fulco CS, Rock PB, Muza SR, et al. Slower fatigue and faster recovery of the adductor pollicis muscle in women matched for strength with men. Acta Physiol Scand 1999 Nov; 167 (3): 233-9 91. Hunter SK, Enoka RM. Changes in muscle activation can prolong the endurance time of a submaximal isometric contraction in humans. J Appl Physiol 2003 Jan; 94 (1): 108-18 92. Kent-Braun JA, Ng AV, Doyle JW, et al. Human skeletal muscle responses vary with age and gender during fatigue due to incremental isometric exercise. J Appl Physiol 2002 Nov; 93 (5): 1813-23 93. Russ DW, Kent-Braun JA. Sex differences in human skeletal muscle fatigue are eliminated under ischemic conditions. J Appl Physiol 2003 Jun; 94 (6): 2414-22 94. Carter S, McKenzie S, Mourtzakis M, et al. Short-term 17beta-estradiol decreases glucose R(a) but not whole body metabolism during endurance exercise. J Appl Physiol 2001 Jan; 90 (1): 139-46 95. Komulainen J, Koskinen SO, Kalliokoski R, et al. Gender differences in skeletal muscle fibre damage after eccentrically biased downhill running in rats. Acta Physiol Scand 1999 Jan; 165 (1): 57-63 96. Tarnopolsky M, editor. Gender differences in metabolism: practical and nutritional implications. Boca Raton (FL): CRC Press; 1999 97. Mair J, Koller A, Artner-Dworzak E, et al. Effects of exercise on plasma myosin heavy chain fragments and MRI of skeletal muscle. J Appl Physiol 1992 Feb; 72 (2): 656-63 98. Nosaka K, Clarkson PM, Apple FS. Time course of serum protein changes after strenuous exercise of the forearm flexors. J Lab Clin Med 1992 Feb; 119 (2): 183-8 99. Harris EK, Wong ET, Shaw Jr ST. Statistical criteria for separate reference intervals: race and gender groups in creatine kinase. Clin Chem 1991 Sep; 37 (9): 1580-2 100. Norton JP, Clarkson PM, Graves JE, et al. Serum creatine kinase activity and body composition in males and females. Hum Biol 1985 Dec; 57 (4): 591-8 101. Apple FS, Rogers MA, Casal DC, et al. Skeletal muscle creatine kinase MB alterations in women marathon runners. Eur J Appl Physiol Occup Physiol 1987; 56 (1): 49-52 102. Shumate JB, Brooke MH, Carroll JE, et al. Increased serum creatine kinase after exercise: a sex-linked phenomenon. Neurology 1979 Jun; 29 (6): 902-4 103. Nuttall FQ, Jones B. Creatine kinase and glutamic oxalacetic transaminase activity in serum: kinetics of change with exercise and effect of physical conditioning. J Lab Clin Med 1968 May; 71 (5): 847-54 104. Herbert TB, Cohen S. Stress and immunity in humans: a meta-analytic review. Psychosom Med 1993 Jul-Aug; 55 (4): 364-79 105. Kiecolt-Glaser JK, Cacioppo JT, Malarkey WB, et al. Acute psychological stressors and short-term immune changes: what, why, for whom, and to what extent? Psychosom Med 1992 Nov-Dec; 54 (6): 680-5 106. Blalock JE. The immune system as a sensory organ. J Immunol 1984 Mar; 132 (3): 1067-70
Sports Med 2011; 41 (8)
Fragala et al.
636
107. Shek PN, Sabiston BH, Buguet A, et al. Strenuous exercise and immunological changes: a multiple-time-point analysis of leukocyte subsets, CD4/CD8 ratio, immunoglobulin production and NK cell response. Int J Sports Med 1995 Oct; 16 (7): 466-74 108. Simpson RJ, Florida-James GD, Whyte GP, et al. The effects of intensive, moderate and downhill treadmill running on human blood lymphocytes expressing the adhesion/activation molecules CD54 (ICAM-1), CD18 (beta2 integrin) and CD53. Eur J Appl Physiol 2006 May; 97 (1): 109-21 109. Gannon GA, Rhind SG, Shek PN, et al. Differential cell adhesion molecule expression and lymphocyte mobilisation during prolonged aerobic exercise. Eur J Appl Physiol 2001 Apr; 84 (4): 272-82 110. Simpson RJ, Cosgrove C, Ingram LA, et al. Senescent T-lymphocytes are mobilised into the peripheral blood compartment in young and older humans after exhaustive exercise. Brain Behav Immun 2008 May; 22 (4): 544-51 111. Gleeson M. Immune function in sport and exercise. J Appl Physiol 2007 Aug; 103 (2): 693-9 112. Kraemer WJ, Clemson A, Triplett NT, et al. The effects of plasma cortisol elevation on total and differential leukocyte counts in response to heavy-resistance exercise. Eur J Appl Physiol Occup Physiol 1996; 73 (1-2): 93-7 113. Miles MP, Leach SK, Kraemer WJ, et al. Leukocyte adhesion molecule expression during intense resistance exercise. J Appl Physiol 1998 May; 84 (5): 1604-9 114. Calle MC, Fernandez ML. Effects of resistance training on the inflammatory response. Nutr Res Pract 2010 Aug; 4 (4): 259-69 115. Mathur N, Pedersen BK. Exercise as a mean to control low-grade systemic inflammation. Mediators Inflamm. Epub 2009 Jan 11 116. Mastro AM, Schlosser DA, Grove DS, et al. Lymphocyte subpopulations in lymphoid organs of rats after acute resistance exercise. Med Sci Sports Exerc 1999 Jan; 31 (1): 74-81 117. Purtilo DT, Sullivan JL. Immunological bases for superior survival of females. Am J Dis Child 1979 Dec; 133 (12): 1251-3 118. Verthelyi D. Sex hormones as immunomodulators in health and disease. Int Immunopharmacol 2001 Jun; 1 (6): 983-93 119. Cannon JG, St Pierre BA. Gender differences in host defense mechanisms. J Psychiatr Res 1997 Jan-Feb; 31 (1): 99-113 120. Diodato MD, Knoferl MW, Schwacha MG, et al. Gender differences in the inflammatory response and survival following haemorrhage and subsequent sepsis. Cytokine 2001 May 7; 14 (3): 162-9 121. Styrt B, Sugarman B. Estrogens and infection. Rev Infect Dis 1991 Nov-Dec; 13 (6): 1139-50 122. Yancey AL, Watson HL, Cartner SC, et al. Gender is a major factor in determining the severity of mycoplasma respiratory disease in mice. Infect Immun 2001 May; 69 (5): 2865-71 123. Whitacre CC. Sex differences in autoimmune disease. Nat Immunol 2001 Sep; 2 (9): 777-80 124. Aljubeh J, Miller A, Meyer 3rd W, et al. Glucocorticoid receptor characteristics in healthy childrens’ leukocytes:
ª 2011 Adis Data Information BV. All rights reserved.
125.
126.
127.
128.
129.
130.
131.
132.
133.
134.
135.
136.
137.
138.
139.
140.
correlation with gender, weight, age and plasma cortisol. J Pediatr Endocrinol Metab 2001 Nov-Dec; 14 (9): 1641-7 Giron-Gonzalez JA, Moral FJ, Elvira J, et al. Consistent production of a higher TH1:TH2 cytokine ratio by stimulated T cells in men compared with women. Eur J Endocrinol 2000 Jul; 143 (1): 31-6 Posma E, Moes H, Heineman MJ, et al. The effect of testosterone on cytokine production in the specific and nonspecific immune response. Am J Reprod Immunol 2004 Oct; 52 (4): 237-43 Blondeau JM, Embil JA, McFarlane ES. Herpes simplex virus infections in male and female mice following pinna inoculation: responses to primary infection and artificially induced recurrent disease. J Med Virol 1989 Dec; 29 (4): 320-6 Travi BL, Osorio Y, Melby PC, et al. Gender is a major determinant of the clinical evolution and immune response in hamsters infected with Leishmania spp. Infect Immun 2002 May; 70 (5): 2288-96 Choudhry MA, Bland KI, Chaudry IH. Trauma and immune response: effect of gender differences. Injury 2007 Dec; 38 (12): 1382-91 Gabrilovac J, Marotti T. Gender-related differences in murine T- and B-lymphocyte proliferative ability in response to in vivo [Met(5)]enkephalin administration. Eur J Pharmacol 2000 Mar 24; 392 (1-2): 101-8 De Lanne R, Barnes JR, Brouha L. Hematological changes during muscular activity and recovery. J Appl Physiol 1960 Jan; 15: 31-6 Timmons BW, Hamadeh MJ, Devries MC, et al. Influence of gender, menstrual phase, and oral contraceptive use on immunological changes in response to prolonged cycling. J Appl Physiol 2005 Sep; 99 (3): 979-85 Bouillon LE, Flynn MG, Lambert CP, et al. Exercise during late-follicular menstrual phase: influence on immune parameters. J Sports Med Phys Fitness 2006 Mar; 46 (1): 143-51 de la Fuente M, Martin MI, Ortega E. Changes in the phagocytic function of peritoneal macrophages from old mice after strenuous physical exercise. Comp Immunol Microbiol Infect Dis 1990; 13 (4): 189-98 Brown AS, Davis JM, Murphy EA, et al. Gender differences in viral infection after repeated exercise stress. Med Sci Sports Exerc 2004 Aug; 36 (8): 1290-5 Navalta JW, Sedlock DA, Park KS, et al. Neither gender nor menstrual cycle phase influences exercise-induced lymphocyte apoptosis in untrained subjects. Appl Physiol Nutr Metab 2007 Jun; 32 (3): 481-6 Miles MP, Kraemer WJ, Grove DS, et al. Effects of resistance training on resting immune parameters in women. Eur J Appl Physiol 2002 Oct; 87 (6): 506-8 Webster Marketon JI, Glaser R. Stress hormones and immune function. Cell Immunol 2008 Mar-Apr; 252 (1-2): 16-26 Brenner I, Shek PN, Zamecnik J, et al. Stress hormones and the immunological responses to heat and exercise. Int J Sports Med 1998 Feb; 19 (2): 130-43 Pyne DB. Exercise-induced muscle damage and inflammation: a review. Aust J Sci Med Sport 1994 SepDec; 26 (3-4): 49-58
Sports Med 2011; 41 (8)
Neuroendocrine-Immune Interactions
141. Pyne DB. Regulation of neutrophil function during exercise. Sports Med 1994 Apr; 17 (4): 245-58 142. Nieman DC. Exercise, upper respiratory tract infection, and the immune system. Med Sci Sports Exerc 1994 Feb; 26 (2): 128-39 143. Cupps TR, Fauci AS. Corticosteroid-mediated immunoregulation in man. Immunol Rev 1982; 65: 133-55 144. Nieman DC. Immune response to heavy exertion. J Appl Physiol 1997 May; 82 (5): 1385-94 145. Tanaka H, Akama H, Ichikawa Y, et al. Glucocorticoid receptors in normal leukocytes: effects of age, gender, season, and plasma cortisol concentrations. Clin Chem 1991 Oct; 37 (10 Pt 1): 1715-9 146. Maki T. Density and functioning of human lymphocytic beta-adrenergic receptors during prolonged physical exercise. Acta Physiol Scand 1989 Aug; 136 (4): 569-74 147. Blalock JE. Shared ligands and receptors as a molecular mechanism for communication between the immune and neuroendocrine systems. Ann N Y Acad Sci 1994 Nov 25; 741: 292-8 148. Garza Jr HH, Carr DJ. Neuroendocrine peptide receptors on cells of the immune system. Chem Immunol 1997; 69: 132-54 149. Weigent DA, Carr DJ, Blalock JE. Bidirectional communication between the neuroendocrine and immune systems: common hormones and hormone receptors. Ann N Y Acad Sci 1990; 579: 17-27 150. Dohi K, Kraemer WJ, Mastro AM. Exercise increases prolactin-receptor expression on human lymphocytes. J Appl Physiol 2003 Feb; 94 (2): 518-24 151. Yamamoto KR. Steroid receptor regulated transcription of specific genes and gene networks. Annu Rev Genet 1985; 19: 209-52 152. Gustafsson JA, Carlstedt-Duke J, Poellinger L, et al. Biochemistry, molecular biology, and physiology of the glucocorticoid receptor. Endocr Rev 1987 May; 8 (2): 185-234 153. Claman HN. Corticosteroids as immunomodulators. Ann N Y Acad Sci 1993 Jun 23; 685: 288-92 154. Yehuda R, Boisoneau D, Lowy MT, et al. Dose-response changes in plasma cortisol and lymphocyte glucocorticoid receptors following dexamethasone administration in combat veterans with and without posttraumatic stress disorder. Arch Gen Psychiatry 1995 Jul; 52 (7): 583-93 155. Sanchez ER, Faber LE, Henzel WJ, et al. The 56-59-kilodalton protein identified in untransformed steroid receptor complexes is a unique protein that exists in cytosol in a complex with both the 70- and 90-kilodalton heat shock proteins. Biochemistry 1990 May 29; 29 (21): 5145-52 156. de Waal RM. The anti-inflammatory activity of glucocorticoids. Mol Biol Rep 1994 Mar; 19 (2): 81-8 157. Funder JW. Mineralocorticoid receptors and glucocorticoid receptors. Clin Endocrinol (Oxf) 1996 Dec; 45 (6): 651-6 158. Soontjens CD, Rafter JJ, Gustafsson JA. Ligands for orphan receptors? J Endocrinol 1996 Sep; 150 Suppl.: S241-57 159. Besedovsky HO, Del Rey A, Sorkin E. Antigenic competition between horse and sheep red blood cells as a hormone-dependent phenomenon. Clin Exp Immunol 1979 Jul; 37 (1): 106-13
ª 2011 Adis Data Information BV. All rights reserved.
637
160. del Rey A, Besedovsky H, Sorkin E. Endogenous blood levels of corticosterone control the immunologic cell mass and B cell activity in mice. J Immunol 1984 Aug; 133 (2): 572-5 161. Hench PS, Kendall EC, Slocumb CH, et al. The effect of a hormone of the adrenal cortex (17-hydroxycorticosterone: compound E) and of pituitary adrenocorticotropic hormone on rheumatoid arthritis. Mayo Clinic Proc 1949; 24: 181-97 162. Newton R. Molecular mechanisms of glucocorticoid action: what is important? Thorax 2000 Jul; 55 (7): 603-13 163. Wiegers GJ, Knoflach M, Bock G, et al. CD4(+)CD8(+)TCR(low) thymocytes express low levels of glucocorticoid receptors while being sensitive to glucocorticoid-induced apoptosis. Eur J Immunol 2001 Aug; 31 (8): 2293-301 164. Fragala MS, Kraemer WJ, Mastro AM, et al. Glucocorticoid receptor expression on human b-cells in response to acute heavy resistance exercise. Neuroimmunomodulation. 2011; 18 (3): 156-64 165. Collins S. Recent perspectives on the molecular structure and regulation of the beta 2-adrenoceptor. Life Sci 1993; 52 (26): 2083-91 166. Collins S, Caron MG, Lefkowitz RJ. From ligand binding to gene expression: new insights into the regulation of G-protein-coupled receptors. Trends Biochem Sci 1992 Jan; 17 (1): 37-9 167. Collins S, Caron MG, Lefkowitz RJ. Regulation of adrenergic receptor responsiveness through modulation of receptor gene expression. Annu Rev Physiol 1991; 53: 497-508 168. Dohlman HG, Thorner J, Caron MG, et al. Model systems for the study of seven-transmembrane-segment receptors. Annu Rev Biochem 1991; 60: 653-88 169. Haen E, Hauck R, Emslander HP, et al. Nocturnal asthma. Beta 2-adrenoceptors on peripheral mononuclear leukocytes, cAMP- and cortisol-plasma concentrations. Chest 1991 Nov; 100 (5): 1239-45 170. Inglese J, Luttrell LM, Iniguez-Lluhi JA, et al. Functionally active targeting domain of the beta-adrenergic receptor kinase: an inhibitor of G beta gamma-mediated stimulation of type II adenylyl cyclase. Proc Natl Acad Sci U S A 1994 Apr 26; 91 (9): 3637-41 171. Pei G, Tiberi M, Caron MG, et al. An approach to the study of G-protein-coupled receptor kinases: an in vitropurified membrane assay reveals differential receptor specificity and regulation by G beta gamma subunits. Proc Natl Acad Sci U S A 1994 Apr 26; 91 (9): 3633-6 172. Clausen T, Flatman JA. Beta 2-adrenoceptors mediate the stimulating effect of adrenaline on active electrogenic NaK-transport in rat soleus muscle. Br J Pharmacol 1980 Apr; 68 (4): 749-55 173. Holmberg E, Waldeck B. On the possible role of potassium ions in the action of terbutaline on skeletal muscle contractions. Acta Pharmacol Toxicol (Copenh) 1980 Feb; 46 (2): 141-9 174. Elenkov IJ, Wilder RL, Chrousos GP, et al. The sympathetic nerve. An integrative interface between two supersystems: the brain and the immune system. Pharmacol Rev 2000 Dec; 52 (4): 595-638 175. Van Tits LJ, Michel MC, Grosse-Wilde H, et al. Catecholamines increase lymphocyte beta 2-adrenergic receptors
Sports Med 2011; 41 (8)
Fragala et al.
638
176.
177.
178.
179.
180. 181. 182.
183.
184.
185.
186.
187.
188.
189.
190.
191.
192.
via a beta 2-adrenergic, spleen-dependent process. Am J Physiol 1990 Jan; 258 (1 Pt 1): E191-202 Boxer LA, Allen JM, Baehner RL. Diminished polymorphonuclear leukocyte adherence: function dependent on release of cyclic AMP by endothelial cells after stimulation of beta-receptors by epinephrine. J Clin Invest 1980 Aug; 66 (2): 268-74 Schedlowski M, Falk A, Rohne A, et al. Catecholamines induce alterations of distribution and activity of human natural killer (NK) cells. J Clin Immunol 1993 Sep; 13 (5): 344-51 Fragala MS, Kraemer WJ, Mastro AM, et al. Leukocyte b2-adrenergic receptor expression in response to resistance exercise. Med Sci Sports Exerc. In press Bunt JC, Boileau RA, Bahr JM, et al. Sex and training differences in human growth hormone levels during prolonged exercise. J Appl Physiol 1986 Nov; 61 (5): 1796-801 Eskes T, Haanen C. Why do women live longer than men? Eur J Obstet Gynecol Reprod Biol 2007 Aug; 133 (2): 126-33 Lunenfeld B. The ageing male: demographics and challenges. World J Urol 2002 May; 20 (1): 11-6 Carlsten H, Holmdahl R, Tarkowski A, et al. Oestradioland testosterone-mediated effects on the immune system in normal and autoimmune mice are genetically linked and inherited as dominant traits. Immunology 1989 Oct; 68 (2): 209-14 Carlsten H, Holmdahl R, Tarkowski A, et al. Oestradiol suppression of delayed-type hypersensitivity in autoimmune (NZB/NZW)F1 mice is a trait inherited from the healthy NZW parental strain. Immunology 1989 Jun; 67 (2): 205-9 Josefsson E, Tarkowski A, Carlsten H. Anti-inflammatory properties of estrogen. I: in vivo suppression of leukocyte production in bone marrow and redistribution of peripheral blood neutrophils. Cell Immunol 1992 Jun; 142 (1): 67-78 Hanna N, Schneider M. Enhancement of tumor metastasis and suppression of natural killer cell activity by betaestradiol treatment. J Immunol 1983 Feb; 130 (2): 974-80 Nilsson N, Carlsten H. Estrogen induces suppression of natural killer cell cytotoxicity and augmentation of polyclonal B cell activation. Cell Immunol 1994 Oct 1; 158 (1): 131-9 Masuzawa T, Miyaura C, Onoe Y, et al. Estrogen deficiency stimulates B lymphopoiesis in mouse bone marrow. J Clin Invest 1994 Sep; 94 (3): 1090-7 Smithson G, Beamer WG, Shultz KL, et al. Increased B lymphopoiesis in genetically sex steroid-deficient hypogonadal (hpg) mice. J Exp Med 1994 Aug 1; 180 (2): 717-20 Wilson CA, Mrose SA, Thomas DW. Enhanced production of B lymphocytes after castration. Blood 1995 Mar 15; 85 (6): 1535-9 Medina KL, Kincade PW. Pregnancy-related steroids are potential negative regulators of B lymphopoiesis. Proc Natl Acad Sci U S A 1994 Jun 7; 91 (12): 5382-6 Rijhsinghani AG, Thompson K, Bhatia SK, et al. Estrogen blocks early T cell development in the thymus. Am J Reprod Immunol 1996 Nov; 36 (5): 269-77 Medina KL, Smithson G, Kincade PW. Suppression of B lymphopoiesis during normal pregnancy. J Exp Med 1993 Nov 1; 178 (5): 1507-15
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193. Mills PJ, Ziegler MG, Dimsdale JE, et al. Enumerative immune changes following acute stress: effect of the menstrual cycle. Brain Behav Immun 1995 Sep; 9 (3): 190-5 194. Grimaldi CM, Hill L, Xu X, et al. Hormonal modulation of B cell development and repertoire selection. Mol Immunol 2005 May; 42 (7): 811-20 195. McMurray RW, Ndebele K, Hardy KJ, et al. 17-betaestradiol suppresses IL-2 and IL-2 receptor. Cytokine 2001 Jun 21; 14 (6): 324-33 196. Smithson G, Couse JF, Lubahn DB, et al. The role of estrogen receptors and androgen receptors in sex steroid regulation of B lymphopoiesis. J Immunol 1998 Jul 1; 161 (1): 27-34 197. Hewitt SC, Harrell JC, Korach KS. Lessons in estrogen biology from knockout and transgenic animals. Annu Rev Physiol 2005; 67: 285-308 198. Matthews J, Gustafsson JA. Estrogen signaling: a subtle balance between ER alpha and ER beta. Mol Interv 2003 Aug; 3 (5): 281-92 199. Phiel KL, Henderson RA, Adelman SJ, et al. Differential estrogen receptor gene expression in human peripheral blood mononuclear cell populations. Immunol Lett 2005 Feb 15; 97 (1): 107-13 200. Bakir S, Mori T, Durand J, et al. Estrogen-induced vasoprotection is estrogen receptor dependent: evidence from the balloon-injured rat carotid artery model. Circulation 2000 May 23; 101 (20): 2342-4 201. Miller AP, Feng W, Xing D, et al. Estrogen modulates inflammatory mediator expression and neutrophil chemotaxis in injured arteries. Circulation 2004 Sep 21; 110 (12): 1664-9 202. Xing D, Miller A, Novak L, et al. Estradiol and progestins differentially modulate leukocyte infiltration after vascular injury. Circulation 2004 Jan 20; 109 (2): 234-41 203. Luster AD. Chemokines: chemotactic cytokines that mediate inflammation. N Engl J Med 1998 Feb 12; 338 (7): 436-45 204. Meyers MJ, Sun J, Carlson KE, et al. Estrogen receptor-beta potency-selective ligands: structure-activity relationship studies of diarylpropionitriles and their acetylene and polar analogues. J Med Chem 2001 Nov 22; 44 (24): 4230-51 205. Xing D, Feng W, Miller AP, et al. Estrogen modulates TNF-alpha-induced inflammatory responses in rat aortic smooth muscle cells through estrogen receptor-beta activation. Am J Physiol Heart Circ Physiol 2007 Jun; 292 (6): H2607-12 206. Lew KH, Ludwig EA, Milad MA, et al. Gender-based effects on methylprednisolone pharmacokinetics and pharmacodynamics. Clin Pharmacol Ther 1993 Oct; 54 (4): 402-14 207. Nelson DH, Tanney H, Mestman G, et al. Potentiation of the biologic effect of administered cortisol by estrogen treatment. J Clin Endocrinol Metab 1963 Mar; 23: 261-5 208. Bulbrook RD, Herian M, Tong D, et al. Effect of steroidal contraceptives on levels of plasma androgen sulphates and cortisol. Lancet 1973 Mar 24; 1 (7804): 628-31 209. Plager JE, Schmidt KG, Staubitz WJ. Increased unbound cortisol in the plasma of estrogen-treated subjects. J Clin Invest 1964 Jun; 43: 1066-72 210. Janele D, Lang T, Capellino S, et al. Effects of testosterone, 17beta-estradiol, and downstream estrogens on cytokine
Sports Med 2011; 41 (8)
Neuroendocrine-Immune Interactions
211.
212.
213.
214.
215.
secretion from human leukocytes in the presence and absence of cortisol. Ann N Y Acad Sci 2006 Jun; 1069: 168-82 Fujimoto R, Morimoto I, Morita E, et al. Androgen receptors, 5 alpha-reductase activity and androgen-dependent proliferation of vascular smooth muscle cells. J Steroid Biochem Mol Biol 1994 Aug; 50 (3-4): 169-74 Benten WP, Lieberherr M, Giese G, et al. Functional testosterone receptors in plasma membranes of T cells. Faseb J 1999 Jan; 13 (1): 123-33 Benten WP, Lieberherr M, Stamm O, et al. Testosterone signaling through internalizable surface receptors in androgen receptor-free macrophages. Mol Biol Cell 1999 Oct; 10 (10): 3113-23 Mealy K, Robinson B, Millette CF, et al. The testicular effects of tumor necrosis factor. Ann Surg 1990 Apr; 211 (4): 470-5 Mosmann TR, Sad S. The expanding universe of T-cell subsets: Th1, Th2 and more. Immunol Today 1996 Mar; 17 (3): 138-46
ª 2011 Adis Data Information BV. All rights reserved.
639
216. Butts CL, Jones YL, Lim JK, et al. Tissue expression of steroid hormone receptors is associated with differential immune responsiveness. Brain Behav Immun 2011 Jul; 25 (5): 1000-7 217. MacLean HE, Chiu WS, Notini AJ, et al. Impaired skeletal muscle development and function in male, but not female, genomic androgen receptor knockout mice. Faseb J 2008 Aug; 22 (8): 2676-89 218. Ophoff J, Van Proeyen K, Callewaert F, et al. Androgen signaling in myocytes contributes to the maintenance of muscle mass and fiber type regulation but not to muscle strength or fatigue. Endocrinology 2009 Aug; 150 (8): 3558-66
Correspondence: William J. Kraemer, PhD, Human Performance Laboratory, Department of Kinesiology, 2095 Hillside Road, Unit-1110, University of Connecticut, Storrs, CT 06269-1110, USA. E-mail:
[email protected]
Sports Med 2011; 41 (8)
Sports Med 2011; 41 (8): 641-671 0112-1642/11/0008-0641/$49.95/0
REVIEW ARTICLE
ª 2011 Adis Data Information BV. All rights reserved.
The Pleasure and Displeasure People Feel When they Exercise at Different Intensities Decennial Update and Progress towards a Tripartite Rationale for Exercise Intensity Prescription Panteleimon Ekkekakis,1 Gaynor Parfitt2 and Steven J. Petruzzello3 1 Department of Kinesiology, Iowa State University, Ames, IA, USA 2 School of Health Sciences, University of South Australia, Adelaide, SA, Australia 3 Department of Kinesiology and Community Health, University of Illinois at Urbana-Champaign, Urbana, IL, USA
Contents Abstract. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1. The Exercise Paradox: A ‘Best Buy’ But a ‘Tough Sell’ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1 The Role of Affect in Exercise Behaviour. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2 The Role of Intensity in Exercise Behaviour . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.3 A Possible Intensity-Affect-Exercise Behaviour Causal Chain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.4 Necessity of the Present Update . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2. Summary of Conclusions and Recommendations of the 1999 Review. . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Overhaul of the Methodological Platform. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3. Updated Review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 The Importance of Physiological Landmarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 The Phenomenon of Individual Variability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 Affective Responses and the Self-Selection of Intensity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.4 Emergence of Theory and Theory-Testing Studies. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4. Future Directions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 Further Investigation of Individual Differences. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 Study of the Mechanistic Bases of Affective Responses at Different Intensities . . . . . . . . . . . . . . 4.3 Examination of Population-Specific Variations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4 Consistency in the System Used to Classify Exercise Intensities . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5. Conclusion: Towards a Tripartite Rationale for Exercise Intensity Prescriptions. . . . . . . . . . . . . . . . . . . .
Abstract
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The public health problem of physical inactivity has proven resistant to research efforts aimed at elucidating its causes and interventions designed to alter its course. Thus, in most industrialized countries, the majority of the population is physically inactive or inadequately active. Most theoretical models of exercise behaviour assume that the decision to engage in exercise is based on cognitive factors (e.g. weighing pros and cons, appraising personal capabilities, evaluating sources of support). Another, still-under-appreciated, possibility is that these decisions are influenced by affective variables, such as whether previous exercise experiences were associated with pleasure or
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displeasure. This review examines 33 articles published from 1999 to 2009 on the relationship between exercise intensity and affective responses. Unlike 31 studies that were published until 1998 and were examined in a 1999 review, these more recent studies have provided evidence of a relation between the intensity of exercise and affective responses. Pleasure is reduced mainly above the ventilatory or lactate threshold or the onset of blood lactate accumulation. There are pleasant changes at sub-threshold intensities for most individuals, large inter-individual variability close to the ventilatory or lactate threshold and homogeneously negative changes at supra-threshold intensities. When the intensity is self-selected, rather than imposed, it appears to foster greater tolerance to higher intensity levels. The evidence of a doseresponse relation between exercise intensity and affect sets the stage for a reconsideration of the rationale behind current guidelines for exercise intensity prescription. Besides effectiveness and safety, it is becoming increasingly clear that the guidelines should take into account whether a certain level of exercise intensity would be likely to cause increases or decreases in pleasure.
1. The Exercise Paradox: A ‘Best Buy’ But a ‘Tough Sell’ In a landmark paper, the late Jeremy Morris characterized physical activity as ‘‘today’s best buy in public health.’’[1] The evidence that has accumulated on the causal relationship between physical activity and numerous aspects of health supports this characterization.[2-4] At the same time, however, promoting exercise to the public has proven a very ‘tough sell’.[5] Despite the issuance of evidence-based recommendations, the advent of social marketing campaigns, the institution of public health policy and the investment of considerable research funds, the rates of physical inactivity in most industrialized countries have not shown signs of change.[6-10] Thus, combating physical inactivity was recently characterized as ‘‘the biggest public health problem of the 21st century.’’[11] Although the current situation calls for what the Chief Medical Officer[12] in the UK described as ‘‘a mass shift in current activity levels’’ (p. iv), activity-promotion interventions have shown limited effectiveness.[13,14] Moreover, of those individuals who initiate exercise programmes, there is an estimated 45% dropout (range from 9% to 87%).[14] Since these data come from research trials, most of which include intervention components designed to improve adherence and retenª 2011 Adis Data Information BV. All rights reserved.
tion, it is reasonable to speculate that, in real-life conditions, where no such support is usually present, dropout is probably even higher. 1.1 The Role of Affect in Exercise Behaviour
One assumption underpinning the theories that are commonly used to explain and predict exercise behaviour and to design interventions (e.g. the theory of planned behaviour, social-cognitive theory or the trans-theoretical model) is that people make behavioural decisions after they collect pertinent information, weigh pros and cons, appraise sources of support and make probabilistic predictions about the consequences of their actions. Consequently, to improve the chances of choosing exercise over sedentary alternatives, interventions focus on providing information about such parameters as the health benefits of an active lifestyle or the individual’s physical readiness to perform the recommended amount of exercise. However, evidence indicates that interventions based on education and modifications of cognitive appraisals are minimally effective.[13] Another assumption that is implicit in the application of these theories in the field of exercise behaviour is that the factors that influence this particular behaviour are the same as those underlying other health behaviours (such as brushing one’s teeth, quitting smoking, eating fruits and Sports Med 2011; 41 (8)
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vegetables or practicing safe sex). However, data from 250 000 respondents in North America indicate that other health behaviours share virtually no common variance with exercise.[15] Therefore, exercise appears to be driven by at least some unique mechanisms. Nevertheless, the unique mechanisms underlying exercise behaviour remain unexplored and have yet to be targeted in intervention efforts. One feature of exercise that has been identified as having potential motivational significance is the affective response (e.g. pleasure or displeasure, tension or relaxation, energy or tiredness) that exercisers experience. Dishman et al.[16] noted that ‘‘feelings of enjoyment and well-being seem to be stronger motives for continued participation [than] knowledge of and belief in the health benefits of physical activity’’ (p. 162), as well as ‘‘more important to maintaining activity than concerns about health’’ (p. 166). Dishman[17] also wrote that ‘‘knowledge and belief in the health benefits of physical activity may motivate initial involvement and return to activity following relapse, but feelings of enjoyment and wellbeing seem to be stronger motives for continued participation’’ (p. 83). It was not until recently that the first direct evidence linking affective responses and exercise behaviour emerged. Williams et al.[18] recorded pleasure ratings during an exercise test at the minute at which sedentary adults reached a ‘moderate’ level of intensity (64% of age-predicted maximal heart rate [HRmax]). These ratings were significantly correlated with self-reported physical activity at 6-month (r = 0.50) and 12-month (r = 0.47) follow-ups. A 1-unit increase on the 11-point rating scale of pleasure[19] was associated with 38 additional minutes of at least moderate physical activity per week at the 6-month followup and 41 minutes at the 12-month follow-up. Schneider et al.[20] measured pleasure while 124 adolescents exercised on a cycle ergometer for 30 minutes at 80% of their previously determined ventilatory threshold (VT) workload. Participants who reported increases in pleasure averaged 54.25 minutes of daily moderate-tovigorous physical activity, assessed by accelerometers. Those who reported no change averaged ª 2011 Adis Data Information BV. All rights reserved.
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46.94 minutes and those who reported declines averaged 39.83 minutes. After controlling for aerobic fitness and sex, a 1-unit increase on the 11-point rating scale of pleasure[19] predicted 4.18 minutes of additional daily moderate-tovigorous physical activity. Kwan and Bryan[21] assessed positive affect (e.g. enthusiastic, energetic), negative affect (e.g. crummy, miserable), tranquility (e.g. calm, relaxed) and fatigue (e.g. fatigued, tired) during and after 30 minutes of treadmill exercise at 65% max. imal oxygen uptake (VO2max) in 129 adults. Larger increases in positive affect and decreases in fatigue during exercise were associated with more frequent self-reported aerobic exercise 3 months later. More tranquility and less fatigue during recovery were also related with more frequent exercise. Although preliminary, these findings raise the possibility that exercise-induced increases or decreases in pleasure may contribute to the formation of a positive or negative memory trace for exercise. In turn, this memory, consciously or subconsciously, may influence subsequent decisions to engage in, adhere to or drop out from exercise.[22] 1.2 The Role of Intensity in Exercise Behaviour
Intensity is a key component of exercise prescriptions because, according to the American College of Sports Medicine (ACSM),[23] it is both ‘‘the most important exercise prescription variable to maintain a cardiovascular training response’’ (p. 161) and ‘‘associated with an increased risk of orthopedic injury [and] cardiovascular incidence’’ (p. 147). Moreover, characterizing intensity as ‘‘the most important exercise prescription variable’’ is justified by its apparent impact on adherence. According to ACSM,[23] ‘‘adherence is lower with higher-intensity exercise programs’’ (p. 142). Although a recent review casts doubt on the strength of this link,[24] the role of intensity is supported by several large studies.[25-28] Furthermore, a meta-analysis showed that activitypromotion efforts were more effective when the intensity was lower rather than higher.[13] Other components of the exercise ‘dose’, such as duration or frequency, do not seem to have similar relations to adherence.[13,27] Sports Med 2011; 41 (8)
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1.3 A Possible Intensity-Affect-Exercise Behaviour Causal Chain
Among the variables likely to mediate the relationship between intensity and adherence, affect has long been postulated to play a key role. Pollock[29] proposed an intensity-affect-adherence causal chain in 1978: ‘‘People participate in programs they enjoy. The lower intensity effort makes the programs more enjoyable’’ (p. 59). This intuitively appealing idea reappeared in the text of the Healthy People 2010[30] programme: ‘‘each person should recognize that starting out slowly with an activity that is enjoyable [is] central to the adoption and maintenance of physical activity behavior’’ (chapter 22, p. 4). However, no studies to date have examined this mediational relationship. One possible explanation for this void is that the first link, between intensity and affect, has remained enigmatic.[22] 1.4 Necessity of the Present Update
Several reasons necessitate a re-examination of the evidence on the intensity-affect relationship, a decade after Ekkekakis and Petruzzello’s[22] review of this literature. First, in the last decade, the studies investigating the intensity-affect relationship have more than doubled. Compared with 31 studies published between 1971 and 1998, 41 new articles were published from 1999 to 2009. Therefore, interest in this topic has been growing stronger. Second, there has been a change in the rationale behind the newer studies. The purpose of most of the earlier studies was to investigate the utility of exercise as an intervention for improving mental health (i.e. whether exercise can make people ‘feel better’ and, thus, help combat such mental health problems as anxiety or depression). In contrast, most recent studies target affect because of its possible implications for exercise adherence. Third, newer studies paint a fundamentally different picture of the intensity-affect relation than earlier ones. Although Ekkekakis and Petruzzello[22] found that 54% of the studies they reviewed showed no intensity effects, the newer studies, due to a combination of stronger methodologies and more refined hypotheses, have ª 2011 Adis Data Information BV. All rights reserved.
produced evidence of a dose-response pattern. As the reliability of these findings is established through replications by independent laboratories, new prospects arise. A few years after the publication of the first ACSM guidelines for exercise testing and prescription, Dishman recognized the need to find a ‘‘compromise’’ between the ‘‘ideal physiological prescription’’ and a ‘‘manageable behavioral prescription’’ in order to ‘‘allow adherence to be sufficient for desired biological changes to occur’’[31,32] (p. 248 and p. 174, respectively). This was a pioneering proposal for a transition to a tripartite model upon which exercise prescription guidelines should be based. Besides ‘‘the dose that induces the greatest health benefit’’ and ‘‘the potential risk in a particular population’’[23] (p. 133), it is time to also consider which intensity is more likely to increase pleasure and, thus, promote motivation and adherence. Fourth, in the latest edition of the Guidelines for Exercise Testing and Prescription, the ACSM[33] identified the use of ‘‘measures of affective valence’’ (i.e. pleasure/displeasure) as a potentially useful adjunct method of self-monitoring exercise intensity besides heart rate (HR) and ratings of perceived exertion (RPE). The ACSM[33] also noted the need for ‘‘further research’’ before measures of affective valence can be ‘‘recommended as primary tools for the estimation of exercise intensity’’ (p. 157). Thus, an updated review on the relation between exercise intensity and affect seems warranted. 2. Summary of Conclusions and Recommendations of the 1999 Review According to earlier proposals,[34,35] the relation between exercise intensity and affective responses can be modelled as an inverted-U curve. This implies that mid-range intensities should result in optimal affective changes, whereas intensities that are ‘too low’ or ‘too high’ are less effective. Ekkekakis and Petruzzello[22] discussed evidence that the inverted-U is an unsatisfactory model of the intensity-affect relation for at least three reasons. First, the model does not fit the data well. Lowintensity, short-duration exercise (e.g. self-paced Sports Med 2011; 41 (8)
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walks) has been found to produce transient but significant increases in pleasure and energy.[36-40] A meta-analysis focusing on the influence of exercise on high-activation pleasant affect (e.g. vigour, energy) concluded that the effect size associated . with low intensities (15–39% oxygen uptake [VO2] reserve) was almost twice as large (d = 0.57) as . that associated with moderate (40–59% VO2. reserve; d = 0.35) or high intensities (60–85% VO2 reserve; d = 0.31).[41] On the other hand, highintensity exercise stimuli, such as incremental exercise protocols to volitional exhaustion, in addition to increases in fatigue, have been found to yield some positive changes, such as improveperments in self-esteem.[42] Finally, during exercise . formed at mid-range intensities (e.g. 60% VO2max), some individuals report increases but others decreases in pleasure.[43] Second, the inverted-U model does not take into account inter-individual variability in affective responses. However, variability, even to the same exercise intensity and for individuals of the same sex, age, health and physical fitness, is often pronounced.[43,44] Evidence also shows that the degree of variability changes as a function of exercise intensity.[45] Thus, the phenomenon of variability warrants substantive research attention.[46] Third, the inverted-U is a descriptive model, not a mechanistic one. Consequently, it does not yield testable hypotheses that could elucidate the underlying causes of the observed affective changes. However, mechanistic explanations are necessary insofar as they form a basis for developing interventions to optimize affective responses. The review of the 31 studies published up until 1998 revealed two groups of studies with distinct findings. The largest group consisted of 26 studies in which affective variables (e.g. state anxiety, mood states) were assessed, typically with multiitem inventories, only before and after or before, during and after the exercise bouts. Slightly more than half of these studies (14 of 26) did not show significant intensity effects. Of those that did, there was some evidence that (i) when tension or state anxiety were measured during or immediately after a bout, higher intensities were associated with higher scores; and (ii) fatigue tended to be higher and energy or vigour tended to be ª 2011 Adis Data Information BV. All rights reserved.
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lower in response to higher exercise intensities, particularly among participants with low cardiorespiratory fitness. The second group consisted of seven studies (with a two-study overlap with the first group), in which affective responses during exercise were assessed along the dimension of pleasure/ displeasure, using the single-item Feeling Scale (FS).[19] The FS is an 11-point rating scale, ranging from (I feel) ‘very good’ (+5) to ‘very bad’ (-5). Six of these seven studies showed that, as the intensity increased, pleasure ratings declined. 2.1 Overhaul of the Methodological Platform
Most earlier investigations of the relationship between exercise intensity and affective responses were based on a methodological platform with several features that were identified by Ekkekakis and Petruzzello[22] as problematic. First, to assess ‘how people feel’, researchers used questionnaires tapping certain distinct states (e.g. anxiety, vigour, fatigue, depression). These variables were chosen because they were the ones measured by the questionnaires that were available for nonclinical use in the 1970s and 1980s. Second, because these questionnaires were relatively long and, therefore, inconvenient to administer during exercise, they were typically completed only before and after exercise. Third, the intensity of the exercise bouts was set as a percentage of HRmax . or VO2max, usually without providing a rationale. Thus, .one study might have compared 40% to 60% VO2max while another compared 50% to 75%. Fourth, analyses of change were based on the general linear model and, thus, individual differences in affective responses to the same intensity were treated as error. Collectively, these methodological features might have obfuscated intensity effects. Focusing on only a few distinct states left open the possibility that intensity effects occurred not in the states being assessed but in others.[47] Measuring affect only before and after the bout allowed the possibility that intensity effects occurred during exercise but dissipated thereafter.[48,49] Attempting to equate the intensity across individuals by using percentages of maximal capacity cannot Sports Med 2011; 41 (8)
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standardize the contribution of aerobic and anaerobic metabolic pathways or a multitude of attendant physiological processes.[50-59] This increases variability in affective responses and reduces statistical power to detect intensity effects. Finally, analysing changes only at the level of group averages neglects important individual differences and can conceal divergent patterns among individuals or subgroups.[43-46,48] In the most extreme case, if two groups exhibit equal but opposite changes during the bout, the group average will deceptively indicate that there was no change.[43] To address these problems, Ekkekakis and Petruzzello[22] proposed certain changes to the methodological platform that are important to revisit, to set the backdrop against which the newer studies can be evaluated. The domain of affect can be conceptualized as defined by a small set of dimensions that account for most of the similarities and differences among affective states. A model called the circumplex includes the bipolar and orthogonal dimensions of affective valence (pleasure/displeasure) and perceived activation.[60] The full trajectory of the affective response to an exercise bout can be tracked with repeated administrations of two single-item rating scales, one for each dimension.[22] It should be noted that, because responses depend on a single rating that could be swayed by random error (e.g. respondent carelessness), single-item scales are considered less reliable than multi-item ones. On the other hand, due to their brevity, they are minimally intrusive, thus allowing assessments with even minute-by-minute frequency. The intensity of exercise should be set in relation to a physiological marker that reflects the contributions of aerobic and anaerobic metabolic processes, such as the VT or the lactate threshold (LT).[58,59] Finally, exercise-induced changes in affect should be examined not only at the level of group averages, but also at the level of individuals and subgroups.[43,48] 3. Updated Review Articles were located by a combination of (i) monitoring the tables of contents of journals in exercise science, exercise psychology, health psyª 2011 Adis Data Information BV. All rights reserved.
chology, preventive medicine and behavioural medicine for the last decade; (ii) performing literature searches using scientific databases (PubMed, PsycINFO, Web of Knowledge, Scopus); and (iii) conducting extensive cross-referencing. Fortyone articles were identified, published between January 1999 and December 2009. Of these, eight were excluded for the following reasons: (i) exercise intensity was set solely on the basis of RPE;[61] (ii) different intensities were prescribed verbally but the actual intensities were not monitored;[62] (iii) the effect of different intensities was not analysed;[63] (iv) the effects of intensity could not be disentangled from the effects of another independent variable (music);[64] or (v) the effects of intensity were confounded with the effects of perceived autonomy.[65-68] Of the 33 remaining publications, three pairs referred to the same three studies (see Cox et al.[69] and Cox et al.;[70] Katula et al.[71] and McAuley et al.;[72] and Lochbaum et al.[73] and Lochbaum[74]), so there were 30 unique studies. Because the publications within each pair dealt with different dependent variables, all were retained. The 33 publications were organized into three groups. First, in 15 publications describing 12 studies, the levels of exercise intensity being compared represented different percentages of maximal capacity (see table I). Second, in ten publications, the levels of exercise intensity being compared were defined in relation to the VT, the LT or the onset of blood lactate accumulation (OBLA) [see table II]. Third, eight publications described affective responses to graded exercise tests (see table III). A total of 1007 individuals participated (491 males, 516 females). This number corresponds to an average sample size of 34, which, interestingly, is the number required to detect a difference between two dependent means, assuming a medium effect size (d = 0.5), alpha of 0.05, power of 0.80, and a two-tailed test. There was a noteworthy improvement in the diversity of samples compared with previous decades. The age range was extended in both directions, with studies now covering children and adolescents,[96,97,106] and older adults.[71,72,81] The average age was 26 years but the range extended from 12.5 years[106] to 68.2 years.[71] Likewise, about one-third of the studies either Sports Med 2011; 41 (8)
No. of subjects, sex and fitness level (agea and . VO2max)
Design and factors
Intensity, mode and duration
Measures and administration timepoints
Findings
Blanchard et al.[75]
12 F fit (23.4 y, 53.8 mL/kg/min) 12 F unfit (24.8 y, 33.0 mL/kg/min)
Mixed, fitness status (between) by intensity (within) by time
Low (50% HRR), high (85% HRR), stationary cycling, 30 min
SEES; upon arrival and when HRs returned to – 10 beats/min of when entered lab
Positive Well-being: no effect of fitness. Higher in the 50% than the 80% condition. Psychological Distress: in low intensity, no change for either fit or unfit. In high intensity, no change for fit but significant increase for the unfit. Fatigue: no changes
Blanchard et al.[76]
60 F physically active, (~22 y) 12 per group
Mixed, intensity/duration combination or control (between) by time
Low (50% HRR), high (85% HRR), stationary cycling, 15 or 30 min
EFI; upon arrival, at 7.5 min for 15 min bout and at 15 min for 30 min bout, when HRs returned to – 10 beats/min of entering the lab
No main effects of duration, so data from the two durations were collapsed. Tranquility: no change. Positive Engagement and Revitalization: increased significantly from pre to post, with no differences between intensities. Physical Exhaustion: decreased significantly in the 50%, no change in the 85% condition
Cox et al.[69]
24 F, active, 12 younger (18.6 y, 42.3 mL/kg/min) 12 older (40.2 y, 36.2 mL/kg/min)
Mixed, age (between) by intensity (within) by time
SAI; upon arrival, ~5 min later, 30, 60, 90 min after
No differences in state anxiety between conditions at baseline or 5 min post. At 30 and 60 min post, 80% was lower than control. At 90 min post, all conditions were different, with control showing the highest and 80% the lowest scores. SAI was lower than baseline in the control condition at post min 5, 30, 60. At 60%, all post-exercise timepoints were lower than baseline. At 80%, SAI was not below baseline at post min 5 but was lower at min 30, 60, 90
Cox et al.[70]
24 F, active, 12 younger (18.6 y, 42.3 mL/kg/min) 12 older (40.2 y, 36.2 mL/kg/min)
Mixed, age (between) by intensity (within) by time
SEES; upon arrival, ~5 min after, 30, 60, 90 min after
Fatigue: only time main effect (lower at 90 min post than baseline). Psychological Distress: main effect of time (lower throughout recovery than baseline) and an intensity by age interaction (but none of the follow-ups were significant). Positive Well-being: triple interaction. For younger, intensity effect (higher . for 80% VO2max) but no time effect or intensity by time interaction. For older, intensity effect and intensity by time interaction. Throughout . recovery, 60% and 80% VO2max higher than control. Increase from baseline only for 80% . VO2max at 30 min post
. 60% VO2max, 80% . VO2max, control, treadmill exercise, 33 min (2 min walk, 8 min ramp, 20 min steady, 3 min walk)
. 60% VO2max, 80% . VO2max, control, treadmill exercise, 33 min (2 min walk, 8 min ramp, 20 min steady, 3 min walk)
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Study
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ª 2011 Adis Data Information BV. All rights reserved.
Table I. Studies examining the relationship between exercise intensity (operationally defined as different percentages of maximal exercise capacity) and affective responses
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Table I. Contd No. of subjects, sex and fitness level (agea and . VO2max)
Design and factors
Intensity, mode and duration
Measures and administration timepoints
Findings
Daley and Huffen[77]
30 active adults, 16 M, 14 F, (31.7 y)
Within-subject
40% HRmax, 70% HRmax, stationary cycling, 20 min
SEES; before, 10 min during, 5 min after
Positive Well-being: no significant changes in the 40% condition but significant increase postexercise in the 70% condition. Fatigue: no significant changes in the 40% condition, but an increase over time in the 70% condition. Psychological Distress: no significant changes
Daley and Welch[78]
16 F, 8 active (20.1 y, 3.01 L/min) 8 inactive (20.1 y, 2.13 L/min)
Mixed, activity status (between) by intensity (within) by time
50–55% age-predicted HRmax, 80–85% agepredicted HRmax, treadmill exercise, 20 min
SEES; before, 10 min during, 5 min after
Active and inactive participants did not differ. Positive Well-being: during exercise, increase in the low-intensity condition but not the highintensity condition. In high-intensity condition, scores increased only after exercise and were higher than after the low-intensity condition. Psychological Distress: no intensity effect. Scores significantly reduced during and after exercise compared with before. Fatigue: no significant changes
Dunn and McAuley[79]
42 F low active (20 y, 32.5 mL/kg/min)
Within-subject
SEES, EFI; immediately prior, midpoint, immediately following, 20 min post
Positive Well-being: increased in both conditions, with no significant differences. Psychological Distress: significant decreases in 60% from pre to 20 min post and in 80% from immediately post to 20 min post. Fatigue: for 60%, decreases from pre to all remaining points. For 80%, decrease from immediately post to 20 min post. Exhaustion: reductions only in 60%, from pre to all remaining times. Positive Engagement: in 60%, increase from pre to immediately post and 20 min post. In 80%, increase from pre to 20 min post. Revitalization: in 60%, increases from pre to all remaining points. In 80%, increases from pre to immediately post and 20 min post. Tranquility: in 60%, increases from during and immediately post to 20 min post. In 80%, non-significant decrease during and immediately post, followed by a significant improvement over pre at 20 min post
. 60% VO2peak, 80% . VO2peak, treadmill walking or jogging, 20 min
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Study
Study
No. of subjects, sex and fitness level (agea and . VO2max)
Design and factors
Intensity, mode and duration
Measures and administration timepoints
Findings
Katula et al.[71]
80 sedentary older adults, 17 M (62.68 y, 23.35 mL/kg/min) 63 F (68.24 y, 19.34 mL/kg/min)
Within-subject
SAI (10 item); before and after
Significant decrease following light, nonsignificant decrease following moderate and a significant increase following maximal
McAuley et al.[72]
80 sedentary older adults, 17 M (66.58 y, 23.90 mL/kg/min) 63 F (67.50 y, 19.78 mL/kg/min)
Within-subject
Light (walking or stretching and toning, 29% HRR); moderate (1-mile indoor walking test, 49% HRR), maximal (maximal graded treadmill test, 96% HRR) Light (walking or stretching and toning), 28% HRR, 29.77 min, moderate (1-mile indoor walking test), 46%, 17.36 min, maximal (maximal graded treadmill test, 96% HRR, 11.42 min)
SEES; before and after
Kilpatrick et al.[80]
29 undergraduate students, 15 M, 14 F, (20.8 y, 35.1 mL/kg/min)
Within-subject
SEES; immediately after each exercise protocol and after 15 min quiet rest
Lochbaum et al.[73]
53 university students, 28 active: 15 M, 13 F (24.4 y, 49.9 mL/kg/min) 25 inactive: 13 M, 12 F, (23.4 y, 39.3 mL/kg/min)
Mixed, activity status (between) by intensity (within) by time
10 min warm-up and . 20 min at 60% VO2max (stationary cycling), followed by (i) additional time at 60% (3.9 min), (ii) cool-down (10 min) or (iii) sprint (2.7 min) [equated work] . 50–55% VO2max, . 70–75% VO2max, treadmill exercise, 30 min
Positive Well-being: with exercise intensity and duration as covariates, significant increase after light, non-significant decrease after moderate and significant decrease after maximal. Psychological Distress: with exercise intensity and duration as covariates, decrease in Psychological Distress after light, a nonsignificant increase after moderate and a significant increase after maximal. Fatigue: with exercise intensity and duration as covariates, no change after light and significant increases after moderate and maximal Fatigue: higher following the sprint compared to the cool-down, both at 0 and 15 min post. However, there was a significant decrease from 0 to 15 min post. Psychological Distress: trial by time interaction approached but did not reach significance. Distress elevated following the sprint at 0 min post and reduced thereafter. Positive Well-being: no significant effects
AD ACL; immediately prior, min 5, 15, 25 during, immediately after, min 10 and 20 after
Exercise Intensity and Pleasure
ª 2011 Adis Data Information BV. All rights reserved.
Table I. Contd
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‘Affective balance’ score was calculated (EA minus TA) from the AD ACL. Greater positive affect found during the 55% condition compared with the 70% condition, with the significant differences being during exercise and not during recovery. This was more pronounced among the inactive, who showed a significant decline during the 70% condition (mean positive affect balance score at min 25 of exercise of 0.0) but no change during the 55% condition
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Table I. Contd Study
No. of subjects, sex and fitness level (agea and . VO2max)
Design and factors
Lochbaum[74]
53 university students, 28 active: 15 M, 13 F (24.4 y, 49.9 mL/kg/min) 25 inactive: 13 M, 12 F (23.4 y, 39.3 mL/kg/min)
Mixed, activity status (between) by time (intensity not treated as a factor)
Oweis and Spinks[81]
21 F, (55.5 y, 22.0 mL/kg/min)
Within-subject
Smith et al.[82]
26 F college students (22 y, 39.2)
Within-subject
Tieman et al.[83]
26 M adults, (24.5 y) 13 high active (53.8 mL/kg/min) 13 low active (43.0 mL/kg/min)
Mixed, activity status (between) by intensity (within) by time
. Age and VO2max are presented as sample means.
. 50–55% VO2max, . 70–75% VO2max, treadmill exercise, 30 min
. Light (45% VO2max), moderate (60% . VO2max), high (75% . VO2max), control (zero resistance), stationary cycling, 10 min plus 2 min warm-up and 2 min cool-down . 40% VO2peak, 70% . VO2peak, quiet rest; stationary cycling, 25 min plus 5 min warm-up . 40% VO2peak, 75% . VO2peak, quiet reading; stationary cycling, 20 min
Measures and administration timepoints
Findings
AD ACL, SAI, immediately prior, min 5, 10, 25 during, immediately after, min 10 and 20 after
The three measurement timepoints during and after exercise were averaged. For 55%, EA and TA were elevated from baseline both during and after exercise. The inactive group showed increases in TA and SAI over time, whereas the active showed no change in TA and a decrease in SAI from pre to post. No group by time interaction for EA. For 70%, EA and TA increased from baseline during and after exercise. SAI increased only during exercise. TA was higher for the inactive throughout and showed a larger increase during and after than in the active. EA showed a significant group by time interaction but no significant follow-ups. No group by time interaction for SAI
AD ACL, FS; ‘directly following each physical activity bout’
EA: lower after light than control, higher after high than light. TA: lower after high than control and light. FS: lower after high than light and moderate
SAI (10 item), SAM; SAI: upon arrival, immediately before and 20 min after. SAM: min 15 and 25 during
SAI: No intensity effects. Scores decreased post compared with pre-preparation and preexercise. SAM: valence was higher (more positive or pleasant) during cycling at 40% than 70%. Likewise, dominance was higher during 40% than 70%
SAI; upon arrival, 20 and 5 min prior to, 5 and 25 min after
Among low active, SAI was lower after light cycling compared with quiet rest and hard cycling. Among high active, SAI was unchanged. Additional analyses examined SAI responses to a maximal cycling test. SAI was assessed 60 and 5 min prior to and 5 min after the test. Among low active, SAI increased 5 min post compared with 60 and 5 min pre. Among high-active, scores were unchanged
AD ACL = Activation Deactivation Adjective Check List[84]; EFI = Exercise-induced Feeling Inventory[85]; EA = energetic arousal; F = female; FS = Feeling Scale[19]; HRmax = maximal [86] heart rate; HRR = heart rate reserve; HRs = heart rates; lab. = laboratory; M = male;. SAI = State Anxiety portion of the . State-Trait Anxiety Inventory ; SAM = Self-Assessment Manikin[87]; SEES = Subjective Exercise Experiences Scale[88]; TA = tense arousal; VO2max = maximal oxygen uptake; VO2peak = peak oxygen uptake; ~ indicates approximately.
Ekkekakis et al.
Sports Med 2011; 41 (8)
a
Intensity, mode and duration
No. of subjects, sex and fitness level (agea . and VO2max)
Design and factors
Intensity, mode and duration
Measures and administration timepoints
Findings
Bixby and Lochbaum[89]
7 M, 8 F, high-fit (23.53 y, 48.99 mL/kg/min) 5 M, 12 F, low-fit (23.52 y, 34.74 mL/kg/min)
Mixed, fitness level (between) by intensity (within) by time
Low (75% of HR at VT), high (‘just below’ [3 beats/min] HR at VT), recumbent cycling, 30 min
AD ACL; 5 min into baseline, start of exercise, 10, 20, 30 min of exercise, 10, 20, 30 min of recovery
Bixby et al.[49]
27 college students, 14 F (23.1 y, 37.1 mL/kg/min) 13 M (23.6 y, 40.9 mL/kg/min)
Within-subject
Low (75% of HR at VT), high (‘just below’ HR at VT), stationary cycling, 30 min
VAMS at 15, 10 and 5 min before, 10, 20, 30 min during and 10, 20, 30 min after; PANAS 5 min before, 20 min during, 20 min after
Blanchard et al.[90]
44 community residents, 35 F, 9 M (41.5 y, 30.1 mL/kg/min)
Between-subject
High-intensity short duration (second VT, . 70.3% VO2peak, 19.5 min), low-intensity long duration (first VT, . 49.8% VO2peak, 35.25 min), volume of work equated, stationary cycling
SEES; pre, 5 min post
Ekkekakis et al.[91]
14 F (21.2 y, 47.7 mL/kg/min) 16 M (21.5 y, 56.6 mL/kg/min)
Within-subject
‘Affective balance’ score was calculated from AD ACL (EA minus TA). Significant intensity by time interaction, with more positive affect during the lowintensity condition (no differences during recovery). Fitness group main effect significant (fit showed more positive affect overall) but no interaction with time or with three-way (group by intensity by time) VAMS: No differences at baseline or recovery. During low intensity, no change at min 10, but significant improvement at min 20 and 30. During recovery, scores still higher than baseline until min 30. During high intensity, scores lower than baseline throughout the bout. During recovery, scores better than all exercise timepoints and the last baseline time point. No differences between intensities during recovery. PANAS: Positive Affect was higher during exercise than during baseline and recovery (no intensity effects). During lowintensity exercise, Negative Affect lower than baseline during exercise and recovery. During high intensity, Negative Affect not reduced during but only after. The two intensity conditions were different during exercise but not during baseline and recovery Participants were enrolled in a 12 wk programme and data were drawn from exercise bouts #9 (wk 3), #18 (wk 6) and #27 (wk 9). Positive Well-being: increased for bouts #9 and #18. Psychological Distress: decreased for bouts #9 and #18. Fatigue: increased for bout #18. Exercise condition did not influence changes in Positive Well-being and Psychological Distress. In the high-intensity shortduration condition, Fatigue showed larger increase than low-intensity long-duration condition. Fitness did not influence the changes in any variable Regardless of intensity, FS improved from pre- to all-times post-exercise. During exercise, FS declined significantly in the >VT condition, whereas decreases during
. 20% VO2max
VT, treadmill, 15 min
FS, AD ACL; pre-, postcool-down, 10, 20 min post; FS also every 3 min during
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Study
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ª 2011 Adis Data Information BV. All rights reserved.
Table II. Studies examining the relationship between exercise intensity (operationally defined in relation to the ventilatory threshold [VT], lactate threshold [LT] or the onset of blood lactate accumulation) and affective responses
Study
652
ª 2011 Adis Data Information BV. All rights reserved.
Table II. Contd No. of subjects, sex and fitness level (agea . and VO2max)
Design and factors
Intensity, mode and duration
Measures and administration timepoints
Findings
not significant. Regardless of intensity, EA increased from pre- to post-cool-down, then decreased by 10 min post. Regardless of intensity, TA at 10 and 20 min post was lower than post-cooldown No differences between intensities
20 adults; 12 M, 8 F (23.4 y, 34.2 mL/kg/min)
Within-subject
85% of VT for 30 min, 105% of VT for ~24 min, total work equated, treadmill exercise
AD ACL, PANAS; postexercise only
Kilpatrick et al.[93]
37 college students (23.9 y); 20 M, (37.3 mL/kg/min) 17 F (32.1 mL/kg/min)
Within-subject
85% of VT (64.7% . VO2max) for 30 min, 105% of VT (50.1% . VO2max) for 24.2 min, total work equated, stationary cycling
FS, immediately before exercise, every 6 min (85% VT) or every 5 min (105% VT), after cool-down, 15 min post
No FS differences between intensities before or after exercise but a significant intensity by time interaction during exercise. No significant changes at 85% VT but a significant decrease from baseline throughout 105% VT
Parfitt et al.[94]
12 M sedentary (36.5 y, 34.1 mL/kg/min)
Within-subject
Below OBLA (39.8% . VO2max), above OBLA . (72.6% VO2max), selfselected (54.1% . VO2max), treadmill exercise, 20 min
FS; pre, last 45 sec of each 5 min period during, last 45 sec of each 10 min period following up to 30 min
During exercise, FS became less positive and ultimately negative above threshold but remained positive and stable in the other two conditions. The levels were more positive during self-selected and below threshold than above threshold, with no difference between below threshold and selfselected. FS was more positive at all timepoints post compared with pre, with no differences between intensities
Rose and Parfitt[95]
19 F, sedentary (39.37 y, 36.1 mL/kg/min)
Within-subject
FS; last 45 sec of each 5 min period during, after cool-down, at 10, 20 min post
FS less positive >LT than LT, FS was less positive post than pre (but more positive by 10 min post). For all other conditions, no difference between pre and post
Schneider and Graham[96]
146 adolescents (14.79 y); 82 M, (44.02 mL/kg/min) 64 F, (33.47 mL/kg/min)
Mixed, low-high behavioural activation (between) by low-high behavioural inhibition (between) by intensity (within) by time
FS, AD ACL; FS at 0, 10, 20, 30 min during, 10 min post, AD ACL at 0, 30, and 10 min post
Adolescents with high behavioural inhibition or low behavioural activation showed lower FS regardless of intensity. Significant intensity by time interaction, with hard leading to decreases in FS during exercise. For EA, those with high behavioural activation scored higher in the moderate condition but not in the hard condition post-exercise. No main effects or interactions for TA
. LT (85.27% VO2max), self-selected (60.20% . VO2max), treadmill exercise, 20 min Moderate (80% of the Watts @VT), hard (Watts at 50% of the difference between VT . and VO2max), stationary cycling, 30 min
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Kilpatrick et al.[92]
>LT = above the LT; M = male; OBLA = onset of blood lactate accumulation; PANAS = Positive and Negative Affect Schedule[98]; SEES = Subjective Exercise Experiences Scale[88]; . TA = tense arousal; @VT = at the VT; VT = above the VT; VO2max = maximal oxygen uptake; EA = energetic arousal; VAMS = Visual Analogue Mood Scale[99]; . VO2peak = peak oxygen uptake; ~ indicates approximately; # indicates number.
. Age and VO2max are presented as sample means. a
ª 2011 Adis Data Information BV. All rights reserved.
AD ACL = Activation Deactivation Adjective Check List[84]; EA = energetic arousal; F = female; FS = Feeling Scale[19]; HR = heart rate; @LT = at the LT;
FS; 5 min pre, immediately before the start, last 45 sec of each 5 min period during, 5, 10, 15, 30 min post
No difference in FS between the low and selfselected intensity. FS became less positive during exercise in the high-intensity condition but not in the low- or self-selected intensity condition. In pre-to-post analyses, FS was found to be lower immediately post and 5 min post in the high-intensity condition. There was also an increase in FS from 5 min pre to 30 min post in the self-selected condition
653
Low (80% of power output @VT), high (130% of power output @VT), self-selected, stationary cycling, 15 min (3 min warm-up) 22 adolescents (13.3 y); 11 M, (48.2 mL/kg/min) 11 F, (38.4 mL/kg/min) Sheppard and Parfitt[97]
Within-subject
No. of subjects, sex and fitness level (agea . and VO2max) Study
Table II. Contd
Design and factors
Intensity, mode and duration
Measures and administration timepoints
Findings
Exercise Intensity and Pleasure
targeted physically inactive individuals or examined physical activity and/or physical fitness as a moderator. Tests of aerobic. capacity were conducted in 27 of 29 studies. VO2max averaged 39 mL/kg/min but ranged from 19.3 mL/kg/min (63 older women)[71] to 67.7 mL/kg/min (11 male distance runners).[100] As was the case in the earlier review, nearly all studies took place in a laboratory. The treadmill (walking or running) was used in 14 studies and stationary cycling was used in the remaining 16 studies. With the exception of studies investigating affective responses to graded exercise tests, the duration of exercise bouts generally ranged between 15 and 30 minutes. In a noteworthy new development, some studies addressed the problem of confounding the effects of intensity with those of larger amounts of work (when bouts of lower and higher intensities are performed for the same duration) by varying the duration to produce isocaloric bouts.[80,90,92,93] Perhaps responding to the call for tracking of affective changes during the bouts,[22] two-thirds of the studies included at least one assessment of affect during exercise, whereas pre- to postexercise or post-test-only assessment protocols were reported in one-third (ten of 33) of the publications. Consistent with this trend, the singleitem FS[19] was used in 12 studies, followed by the 20-item Activation Deactivation Adjective Check List[84] in nine and the 12-item Subjective Exercise Experiences Scale[88] in eight. Of the 22 studies comparing the effects of distinct bouts performed at different intensities, 14 compared two levels of intensity, precluding the detection of curvilinear dose-response patterns. Interestingly, a series of studies compared bouts performed at different imposed levels of intensity to a bout performed at self-selected intensity.[94,95,97] Given their theoretical and practical interest, these studies were reviewed in detail elsewhere.[109] The assessment of fitness and close monitoring of intensity levels, the examination of diverse samples and the frequent sampling of affect are all signs of improved methodologies. On the other hand, some methodological problems persisted, including confounds with the ecological and social setting,[71,72] imprecise standardization Sports Med 2011; 41 (8)
Design and factors
Intensity, mode and duration
Measures and administration timepoints
Findings
FS during the fifth (final) min of each intensity run
Significant decline in FS over time, but followup analyses showed that the decline was only significant from OBLA to 10% above OBLA (where FS ratings were below zero). No significant relationships between FS and other variables below and at OBLA. Above OBLA, FS was related to RPE (-0.67), HR (-0.43), and ventilation (-0.41)
No. of subjects, sex and fitness level (agea . and VO2max)
Acevedo et al.[100]
11 competitive distance Within-subject runners, (22.6 y, 67.7 mL/kg/min)
Acevedo et al.[101]
7 M well-trained runners 18–39 y (28.71 y, 61.01 mL/kg/min)
Within-subject
Ekkekakis et al.[102]
Group A: 13 F (22.8 y, 46.9 mL/kg/min); 17 M (24.4 y, 51.5 mL/kg/min) Group B: 14 F (21.2 y, 47.7 mL/kg/min) 16 M (21.5 y, 56.6 mL/kg/min)
Within-subject (the two groups were analysed separately)
Eight timepoints during max. FS; every min during test: first 2 min, min before, min of, 2 min after the VT, last 2 min; treadmill exercise, 11.3 min (group A), 12.1 min (group B)
Ekkekakis et al.[103]
9 F normal-weight (43.7 y, 25.9 mL/kg/min) 8 F overweight (39.1 y, 24.0 mL/kg/min) 7 F obese (44.7 y, 17.5 mL/kg/min)
Mixed, weight group (between) by time
Six timepoints during max. test (rest, warm-up, 1 min before VT, min of VT, min after VT, final min) plus cool-down and 20 min seated recovery; treadmill exercise
FS, AD ACL; AD ACL before, immediately after, after cool-down, min 10 and 20 post, FS during
FS declined gradually during the test and was lower overall for the obese women compared with the other two groups. Energy increased post-exercise in normal-weight and overweight but not in obese, then returned to baseline by min 10 of recovery. Tiredness decreased postexercise regardless of group. Tension decreased compared with baseline, regardless of group, during first 10 min of recovery. Calmness decreased immediately postexercise but returned to baseline after cooldown
Hall et al.[104]
30 college students, 13 F, 17 M (23.9 y, 49.6 mL/kg/min)
Within-subject
Eight timepoints during max. test: first 2 min, min before, min of, 2 min after the VT, last 2 min; treadmill exercise, 11.3 min
FS, AD ACL; AD ACL before, immediately after cool-down, min 10 and 20 post; FS also every min during
During the test, FS gradually declined. Every min-to-min change starting with 1 min after the VT and until test termination was significant. From pre to immediately post, increase in EA, decreases in TA from pre to min 10 and 20 post. FS improved from pre to all timepoints post
. . VO2 10% below OBLA, VO2 at . OBLA, VO2 10% above OBLA, consecutive runs; treadmill running (a minimum of 5 min) per intensity
. 60% VO2max (10 min), 75% . . VO2max (10 min), 90% VO2max . (5 min), 100% VO2max (2 min), 4 min walks in-between; treadmill running
VAS from ‘excitement’ Affect ‘relatively unchanged’ from 60% to 75% . to ‘apprehension’ at the VO2max but a significant change toward . end of each ‘apprehension’ from 75% to 90% VO2max, followed again by a plateau from 90% to 100% . VO2max Quadratic decline patterns in FS across both protocols. Follow-up analyses showed that the only three-point segments for which quadratic decline was significant were those starting with the VT
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ª 2011 Adis Data Information BV. All rights reserved.
Table III. Studies examining the relationship between exercise intensity (operationally defined as different stages of graded exercise tests) and affective responses
ª 2011 Adis Data Information BV. All rights reserved.
. a Age and VO2max are presented as sample means. [19] AD ACL = Activation Deactivation Adjective Check List[84]; EA = energetic arousal; F = female; FS = Feeling . Scale ; M = male;. max. = maximum; .OBLA = onset of blood lactate accumulation; RPE = Rating of Perceived Exertion[108]; TA = tense arousal; VAS = Visual Analogue Scale; VO2 = oxygen uptake; VO2max = maximal VO2; VT = ventilatory threshold.
FS declined continuously during the test (compared with min 1, all subsequent timepoints were lower). However, declines were larger from the min after the VT to the end. No change in FS from pre- to post-0 or post-5 but increases from pre- to post-10 and post-20 FS; before exercise, every min during, 0, 5, 10, 20 min post 20 F, inactive (23.2 y, 33.6 mL/kg/min) Welch et al.[107]
Within-subject
Age group did not show main effect or interaction with time. Significant declines in FS after the VT (quadratic declines in FS from VT to final min in both men and boys) FS; every 2 min during 23 M, sedentary: 13 men (35.3 y), 10 boys (12.5 y) Sheppard and Parfitt[106]
Mixed, age (between) by time
FS stable for stages 1 and 2 but declined sharply during stages 3 and 4. There was a rebound 10 min post FS, every 2 min during, 10 min post
Four timepoints during max. test: stage 1 (50 Watts), stage 2 (before VT), stage 3 (VT), stage 4 (last); recumbent cycling Five timepoints during max. test: second min, min before VT, min of VT, second min after VT, last min; stationary cycling, 18.9 min for men, 14.0 min for boys Six timepoints during max. test: first min, min before VT, min of VT, min after VT, second min after VT, last min; stationary cycling, 10.43 min 12 M college students, (24 y, 40.4 mL/kg/min) Hall et al.[105]
Within-subject
Findings Measures and administration timepoints Design and factors No. of subjects, sex and fitness level (agea . and VO2max) Study
Table III. Contd
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Intensity, mode and duration
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of intensity,[61,62] variable periods before the post-activity assessment[75,76] and post-test-only designs.[80,81] What is remarkable about the new crop of studies is the consistency of their findings. Unlike the earlier review, in which a slight majority of the studies (54%) indicated a lack of intensity effects,[22] all but one of the studies examined in this review showed a significant intensity effect for at least one of the dependent variables. The general conclusion that emerges is that there is an inverse relationship between exercise intensity and affective responses, a phenomenon that appears stronger among those studies that included assessments during exercise. In the only exception,[92] in which no significant intensity effects were reported, the study was probably underpowered (n = 20) and the dependent variables were only assessed postexercise. In the following sections we examine the most significant trends more closely. 3.1 The Importance of Physiological Landmarks
In their conclusions, Ekkekakis and Petruzzello[22] had noted that ‘‘a more appropriate avenue for future research would be to define exercise intensity in terms of metabolic landmarks with biological significance for the organism, such as the gas exchange or the lactate threshold, or the power-time asymptote’’ (p. 357). Consistent with this recommendation, in half of the new studies, the intensity was set in relation to the VT,[49,89,90,92,93,96,97,102-107] the LT[95] or OBLA (4 mmol/L).[94,100] The experimental protocols varied, with some studies involving incremental exercise tests on the treadmill or cycle ergometer,[91,102-107] some involving a series of consecutively performed short bouts[100] and some involving steady-workload bouts performed on different days.[49,89,91,93-95,97] Furthermore, studies involved diverse samples, including adolescents,[96,97,106] inactive young or middle-aged adults,[94,95,103,106,107] regularly active college students[49,89,91,93,102,104,105] and trained athletes.[100] Despite their differences, these studies produced the first reliable evidence of a dose-response Sports Med 2011; 41 (8)
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phenomenon. Nevertheless, ‘‘while it is possible to dissociate the [LT] from the [VT] by using a variety of manipulations of protocol and dietary status owing to the complexity of both lactate accumulation and ventilatory control, in most situations the [LT] and [VT] are coincident’’[110] (p. 241). This claim is supported by a metaanalysis.[111] On the other hand, the relation of these thresholds to the OBLA is less clear.[112] Although the concept of the OBLA guarantees objectivity (since it is based on a ‘fixed’ accumulation of 4 mmol/L), the problem is that it ‘‘takes no account of inter-individual differences in the rate of blood lactate accumulation’’[110] (p. 245), although such differences can be large. Furthermore, a level of blood lactate accumulation of 4 mmol/L, which is the value commonly designated as OBLA,[94,100] is ‘‘reached at a significantly higher exercise intensity than the [LT]’’[110] (p. 245) and typically exceeds the maximum lactate steady state. Therefore, unlike intensities proximal to the VT or LT, which can be maintained for a long time without a severe homeostatic perturbation, an intensity corresponding to the OBLA makes
5 4
Highactivation displeasure (tension, distress)
Higher activation
6 Highactivation pleasure
Maximal treadmill test
>VT
Selfpaced treadmill walk
End
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@VT Min 15
(energy, vigour)
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Min 9
VT
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Perceived activation (Felt Arousal Scale)
pattern, a finding that represents a major advance in this line of research. These studies have shown that exercise intensities below the VT, LT or OBLA typically do not have a negative impact on during-exercise affective states when analyses of change are performed at the level of groups. In fact, such intensities may improve affect during exercise either at the level of entire groups[49] or at least within subgroups.[91,94,95] In contrast, when the intensity exceeds these physiological landmarks, there is a decline in the positivity of affect (see figure 1). Studies of incremental exercise tests have shown that, as intensity increases and approaches maximal capacity, declines are reported by an increasing percentage of participants. Finally, when the intensity reaches maximal capacity, a decline is reported by all or nearly all participants.[45,102,104] At that point, the average rating is not only significantly less positive compared with baseline but it also crosses into affective negativity (worse than ‘neutral’ on the FS). It should be noted that the VT and LT may be driven by partly dissociable mechanisms and cannot be assumed to represent the same underlying
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Affective valence (Feeling Scale) Fig. 1. Left circle: the circumplex model of affect, which can be used as a template (or two-dimensional ‘map’) for plotting affective responses to exercise of different intensities. The horizontal dimension represents ‘affective valence’ (pleasure/displeasure) and the vertical dimension represents perceived activation. This ‘affective space’ is divided into four quadrants: (i) high-activation displeasure (e.g. tension, distress, nervousness, jitteriness); (ii) high-activation pleasure (e.g. energy, vigour, excitement, revitalization); (iii) low-activation displeasure (e.g. tiredness, boredom, fatigue, lethargy); and (iv) low-activation pleasure (e.g. calmness, . relaxation, tranquility, serenity). Middle . circle: affective responses to 15 min bouts of treadmill exercise performed at intensities (i) 20% VO2max VT. The decreases in pleasure during the VT condition, the decrease reached statistical significance as early as min 6 (d = -0.53) and grew increasingly larger through min 15 (d = -1.22). Data from Ekkekakis et al.[91] Right circle: for comparison, affective responses to a 15 min self-paced treadmill walk (showing an increase in pleasure, with effect size d = 1.18) and a graded treadmill test to exhaustion with . average duration of 11.3 min (showing a decrease in pleasure, with effect size d = -2.08). Data from Ekkekakis et al.[38] and Hall et al.[104] VO2max = maximal oxygen uptake; VT = ventilatory threshold; @VT = at the VT; >VT = above the VT;
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the maintenance of a physiological steady state impossible. For example, in the study by Parfitt et al.,[94] a 20-minute bout of treadmill exercise at an intensity that initially corresponded to 4 mmol/L culminated in an average accumulation of 7.17 mmol/L. These facts should be kept in mind when comparing the studies summarized here. Group-level declines in pleasure beyond the VT, LT and OBLA have been found both in studies that used incremental protocols and in those that compared steady-workload bouts performed at intensities below and above these thresholds. The former have shown that declines only begin when the intensity exceeds the VT.[102,104,105] Similarly, the latter have shown that declines only occur when the intensity is initially set at or above the VT,[49,89,91,93,97] the LT[95] or OBLA.[94] The only exceptions have been two studies in which affective variables were not assessed during exercise but rather only several minutes post-exercise.[90,92] In these studies, there were no differences in affective states after bouts performed below or above the VT. This, however, is not surprising, since research has established that dose-response effects that occur during exercise tend to dissipate rather rapidly once the bouts are terminated, especially among young and healthy participants.[49,91,93] In studies that examined the affective responses of physically inactive college women,[107] physically inactive boys and men[106] or physically inactive and obese middle-aged women[103] to incremental tests to exhaustion, a decrease in FS scores started from the beginning of the test rather than only after VT. However, the rate of decline was larger above the VT than below (e.g. with d = 0.62, 0.54, 0.72 from the beginning to the VT and 1.56, 1.72, 1.54 from the VT to the end in Welch et al.[107] and the boy and men samples of Sheppard and Parfitt,[106] respectively). In these studies, the combination of the physically inactive and/or obese status of the participants and the intimidating nature of the exercise tests possibly accounted for the earlier onset of the decline in pleasure. A question that arises from these data is: is it possible that the effect of intensity is confounded by the effect of total work, since most of these ª 2011 Adis Data Information BV. All rights reserved.
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studies compared bouts of higher-versus-lower intensity but of the same duration? To address this issue, Kilpatrick et al.[93] adjusted the duration to produce bouts of different intensities but equal caloric expenditure. Thus, .they compared 30 minutes of cycling at 85% of VO2. at VT and 24 minutes (on average) at 105% of VO2 at VT. The results showed that the sub-VT bout did not produce a decline in pleasure during exercise but the supra-VT bout did. Thus, the affective decline can be specifically attributed to the suprathreshold intensity rather than differences in total energy expenditure. 3.2 The Phenomenon of Individual Variability
Making the case for the need to evaluate the magnitude and causes of inter-individual differences in affective responses, Ekkekakis and Petruzzello[22] had noted that ‘‘even patterns that appear consistent when examined at a group level might subsume psychologically important individual variation’’ (p. 367). Several studies have since focused on this issue.[43,45,48,94,95,107] This is highlighted here because the elevation of variability from being treated as error to becoming a bona fide topic of investigation represents a significant paradigm shift. From a theoretical perspective, the study of variability is important because it is reasonable to assume that part of it does not reflect random error (including errors in the determination of the VT or LT) but may rather reflect systematic sources of variance, at least some of which may be psychological (e.g. differences in personality, temperament or situational appraisals). From a practical standpoint, if the factors that contribute to variability in affective responses are identified, this could spur the development of individually tailored interventions, thus optimizing the exercise experience. Recently, de Geus and de Moor[113] presented a conceptual model, according to which adherence to exercise may be influenced by immediate affective responses and long-term effects of exercise on self-esteem. In turn, genetically determined individual differences can influence both of these mechanisms by making some Sports Med 2011; 41 (8)
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individuals more and others less likely to experience improved affect and self-esteem. Based on this model, de Geus and de Moor[113] advocated the customization of exercise prescriptions: ‘‘We should not close our eyes to human genetic variation. Some individuals may require a different exercise programme which emphasizes the appetitive aspects for an individual and reduces the aversive aspects. The exact strategy to optimize this balance requires a furthering of our understanding of genetic differences in the psychological responses to exercise. In some cases, obtaining increased adherence can be as simple as reducing exercise intensity’’ (p. 58). Acknowledging this variability is crucial. It should be noted that one of the reasons that delayed the investigation of the affect-adherence link was the belief that nearly all individuals find exercise pleasant. For example, Morgan and O’Connor[114] had argued that investigating this link might seem ‘‘intuitively defensible’’ but is actually ‘‘simplistic’’ and ‘‘probably not necessary.’’ The reason was that ‘‘roughly 80–90% of individuals’’ report that they ‘‘feel better’’ when they exercise but ‘‘50% drop out’’ (p. 116). The newer data challenge the notion of a nearlyuniversal ‘feel-better’ exercise effect (see figure 2).
The key was the shift from examining only pre- to post-exercise changes to tracking the trajectory of affective change during and after the exercise bout. A conceptual framework to facilitate the interpretation of these findings was proposed by Ekkekakis et al.[45] Based on evolutionary principles, it was argued that a homogeneous response indicates high adaptational significance (i.e. strong implications for optimizing Darwinian fitness). This is because responses closely tied to either the promotion or the endangerment of adaptation tend to spread throughout the population. Thus, a homogeneously positive affective response indicates approach towards a useful stimulus, whereas a homogeneously negative affective response indicates avoidance of a dangerous stimulus. On the other hand, variable responses (e.g. some individuals responding with increases and others with decreases in pleasure) indicate either a lack of adaptational significance or a trade-off between benefits and risks. For example, individual differences in pain sensitivity or tolerance can be explained by the fact that those possessing these traits may benefit in some circumstances (e.g. being able to withstand an injury during a fight, thus gaining a
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Fig. 2. Scatter plots of the relation between blood lactate accumulation at the end of the exercise bout and the percentage of participants reporting increases (a) or decreases (b) in Feeling Scale (FS) scores during the bout. Each marker represents the results from one bout from several different studies. Data points (c) and (g) are marked in light grey because they represent bouts performed at self-selected intensities. A second-degree polynomial has been fitted to the data to illustrate the trend. Data from Parfitt et al.:[94] below the lactate threshold (LT) [point a], above the LT (point b) and self-selected intensity (point c); Rose and Parfitt:[95] below the LT (point d), at the LT (point e), above the LT (point f) and self-selected intensity (point g); Ekkekakis et al.:[91] below the ventilatory threshold (VT) [point h], at the VT (point i) and above the VT (point j).
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a
FS declined FS stable FS improved
b
100 90
% of participants
80 70 60 50 40 30 20 10 0 15 min self-paced walk
30 min cycling at . 60% VO2max
Incremental Cycling to treadmill exhaustion test under dehydration
Warm-up Min 2 to 1 (3 min walk, min post2 min jog) VT
1 min post-VT to end
End to Min 1 to Min 2 of min 1 of min 2 of cool-down cool-down cool-down to min 20 of recovery
Fig. 3. (a) Percentages of participants reporting increases, no change and decreases in Feeling Scale (FS) scores during exercise bouts with different demand characteristics. The data show generally positive changes at low intensities, generally negative changes at high intensities and heterogeneity at mid-range intensities. Data from Ekkekakis et al.[45] (b) Percentages of participants reporting increases, no change and decreases in FS scores across different stages of a graded treadmill test to exhaustion and subsequent recovery. The data show mostly positive changes with light intensities (below the ventilatory threshold [VT]), heterogeneity close to the VT and homogeneously negative changes above the VT. The termination of the test is followed by a rapid and homogeneously positive ‘rebound’ during the . cool-down and, progressively, the re-emergence of heterogeneous changes during the 20 min recovery. Data from Ekkekakis et al.[45] VO2max = maximal oxygen uptake.
critical advantage, or tolerating hard physical labour, thus accumulating more resources) but risk their safety in others (e.g. bringing themselves closer to biological limits, thus risking injuries, exhaustion or death). The data in figure 2 suggest that the range of variable affective responses (i.e. approximately 20–60% reporting improvements and 20–45% reporting declines) is below a blood lactate accumulation of 3.5–4.0 mmol/L. Conversely, beyond this intensity, the percentage of those reporting increases in pleasure drops to 10–15%, whereas the percentage of those reporting decreases in pleasure rises to 75–80%. The data in figure 2 also suggest that, when the intensity is submaximal, it is possible for relevant traits or situational appraisals to produce deviations from this general trend. Despite a lactate accumulation of 4.34 mmol/L, the self-selected intensity condition in the study by Parfitt et al.[94] resulted in 92% of the participants (sedentary men, mean age 36.5 years) reporting improvements in pleasure. The perception of autonomy that the ª 2011 Adis Data Information BV. All rights reserved.
self-selection of intensity entailed was the likely reason for the markedly different response compared with the other conditions (also see next section). Figure 3 illustrates two additional noteworthy phenomena. First, the positive affective responses to self-paced walking seem to be shared by most participants. In a re-analysis of data that included affective responses to short self-paced walks, Ekkekakis et al.[45] noted improved FS scores in 74–77% of individuals. Second, homogeneously positive affective responses also appear after the cessation of strenuous exercise. This ‘affective rebound’ is shared by nearly all (>95%) participants. Having established that affective responses to exercise can vary between individuals, the next step is to investigate the sources of this variability. Based on evidence of variability in the intensity of activity that individuals choose and can tolerate when forced, Ekkekakis et al.[46] proposed the constructs of intensity preference and intensity tolerance. Intensity preference was defined as ‘‘a predisposition to select a particular level of exercise intensity when given the opportunity Sports Med 2011; 41 (8)
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(e.g. when engaging in self-selected or unsupervised exercise).’’ Intensity tolerance was defined as ‘‘a trait that influences one’s ability to continue exercising at an imposed level of intensity even when the activity becomes uncomfortable or unpleasant’’ (p. 354). The measure that was developed to assess these two constructs was the Preference for and Tolerance of the Intensity of Exercise Questionnaire (PRETIE-Q).[46,115] At the core of the conceptualization of intensity preference and intensity tolerance was the idea that what determines whether an exercise intensity is preferred or can be tolerated, is the pleasure or displeasure that is experienced. Consistent with this notion, both the preference and the tolerance scales of the PRETIE-Q predicted FS scores during exercise at the VT (16–18% and 16–21% of the variance, respectively).[46] Neither scale was a significant predictor during exercise below the VT and only the tolerance scale was a significant predictor above the VT (16–29% of the variance).[46] Furthermore, the preference (but not the tolerance) scale accounted for significant portions of the .variance in self-selected intensity (percentage of VO2 at VT), contributing 18–19% beyond the variance accounted for by age, body . mass index and VO2max.[116] Conversely, the tolerance scale accounted for significant portions of the variance in the amount of time individuals persevered during incremental treadmill tests after reaching their VT, contributing 14–20% beyond the variance accounted for by age, body mass index, . physical activity habits and even VO2max.[117] In a study based on the theory of psychological reversals, Legrand et al.[118] tested whether the individual-difference variable of telic dominance could moderate affective responses during bouts of treadmill running at an intensity that was maintained near a respiratory exchange ratio (RER) of 1.0 for 10 minutes. A telic-dominant person tends to avoid high levels of arousal (experiencing them as tension or anxiety) whereas a paratelic-dominant person tends to seek out high levels of arousal (experiencing them as excitement). Participants who scored high on telic dominance reported significantly less pleasure than those who scored . low at minute 6 and 9, after controlling for VO2max. ª 2011 Adis Data Information BV. All rights reserved.
Ekkekakis et al.
Finally, Schneider and Graham[96] investigated the role of the individual-difference variables of behavioural activation and behavioural inhibition. The behavioural-activation trait refers to high sensitivity to reward, approach motivation and propensity for positive affective responses. Conversely, the behavioural-inhibition trait refers to high sensitivity to punishment, withdrawal motivation and propensity for negative affective responses. Behavioural activation and inhibition did not interact with exercise intensity (below or above VT) or time but both had main effects on affective responses. Adolescents scoring highly on behavioural activation reported significantly higher and those scoring highly on behavioural inhibition reported significantly lower levels of pleasure before, during and after exercise. 3.3 Affective Responses and the Self-Selection of Intensity
Ekkekakis and Petruzzello[22] had noted that ‘‘there seems to be sufficient theoretical justification to recommend the systematic study of the distinction between ‘self-selected’ or ‘preferred’ versus imposed exercise doses’’ (p. 367). They reviewed results from earlier research showing that, although the correlation between FS scores and HR or RPE became more negative as exercise intensity increased, the correlation was positive when the intensity was self-selected. This was consistent with an observation by Dishman et al.[119] that ‘‘[RPE] at preferred intensities of exercise can uncouple from indicators of relative metabolic intensity typically linked with [RPE]’’ (p. 787). A possible reason for this intriguing ‘uncoupling’ is that the self-selection of intensity creates a sense of autonomy and control, allowing exercisers to cognitively ‘reframe’ the exercise experience (i.e. it is not something I must do, it is something I choose to do). As shown in figure 2, the ‘uncoupling’ phenomenon also applies to FS scores. Eleven of the 12 sedentary men studied by Parfitt et al.,[94] despite an average lactate accumulation of 4.34 mmol/L, reported feeling better when asked to self-select the intensity, yielding the most positive pattern of responses (compared with imposed intensities at 2.5 and 4.0 mmol/L of lactate accumulation). Sports Med 2011; 41 (8)
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For detailed discussions of the implications of self-selected exercise intensity for affective responses, readers are referred to recent reviews.[109,120] Nevertheless, a mention of this issue was deemed necessary due to its significance for the intensityaffect link. It has been suggested that what guides people in the selection of an exercise intensity is the pleasure or displeasure they experience. In other words, in this case as in many others, people seek to maximize pleasure and/or minimize displeasure.[121] Acevedo et al.,[100] commenting on their finding of a drop in FS scores above the OBLA, argued that this apparently perceptible event could be used by exercisers as a guide in regulating their intensity. Specifically, they wrote that ‘‘the documented nonlinear drop in [FS scores] following [the OBLA] versus the linear increase demonstrated by [RPE] may be clearly identified by exercisers’’ (p. 272). Working on the same idea but focusing on the VT, Ekkekakis et al.[102] found quadratic declines in pleasure at intensities above the VT and suggested that these declines ‘‘could be valuable as a practical marker’’ of the VT, such that ‘‘exercisers could y monitor when they begin to feel substantially worse than they felt before, and regulate their pace accordingly’’ (p. 157). This finding was the basis for the recent recommendation by the ACSM[33] that ratings of affective valence could be used as an adjunct method of self-monitoring exercise intensity. If people self-regulate their exercise intensity by using the maximization of pleasure and/or the minimization of displeasure as guides, this implies that most individuals would spontaneously choose intensities near the VT or LT, since further increases in intensity would reduce pleasure (see section 3.1). This phenomenon has also been observed with endurance athletes.[122,123] Indeed, Lind et al.[124] showed that a group of sedentary middle-aged women selected intensities not significantly different from their VT (92% and 97% . of VO2 at VT) at the fifteenth and twentieth minute of a 20-minute bout of treadmill exercise; consistent with predictions, pleasure ratings remained stable. In a follow-up study, Lind et al.[67] examined the fragility of this phenomenon, simulating what ª 2011 Adis Data Information BV. All rights reserved.
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would happen if a treadmill speed just 10% higher than the self-selected was imposed . (e.g. by a personal trainer). They found that VO2 reached 115% of the level at VT and pleasure declined significantly. However, besides the added intensity, the loss of perceived autonomy[125] inherent in an externally imposed intensity prescription might have also lowered pleasure. Indeed, Vazou-Ekkekakis and Ekkekakis[126] found that, when participants exercised at an intensity that was identical to one they had previously selfselected but were told that the intensity was controlled by the experimenters, they reported not only less autonomy but also attenuated levels of enjoyment and energy. A study by Rose and Parfitt[127] examined the intensity that sedentary women (mean age 44.8 years) selected when instructed to choose a treadmill speed and gradient that would result in them feeling ‘good’ (+3 on FS) or ‘fairly good’ (+1 on FS) during four 30-minute workouts in each condition. The women selected intensities that allowed them to maintain a physiological steady state. For the ‘feel good’ condition, the . average intensity was just 6% higher than the VO2 at VT (95% CI included the VT during all four workouts). In fact, the average intensity was just 2–4% above the VT during the first workout (it rose to 6–10% during the three subsequent workouts, in parallel with increases in self-efficacy). To reduce their pleasure to ‘feel fairly good’, the women slightly increased their intensity (8% higher than . VO2 at VT). Across the four trials within each condition, the selected intensities were remarkably . consistent (intraclass correlations for %VO2 at VT of 0.98–0.99). Rose and Parfitt[127] cautioned that ‘‘even a very subtle increase in intensity can be enough to make the individual feel less positive’’ (p. 1857). These studies have far-reaching implications. Exercising while having the freedom to regulate one’s intensity apparently ‘rewrites the rules’ to some extent, enabling some participants to experience affective responses that can remain positive over a larger portion of the exercise-intensity range than one would have predicted based on studies following the imposed-intensity paradigm. In most cases, the average self-selected levels of Sports Med 2011; 41 (8)
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exercise intensity fall within the range recommended by the ACSM[33] for the development and maintenance of cardiorespiratory fitness.[109] However, there is considerable inter-individual variability. In the study by Lind et al.,[124] although the peak of the self-selected intensity dis. tribution was centred near 100% of VO2 at VT, individual values ranged from 62% to 160% at the end of the 20-minute bout. Thus, although these findings support a paradigmatic shift from a prescription-based to a preference-based model of exercise promotion,[109,120] they also underscore the need to provide customized exercise options to participants. 3.4 Emergence of Theory and Theory-Testing Studies
Ekkekakis and Petruzzello[22] foresaw ‘‘an evolving trend towards more theory-testing research’’ (p. 349). In the last decade, there were indeed signs of change on this issue. Several researchers identified theories as the basis of their hypotheses and offered theory-grounded rationales for methodological decisions. The theories that were examined include reversal theory,[62] opponentprocess theory,[73,89] multidimensional arousal theory[81] and the dual-mode theory.[91,93-97,106,107] Reversal theory, the opponent-process theory and the multidimensional arousal theory were reviewed by Ekkekakis and Petruzzello.[22] The dual-mode theory is outlined in this section. In the framework of the dual-mode theory,[45,128-130] affective responses to exercise are examined from an evolutionary perspective and are, thus, considered adaptive responses that were shaped through natural selection to promote adaptation in the specific context of exercise. The theory postulates that affective responses to exercise are determined by the continuous interplay between two factors, namely cognitive parameters (e.g. physical self-efficacy, self-presentational concerns) and interoceptive cues (e.g. signals from chemoreceptors, baroreceptors, thermoreceptors and visceroceptors). The relative importance of these two factors is theorized to change systematically as a function of exercise intensity. Specifically, cognitive factors are expected to be the ª 2011 Adis Data Information BV. All rights reserved.
dominant determinants of affect at intensities below and (mainly) near the VT/LT, as the intensity begins to pose a challenge. On the other hand, interoceptive cues will gain salience at intensities that exceed the VT/LT and a physiological steady state becomes difficult or impossible to maintain. Thus, the theory predicts that (i) at intensities below the VT/LT, affect will be mainly positive, (ii) at intensities proximal to the VT/LT, affective responses will differ considerably between individuals, with some reporting increases and others decreases in pleasure; and (iii) at intensities above the VT/LT, most individuals will report reduced pleasure. Finally, the theory predicts that exercise that induces a decline in pleasure during the bout will be followed by a positive affective rebound after the bout. Until now, there is reasonable support for those tenets of the dual-mode theory that have been investigated. Specifically, as noted in section 3.1, several studies have shown that the intensity that exceeds the VT or LT acts a ‘turning point’ toward reduced pleasure during exercise. Furthermore, as summarized in section 3.2 and figures 2 and 3, it seems that there is a predominantly pleasant response below the VT/LT, marked variability proximal to the VT/LT and a homogeneous reduction in pleasure above the VT/LT. The aspect of the theory that has not been tested rigorously yet is the mechanistic basis, involving intensity-dependent shifts in the relative contribution of cognitive and interoceptive influences. Preliminary data consist of correlations of cognitive (e.g. self-efficacy) and . peripheral physiological variables (e.g. HR, VO2, RER, blood lactate) with FS scores across different exercise intensities,[103,128] correlations between associative-dissociative thoughts and FS scores,[107] and post-exercise interviews based on such questions as ‘‘Can you describe how you felt while you were exercising on the treadmill?’’ and ‘‘Can you explain why you felt that way?’’[95] The evidence seems consistent with theoretical predictions. For example, Ekkekakis[128] reported that, as participants progressed through the stages of a treadmill test, self-efficacy contributed nearly all (80–100%) of the accounted variance in FS scores (R2 of 12–23%) while the intensity was below the VT. Sports Med 2011; 41 (8)
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. On the other hand, from the VT to VO2max, the RER contributed most (65–80%) of the accounted variance (R2 of 34–55%). Welch et al.[107] found that, in their sample of physically inactive women undergoing an exercise test, ‘‘attentional focus was largely dissociative at the beginning of exercise (min 1) and became progressively more associative as intensity increased’’ (p. 412), possibly indicating the strengthening of afferent cues. Consistent with this finding, Rose and Parfitt[95] noted that, during exercise performed at or above the LT, most participants reported not being able to focus on anything other than the exercise itself and the discomfort it caused. Although these findings appear to support the tenets of the dual-mode theory, the limitations of the descriptive methods preclude strong inferences. Since participants can be taught techniques to control their cognitions but have limited capacity to attenuate their physiological responses unless the intensity is lowered or exercise is stopped, the relative influence of cognitive and interoceptive factors on affective responses has profound practical implications. According to theoretical predictions and preliminary evidence, the ability of most participants to cognitively control the negative affect that is elicited at intensities exceeding the VT/LT may be diminished. It should be kept in mind that the.VT is estimated to occur between 50% and 58% VO2max in healthy but sedentary adults.[131] 4. Future Directions As demonstrated in this review, in the last decade, this line of research has not only seen an increase in the rate of accumulation of new data but also improved methodologies and more systematic hypothesis testing, resulting in meaningful new information. In the following sections, we identify directions for future growth based on what we see as key voids in current knowledge. 4.1 Further Investigation of Individual Differences
Several recent studies have established that individuals differ in their affective responses to ª 2011 Adis Data Information BV. All rights reserved.
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the same exercise intensity. Dissecting the sources of this variability will be perhaps the greatest challenge for researchers in the years ahead. The pursuit of this goal could help elucidate what de Geus and de Moor[113] characterized as two of the ‘‘most vexing questions in exercise interventions,’’ namely ‘‘why exercisers exercise, and why non-exercisers do not’’ (p. 57). We envision that research will follow two major paths. One will deal with situational appraisals, such as self-efficacy for exercise tasks,[132,133] selfconscious apprehension about one’s physical appearance and capabilities,[66,103,134,135] or perceptions of autonomy.[94,126,136] The other will focus on dispositional factors, such as individual differences in somatosensory modulation,[46] behavioural approach versus inhibition[96,118] or approach versus withdrawal motivation.[74,137,138] Furthermore, researchers have called for studies on genetic polymorphisms, a topic that remains unexplored.[113,139] 4.2 Study of the Mechanistic Bases of Affective Responses at Different Intensities
Although more studies tested theory-based hypotheses, no experimental studies focused on the mechanisms underlying affective responses to exercise. The findings summarized in this review make it clear that the exercise-affect relationship comprises multiple phenomena.[128] Consequently, mechanisms must account for this complexity.[48,130] An expansion of the methodological toolbox, from qualitative approaches to neuroscientific methods (including both basic neuroanatomy and neurophysiology with animal models and human neuroimaging studies) could prove very fruitful in the coming years. As noted in section 3.4, the dual-mode theory[128] offers a framework from which testable hypotheses about the mechanisms underlying the pattern of affective responses observed in recent studies can be derived. However, the postulated mechanisms, particularly the neural mechanisms,[130] have not been examined. For example, one outstanding question refers to the mechanisms responsible for the robust improvements in affect observed with low-intensity and self-paced Sports Med 2011; 41 (8)
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exercise, such as short walks.[36-41] According to the dual-mode theory, at intensities below the VT/LT, there is ‘low to moderate’ influence of cognitive factors.[45,128] So far, studies have shown very weak or null correlations between affective responses and cognitive factors (e.g. self-efficacy) at low intensities.[128] The correlations with peripheral physiological parameters are also near zero. This begs the question of what accounts for the positive responses within this intensity domain. Mixed methods, combining quantitative and qualitative approaches,[95] might be an appropriate avenue to tackle this question. At the high end of the intensity range, the dual-mode theory predicts a unified trend toward reduced pleasure, which is attributed to an intensification of afferent homeostatic signals.[128-130] This postulate is based on strong negative correlations between ratings of pleasure and various peripheral physiological variables above the VT/ LT.[128] An alternative possibility emerged recently[140] from findings of reduced prefrontal cortical oxygenation (assessed by near-infrared spectroscopy) at high exercise intensities.[141-143] According to the neural basis of the dual-mode theory,[130] at intensities above the VT/LT, affective responses depend increasingly on subcortical, rather than cortically mediated, paths to the amygdala. The postulated function of this switch from a mode of affect induction that relies on cortical input (near VT/LT) to a mode that bypasses the cortex (at higher intensities) is to ensure that a strong negative affective response would be generated, unmitigated by cognitive coping efforts. The oxygenation data suggest that this ‘switch’ might occur not only as a result of the intensification of homeostatic afferents but also as a result of an additional safety mechanism; namely, the reduced activity of the prefrontal cortex. According to Davidson,[144,145] the prefrontal cortex exerts an inhibitory control over the amygdala during exposure to aversive stimuli, thus regulating the negative affective responses that accompany aversive stimuli. Davidson et al.[146] proposed that ‘‘in the absence of this normal inhibitory input, the amygdala remains unchecked and continues to remain activated’’ (p. 898). From a practical standpoint, this mechanism, if true, implies that cognitive interventions aimed ª 2011 Adis Data Information BV. All rights reserved.
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at controlling the displeasure of strenuous exercise (e.g. by attentional dissociation, cognitive reframing or bolstering one’s sense of self-efficacy) would be ineffective at intensities exceeding the VT/LT.[147] Thus, for individuals who have difficulty maintaining a physiological steady state during exercise (e.g. chronically sedentary, overweight or obese), a biofeedback-based intervention aimed at improving the self-monitoring and self-regulation of intensity might prove more effective.[148] 4.3 Examination of Population-Specific Variations
Some of the studies on the exercise-affect relationship that were conducted in the last decade focused on samples selected to be sedentary or overweight/obese. These samples represent better approximations of the ‘average’ adult population than college students and are, therefore, of great public-health interest. Ekkekakis and Lind[149] reported that middle-aged, sedentary, overweight women responded with decreases in pleasure when walking on the treadmill at a speed 10% higher than the one they had self-selected, whereas normal-weight women did not. Welch et al.[107] studied women between the ages of 18 and 35 years who were physically inactive for at least a year. Unlike earlier findings from college students, which showed that decreases in pleasure occurred only when the intensity exceeded the VT,[102,104] Welch et al. observed a continual decrease in pleasure for the duration of a graded test. Similarly, Sheppard and Parfitt[106] found decreases in pleasure before the VT in inactive middle-aged men. Ekkekakis et al.[103] found the same for obese middle-aged women. These data underscore the need to direct more research attention to individuals who are physically inactive and/or overweight or obese. Although these characteristics are now shared by the majority of adults in industrialized countries, the lack of information about the affective responses in these populations is striking. Preliminary data show that most adults who are sedentary and overweight or obese experience reduced pleasure over most of the range of exSports Med 2011; 41 (8)
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ercise intensity, making the high dropout and non-participation among overweight and obese adults seem less surprising. There are several possible explanations for this phenomenon. On the one hand, the causes might be physical, such as respiratory difficulties and dyspnoea, a compromised thermoregulatory capacity or intensified muscular and skeletal pain. On the other hand, the culprit might be a diminished sense of efficacy, self-presentational concerns or the fear of intense and unfamiliar physical symptoms. These possibilities warrant systematic investigation in the years ahead. 4.4 Consistency in the System Used to Classify Exercise Intensities
As noted in section 3.1, although many researchers investigated the role of the VT, LT or OBLA in affective responses to exercise, different laboratories focused on different markers or used different procedures to determine these markers. However, as authors in exercise physiology have cautioned,[112,150] such inconsistencies are bound to create confusion. Given the demonstrated importance of these physiological markers for affective responses, it seems reasonable to predict that they will continue to attract research attention in the following years. Researchers are urged to provide physiologically defensible rationales for choosing to focus on the VT, LT or OBLA. Furthermore, the procedures used for the determination of these markers must be reported in sufficient detail to allow replication by others. Consistent with recently published guidelines, we call for a strong commitment to quality assurance procedures, such as use of multiple graphing options and independent judges.[131,151] We also caution that, at least at the present stage of technological development, exclusive reliance on computer algorithms for the determination of the VT or LT may lead to errors.[152] It is also crucial to ensure that factors known to influence the VT and LT (including the exercise testing protocol, diet or state of sympathetic stimulation) are carefully controlled. Addressing the challenge of employing physiologically defensible methods for defining ª 2011 Adis Data Information BV. All rights reserved.
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exercise intensity is a prerequisite for effectively communicating findings from this line of research with practitioners and other researchers within the exercise sciences. 5. Conclusion: Towards a Tripartite Rationale for Exercise Intensity Prescriptions The model underpinning the exercise prescription guidelines issued by ACSM[33] is based on two considerations, namely the maximization of effectiveness (i.e. improvements in fitness and/or health) and the minimization of risk (i.e. potential for injury). As more evidence linking affect to adherence accumulates, it is becoming clear that this bipartite rationale should be reconsidered. Simply put, a prescription may well be effective and safe but, if very few want to follow it, then its public-health relevance becomes questionable. The neglect of pleasure in exercise prescription guidelines until now was, arguably, a consequence of the lack of reliable evidence of a doseresponse relationship between exercise intensity and affective responses.[22] However, the research reviewed in this article suggests that the ‘compromise’ between the ‘ideal physiological prescription’ and a ‘manageable behavioural prescription’ that Dishman[31,32] envisioned decades ago might be closer to becoming a reality. There are certainly several remaining stumbling blocks. First, as in other scientific fields, a dualistic rift also exists within exercise science. Citations by health-oriented exercise physiologists to research in health-oriented exercise psychology, or vice versa, are rare, as if the two subdisciplines did not share the same goal. Accepting affect as an essential pillar of exercise prescription, alongside effectiveness and safety, requires overcoming some long-held beliefs and ‘traditional’ divisions. Second, since their first edition almost 35 years ago, exercise prescription guidelines have been based on a ‘recommended range’ model. Specifically, recent guidelines[33] specify that the range of . 40% . effective and safe intensity extends from VO2 or HR reserve (64% HRmax) to 85% VO2 or HR reserve (94% HRmax). For most adults, these Sports Med 2011; 41 (8)
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intensities encompass a very broad range of activities, from a moderately paced walk to a hard run. This range is reportedly ‘intentionally broad’ to accommodate individuals of very different levels of aerobic fitness. However, in the effort to be as broad as possible, this range has become almost all-encompassing and, thus, potentially confusing. Similarly, the descriptors ‘moderate’ (i.e. 3–6 metabolic equivalents [METs] or 10.5– 21.0 mL/kg/min) and ‘vigorous’ (i.e. >6 METs or 21.0 mL/kg/min) that are used in physical activity recommendation for health[153] are also, essentially, all-encompassing. The data reviewed in this article suggest that these broad ranges include intensities likely to be pleasant and intensities that will, in most cases, be unpleasant. An alternative to the range-based model is the threshold-based model that is commonly used in rehabilitation.[131,154-157] The main argument for the threshold-based approach to exercise prescription is that there is a specific level of intensity above which exercise becomes a systemic stressor, as evidenced by a wide range of physiological indices.[158] That level of intensity seems to correspond to the VT/LT. As the data reviewed in this article show, these thresholds demarcate a domain of intensity that, besides being stressful for several physiological systems, is also felt as unpleasant. In a sense, supra-threshold intensities induce an integrated psychobiological stress response. Conversely, intensities up to these thresholds can remain safe and effective for improving health and fitness but are also pleasant (or at least tolerable) for most healthy individuals. An obstacle in the transition from a range-based to a threshold-based model of exercise prescription is the long precedent; a familiar modus operandi is always hard to change. Moreover, the concepts of the VT and LT have a controversial history in exercise science.[112,150,151] Some researchers question their significance as physiological indices or even their existence. Many practitioners suggest that both markers require expensive instruments (a metabolic or lactate analysis system), making them impractical for routine exercise testing and prescription.[159] Even if the data can be gathered, the reliable determination of these markers is challenging.[131,151,152] ª 2011 Adis Data Information BV. All rights reserved.
To overcome these difficulties, researchers have proposed some practical alternatives. These include teaching exercisers to self-regulate their intensity using the non-linear decline in pleasure that accompanies the transition to supra-threshold intensities,[100] a combination of the non-linear decline in pleasure with a RPE of 12–14 on the 6–20 scale[102] or the talk test.[160,161] The accuracy of these methods is still being evaluated. We foresee that this will continue, especially given the recent call by ACSM[33] for ‘‘further research’’ before these methods can be ‘‘recommended as primary tools for the estimation of exercise intensity’’ (p. 157). Perhaps more importantly, given the interindividual variability in affective responses near the VT/LT, the precise determination of VT/LT is not an absolute prerequisite for exercise prescription. A more appropriate goal for practitioners is to identify a level of intensity near the VT/LT, at which participants can maintain a constant or improving (but not diminishing) level of pleasure. In some cases, this level might be below the VT/LT and in other cases slightly above. Because increases or decreases of the intensity compared with the self-selected level by the exercise practitioner might incur a psychological cost (by lowering perceived autonomy), such interventions should be rare as long as the deviations are small. However, in some cases, the selfselected intensity might be clearly too low to be effective or too high to be safe.[124] Even in such cases, the exercise practitioner should avoid directly imposing an intensity. Instead, we recommend an educational approach aimed at improving the participants’ self-monitoring and self-regulation skills based on the principles of biofeedback[148] and using the participant’s sense of pleasure or displeasure as a guide. Acknowledgements No sources of funding were used in the preparation of this review. The authors have no conflicts of interest relevant to the content of this review.
References 1. Morris JN. Exercise in the prevention of coronary heart disease: today’s best buy in public health. Med Sci Sports Exerc 1994; 26: 807-14
Sports Med 2011; 41 (8)
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2. Miles L. Physical activity and health. Nutr Bull 2007; 32: 314-63 3. Pedersen BK, Saltin B. Evidence for prescribing exercise as therapy in chronic disease. Scand J Med Sci Sports 2006; 16 Suppl. 1: 3-63 4. Warburton DER, Katzmarzyk PT, Rhodes RE, et al. Evidence-informed physical activity guidelines for Canadian adults. Appl Physiol Nutr Metab 2007; 32: S16-68 5. Dishman RK. The problem of exercise adherence: fighting sloth in nations with market economies. Quest 2001; 53: 279-94 6. Bauman A, Armstrong T, Davies J, et al. Trends in physical activity participation and the impact of integrated campaigns among Australian adults, 1997-99. Aust N Z J Public Health 2003; 27: 76-9 7. Brownson RC, Boehmer TK, Luke DA. Declining rates of physical activity in the United States: what are the contributors? Annu Rev Public Health 2005; 26: 421-43 8. Craig CL, Russell SJ, Cameron C, et al. Twenty-year trend in physical activity among Canadian adults. Can J Public Health 2004; 95: 59-63 9. Merom D, Phongsavan P, Chey T, et al. Long-term changes in leisure-time walking, moderate and vigorous exercise: were they influenced by the national physical activity guidelines? J Sci Med Sport 2006; 9: 199-208 10. Stamatakis E, Ekelund U, Wareham NJ. Temporal trends in physical activity in England: the Health Survey for England, 1991 to 2004. Prev Med 2007; 45: 416-23 11. Blair SN. Physical inactivity: the biggest public health problem of the 21st century. Br J Sports Med 2009; 43: 1-2 12. United Kingdom Department of Health, Physical Activity, Health Improvement and Prevention. At least five a week: evidence on the impact of physical activity and its relationship to health, a report from the Chief Medical Officer, 2004 [online]. Available from URL: http://www. dh.gov.uk/en/Publicationsandstatistics/Publications/Pub licationsPolicyAndGuidance/DH_4080994 [Accessed 2011 Jun 16] 13. Dishman RK, Buckworth J. Increasing physical activity: a quantitative synthesis. Med Sci Sports Exerc 1996; 28: 706-19 14. Marcus BH, Williams DM, Dubbert PM, et al. Physical activity intervention studies: what we know and what we need to know. Circulation 2006; 114: 2739-52 15. Newsom JT, McFarland BH, Kaplan MS, et al. The health consciousness myth: implications of the near independence of major health behaviors in the North American population. Soc Sci Med 2005; 60: 433-7 16. Dishman RK, Sallis JF, Orenstein DR. The determinants of physical activity and exercise. Public Health Rep 1985; 100: 158-71 17. Dishman RK. Determinants of participation in physical activity. In: Bouchard C, Shephard RJ, Stephens T, et al., editors. Exercise, fitness, and health: a consensus of current knowledge. Champaign (IL): Human Kinetics, 1990: 75-101 18. Williams DM, Dunsiger S, Ciccolo JT, et al. Acute affective response to a moderate-intensity exercise stimulus predicts physical activity participation 6 and 12 months later. Psychol Sport Exerc 2008; 9: 231-45
ª 2011 Adis Data Information BV. All rights reserved.
667
19. Hardy CJ, Rejeski WJ. Not what, but how one feels: the measurement of affect during exercise. J Sport Exerc Psychol 1989; 11: 304-17 20. Schneider M, Dunn A, Cooper D. Affect, exercise, and physical activity among healthy adolescents. J Sport Exerc Psychol 2009; 31: 706-23 21. Kwan BM, Bryan A. In-task and post-task affective response to exercise: translating exercise intentions into behaviour. Br J Health Psychol 2010; 15: 115-31 22. Ekkekakis P, Petruzzello SJ. Acute aerobic exercise and affect: current status, problems, and prospects regarding dose-response. Sports Med 1999; 28: 337-74 23. American College of Sports Medicine. ACSM’s guidelines for exercise testing and prescription (7th ed.). Philadelphia (PA): Lippincott Williams & Wilkins, 2006 24. Rhodes RE, Warburton DER, Murray H. Characteristics of physical activity guidelines and their effect on adherence: a review of randomized trials. Sports Med 2009; 39: 355-75 25. Cox KL, Burke V, Gorely TJ, et al. Controlled comparison of retention and adherence in home- vs center-initiated exercise interventions in women ages 40-65 years: the S.W.E.A.T. study (Sedentary Women Exercise Adherence Trial). Prev Med 2003; 36: 17-29 26. Lee JY, Jensen BE, Oberman A, et al. Adherence in the Training Levels Comparison Trial. Med Sci Sports Exerc 1996; 28: 47-52 27. Perri MG, Anton SD, Durning PE, et al. Adherence to exercise prescriptions: effects of prescribing moderate versus higher levels of intensity and frequency. Health Psychol 2002; 21: 452-8 28. Sallis JF, Haskell WL, Fortmann SP, et al. Predictors of adoption and maintenance of physical activity in a community sample. Prev Med 1986; 15: 331-41 29. Pollock ML. How much exercise is enough? Phys Sportsmed 1978; 6: 50-64 30. United States Department of Health and Human Services. Healthy People 2010. 2nd ed., vol. 2. Washington, DC: U.S. Government Printing Office, 2000 31. Dishman RK. Compliance/adherence in health-related exercise. Health Psychol 1982; 1: 237-67 32. Dishman RK. Health psychology and exercise adherence. Quest 1982; 33: 166-80 33. American College of Sports Medicine. ACSM’s guidelines for exercise testing and prescription. 8th ed. Philadelphia (PA): Lippincott Williams & Wilkins, 2010 34. Kirkcaldy BC, Shephard RJ. Therapeutic implications of exercise. Int J Sport Psychol 1990; 21: 165-84 35. Ojanen M. Can the true effects of exercise on psychological variables be separated from placebo effects? Int J Sport Psychol 1994; 25: 63-80 36. Saklofske DH, Blomme GC, Kelly IW. The effects of exercise and relaxation on energetic and tense arousal. Pers Individ Dif 1992; 13: 623-5 37. Thayer RE. Energy, tiredness, and tension effects of a sugar snack versus moderate exercise. J Pers Soc Psychol 1987; 52: 119-25 38. Ekkekakis P, Hall EE, Van Landuyt LM, et al. Walking in (affective) circles: can short walks enhance affect? J Behav Med 2000; 23: 245-75
Sports Med 2011; 41 (8)
668
39. Ekkekakis P, Backhouse SH, Gray C, et al. Walking is popular among adults but is it pleasant? A framework for clarifying the link between walking and affect as illustrated in two studies. Psychol Sport Exerc 2008; 9: 246-64 40. Focht BC. Brief walks in outdoor and laboratory environments: effects on affective responses, enjoyment, and intentions to walk for exercise. Res Q Exerc Sport 2009; 80: 611-20 41. Reed J, Ones DS. The effect of acute aerobic exercise on positive activated affect: a meta-analysis. Psychol Sport Exerc 2006; 7: 477-514 42. Pronk NP, Crouse SF, Rohack JJ. Maximal exercise and acute mood response in women. Physiol Behav 1995; 57: 1-4 43. Van Landuyt LM, Ekkekakis P, Hall EE, et al. Throwing the mountains into the lakes: on the perils of nomothetic conceptions of the exercise-affect relationship. J Sport Exerc Psychol 2000; 22: 208-34 44. Gauvin L, Brawley LR. Alternative psychological models and methodologies for the study of exercise and affect. In: Seraganian P, editor. Exercise psychology: the influence of physical exercise on psychological processes. New York: John Wiley & Sons, 1993: 146-71 45. Ekkekakis P, Hall EE, Petruzzello SJ. Variation and homogeneity in affective responses to physical activity of varying intensities: an alternative perspective on doseresponse based on evolutionary considerations. J Sports Sci 2005; 23: 477-500 46. Ekkekakis P, Hall EE, Petruzzello SJ. Some like it vigorous: individual differences in the preference for and tolerance of exercise intensity. J Sport Exerc Psychol 2005; 27: 350-74 47. Ekkekakis P, Petruzzello SJ. Analysis of the affect measurement conundrum in exercise psychology: I. Fundamental issues. Psychol Sport Exerc 2000; 1: 71-88 48. Backhouse SH, Ekkekakis P, Biddle SJH, et al. Exercise makes people feel better but people are inactive: paradox or artifact? J Sport Exerc Psychol 2007; 29: 498-517 49. Bixby WR, Spalding TW, Hatfield BD. Temporal dynamics and dimensional specificity of the affective response to exercise of varying intensity: differing pathways to a common outcome. J Sport Exerc Psychol 2001; 23: 171-90 50. Katch V, Weltman A, Sady S, et al. Validity of the relative percent concept for equating training intensity. Eur J Appl Physiol 1978; 39: 219-27 51. Coplan NL, Gleim GW, Nicholas JA. Using exercise respiratory measurements to compare methods of exercise prescription. Am J Cardiol 1986; 58: 832-6 52. Dwyer J. Metabolic character of exercise at traditional training intensities in cardiac patients and healthy persons. J Cardiopulm Rehabil 1994; 14: 189-96 53. Dwyer J, Bybee R. Heart rate indices of the anaerobic threshold. Med Sci Sports Exerc 1983; 15: 72-6 54. Goldberg L, Elliot DL, Kuehl KS. Assessment of exercise intensity formulas by use of ventilatory threshold. Chest 1988; 94: 95-8 55. McConnell TR, Clark BA, Conlin NC, et al. Gas exchange anaerobic threshold: implications for prescribing exercise in cardiac rehabilitation. J Cardiopulm Rehabil 1993; 13: 31-6
ª 2011 Adis Data Information BV. All rights reserved.
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56. Meyer T, Gabriel HHW, Kindermann W.. Is determination of exercise intensities as percentages of VO2max of HRmax adequate? Med Sci Sports Exerc 1999; 31: 1342-5 57. Normandin EA, Camaione DN, Clark BA, et al. A comparison of conventional versus anaerobic threshold exercise prescription methods in subjects with left ventricular dysfunction. J Cardiopulm Rehabil 1993; 13: 110-6 58. Whipp BJ. Domains of aerobic function and their limiting parameters. In: Steinacker JM, Ward SA, editors. The physiology and pathophysiology of exercise tolerance. New York: Plenum, 1996: 83-9 59. Gaesser GA, Poole DC. The slow component of oxygen uptake kinetics in humans. Exerc Sport Sci Rev 1996; 24: 35-70 60. Ekkekakis P, Petruzzello SJ. Analysis of the affect measurement conundrum in exercise psychology: IV. A conceptual case for the affect circumplex. Psychol Sport Exerc 2002; 3: 35-63 61. Annesi JJ. Effects of differing durations and intensities of cardiovascular exercise on aversion and feeling states in new women exercisers. Percept Mot Skills 2002; 94: 735-8 62. Kerr JH, Kuk G. The effects of low and high intensity exercise on emotions, stress and effort. Psychol Sport Exerc 2001; 2: 173-86 63. Wininger SR. Improvement of affect following exercise: methodological artifact or real finding? Anxiety Stress Coping 2007; 20: 93-102 64. Dyrlund AK, Wininger SR. The effects of music preference and exercise intensity on psychological variables. J Music Ther 2008; 45: 114-34 65. Focht BC, Hausenblas HA. State anxiety responses to acute exercise in women with high social physique anxiety. J Sport Exerc Psychol 2003; 25: 123-44 66. Focht BC, Hausenblas HA. Exercising in public and private environments: effects on feeling states in women with social physique anxiety. J Appl Biobehav Res 2006; 11: 147-65 67. Lind E, Ekkekakis P, Vazou S. The affective impact of exercise intensity that slightly exceeds the preferred level: ‘pain’ for no added ‘gain.’ J Health Psychol 2008; 13: 464-8 68. Parfitt G, Rose EA, Markland D. The effect of prescribed and preferred intensity exercise on psychological affect and the influence of baseline measures of affect. J Health Psychol 2000; 5: 231-40 69. Cox RH, Thomas TR, Hinton PS, et al. Effects of acute . 60 and 80% VO2max bouts of aerobic exercise on state anxiety of women of different age groups across time. Res Q Exerc Sport 2004; 75: 165-75 70. Cox RH, Thomas TR, Hinton PS, et al. Effects of acute bouts of aerobic exercise of varied intensity on subjective mood experiences in women of different age groups across time. J Sport Behav 2006; 29: 40-59 71. Katula JA, Blissmer BJ, McAuley E. Exercise intensity and self-efficacy effects on anxiety reduction in healthy, older adults. J Behav Med 1999; 22: 233-47 72. McAuley E, Blissmer B, Katula J, et al. Exercise environment, self-efficacy, and affective responses to acute exercise in older adults. Psychol Health 2000; 15: 341-55 73. Lochbaum MR, Karoly P, Landers DM. Affect responses to acute bouts of aerobic exercise: a test of opponentprocess theory. J Sport Behav 2004; 27: 330-48
Sports Med 2011; 41 (8)
Exercise Intensity and Pleasure
74. Lochbaum MR. Viability of resting electroencephalograph asymmetry as a predictor of exercise-induced affect: a lack of consistent support. J Sport Behav 2006; 29: 315-36 75. Blanchard CM, Rodgers WM, Spence JC, et al. Feeling state responses to acute exercise of high and low intensity. J Sci Med Sport 2001; 4: 30-8 76. Blanchard CM, Rodgers WM, Courneya KS, et al. Moderators of the exercise/feeling-state relationship: the influence of self-efficacy, baseline, and in-task feeling states at moderate- and high-intensity exercise. J Appl Soc Psychol 2002; 32: 1379-95 77. Daley AJ, Huffen C. The effects of low and moderate intensity exercise on subjective experiences in a naturalistic health and fitness club setting. J Health Psychol 2003; 8: 685-91 78. Daley AJ, Welch A. Subjective exercise experiences during and after high and low intensity exercise in active and inactive adult females. J Sports Med Phys Fitness 2003; 43: 220-2 79. Dunn EC, McAuley E. Affective responses to exercise bouts of varying intensities. J Soc Behav Pers 2000; 15: 201-14 80. Kilpatrick M, Hebert E, Bartholomew J, et al. Effect of exertional trend during cycle ergometry on postexercise affect. Res Q Exerc Sport 2003; 74: 353-9 81. Oweis P, Spinks W. Biopsychological, affective and cognitive responses to acute physical activity. J Sports Med Phys Fitness 2001; 41: 528-38 82. Smith JC, O’Connor PJ, Crabbe JB, et al. Emotional responsiveness after low- and moderate-intensity exercise and seated rest. Med Sci Sports Exerc 2002; 34: 1158-67 83. Tieman JG, Peacock LJ, Cureton KJ, et al. The influence of exercise intensity and physical activity history on state anxiety after exercise. Int J Sport Psychol 2002; 33: 155-66 84. Thayer RE. The biopsychology of mood and arousal. New York: Oxford University Press, 1989 85. Gauvin L, Rejeski WJ. The Exercise-induced Feeling Inventory: development and initial validation. J Sport Exerc Psychol 1993; 15: 403-23 86. Spielberger CD, Gorsuch RL, Lushene RE. Manual for the State-Trait Anxiety Inventory. Palo Alto (CA): Consulting Psychologists, 1970 87. Bradley MM, Lang PJ. Measuring emotion: the SelfAssessment Manikin and the Semantic Differential. J Behav Ther Exp Psychiatry 1994; 25: 49-59 88. McAuley E, Courneya KS. The Subjective Exercise Experiences Scale (SEES): development and preliminary validation. J Sport Exerc Psychol 1994; 16: 163-77 89. Bixby WR, Lochbaum MR. Affect responses to acute bouts of aerobic exercise in fit and unfit participants: an examination of opponent-process theory. J Sport Behav 2006; 29: 111-25 90. Blanchard CM, Rodgers WM, Wilson PM, et al. Does equating total volume of work between two different exercise conditions matter when examining exercise-induced feeling states? Res Q Exerc Sport 2004; 75: 209-15 91. Ekkekakis P, Hall EE, Petruzzello SJ. The relationship between exercise intensity and affective responses demystified: to crack the forty-year-old nut, replace the fortyyear-old nutcracker! Ann Behav Med 2008; 35: 136-49
ª 2011 Adis Data Information BV. All rights reserved.
669
92. Kilpatrick M, Jarreau D, Bartholomew J, et al. Comparing exercise bouts of different intensities and durations on post-exercise mood [abstract]. Med Sci Sports Exerc 2004; 36: S286-7 93. Kilpatrick MW, Kraemer RR, Bartholomew JB, et al. Affective responses to exercise are dependent on intensity rather than total work. Med Sci Sports Exerc 2007; 39: 1417-22 94. Parfitt G, Rose EA, Burgess WM. The psychological and physiological responses of sedentary individuals to prescribed and preferred intensity exercise. Br J Health Psychol 2006; 11: 39-53 95. Rose EA, Parfitt G. A quantitative analysis and qualitative explanation of the individual differences in affective responses to prescribed and self-selected exercise intensities. J Sport Exerc Psychol 2007; 29: 281-309 96. Schneider M, Graham D. Personality, physical fitness, and affective response to exercise among adolescents. Med Sci Sports Exerc 2009; 41: 947-55 97. Sheppard KE, Parfitt G. Affective responses to prescribed and self-selected exercise intensities in young adolescent boys and girls. Pediatr Exerc Sci 2008; 20: 129-41 98. Watson D, Clark LA, Tellegen A. Development and validation of brief measures of positive and negative affect: the PANAS scales. J Pers Soc Psychol 1988; 54: 1063-70 99. Folstein MF, Luria R. Reliability, validity, and clinical application of the Visual Analogue Mood Scale. Psychol Med 1973; 3: 479-86 100. Acevedo EO, Kraemer RR, Haltom RW, et al. Perceptual responses proximal to the onset of blood lactate accumulation. J Sports Med Phys Fitness 2003; 43: 267-73 101. Acevedo EO, Kraemer RR, Kamimori GH, et al. Stress hormones, effort sense, and perceptions of stress during incremental exercise: an exploratory investigation. J Strength Cond Res 2007; 21: 283-8 102. Ekkekakis P, Hall EE, Petruzzello SJ. Practical markers of the transition from aerobic to anaerobic metabolism during exercise: rationale and a case for affect-based exercise prescription. Prev Med 2004; 38: 149-59 103. Ekkekakis P, Lind E, Vazou S. Affective responses to increasing levels of exercise intensity in normal-weight, overweight, and obese middle-aged women. Obesity 2010; 18: 79-85 104. Hall EE, Ekkekakis P, Petruzzello SJ. The affective beneficence of vigorous exercise revisited. Br J Health Psychol 2002; 7: 47-66 105. Hall EE, Folger SE, Miller PC, et al. Affective responses to a graded exercise test on a recumbent bicycle: when do I start to feel bad [abstract]? Med Sci Sports Exerc 2004; 36: S166 106. Sheppard KE, Parfitt G. Patterning of physiological and affective responses during a graded exercise test in sedentary men and boys. J Exerc Sci Fitness 2008; 6: 121-9 107. Welch AS, Hulley A, Ferguson C, et al. Affective responses of inactive women to a maximal incremental exercise test: a test of the dual-mode model. Psychol Sport Exerc 2007; 8: 401-23 108. Borg G. Borg’s perceived exertion and pain scales. Champaign (IL): Human Kinetics, 1998 109. Ekkekakis P. Let them roam free? Physiological and psychological evidence for the potential of self-selected
Sports Med 2011; 41 (8)
Ekkekakis et al.
670
110.
111.
112.
113.
114.
115.
116.
117.
118.
119.
120.
121.
122.
123.
124.
125.
126.
exercise intensity in public health. Sports Med 2009; 39: 857-88 Jones AM, Doust JH. Limitations to submaximal exercise performance. In: Eston R, Reilly T, editors. Kinanthropometry and exercise physiology laboratory manual: tests, procedures and data. Vol. 2. London: Routledge, 2001: 280-318 Wyatt FB. Comparison of lactate and ventilatory threshold to maximal oxygen consumption: a meta-analysis. J Strength Cond Res 1999; 13: 67-71 Svedahl K, MacIntosh BR. Anaerobic threshold: the concept and methods of measurement. Can J Appl Physiol 2003; 28: 299-323 de Geus EJC, de Moor MHM. A genetic perspective on the association between exercise and mental health. Ment Health Phys Act 2008; 1: 53-61 Morgan WP, O’Connor PJ. Exercise and mental health. In: Dishman RK, editor. Exercise adherence: its impact on public health. Champaign (IL): Human Kinetics, 1988: 91-121 Ekkekakis P, Thome J, Hall EE, et al. The Preference for and Tolerance of the Intensity of Exercise Questionnaire: a psychometric evaluation among college women. J Sports Sci 2008; 26: 499-510 Ekkekakis P, Lind E, Joens-Matre RR. Can self-reported preference for exercise intensity predict physiologically defined self-selected exercise intensity? Res Q Exerc Sport 2006; 77: 81-90 Ekkekakis P, Lind E, Hall EE, et al. Can self-reported tolerance of exercise intensity play a role in exercise testing? Med Sci Sports Exerc 2007; 39: 1193-9 Legrand FD, Bertucci WM, Thatcher J. Telic dominance influences affective response to a heavy-intensity 10-min treadmill running session. J Sports Sci 2009; 27: 1059-67 Dishman RK, Farquhar RP, Cureton KJ. Responses to preferred intensities of exertion in men differing in activity levels. Med Sci Sports Exerc 1994; 26: 783-90 Williams DM. Exercise, affect, and adherence: an integrated model and a case for self-paced exercise. J Sport Exerc Psychol 2008; 30: 471-96 Cabanac M. Exertion and pleasure from an evolutionary perspective. In: Acevedo EO, Ekkekakis P, editors. Psychobiology of physical activity. Champaign (IL): Human Kinetics, 2006: 79-89 Farrell PA, Wilmore JH, Coyle EF, et al. Plasma lactate accumulation and distance running performance. Med Sci Sports Exerc 1979; 11: 338-44 Tanaka K, Matsuura Y. Marathon performance, anaerobic threshold, and onset of blood lactate accumulation. J Appl Physiol 1984; 57: 640-3 Lind E, Joens-Matre RR, Ekkekakis P. What intensity of physical activity do formerly sedentary middle-aged women select? Evidence of a coherent pattern from physiological, perceptual, and affective markers. Prev Med 2005; 40: 407-19 Deci EL, Ryan RM. The ‘what’ and ‘why’ of goal pursuits: human needs and the self-determination of behavior. Psychol Inq 2000; 11: 227-68 Vazou-Ekkekakis S, Ekkekakis P. Affective consequences of imposing the intensity of physical activity: does the loss
ª 2011 Adis Data Information BV. All rights reserved.
127.
128. 129.
130.
131.
132.
133.
134.
135.
136.
137.
138.
139.
140.
141.
142. 143.
of perceived autonomy matter? Hell J Psychol 2009; 6: 125-44 Rose EA, Parfitt G. Can the Feeling Scale be used to regulate exercise intensity? Med Sci Sports Exerc 2008; 40: 1852-60 Ekkekakis P. Pleasure and displeasure from the body: perspectives from exercise. Cogn Emot 2003; 17: 213-39 Ekkekakis P. The study of affective responses to acute exercise: the dual-mode model. In: Stelter R, Roessler KK, editors. New approaches to sport and exercise psychology. Oxford: Meyer & Meyer, 2005: 119-46 Ekkekakis P, Acevedo EO. Affective responses to acute exercise: toward a psychobiological dose-response model. In: Acevedo EO, Ekkekakis P, editors. Psychobiology of physical activity. Champaign (IL): Human Kinetics, 2006: 91-109 Meyer T, Lucı´ a A, Earnest CP, et al. A conceptual framework for performance diagnosis and training prescription from submaximal gas exchange parameters: theory and application. Int J Sports Med 2005; 26 (Suppl. 1): S38-48 Hu L, Motl RW, McAuley E, et al. Effects of self-efficacy on physical activity enjoyment in college-aged women. Int J Behav Med 2007; 14: 92-6 Jerome GJ, Marquez DX, McAuley E, et al. Self-efficacy effects on feeling states in women. Int J Behav Med 2002; 9: 139-54 Martin Ginis KA, Burke SM, Gauvin L. Exercising with others exacerbates the negative effects of mirrored environments on sedentary women’s feeling states. Psychol Health 2007; 22: 945-62 Raedeke TD, Focht BC, Scales D. Social environmental factors and psychological responses to acute exercise for socially physique anxious females. Psychol Sport Exerc 2007; 8: 463-76 Lutz R, Lochbaum M, Turnbow K. The role of relative autonomy in post-exercise affect responding. J Sport Behav 2003; 26: 137-54 Petruzzello SJ, Hall EE, Ekkekakis P. Regional brain activation as a biological marker of affective responsivity to acute exercise: influence of fitness. Psychophysiology 2001; 38: 99-106 Hall EE, Ekkekakis P, Petruzzello SJ. Regional brain activity and strenuous exercise: predicting affective responses using EEG asymmetry. Biol Psychol 2007; 75: 194-200 Ekkekakis P. The genetic tidal wave finally reached our shores: will it be the catalyst for a critical overhaul of the way we think and do science? Ment Health Phys Act 2008; 1: 47-52 Ekkekakis P. Illuminating the black box: investigating prefrontal cortical hemodynamics during exercise with near-infrared spectroscopy. J Sport Exerc Psychol 2009; 31: 505-53 Bhambhani Y, Malik R, Mookerjee S. Cerebral oxygenation declines at exercise intensities above the respiratory compensation threshold. Respir Physiol Neurobiol 2007; 156: 196-202 Perrey S. Non-invasive NIR spectroscopy of human brain function during exercise. Methods 2008; 45: 289-99 Ruppe T, Perrey S. Prefrontal cortex oxygenation and neuromuscular responses to exhaustive exercise. Eur J Appl Physiol 2008; 102: 153-63
Sports Med 2011; 41 (8)
Exercise Intensity and Pleasure
144. Davidson RJ. The neural circuitry of emotion and affective style: prefrontal cortex and amygdala contributions. Soc Sci Inf 2001; 40: 11-37 145. Davidson RJ. Anxiety and affective style: role of prefrontal cortex and amygdala. Biol Psychiatry 2002; 51: 68-80 146. Davidson RJ, Jackson DC, Kalin NH. Emotion, plasticity, context, and regulation: perspectives from affective neuroscience. Psychol Bull 2000; 126: 890-909 147. Lind E, Welch AS, Ekkekakis P. Do ‘mind over muscle’ strategies work? Examining the effects of attentional association and dissociation on exertional, affective, and physiological responses to exercise. Sports Med 2009; 39: 743-64 148. Ekkekakis P, Petruzzello SJ. Biofeedback in exercise psychology. In: Blumenstein B, Bar-Eli M, Tenenbaum G, editors. Brain and body in sport and exercise: biofeedback application in performance enhancement. Chichester: John Wiley & Sons, 2002: 77-100 149. Ekkekakis P, Lind E. Exercise does not feel the same when you are overweight: the impact of self-selected and imposed intensity on affect and exertion. Int J Obes 2006; 30: 652-60 150. Myers J, Ashley E. Dangerous curves: a perspective on exercise, lactate, and the anaerobic threshold. Chest 1997; 111: 787-95 151. Binder RK, Wonisch M, Corra U, et al. Methodological approach to the first and second lactate threshold in incremental cardiopulmonary exercise testing. Eur J Cardiovasc Prev Rehabil 2008; 15: 726-34 152. Ekkekakis P, Lind E, Hall EE, et al. Do regression-based computer algorithms for determining the ventilatory threshold agree? J Sports Sci 2008; 26: 967-76 153. Haskell WL, Lee IM, Pate RR, et al. Physical activity and public health: updated recommendation for adults from the American College of Sports Medicine and the American Heart Association. Med Sci Sports Exerc 2007; 39: 1423-34
ª 2011 Adis Data Information BV. All rights reserved.
671
154. Gordon NF, Scott CB. Exercise intensity prescription in cardiovascular disease: theoretical basis for anaerobic threshold determination. J Cardiopulm Rehabil 1995; 15: 193-6 155. Meyer T, Go¨rge G, Schwaab B, et al. An alternative approach for exercise prescription and efficacy testing in patients with chronic heart failure: a randomized controlled training study. Am Heart J 2005; 149 (5): 926.e1-e7 156. Nieuwland W, Berkhuysen MA, Van Veldhuisen DJ, et al. Individual assessment of intensity-level for exercise training in patients with coronary artery disease is necessary. Int J Cardiol 2002; 84: 15-20 157. Strzelczyk TA, Quigg RJ, Pfeifer PB, et al. Accuracy of estimating exercise prescription intensity in patients with left ventricular systolic dysfunction. J Cardiopulm Rehabil 2001; 21: 158-63 158. Soya H, Mukai A, Deocaris CC, et al. Threshold-like pattern of neuronal activation in the hypothalamus during treadmill running: establishment of a minimum running stress (MRS) rat model. Neurosci Res 2007; 58: 341-8 159. Welsch MA, Pollock ML, Brechue WF, et al. Using the exercise test to develop the exercise prescription in health and disease. Prim Care 1994; 21: 589-609 160. Foster C, Porcari JP, Anderson J, et al. The Talk Test as a marker of exercise training intensity. J Cardiopulm Rehabil Prev 2008; 28: 24-30 161. Persinger R, Foster C, Gibson M, et al. Consistency of the talk test for exercise prescription. Med Sci Sports Exerc 2004; 36: 1632-6
Correspondence: Dr Panteleimon Ekkekakis, 235 Barbara E. Forker Building, Department of Kinesiology, Iowa State University, Ames, IA 50011, USA. E-mail: [email protected]
Sports Med 2011; 41 (8)
Sports Med 2011; 41 (8): 673-694 0112-1642/11/0008-0673/$49.95/0
REVIEW ARTICLE
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Repeated-Sprint Ability – Part I Factors Contributing to Fatigue Olivier Girard,1 Alberto Mendez-Villanueva2 and David Bishop3 1 ASPETAR – Qatar Orthopaedic and Sports Medicine Hospital, Research and Education Centre, Doha, Qatar 2 Physiology Unit, Sport Science Department, ASPIRE Academy for Sport Excellence, Doha, Qatar 3 Institute of Sport, Exercise and Active Living (ISEAL), School of Sport and Exercise Science, Victoria University, Melbourne, VIC, Australia
Contents Abstract. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1 Defining Repeated-Sprint Ability (RSA) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2 Fatigue During Repeated-Sprint Exercise . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.3 Relevance of RSA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2. Manifestation of Fatigue . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Indices. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Influence of Initial Sprint Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3 Task Dependency . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4 Influence of Other Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3. Limiting Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Muscular Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1.1 Muscle Excitability. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1.2 Limitations in Energy Supply. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1.3 Metabolite Accumulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Neural Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.1 Neural Drive. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.2 Muscle Recruitment Strategies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4. Additional Factors Affecting RSA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 Stiffness Regulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 Environmental Perturbations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Abstract
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Short-duration sprints (<10 seconds), interspersed with brief recoveries (<60 seconds), are common during most team and racket sports. Therefore, the ability to recover and to reproduce performance in subsequent sprints is probably an important fitness requirement of athletes engaged in these disciplines, and has been termed repeated-sprint ability (RSA). This review (Part I) examines how fatigue manifests during repeated-sprint exercise (RSE), and discusses the potential underpinning muscular and neural mechanisms. A subsequent companion review to this article will explain a better understanding of the training interventions that could eventually improve RSA.
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Using laboratory and field-based protocols, performance analyses have consistently shown that fatigue during RSE typically manifests as a decline in maximal/mean sprint speed (i.e. running) or a decrease in peak power or total work (i.e. cycling) over sprint repetitions. A consistent result among these studies is that performance decrements (i.e. fatigue) during successive bouts are inversely correlated to initial sprint performance. To date, there is no doubt that the details of the task (e.g. changes in the nature of the work/recovery bouts) alter the time course/magnitude of fatigue development during RSE (i.e. task dependency) and potentially the contribution of the underlying mechanisms. At the muscle level, limitations in energy supply, which include energy available from phosphocreatine hydrolysis, anaerobic glycolysis and oxidative metabolism, and the intramuscular accumulation of metabolic by-products, such as hydrogen ions, emerge as key factors responsible for fatigue. Although not as extensively studied, the use of surface electromyography techniques has revealed that failure to fully activate the contracting musculature and/or changes in inter-muscle recruitment strategies (i.e. neural factors) are also associated with fatigue outcomes. Pending confirmatory research, other factors such as stiffness regulation, hypoglycaemia, muscle damage and hostile environments (e.g. heat, hypoxia) are also likely to compromise fatigue resistance during repeated-sprint protocols.
1. Introduction 1.1 Defining Repeated-Sprint Ability (RSA)
Team and racket sports are popular with millions of participants worldwide. Athletes engaged in these disciplines are required to repeatedly produce maximal or near maximal efforts (i.e. sprints), interspersed with brief recovery intervals (consisting of complete rest or low- to moderate-intensity activity), over an extended period of time (1–4 hours), and this has been termed repeated-sprint ability (RSA).[1-8] Time-motion analysis in team sports has shown that sprinting generally constitutes 1–10% of the total distance covered (1–3% of effective playing time).[9-12] There is potential for confusion, however, as some authors have used the word ‘sprint’ to describe exercise lasting 30 seconds or more.[13-15] For the purposes of this review, the definition of ‘sprint’ activity will be limited to brief exercise, in general £10 seconds, where maximal workout (i.e. power/speed) can be nearly maintained until the end of the exercise (figure 1). Longer duration, maximal-intensity exercise, where there is a considerable decrease in performance will be referred ª 2011 Adis Data Information BV. All rights reserved.
to as ‘all-out’ exercise, but is not the topic of this review. When sprints are repeated, it is also useful to define two different types of exercise, i.e. intermittent-sprint and repeated-sprint exercise (RSE). Intermittent-sprint exercise can be characterized by short-duration sprints (£10 seconds), interspersed with recovery periods long enough (60–300 seconds) to allow near complete recovery of sprint performance.[16,17] In comparison, RSE is characterized by short-duration sprints (£10 seconds) interspersed with brief recovery periods (usually £60 seconds). The main difference is that during intermittent-sprint exercise there is little or no performance decrement,[18,19] whereas during RSE there is a marked performance decrement (figure 2).[20] Such a distinction is important as the factors contributing to fatigue are likely to be different for these two types of exercise. 1.2 Fatigue During Repeated-Sprint Exercise
For the purpose of this review, fatigue is defined as a RSE-induced reduction in the maximal power output (i.e. during cycling exercise) or speed (i.e. during running exercise), even though the task can Sports Med 2011; 41 (8)
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100 m 200 m 13 12
Velocity (m/s−1)
11 10 9 8 7 6 5 4 10 20 30 40 50 60 70 80 90 100 110 120 130 140 150 160 170 180 190 200 Distance (m) Fig. 1. Sprint profiles of 100 m and 200 m world records for men. In the above example, the 100 m performance would be defined as a sprint exercise, while the 200 m performance would be defined as an ‘all-out’ exercise.
1.3 Relevance of RSA
Although performance in most multiple-sprint sports is dominated by technical and tactical proficiencies,[30] and the importance of RSA as a crucial physical component of team-sport performance[31] has been recently questioned,[12] fatigue developª 2011 Adis Data Information BV. All rights reserved.
ment in team sports (e.g. soccer) has been linked with the ability to reproduce sprints.[32] In this regard, significant reductions in sprinting and highspeed running actions have been observed toward the end of elite soccer matches in men[33] and women.[34] Due to the unpredictable nature of the
Intermittent sprints Repeated sprints 2400 2200
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5
2000 Work (J)
be sustained. Fatigue during RSE typically develops rapidly after the first sprint (figure 2).[21] It is now accepted that fatigue can be caused by a variety of factors, ranging from the generation of an inadequate motor command in the motor cortex (i.e. neural factors) to the accumulation of metabolites within muscle fibres (i.e. muscular factors), and that there is no one global mechanism responsible for all manifestations of fatigue. The complex nature of fatigue is also highlighted by the diversity of approaches, models or indices (see section 2.1) that have been used to account for the decline in muscular performance. In recent years, there has been an exponential growth of interest in factors underlying fatigue during RSE (figure 3). This is probably due to technological advances, the study of new potential limiting factors and the inclusion of diverse RSE protocols. However, there is still no clear explanation for the mechanisms that limit RSA.[5]
1800 1600 1400 1200 1
2
Sprint number Fig. 2. Graph showing the effects of rest duration on maximal 4 sec, cycle sprint performance. Intermittent sprints were performed every 2 min,[19] whereas repeated sprints were executed every 30 sec.[20] * Significantly different from sprint 1 in the repeated-sprint condition.
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Cerebral oxygenation (NIRS) (Smith and Billaut, 2010)
100
Parasympathic reactivation (heart rate variability) (Buchheit et al. 2007)
Number of studies
80
60 Neuromuscular activity (EMG) (Hautier et al. 2000) 40
20
Cardiorespiratory variables (gas analyser) (Balsom et al. 1999) Muscle biopsies (Gaitanos et al. 1993)
Muscle oxygenation (NIRS) (Racinais et al. 2007)
Muscle buffer capacity (Bishop et al. 2004)
Muscle PCr, Pi and pH (31P magnetic resonance spectroscopy) (Yquel et al. 2002) 0 1990−4
1995−9
2000−4
2005−present
Periods Fig. 3. Published research on the possible physiological mechanisms responsible for fatigue during repeated-sprint exercise (Gaitanos et al.,[22] Balsom et al.,[23] Hautier et al.,[24] Yquel et al.,[25] Bishop et al.,[26] Racinais et al.,[27] Buchheit et al.[28] and Smith and Billaut[29]). Timepoints when new analysis methods were introduced into the investigation of repeated-sprint ability are also shown. EMG = electromyogram; NIRS = near-infrared spectroscopy; PCr = phosphocreatine; Pi = inorganic phosphate.
game, it is thought that intense periods of sprinting activity may on occasion determine the final outcome of a game, by influencing the ability to win possession of the ball or to concede goals.[35] For example, a ~0.8% impairment in sprint speed would have a substantial effect on the likelihood of a player losing possession of the ball against an opponent, when both players sprint for the ball.[36] Moreover, repeated-sprint tests performed before and after elite soccer games have demonstrated that RSA deteriorates substantially with fatigue development.[37,38] Thus, considering that the aetiology of fatigue is dependent on the exercise mode (the socalled ‘task dependency’),[39] a better understanding of the factors contributing to fatigue during RSA is arguably the first step in order to design interventions (i.e. training programmes, ergogenic aids) that could delay the onset of fatigue, enhance RSA and eventually improve physical match performance in team-sport athletes. The aim of this review, therefore, is to discuss mechanisms that have been proposed to contribute to fatigue during RSE. To achieve this objective, the databases SportDiscus, PubMed, Web of Science ª 2011 Adis Data Information BV. All rights reserved.
and MEDLINE were searched, without any time restriction, using the following combination of terms: ‘fatigue’, ‘repeated-sprint exercise’, ‘repeated-sprint ability’ and ‘multiple sprint’. The reference lists of the articles obtained were searched manually to obtain further studies not identified electronically. The insights gained from this review should assist the prescription of training strategies to more effectively combat factors responsible for fatigue during repeated sprints (as discussed in a subsequent companion review to this article[40]). 2. Manifestation of Fatigue 2.1 Indices
During RSE, fatigue manifests as a decline in maximal sprint speed (i.e. running), or a decrease in peak power or total work (i.e. cycling), over sprint repetitions (figure 4). To quantify the ability to resist fatigue during RSE, researchers have tended to use one of two terms, the fatigue index (FI) or the percentage decrement score (Sdec). The FI has generally been calculated as the drop-off in performance Sports Med 2011; 41 (8)
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from the best to worst sprint performance during an RSE (equation 1). ðSbest Sworst Þ FI ¼ 100 Sbest (Eq. 1) where S refers to sprint performance and can be calculated for either speed, work or power scores. In comparison, the Sdec attempts to quantify fatigue by comparing actual performance to an imagined ‘ideal performance’ (i.e. where the best effort would be replicated in each sprint) as shown in equation 2.[7,42] ðS1 þ S2 þ S3 þ . . . þ Sfinal Þ Sdec ð%Þ ¼ 1 100 Sbest number of sprints
(Eq: 2Þ A slight modification of the formula is required for sprint running performance (as times will increase as subjects fatigue) as shown in equation 3. Sdec ð%Þ ¼
ðS1 þ S2 þ S3 þ . . . þ Sfinal Þ 1 100 Sbest number of sprints
(Eq: 3Þ A possible advantage of the Sdec is that it takes into consideration all sprints, whereas the FI will be influenced more by a particularly good or bad first or last sprint. By comparing eight different Morning sprint tests Evening sprint tests 1000
*
Peak power output (W)
950 900 850 800 750 700 650 1
2
3 Sprint number
4
5
Fig. 4. Peak power output during a 5 · 6 sec repeated-sprint cycling test performed in the morning and evening. Note that in the evening, peak power was higher during the first sprint, but not different in the latter sprints, which produced a higher calculated sprint decrement (indicated by *) [modified from Racinais et al.[41]].
ª 2011 Adis Data Information BV. All rights reserved.
approaches, Glaister et al.[43] concluded that the Sdec calculation was the most valid and reliable method to quantify fatigue in tests of RSA. While this review only deals with fatigue outcomes, it is important to note that other performance indices, such as total mechanical work/sprint time (i.e. sum of power outputs/times for all sprint repetitions) should be used in conjunction with indices of relative decrement in performance (i.e. fatigue) to asses repeated-sprint performance.[44] In fact, it is absolutely necessary to contextualize the calculated fatigue indices when RSA is evaluated because less/greater fatigue does not always equate to better/worse performance.[45,46] An example of this is illustrated in figure 4. Here, a significant increase in performance during sprint 1 will lead to a greater calculated FI. It would be incorrect to interpret this as a decrease in RSA, when there is also an increase in total/mean sprint performance. 2.2 Influence of Initial Sprint Performance
An important determinant of fatigue during RSE is the initial (i.e. first sprint) mechanical score, which has consistently been reported to be positively correlated with performance decrement over subsequent sprints.[21,47-49] This can probably be attributed to the observation that subjects with a greater initial sprint performance will have greater changes in muscle metabolites, arising secondary to a higher anaerobic contribution, which in turn has been related to larger performance decrements.[22] In support of this, Mendez-Villanueva et al.[21] have reported that individuals with lower anaerobic power reserves, implying less reliance on anaerobic metabolism, showed a higher fatigue resistance during repeated cycling sprints. This suggests that metabolic pathways supporting force production, and not the absolute force generated per se, might explain power decrements during RSE. Therefore, initial sprint mechanical output per se cannot solely account for performance decrements during RSE. Indeed, Mendez-Villanueva et al.[50] have highlighted that previous fatiguing muscle contractions (i.e. a set of repeated sprints) exacerbated the rate of fatigue development during subsequent sprints, despite being matched for initial sprint power. Similarly, Bishop and Edge[51] found a greater fatigability Sports Med 2011; 41 (8)
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(i.e. larger work decrement) across five 6-second cycling sprints repeated every 30 seconds in low versus moderately aerobically trained females matched for single-sprint performance. 2.3 Task Dependency
There is no doubt that the degree of fatigue experienced during RSE is largely influenced by the details of the task being performed (i.e. task dependency).[39] For example, fatigue resistance during RSE is directly dependent on the exercise mode (e.g. cycling vs running);[8] decrement scores during repeated-sprint cycling protocols (10–25%) have typically been reported to be greater than those for running protocols (5–15%). Fatigue development during RSE also appears to depend on resistive load (e.g. mechanically, wind or electromagnetically resisted[52,53]) or the running surface (e.g. indoor tartan track, outdoor football field). Moreover, fatigue resistance during RSE depends on the distribution (e.g. number of repetitions) and duration of the work periods,[54] and the recovery pattern; i.e. the nature,[55-58] duration[16,59-64] and intensity[65] of the recovery between sprints. Although not a universal finding,[66] performing active versus passive recovery is generally associated with a higher degree of fatigue development.[55,58,65,67] Compared with a passive recovery, low- and moderateintensity active recoveries (~20% and 35% maximal . oxygen uptake [VO2max], respectively) have similar effects on RSA and muscle metabolism.[65] One limitation of the above-mentioned studies, however, is that researchers have typically imposed fixedduration recovery periods between repeated sprints, while the pattern of exercise and recovery seen in team sports can best be described as random (i.e. imposed by tactical factors and the player’s ability to self-select the intensity and nature of their efforts). By manipulating different recovery durations (i.e. constant, increasing and decreasing recovery pattern) Billaut and Basset[59] have reported that reductions in peak and mean power output were delayed with the decreasing recovery pattern, but were subsequently more marked and associated with greater neuromuscular perturbations. The fatigue experienced during RSE also appears to be influenced by priory activity. For exª 2011 Adis Data Information BV. All rights reserved.
ample, when static stretching is conducted after dynamic activities during the warm-up, and immediately prior to performance, Sim et al.[68] have shown that the ability to resist fatigue during RSE is compromised. However, these results have been challenged since performing static stretching within the warm-up for 3 consecutive days did not negatively affect subsequent RSA.[69] It has also been reported that preceding high-intensity exercise may compromise RSA.[32,50] Hence, previous fatiguing RSE, followed by a rest period, exacerbates the rate of loss of muscle power output during a subsequent repeated-sprint bout.[50] Despite the potential influence of prior activity on RSA, very few studies have employed RSA tests that mimic the actual game situation. More research is required using repeated-sprint tests that assess RSA following and prior to activities specific to a given sporting discipline, as Jougla et al.[67] did for rugby union players, while also simulating work-torest ratios specific to such activities in competition. In this context, Krustrup et al.[32] have reported that repeated 30 m sprint performance is impaired following a competitive football (soccer) game in Danish Premier League women players. In contrast, no differences were found in the performance decrement between repeated-sprint tests performed by young basketball players at different stages of a game.[70] A limited number of studies have investigated RSA during team-sport competition.[9,10,12] When elite field hockey players played three games within 4 days, there were significant changes in time-motion analysis, as the frequency of exercise bouts that met the criteria for ‘repeated sprints’ decreased across the three games.[10] With respect to task specificity, it is important to note that most of our knowledge relative to the development of fatigue during RSE has been gained from cycle-based, repeated sprinting performed in the laboratory environment. The strength of this approach is to accurately control and manipulate most of the influencing variables (e.g. environmental conditions). However, the applicability of findings arising from laboratory settings has been questioned.[71] Further research is therefore required to assess RSA using more sport-specific tests, while still ensuring a high level of standardization and reliability of measures. Sports Med 2011; 41 (8)
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2.4 Influence of Other Factors
Other factors, such as sex,[72,73] age,[63,64,74,75] playing position (soccer[76]), training status (activity performed, level of competitiveness)[76,77] and whether or not subjects are sickle cell trait carriers,[78] have also been reported to influence RSA. In general, being female, young or aerobically trained has typically been associated with a smaller decrement score. However, further research is required to establish whether these differences can be attributed to differences in fatigability or can largely be explained by differences in initial mechanical output (see section 2.3). The effect of the time of day on RSA has also been studied.[41,46,79] Muscle power during the first sprint was improved in the afternoon, compared with the morning, leading to a sharper decrease in performance, with no significant difference for total work (figure 4).[41] While a greater decrement score in the afternoon could be interpreted as impaired RSA, mechanical power during the final sprints was not significantly different between the morning and afternoon conditions. Thus, the higher decrement score in the afternoon is simply the consequence of the greater initial mechanical output, and, as previously mentioned (see section 2.1), a greater sprint decrement score cannot always be interpreted as a poorer RSA. This was confirmed by a subsequent study showing no difference in sprint decrement in the afternoon when initial sprint performance was matched to that performed in the morning.[46] This further highlights the need to carefully interpret changes in the decrement score if there are concomitant changes in initial sprint performance. 3. Limiting Factors 3.1 Muscular Factors 3.1.1 Muscle Excitability
At the skeletal muscle level, marked ionic disturbances, arising secondary to decreases in sodium (Na+)/potassium (K+)-adenosine triphosphatase (ATPase) activity, have been observed following intense dynamic contractions.[80,81] In such cases, the Na+/K+ pump cannot readily re-accumulate the K+ efflux out of the muscles cells, inducing at least a ª 2011 Adis Data Information BV. All rights reserved.
679
doubling of muscle extra-cellular K+ concentration ([K+]).[82] These modifications will impair cell membrane excitability and depress force development, probably by slow inactivation of Na+ channels,[83] and will be manifested indirectly by a reduction in action potential amplitude and a slowing of impulse conduction.[84] Since most of our knowledge to date has been gained from in vitro studies, it is still unclear whether these ionic disturbances contribute to fatigue during RSE. Unpublished observations have shown that plasma [K+], when corrected for changes in plasma volume, does not change following 5 · 6 second sprints (30 seconds of recovery). However, further research is required since (i) interstitial [K+] is considerably higher than venous plasma [K+] at similar work intensities; and (ii) venous [K+] values may not reflect the concentration in the interstitium (i.e. the site where K+ may have its effects).[82] By applying an electrical stimulus to peripheral nerves, the study of the in vivo muscle compound action potential (M-wave) characteristics has been used to determine whether exercise-induced fatigue alters muscle excitability. Decreased M-wave amplitude, but not duration, was reported after a repeated-sprint running protocol (12 · 40 m, 30 seconds of recovery), suggesting that action potential synaptic transmission, rather than propagation (i.e. impulse conduction velocity along the sarcolemma), may be impaired during such exercise (figure 5[85]). However, whether a loss of membrane excitability contributes to fatigue is equivocal since a potentiation of the M-wave response has also been reported following a repeatedsprint cycle exercise.[27] As the actual size of the M-wave depends on the sum of a number of factors, e.g. the muscle investigated, the amount of preceding activity and/or the motor unit firing rates, further research is needed to elucidate the contribution of an impairment in muscle excitability to muscle fatigue induced by the repetition of sprints with a strict control of the abovementioned influencing factors. 3.1.2 Limitations in Energy Supply Phosphocreatine Availability
With total intramuscular stores of approximately 80 mmol kg dry muscle (dm)-1 [figure 6] and
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adenosine triphosphate (ATP). As a consequence, phosphocreatine is particularly important during RSE, where a high rate of ATP utilization and resynthesis is required. In this respect, it is interesting to note that stores after a maximal 6-second sprint can be reduced to around 35–55% of resting levels,[22,87] and that the complete recovery of phosphocreatine stores can require more than 5 minutes.[15,88] In addition, human skeletal muscle fibres have been reported to have fibre-type-dependent differences in the usage of ‘high-energy’ phosphates with greater phosphocreatine reduction in fasttwitch fibres than in slow-twitch fibres.[89,90] Fasttwitch fibres dominate power production during supra-maximal exercise such as RSE. Thus, selective ‘phosphocreatine deficit’ of those fibres might be related to the failure to replicate performance when sprints are repeated.[91] As recovery times during RSE generally do not exceed 60 seconds, the ATP/phosphocreatine stores may only be partially restored before the onset of subsequent exercise,[14,87] resulting in compromised performance during successive sprints.[22,92] Coupled with the fact that the recovery of power output and the resynthesis of phosphocreatine follow similar time courses, several authors have proposed
Before exercise After exercise
M-waves (soleus muscle) Stimulation artifact
Tibial nerve stimulation (supramaximal intensity)
3 mV 5 ms
EMG electrodes (measurement site) Fig. 5. Typical changes from one representative subject for the resting soleus muscle compound action potential (M-wave) before and after a repeated running sprint exercise (12 · 40 m with 30 sec of recovery). By analysing the changes in the electrically evoked M-wave following a supra-maximal tibial nerve stimulation, surface electromyography (EMG) can be a reliable non-invasive method to characterize sarcolemmal excitability. In human experiments, the M-wave is commonly used as an index of neuromuscular transmission (amplitude) and action potential propagation (duration) in muscle fibres. Note that the peak-to-peak amplitude of the M-wave recorded after the repeated running sprints was depressed compared with values obtained before exercise (adapted from Perrey et al.[85])
maximal turnover rates approaching 9 mmol kg dm-1 s-1,[86] phosphocreatine represents the most immediate reserve for the rephosphorylation of 90 80
[PCr] (mmol • kg−1 dm)
70 60 44.3 mmol • kg−1 dm 50 40 30 25.3 mmol • kg−1 dm
20 10 0 1
2
3
4
5
6
7
8
9
10
Sprint number Fig. 6. Changes in phosphocreatine concentration ([PCr]) utilization before and after the first and last sprint of a 10 · 6 sec repeated-sprint test (with 30 sec of recovery between sprints) on a cycle ergometer (modified from Gaitanos et al.[22]). dm = dry muscle.
ª 2011 Adis Data Information BV. All rights reserved.
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Fatigue and Repeated-Sprint Ability
that performance during this type of work may become increasingly limited by phosphocreatine availability – i.e. a decrease in the absolute contribution of phosphocreatine to the total ATP production with each subsequent sprint (figure 6).[15,91] In line with this proposition, significant correlations have been reported between the resynthesis of phosphocreatine and power output recovery in the first 10 seconds of a second 30-second sprint (r = 0.84; p < 0.05)[14] and the partial restoration of repeatedsprint performance (i.e. total work done) following a fatigue-induced reduction in muscle phosphocreatine stores (r = 0.67, p < 0.05) [MendezVillanueva A, et al., unpublished observations]. This would suggest that better maintenance of muscle power output could be attributed to a faster rate of phosphocreatine resynthesis during the recovery between sprints.
681
ATP PCr Glycolysis Aerobic a
8%
6%
40%
46%
2%
b
40% 49%
Anaerobic Glycolysis
Anaerobic glycolysis supplies approximately 40% of the total energy during a single 6-second sprint, with a progressive inhibition of glycolysis as sprints are repeated (figure 7).[22,94] For instance, Gaitanos et al.[22] reported an 8-fold decrease in the absolute ATP production from glycolysis from the first to the last sprint of 10 · 6-second maximal sprints interspersed with 30-second recovery periods. It is unclear, however, whether increasing the maximal anaerobic glycogenolytic and glycolytic rate will lead to improvements in RSA. For example, it could be argued that training which increases the ability to supply ATP from anaerobic glycolysis would be detrimental to RSA, as individuals with the greatest decrements in power output during RSE have been reported to have the greatest glycolytic rate during the first sprint.[26] However, it also needs to be considered that subjects with a greater glycogenolytic rate have also been reported to have a greater initial sprint performance[15] and that there is a strong correlation between initial sprint performance and both final sprint performance and total sprint performance[26,47] during tests of RSA. Thus, while these findings highlight the difficulties associated with interpreting contrasting effects on the various RSA test measures, they also point out the need for future investigations that should determine whether increasing the ª 2011 Adis Data Information BV. All rights reserved.
9% Fig. 7. Changes in metabolism during (a) the first and (b) the last sprint of a repeated-sprint exercise.[55,62,93] Note that the area of each circle represents the total absolute energy used during each sprint. ATP = adenosine triphosphate; PCr = phosphocreatine.
anaerobic contribution is likely to improve both initial and mean sprint performance, and thus the ability to perform repeated sprints. Oxidative Metabolism
The contribution of oxidative phosphorylation to total energy expenditure during a single short sprint is limited (<10%).[95,96] As sprints are repeated, however, the level of aerobic ATP provision progressively increases such that aerobic metabolism may contribute as much as 40% of the total energy supply during the final repetitions of a RSE (figure 8).[95] Furthermore, subjects may reach their . VO2max (moderate to high values generally ranging from 50 to 65 mL min kg-1 across racket and team sports)[4,11] during the latter sprints.[95,97] This suggests that the aerobic . contribution during RSE may be limited by VO 2max and that increasing . VO2max via appropriate training (as discussed in the subsequent companion review[40])[98] and/or
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AOD Aerobic 10 9 8
VO2 (L/min−1)
7
.
6 5 4
. VO2max
3 2 1 0 Sprint 1
Sprint 5
Fig. 8. As sprints are repeated, there is an increase in the aerobic contribution to individual . sprints. The dashed line represents the max[95] imal oxygen uptake (VO2max) [adapted . from McGawley and Bishop ]. AOD = accumulated oxygen deficit; VO2 = oxygen uptake.
ergogenic aids (e.g. erythropoietin or EPO)[99] may allow for a greater aerobic contribution during the latter sprints, potentially minimizing fatigue. This hypothesis . may explain why subjects with a greater VO2max are more able to maintain power output/sprint times during a RSE, and is supported by significant correlations (r = -0.45 to -0.75) . between VO2max and performance fatigue indices (e.g. Sdec or FI).[51,77,100-102] This is not a universal finding, however, with others reporting low to . nonsignificant correlations between VO2max and FIs during RSE (r = -0.20 to 0.30).[47,93,103-108] This mixed view regarding the effect of an elevated . VO2max on RSA may be due to the difference between studies for the fitness level of the tested subjects and/or the nature of the RSE, together with the use of relatively homogenous samples. The absence of stronger correlations between . VO2max and RSA may also be related . to the belief that the primary factor limiting VO2max is the ability of the cardiorespiratory system to deliver O2 to the exercising muscles (i.e. central factors), whereas RSA may be primarily limited by muscle disturbances (i.e. peripheral factors).[109] This is supported by the observation that the FI during a RSE has been reported to be inversely correlated ª 2011 Adis Data Information BV. All rights reserved.
with maximal ADP-stimulated mitochondrial respiration measured directly in muscle fibres.[110] Interestingly, subjects who desaturated the most during a prolonged RSA test had the greatest work decrement over .20 · 5-second cycle sprints (and also had the lowest VO2max).[111] Other indirect measures of muscle oxidative capacity, such as oxygen con. sumption (VO2) kinetics[97,112] and the velocity at the onset of blood lactate accumulation,[113] have also been reported to be correlated . with RSA. For example, subjects with faster VO2 off-kinetics during exercise of severe intensity (two runs at 120% of maximal aerobic speed, interspersed by 6 minutes of recovery, until exhaustion) are those with the smallest sprint decrement score during a repeated-sprint test.[112] Finally, using the near-infrared spectroscopy (NIRS) technique, two studies have shown that the increase in muscle deoxyhaemoglobin engendered by sprint repetitions remains fairly constant.[27,29] This indicates that despite a progressive deoxygenation as sprints are repeated, the ability of the subjects to use available oxygen during RSE may be well preserved. Furthermore, the rate of muscle reoxygenation during the recovery periods between sprints would be an important factor limiting RSA, as evidenced by the strong correlation between the improvement of this parameter and the sprint decrement calculated for shuttle sprints after an 8-week endurance training programme.[114] Nevertheless, future studies combining pulmonary gas exchange and muscle oxygenation kinetics during RSE are needed to determine whether both ‘central’ (cardiovascular) and ‘peripheral’ (at the skeletal muscle level) impairments to oxidative pathways contribute to performance decrements. 3.1.3 Metabolite Accumulation Acidosis
It has been argued that the considerable increases in muscle[51,65] and blood[47,64] hydrogen ion (H+) accumulation that occur during RSE may affect sprinting performance via adverse effects on the contractile machinery and/or through the inhibition of ATP derived from glycolysis, possibly via negative effects on phosphofructokinase and glycogen phosphorylase.[115] In support of this suggestion, correlations have been observed between sprint Sports Med 2011; 41 (8)
Fatigue and Repeated-Sprint Ability
decrement and both muscle buffer capacity and changes in blood pH.[26,47,51] Furthermore, the content of skeletal muscle monocarboxylate transporters (i.e. MCT1), which facilitate the intramuscular lactate and H+ removal process, has been inversely correlated with FIs calculated during ten successive 10-second cycling sprints (30 seconds of recovery).[116] At physiological temperatures, however, acidification as a direct cause of muscle fatigue has been challenged for at least three reasons as follows: (i) the time course of the recovery of force/power following a bout of intense/maximal work is much faster than that of pH; (ii) high power outputs have been obtained under acidic conditions; and (iii) the ingestion of sodium bicarbonate (known to increase extra-cellular buffering capacity) has, in some cases, been reported to have no effect on RSA.[117,118] Furthermore, no significant correlations have been observed between the recovery of muscle pH and short-term recovery of both single 30-second ‘allout’ bouts[15] and repeated, 6-second cycling sprints (Mendez-Villanueva A, et al., unpublished observation). Further research is therefore needed to clarify the effects of H+ accumulation on the aetiology of fatigue during RSE. Inorganic Phosphate
Indirect evidence that impairment of excitationcontraction coupling (i.e. the mechanisms that link sarcolemmal depolarization to calcium release) may contribute to fatigue during RSE has been obtained from experiments that have used electrically evoked contractions. With this approach, peripheral contractile properties can be identified and isolated from components located upstream from the neuromuscular junction.[119] In the fatigued state, lower peak twitch force in both the plantar flexors[85] and the knee extensors[27] has been observed following two different repeatedsprint protocols, suggesting that contractile properties of the active muscles had become less optimal across repetitions. In line with these results, lowfrequency fatigue (i.e. a decrease in the ratio between mechanical responses to tetanus at low- and high-frequency stimulations) has also been detected after repeated running sprints.[85] In vitro studies provide evidence that increased inorganic ª 2011 Adis Data Information BV. All rights reserved.
683
phosphate levels affect calcium release from the sarcoplasmic reticulum and/or myofibrillar calcium sensitivity, which in turn decrease the number of strong binding cross-bridges.[120,121] However, whether this scenario occurs during RSE is still unknown and requires further research. 3.2 Neural Factors 3.2.1 Neural Drive
As maximal sprint exercise demands high levels of neural drive,[122] failure to fully activate the contracting musculature, as assessed by surface electromyogram (EMG), will theoretically decrease force production and therefore reduce RSA. While not a universal finding,[24,59,85,117] a concurrent decline in mechanical scores and the amplitude of EMG signals (root mean square [RMS] and integrated EMG values) has been reported in several studies (table I).[21,27,29,50,72,111] When fatigue is mild (FI or sprint decrement score <10%), previous research has typically reported a steady level of neural activation during RSE.[24,59,85,117] However, when the fatigue level is more substantial (>10%), a concurrent decline in mechanical performance and the amplitude of EMG signals has consistently been reported across sprint repetitions.[21,27,50] This suggests that under conditions of considerable fatigue, failure to fully activate the contracting musculature may become an important factor contributing to fatigue during RSE. Interestingly, changes in quadriceps EMG amplitude explained 97% of the variance in total work done during ten successive cycle sprints, interspersed with 30 seconds of rest.[21] Billaut and Smith[72] also add that there is no sex dimorphism in this relation (r2 = 0.97 and 0.86 in men and women, respectively; p < 0.05). The reduction in power output during RSE, however, makes it difficult to relate neural adjustments to RSA, as the lower EMG activity could also be the consequence, rather than the cause, of the reduced power output. It is also noteworthy that resistance load affects surface EMG activity during RSE, as a decrement in the RMS value was observed from the first to the ninth repetition when ten 10-second cycling sprints were performed under light-load but not heavy-load conditions.[53] Furthermore, difficulties in interSports Med 2011; 41 (8)
Study (y)
RSE
Fatigue effects
no. of subjects and training level
repetitions
Billaut et al.[123] (2005)
12 physically active
10
Billaut et al.[124] (2006)
12 physically active
Billaut and Basset[59] (2007)
13 physically active
Billaut and Smith[72] (2009)
32 trained
684
ª 2011 Adis Data Information BV. All rights reserved.
Table I. A summary of the characteristics and results of studies that have investigated changes in muscle activation parameters during cycling repeated-sprint exercise (RSE)a
10
10
sprint duration (sec) 6
6
6
recovery duration (sec)
mechanical changes
muscle activation changes
30
fl PPO (11%), PR (7%) and PT (14%) from sp1 to sp10
- iEMGsprint during RSE
30
30
fl PPO (8%, 10% and 11% after sp8, 9 and 10, respectively)
› VL RMSMVC (~15%) post-RSE - VM RMSMVC (~ +10%) post-RSE
fl MVCpost (13%) and MVC+5min (10%)
fl VL and VM MFMVC (~15%) post-RSE
fl PPO and MPO (~9–13%) from sp1 to sp8
- VL RMSMVC (~+10%) - MFMVC (~ -8%)
fl MVCpost (~10%) - MVC+5min (~ -8%) and MVC+10min (~ -6%) 20
5
25
fl activation time delays (~90 min) between VL and BF EMG onsets from sp1 to sp10
fl TW from s1 to sp7 (~9%) and sp20 (~25%)
fl iEMGsprint (~8% from sp1 to sp9 + 15.5% across all reps) fl VL, RF and GM MFsprint (~10–13%) from sp1 to sp20
Billaut and Smith[111] (2010)
15 trained
20
5
25
fl TW across reps (~23.5%)
fl iEMGsprint (~14.2% vs -16.4% in VL and RF, respectively)
Giacomoni et al.[79] (2006)
12 trained
10
6
30
fl PPO (~10% and 11%), PT (~2% and 9%) and TW (~16%) from sp1 to sp10 in the morning and evening, respectively.
› VL RMSMVC (~7.5% and 10% in the morning and evening) after RSE
fl MVCpost (~15% and 13%) and MVC+5min (~10% and 11%) in the morning and evening, respectively 10 physically active
15
5
25
fl PPO (~11%), moment produced (~6%) and PR (~5%) from sp1 to sp13
fl RMSsprint in BF and GL (~13% and 17%) from sp1 to sp13 - RMSsprint in GMax, VL and RF from sp1 to sp13
Matsuura et al.[125] (2006)
8 trained
10
10
35
fl PPO (~17%) from sp1 to sp10
fl VL and RF iEMGsprint (~12–15% and 20%) from sp1 to sp10 - VL and RF MPFsprint from sp1 to sp10
Matsuura et al.[117] (2007)
8 trained
10
10
30
fl PPO and MPO (~25%) after sp8
- VL RMSsprint during RSE
MendezVillanueva et al.[50] (2007)
8 physically active
10
6
30
fl VL MPFsprint (~5–10%) after sp3 and sp7 only fl PPO (~24%) from sp1 to sp10
fl VL RMSsprint (~14%) from sp1 to sp10
fl TW (~27%) from sp1 to sp10
fl VL MFsprint (~11%) from sp1 to sp10
Continued next page
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Sports Med 2011; 41 (8)
Hautier et al.[24] (2000)
All data were collected during cycle-based repeated sprinting protocols using a passive recovery mode between sprints. a
13 trained
BF = biceps femoris; EMG = electromyogram; GL = gastrocnemius lateralis; GM = gastrocnemius medialis; GMax = gluteus maximus; iEMGsprint = during sprinting after integrated EMG; MFsprint = median frequency during sprinting; MFMVC = median frequency during maximal voluntary contraction; MPFsprint = mean power frequency during sprinting; MPO = mean power output; MVC+5min and +10min = maximal voluntary contraction torque measured +5min and +10min after RSE; MVCpost = maximal voluntary contraction torque post-exercise; PPO = peak power output; PR = maximal pedalling rate; PT = peak torque applied on the crank; reps = repetitions; RF = rectus femoris; RMS/MMVC = normalized root mean square activity obtained during maximal voluntary contraction; RMSMVC = RMS measured during maximal voluntary contraction; RMSsprint = RMS measured during sprinting; sp = sprint; TW = total work; VA = voluntary activation; VL = vastus lateralis; VM = vastus medialis; fl indicates decrease; › indicates increase; - indicates no significant change.
685
fl VL iEMGsprint (-12.4% vs 26.5% in normoxia and hypoxia, respectively) from sp1 to sp6–10 fl TW (overall decrement -31.2%) from sp2 to sp10 30 10
fl MVCpost (16.5%)
Smith and Billaut[29] (2010)
10
fl VL RMSsprint (~14%)
fl VL RMS/MMVC (14.5%) and VA (2.5%)
fl PPO (~10%) from sp1 to sp10 30 6 9 physically active
10
fl VL RMSsprint from sp1 to sp5 (~9%) and from sp1 to sp10 (~14%)
Racinais et al.[27] (2007)
mechanical changes
fl PPO and MPO from sp1 to sp5 (~14% and ~17%) and from sp1 to sp10 (~25 and ~28%), respectively 30 6 10 8 physically active MendezVillanueva et al.[21] (2008)
RSE Study (y)
Table I. Contd
no. of subjects and training level
repetitions
sprint duration (sec)
recovery duration (sec)
Fatigue effects
muscle activation changes
Fatigue and Repeated-Sprint Ability
ª 2011 Adis Data Information BV. All rights reserved.
preting EMG data need to be acknowledged (e.g. amplitude cancellation phenomena, excessive sweat, changes in fibre membrane and motor unit properties).[126] For instance, interpretation of EMG scores (e.g. RMS) is complicated by the fact that, at the muscle level, EMG signal can be influenced by modifications in sarcolemmal excitability.[127] Future studies should therefore control for potential modifications in M-wave amplitude (i.e. an index of sarcolemmal excitability)[27] obtained after the successive sprint bouts, and calculate the ratio of the EMG signal to the M-wave response (i.e. RMS/ M-wave ratio) to ensure that neural input reaching the neuromuscular junction effectively decreases with fatigue. Nonetheless, the suboptimal motor unit activity (i.e. a decrease in recruitment, firing rate or both), inferred by changes in surface EMG activity, has also been highlighted via the MRI technique[128] and interpolated-twitch results obtained during post-RSE assessment of neuromuscular function (figure 9).[27,85] These results have implications in the context of multiple-sprint sports, since muscle activation is known to influence the sensorimotor control of force with fatigue,[129] which may in turn negatively affect the quality of specific sporting skills, and potentially increase the risk of injury (e.g. extreme range of motion and/or higher mechanical stress/load imposed on joints).[130] The mechanisms that lead to a decreased motor unit activity of the active muscle – notably in the context of RSE – are still not well understood. Nevertheless, it has been proposed that the CNS receives sensory input from muscle afferents (e.g. muscle spindles, Golgi tendon organs, free endings of group III and IV nerves), which are incorporated into the determination of central neural drive, to adjust for the rate of intramuscular fatigue-related metabolite accumulation (e.g. H+ and phosphate), with the purpose of avoiding the development of peripheral fatigue beyond a given individual threshold.[131] This viewpoint is supported by studies demonstrating a correlation between H+ accumulation and change in group III and IV muscle afferents discharge rate.[132] To date, however, it remains unclear whether afferent feedback from fatigued muscle differs according to the continuous/ intermittent nature of the exercise task.[133,134] Regarding RSE, it is reasonable to expect that the Sports Med 2011; 41 (8)
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Before Superimposed twitch
Femoral nerve stimulation (supramaximal intensity)
Potentiated twitch
EMG (Vastus lateralis) After
Force
Fig. 9. Typical force and electromyogram (EMG) [vastus lateralis muscle] traces during knee extensor maximal voluntary contractions (MVC) before and after a repeated-sprint cycling exercise (10 · 6 sec with 30 sec of recovery). By comparing the twitch superimposed to a MVC and the twitch evoked on the relaxed muscle (i.e. femoral nerve supra-maximal stimulation), the twitch interpolation technique in conjunction with surface EMG (i.e. root mean square [RMS] value normalized by the maximal muscle compound action potential [M-wave]) can be a reliable non-invasive technique to characterize muscle activation. Voluntary activation level (%) was estimated according to the following formula: (1 – [superimposed twitch/potentiated twitch)] · 100). Note that both the voluntary activation level and the normalized RMS activity were depressed (-2.5% and -14.5%, respectively) compared with values obtained before exercise (adapted from Racinais et al.[27]).
dramatic metabolic disruptions occurring within the muscle cell (see section 3.1.3) might also have consequences for central neural drive. However, the manipulation of intramuscular pH by oral administration of sodium bicarbonate did not affect surface EMG activity or peak/mean power output during repeated cycling sprints.[117] In this regard, it has also been suggested, in a sprint-like exercise, that sensory feedback signalling peripheral fatigue might be suppressed, blocked or simply counteracted by a stronger central command.[135,136] In addition to muscle afferents sensitive to metabolite accumulation, the reduction in arterial O2 saturation (and brain oxygenation) has been shown to be a major determinant of the attenuation in motor unit activity.[111] When 15 national-level soccer players performed 20 · 5-second cycle sprints (25 seconds of rest), Billaut and Smith[111] have reported that the progressive arterial O2 desaturation that develops across repetitions is strongly correlated with reductions in mechanical work and in ª 2011 Adis Data Information BV. All rights reserved.
the surface integrated EMG (r2 = 0.68 and 0.62, respectively; p < 0.05). These findings are compatible with those of several in vitro and in vivo experiments, demonstrating that motor cortex excitability and neuromuscular activity are influenced by O2 availability.[137,138] A decrease in motor unit activity can theoretically arise from changes at the spinal level and/or supraspinal factors. At the spinal level, changes in the number of a-motoneurons that are recruited in the motoneuron pool (i.e. motoneuron excitability) can be detected with the Hoffman (H)-reflex recordings.[139] As no modification in the soleus resting H-reflex response was observed following 12 · 40 m sprints (30 seconds of recovery), preliminary evidence therefore questions the possibility of a reduced reflex excitability of spinal a-motoneurons as a fatigue agent during RSE.[85] Under fatigue, adaptations in neural function can also result in a reduced efficiency in the generation of the motor command due to supraspinal factors, as potentially Sports Med 2011; 41 (8)
Fatigue and Repeated-Sprint Ability
reflected by disturbances in brain electrical activity, cortical excitability and/or brain neurotransmitter (e.g. serotonin, dopamine, acetylcholine) concentration.[140,141] While no study has directly investigated whether these changes can compromise RSA, those observations are consistent with highintensity, exercise-induced, post-fatigue impairments in supraspinal function as reductions in cortical drive[142,143] and corticospinal synaptic transmission.[144,145] However, the actual relevance that these changes in the CNS can have on RSA remains largely unknown. In this regard, the maintenance of motor neuron activity and power output may be due to entirely different mechanisms.[146] For example, it is known that exercise-induced fatigue can be caused by slowed muscle contractile properties.[142,146] As the relaxation rate of the muscle declines during fatigue, the lower neural stimulation frequency (i.e. firing rates) maintains the tetanus and thus optimizes maximum force production because the metabolic activity involved in the contractions changes the muscle properties in tandem.[147,148] Further studies are therefore needed to better understand the role of decreases in neural drive on the aetiology of fatigue during RSE and the spinal/supraspinal mechanisms of these adaptations. To reach this target, neural adaptations should be studied in terms of neurotransmitter turnover (e.g. serotonin and dopamine concentrations), cerebral oxygenation (e.g. NIRS), brain electrical activity (e.g. electroencephalography), and cortical excitability (e.g. transcranial magnetic stimulation).
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RSE. Using 15 · 5-second cycle sprints separated by 25 seconds of recovery, Hautier et al.[24] observed a significant reduction in RMS for the knee flexor muscles in the thirteenth compared with the first sprint without changes in RMS for the knee extensor muscles, highlighting a possible decrease in muscle coactivation with fatigue. The lower activation of antagonist muscles after fatigue has been interpreted by these authors as an efficient adaptation of the inter-muscular coordination to transfer reduced force and power to the pedal. A shift in median frequency values (obtained during maximal isometric voluntary contractions) toward lower frequencies has also been reported post-RSE.[124] This has been interpreted as a modification in the pattern of muscle fibre recruitment; i.e. decreased recruitment of fibres with faster conduction velocities. More tellingly, it is probable that the relative contribution of type I muscle fibres involved in force generation may increase during RSE as a result of the greater fatigability of type II fibres, highly solicited during this exercise mode.[149] Caution is needed, however, when interpreting these data since the external validity of standard tests for strength production capacity (maximal voluntary contractions) to reflect fatigue resistance could be challenged due to methodological differences in subject’s positioning and/or muscle contraction mode.[150] However, using EMG recordings during cycle-based repeated sprinting, Matsuura et al.[125] concluded that greater fatigue was linked to a decreased preferential recruitment of fast-twitch motor units as mean power frequency was higher with 35-second than with 350-second recovery periods.
3.2.2 Muscle Recruitment Strategies
An additional neural factor that may contribute to fatigue during RSE is a modification of muscle recruitment strategies. Billaut et al.[123] have reported that the time delay between the knee extensor and the flexor EMG activation onsets was reduced during the last sprint of a RSE, owing to earlier antagonist activation with fatigue occurrence. In the same study, no modification of the integrated EMG score was noted across sprint repetitions. This suggests that changes in intermuscle coordination (e.g. vastus lateralis/biceps femoris coordination pattern) could contribute to the power output reduction under fatigue during ª 2011 Adis Data Information BV. All rights reserved.
4. Additional Factors Affecting RSA 4.1 Stiffness Regulation
Although not as extensively studied, changes in mechanical behaviour (stiffness regulation) may also indirectly alter fatigue resistance during repeated running sprints.[122] It is generally believed that a stiffer system allows for a more efficient elastic energy contribution, potentially enhancing force production during the concentric phase of the movement.[151] Supported by the close relationship between leg stiffness and sprint running perSports Med 2011; 41 (8)
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formance,[152] it has been argued that stiffness regulation is a vital component for setting stride frequency.[151] In line with this statement, decreased stride frequencies have been shown to accompany fatigue development during run-based repeated sprinting.[55,64] The clear relationship between impairment of spring-mass model properties of runners’ lower limbs and the decrease in performance induced by the repetition of all-out efforts (4 · 100 m interspersed with 2 minutes of recovery) has previously been highlighted.[153] Marked alterations in leg-spring behaviour were also reported by Girard et al.[154] when 16 active subjects performed 12 · 40 m sprints interspersed with 30 seconds of passive recovery. As peak vertical force was not modified by sprint repetitions, fatigue-induced slower stride frequencies, stemming from changes in vertical displacement of the centre of mass (decreased vertical stiffness) rather than changes in leg length (preserved leg stiffness), are likely to explain the longer sprint times across trials.[154] Interestingly, athletes participating in a training programme that includes field, resistance, plyometric and eccentric training are more successful than recreational sporting participants at regulating joint stiffness during repeated running sprints.[155] These findings may support the view that the ability to maintain a high level of stiffness condition may improve fatigue resistance during RSE. Further research is required to verify this hypothesis. 4.2 Environmental Perturbations
RSA is also likely to be further compromised for subjects who are exposed to environmental stresses, such as when competing in hot environments (Tennis Australian Open) or at altitude (2010 Football World Cup in South Africa). The experimental approach of using an additional environmental stress to further perturb homeostasis is also potentially useful to gain knowledge regarding the nature of the mechanisms limiting RSA. To date, little is known about the impact of such influencing factors on RSA since most of our knowledge in this area comes from intermittent-sprint exercises (e.g. heat exposure;[17,156] simulated altitude[157,158]). Nevertheless, investigating how thermal stress affects power output during repeated 30-second bouts ª 2011 Adis Data Information BV. All rights reserved.
of maximal, cycling exercise – each bout being separated by 4 minutes of recovery – Ball et al.[13] have reported increased peak and mean power outputs (~25% and 15%, respectively) when the 30-second all-out bouts were performed in a warm (~30C, 55% relative humidity) versus a thermo-neutral (~19C, 40% relative humidity) environment; this was due to achieving a higher pedal cadence in the heat, probably through an elevated rate of anaerobic ATP turnover and muscle fibre conduction velocity.[159] When the intermittent-sprint and repeated-sprint performance (i.e. a pattern of 5 · 2-second sprints, separated by ~21 seconds, reproduced twice) of subjects performing 0, 10 and 20 minutes of active warm-up prior to a 36-minute intermittent-sprint test performed in hot conditions (35.5C, 49% relative humidity) was measured, Bishop and Maxwell[160] found a greater increase in core temperature following the longer warm-up, which was associated with a compromised repeatedsprint performance. Drust et al.[161] have also reported an impaired ability to produce power during five 15-second all-out efforts on a cycle ergometer when core and muscle temperatures are simultaneously elevated. This impairment in performance occurred after the completion of the first sprint and was observed following both the completion of a 40-minute intermittent exercise in a hot environment and after passively induced hyperthermia. In the absence of metabolic changes (i.e. muscle lactate, extra-cellular potassium), these authors have associated the larger reduction in peak and mean power output in the heat to the negative influence of a high core temperature on the function of the CNS (e.g. alterations in brain activity, reductions in cerebral blood flow, increases in whole-brain energy turnover, reduced muscle activation). Despite a greater physiological strain experienced with the greatest level of hypo-hydration, reductions in work performed and peak power output were only observed after a second, intense RSE during the latter stages of a 36-minute, cycling, intermittentsprint test.[162] To date, little research has investigated the role of hypoxia on RSA.[29,163] In one study, Balsom et al.[163] examined the influence of oxygen availability on factors responsible for fatigue during 10 · 6-second cycle sprints interspersed with Sports Med 2011; 41 (8)
Fatigue and Repeated-Sprint Ability
30-second rest periods. While subjects were instructed to try and maintain a pedalling frequency of 140 revolutions per minute throughout each sprint, pedalling frequencies during the final 2 seconds of the last two repetitions were lower under hypoxic than under normoxic conditions. . A slower on-transient VO2 response, as a result of reduced oxygen availability, would increase the magnitude of the O2 deficit incurred during each sprint and thereby place more demand on anaerobic sources to maintain the required rate of ATP provision. The increased rate of fatigue under hypoxic conditions may have also been the result of a more rapid accumulation of inorganic phosphate during each sprint and a reduced rate of removal during recovery.[164] Nevertheless, the consequences of reduced oxygen content are not exclusively ascribed to peripheral sources, as CNS function during exercise in hypoxia also has the potential to curtail muscle activation and therefore alter fatigue resistance.[165] Using NIRS measurements, it has been reported that an earlier and larger degree of deoxygenation of the prefrontal cortex in acute moderate hypoxia (i.e. insufficient O2 delivery and/or low pressure gradient to drive the diffusion of O2 from the capillaries to the mitochondria) was associated with impairments in RSA.[29] Little is known, however, about these cortical dysfunctions, especially as most of our knowledge in this area concerns continuous locomotor tasks. 5. Conclusions During RSE, the inability to reproduce performance in subsequent sprints (fatigue) is manifested by a decline in sprint speed (running) or peak/mean power output (cycling). Although many issues remain unresolved, proposed factors responsible for fatigue include limitations in .energy supply (e.g. phosphocreatine content and VO2) and metabolic by-product accumulation (e.g. inorganic phosphate, H+). Although not as extensively studied, failure to fully activate the contracting muscle may also compromise fatigue resistance during RSE. Moreover, the details of the task (e.g. changes in the nature of the work/recovery bouts) and additional environmental perturbations will determine the relative contribution of the underlying mechª 2011 Adis Data Information BV. All rights reserved.
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anisms (task dependency) to fatigue. Interventions (e.g. ergogenic aids or training) that can lessen the influence of these limiting factors should improve RSA (as discussed in the subsequent companion review[40]). Acknowledgements No sources of funding were used to assist in the preparation of this review. The authors have no conflicts of interest that are directly relevant to the content of this review.
References 1. Bangsbo J, Norregaard L, Thorso F. Activity profile of competition soccer. Can J Sport Sci 1991; 16: 110-6 2. Cabello Manrique D, Gonzalez-Badillo JJ. Analysis of the characteristics of competitive badminton. Br J Sports Med 2003; 37: 62-6 3. Faude O, Meyer T, Rosenberger F, et al. Physiological characteristics of badminton match play. Eur J Appl Physiol 2007; 100: 479-85 4. Girard O, Millet GP. Neuromuscular fatigue in racquet sports. Neurol Clin 2008; 26: 181-94 5. Glaister M. Multiple sprint work: physiological responses, mechanisms of fatigue and the influence of aerobic fitness. Sports Med 2005; 35: 757-77 6. Spencer M, Bishop D, Dawson B, et al. Physiological and metabolic responses of repeated-sprint activities:specific to field-based team sports. Sports Med 2005; 35: 1025-44 7. Bishop D, Spencer M, Duffield R, et al. The validity of a repeated sprint ability test. J Sci Med Sport 2001; 4: 19-29 8. Fitzsimons M, Dawson B, Ward D, et al. Cycling and running tests of repeated sprint ability. Aus J Sci Med Sport 1993; 25: 82-7 9. Spencer M, Lawrence S, Rechichi C, et al. Time-motion analysis of elite field hockey, with special reference to repeated-sprint activity. J Sports Sci 2004; 22: 843-50 10. Spencer M, Rechichi C, Lawrence S, et al. Time-motion analysis of elite field hockey during several games in succession: a tournament scenario. J Sci Med Sport 2005; 8: 382-91 11. Stolen T, Chamari K, Castagna C, et al. Physiology of soccer: an update. Sports Med 2005; 35: 501-36 12. Buchheit M, Mendez-Villanueva A, Simpson BM, et al. Repeated-sprint sequences during youth soccer matches. Int J Sports Med 2010; 31: 709-16 13. Ball D, Burrows C, Sargeant AJ. Human power output during repeated sprint cycle exercise: the influence of thermal stress. Eur J Appl Physiol Occup Physiol 1999; 79: 360-6 14. Bogdanis GC, Nevill ME, Boobis LH, et al. Contribution of phosphocreatine and aerobic metabolism to energy supply during repeated sprint exercise. J Appl Physiol 1996; 80: 876-84 15. Bogdanis GC, Nevill ME, Boobis LH, et al. Recovery of power output and muscle metabolites following 30 s of maximal sprint cycling in man. J Physiol 1995; 482 (Pt 2): 467-80
Sports Med 2011; 41 (8)
690
16. Balsom PD, Seger JY, Sjodin B, et al. Maximal-intensity intermittent exercise: effect of recovery duration. Int J Sports Med 1992; 13: 528-33 17. Duffield R, King M, Skein M. Recovery of voluntary and evoked muscle performance following intermittent-sprint exercise in the heat. Int J Sports Physiol Perform 2009; 4: 254-68 18. Balsom PD, Seger JY, Sjodin B, et al. Physiological responses to maximal intensity intermittent exercise. Eur J Appl Physiol Occup Physiol 1992; 65: 144-9 19. Bishop D, Claudius B. Effects of induced metabolic alkalosis on prolonged intermittent-sprint performance. Med Sci Sports Exerc 2005; 37: 759-67 20. Bishop D, Edge J, Davis C, et al. Induced metabolic alkalosis affects muscle metabolism and repeated-sprint ability. Med Sci Sports Exerc 2004; 36: 807-13 21. Mendez-Villanueva A, Hamer P, Bishop D. Fatigue in repeated-sprint exercise is related to muscle power factors and reduced neuromuscular activity. Eur J Appl Physiol 2008; 103: 411-9 22. Gaitanos GC, Williams C, Boobis LH, et al. Human muscle metabolism during intermittent maximal exercise. J Appl Physiol 1993; 75: 712-9 23. Balsom PD, Gaitanos GC, So¨derlund K, et al. Highintensity exercise and muscle glycogen availability in humans. Acta Physiol Scand 1999; 165: 337-45 24. Hautier CA, Arsac LM, Deghdegh K, et al. Influence of fatigue on EMG/force ratio and cocontraction in cycling. Med Sci Sports Exerc 2000; 32: 839-43 25. Yquel RJ, Arsac LM, Thiaudie`re E, et al. Effect of creatine supplementation on phosphocreatine resynthesis, inorganic phosphate accumulation and pH during intermittent maximal exercise. J Sports Sci 2002; 20: 427-37 26. Bishop D, Edge J, Goodman C. Muscle buffer capacity and aerobic fitness are associated with repeated-sprint ability in women. Eur J Appl Physiol 2004; 92: 540-7 27. Racinais S, Bishop D, Denis R, et al. Muscle deoxygenation and neural drive to the muscle during repeated sprint cycling. Med Sci Sports Exerc 2007; 39: 268-74 28. Buchheit M, Laursen PB, Ahmaidi S. Parasympathetic reactivation after repeated sprint exercise. Am J Physiol Heart Circ Physiol 2007; 293: H133-41 29. Smith KJ, Billaut F. Influence of cerebral and muscle oxygenation on repeated-sprint ability. Eur J Appl Physiol 2010; 109: 989-99 30. Lippi M. UEFA Newsletter for coaches. 2007; 4-7 [online]. Available from URL: http://www.uefa.com/newsfiles/ 493216.pdf [Accessed 2011 Jun 17] 31. Rampinini E, Bishop D, Marcora SM, et al. Validity of simple field tests as indicators of match-related physical performance in top-level professional soccer players. Int J Sports Med 2007; 28: 228-35 32. Krustrup P, Zebis M, Jensen JM, et al. Game-induced fatigue patterns in elite female soccer. J Strength Cond Res 2010; 24: 437-41 33. Mohr M, Krustrup P, Bangsbo J. Match performance of high-standard soccer players with special reference to development of fatigue. J Sports Sci 2003; 21: 519-28
ª 2011 Adis Data Information BV. All rights reserved.
Girard et al.
34. Krustrup P, Mohr M, Ellingsgaard H, et al. Physical demands during an elite female soccer game: importance of training status. Med Sci Sports Exerc 2005; 37: 1242-8 35. Trapattoni G. Coaching high performance soccer. Spring City (PA): Reedswain Inc., 1999 36. Paton CD, Hopkins WG, Vollebregt L. Little effect of caffeine ingestion on repeated sprints in team-sport athletes. Med Sci Sports Exerc 2001; 33: 822-5 37. Mohr M, Krustrup P, Nybo L, et al. Muscle temperature and sprint performance during soccer matches: beneficial effect of re-warm-up at half-time. Scand. J Med Sci Sports 2004; 14: 156-62 38. Krustrup P, Mohr M, Steensberg A, et al. Muscle and blood metabolites during a soccer game: implications for sprint performance. Med Sci Sports Exerc 2006; 38: 1165-74 39. Enoka RM, Stuart DG. Neurobiology of muscle fatigue. J Appl Physiol 1992; 72: 1631-48 40. Bishop D, Girard O and Mendez-Villanueva A. Repeated sprint ability. Part II: recommendations for training. Sports Med. In press 41. Racinais S, Connes P, Bishop D, et al. Morning versus evening power output and repeated-sprint ability. Chronobiol Int 2005; 22: 1029-39 42. Spencer M, Fitzsimons M, Dawson B, et al. Reliability of a repeated-sprint test for field-hockey. J Sci Med Sport 2006; 9: 181-4 43. Glaister M, Howatson G, Pattison JR, et al. The reliability and validity of fatigue measures during multiple – sprint work: an issue revisited. J Strength Cond Res 2008; 22: 1597-601 44. Pyne DB, Saunders PU, Montgomery PG, et al. Relationships between repeated sprint testing, speed, and endurance. J Strength Cond Res 2008; 22: 1633-7 45. Mohr M, Krustrup P, Nielsen JJ, et al. Effect of two different intense training regimens on skeletal muscle ion transport proteins and fatigue development. Am J Physiol Regul Integr Comp Physiol 2007; 292: R1594-602 46. Racinais S, Perrey S, Denis R, et al. Maximal power, but not fatigability, is greater during repeated sprints performed in the afternoon. Chronobiol Int 2010; 27: 855-64 47. Bishop D, Lawrence S, Spencer M. Predictors of repeatedsprint ability in elite female hockey players. J Sci Med Sport 2003; 6: 199-209 48. Hamilton AL, Nevill ME, Brooks S, et al. Physiological responses to maximal intermittent exercise: differences between endurance-trained runners and games players. J Sports Sci 1991; 9: 371-82 49. Yanagiya T, Kanehisa H, Kouzaki M, et al. Effect of gender on mechanical power output during repeated bouts of maximal running in trained teenagers. Int J Sports Med 2003; 24: 304-10 50. Mendez-Villanueva A, Hamer P, Bishop D. Fatigue responses during repeated sprints matched for initial mechanical output. Med Sci Sports Exerc 2007; 39: 2219-25 51. Bishop D, Edge J. Determinants of repeated-sprint ability in females matched for single-sprint performance. Eur J Appl Physiol 2006; 97: 373-9 52. Falgairette G, Billaut F, Giacomoni M, et al. Effect of inertia on performance and fatigue pattern during repeated
Sports Med 2011; 41 (8)
Fatigue and Repeated-Sprint Ability
53.
54.
55.
56.
57.
58.
59.
60.
61.
62.
63.
64.
65.
66.
67.
68.
69.
cycle sprints in males and females. Int J Sports Med 2004; 25: 235-40 Matsuura R, Arimitsu T, Yunoki T, et al. Effects of resistive load on performance and surface EMG activity during repeated cycling sprints on a non-isokinetic cycle ergometer. Br J Sports Med. Epub 2010 Dec 14 Little T, Williams AG. Effects of sprint duration and exercise: rest ratio on repeated sprint performance and physiological responses in professional soccer players. J Strength Cond Res 2007; 21: 646-8 Buchheit M, Cormie P, Abbiss CR, et al. Muscle deoxygenation during repeated sprint running: Effect of active vs. passive recovery. Int J Sports Med 2009; 30: 418-25 Castagna C, Abt G, Manzi V, et al. Effect of recovery mode on repeated sprint ability in young basketball players. J Strength Cond Res 2008; 22: 923-9 Hamlin MJ. The effect of contrast temperature water therapy on repeated sprint performance. J Sci Med Sport 2007; 10: 398-402 Spencer M, Bishop D, Dawson B, et al. Metabolism and performance in repeated cycle sprints: active versus passive recovery. Med Sci Sports Exerc 2006; 38: 1492-9 Billaut F, Basset FA. Effect of different recovery patterns on repeated-sprint ability and neuromuscular responses. J Sports Sci 2007; 25: 905-13 Glaister M, Stone MH, Stewart AM, et al. The influence of recovery duration on multiple sprint cycling performance. J Strength Cond Res 2005; 19: 831-7 Glaister M, Witmer C, Clarke DW, et al. Familiarization, reliability, and evaluation of a multiple sprint running test using self-selected recovery periods. J Strength Cond Res 2010; 24 (12): 3296-301 Holmyard DJ, Cheetham ME, Lakomy HK, et al. Effect of recovery duration on performance during multiple treadmill sprints. In: Reilly T, Lees A, Davids K, et al., editors. Science and football. London: F & N Spon, 1988: 134-42 Ratel S, Bedu M, Hennegrave A, et al. Effects of age and recovery duration on peak power output during repeated cycling sprints. Int J Sports Med 2002; 23: 397-402 Ratel S, Williams CA, Oliver J, et al. Effects of age and recovery duration on performance during multiple treadmill sprints. Int J Sports Med 2006; 27: 1-8 Spencer M, Dawson B, Goodman C, et al. Performance and metabolism in repeated sprint exercise: effect of recovery intensity. Eur J Appl Physiol 2008; 103: 545-52 Signorile JF, Ingalls C, Tremblay LM. The effects of active and passive recovery on short-term, high intensity power output. Can J Appl Physiol 1993; 18: 31-42 Jougla A, Micallef JP, Mottet D. Effects of active vs. passive recovery on repeated rugby-specific exercises. J Sci Med Sport 2010; 13: 350-5 Sim AY, Dawson BT, Guelfi KJ, et al. Effects of static stretching in warm-up on repeated sprint performance. J Strength Cond Res 2009; 23: 2155-62 Wong PL, Lau PW, Mao de W, et al. Three days of static stretching within a warm-up does not affect repeatedsprint ability in youth soccer players. J Strength Cond Res 2011; 25 (3): 838-45
ª 2011 Adis Data Information BV. All rights reserved.
691
70. Meckel Y, Gottlieb R, Eliakim A. Repeated sprint tests in young basketball players at different game stages. Eur J Appl Physiol 2009; 107: 273-9 71. Glaister M. Multiple-sprint work: methodological, physiological, and experimental issues. Int J Sports Physiol Perform 2009; 3: 107-12 72. Billaut F, Smith K. Sex alters impact of repeated bouts of sprint exercise on neuromuscular activity in trained athletes. Appl Physiol Nutr Metab 2009; 34: 689-99 73. Billaut F, Bishop D. Muscle fatigue in males and females during multiple-sprint exercise. Sports Med 2009; 39: 257-78 74. Abrantes C, Macas V, Sampaio J. Variation in football player’s sprint test performance across different ages and levels of competition. J Sports Sci Med 2004; 3: 44-9 75. Mujika I, Spencer M, Santisteban J, et al. Age-related differences in repeated-sprint ability in highly trained youth football players. J Sports Sci 2009; 27: 1581-90 76. Aziz AR, Mukherjee S, Chia MY, et al. Validity of the running repeated sprint ability test among playing positions and level of competitiveness in trained soccer players. Int J Sports Med 2008; 29: 833-8 77. Rampinini E, Sassi A, Morelli A, et al. Repeated-sprint ability in professional and amateur soccer players. Appl Physiol Nutr Metab 2009; 34: 1048-54 78. Connes P, Racinais S, Sra F, et al. Does the pattern of repeated sprint ability differ between sickle cell trait carriers and healthy subjects. Int J Sports Med 2006; 27: 937-42 79. Giacomoni M, Billaut F, Falgairette G. Effects of the time of day on repeated all-out cycle performance and shortterm recovery patterns. Int J Sports Med 2006; 27: 468-74 80. Fraser SF, Li JL, Carey MF, et al. Fatigue depresses maximal in vitro skeletal muscle Na(+)-K(+)-ATPase activity in untrained and trained individuals. J Appl Physiol 2002; 93: 1650-9 81. Clausen T, Nielsen OB, Harrison AP, et al. The Na+,K+ pump and muscle excitability. Acta Physiol Scand 1998; 162: 183-90 82. Juel C, Pilegaard H, Nielsen JJ, et al. Interstitial K(+) in human skeletal muscle during and after dynamic graded exercise determined by microdialysis. Am J Physiol Regul Integr Comp Physiol 2000; 278: R400-6 83. Ruff RL, Simoncini L, Stuhmer W. Slow sodium channel inactivation in mammalian muscle: a possible role in regulating excitability. Muscle Nerve 1988; 11: 502-10 84. Fuglevand AJ, Zackowski KM, Huey KA, et al. Impairment of neuromuscular propagation during human fatiguing contractions at submaximal forces. J Physiol 1993; 460: 549-72 85. Perrey S, Racinais S, Saimouaa K, et al. Neural and muscular adjustments following repeated running sprints. Eur J Appl Physiol 2010; 109: 1027-36 86. Hultman E, Sjoholm H. Energy metabolism and contraction force of human skeletal muscle in situ during electrical stimulation. J Physiol 1983; 345: 525-32 87. Dawson B, Goodman C, Lawrence S, et al. Muscle phosphocreatine repletion following single and repeated short sprint efforts. Scand J Med Sci Sports 1997; 7: 206-13 88. Tomlin DL, Wenger HA. The relationship between aerobic fitness and recovery from high intensity intermittent exercise. Sports Med 2001; 31: 1-11
Sports Med 2011; 41 (8)
692
89. Soderlund K, Hultman E. ATP and phosphocreatine changes in single human muscle fibers after intense electrical stimulation. Am J Physiol 1991; 261: E737-41 90. Karatzaferi C, de Haan A, van Mechelen W, et al. Metabolism changes in single human fibres during brief maximal exercise. Exp Physiol 2001; 86: 411-5 91. Sahlin K, Ren JM. Relationship of contraction capacity to metabolic changes during recovery from a fatiguing contraction. J Appl Physiol 1989; 67: 648-54 92. Yoshida T, Watari H. 31P-nuclear magnetic resonance spectroscopy study of the time course of energy metabolism during exercise and recovery. Eur J Appl Physiol Occup Physiol 1993; 66: 494-9 93. Gaul CA, Docherty D, Wolski LA. The relationship between aerobic fitness and intermittent high intensity anaerobic performance in active females [abstract]. Can J Appl Physiol 1997; 22 Suppl.: 19P 94. Boobis L, Williams C, Wootton SA. Human muscle metabolism during brief maximal exercise [abstract]. J Physiol 1982; 338: 21-2P 95. McGawley K, Bishop D. Anaerobic and aerobic contribution to two, 5 · 6-s repeated-sprint bouts. Coach Sport Sci J 2008; 3: 52 96. Parolin ML, Chesley A, Matsos MP, et al. Regulation of skeletal muscle glycogen phosphorylase and PDH during maximal intermittent exercise. Am. J Physiol 1999; 277: E890-900 97. Dupont G, Millet GP, Guinhouya C, et al. Relationship between oxygen uptake kinetics and performance in repeated running sprints. Eur J Appl Physiol 2005; 95: 27-34 98. Edge J, Bishop D, Goodman C, et al. Effects of high- and moderate-intensity training on metabolism and repeated sprints. Med Sci Sports Exerc 2005; 37: 1975-82 99. Balsom PD, Ekblom B, Sjodin B. Enhanced oxygen availability during high intensity intermittent exercise decreases anaerobic metabolite concentrations in blood. Acta Physiol Scand 1994; 150: 455-6 100. Bishop D, Spencer M. Determinants of repeated-sprint ability in well-trained team-sport athletes and endurancetrained athletes. J Sports Med Phys Fitness 2004; 44: 1-7 101. Brown PI, Hughes MG, Tong RJ. Relationship between VO(2max) and repeated sprint ability using non-motorised treadmill ergometry. J Sports Med Phys Fitness 2007; 47: 186-90 102. Dawson B, Fitzsimons M, Ward D. The relationship of repeated sprinting ability to aerobic power and performance measures of anaerobic capacity and power. Aus J Sci Med Sport 1993; 25: 88-93 103. Aziz AR, Mukherjee S, Chia MY, et al. Relationship between measured maximal oxygen uptake and aerobic endurance performance with running repeated sprint ability in young elite soccer players. J Sports Med Phys Fitness 2007; 47: 401-7 104. Castagna C, Manzi V, D’Ottavio S, et al. Relation between maximal aerobic power and the ability to repeat sprints in young basketball players. J Strength Cond Res 2007; 21: 1172-6 105. Lane KN, Wenger HA, Blair C. Relationship between maximal aerobic power and the ability to recover from repeated, high intensity, on ice sprints in male ice hockey players [abstract]. Can. J Appl Physiol 1997; 22: 35
ª 2011 Adis Data Information BV. All rights reserved.
Girard et al.
106. McMahon S, Wenger HA. The relationship between aerobic fitness and both power output and subsequent recovery during maximal intermittent exercise. J Sci Med Sport 1998; 1: 219-27 107. Wadley G, Le Rossignol P. The relationship between repeated sprint ability and the aerobic and anaerobic energy systems. J Sci Med Sport 1998; 1: 100-10 108. Aziz AR, Chia M, Teh KC. The relationship between maximal oxygen uptake and repeated sprint performance indices in field hockey and soccer players. J Sports Med Phys Fitness 2000; 40: 195-200 109. Bassett Jr DR, Howley ET. Limiting factors for maximum oxygen uptake and determinants of endurance performance. Med Sci Sports Exerc 2000; 32: 70-84 110. Thomas C, Sirvent P, Perrey S, et al. Relationships between maximal muscle oxidative capacity and blood lactate removal after supramaximal exercise and fatigue indexes in humans. J Appl Physiol 2004; 97: 2132-8 111. Billaut F, Smith K. Prolonged repeated-sprint ability is related to arterial O2 desaturation in men. Int J Sports Physiol Perform 2010; 5: 197-209 112. Dupont G, McCall A, Prieur F, et al. Faster oxygen uptake kinetics during recovery is related to better repeated sprinting ability. Eur J Appl Physiol 2010; 110 (3): 627-34 113. da Silva JF, Guglielmo LG, Bishop D. Relationship between different measures of aerobic fitness and repeatedsprint ability in elite soccer players. J Strength Cond Res 2010; 24: 2115-21 114. Buchheit M, Ufland P. Effect of endurance training on performance and muscle reoxygenation rate during repeatedsprint running. Eur J Appl Physiol 2011; 111 (2): 293-301 115. Spriet LL, Lindinger MI, McKelvie RS, et al. Muscle glycogenolysis and H+ concentration during maximal intermittent cycling. J Appl Physiol 1989; 66: 8-13 116. Thomas C, Perrey S, Lambert K, et al. Monocarboxylate transporters, blood lactate removal after supramaximal exercise, and fatigue indexes in humans. J Appl Physiol 2005; 98: 804-9 117. Matsuura R, Arimitsu T, Kimura T, et al. Effect of oral administration of sodium bicarbonate on surface EMG activity during repeated cycling sprints. Eur J Appl Physiol 2007; 101: 409-17 118. Gaitanos GC, Nevill ME, Brooks S, et al. Repeated bouts of sprint running after induced alkalosis. J Sports Sci 1991; 9: 355-70 119. Vollestad NK. Measurement of human muscle fatigue. J Neurosci Methods 1997; 74: 219-27 120. Dutka TL, Lamb GD. Effect of low cytoplasmic [ATP] on excitation-contraction coupling in fast-twitch muscle fibres of the rat. J Physiol 2004; 560: 451-68 121. Westerblad H, Allen DG, Lannergren J. Muscle fatigue: lactic acid or inorganic phosphate the major cause? News Physiol Sci 2002; 17: 17-21 122. Ross A, Leveritt M, Riek S. Neural influences on sprint running: training adaptations and acute responses. Sports Med 2001; 31: 409-25 123. Billaut F, Basset FA, Falgairette G. Muscle coordination changes during intermittent cycling sprints. Neurosci Lett 2005; 380: 265-9
Sports Med 2011; 41 (8)
Fatigue and Repeated-Sprint Ability
124. Billaut F, Basset FA, Giacomoni M, et al. Effect of highintensity intermittent cycling sprints on neuromuscular activity. Int J Sports Med 2006; 27: 25-30 125. Matsuura R, Ogata H, Yunoki T, et al. Effect of blood lactate concentration and the level of oxygen uptake immediately before a cycling sprint on neuromuscular activation during repeated cycling sprints. J Physiol Anthropol 2006; 25: 267-73 126. Farina D, Merletti R, Enoka RM. The extraction of neural strategies from the surface EMG. J Appl Physiol 2004; 96: 1486-95 127. Pasquet B, Carpentier A, Duchateau J, et al. Muscle fatigue during concentric and eccentric contractions. Muscle Nerve 2000; 23: 1727-35 128. Kinugasa R, Akima H, Ota A, et al. Short-term creatine supplementation does not improve muscle activation or sprint performance in humans. Eur J Appl Physiol 2004; 91: 230-7 129. Missenard O, Mottet D, Perrey S. Factors responsible for force steadiness impairment with fatigue. Muscle Nerve 2009; 40: 1019-32 130. Kibler WB, Safran MR. Musculoskeletal injuries in the young tennis player. Clin. Sports Med 2000; 19: 781-92 131. Amann M, Dempsey JA. Locomotor muscle fatigue modifies central motor drive in healthy humans and imposes a limitation to exercise performance. J Physiol 2008; 586: 161-73 132. Sinoway LI, Hill JM, Pickar JG, et al. Effects of contraction and lactic acid on the discharge of group III muscle afferents in cats. J Neurophysiol 1993; 69: 1053-9 133. Duchateau J, Balestra C, Carpentier A, et al. Reflex regulation during sustained and intermittent submaximal contractions in humans. J Physiol 2002; 541: 959-67 134. Racinais S, Girard O, Micallef JP, et al. Failed excitability of spinal motoneurons induced by prolonged running exercise. J Neurophysiol 2007; 97: 596-603 135. Hunter AM, St Clair Gibson A, Lambert MI, et al. Effects of supramaximal exercise on the electromyographic signal. Br J Sports Med 2003; 37: 296-9 136. Bundle MW, Ernst CL, Bellizzi MJ, et al. A metabolic basis for impaired muscle force production and neuromuscular compensation during sprint cycling. Am J Physiol Regul Integr Comp Physiol 2006; 291: R1457-64 137. Szubski C, Burtscher M, Loscher WN. The effects of shortterm hypoxia on motor cortex excitability and neuromuscular activation. J Appl Physiol 2006; 101: 1673-7 138. Dillon GH, Waldrop TG. In vitro responses of caudal hypothalamic neurons to hypoxia and hypercapnia. Neuroscience 1992; 51: 941-50 139. Zehr PE. Considerations for use of the Hoffmann reflex in exercise studies. Eur J Appl Physiol 2002; 86: 455-68 140. Gandevia SC. Spinal and supraspinal factors in human muscle fatigue. Physiol Rev 2001; 81: 1725-89 141. Meeusen R, Watson P, Hasegawa H, et al. Central fatigue: the serotonin hypothesis and beyond. Sports Med 2006; 36: 881-909 142. Kalmar JM, Cafarelli E. Central excitability does not limit postfatigue voluntary activation of quadriceps femoris. J Appl Physiol 2006; 100: 1757-64
ª 2011 Adis Data Information BV. All rights reserved.
693
143. Sidhu SK, Bentley DJ, Carroll TJ. Locomotor exercise induces long-lasting impairments in the capacity of the human motor cortex to voluntarily activate knee extensor muscles. J Appl Physiol 2009; 106: 556-65 144. Gandevia SC, Petersen N, Butler JE, et al. Impaired response of human motoneurones to corticospinal stimulation after voluntary exercise. J Physiol 1999; 521 (Pt 3): 749-59 145. Petersen NT, Taylor JL, Butler JE, et al. Depression of activity in the corticospinal pathway during human motor behavior after strong voluntary contractions. J Neurosci 2003; 23: 7974-80 146. Bigland-Ritchie B, Johansson R, Lippold OC, et al. Contractile speed and EMG changes during fatigue of sustained maximal voluntary contractions. J Neurophysiol 1983; 50: 313-24 147. Bigland-Ritchie B, Woods JJ. Changes in muscle contractile properties and neural control during human muscular fatigue. Muscle Nerve 1984; 7: 691-9 148. Allen DG, Lamb GD, Westerblad H. Impaired calcium release during fatigue. J Appl Physiol 2008; 104: 296-305 149. Casey A, Constantin-Teodosiu D, Howell S, et al. Metabolic response of type I and II muscle fibers during repeated bouts of maximal exercise in humans. Am. J Physiol 1996; 271: E38-43 150. Wilson GJ, Murphy AJ. The use of isometric tests of muscular function in athletic assessment. Sports Med 1996; 22: 19-37 151. Farley CT, Blickhan R, Saito J, et al. Hopping frequency in humans: a test of how springs set stride frequency in bouncing gaits. J Appl Physiol 1991; 71: 2127-32 152. Chelly SM, Denis C. Leg power and hopping stiffness: relationship with sprint running performance. Med Sci Sports Exerc 2001; 33: 326-33 153. Morin JB, Jeannin T, Chevallier B, et al. Spring-mass model characteristics during sprint running: correlation with performance and fatigue-induced changes. Int J Sports Med 2006; 27: 158-65 154. Girard O, Micallef J-P, Millet GP. Changes in spring-mass model characteristics during repeated running sprints. Eur J Appl Physiol 2011; 111 (1): 125-34 155. Clark RA. The effect of training status on inter-limb joint stiffness regulation during repeated maximal sprints. J Sci Med Sport 2009; 12: 406-10 156. Morris JG, Nevill ME, Williams C. Physiological and metabolic responses of female games and endurance athletes to prolonged, intermittent, high-intensity running at 30 degrees and 16 degrees C ambient temperatures. Eur J Appl Physiol 2000; 81: 84-92 157. Brosnan MJ, Martin DT, Hahn AG, et al. Impaired interval exercise responses in elite female cyclists at moderate simulated altitude. J Appl Physiol 2000; 89: 1819-24 158. Ogawa T, Hayashi K, Ichinose M, et al. Metabolic response during intermittent graded sprint running in moderate hypobaric hypoxia in competitive middle-distance runners. Eur J Appl Physiol 2007; 99: 39-46 159. Gray SR, De Vito G, Nimmo MA, et al. Skeletal muscle ATP turnover and muscle fiber conduction velocity are elevated at higher muscle temperatures during maximal power output development in humans. Am J Physiol Regul Integr Comp Physiol 2006; 290: R376-82
Sports Med 2011; 41 (8)
694
160. Bishop D, Maxwell NS. Effects of active warm up on thermoregulation and intermittent-sprint performance in hot conditions. J Sci Med Sport 2009; 12: 196-204 161. Drust B, Rasmussen P, Mohr M, et al. Elevations in core and muscle temperature impairs repeated sprint performance. Acta Physiol Scand 2005; 183: 181-90 162. Maxwell NS, McKenzie RW, Bishop D. Influence of hypohydration on intermittent sprint performance in the heat. Int J Sports Physiol Perform 2009; 4: 54-67 163. Balsom PD, Gaitanos GC, Ekblom B, et al. Reduced oxygen availability during high intensity intermittent exercise impairs performance. Acta Physiol Scand 1994; 152: 279-85
ª 2011 Adis Data Information BV. All rights reserved.
Girard et al.
164. Hogan MC, Richardson RS, Haseler LJ. Human muscle performance and PCr hydrolysis with varied inspired oxygen fractions: a 31P-MRS study. J Appl Physiol 1999; 86: 1367-73 165. Amann M, Kayser B. Nervous system function during exercise in hypoxia. High Alt Med Biol 2009; 10: 149-64
Correspondence: Dr Olivier Girard, Research and Education Centre, ASPETAR – Qatar Orthopaedic and Sports Medicine Hospital, PO Box 29222, Doha, Qatar. E-mail: [email protected]
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