Rating of Perceived Exertion: A Large Cross-Sectional Study Defining Intensity Levels for Individual Physical Activity Recommendations.
Age
Cardiopulmonary fitness
Duration of exercise
Individualized intensity recommendation
RPE
Rating of perceived exertion
Sex
Type of ergometry
Journal
Sports medicine - open
ISSN: 2199-1170
Titre abrégé: Sports Med Open
Pays: Switzerland
ID NLM: 101662568
Informations de publication
Date de publication:
10 Jun 2024
10 Jun 2024
Historique:
received:
07
02
2024
accepted:
15
05
2024
medline:
10
6
2024
pubmed:
10
6
2024
entrez:
10
6
2024
Statut:
epublish
Résumé
Physical inactivity is a growing risk factor worldwide, therefore getting people into sports is necessary. When prescribing physical activity, it is essential to recommend the correct training intensities. Cardiopulmonary exercise testing (CPX) enables precise determination of individuals' training intensities but is unavailable for a broad population. Therefore, the Borg scale allows individuals to assess perceived exertion and set their intensity easily and cost-efficiently. In order to transfer CPX to rating of perceived exertion (RPE), previous studies investigated RPE on specific physiological anchors, e.g. blood lactate (bLa) concentrations, but representativeness for a broad population is questionable. Some contradictory findings regarding individual factors influencing RPE occur, whereas univariable analysis has been performed so far. Moreover, a multivariable understanding of individual factors influencing RPE is missing. This study aims to determine RPE values at the individual anaerobic threshold (LT2) and defined bLa concentrations in a large cohort and to evaluate individual factors influencing RPE with multivariable analysis. CPX with bicycle or treadmill ergometer of 6311 participants were analyzed in this cross-sectional study. RPE values at bLa concentrations 2 mmol/l, 3 mmol/l, 4 mmol/l, and LT2 (first rise in bLa over baseline + 1.5 mmol/l) were estimated by spline interpolation. Multivariable cumulative ordinal regression models were performed to assess the influence of sex, age, type of ergometry, VO2max, and duration of exercise testing on RPE. Median values [interquartile range (IQR)] of the total population were RPE 13 [11; 14] at 2 mmol/l, RPE 15 [13; 16] at 3 mmol/l, RPE 16 [15; 17] at 4 mmol/l, and RPE 15 [14; 16] at LT2. Main influence of individual factors on RPE were seen especially at 2 mmol/l: male sex (odds ratio (OR) [95%-CI]: 0.65 [0.587; 0.719]), treadmill ergometry (OR 0.754 [0.641; 0.886]), number of stages (OR 1.345 [1.300; 1.394]), age (OR 1.015 [1.012; 1.018]), and VO2max (OR 1.023 [1.015; 1.030]). Number of stages was the only identified influencing factor on RPE at all lactate concentrations/LT2 (3 mmol/l: OR 1.290 [1.244; 1.336]; 4 mmol/l: OR 1.229 [1.187; 1.274]; LT2: OR 1.155 [1.115; 1.197]). Our results suggest RPE ≤ 11 for light intensity, RPE 12-14 for moderate intensity, and RPE 15-17 for vigorous intensity, which slightly differs from the current American College of Sports Medicine (ACSM) recommendations. Additionally, we propose an RPE of 15 delineating heavy and severe intensity domain. Age, sex, type of ergometry, duration of exercise, and cardiopulmonary fitness should be considered when recommending individualized intensities with RPE, primarily at lower intensities. Therefore, this study can be used as a new guideline for prescribing individual RPE values in the clinical practice, predominantly for endurance type exercise.
Sections du résumé
BACKGROUND
BACKGROUND
Physical inactivity is a growing risk factor worldwide, therefore getting people into sports is necessary. When prescribing physical activity, it is essential to recommend the correct training intensities. Cardiopulmonary exercise testing (CPX) enables precise determination of individuals' training intensities but is unavailable for a broad population. Therefore, the Borg scale allows individuals to assess perceived exertion and set their intensity easily and cost-efficiently. In order to transfer CPX to rating of perceived exertion (RPE), previous studies investigated RPE on specific physiological anchors, e.g. blood lactate (bLa) concentrations, but representativeness for a broad population is questionable. Some contradictory findings regarding individual factors influencing RPE occur, whereas univariable analysis has been performed so far. Moreover, a multivariable understanding of individual factors influencing RPE is missing. This study aims to determine RPE values at the individual anaerobic threshold (LT2) and defined bLa concentrations in a large cohort and to evaluate individual factors influencing RPE with multivariable analysis.
METHODS
METHODS
CPX with bicycle or treadmill ergometer of 6311 participants were analyzed in this cross-sectional study. RPE values at bLa concentrations 2 mmol/l, 3 mmol/l, 4 mmol/l, and LT2 (first rise in bLa over baseline + 1.5 mmol/l) were estimated by spline interpolation. Multivariable cumulative ordinal regression models were performed to assess the influence of sex, age, type of ergometry, VO2max, and duration of exercise testing on RPE.
RESULTS
RESULTS
Median values [interquartile range (IQR)] of the total population were RPE 13 [11; 14] at 2 mmol/l, RPE 15 [13; 16] at 3 mmol/l, RPE 16 [15; 17] at 4 mmol/l, and RPE 15 [14; 16] at LT2. Main influence of individual factors on RPE were seen especially at 2 mmol/l: male sex (odds ratio (OR) [95%-CI]: 0.65 [0.587; 0.719]), treadmill ergometry (OR 0.754 [0.641; 0.886]), number of stages (OR 1.345 [1.300; 1.394]), age (OR 1.015 [1.012; 1.018]), and VO2max (OR 1.023 [1.015; 1.030]). Number of stages was the only identified influencing factor on RPE at all lactate concentrations/LT2 (3 mmol/l: OR 1.290 [1.244; 1.336]; 4 mmol/l: OR 1.229 [1.187; 1.274]; LT2: OR 1.155 [1.115; 1.197]).
CONCLUSION
CONCLUSIONS
Our results suggest RPE ≤ 11 for light intensity, RPE 12-14 for moderate intensity, and RPE 15-17 for vigorous intensity, which slightly differs from the current American College of Sports Medicine (ACSM) recommendations. Additionally, we propose an RPE of 15 delineating heavy and severe intensity domain. Age, sex, type of ergometry, duration of exercise, and cardiopulmonary fitness should be considered when recommending individualized intensities with RPE, primarily at lower intensities. Therefore, this study can be used as a new guideline for prescribing individual RPE values in the clinical practice, predominantly for endurance type exercise.
Identifiants
pubmed: 38856875
doi: 10.1186/s40798-024-00729-1
pii: 10.1186/s40798-024-00729-1
doi:
Types de publication
Journal Article
Langues
eng
Pagination
71Informations de copyright
© 2024. The Author(s).
Références
Paffenbarger RSJ, Hyde RT, et al. The association of changes in physical-activity level and other lifestyle characteristics with mortality among men. N Engl J Med. 1993;328(8):538–45. https://doi.org/10.1056/nejm199302253280804 .
doi: 10.1056/nejm199302253280804
pubmed: 8426621
Knowler WC, Barrett-Connor E, et al. Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. N Engl J Med. 2002;346(6):393–403. https://doi.org/10.1056/NEJMoa012512 .
doi: 10.1056/NEJMoa012512
pubmed: 11832527
Kyu HH, Bachman VF, et al. Physical activity and risk of breast cancer, colon cancer, diabetes, ischemic heart disease, and ischemic stroke events: systematic review and dose-response meta-analysis for the Global Burden of Disease Study 2013. BMJ. 2016;354: i3857. https://doi.org/10.1136/bmj.i3857 .
doi: 10.1136/bmj.i3857
pubmed: 27510511
pmcid: 4979358
Hussain N, Gersh BJ, et al. Impact of cardiorespiratory fitness on frequency of atrial fibrillation, stroke, and all-cause mortality. Am J Cardiol. 2018;121(1):41–9. https://doi.org/10.1016/j.amjcard.2017.09.021 .
doi: 10.1016/j.amjcard.2017.09.021
pubmed: 29221502
Laukkanen JA, Zaccardi F, et al. Long-term change in cardiorespiratory fitness and all-cause mortality: a population-based follow-up study. Mayo Clin Proc. 2016;91(9):1183–8. https://doi.org/10.1016/j.mayocp.2016.05.014 .
doi: 10.1016/j.mayocp.2016.05.014
pubmed: 27444976
Myers J, Prakash M, et al. Exercise capacity and mortality among men referred for exercise testing. N Engl J Med. 2002;346(11):793–801. https://doi.org/10.1056/NEJMoa011858 .
doi: 10.1056/NEJMoa011858
pubmed: 11893790
Centers for Disease Control and Prevention (CDC). Behavioral risk factor surveillance system survey data. Atlanta: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention; 2019.
Medicine ACoS, Liguori G, et al. ACSM’s guidelines for exercise testing and prescription. 11th ed. Wolters Kluwer; 2021.
Nelson ME, Rejeski WJ, et al. Physical activity and public health in older adults: recommendation from the American College of Sports Medicine and the American Heart Association. Circulation. 2007;116(9):1094–105. https://doi.org/10.1161/CIRCULATIONAHA.107.185650 .
doi: 10.1161/CIRCULATIONAHA.107.185650
pubmed: 17671236
Smith AE, Eston R, et al. Patterning of physiological and affective responses in older active adults during a maximal graded exercise test and self-selected exercise. Eur J Appl Physiol. 2015;115(9):1855–66. https://doi.org/10.1007/s00421-015-3167-z .
doi: 10.1007/s00421-015-3167-z
pubmed: 25876526
Jamnick NA, Pettitt RW, et al. An examination and critique of current methods to determine exercise intensity. Sports Med. 2020;50(10):1729–56. https://doi.org/10.1007/s40279-020-01322-8 .
doi: 10.1007/s40279-020-01322-8
pubmed: 32729096
Mann T, Lamberts RP, Lambert MI. Methods of prescribing relative exercise intensity: physiological and practical considerations. Sports Med. 2013;43(7):613–25. https://doi.org/10.1007/s40279-013-0045-x .
doi: 10.1007/s40279-013-0045-x
pubmed: 23620244
Gaskill SE, Serfass RC, et al. Responses to training in cross-country skiers. Med Sci Sports Exerc. 1999;31(8):1211–7. https://doi.org/10.1097/00005768-199908000-00020 .
doi: 10.1097/00005768-199908000-00020
pubmed: 10449026
Seiler KS, Kjerland G. Quantifying training intensity distribution in elite endurance athletes: Is there evidence for an “optimal” distribution? Scand J Med Sci Sports. 2006;16(1):49–56. https://doi.org/10.1111/j.1600-0838.2004.00418.x .
doi: 10.1111/j.1600-0838.2004.00418.x
pubmed: 16430681
Seiler S. What is best practice for training intensity and duration distribution in endurance athletes? Int J Sports Physiol Perform. 2010;5(3):276–91. https://doi.org/10.1123/ijspp.5.3.276 .
doi: 10.1123/ijspp.5.3.276
pubmed: 20861519
Sjodin B, Svedenhag J. Applied physiology of marathon running. Sports Med. 1985;2(2):83–99. https://doi.org/10.2165/00007256-198502020-00002 .
doi: 10.2165/00007256-198502020-00002
pubmed: 3890068
Stöggl TL, Sperlich B. The training intensity distribution among well-trained and elite endurance athletes. Front Physiol. 2015. https://doi.org/10.3389/fphys.2015.00295 .
doi: 10.3389/fphys.2015.00295
pubmed: 26578968
pmcid: 4621419
Dickhuth H-H, Huonker M, et al., editors. Individual Anaerobic Threshold for Evaluation of Competitive Athletes and Patients with Left Ventricular Dysfunction. Berlin, Heidelberg: Springer Berlin Heidelberg; 1991. https://doi.org/10.1007/978-3-642-76442-4_26
Dickhuth HH, Yin L, et al. Ventilatory, lactate-derived and catecholamine thresholds during incremental treadmill running: relationship and reproducibility. Int J Sports Med. 1999;20(2):122–7. https://doi.org/10.1055/s-2007-971105 .
doi: 10.1055/s-2007-971105
pubmed: 10190774
Stegmann H, Kindermann W, Schnabel A. Lactate kinetics and individual anaerobic threshold. Int J Sports Med. 1981;2(3):160–5. https://doi.org/10.1055/s-2008-1034604 .
doi: 10.1055/s-2008-1034604
pubmed: 7333753
Binder RK, Wonisch M, et al. Methodological approach to the first and second lactate threshold in incremental cardiopulmonary exercise testing. Eur J Cardiovasc Prev Rehabil. 2008;15(6):726–34. https://doi.org/10.1097/HJR.0b013e328304fed4 .
doi: 10.1097/HJR.0b013e328304fed4
pubmed: 19050438
Kindermann W, Simon G, Keul J. The significance of the aerobic-anaerobic transition for the determination of work load intensities during endurance training. Eur J Appl Physiol Occup Physiol. 1979;42(1):25–34. https://doi.org/10.1007/BF00421101 .
doi: 10.1007/BF00421101
pubmed: 499194
Sjodin B, Jacobs I. Onset of blood lactate accumulation and marathon running performance. Int J Sports Med. 1981;2(1):23–6. https://doi.org/10.1055/s-2008-1034579 .
doi: 10.1055/s-2008-1034579
pubmed: 7333732
Weltman A, Seip R, et al. Prediction of lactate threshold (LT) and fixed blood lactate concentrations (FBLC) from 3200-m running performance in women. Int J Sports Med. 1990;11(5):373–8. https://doi.org/10.1055/s-2007-1024821 .
doi: 10.1055/s-2007-1024821
pubmed: 2262230
Beneke R, Leithauser RM, Ochentel O. Blood lactate diagnostics in exercise testing and training. Int J Sports Physiol Perform. 2011;6(1):8–24. https://doi.org/10.1123/ijspp.6.1.8 .
doi: 10.1123/ijspp.6.1.8
pubmed: 21487146
Held T, Marti B. Substantial influence of level of endurance capacity on the association of perceived exertion with blood lactate accumulation. Int J Sports Med. 1999;20(1):34–9. https://doi.org/10.1055/s-2007-971088 .
doi: 10.1055/s-2007-971088
pubmed: 10090459
Heck H, Mader A, et al. Justification of the 4-mmol/l lactate threshold. Int J Sports Med. 1985;6(3):117–30. https://doi.org/10.1055/s-2008-1025824 .
doi: 10.1055/s-2008-1025824
pubmed: 4030186
Faude O, Kindermann W, Meyer T. Lactate threshold concepts: How valid are they? Sports Med. 2009;39(6):469–90. https://doi.org/10.2165/00007256-200939060-00003 .
doi: 10.2165/00007256-200939060-00003
pubmed: 19453206
Skinner JS, McLellan TM. The transition from aerobic to anaerobic metabolism. Res Q Exerc Sport. 1980;51(1):234–48. https://doi.org/10.1080/02701367.1980.10609285 .
doi: 10.1080/02701367.1980.10609285
pubmed: 7394286
Eston R. Use of ratings of perceived exertion in sports. Int J Sports Physiol Perform. 2012;7(2):175–82. https://doi.org/10.1123/ijspp.7.2.175 .
doi: 10.1123/ijspp.7.2.175
pubmed: 22634967
Foster C, Porcari J, et al. Exercise prescription when there is no exercise test: the talk test. Kinesiology. 2018;50:33–48.
Ekkekakis P, Parfitt G, Petruzzello SJ. The pleasure and displeasure people feel when they exercise at different intensities: decennial update and progress towards a tripartite rationale for exercise intensity prescription. Sports Med. 2011;41(8):641–71. https://doi.org/10.2165/11590680-000000000-00000 .
doi: 10.2165/11590680-000000000-00000
pubmed: 21780850
Bok D, Rakovac M, Foster C. An examination and critique of subjective methods to determine exercise intensity: the talk test, feeling scale, and rating of perceived exertion. Sports Med. 2022;52(9):2085–109. https://doi.org/10.1007/s40279-022-01690-3 .
doi: 10.1007/s40279-022-01690-3
pubmed: 35507232
Borg GA. Psychophysical bases of perceived exertion. Med Sci Sports Exerc. 1982;14(5):377–81. https://doi.org/10.1249/00005768-198205000-00012 .
doi: 10.1249/00005768-198205000-00012
pubmed: 7154893
Noble BJ, Borg GA, et al. A category-ratio perceived exertion scale: relationship to blood and muscle lactates and heart rate. Med Sci Sports Exerc. 1983;15(6):523–8. https://doi.org/10.1249/00005768-198315060-00015 .
doi: 10.1249/00005768-198315060-00015
pubmed: 6656563
Mays RJ, Goss FL, et al. Validation of adult omni perceived exertion scales for elliptical ergometry. Percept Mot Skills. 2010;111(3):848–62. https://doi.org/10.2466/05.06.Pms.111.6.848-862 .
doi: 10.2466/05.06.Pms.111.6.848-862
pubmed: 21319623
pmcid: 3541829
Eston RG, Davies BL, Williams JG. Use of perceived effort ratings to control exercise intensity in young healthy adults. Eur J Appl Physiol Occup Physiol. 1987;56(2):222–4. https://doi.org/10.1007/bf00640648 .
doi: 10.1007/bf00640648
pubmed: 3569229
Garnacho-Castano MV, Dominguez R, et al. Exercise prescription using the borg rating of perceived exertion to improve fitness. Int J Sports Med. 2018;39(2):115–23. https://doi.org/10.1055/s-0043-120761 .
doi: 10.1055/s-0043-120761
pubmed: 29190852
Lins-Filho Ode L, Robertson RJ, et al. Effects of exercise intensity on rating of perceived exertion during a multiple-set resistance exercise session. J Strength Cond Res. 2012;26(2):466–72. https://doi.org/10.1519/JSC.0b013e31822602fa .
doi: 10.1519/JSC.0b013e31822602fa
pubmed: 22233796
Dantas JL, Doria C, et al. Determination of blood lactate training zone boundaries with rating of perceived exertion in runners. J Strength Cond Res. 2015;29(2):315–20. https://doi.org/10.1519/jsc.0000000000000639 .
doi: 10.1519/jsc.0000000000000639
pubmed: 25187249
Santos GAD, Numata-Filho ES, et al. Anaerobic threshold determination in cycle ergometer from rating of perceived exertion. J Strength Cond Res. 2022;36(5):1277–81. https://doi.org/10.1519/jsc.0000000000003627 .
doi: 10.1519/jsc.0000000000003627
pubmed: 32412967
da Silva JKF, Sotomaior BB, et al. Predicting lactate threshold with rate of perceived exertion in young competitive male swimmers. Percept Mot Skills. 2021;128(4):1530–48. https://doi.org/10.1177/00315125211005227 .
doi: 10.1177/00315125211005227
pubmed: 33818161
Parfitt G, Evans H, Eston R. Perceptually regulated training at RPE13 is pleasant and improves physical health. Med Sci Sports Exerc. 2012;44(8):1613–8. https://doi.org/10.1249/MSS.0b013e31824d266e .
doi: 10.1249/MSS.0b013e31824d266e
pubmed: 22330020
Borg G. Perceived exertion as an indicator of somatic stress. Scand J Rehabil Med. 1970;2(2):92–8. https://doi.org/10.2340/1650197719702239298 .
doi: 10.2340/1650197719702239298
pubmed: 5523831
Scherr J, Wolfarth B, et al. Associations between Borg’s rating of perceived exertion and physiological measures of exercise intensity. Eur J Appl Physiol. 2013;113(1):147–55. https://doi.org/10.1007/s00421-012-2421-x .
doi: 10.1007/s00421-012-2421-x
pubmed: 22615009
Hutchinson MJ, Kouwijzer I, et al. Comparison of two Borg exertion scales for monitoring exercise intensity in able-bodied participants, and those with paraplegia and tetraplegia. Spinal Cord. 2021;59(11):1162–9. https://doi.org/10.1038/s41393-021-00642-4 .
doi: 10.1038/s41393-021-00642-4
pubmed: 34040150
pmcid: 8560635
Abe D, Yoshida T, et al. Relationship between perceived exertion and blood lactate concentrations during incremental running test in young females. BMC Sports Sci Med Rehabil. 2015;7:5. https://doi.org/10.1186/2052-1847-7-5 .
doi: 10.1186/2052-1847-7-5
pubmed: 25973209
pmcid: 4429818
Fabre N, Mourot L, et al. A novel approach for lactate threshold assessment based on rating of perceived exertion. Int J Sports Physiol Perform. 2013;8(3):263–70. https://doi.org/10.1123/ijspp.8.3.263 .
doi: 10.1123/ijspp.8.3.263
pubmed: 22954509
Irving BA, Rutkowski J, et al. Comparison of Borg- and OMNI-RPE as markers of the blood lactate response to exercise. Med Sci Sports Exerc. 2006;38(7):1348–52. https://doi.org/10.1249/01.mss.0000227322.61964.d2 .
doi: 10.1249/01.mss.0000227322.61964.d2
pubmed: 16826034
Hetzler RK, Seip RL, et al. Effect of exercise modality on ratings of perceived exertion at various lactate concentrations. Med Sci Sports Exerc. 1991;23(1):88–92.
doi: 10.1249/00005768-199101000-00014
pubmed: 1997817
Demello JJ, Cureton KJ, et al. Ratings of perceived exertion at the lactate threshold in trained and untrained men and women. Med Sci Sports Exerc. 1987;19(4):354–62.
doi: 10.1249/00005768-198708000-00006
pubmed: 3657484
Rynders CA, Angadi SS, et al. Oxygen uptake and ratings of perceived exertion at the lactate threshold and maximal fat oxidation rate in untrained adults. Eur J Appl Physiol. 2011;111(9):2063–8. https://doi.org/10.1007/s00421-010-1821-z .
doi: 10.1007/s00421-010-1821-z
pubmed: 21259025
pmcid: 3995406
Dias KJ, Mungenast A, et al. Differences in rate of perceived exertion and workload intensity in males and females during submaximal arm and leg ergometry. Int J Exerc Sci. 2022;15(4):1222–35.
pubmed: 36620191
pmcid: 9799232
Robertson RJ, Moyna NM, et al. Gender comparison of RPE at absolute and relative physiological criteria. Med Sci Sports Exerc. 2000;32(12):2120–9. https://doi.org/10.1097/00005768-200012000-00024 .
doi: 10.1097/00005768-200012000-00024
pubmed: 11128861
Prettin S, Roecker K, et al. Changes in blood lactate concentrations during different treadmill exercise test protocols. J Sports Med Phys Fitness. 2011;51(2):179–84.
pubmed: 21681150
Marcora S, Goldstein E. Encyclopedia of perception; 2010. https://doi.org/10.4135/9781412972000.n119
Kokkinos P, Kaminsky LA, et al. A new generalized cycle ergometry equation for predicting maximal oxygen uptake: the fitness registry and the importance of exercise national database (FRIEND). Eur J Prev Cardiol. 2018;25(10):1077–82. https://doi.org/10.1177/2047487318772667 .
doi: 10.1177/2047487318772667
pubmed: 29692203
Kokkinos P, Kaminsky LA, et al. New generalized equation for predicting maximal oxygen uptake (from the fitness registry and the importance of exercise national database). Am J Cardiol. 2017;120(4):688–92. https://doi.org/10.1016/j.amjcard.2017.05.037 .
doi: 10.1016/j.amjcard.2017.05.037
pubmed: 28676154
Roecker K, Niess AM, et al. Heart rate prescriptions from performance and anthropometrical characteristics. Med Sci Sports Exerc. 2002;34(5):881–7. https://doi.org/10.1097/00005768-200205000-00024 .
doi: 10.1097/00005768-200205000-00024
pubmed: 11984310
Roecker K, Mayer F, et al. Increase characteristics of the cumulated excess-CO
doi: 10.1055/s-2000-3836
pubmed: 10961517
Beaver WL, Wasserman K, Whipp BJ. Improved detection of lactate threshold during exercise using a log-log transformation. J Appl Physiol. 1985;59(6):1936–40. https://doi.org/10.1152/jappl.1985.59.6.1936 .
doi: 10.1152/jappl.1985.59.6.1936
pubmed: 4077801
Fritsch FN, Carlson RE. Monotone piecewise cubic interpolation. SIAM J Numer Anal. 1980;17(2):238–46.
doi: 10.1137/0717021
Eurostat. Population structure indicators at national level. Luxembourg: Eurostat, The Statistical Office of the European Union; 2022.
European Health Interview Survey (EHIS). Luxembourg: Eurostat, The Statistical Office of the European Union; 2019.
Hampson DB, St Clair Gibson A, et al. The influence of sensory cues on the perception of exertion during exercise and central regulation of exercise performance. Sports Med. 2001;31(13):935–52. https://doi.org/10.2165/00007256-200131130-00004 .
doi: 10.2165/00007256-200131130-00004
pubmed: 11708402
Bergevin M, Steele J, et al. Pharmacological blockade of muscle afferents and perception of effort: a systematic review with meta-analysis. Sports Med. 2023;53(2):415–35. https://doi.org/10.1007/s40279-022-01762-4 .
doi: 10.1007/s40279-022-01762-4
pubmed: 36318384
McCloskey DI. Corollary Discharges: Motor Commands and Perception. Comprehensive Physiology. p. 1415–47 https://doi.org/10.1002/cphy.cp010232 .
de Morree HM, Klein C, Marcora SM. Perception of effort reflects central motor command during movement execution. Psychophysiology. 2012;49(9):1242–53. https://doi.org/10.1111/j.1469-8986.2012.01399.x .
doi: 10.1111/j.1469-8986.2012.01399.x
pubmed: 22725828
Weavil JC, Amann M. Corticospinal excitability during fatiguing whole body exercise. Prog Brain Res. 2018;240:219–46. https://doi.org/10.1016/bs.pbr.2018.07.011 .
doi: 10.1016/bs.pbr.2018.07.011
pubmed: 30390833
pmcid: 6363483
Rapp D, Scharhag J, et al. Reference values for peak oxygen uptake: cross-sectional analysis of cycle ergometry-based cardiopulmonary exercise tests of 10,090 adult German volunteers from the prevention first registry. BMJ Open. 2018;8(3): e018697. https://doi.org/10.1136/bmjopen-2017-018697 .
doi: 10.1136/bmjopen-2017-018697
pubmed: 29506981
pmcid: 5855221
Ogawa T, Spina RJ, et al. Effects of aging, sex, and physical training on cardiovascular responses to exercise. Circulation. 1992;86(2):494–503. https://doi.org/10.1161/01.cir.86.2.494 .
doi: 10.1161/01.cir.86.2.494
pubmed: 1638717
Christou DD, Seals DR. Decreased maximal heart rate with aging is related to reduced {beta}-adrenergic responsiveness but is largely explained by a reduction in intrinsic heart rate. J Appl Physiol. 2008;105(1):24–9. https://doi.org/10.1152/japplphysiol.90401.2008 .
doi: 10.1152/japplphysiol.90401.2008
pubmed: 18483165
pmcid: 2494835
Tanaka H, Monahan KD, Seals DR. Age-predicted maximal heart rate revisited. J Am Coll Cardiol. 2001;37(1):153–6. https://doi.org/10.1016/s0735-1097(00)01054-8 .
doi: 10.1016/s0735-1097(00)01054-8
pubmed: 11153730
Konopka AR, Sreekumaran NK. Mitochondrial and skeletal muscle health with advancing age. Mol Cell Endocrinol. 2013;379(1–2):19–29. https://doi.org/10.1016/j.mce.2013.05.008 .
doi: 10.1016/j.mce.2013.05.008
pubmed: 23684888
pmcid: 3788080
Seo DY, Lee SR, et al. Age-related changes in skeletal muscle mitochondria: the role of exercise. Integr Med Res. 2016;5(3):182–6. https://doi.org/10.1016/j.imr.2016.07.003 .
doi: 10.1016/j.imr.2016.07.003
pubmed: 28462116
pmcid: 5390452
Taylor BJ, Johnson BD. The pulmonary circulation and exercise responses in the elderly. Semin Respir Crit Care Med. 2010;31(5):528–38. https://doi.org/10.1055/s-0030-1265894 .
doi: 10.1055/s-0030-1265894
pubmed: 20941654
pmcid: 3919503
Smith JR, Kurti SP, et al. Expiratory flow limitation and operating lung volumes during exercise in older and younger adults. Respir Physiol Neurobiol. 2017;240:26–31. https://doi.org/10.1016/j.resp.2016.12.016 .
doi: 10.1016/j.resp.2016.12.016
pubmed: 28232071
Shah M, Suresh S, et al. Age-related changes in responsiveness to non-invasive brain stimulation neuroplasticity paradigms: a systematic review with meta-analysis. Clin Neurophysiol. 2024;162:53–67. https://doi.org/10.1016/j.clinph.2024.03.002 .
doi: 10.1016/j.clinph.2024.03.002
pubmed: 38579515
Stapleton JM, Poirier MP, et al. At what level of heat load are age-related impairments in the ability to dissipate heat evident in females? PLoS ONE. 2015;10(3): e0119079. https://doi.org/10.1371/journal.pone.0119079 .
doi: 10.1371/journal.pone.0119079
pubmed: 25790024
pmcid: 4366400
Armstrong CG, Kenney WL. Effects of age and acclimation on responses to passive heat exposure. J Appl Physiol. 1993;75(5):2162–7. https://doi.org/10.1152/jappl.1993.75.5.2162 .
doi: 10.1152/jappl.1993.75.5.2162
pubmed: 8307874
Gagnon D, Romero SA, et al. Volume loading augments cutaneous vasodilatation and cardiac output of heat stressed older adults. J Physiol. 2017;595(20):6489–98. https://doi.org/10.1113/jp274742 .
doi: 10.1113/jp274742
pubmed: 28833129
pmcid: 5638885
Székely M, Garai J. Thermoregulation and age. In: Romanovsky AA, editor. Handbook of clinical neurology, vol. 156. Elsevier; 2018. p. 377–95.
Racinais S, Oksa J. Temperature and neuromuscular function. Scand J Med Sci Sports. 2010;20(Suppl 3):1–18. https://doi.org/10.1111/j.1600-0838.2010.01204.x .
doi: 10.1111/j.1600-0838.2010.01204.x
pubmed: 21029186
Cheung SS. Neuromuscular response to exercise heat stress. In: Marino FE, editor. Thermoregulation and human performance: physiological and biological aspects, vol. 53. S.Karger AG; 2008.
doi: 10.1159/000151549
Bevan A, Vidoni E, Watts A. Rate of perceived exertion and cardiorespiratory fitness in older adults with and without Alzheimer’s disease. Int J Exerc Sci. 2020;13(3):18–35.
pubmed: 32148626
pmcid: 7039494
Hausdorff JM, Levy BR, Wei JY. The power of ageism on physical function of older persons: reversibility of age-related gait changes. J Am Geriatr Soc. 1999;47(11):1346–9. https://doi.org/10.1111/j.1532-5415.1999.tb07437.x .
doi: 10.1111/j.1532-5415.1999.tb07437.x
pubmed: 10573445
Breda AI, Watts AS. Expectations Regarding Aging, Physical Activity, and Physical Function in Older Adults. Gerontol Geriatr Med. 2017;3:2333721417702350. https://doi.org/10.1177/2333721417702350 .
doi: 10.1177/2333721417702350
pubmed: 28491915
pmcid: 5406123
Levy B. Stereotype Embodiment: A Psychosocial Approach to Aging. Curr Dir Psychol Sci. 2009;18(6):332–6. https://doi.org/10.1111/j.1467-8721.2009.01662.x .
doi: 10.1111/j.1467-8721.2009.01662.x
pubmed: 20802838
pmcid: 2927354
Fagard R, Bielen E, Amery A. Heritability of aerobic power and anaerobic energy generation during exercise. J Appl Physiol. 1991;70(1):357–62. https://doi.org/10.1152/jappl.1991.70.1.357 .
doi: 10.1152/jappl.1991.70.1.357
pubmed: 2010392
Bouchard C, Sarzynski MA, et al. Genomic predictors of the maximal O
Hellsten Y, Nyberg M. Cardiovascular adaptations to exercise training. Compr Physiol. 2015;6(1):1–32. https://doi.org/10.1002/cphy.c140080 .
doi: 10.1002/cphy.c140080
pubmed: 26756625
Holloszy JO. Regulation by exercise of skeletal muscle content of mitochondria and GLUT4. J Physiol Pharmacol. 2008;59(Suppl 7):5–18.
pubmed: 19258654
Rivera-Brown AM, Frontera WR. Principles of exercise physiology: responses to acute exercise and long-term adaptations to training. Pm r. 2012;4(11):797–804. https://doi.org/10.1016/j.pmrj.2012.10.007 .
doi: 10.1016/j.pmrj.2012.10.007
pubmed: 23174541
Skinner JS, Jaskólski A, et al. Age, sex, race, initial fitness, and response to training: the HERITAGE Family Study. J Appl Physiol. 2001;90(5):1770–6. https://doi.org/10.1152/jappl.2001.90.5.1770 .
doi: 10.1152/jappl.2001.90.5.1770
pubmed: 11299267
Bacon AP, Carter RE, et al. VO2max trainability and high intensity interval training in humans: a meta-analysis. PLoS ONE. 2013;8(9): e73182. https://doi.org/10.1371/journal.pone.0073182 .
doi: 10.1371/journal.pone.0073182
pubmed: 24066036
pmcid: 3774727
Lundsgaard AM, Kiens B. Gender differences in skeletal muscle substrate metabolism - molecular mechanisms and insulin sensitivity. Front Endocrinol. 2014;5:195. https://doi.org/10.3389/fendo.2014.00195 .
doi: 10.3389/fendo.2014.00195
Besson T, Macchi R, et al. Sex differences in endurance running. Sports Med. 2022;52(6):1235–57. https://doi.org/10.1007/s40279-022-01651-w .
doi: 10.1007/s40279-022-01651-w
pubmed: 35122632
Tarnopolsky MA. Sex differences in exercise metabolism and the role of 17-beta estradiol. Med Sci Sports Exerc. 2008;40(4):648–54. https://doi.org/10.1249/MSS.0b013e31816212ff .
doi: 10.1249/MSS.0b013e31816212ff
pubmed: 18317381
Carter SL, Rennie C, Tarnopolsky MA. Substrate utilization during endurance exercise in men and women after endurance training. Am J Physiol Endocrinol Metab. 2001;280(6):E898-907. https://doi.org/10.1152/ajpendo.2001.280.6.E898 .
doi: 10.1152/ajpendo.2001.280.6.E898
pubmed: 11350771
Hunter SK. Sex differences in human fatigability: mechanisms and insight to physiological responses. Acta Physiol. 2014;210(4):768–89. https://doi.org/10.1111/apha.12234 .
doi: 10.1111/apha.12234
Delp M, Chesbro GA, et al. Higher rating of perceived exertion and lower perceived recovery following a graded exercise test during menses compared to non-bleeding days in untrained females. Front Physiol. 2023;14:1297242. https://doi.org/10.3389/fphys.2023.1297242 .
doi: 10.3389/fphys.2023.1297242
pubmed: 38274043
Hermansen L, Ekblom B, Saltin B. Cardiac output during submaximal and maximal treadmill and bicycle exercise. J Appl Physiol. 1970;29(1):82–6. https://doi.org/10.1152/jappl.1970.29.1.82 .
doi: 10.1152/jappl.1970.29.1.82
pubmed: 4912876
Matsui H, Kitamura K, Miyamura M. Oxygen uptake and blood flow of the lower limb in maximal treadmill and bicycle exercise. Eur J Appl Physiol Occup Physiol. 1978;40(1):57–62. https://doi.org/10.1007/bf00420989 .
doi: 10.1007/bf00420989
pubmed: 729570
Millet GP, Vleck VE, Bentley DJ. Physiological differences between cycling and running: lessons from triathletes. Sports Med. 2009;39(3):179–206. https://doi.org/10.2165/00007256-200939030-00002 .
doi: 10.2165/00007256-200939030-00002
pubmed: 19290675
Bijker KE, de Groot G, Hollander AP. Differences in leg muscle activity during running and cycling in humans. Eur J Appl Physiol. 2002;87(6):556–61. https://doi.org/10.1007/s00421-002-0663-8 .
doi: 10.1007/s00421-002-0663-8
pubmed: 12355196
Giandolini M, Vernillo G, et al. Fatigue associated with prolonged graded running. Eur J Appl Physiol. 2016;116(10):1859–73. https://doi.org/10.1007/s00421-016-3437-4 .
doi: 10.1007/s00421-016-3437-4
pubmed: 27456477
Millet GY. Can neuromuscular fatigue explain running strategies and performance in ultra-marathons?: The flush model. Sports Med. 2011;41(6):489–506. https://doi.org/10.2165/11588760-000000000-00000 .
doi: 10.2165/11588760-000000000-00000
pubmed: 21615190
Jesus RS, Batista RÉS, et al. Exercise duration affects session ratings of perceived exertion as a function of exercise intensity. Percept Mot Skills. 2021;128(4):1730–46. https://doi.org/10.1177/00315125211018445 .
doi: 10.1177/00315125211018445
pubmed: 34039119