Resistance training and exercise tolerance during high-intensity exercise: moving beyond just running economy and muscle strength.

Abstract

ViewpointResistance training and exercise tolerance during high-intensity exercise: moving beyond just running economy and muscle strengthBenedito Sérgio Denadai and Camila Coelho GrecoBenedito Sérgio DenadaiHuman Performance Laboratory, Paulista State University, Rio Claro, SP, Brazil and Camila Coelho GrecoHuman Performance Laboratory, Paulista State University, Rio Claro, SP, BrazilPublished Online:26 Feb 2018https://doi.org/10.1152/japplphysiol.00800.2017This is the final version - click for previous versionMoreSectionsPDF (70 KB)Download PDF ToolsExport citationAdd to favoritesGet permissionsTrack citations ShareShare onFacebookTwitterLinkedInWeChat The critical power [(CP) the asymptote of the power/time hyperbola] and its equivalent for running [i.e., critical velocity (CV)] are the lower boundaries of the severe-intensity domain, within which any exercise intensity performed to task failure leads to the attainment of V̇o2max (26). The curvature constant of this hyperbola (W′) and its equivalent for running (D′) represent the total amount of work/distance that can be performed above CP/CV before exhaustion occurs (17). Indeed, different experimental designs have confirmed that the size of the W′ remains constant regardless of its rate of expenditure, with task failure coinciding with invariable muscle metabolic milieu (PCr and pH) and accumulation of fatigue-related metabolites (i.e., Pi, H+) (21, 26). Thus, for any exercise intensity performed within the severe-intensity domain, task failure is coincident with complete utilization of W′, V̇o2max attainment, and similar peripheral fatigue (6, 12). In this scenario, W′ seems to be mechanistically determined by some specific levels of fatigue developed during exercise supra CP (9). There is some evidence that resistance training performed by untrained individuals during short-term periods (6–8 wk) has a positive influence on W′. Bishop and Jenkins (5) and Sawyer et al. (32) showed that resistance training improved W′ (~35% and ~40–60%, respectively), whereas CP and V̇o2max remained unchanged. Moreover, Sawyer et al. (32) demonstrated that the changes in W′ were positively correlated (r = 0.46–0.96) with changes in exercise tolerance during constant-work rate cycling exercise (CWR) within severe intensity domain after resistance training. However, the physiological mechanisms for the W′ improvements after resistance training remain elusive. Thus our goal is to shed light on the effects of resistance training on W′, which warrants further insight into the physiological mechanisms underlying exercise tolerance within the severe-domain for different populations.Resistance training and endurance running performance.Traditionally, submaximal endurance training and high-intensity interval training have been used to improve both endurance running performance and the key parameters of aerobic fitness (e.g., V̇o2max and running economy) of trained runners (15). Alternatively, some studies have shown that explosive or heavy weight training added to regular endurance training (i.e., concurrent training) enhances both muscle strength and endurance running performance after short to medium training periods (4–6 wk) (20, 36). Indeed, previous systematic reviews have provided evidence that concurrent training has a positive effect on middle- and long-distance performance (4). These beneficial effects seem to be independent of performance level and sport discipline category (i.e., running, cycling, cross-country skiing, and swimming) (4). Berryman et al. (4) suggested that concurrent training enhances middle- and long-distance performance, mainly by improving energy cost of locomotion and neuromuscular parameters (i.e., maximal power and maximal strength). Accordingly, Denadai et al. (16) showed that explosive training and heavy weight training have similar positive effects on running economy (RE) of endurance athletes after a short to medium training period, independently of training status. Moreover, Paavolainen et al. (29) found that changes in the 5-km time trial performance after 9 wk of concurrent training was correlated with the changes in RE (r = −0.54).However, it is unlikely that enhanced RE plays a central role on the improvement of middle-distance running performance after concurrent training period. First, randomized controlled trials performed in endurance runners challenge the actual contribution of RE to explain the changes of middle-distance running performance (3, 33). Sedano et al. (33) have assessed the effects of different concurrent training (i.e., explosive strength training vs. endurance-strength training) on middle-distance running performance (3-km time trial) in highly trained runners. RE was increased in all concurrent training programs, whereas time trial in a 3-km track running test was significantly improved only after explosive strength training. In line with these data, Berryman et al. (3) showed that plyometric training induced a larger decrease of the energy cost of running than concentric resistance training, whereas it remained unchanged in control group (i.e., endurance training). However, all groups showed similar improvements in middle-distance running performance (3-km time trial) after the experimental period. Thus it seems that modifications in RE are not necessarily associated with improvements in middle-distance running performance after a concurrent training period. Second, studies using cross-sectional design (i.e., correlations analyses and multiple regression analyses), showed that middle-distance running performance (800 and 1,500 m) is not significantly correlated with RE, especially in highly trained male runners (25, 35).It is important to note that exercise tolerance during high-intensity exercise can be predicted by a hyperbolic work rate/time function (i.e., critical power model) regardless of the work rate forcing function (incremental or CWR) or pacing strategy (enforced pace or self-paced) (14, 34). In line with these studies, Bosquet et al. (8) showed that middle-distance performance (800-m time trial) can be predicted by critical velocity models (0.83< r <0.94) in trained middle- and long-distance runners. Thus resistance training-induced improvement in W′ would be expected to increase middle-distance performance of endurance runners.Resistance training and clinical population.Skeletal muscle dysfunction has been associated with exercise intolerance characterizing both chronic obstructive pulmonary disease (COPD) and heart failure (HF) patients (2, 11). Moreover, skeletal muscle dysfunction is also an independent predictor of morbidity and mortality in COPD and HF (2). Thus exercise training has been considered an important nonpharmacological intervention to ameliorate the severity of muscle dysfunction in these diseases. These exercise programs have mainly focused on aerobic-based training given its ability to increase aerobic power (V̇o2max). More recently, however, resistance training has been used to improve exercise tolerance in COPD and HF. This therapeutic approach is considered safe and seems to improve health-related quality of life in these patients. Indeed, systematic reviews and meta-analysis have shown that resistance training can increase muscle strength, V̇o2peak and 6-min walk distance (6MWD) in COPD (24) and HF (19). Initially, it is possible to hypothesize that 6MWD was enhanced after resistance training due to improvement in V̇o2peak. However, an alternative hypothesis is that the enhanced W′ can help to explain, at least in part, the changes in 6MWD after resistance training period. In line with this hypothesis, Rausch-Osthoff et al. (31) found that maximal isometric strength of the quadriceps muscle was correlated with the 6MWD in patients with COPD. Moreover, Nápolis et al. (27) found that high-frequency neuromuscular electrical stimulation improved the exercise tolerance (cycling at 75–80%) of COPD patients with better-preserved fat-free mass. Local mineral-free thigh lean mass is significantly related with W′ determined during cycle exercise (13). Finally, Neder et al. (28) showed that CP expressed as percentage of peak work rate was significantly higher in COPD compared with control, whereas W′ was lower. Thus W′ is reduced in chronic disease [for review, see Poole et al. (30)], and the enhanced W′ could hypothetically explain changes in exercise tolerance after resistance training performed by COPD and HF patients.Possible mechanisms.The mechanistic bases for the W′ enhancement after resistance training has not been yet appropriately investigated. Based on the paradigm proposed by Amann et al. (1), it has been hypothesized that the central projection of group III/IV muscle afferent feedback limits the level of peripheral fatigue development (i.e., critical fatigue threshold), and consequently, the amplitude of W′ [for review, see Hureau et al. (22)]. Indeed, during handgrip exercise performed with blood flow occlusion, Broxterman et al. (9) found a significant relationship between muscle peripheral fatigue and the magnitude of W′. Moreover, a strong relationship between metabolite changes (e.g., H+ and Pi) within the muscle and peripheral fatigue development have been found during both whole body exercise (7) and small muscle mass exercise (10). Collectively, these data support a stronger relationship among W′, peripheral fatigue, and intramuscular metabolic perturbation during high-intensity exercise. In this context, some hypothesis/research questions can be formulated to explain/investigate the effects of resistance training on both exercise tolerance and W′ of different populations. First, it is possible that resistance training may increase muscle buffer capacity and/or decrease accumulation of end products of anaerobic metabolism during high-intensity exercise. Edge et al. (18) did not found improvement in muscle buffer capacity after 5 wk of the resistance training. However, there were significant reductions in the accumulation of H+ in the muscle and blood after high-intensity exercise (~160% V̇o2peak) (18). Thus a lower rate of H+ production and/or H+ accumulation during high-intensity exercise could attenuate the firing frequency of group III/IV afferents, increasing exercise tolerance and W′. Additionally, or alternatively, there may be a decrease in the sensitivity of group III/IV afferents to accumulation of end products of anaerobic metabolism after resistance training. Hypothetically, this adaptation could be found mainly in COPD and HF patients who present both overactive group III/IV muscle afferents (22) and low W′ (28). These resistance training-induced reductions in firing frequency of group III/IV afferents could change the “sensory tolerance limit” [for review, see Hureau et al. (23)], enhancing exercise tolerance and W′. Independent of whether any proposed hypothesis explain the enhanced exercise tolerance/W′ after resistance exercise, they deserve attention because both quality of life of patients and aerobic performance can be improved with this approach.DISCLOSURESNo conflicts of interest, financial or otherwise, are declared by the authors.AUTHOR CONTRIBUTIONSB.S.D. drafted manuscript; B.S.D. and C.C.G. edited and revised manuscript; B.S.D. and C.C.G. approved final version of manuscript.REFERENCES1. Amann M, Venturelli M, Ives SJ, McDaniel J, Layec G, Rossman MJ, Richardson RS. Peripheral fatigue limits endurance exercise via a sensory feedback-mediated reduction in spinal motoneuronal output. J Appl Physiol (1985) 115: 355–364, 2013. doi:10.1152/japplphysiol.00049.2013. Link | ISI | Google Scholar2. Barreiro E. Skeletal muscle dysfunction in COPD: Novelties in the last decade. Arch Bronconeumol 53: 43–44, 2017. doi:10.1016/j.arbres.2016.07.009. Crossref | PubMed | ISI | Google Scholar3. Berryman N, Maurel DB, Bosquet L. Effect of plyometric vs. dynamic weight training on the energy cost of running. J Strength Cond Res 24: 1818–1825, 2010. doi:10.1519/JSC.0b013e3181def1f5. Crossref | PubMed | ISI | Google Scholar4. Berryman N, Mujika I, Arvisais D, Roubeix M, Binet C, Bosquet L. Strength training for middle- and long-distance performance: A meta-analysis. Int J Sports Physiol Perform 13: 57–63, 2018. doi:10.1123/ijspp.2017-0032. Crossref | PubMed | ISI | Google Scholar5. Bishop D, Jenkins DG. The influence of resistance training on the critical power function & time to fatigue at critical power. Aust J Sci Med Sport 28: 101–105, 1996. PubMed | Google Scholar6. Black MI, Jones AM, Blackwell JR, Bailey SJ, Wylie LJ, McDonagh ST, Thompson C, Kelly J, Sumners P, Mileva KN, Bowtell JL, Vanhatalo A. Muscle metabolic and neuromuscular determinants of fatigue during cycling in different exercise intensity domains. J Appl Physiol (1985) 122: 446–459, 2017. doi:10.1152/japplphysiol.00942.2016. Link | ISI | Google Scholar7. Blain GM, Mangum TS, Sidhu SK, Weavil JC, Hureau TJ, Jessop JE, Bledsoe AD, Richardson RS, Amann M. Group III/IV muscle afferents limit the intramuscular metabolic perturbation during whole body exercise in humans. J Physiol 594: 5303–5315, 2016. doi:10.1113/JP272283. Crossref | PubMed | ISI | Google Scholar8. Bosquet L, Duchene A, Lecot F, Dupont G, Leger L. Vmax estimate from three-parameter critical velocity models: validity and impact on 800 m running performance prediction. Eur J Appl Physiol 97: 34–42, 2006. doi:10.1007/s00421-006-0143-7. Crossref | PubMed | ISI | Google Scholar9. Broxterman RM, Craig JC, Smith JR, Wilcox SL, Jia C, Warren S, Barstow TJ. Influence of blood flow occlusion on the development of peripheral and central fatigue during small muscle mass handgrip exercise. J Physiol 593: 4043–4054, 2015. doi:10.1113/JP270424. Crossref | PubMed | ISI | Google Scholar10. Broxterman RM, Layec G, Hureau TJ, Amann M, Richardson RS. Skeletal muscle bioenergetics during all-out exercise: mechanistic insight into the oxygen uptake slow component and neuromuscular fatigue. J Appl Physiol (1985) 122: 1208–1217, 2017. doi:10.1152/japplphysiol.01093.2016. Link | ISI | Google Scholar11. Brum PC, Bacurau AV, Cunha TF, Bechara LR, Moreira JB. Skeletal myopathy in heart failure: effects of aerobic exercise training. Exp Physiol 99: 616–620, 2014. doi:10.1113/expphysiol.2013.076844. Crossref | PubMed | ISI | Google Scholar12. Burnley M. Estimation of critical torque using intermittent isometric maximal voluntary contractions of the quadriceps in humans. J Appl Physiol (1985) 106: 975–983, 2009. doi:10.1152/japplphysiol.91474.2008. Link | ISI | Google Scholar13. Byrd MT, Switalla JR, Eastman JE, Wallace BJ, Clasey JL, Bergstrom HC. Contributions of body composition characteristics to critical power and anaerobic work capacity. Int J Sports Physiol Perform [ahead of print]. doi:10.1123/ijspp.2016-0810. Crossref | PubMed | ISI | Google Scholar14. Chidnok W, Dimenna FJ, Bailey SJ, Wilkerson DP, Vanhatalo A, Jones AM. Effects of pacing strategy on work done above critical power during high-intensity exercise. Med Sci Sports Exerc 45: 1377–1385, 2013. doi:10.1249/MSS.0b013e3182860325. Crossref | PubMed | ISI | Google Scholar15. Denadai BS, Ortiz MJ, Greco CC, de Mello MT. Interval training at 95% and 100% of the velocity at VO2 max: effects on aerobic physiological indexes and running performance. Appl Physiol Nutr Metab 31: 737–743, 2006. doi:10.1139/h06-080. Crossref | PubMed | ISI | Google Scholar16. Denadai BS, de Aguiar RA, de Lima LC, Greco CC, Caputo F. Explosive training and heavy weight training are effective for improving running economy in endurance athletes: A systematic review and meta-analysis. Sports Med 47: 545–554, 2017. doi:10.1007/s40279-016-0604-z. Crossref | PubMed | ISI | Google Scholar17. Dekerle J, de Souza KM, de Lucas RD, Guglielmo LG, Greco CC, Denadai BS. Exercise tolerance can be enhanced through a change in work rate within the severe intensity domain: Work above critical power is not constant. PLoS One 10: e0138428, 2015. doi:10.1371/journal.pone.0138428. Crossref | PubMed | ISI | Google Scholar18. Edge J, Hill-Haas S, Goodman C, Bishop D. Effects of resistance training on H+ regulation, buffer capacity, and repeated sprints. Med Sci Sports Exerc 38: 2004–2011, 2006. doi:10.1249/01.mss.0000233793.31659.a3. Crossref | PubMed | ISI | Google Scholar19. Giuliano C, Karahalios A, Neil C, Allen J, Levinger I. The effects of resistance training on muscle strength, quality of life and aerobic capacity in patients with chronic heart failure - A meta-analysis. Int J Cardiol 227: 413–423, 2017. doi:10.1016/j.ijcard.2016.11.023. Crossref | PubMed | ISI | Google Scholar20. Guglielmo LG, Greco CC, Denadai BS. Effects of strength training on running economy. Int J Sports Med 30: 27–32, 2009. doi:10.1055/s-2008-1038792. Crossref | PubMed | ISI | Google Scholar21. Hogan MC, Richardson RS, Haseler LJ. Human muscle performance and PCr hydrolysis with varied inspired oxygen fractions: a 31P-MRS study. J Appl Physiol (1985) 86: 1367–1373, 1999. doi:10.1152/jappl.1999.86.4.1367. Link | ISI | Google Scholar22. Hureau TJ, Broxterman RM, Weavil JC. The mechanistic basis of the power-time relationship: potential role of the group III/IV muscle afferents. J Physiol 594: 7165–7166, 2016. doi:10.1113/JP273333. Crossref | PubMed | ISI | Google Scholar23. Hureau TJ, Romer LM, Amann M. The ‘sensory tolerance limit’: A hypothetical construct determining exercise performance? Eur J Sport Sci 18: 13–24, 2018. doi:10.1080/17461391.2016.1252428. Crossref | PubMed | ISI | Google Scholar24. Iepsen UW, Jørgensen KJ, Ringbaek T, Hansen H, Skrubbeltrang C, Lange P. A systematic review of resistance training versus endurance training in COPD. J Cardiopulm Rehabil Prev 35: 163–172, 2015. doi:10.1097/HCR.0000000000000105. Crossref | PubMed | ISI | Google Scholar25. Ingham SA, Whyte GP, Pedlar C, Bailey DM, Dunman N, Nevill AM. Determinants of 800-m and 1500-m running performance using allometric models. Med Sci Sports Exerc 40: 345–350, 2008. doi:10.1249/mss.0b013e31815a83dc. Crossref | PubMed | ISI | Google Scholar26. Jones AM, Vanhatalo A, Burnley M, Morton RH, Poole DC. Critical power: implications for determination of V̇o2max and exercise tolerance. Med Sci Sports Exerc 42: 1876–1890, 2010. doi:10.1249/MSS.0b013e3181d9cf7f. Crossref | PubMed | ISI | Google Scholar27. Nápolis LM, Dal Corso S, Neder JA, Malaguti C, Gimenes AC, Nery LE. Neuromuscular electrical stimulation improves exercise tolerance in chronic obstructive pulmonary disease patients with better preserved fat-free mass. Clinics (Sao Paulo) 66: 401–406, 2011. doi:10.1590/S1807-59322011000300006. Crossref | PubMed | ISI | Google Scholar28. Neder JA, Jones PW, Nery LE, Whipp BJ. Determinants of the exercise endurance capacity in patients with chronic obstructive pulmonary disease. The power-duration relationship. Am J Respir Crit Care Med 162: 497–504, 2000. doi:10.1164/ajrccm.162.2.9907122. Crossref | PubMed | ISI | Google Scholar29. Paavolainen L, Häkkinen K, Hämäläinen I, Nummela A, Rusko H. Explosive-strength training improves 5-km running time by improving running economy and muscle power. J Appl Physiol (1985) 86: 1527–1533, 1999. doi:10.1152/jappl.1999.86.5.1527. Link | ISI | Google Scholar30. Poole DC, Burnley M, Vanhatalo A, Rossiter HB, Jones AM. Critical power: An important fatigue threshold in exercise physiology. Med Sci Sports Exerc 48: 2320–2334, 2016. doi:10.1249/MSS.0000000000000939. Crossref | PubMed | ISI | Google Scholar31. Rausch-Osthoff AK, Kohler M, Sievi NA, Clarenbach CF, van Gestel AJ. Association between peripheral muscle strength, exercise performance, and physical activity in daily life in patients with Chronic Obstructive Pulmonary Disease. Multidiscip Respir Med 9: 37, 2014. doi:10.1186/2049-6958-9-37. Crossref | PubMed | Google Scholar32. Sawyer BJ, Stokes DG, Womack CJ, Morton RH, Weltman A, Gaesser GA. Strength training increases endurance time to exhaustion during high-intensity exercise despite no change in critical power. J Strength Cond Res 28: 601–609, 2014. doi:10.1519/JSC.0b013e31829e113b. Crossref | PubMed | ISI | Google Scholar33. Sedano S, Marín PJ, Cuadrado G, Redondo JC. Concurrent training in elite male runners: the influence of strength versus muscular endurance training on performance outcomes. J Strength Cond Res 27: 2433–2443, 2013. doi:10.1519/JSC.0b013e318280cc26. Crossref | PubMed | ISI | Google Scholar34. Souza KM, de Lucas RD, do Nascimento Salvador PC, Guglielmo LG, Caritá RA, Greco CC, Denadai BS. Maximal power output during incremental cycling test is dependent on the curvature constant of the power-time relationship. Appl Physiol Nutr Metab 40: 895–898, 2015. doi:10.1139/apnm-2015-0090. Crossref | PubMed | ISI | Google Scholar35. Tartaruga MP, Mota CB, Peyré-Tartaruga LA, Brisswalter J. Scale model on performance prediction in recreational and elite endurance runners. Int J Sports Physiol Perform 9: 650–655, 2014. doi:10.1123/ijspp.2013-0165. Crossref | PubMed | ISI | Google Scholar36. Turner AM, Owings M, Schwane JA. Improvement in running economy after 6 weeks of plyometric training. J Strength Cond Res 17: 60–67, 2003. PubMed | ISI | Google ScholarAUTHOR NOTESAddress for reprint requests and other correspondence: B. S. Denadai, Human Performance Laboratory, Av. 24 A, 1515, Bela Vista, Rio Claro, SP, Brazil CEP 13506-900 (e-mail: [email protected]unesp.br). Download PDF Previous Back to Top Next FiguresReferencesRelatedInformation Cited ByMaximal strength training increases muscle force generating capacity and the anaerobic ATP synthesis flux without altering the cost of contraction in elderlyExperimental Gerontology, Vol. 111Effects of Strength Training on the Physiological Determinants of Middle- and Long-Distance Running Performance: A Systematic Review16 December 2017 | Sports Medicine, Vol. 48, No. 5Commentaries on Viewpoint: Resistance training and exercise tolerance during high-intensity exercise: moving beyond just running economy and muscle strength26 February 2018 | Journal of Applied Physiology, Vol. 124, No. 2 More from this issue > Volume 124Issue 2February 2018Pages 526-528 Copyright & PermissionsCopyright © 2018 the American Physiological Societyhttps://doi.org/10.1152/japplphysiol.00800.2017PubMed28982948History Received 7 September 2017 Accepted 2 October 2017 Published online 26 February 2018 Published in print 1 February 2018 Metrics