European Journal of Applied Physiology

, Volume 115, Issue 7, pp 1513–1522 | Cite as

Effects of resistance training on neuromuscular characteristics and pacing during 10-km running time trial

  • Mayara V. Damasceno
  • Adriano E. Lima-Silva
  • Leonardo A. Pasqua
  • Valmor Tricoli
  • Marcos Duarte
  • David J. Bishop
  • Rômulo Bertuzzi
Original Article

Abstract

Purpose

The purpose of this study was to analyze the impact of an 8-week strength training program on the neuromuscular characteristics and pacing adopted by runners during a self-paced endurance running.

Methods

Eighteen endurance runners were allocated into either strength training group (STG, n = 9) or control group (CG, n = 9) and performed the following tests before and after the training period: (a) incremental test, (b) running speed-constant test, (c) 10-km running time trial, (d) drop jump test, (e) 30-s Wingate anaerobic test, (f) maximum dynamic strength test (1RM). During 1RM, the electromyographic activity was measured.

Results

In the STG, the magnitude of improvement for 1RM (23.0 ± 4.2 %, P = 0.001), drop jump (12.7 ± 4.6 %, P = 0.039), and peak treadmill speed (2.9 ± 0.8 %, P = 0.013) was significantly higher compared to CG. This increase in the 1RM for STG was accompanied by a tendency to a higher electromyographic activity (P = 0.080). The magnitude of improvement for 10-km running performance was higher (2.5 %) for STG than for CG (−0.7 %, P = 0.039). Performance was improved mainly due to higher speeds during the last seven laps (last 2800 m) of the 10-km running trial. There were no significant differences between before and after training period for maximal oxygen uptake, respiratory compensation point, running economy, and anaerobic performance for both groups (P > 0.05).

Conclusions

These findings suggest that a strength training program offers a potent stimulus to counteract fatigue during the last parts of a 10-km running race, resulting in an improved overall running performance.

Keywords

Maximum dynamic strength Electromyographic activity Anaerobic performance Running economy Maximal oxygen uptake 

Abbreviations

1RM

Maximum dynamic strength

CG

Control group

CT

Contact time

iEMG

Electromyographic activity

DJH

Drop jump height

MP

Mean power

PP

Peak power

PTS

Peak treadmill speed

RCP

Respiratory compensation point

RE

Running economy

RPE

Rate of perceived exertion

RSI

Reactive strength index

STG

Strength training group

ST

Strength training

\( {\dot{\text{V}}} \)O2max

Maximal oxygen uptake

VM

Vastus medialis

Notes

Acknowledgments

The authors thank each of the individuals for their participation. The study was supported by grant from São Paulo Research Foundation (FAPESP 2011/10742-9). Mayara Vieira Damasceno is supported by a master scholarship from São Paulo Research Foundation (FAPESP 2013/00371-9).

Conflict of interest

The authors declare that they have no conflict of interest.

References

  1. Aagaard P, Mayer F (2007) Neuronal adaptations to strength training. Deutsche Zeit Sport med 58(2):50–53Google Scholar
  2. Abbiss CR, Laursen PB (2008) Describing and understanding pacing strategies during athletic competition. Sports Med 38(3):239–252PubMedCrossRefGoogle Scholar
  3. Bar-Or O (1987) The Wingate anaerobic test: an update on methodology, reliability and validity. Sports Med 50:273–282Google Scholar
  4. Beattie K, Kenny IC, Lyons M, Carson BP (2014) The effect of strength training on performance in endurance athletes. Sports Med 44(6):845–865PubMedCrossRefGoogle Scholar
  5. Bertuzzi R, Pasqua LA, Bueno S, Damasceno MV, Lima-Silva AE, Bishop D, Tricoli V (2013) Strength-training with whole-body vibration in long-distance runners: a randomized trial. Int J Sports Med 34:917–923PubMedCrossRefGoogle Scholar
  6. Bertuzzi R, Lima-Silva AE, Pires FO, Damasceno MV, Bueno S, Pasqua LA, Bishop DJ (2014) Pacing strategy determinants during a 10-km running time trial: contributions of perceived effort, physiological, and muscular parameters. J Strength Cond Res 28(6):1688–1696PubMedGoogle Scholar
  7. Billat VL, Sirvent P, Lepretre PM, Koralsztein JP (2004) Training effect on performance, substrate balance and blood lactate concentration at maximal lactate steady state in master endurance runners. Pflugers Arch 447(6):875–883PubMedCrossRefGoogle Scholar
  8. Borg GA (1982) Psychophysical bases of perceived exertion. Med Sci Sports Exerc 14(5):377–381PubMedCrossRefGoogle Scholar
  9. Brown LE, Weir JP (2001) Procedures recommendation I: accurate assessment of muscular strength and power. J Exerc Physiol 4:1–21Google Scholar
  10. Brozek J, Grande F, Anderson JT, Keys A (1963) Densitometric analysis o body composition: revision of some quantitative assumptions. Ann NY Acad Sci 26(110):113–140Google Scholar
  11. Creer AR, Ricard MD, Conlee RK, Hoyt GL, Parcell AC (2004) Neural, metabolic, and performance adaptations to four weeks of high-intensity sprint-interval training in trained cyclists. Int J Sports Med 25:92–98PubMedCrossRefGoogle Scholar
  12. De Morree HM, Klein C, Marcora SM (2012) Perception of effort reflects central motor command during movement execution. Psychophysiology 49:1242–1253PubMedCrossRefGoogle Scholar
  13. Docherty D, Sporer A (2000) Proposed model for examining the interference phenomenon between concurrent aerobic and strength training. Sports Med 30(6):385–394PubMedCrossRefGoogle Scholar
  14. Faulkner J, Parfitt G, Eston R (2008) The rating of perceived exertion during competitive running scales with time. Psychophysiology 45:977–985PubMedCrossRefGoogle Scholar
  15. Gettman LR, Ayres JJ, Pollock ML, Jackson A (1978) The effect of circuit weight training on strength, cardiorespiratory function, and body composition of adult men. Med Sci Sports Exerc 10(3):171–176Google Scholar
  16. Hakkinen K, Komi PV (1983) Electromyographic changes during strength training and detraining. Med Sci Sports Exerc 15(6):455–460PubMedCrossRefGoogle Scholar
  17. Howley ET, Bassett DR Jr, Welch HG (1995) Criteria for maximal oxygen uptake: review and commentary. Med Sci Sports Exerc 27:1292–1301PubMedCrossRefGoogle Scholar
  18. Hurley BF, Seals DR, Seals DR, Ehsani AA, Cartier LJ, Dalsky GP, Hagberg JM, Holloszy JO (1984) Effects of high-intensity strength training on cardiovascular function. Med Sci Sports Exerc 16(5):483–488PubMedCrossRefGoogle Scholar
  19. Jackson AS, Pollock ML (1985) Practical assessment of body composition. Phys Sports Med 19:76–90Google Scholar
  20. Lambert EV, St Clair Gibson A, Noakes TD (2005) Complex systems model of fatigue: integrative homoeostatic control of peripheral physiological systems during exercise in humans. Br J Sports Med 39:52–62PubMedCentralPubMedCrossRefGoogle Scholar
  21. Lima-Silva AE, Bertuzzi RCM, Pires FO, Barros RV, Gagliardi JF, Hammond J, Kiss MA, Bishop DJ (2010) Effect of performance level on pacing strategy during a 10-km running race. Eur J Appl Physiol 108(5):1045–1053PubMedCrossRefGoogle Scholar
  22. Meyer T, Lucía A, Earnest CP, Kindermann W (2005) A conceptual framework for performance diagnosis and training prescription from submaximal gas exchange parameters—theory and application. Int J Sports Med 26:S38–S48PubMedCrossRefGoogle Scholar
  23. Mikkola J, Rusko H, Nummela A, Pollari T, Häkkinen K (2007) Concurrent endurance and explosive type strength training improves neuromuscular and anaerobic characteristics in young distance runners. Int J Sports Med 28:602–611PubMedCrossRefGoogle Scholar
  24. Mikkola J, Vesterinen V, Taipale R, Capostagno B, Häkkinen K, Nummela A (2011) Effect of resistance training regimens on treadmill running and neuromuscular performance in recreational endurance runners. J Sports Sci 29:1359–1371PubMedCrossRefGoogle Scholar
  25. Noakes TD (1988) Implications of exercise testing for prediction of athletic performance: a contemporary perspective. Med Sci Sports Exerc 20:319–330PubMedCrossRefGoogle Scholar
  26. Norton K, Olds T (1996) Measurement technique in anthropometry. In: Norton K, Olds T (eds) Anthropometrica. University of New South Wale Press, Sydney, pp 25–75Google Scholar
  27. Nummela A, Paavolainen LM, Sharwood KA, Lambert MI, Noakes TD, Rusko HK (2006) Neuromuscular factors determining 5 km running performance and running economy in well-trained athletes. Eur J Appl Physiol 97:1–8PubMedCrossRefGoogle Scholar
  28. Paavolainen L, Hakkinen K, Hamalainen I, Nummela A, Rusko H (1999) Explosive-strength training improves 5-km running time by improving running economy and muscle power. J Appl Physiol 86(5):1527–1533PubMedGoogle Scholar
  29. Pizza FX, Naglieri TA, Holtz RW, Mitchell JB, Starling RD, Phillips MD, Cavender DL, Braun WA (1996) Maximal accumulated oxygen deficit of resistance-trained men. Can J Appl Physiol 21(5):391–402PubMedCrossRefGoogle Scholar
  30. Rønnestad BR, Hansen J, Hollan I, Ellefsen S (2014) Strength training improves performance and pedaling characteristics in elite cyclists. Scand J Med Sci Sports 25(1):e89–e98PubMedCrossRefGoogle Scholar
  31. Schulz KF, Altman DG, Moher D (2010) CONSORT 2010 Statement: updated guidelines for reporting parallel group randomised trials. PLoS Med 7(3):e1000251PubMedCentralPubMedCrossRefGoogle Scholar
  32. St Clair Gibson A, Lambert EV, Rauch LH, Tucker R, Baden DA, Foster C, Noakes TD (2006) The role of information processing between the brain and peripheral physiological systems in pacing and perception of effort. Sports Med 36(8):705–722PubMedCrossRefGoogle Scholar
  33. Storen O, Helgerud J, Stoa EM, Hoff J (2008) Maximal strength training improves running economy in distance runners. Med Sci Sports Exerc 40:1087–1092PubMedCrossRefGoogle Scholar
  34. Taipale RS, Mikkola J, Nummela A, Vesterinen V, Capostagno B, Walker S, Gitonga D, Kraemer WJ, Häkkinen K (2010) Strength training in endurance runners. Int J Sports Med 31:468–476PubMedCrossRefGoogle Scholar
  35. Tanaka H, Swensen T (1998) Impact of resistance training on endurance performance. A new form of cross-training? Sports Med 25(3):191–200PubMedCrossRefGoogle Scholar
  36. Thiel C, Foster C, Banzer W, De Koning J (2012) Pacing in Olympic track races: competitive tactics versus best performance strategy. J Sports Sci 30(11):1107–1115PubMedCrossRefGoogle Scholar
  37. Tucker R, Noakes TD (2009) The anticipatory regulation of performance: the physiological basis for pacing strategies and the development of a perception-based model for exercise performance. Br J Sports Med 43(6):392–400PubMedCrossRefGoogle Scholar
  38. Ulmer HV (1996) Concept of an extracellular regulation of muscular metabolic rate during heavy exercise in humans by psychophysiological feedback. Experientia 52(5):416–420PubMedCrossRefGoogle Scholar
  39. Young WB, Behm DG (2003) Effects of running, static stretching and practice jumps on explosive force production and jumping performance. J Sports Med Phys Fitness 43:21–27PubMedGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Mayara V. Damasceno
    • 1
  • Adriano E. Lima-Silva
    • 2
  • Leonardo A. Pasqua
    • 1
  • Valmor Tricoli
    • 5
  • Marcos Duarte
    • 3
  • David J. Bishop
    • 4
  • Rômulo Bertuzzi
    • 1
  1. 1.Endurance Performance Research Group, Department of Sport, School of Physical Education and SportUniversity of São PauloSão PauloBrazil
  2. 2.Sports Science Research Group, Academic Center of Vitoria (CAV)Federal University of PernambucoPernambucoBrazil
  3. 3.Biomedical EngineeringFederal University of ABCSanto AndréBrazil
  4. 4.Institute of Sport, Exercise and Active LivingVictoria University (VU)MelbourneAustralia
  5. 5.Department of Sport, School of Physical Education and SportUniversity of São PauloSão PauloBrazil

Personalised recommendations