Skip to main content
SpringerLink
Log in

Use of Bioimpedianciometer as Predictor of Mountain Marathon Performance

  • Education & Training
  • Published:
Journal of Medical Systems Aims and scope Submit manuscript

Abstract

This study aimed to examine the relation among body composition, training experience and race time during a mountain marathon. Body composition and training pre-race experience analyses were conducted previous to a mountain marathon in 52 male athletes. A significant correlation between race time and mountain marathon with chronological age, body fat mass, percentage of body fat (BF), level of abdominal obesity, sport experience and daily training volume was revealed. In addition, BF and athlete’s chronological age were negatively associated with race performance. In contrast, the daily training volume was positively associated with mountain marathon time. A regression analysis showed that race time could be predicted (R2 = .948) by the daily training load, sports experience, age, body fat mass, BF and level of abdominal obesity. The comparison between performance groups regarding to body composition and training characteristics showed that the higher performance group was lighter with lower BF, fat mass and level of abdominal obesity, and with more days of training per week compared with the lower performance group (p < .05). Therefore, coaches and fitness trainers working with mountain marathon runners should develop exercise and nutritional strategies to reduce BF and consider increasing mean daily training volume to improve performance.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Hoffman, M.D., Lebus, D.K., Ganong, A.C., Casazza, G.A., and Van Loan, M., Body composition of 161-km ultramarathoners. Int J Sport Med. 31:106–109, 2010.

    Article  CAS  Google Scholar 

  2. Knechtle, B., Knechtle, P., Schulze, I., and Kohler, G., Upper arm circumference is associated with race performance in ultra-endurance runners. Br J. Sports Med. 42:295–299, 2008.

    Article  CAS  PubMed  Google Scholar 

  3. Knechtle, B., Duff, B., Welzel, U., and Kohler, G., Body mass and circumference of upper arm are associated with race performance in ultraendurance runners in a multistage race - the Isarrun 2006. Res Q Exerc Sport. 80:262–268, 2009.

    Article  PubMed  Google Scholar 

  4. Hagan, R.D., Upton, S.J., Duncan, J.J., and Gettman, L.R., Marathon performance in relation to maximal aerobic power and training indices in female distance runners. Br J. Sports Med. 21:3–7, 1987.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Arrese, A.L., and Ostariz, E.S., Skinfold thicknesses associated with distance running performance in highly trained runners. J Sports Sci. 24:69–76, 2006.

    Article  PubMed  Google Scholar 

  6. Hagan, R.D., Smith, M.G., and Gettman, L.R., Marathon performance in relation to maximal aerobic power and training indices. Med Sci Sports Exerc. 13(3):185–189, 1981.

    Article  CAS  PubMed  Google Scholar 

  7. Hoffman, M.D., Anthropometric characteristics of ultramarathoners. Int J. Sports Med. 29:808–811, 2008.

    Article  CAS  PubMed  Google Scholar 

  8. Kenney, W., and Hodgson, J., (1985). Variables predictive of performance in elite middle-distance runners. Brit. J. Sports Med. 19(4):207–209, 1985.

    CAS  Google Scholar 

  9. Conley, D.L., and Krahenbuhl, G.S., Running economy and distance running performance of highly trained athletes. Med Sci Sports Exerc. 12(5):357–360, 1980.

    Article  CAS  PubMed  Google Scholar 

  10. Scott, B.K., and Houmard, J.A., Peak running velocity is highly related to distance running performance. Int J. Sports Med. 15:504–507, 1994.

    Article  CAS  PubMed  Google Scholar 

  11. Bale, P., Bradbury, D., and Colley, E., Anthropometric and training variables related to 10km running performance. Br J. Sports Med. 20:170–173, 1986.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Scrimgeour, A.G., Noakes, T.D., Adams, B., and Myburgh, K., The influence of weekly training distance on fractional utilization of maximum aerobic capacity in marathon and ultra marathon runners. Eur J Appl Physiol. 55:202–209, 1985.

    Article  Google Scholar 

  13. Billat, V.L., Demarle, A., Slawinski, J., et al., Physical and training characteristics of top-class marathon runners. Med Sci Sports Exerc. 33:2089–2097, 2001.

    Article  CAS  PubMed  Google Scholar 

  14. Knechtle, B., Wirth, A., Knechtle, P., and Rosemann, T., Training volume and personal best time in marathon, not anthropometric parameters, are associated with performance in male 100-km ultrarunners. J Strength Cond Res. 24:604–609, 2010.

    Article  PubMed  Google Scholar 

  15. Knechtle, B., Knechtle, P., and Rosemann, T., No correlation of skin-fold thickness and race performance in male ultra-endurance cyclists in a 600 km ultra-cycling marathon. Hum Mov. 10:91–95, 2009.

    Google Scholar 

  16. Clemente, V., Modificaciones de parámetros bioquímicos después de una maratón de montaña. Motricidad. Eur J Hum Mov. 27:75–83, 2011.

    Google Scholar 

  17. Donadio, C., Halim, A.B., Caprio, F., Grassi, G., Khedr, B., and Mazzantini, M., Single- and multi-frequency bioelectrical impedance analyses to analyse body composition in maintenance haemodialysis patients: Comparison with dual-energy x-ray absorptiometry. Physiol Meas. 29(6):S517–S524, 2008.

    Article  CAS  PubMed  Google Scholar 

  18. Sharer, K., Siders, W., Johnson, L., and Lukaski, H., Validity of segmental multiple-frequency bioelectrical impedance analysis to estimate body composition of adults across a range of body mass indexes. Nutrition. 25:25–32, 2009.

    Article  Google Scholar 

  19. Lohman, T.G., Roche, A.F., and Martorell, R., Anthropometric standardization reference manual. Human Kinetics Books, Ilinois, 1988.

    Google Scholar 

  20. Knechtle, B., Rüst, C., Knechtle, P., Rosemann, T., and Lepers, R., Age-related changes in ultra-triathlon performances. Extrem Physiol Med. 1(5):2–9, 2012.

    Google Scholar 

  21. Leyk, D., Erley, O., Ridder, D., Leurs, M., Rüther, T., Wunderlich, M., Sievert, A., Baum, K., and Essfeld, D., Aged-related changes in marathon and half-marathon performances. Int J Sports Med. 28:513–517, 2007.

    Article  CAS  PubMed  Google Scholar 

  22. Knechtle, B., Wirth, A., Knechtle, P., Zimmerman, J., and Kohler, P., Personal best marathon performance is associated with performance in a 24-h run and not anthropometry or training volume. Br J. Sports Med. 43:836–839, 2009.

    Article  CAS  PubMed  Google Scholar 

  23. Knechtle, B., Knechtle, P., Rüst, C.A., Rosemann, T., and Lepers, R., Age, training, and previous experience predict race performance in long-distance inline skaters, not anthropometry. Percept Motor Skill. 114(1):141–156, 2012.

    Article  Google Scholar 

  24. Zamparo, P., Capelli, C., and Pendergast, D., Energetics of swimming: A historical perspective. European Journal of Applied Physiology. 111(3):367–378, 2010.

    Article  PubMed  Google Scholar 

  25. Navarro, F., Endurance training. Gymnos, Madrid, 1998.

    Google Scholar 

  26. Hewson, D.J., and Hopkins, W.G., Specificity of training and its relation to the performance of distance runners. International Journal of Sports Medicine. 17:199–204, 1996.

    Article  CAS  PubMed  Google Scholar 

  27. Der, V.J., Langfristing verzogeerte Training-seffect durch konzentriertes Krafttraining. Leistungs Sport Germany. 3:41–44, 1984.

    Google Scholar 

  28. Knechtle, B., Rosemann, T., Knechtle, P., and Lepers, R., Predictor variables for a 100-km race time in male ultra-marathoners 1, 2. Percept Motor Skill. 111(3):681–693, 2010.

    Article  Google Scholar 

  29. Knechtle, B., Knechtle, P., and Rosemann, T., Race performance in male mountain ultra-marathoners: Anthropometry or training? Percept Motor Skill. 110(3):721–735, 2010.

    Article  Google Scholar 

  30. Clemente, V., and Gonzalez, J., Four weeks of training with different aerobic workload distributions – Effect on aerobic performance. Eur J Sport Sci. 14(1):1–7, 2014.

    Article  Google Scholar 

  31. Clemente-Suárez, V. J., Dalamitros, A. A., & Nikolaidis, P. T. The effect of a short-term training period on physiological parameters and running performance: Intensity distribution versus constant-intensity exercise. J Sports Med Phys Fitness. 2016. Nov 4. [Epub ahead of print]

  32. Clemente-Suárez, V.J., Dalamitros, A., Ribeiro, J., Sousa, A., Fernandes, R.J., and Vilas-Boas, J.P., The effects of two different swimming training periodization on physiological parameters at various exercise intensities. Eur J Sport Sci., 2016. doi:10.1080/17461391.2016.1253775.

    PubMed  Google Scholar 

  33. Clemente-Suárez, V.J., Fernandes, R.J., Arroyo-Toledo, J.J., Figueiredo, P., González-Ravé, J.M., and Vilas-Boas, J.P., Autonomic adaptation after traditional and reverse swimming training periodizations. Ac Physiol Hung. 102(1):105–113, 2015. doi:10.1556/APhysiol.102.2015.1.11.

    Article  Google Scholar 

  34. Clemente-Suarez, V.J., The importance of intensity in the prescription of health training. Rev Int Cienc Deporte. 11(41):192–195, 2015. doi:10.5232/ricyde.

    Article  Google Scholar 

  35. Arroyo-Toledo, J.J., Clemente-Suarez, V.J., and González-Rave, J.M., Effects of Traditional and Reverse Periodization on Strength, Body-Composition and Swim Performance. Imperial J Interdisciplinary Res. 2(12), 2016.

Download references

Author information

Authors and Affiliations

  1. Applied Psychophysiological Research Group, European University of Madrid, Calle Tajo, s/n, 28670 Villaviciosa de Odón, Madrid, Spain

    Vicente Javier Clemente-Suarez

  2. Department of Physical and Cultural Education, Hellenic Army Academy, Athens, Greece

    Pantelis Theodoros Nikolaidis

Authors
  1. Vicente Javier Clemente-Suarez
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Pantelis Theodoros Nikolaidis
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Vicente Javier Clemente-Suarez.

Ethics declarations

Funding

None.

Conflict of Interest

None.

Ethical Approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed Consent

Informed consent was obtained from all individual participants included in the study.

Additional information

This article is part of the Topical Collection on Education & Training

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Clemente-Suarez, V.J., Nikolaidis, P.T. Use of Bioimpedianciometer as Predictor of Mountain Marathon Performance. J Med Syst 41, 73 (2017). https://doi.org/10.1007/s10916-017-0722-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s10916-017-0722-7

Keywords

Search

Navigation