Ultra Trail Performance is Differently Predicted by Endurance Variables in Men and Women
The study aimed to assess the relationship between peak oxygen uptake, ventilatory thresholds and maximal fat oxidation with ultra trail male and female performance. 47 athletes (29 men and 18 women) completed a cardiopulmonary exercise test between 2 to 4 weeks before a 107-km ultra trail. Body composition was also analyzed using a bioelectrical impedance weight scale. Exploratory correlation analyses showed that peak oxygen uptake (men: r=–0.63, p=0.004; women: r=–0.85, p < 0.001), peak speed (men: r=–0.74, p < 0.001; women: r=–0.69, p=0.009), speed at first (men: r=–0.49, p=0.035; women: r=–0.76, p=0.003) and second (men: r=–0.73, p < 0.001; women: r=–0.76, p=0.003) ventilatory threshold, and maximal fat oxidation (men: r=–0.53, p=0.019; women: r=–0.59, p=0.033) were linked to race time in male and female athletes. Percentage of fat mass (men: r=0.58, p=0.010; women: r=0.62, p= 0.024) and lean body mass (men: r=–0.61, p=0.006; women: r=–0.61, p=0.026) were also associated with performance in both sexes. Subsequent multiple regression analyses revealed that peak speed and maximal fat oxidation together were able to predict 66% of male performance; while peak oxygen uptake was the only statistically significant variable explaining 69% of the variation in women’s race time. These results, although exploratory in nature, suggest that ultra trail performance is differently predicted by endurance variables in men and women.
Key wordssex - ultraendurance - maximal oxygen uptake - ventilatory thresholds - maximal fat oxidation
Received: 10 May 2020
Accepted: 24 August 2020
05 October 2020 (online)
© 2020. Thieme. All rights reserved.
© Georg Thieme Verlag KG
Stuttgart · New York
- 1 Knechtle B, Nikolaidis PT. Physiology and pathophysiology in ultra-marathon running. Front Physiol 2018; 9: 634 doi:10.3389/fphys.2018.00634
- 2 Scheer V, Basset P, Giovanelli N. et al. Defining off-road running: A position statement from the ultra sports science foundation. Int J Sports Med 2020; 41: 275-284
- 3 Alvero-Cruz JR, Parent Mathias V, Garcia Romero J. et al. Prediction of performance in a short trail running race: The role of body composition. Front Physiol 2019; 10: 1306 DOI: 10.3389/fphys.2019.01306.
- 4 Balducci P, Clemencon M, Trama R. et al. Performance factors in a mountain ultramarathon. Int J Sports Med 2017; 38: 819-826 DOI: 10.1055/s-0043-112342.
- 5 Bjorklund G, Swaren M, Born DP. et al. Biomechanical adaptations and performance indicators in short trail running. Front Physiol 2019; 10: 506 DOI: 10.3389/fphys.2019.00506.
- 6 Ehrstrom S, Tartaruga MP, Easthope CS. et al. Short trail running race: Beyond the classic model for endurance running performance. Med Sci Sports Exerc 2018; 50: 580-588 DOI: 10.1249/MSS.0000000000001467.
- 7 Fornasiero A, Savoldelli A, Fruet D. et al. Physiological intensity profile, exercise load and performance predictors of a 65-km mountain ultra-marathon. J Sports Sci 2018; 36: 1287-1295 DOI: 10.1080/02640414.2017.1374707.
- 8 Scheer V, Janssen TI, Vieluf S. et al. Predicting trail running performance with laboratory exercise tests and field based results. Int J Sports Physiol Perform 2018; 1-13 DOI: 10.1123/ijspp.2018-0390.
- 9 di Prampero PE, Atchou G, Bruckner JC. et al. The energetics of endurance running. Eur J Appl Physiol Occu Physiol 1986; 55: 259-266
- 10 O'Loughlin E, Nikolaidis PT, Rosemann T. et al. Different predictor variables for women and men in ultra-marathon running-the wellington urban ultramarathon 2018. Int J Environ Res Public Health 2019; 16: 1287
- 11 Millet GY, Hoffman MD, Morin JB. Sacrificing economy to improve running performance–a reality in the ultramarathon?. J Appl Physiol (1985) 2012; 113: 507-509
- 12 Vernillo G, Millet GP, Millet GY. Does the running economy really increase after ultra-marathons?. Front Physiol 2017; 8: 783 doi:10.3389/fphys.2017.00783
- 13 Lazzer S, Salvadego D, Taboga P. et al. Effects of the Etna uphill ultramarathon on energy cost and mechanics of running. Int J Sports Physiol Perform 2015; 10: 238-247 DOI: 10.1123/ijspp.2014-0057.
- 14 Beck ON, Kipp S, Byrnes WC. et al. Use aerobic energy expenditure instead of oxygen uptake to quantify exercise intensity and predict endurance performance. J Appl Physiol (1985) 2018; 125: 672-674 DOI: 10.1152/japplphysiol.00940.2017.
- 15 Maunder E, Plews DJ, Kilding AE. Contextualising maximal fat oxidation during exercise: Determinants and normative values. Front Physiol 2018; 9: 599 doi:10.3389/fphys.2018.00599
- 16 Frandsen J, Vest SD, Larsen S. et al. Maximal fat oxidation is related to performance in an ironman triathlon. Int J Sports Med 2017; 38: 975-982
- 17 Maunder E, Kilding AE, Plews DJ. Substrate metabolism during ironman triathlon: Different horses on the same courses. Sports Med 2018; 48: 2219-2226 doi:10.1007/s40279-018-0938-9
- 18 Vest SD, Frandsen J, Larsen S. et al. Peak fat oxidation is not Independently related to ironman performance in women. Int J Sports Med 2018; 39: 916-923 DOI: 10.1055/a-0660-0031.
- 19 Harriss DJ, MacSween A, Atkinson G. Ethical standards in sport and exercise science research: 2020 update. Int J Sports Med 2019; 40: 813-817 doi:10.1055/a-1015-3123
- 20 Rietjens GJ, Kuipers H, Kester AD. et al. Validation of a computerized metabolic measurement system (Oxycon-Pro) during low and high intensity exercise. Int J Sports Med 2001; 22: 291-294 DOI: 10.1055/s-2001-14342.
- 21 Skinner JS, McLellan TM. The transition from aerobic to anaerobic metabolism. Res Q Exerc Sport 1980; 51: 234-248 doi:10.1080/02701367.1980.10609285
- 22 Frayn KN. Calculation of substrate oxidation rates in vivo from gaseous exchange. J Appl Phys Respir Environ Exerc Physiol 1983; 55: 628-634
- 23 Amaro-Gahete FJ, Sanchez-Delgado G, Jurado-Fasoli L. et al. Assessment of maximal fat oxidation during exercise: A systematic review. Scand J Med Sci Sports 2019; 29: 910-921 DOI: 10.1111/sms.13424.
- 24 Thomas J, Nelson J, Silverman S. Research Methods in Physical Activity. Champaign: Human Kinetics; 2005
- 25 Perez A, Ramos-Campo DJ, Marin-Pagan C. et al. Impact of polarized versus threshold training on fat metabolism and neuromuscular variables in ultrarunners. Int J Sports Physiol Perform 2019; 1-8 DOI: 10.1123/ijspp.2019-0113.
- 26 Amaro-Gahete FJ, Jurado-Fasoli L, Trivino AR. et al. Diurnal variation of maximal fat-oxidation rate in trained male athletes. Int J Sports Physiol Perform 2019; 14: 1140-1146 DOI: 10.1123/ijspp.2018-0854.
- 27 Lima-Silva AE, Bertuzzi RC, Pires FO. et al. Relationship between training status and maximal fat oxidation rate. J Sports Sci Med 2010; 9: 31-35
- 28 Dandanell S, Meinild-Lundby AK, Andersen AB. et al. Determinants of maximal whole-body fat oxidation in elite cross-country skiers: Role of skeletal muscle mitochondria. Scand J Med Sci Sports 2018; 28: 2494-2504 DOI: 10.1111/sms.13298.
- 29 Hoffman MD, Lebus DK, Ganong AC. et al. Body composition of 161-km ultramarathoners. Int J Sports Med 2010; 31: 106-109 DOI: 10.1055/s-0029-1241863.
- 30 Giandolini M, Horvais N, Rossi J. et al. Acute and delayed peripheral and central neuromuscular alterations induced by a short and intense downhill trail run. Scand J Med Sci Sports 2016; 26: 1321-1333 DOI: 10.1111/sms.12583.