TY - JOUR
T1 - Scaling maximal oxygen uptake to predict cycling time-trial performance in the field
T2 - A non-linear approach
AU - Nevill, A. M.
AU - Jobson, S. A.
AU - Palmer, G. S.
AU - Olds, T. S.
PY - 2005/8/1
Y1 - 2005/8/1
N2 - The purpose of the present article is to identify the most appropriate method of scaling V̇O2max for differences in body mass when assessing the energy cost of time-trial cycling. The data from three time-trial cycling studies were analysed (N =79) using a proportional power-function ANCOVA model. The maximum oxygen uptake-to-mass ratio found to predict cycling speed was V̇O2max (m)-0.32, precisely the same as that derived by Swain for sub-maximal cycling speeds (10, 15 and 20 mph). The analysis was also able to confirm a proportional curvilinear association between cycling speed and energy cost, given by (V̇O2max (m)-0.32)0.41. The model predicts, for example, that for a male cyclist (72 kg) to increase his average speed from 30 km h-1 to 35 km h-1, he would require an increase in V̇O2max from 2.36 l min-1 to 3.44 1 min-1, an increase of 1.08 l min-1. In contrast, for the cyclist to increase his mean speed from 40 km h-1 to 45 km h-1, he would require a greater increase in V̇O2max from 4.77 l min-1 to 6.36 l min-1, i.e. an increase of 1.59 l min-1. The model is also able to accommodate other determinants of time-trial cycling, e.g. the benefit of cycling with a side wind (5% faster) compared with facing a predominatly head/tail wind (P<0.05). Future research could explore whether the same scaling approach could be applied to, for example, alternative measures of recording power output to improve the prediction of time-trial cycling performance.
AB - The purpose of the present article is to identify the most appropriate method of scaling V̇O2max for differences in body mass when assessing the energy cost of time-trial cycling. The data from three time-trial cycling studies were analysed (N =79) using a proportional power-function ANCOVA model. The maximum oxygen uptake-to-mass ratio found to predict cycling speed was V̇O2max (m)-0.32, precisely the same as that derived by Swain for sub-maximal cycling speeds (10, 15 and 20 mph). The analysis was also able to confirm a proportional curvilinear association between cycling speed and energy cost, given by (V̇O2max (m)-0.32)0.41. The model predicts, for example, that for a male cyclist (72 kg) to increase his average speed from 30 km h-1 to 35 km h-1, he would require an increase in V̇O2max from 2.36 l min-1 to 3.44 1 min-1, an increase of 1.08 l min-1. In contrast, for the cyclist to increase his mean speed from 40 km h-1 to 45 km h-1, he would require a greater increase in V̇O2max from 4.77 l min-1 to 6.36 l min-1, i.e. an increase of 1.59 l min-1. The model is also able to accommodate other determinants of time-trial cycling, e.g. the benefit of cycling with a side wind (5% faster) compared with facing a predominatly head/tail wind (P<0.05). Future research could explore whether the same scaling approach could be applied to, for example, alternative measures of recording power output to improve the prediction of time-trial cycling performance.
KW - Body mass
KW - Cycling speed
KW - Power function
KW - Proportional allometric model
KW - Wind resistance
UR - http://www.scopus.com/inward/record.url?scp=23744485382&partnerID=8YFLogxK
U2 - 10.1007/s00421-005-1321-8
DO - 10.1007/s00421-005-1321-8
M3 - Article
C2 - 15906080
AN - SCOPUS:23744485382
VL - 94
SP - 705
EP - 710
JO - European Journal of Applied Physiology
JF - European Journal of Applied Physiology
SN - 1439-6319
IS - 5-6
ER -