Estimation of peak oxygen uptake from maximal power output among 9-10 year-old children in Lhasa, Tibet

J Sports Med Phys Fitness. 2010 Sep;50(3):274-80.

Abstract

Aim: The aims of the present study of Tibetan and Han Chinese children were to establish prediction equations for peak oxygen uptake (VO2peak) using conventional power output measures, and to compare with prediction models based on data from sea level.

Methods: In 25 Tibetan children and 15 Han Chinese children aged 9-10 years, living in Lhasa at 3700 meters above sea level, VO2peak was measured directly using a portable oxygen analyzer, and predicted from maximal power output (Wmax) using a maximal cycle ergometer test.

Results: In multiple regression analyses with VO2peak as dependent variable and Wmax and sex as covariates, a total adjusted R2 of 0.76 and 0.82 were found in Tibetan and Han Chinese children, separately. Sex made a unique, and statistically significant, contribution to the prediction of VO2peak. Three equations derived from sea level data were compared with the equations from the present study. None of the three could accurately predict the direct measured V.O2peak, and predictions differed in an unsystematic manner, including over- or underestimation and no differentiation between genders.

Conclusion: Peak oxygen uptake could be estimated from Wmax and sex in a progressive cycle ergometer test among children living at 3700 meters in Tibet. The estimate of VO2peak is probably more valid using the present equations than prediction models based on data from sea level. The equations used for the prediction are: Bianba(eqT): (l·min(-1)) = 0.5419 + (0.0096· Wmax) - (0.0562· sex); boys=0; girls=1 Bianba(eqH): (l·min(-1)) = 0.4060 + (0.0124· Wmax) - (0.1775· sex); boys=0; girls=1.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Altitude*
  • Analysis of Variance
  • Anthropometry
  • Child
  • Exercise Test
  • Female
  • Humans
  • Male
  • Oxygen Consumption / physiology*
  • Predictive Value of Tests
  • Regression Analysis
  • Tibet / ethnology