Methods to Estimate VO2max upon Acute Hypoxia Exposure

Introduction Altitude and an individual's VO^2max contribute to a decrease in VO^2max under hypoxic conditions. The purpose of this study was to update previous reviews with recent research in order to quantitatively determine the individual and interacting effects of altitude and baseline VO^2max on VO^2max upon acute exposure to hypoxia while developing a statistical model to predict an individual's VO^2max under hypoxic conditions. Methods Meta-regression was conducted on 105 independent groups of participants (n = 958 supjects from 80 different studies). A series of regression models was tested. The final model included altitude, baseline VO^2max, Alt², baseline VO^{2max 2}, and the interaction of altitude with baseline VO^2max. Results A curvilinear model provided the best fit for metadata, explaining almost 80% of the variance in the null model. Nonlinear effects of Alt² (β =-0.078; 95% confidence interval,-0.15 to-0.002) and baseline VO^{2max 2} (β =-0.003; 95% confidence interval,-0.004 to-0.001) showed that VO^2max decreases as altitude increases and that the decrease is greater in individuals with higher aerobic capacities. The interaction of these effects (β =-0.028; 95% confidence interval,-0.042 to-0.015) also showed that the effects of altitude were augmented with higher baseline aerobic capacities. Furthermore, the predictions of the model were fairly accurate in predicting individual decreases in VO^2max (root-mean-squared error, 3.9 mL·kg^-1·min^-1). Conclusions These data provide a robust quantitative framework for the curvilinear and interacting effects of altitude and baseline VO^2max in determining an individual's effective VO^2max at altitude. This predictive model is useful for a priori power calculations, design of future experimental studies, and prediction of aerobic capacity declines in applied settings.