Prediction of males’ physical work capacity in various simulated altitudes using an incremental cycle ergometer exercise test at sea level

Abstract

Standard approach to predict the decrease in physical fitness that will occur following a transition to a higher altitude is unavailable. Therefore, the study aimed to design simple mathematical models to predict submaximal exercise performance in various altitude environments, using a simple physical work capacity test conducted at sea level involving >200 subjects. After splitting the subjects’ data in a ratio of 7:3, we used 70% of the data for regression model development and employed 30% for cross-validation testing. All subjects performed submaximal exercise tests using a cycle ergometer at artificial altitudes of 2000 m, 3000 m, 4000 m, 5000 m, and at sea level. We applied simple regression analysis to create a predictive model with the statistical significance set at the level of <5%. There were 233 subjects involved in this study. The coefficient of determination of our regression model was 40–58%, and the standard error of estimation was 14.96–17.27 watts. The cross-validation of our regression model was 8–10%. Among the regression models developed, the one applied to an artificial altitude of 5000 m was 17%, and the regression model applied to an artificial altitude below 4000 m had no issues in generalization since the cross-validation was less than 10%. However, the regression model applied to an artificial altitude of 5000 m had a cross-validity of 17%; therefore, it should be used with caution.

Keywords

• high altitude
• hypoxia
• physical work capacity
• exercise performance
• estimation
• prediction
• regression