Development of non-exercise based VO2max prediction equation in college-aged participants in India.

ABSTRACT

AIM: The purpose of this study was to develop a linear regression model to predict treadmill VO2max scores using non-exercise data. METHODS: In this cross sectional study, one hundred twenty college-aged participants (60 male, 60 female, mean age 22.02±2.29 years) voluntarily participated and successfully completed a maximal graded exercise test (GXT) on a motorized treadmill to assess VO2max (mean±SD; 2.05 L·min-¹±1.03 L·min-¹). The maximal treadmill GXT required participants to exercise to volitional fatigue. RESULTS: Relevant non-exercise data included a mean (±SD) perceived functional ability (PFA) score, and physical activity rating (PA-R) score, body surface area (BSA) of 14.6±3.9, 2.97±1..75, 1.66±0.17, respectively. Multiple linear regression generated the following regression equation (R=0.899, R2=0.805, adjusted R2=0.799, SEE=0.426 L·min-¹) VO2max (L/min)=-1.541+1.096 (gender, 1=male, 0=female) +.081 (PFA) +1.084(BSA). Each predictor variable was statistically significant (P<0.05) with beta weights for gender, PFA, BSA, PA-R, and equal to (-0.518), (0.255), (0.228), (0.092), percent body fat (-0.003), respectively. The accuracy of the model was evaluated by conducting a cross-validation analysis (N.=18). CONCLUSION: This study provides a N-EX regression prediction model that yields results and also provide a convenient and efficient tool that estimate VO2max in healthy college-aged participants in India.