A Maximal Graded Exercise Test to Accurately Predict VO2max in 18-65-Year-Old Adults

The purpose of this study was to develop an age-generalized regression model to predict maximal oxygen uptake (VO2max) based on a maximal treadmill graded exercise test (GXT; George, 1996). Participants (N = 100), ages 18-65 years, reached a maximal level of exertion (mean +/- standard deviation [SD]; maximal heart rate [HRmax] = 185.2 +/- 12.4 beats per minute (bpm); maximal respiratory exchange ratio [RERmax] = 1.18 +/- 0.05; maximal rating of perceived exertion (RPEmax) = 19.1 +/- 0.7) during the GXT to assess VO2max (mean +/- SD; 40.24 +/- 9.11 mL.kg(-1).min(-1)). Multiple linear regression generated the following prediction equation (R = .94, standard error of estimate [SEE] = 3.18 mL.kg(-1).min(-1), % SEE = 7.9): VO2max (mL.kg(-1).min(-1)) = 13.160 + (3.314 x gender; females = 0, males = 1) - (.131 x age) - (.334 x body mass index (BMI)) + (5.177 x treadmill speed; mph) + (1.315 x treadmill grade; %). Cross validation using predicted residual sum of squares (PRESS) statistics revealed minimal shrinkage (R-p = .93 and SEEp = 3.40 mL.kg(-1).min(-1)); consequently, this model should provide acceptable accuracy when it is applied to independent samples of comparable adults. Standardized beta-weights indicate that treadmill speed (.583) was the most effective at predicting VO2max followed by treadmill grade (.356), age (-.197), gender (.183), and BMI (-.148). This study provides a relatively accurate regression model to predict VO2max in relatively fit men and women, ages 18-65 years, based on maximal exercise (treadmill speed and grade), biometric (BMI), and demographic (age and gender) data.