An accurate vo₂max nonexercise regression model for 18–65-year-old adults

The purpose of this study was to develop a regression equation to predict maximal oxygen uptake (VO₂max) based on nonexercise (N-EX) data. All participants (N= 100), ages 18–65 years, successfully completed a maximal graded exercise test (GXT) to assess VO₂max (M= 39.96 mL·kg ^-1· min ^-1, SD = 9.54). The N-EX data collected just before the maximal GXT included the participant’s age; gender; body mass index (BMI); perceived functional ability (PFA) to walk, jog, or run given distances; and current physical activity (PA-R) level. Multiple linear regression generated the following N-EX prediction equation (R =.93, SEE = 3.45 mL·kg ^-1· min ^-1, %SEE= 8.62): VO₂max (mL·kg ^-1· min ^-1) = 48.0730 + (6.1779 x gender; women = 0, men = 1) – (0.2463 × age) – (0.6186 × BMI) + (0.7115 × PFA) + (0.6709 × PA-R). Cross validation using PRESS (predicted residual sum of squares) statistics revealed minimal shrinkage (R _p =.91 and SEE _p = 3.63 mL·kg ^-1· min ^-1); thus, this model should yield acceptable accuracy when applied to an independent sample of adults (ages 18–-65 years) with a similar cardiorespiratory fitness level. Based on standardized β-weights, the PFA variable (0.41) was the most effective at predicting VO₂max followed by age (-0.34), gender (0.33), BMI (-0.27), and PA-R (0.16). This study provides a N-EX regression model that yields relatively accurate results and is a convenient way to predict VO₂max in adult men and women.