A Maximal Graded Exercise Test to Accurately Predict VO_2max in 18–65-Year-Old Adults

Abstract

The purpose of this study was to develop an age-generalized regression model to predict maximal oxygen uptake (VO_2max) 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 [HR_max] = 185.2 ± 12.4 beats per minute (bpm); maximal respiratory exchange ratio [RER_max] = 1.18 ± 0.05; maximal rating of perceived exertion (RPE_max) = 19.1 ± 0.7) during the GXT to assess VO_2max (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): VO_2max (mL·kg⁻¹·min⁻¹) = 13.160 + (3.314 × gender; females = 0, males = 1) − (.131 × age) − (.334 × body mass index (BMI)) + (5.177 × treadmill speed; mph) + (1.315 × treadmill grade; %). Cross validation using predicted residual sum of squares (PRESS) statistics revealed minimal shrinkage (R_p  = .93 and SEE _p  = 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 β-weights indicate that treadmill speed (.583) was the most effective at predicting VO_2max followed by treadmill grade (.356), age (−.197), gender (.183), and BMI (−.148). This study provides a relatively accurate regression model to predict VO_2max 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.

Key words:

• maximum oxygen uptake
• exercise testing
• cardiorespiratory fitness (CRF)