NONEXERCISE REGRESSION-MODELS TO ESTIMATE PEAK OXYGEN-CONSUMPTION

The purpose of this study was to develop a VO2peak prediction model de rived from nonexercise (N-EX) based predictors. VO2peak was measured u sing a walking treadmill protocol with 229 females and 210 males betwe en 20 and 79 yr of age (mean +/- SD: 38.62 +/- 10.36 ml . kg(-1). min( -1)). Subjects were randomly divided into validation (V) (85% of total ; N = 374) and cross-validation (CV) (15% of total; N = 65) groups. Th e V group was used to validate generalized and gender specific models using stepwise multiple regression procedures with gender, age and age percent body fat, and a physical activity code (AC). The generalized ml . kg(-1). min(-1) (R(2) = 0.77, SEE = 4.90 ml . kg(-1). min(-1), SE E% = 12.7%) and gender-specific (females: R2 = 0.72, SEE = 4.64 ml . k g(-1). min(-1) males: R(2) = 0.72, SEE = 5.02 ml . kg(-1). min(-1)) mo dels were highly accurate relative to N-EX and exercise based models i n the literature. Cross-validation procedures were used to evaluate mo del stability. The generalized model was stable across the total CV gr oup and various CV subsamples (by gender, decade-wide age groups, and AC groups), but not across groups similar in VO2peak. These results su ggest that N-EX models can be valid predictors of VO2peak for heteroge nous samples.