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Nonexercise regression models to estimate peak oxygen consumption
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1995
Year
Gait AnalysisPhysical ActivityEngineeringEnergy EfficiencyGas Exchange ProcessPeak Oxygen ConsumptionVo2peak Prediction ModelValid PredictorsBody CompositionKinesiologyExercisePhysical ExerciseApplied PhysiologyStatisticsHealth SciencesPhysical FitnessRespiration (Physiology)Functional Data AnalysisExercise ScienceExercise PhysiologyTissue OxygenationPathological GaitHuman MovementPhysical Activity Code
The purpose of this study was to develop a VO2peak prediction model derived from nonexercise (N-EX) based predictors. VO2peak was measured using a walking treadmill protocol with 229 females and 210 males between 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. The V group was used to validate generalized and gender-specific models using stepwise multiple regression procedures with gender, age and age2, percent body fat, and a physical activity code (AC). The generalized ml.kg-1.min-1 (R2 = 0.77, SEE = 4.90 ml.kg-1.min-1, SEE% = 12.7%) and gender-specific (females: R2 = 0.72, SEE = 4.64 ml.kg-1.min-1; males: R2 = 0.72, SEE = 5.02 ml.kg-1.min-1) models were highly accurate relative to N-EX and exercise based models in the literature. Cross-validation procedures were used to evaluate model stability. The generalized model was stable across the total CV group and various CV subsamples (by gender, decade-wide age groups, and AC groups), but not across groups similar in VO2peak. These results suggest that N-EX models can be valid predictors of VO2peak for heterogenous samples.