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Residual body-mass dependence in $$\dot{\text{V}}$$O₂peak normalization across ratio, allometric and regression–residual methods

Year: 2026
Type: article
Abstract: Conventional ratio-scaled expressions of peak oxygen uptake (VO₂peak; mL·kg⁻¹·min⁻¹) are widely used to normalize aerobic capacity for body size, though residual dependence on body mass may persist. This study examined body-mass dependence in conventional VO₂peak expressions and evaluated allometric and regression–residual approaches for body-size adjustment. Publicly available treadmill cardiopulmonary exercise-testing data from 937 participants (798 males, 139 females) aged 15–59 years in the University of Málaga database were analyzed. VO₂peak was defined as the highest 30-second average oxygen uptake during exercise. Absolute VO₂peak, ratio-scaled VO₂peak, conventional allometric scaling, and sex-specific log–log allometric models were examined. Regression–residual W-scores were derived from sex-specific models and standardized using a T-score metric. Sensitivity analyses compared scaling relationships using single-breath, five-breath, 15-second, and 30-second VO₂peak definitions. Absolute VO₂peak remained positively associated with body mass in both sexes (p < 0.001). Ratio-scaled VO₂peak showed inverse associations with body mass in males (r = − 0.44) and females (r = − 0.26). Sex-specific allometric exponents were 0.422 in males and 0.704 in females. Regression–residual W-scores showed minimal residual association with body mass. Scaling relationships were highly consistent across alternative VO₂peak definitions. Conventional ratio scaling retained substantial residual dependence on body mass. Regression–residual normalization markedly reduced these associations, whereas conventional allometric scaling provided an intermediate correction. Findings were robust across multiple VO₂peak determination procedures.
Authors: Thomas D. Fahey, Miguel A. Rivera
Language: English
Field: Medicine
Open Access status: gold
Estimated APC paid: $2,690
OpenAlex ID: W7208733325
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