PURPOSE: Cardiorespiratory fitness (CRF) is known to be directly related to fat-free mass (FFM), therefore, it has been suggested that normalizing CRF to FFM (V˙O2peakFFM) may be the most accurate expression of CRF as related to exercise performance and cardiorespiratory function. However, the influence of V˙O2peakFFM (mL·kg FFM·min) on predicting mortality has been largely unexplored. This study aimed to primarily assess the relationship between V˙O2peakFFM and all-cause and disease-specific mortality risk in apparently healthy adults. Further, this study sought to compare the predictive ability of V˙O2peakFFM to V˙O2peak normalized to total body weight (V˙O2peakTBW) for mortality outcomes. METHODS: Participants included 2905 adults (1555 men, 1350 women) who completed a cardiopulmonary exercise test between 1970 and 2016 to determine CRF. Body composition was assessed using the skinfold method to estimate FFM. Cardiorespiratory fitness was expressed as V˙O2peakTBW and V˙O2peakFFM. Participants were followed for 19.0 ± 11.7 yr after their cardiopulmonary exercise test for mortality outcomes. Cox-proportional hazard models were performed to determine the relationship of V˙O2peakFFM with mortality outcomes. Parameter estimates were assessed to compare the predictive ability of CRF expressed as V˙O2peakTBW and V˙O2peakFFM. RESULTS: Overall, V˙O2peakFFM was inversely related to all-cause, cardiovascular disease, and cancer mortality, with a 16.2%, 8.4%, and 8.0% lower risk per 1 mL·kg FFM·min improvement, respectively (P < 0.01). Further, assessment of the parameter estimates showed V˙O2peakFFM to be a significantly stronger predictor of all-cause mortality than V˙O2peakTBW (parameter estimates, -0.49 vs -0.16). CONCLUSIONS: Body composition is an important factor when considering the relationship between CRF and mortality risk. Clinicians should consider normalizing CRF to FFM when feasible, because it will strengthen the predictive power of the measure.
PURPOSE:Cardiorespiratory fitness (CRF) is known to be directly related to fat-free mass (FFM), therefore, it has been suggested that normalizing CRF to FFM (V˙O2peakFFM) may be the most accurate expression of CRF as related to exercise performance and cardiorespiratory function. However, the influence of V˙O2peakFFM (mL·kg FFM·min) on predicting mortality has been largely unexplored. This study aimed to primarily assess the relationship between V˙O2peakFFM and all-cause and disease-specific mortality risk in apparently healthy adults. Further, this study sought to compare the predictive ability of V˙O2peakFFM to V˙O2peak normalized to total body weight (V˙O2peakTBW) for mortality outcomes. METHODS:Participants included 2905 adults (1555 men, 1350 women) who completed a cardiopulmonary exercise test between 1970 and 2016 to determine CRF. Body composition was assessed using the skinfold method to estimate FFM. Cardiorespiratory fitness was expressed as V˙O2peakTBW and V˙O2peakFFM. Participants were followed for 19.0 ± 11.7 yr after their cardiopulmonary exercise test for mortality outcomes. Cox-proportional hazard models were performed to determine the relationship of V˙O2peakFFM with mortality outcomes. Parameter estimates were assessed to compare the predictive ability of CRF expressed as V˙O2peakTBW and V˙O2peakFFM. RESULTS: Overall, V˙O2peakFFM was inversely related to all-cause, cardiovascular disease, and cancer mortality, with a 16.2%, 8.4%, and 8.0% lower risk per 1 mL·kg FFM·min improvement, respectively (P < 0.01). Further, assessment of the parameter estimates showed V˙O2peakFFM to be a significantly stronger predictor of all-cause mortality than V˙O2peakTBW (parameter estimates, -0.49 vs -0.16). CONCLUSIONS: Body composition is an important factor when considering the relationship between CRF and mortality risk. Clinicians should consider normalizing CRF to FFM when feasible, because it will strengthen the predictive power of the measure.
Authors: Nicole E Logan; Daniel R Westfall; Lauren B Raine; Sheeba A Anteraper; Laura Chaddock-Heyman; Susan Whitfield-Gabrieli; Arthur F Kramer; Charles H Hillman Journal: Med Sci Sports Exerc Date: 2022-06-24
Authors: Matthew P Harber; McKenzie Metz; James E Peterman; Mitchell H Whaley; Bradley S Fleenor; Leonard A Kaminsky Journal: PLoS One Date: 2020-12-01 Impact factor: 3.240
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