Cardiorespiratory Fitness Normalized to Fat-Free Mass and Mortality Risk
Cardiorespiratory Fitness Normalized to Fat-Free Mass and Mortality Risk
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DOI：
10.1249/mss.0000000000002289
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发表时间：
2020-07-01
期刊：
影响因子：
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通讯作者：
Harber, Matthew P.
中科院分区：
文献类型：
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作者：
Imboden, Mary T.;Kaminsky, Leonard A.;Harber, Matthew P.
研究目的：呼吸适应性（CRF）与去脂体重（FFM）直接相关，因此，将CRF归一化为FFM（（V）over dotO（2 peakFFM））可能是CRF与运动能力和心肺功能关系的最准确表达。然而，（V）对dotO（2 peakFFM）（mL. kgFFM-1.min（-1））预测死亡率的影响在很大程度上尚未探索。本研究旨在主要评估（V）over dotO（2 peakFFM）与表面健康成年人的全因和特定疾病死亡风险之间的关系。此外，本研究试图比较（V）相对于dotO（2 peakFFM）与（V）相对于dotO（2 peak）归一化为总体重（（V）相对于dotO（2 peakTBW））的死亡率结局的预测能力。研究对象包括2905名成年人（1555名男性，1350名女性），他们在1970年至2016年期间完成了心肺运动试验，以确定CRF。使用皮褶法评估身体组成以估计FFM。呼吸适应性表示为（V）对dotO（2 peakTBW）和（V）对dotO（2 peakFFM）。参与者在心肺运动试验后随访19.0 +/- 11.7年，以了解死亡率结果。进行Cox比例风险模型以确定（V）与dotO（2 peakFFM）与死亡率结局的关系。评估参数估计值以比较CRF的预测能力，CRF表示为（V）对dotO（2 peakTBW）和（V）对dotO（2 peakFFM）。结果总的来说，（V）超过dotO（2 peakFFM）与全因死亡率、心血管疾病死亡率和癌症死亡率呈负相关，每增加1个FFM-1.min（-1），风险分别降低16.2%、8.4%和8.0%（P< 0.01）。mL.kg此外，参数估计值的评估显示，（V）超过dotO（2 peakFFM）是比（V）超过dotO（2 peakTBW）更强的全因死亡率预测因子（参数估计值，-0.49 vs -0.16）。结论在考虑CRF与死亡风险的关系时，身体成分是一个重要因素。临床医生应该考虑在可行的情况下将CRF标准化为FFM，因为这将增强该指标的预测能力。
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) over dotO(2peakFFM)) may be the most accurate expression of CRF as related to exercise performance and cardiorespiratory function. However, the influence of (V) over dotO(2peakFFM)(mL.kg FFM-1.min(-1)) on predicting mortality has been largely unexplored. This study aimed to primarily assess the relationship between (V) over dotO(2peakFFM)and all-cause and disease-specific mortality risk in apparently healthy adults. Further, this study sought to compare the predictive ability of (V) over dotO(2peakFFM)to (V) over dotO(2peak)normalized to total body weight ((V) over dotO(2peakTBW)) 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) over dotO(2peakTBW)and (V) over dotO(2peakFFM). 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) over dotO(2peakFFM) with mortality outcomes. Parameter estimates were assessed to compare the predictive ability of CRF expressed as (V) over dotO(2peakTBW)and (V) over dotO(2peakFFM). Results Overall, (V) over dotO(2peakFFM) 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-1.min(-1)i mprovement, respectively (P< 0.01). Further, assessment of the parameter estimates showed (V) over dotO(2peakFFM) to be a significantly stronger predictor of all-cause mortality than (V) over dotO(2peakTBW) (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.