Department of Kinesiology & Sport Management, Texas Tech University, Lubbock, TX 79424, USA.
Appl Physiol Nutr Metab. 2019 Apr;44(4):397-406. doi: 10.1139/apnm-2018-0412. Epub 2018 Sep 21.
Estimation of resting metabolic rate (RMR) is an important step for prescribing an individual's energy intake. The purpose of this study was to evaluate the validity of portable indirect calorimeters and RMR prediction equations in muscular physique athletes. Twenty-seven males (n = 17; body mass index (BMI): 28.8 ± 2.0 kg/m; body fat: 12.5% ± 2.7%) and females (n = 10; BMI: 22.8 ± 1.6 kg/m; body fat: 19.2% ± 3.4%) were evaluated. The reference RMR value was obtained from the ParvoMedics TrueOne 2400 indirect calorimeter, and the Cosmed Fitmate and Breezing Metabolism Tracker provided additional RMR estimates. Existing RMR prediction equations based on body weight (BW) or dual-energy X-ray absorptiometry fat-free mass (FFM) were also evaluated. Errors in RMR estimates were assessed using validity statistics, including t tests with Bonferroni correction, linear regression, and calculation of the standard error of the estimate, total error, and 95% limits of agreement. Additionally, new prediction equations based on BW (RMR (kcal/day) = 24.8 × BW (kg) + 10) and FFM (RMR (kcal/day) = 25.9 × FFM (kg) + 284) were developed using stepwise linear regression and evaluated using leave-one-out cross-validation. Nearly all existing BW- and FFM-based prediction equations, as well as the Breezing Tracker, did not exhibit acceptable validity and typically underestimated RMR. The ten Haaf and Weijs (PLoS ONE, 9: e1084602014 (2014)) and Cunningham (1980) (Am. J. Clin. Nutr. 33: 2372-2374 (1980)) FFM-based equations may produce acceptable RMR estimates, although the Cosmed Fitmate and newly developed BW- and FFM-based equations may be most suitable for RMR estimation in male and female physique athletes. Future research should provide additional external cross-validation of the newly developed equations to refine the ability to predict RMR in physique athletes.
静息代谢率 (RMR) 的估计是为个体能量摄入制定处方的重要步骤。本研究的目的是评估便携式间接测热仪和 RMR 预测方程在肌肉体格运动员中的有效性。评估了 27 名男性(n = 17;体重指数 (BMI):28.8 ± 2.0 kg/m;体脂:12.5% ± 2.7%)和 10 名女性(n = 10;BMI:22.8 ± 1.6 kg/m;体脂:19.2% ± 3.4%)。参考 RMR 值是从 ParvoMedics TrueOne 2400 间接测热仪获得的,Cosmed Fitmate 和 Breezing Metabolism Tracker 提供了额外的 RMR 估计值。还评估了基于体重 (BW) 或双能 X 射线吸收法去脂体重 (FFM) 的现有 RMR 预测方程。使用有效性统计数据评估 RMR 估计值的误差,包括带有 Bonferroni 校正的 t 检验、线性回归以及估计值、总误差和 95%一致性限的标准误差的计算。此外,还使用逐步线性回归开发了基于 BW(RMR(千卡/天)= 24.8 × BW(kg)+ 10)和 FFM(RMR(千卡/天)= 25.9 × FFM(kg)+ 284)的新预测方程,并使用留一法交叉验证进行了评估。几乎所有现有的基于 BW 和 FFM 的预测方程以及 Breezing Tracker 都没有表现出可接受的有效性,通常会低估 RMR。Ten Haaf 和 Weijs(PLoS ONE,9:e1084602014(2014 年))和 Cunningham(1980 年)(Am. J. Clin. Nutr. 33:2372-2374(1980 年))的 FFM 基础方程可能会产生可接受的 RMR 估计值,尽管 Cosmed Fitmate 和新开发的基于 BW 和 FFM 的方程可能最适合男性和女性体格运动员的 RMR 估计。未来的研究应提供新开发方程的额外外部交叉验证,以提高预测体格运动员 RMR 的能力。