The accuracy of ten common resting metabolic rate prediction equations in men and women collegiate athletes.

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS
ACS Applied Bio Materials Pub Date : 2023-10-01 Epub Date: 2022-10-16 DOI:10.1080/17461391.2022.2130098
Jennifer B Fields, Meghan K Magee, Margaret T Jones, Andrew T Askow, Clayton L Camic, Joel Luedke, Andrew R Jagim
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引用次数: 2

Abstract

Predictive resting metabolic rate (RMR) equations are widely used to determine total daily energy expenditure (TDEE). However, it remains unclear whether these predictive RMR equations accurately predict TDEE in the athletic populations. The purpose of this study was to examine the accuracy of 10 commonly used RMR prediction equations (Cunningham, De Lorenzo, Freire, Harris-Benedict, Mifflin St. Jeor, Nelson, Owen, Tinsley, Watson, Schofield) in collegiate men and women athletes. One-hundred eighty-seven National Collegiate Athletic Association Division III men (n = 97) and women (n = 90) athletes were recruited to participate in one day of metabolic testing. RMR was measured using indirect calorimetry and body composition was analyzed using air displacement plethysmography. A repeated measures ANOVA with Bonferroni post hoc analyses was selected to determine mean differences between measured and predicted RMR. Linear regression analysis was used to assess the accuracy of each RMR prediction method (p<0.05). All prediction equations significantly underestimated RMR (p<0.001), although there was no difference between the De Lorenzo and Watson equations and measured RMR (p = 1.00) for women, only. In men, the Tinsley and Freire equations were the most agreeable formulas with the lowest root-mean-square prediction error value of 404 and 412 kcals, respectively. In women, the De Lorenzo and Watson equations were the most agreeable equations with the lowest root-mean-squared error value of 171 and 211 kcals, respectively. The results demonstrate that such RMR equations may underestimate actual energy requirements of athletes and thus, practitioners should interpret such values with caution.Highlights All prediction equations significantly underestimated RMR in men athletes.All prediction equations, except for the De Lorenzo and Watson equations, significantly underestimated RMR in women athletes.Although a significant underestimation of RMR in men athletes, the Freire and Tinsley equations were the most agreeable prediction equations.In women athletes, the De Lorenzo and Watson equations were the most agreeable prediction equations.

男女大学生运动员10个常见静息代谢率预测方程的准确性。
预测静息代谢率(RMR)方程被广泛用于确定每日总能量消耗(TDEE)。然而,目前尚不清楚这些预测RMR方程是否能准确预测运动人群的TDEE。本研究的目的是检验大学男女运动员常用的10个RMR预测方程(Cunningham、De Lorenzo、Freire、Harris Benedict、Mifflin St.Jeor、Nelson、Owen、Tinsley、Watson、Schofield)的准确性。一百八十七名全国大学生体育协会三级男子(n = 97)和妇女(n = 90)名运动员被招募参加为期一天的代谢测试。使用间接量热法测量RMR,并使用空气置换体积描记法分析身体成分。选择Bonferroni事后分析的重复测量方差分析来确定测量和预测RMR之间的平均差异。使用线性回归分析来评估每种RMR预测方法的准确性(ppp = 1.00)。在男性中,Tinsley和Freire方程是最令人满意的公式,其预测均方根误差值最低,分别为404和412千卡。在女性中,De Lorenzo和Watson方程是最令人满意的方程,均方根误差值最低,分别为171和211千卡。结果表明,这种RMR方程可能低估了运动员的实际能量需求,因此,从业者应谨慎解释这些值。所有预测方程都显著低估了男子运动员的RMR。除De Lorenzo和Watson方程外,所有预测方程都显著低估了女运动员的RMR。尽管男子运动员的RMR被严重低估,但Freire和Tinsley方程是最令人满意的预测方程。在女运动员中,De Lorenzo和Watson方程是最令人满意的预测方程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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