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用于估算亚洲印度男性举重运动员静息能量消耗的预测方程准确吗?

Are Predictive Equations for Estimating Resting Energy Expenditure Accurate in Asian Indian Male Weightlifters?

作者信息

Joseph Mini, Gupta Riddhi Das, Prema L, Inbakumari Mercy, Thomas Nihal

机构信息

Department of Home Science, Government College for Women, Thiruvananthapuram, Kerala, India.

Department of Endocrinology, Diabetes and Metabolism, Christian Medical College, Vellore, Tamil Nadu, India.

出版信息

Indian J Endocrinol Metab. 2017 Jul-Aug;21(4):515-519. doi: 10.4103/ijem.IJEM_563_16.

Abstract

BACKGROUND

The accuracy of existing predictive equations to determine the resting energy expenditure (REE) of professional weightlifters remains scarcely studied. Our study aimed at assessing the REE of male Asian Indian weightlifters with indirect calorimetry and to compare the measured REE (mREE) with published equations. A new equation using potential anthropometric variables to predict REE was also evaluated.

MATERIALS AND METHODS

REE was measured on 30 male professional weightlifters aged between 17 and 28 years using indirect calorimetry and compared with the eight formulas predicted by Harris-Benedicts, Mifflin-St. Jeor, FAO/WHO/UNU, ICMR, Cunninghams, Owen, Katch-McArdle, and Nelson. Pearson correlation coefficient, intraclass correlation coefficient, and multiple linear regression analysis were carried out to study the agreement between the different methods, association with anthropometric variables, and to formulate a new prediction equation for this population.

RESULTS

Pearson correlation coefficients between mREE and the anthropometric variables showed positive significance with suprailiac skinfold thickness, lean body mass (LBM), waist circumference, hip circumference, bone mineral mass, and body mass. All eight predictive equations underestimated the REE of the weightlifters when compared with the mREE. The highest mean difference was 636 kcal/day (Owen, 1986) and the lowest difference was 375 kcal/day (Cunninghams, 1980). Multiple linear regression done stepwise showed that LBM was the only significant determinant of REE in this group of sportspersons. A new equation using LBM as the independent variable for calculating REE was computed. REE for weightlifters = -164.065 + 0.039 (LBM) (confidence interval -1122.984, 794.854]. This new equation reduced the mean difference with mREE by 2.36 + 369.15 kcal/day (standard error = 67.40).

CONCLUSION

The significant finding of this study was that all the prediction equations underestimated the REE. The LBM was the sole determinant of REE in this population. In the absence of indirect calorimetry, the REE equation developed by us using LBM is a better predictor for calculating REE of professional male weightlifters of this region.

摘要

背景

现有的用于确定职业举重运动员静息能量消耗(REE)的预测方程的准确性鲜有研究。我们的研究旨在通过间接测热法评估亚洲印度男性举重运动员的REE,并将测量的REE(mREE)与已发表的方程进行比较。还评估了一个使用潜在人体测量变量预测REE的新方程。

材料与方法

使用间接测热法对30名年龄在17至28岁之间的男性职业举重运动员进行REE测量,并与Harris-Benedicts、Mifflin-St. Jeor、FAO/WHO/UNU、ICMR、Cunninghams、Owen、Katch-McArdle和Nelson预测的八个公式进行比较。进行Pearson相关系数、组内相关系数和多元线性回归分析,以研究不同方法之间的一致性、与人体测量变量的相关性,并为该人群制定一个新的预测方程。

结果

mREE与人体测量变量之间的Pearson相关系数显示,与髂上皮肤褶厚度、瘦体重(LBM)、腰围、臀围、骨矿物质质量和体重呈正相关。与mREE相比,所有八个预测方程均低估了举重运动员的REE。最高平均差异为636千卡/天(Owen,1986),最低差异为375千卡/天(Cunninghams,1980)。逐步进行的多元线性回归表明,LBM是该组运动员中REE的唯一重要决定因素。计算了一个以LBM作为自变量计算REE的新方程。举重运动员的REE = -164.065 + 0.039(LBM)(置信区间-1122.984,794.854)。这个新方程使与mREE的平均差异减少了2.36 + 369.15千卡/天(标准误差 = 67.40)。结论:本研究的重要发现是所有预测方程均低估了REE。LBM是该人群中REE的唯一决定因素。在没有间接测热法的情况下,我们使用LBM开发的REE方程是计算该地区职业男性举重运动员REE的更好预测指标。

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