Validation of resting metabolic rate equations in obese and non-obese young healthy adults

被引:15
|
作者
Al-Domi, Hayder [1 ]
Al-Shorman, Alaa [1 ]
机构
[1] Univ Jordan, Sch Agr, Dept Nutr & Food Sci, Amman 11942, Jordan
关键词
D O I
10.1016/j.clnesp.2018.04.008
中图分类号
R15 [营养卫生、食品卫生]; TS201 [基础科学];
学科分类号
100403 ;
摘要
Background and aims: Although validating resting metabolic rate (RMR) prediction equations in different populations is warranted to estimate total energy requirements, there are no data about the accuracy and applicability of RMR predictive equations in young healthy Jordanians. This study aimed to test the validity of predicted RMR using four prediction equations and its agreement with RMR measured using indirect calorimetry in healthy young obese and non-obese Jordanian adults. Methods: Predicted RMR was tested for agreement with indirect calorimetry. HarriseBenedict, Food and Agriculture Organization/World Health Organization/United Nations University, Mifflin and Owen equations were used to predict RMR. A total of 406 (200 females, 206 males) normal bodyweight, overweight, and obese healthy young adults aged 18e25 years were included. Results: Of all tested equations, HarriseBenedict equation showed no significant differences compared to measured RMR using indirect calorimetry (p > 0.05) in normal bodyweight (1374.1 +/- 72.5 vs. 1347.6 +/- 333.4), overweight (1513.1 +/- 66.8 vs. 1492.9 +/- 374.8) and obese (1673.5 +/- 178.4 vs. 1736.4 +/- 386.9) females. While significant differences (p < 0.05) were found in all male participants. The other studied equations showed significant differences (p <= 0.05) compared to measured RMR in gender based groups with different bodyweight status. Conclusion: Only HarriseBenedict equation was the most accurate in predicting RMR among females regardless of bodyweight status. Apart from that, these equations did not perform well at the group level. The tested prediction equations further underestimated RMR. Future studies aiming at validating RMR prediction equations in different populations are warranted in order to understand the factors that could affect the accuracy of RMR prediction. (c) 2018 European Society for Clinical Nutrition and Metabolism. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码:91 / 96
页数:6
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