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Accuracy of predictive equations for resting metabolic rate in Korean athletic and non-athletic adolescents

BACKGROUND/OBJECTIVES: Athletes generally desire changes in body composition in order to enhance their athletic performance. Often, athletes will practice chronic energy restrictions to attain body composition changes, altering their energy needs. Prediction of resting metabolic rates (RMR) is impor...

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Autores principales: Kim, Jae-Hee, Kim, Myung-Hee, Kim, Gwi-Sun, Park, Ji-Sun, Kim, Eun-Kyung
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Korean Nutrition Society and the Korean Society of Community Nutrition 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4523480/
https://www.ncbi.nlm.nih.gov/pubmed/26244075
http://dx.doi.org/10.4162/nrp.2015.9.4.370
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author Kim, Jae-Hee
Kim, Myung-Hee
Kim, Gwi-Sun
Park, Ji-Sun
Kim, Eun-Kyung
author_facet Kim, Jae-Hee
Kim, Myung-Hee
Kim, Gwi-Sun
Park, Ji-Sun
Kim, Eun-Kyung
author_sort Kim, Jae-Hee
collection PubMed
description BACKGROUND/OBJECTIVES: Athletes generally desire changes in body composition in order to enhance their athletic performance. Often, athletes will practice chronic energy restrictions to attain body composition changes, altering their energy needs. Prediction of resting metabolic rates (RMR) is important in helping to determine an athlete's energy expenditure. This study compared measured RMR of athletic and non-athletic adolescents with predicted RMR from commonly used prediction equations to identify the most accurate equation applicable for adolescent athletes. SUBJECTS/METHODS: A total of 50 athletes (mean age of 16.6 ± 1.0 years, 30 males and 20 females) and 50 non-athletes (mean age of 16.5 ± 0.5 years, 30 males and 20 females) were enrolled in the study. The RMR of subjects was measured using indirect calorimetry. The accuracy of 11 RMR prediction equations was evaluated for bias, Pearson's correlation coefficient, and Bland-Altman analysis. RESULTS: Until more accurate prediction equations are developed, our findings recommend using the formulas by Cunningham (-29.8 kcal/day, limits of agreement -318.7 and +259.1 kcal/day) and Park (-0.842 kcal/day, limits of agreement -198.9 and +196.9 kcal/day) for prediction of RMR when studying male adolescent athletes. Among the new prediction formulas reviewed, the formula included in the fat-free mass as a variable [RMR = 730.4 + 15 × fat-free mass] is paramount when examining athletes. CONCLUSIONS: The RMR prediction equation developed in this study is better in assessing the resting metabolic rate of Korean athletic adolescents.
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spelling pubmed-45234802015-08-04 Accuracy of predictive equations for resting metabolic rate in Korean athletic and non-athletic adolescents Kim, Jae-Hee Kim, Myung-Hee Kim, Gwi-Sun Park, Ji-Sun Kim, Eun-Kyung Nutr Res Pract Original Research BACKGROUND/OBJECTIVES: Athletes generally desire changes in body composition in order to enhance their athletic performance. Often, athletes will practice chronic energy restrictions to attain body composition changes, altering their energy needs. Prediction of resting metabolic rates (RMR) is important in helping to determine an athlete's energy expenditure. This study compared measured RMR of athletic and non-athletic adolescents with predicted RMR from commonly used prediction equations to identify the most accurate equation applicable for adolescent athletes. SUBJECTS/METHODS: A total of 50 athletes (mean age of 16.6 ± 1.0 years, 30 males and 20 females) and 50 non-athletes (mean age of 16.5 ± 0.5 years, 30 males and 20 females) were enrolled in the study. The RMR of subjects was measured using indirect calorimetry. The accuracy of 11 RMR prediction equations was evaluated for bias, Pearson's correlation coefficient, and Bland-Altman analysis. RESULTS: Until more accurate prediction equations are developed, our findings recommend using the formulas by Cunningham (-29.8 kcal/day, limits of agreement -318.7 and +259.1 kcal/day) and Park (-0.842 kcal/day, limits of agreement -198.9 and +196.9 kcal/day) for prediction of RMR when studying male adolescent athletes. Among the new prediction formulas reviewed, the formula included in the fat-free mass as a variable [RMR = 730.4 + 15 × fat-free mass] is paramount when examining athletes. CONCLUSIONS: The RMR prediction equation developed in this study is better in assessing the resting metabolic rate of Korean athletic adolescents. The Korean Nutrition Society and the Korean Society of Community Nutrition 2015-08 2015-05-22 /pmc/articles/PMC4523480/ /pubmed/26244075 http://dx.doi.org/10.4162/nrp.2015.9.4.370 Text en ©2015 The Korean Nutrition Society and the Korean Society of Community Nutrition http://creativecommons.org/licenses/by-nc/3.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Research
Kim, Jae-Hee
Kim, Myung-Hee
Kim, Gwi-Sun
Park, Ji-Sun
Kim, Eun-Kyung
Accuracy of predictive equations for resting metabolic rate in Korean athletic and non-athletic adolescents
title Accuracy of predictive equations for resting metabolic rate in Korean athletic and non-athletic adolescents
title_full Accuracy of predictive equations for resting metabolic rate in Korean athletic and non-athletic adolescents
title_fullStr Accuracy of predictive equations for resting metabolic rate in Korean athletic and non-athletic adolescents
title_full_unstemmed Accuracy of predictive equations for resting metabolic rate in Korean athletic and non-athletic adolescents
title_short Accuracy of predictive equations for resting metabolic rate in Korean athletic and non-athletic adolescents
title_sort accuracy of predictive equations for resting metabolic rate in korean athletic and non-athletic adolescents
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4523480/
https://www.ncbi.nlm.nih.gov/pubmed/26244075
http://dx.doi.org/10.4162/nrp.2015.9.4.370
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