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Are Predictive Equations for Estimating Resting Energy Expenditure Accurate in Asian Indian Male Weightlifters?
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)...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Medknow Publications & Media Pvt Ltd
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5477436/ https://www.ncbi.nlm.nih.gov/pubmed/28670532 http://dx.doi.org/10.4103/ijem.IJEM_563_16 |
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author | Joseph, Mini Gupta, Riddhi Das Prema, L. Inbakumari, Mercy Thomas, Nihal |
author_facet | Joseph, Mini Gupta, Riddhi Das Prema, L. Inbakumari, Mercy Thomas, Nihal |
author_sort | Joseph, Mini |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-5477436 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Medknow Publications & Media Pvt Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-54774362017-07-01 Are Predictive Equations for Estimating Resting Energy Expenditure Accurate in Asian Indian Male Weightlifters? Joseph, Mini Gupta, Riddhi Das Prema, L. Inbakumari, Mercy Thomas, Nihal Indian J Endocrinol Metab Original Article 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. Medknow Publications & Media Pvt Ltd 2017 /pmc/articles/PMC5477436/ /pubmed/28670532 http://dx.doi.org/10.4103/ijem.IJEM_563_16 Text en Copyright: © 2017 Indian Journal of Endocrinology and Metabolism http://creativecommons.org/licenses/by-nc-sa/3.0 This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as the author is credited and the new creations are licensed under the identical terms. |
spellingShingle | Original Article Joseph, Mini Gupta, Riddhi Das Prema, L. Inbakumari, Mercy Thomas, Nihal Are Predictive Equations for Estimating Resting Energy Expenditure Accurate in Asian Indian Male Weightlifters? |
title | Are Predictive Equations for Estimating Resting Energy Expenditure Accurate in Asian Indian Male Weightlifters? |
title_full | Are Predictive Equations for Estimating Resting Energy Expenditure Accurate in Asian Indian Male Weightlifters? |
title_fullStr | Are Predictive Equations for Estimating Resting Energy Expenditure Accurate in Asian Indian Male Weightlifters? |
title_full_unstemmed | Are Predictive Equations for Estimating Resting Energy Expenditure Accurate in Asian Indian Male Weightlifters? |
title_short | Are Predictive Equations for Estimating Resting Energy Expenditure Accurate in Asian Indian Male Weightlifters? |
title_sort | are predictive equations for estimating resting energy expenditure accurate in asian indian male weightlifters? |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5477436/ https://www.ncbi.nlm.nih.gov/pubmed/28670532 http://dx.doi.org/10.4103/ijem.IJEM_563_16 |
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