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Prediction and evaluation of resting energy expenditure in a large group of obese outpatients
BACKGROUND/OBJECTIVES: The aim of this study was to compare resting energy expenditure (REE) measured (MREE) by indirect calorimetry (IC) and REE predicted (PREE) from established predictive equations in a large sample of obese Caucasian adults. SUBJECTS/METHODS: We evaluated 1851 obese patients (bo...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5418562/ https://www.ncbi.nlm.nih.gov/pubmed/28163316 http://dx.doi.org/10.1038/ijo.2017.34 |
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author | Marra, M Cioffi, I Sammarco, R Montagnese, C Naccarato, M Amato, V Contaldo, F Pasanisi, F |
author_facet | Marra, M Cioffi, I Sammarco, R Montagnese, C Naccarato, M Amato, V Contaldo, F Pasanisi, F |
author_sort | Marra, M |
collection | PubMed |
description | BACKGROUND/OBJECTIVES: The aim of this study was to compare resting energy expenditure (REE) measured (MREE) by indirect calorimetry (IC) and REE predicted (PREE) from established predictive equations in a large sample of obese Caucasian adults. SUBJECTS/METHODS: We evaluated 1851 obese patients (body mass index (BMI)>30 kg m(−)(2)) aged between 18a and 65 years. Data were obtained by comparing MREE with PREE, derived from different equations, within and between normal weight and obese groups. The mean differences between PREE and MREE as well as the accuracy prediction within ±10% level were investigated in the whole sample and in three subgroups, classified by BMI (Group 1=30–39.9 kg m(−)(2); Group 2=40–49.9 kg m(−)(2); Group 3>50 kg m(−)(2)). RESULTS: We observed that FAO, Henry and Muller3 (body composition (BC)) equations provided good mean PREE–MREE (bias −0.7, −0.3 and 0.9% root mean standard error (RMSE) 273, 263 and 269 kcal per day, respectively); HB and Henry equations were more accurate individually (57 and 56.9%). Only the Muller1 (BC) equation gave the lowest PREE–MREE difference (bias −1.7% RMSE 228 kcal per day) in females, while Johnstone and De Lorenzo equations were the most accurate (55.1 and 54.8%). When the sample was split into three subgroups according to BMI, no differences were found in males; however, the majority of the equations included in this study failed to estimate REE in severely obese females (BMI>40 kg m(−)(2)). Overall, prediction accuracy was low (~55%) for all predictive equations, regardless of BMI. CONCLUSIONS: Different established equations can be used for estimating REE at the population level in both sexes. However, the accuracy was very low for all predictive equations used, particularly among females and when BMI was high, limiting their use in clinical practice. Our findings suggest that the validation of new predictive equations would improve the accuracy of REE prediction, especially for severely obese subjects (BMI>40 kg m(−)(2)). |
format | Online Article Text |
id | pubmed-5418562 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-54185622017-05-18 Prediction and evaluation of resting energy expenditure in a large group of obese outpatients Marra, M Cioffi, I Sammarco, R Montagnese, C Naccarato, M Amato, V Contaldo, F Pasanisi, F Int J Obes (Lond) Original Article BACKGROUND/OBJECTIVES: The aim of this study was to compare resting energy expenditure (REE) measured (MREE) by indirect calorimetry (IC) and REE predicted (PREE) from established predictive equations in a large sample of obese Caucasian adults. SUBJECTS/METHODS: We evaluated 1851 obese patients (body mass index (BMI)>30 kg m(−)(2)) aged between 18a and 65 years. Data were obtained by comparing MREE with PREE, derived from different equations, within and between normal weight and obese groups. The mean differences between PREE and MREE as well as the accuracy prediction within ±10% level were investigated in the whole sample and in three subgroups, classified by BMI (Group 1=30–39.9 kg m(−)(2); Group 2=40–49.9 kg m(−)(2); Group 3>50 kg m(−)(2)). RESULTS: We observed that FAO, Henry and Muller3 (body composition (BC)) equations provided good mean PREE–MREE (bias −0.7, −0.3 and 0.9% root mean standard error (RMSE) 273, 263 and 269 kcal per day, respectively); HB and Henry equations were more accurate individually (57 and 56.9%). Only the Muller1 (BC) equation gave the lowest PREE–MREE difference (bias −1.7% RMSE 228 kcal per day) in females, while Johnstone and De Lorenzo equations were the most accurate (55.1 and 54.8%). When the sample was split into three subgroups according to BMI, no differences were found in males; however, the majority of the equations included in this study failed to estimate REE in severely obese females (BMI>40 kg m(−)(2)). Overall, prediction accuracy was low (~55%) for all predictive equations, regardless of BMI. CONCLUSIONS: Different established equations can be used for estimating REE at the population level in both sexes. However, the accuracy was very low for all predictive equations used, particularly among females and when BMI was high, limiting their use in clinical practice. Our findings suggest that the validation of new predictive equations would improve the accuracy of REE prediction, especially for severely obese subjects (BMI>40 kg m(−)(2)). Nature Publishing Group 2017-05 2017-02-28 /pmc/articles/PMC5418562/ /pubmed/28163316 http://dx.doi.org/10.1038/ijo.2017.34 Text en Copyright © 2017 The Author(s) http://creativecommons.org/licenses/by-nc-nd/4.0/ This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/4.0/ |
spellingShingle | Original Article Marra, M Cioffi, I Sammarco, R Montagnese, C Naccarato, M Amato, V Contaldo, F Pasanisi, F Prediction and evaluation of resting energy expenditure in a large group of obese outpatients |
title | Prediction and evaluation of resting energy expenditure in a large group of obese outpatients |
title_full | Prediction and evaluation of resting energy expenditure in a large group of obese outpatients |
title_fullStr | Prediction and evaluation of resting energy expenditure in a large group of obese outpatients |
title_full_unstemmed | Prediction and evaluation of resting energy expenditure in a large group of obese outpatients |
title_short | Prediction and evaluation of resting energy expenditure in a large group of obese outpatients |
title_sort | prediction and evaluation of resting energy expenditure in a large group of obese outpatients |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5418562/ https://www.ncbi.nlm.nih.gov/pubmed/28163316 http://dx.doi.org/10.1038/ijo.2017.34 |
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