Literature DB >> 20045143

Poor prediction of resting energy expenditure in obese women by established equations.

Britta Wilms1, Sebastian M Schmid, Barbara Ernst, Martin Thurnheer, Manfred J Mueller, Bernd Schultes.   

Abstract

The objective of the study was to evaluate the accuracy of established prediction equations that calculate resting energy expenditure (REE) in obese women. This was a cross-sectional study. In 273 mildly to severely obese women (age, 41.7 +/- 13.2 years; body mass index, 42.8 +/- 7.0 kg/m(2)), REE was measured by indirect calorimetry (mREE), along with fat mass (FM) and fat-free mass (FFM) by bioelectrical impedance analysis. Eleven established equations were used to predict REE (pREE), with 9 equations basing on the anthropometric parameters body weight and height and 2 equations including body composition parameters (FM, FFM). All equations provided pREE values that significantly correlated with mREE (r > 0.66, P < .001), although 8 equations systematically underestimated mREE (P < .05). Of note, even the best equation was not able to accurately predict mREE with a deviation of less than +/-10% in more than 70% of the tested women. Furthermore, equations using body composition data were not superior in predicting REE as compared with equations exclusively including anthropometric variables. Multiple linear regression analyses revealed 2 new equations--one including body weight and age and another including FM, FFM, and age--that explained 56.9% and 57.2%, respectively, of variance in mREE. However, when these 2 new equations were applied to an independent sample of 33 obese women, they also provided an accurate prediction (+/-10%) of mREE in only 56.7% and 60.6%, respectively, of the women. Data show that an accurate prediction of REE is not feasible using established equations in obese women. Equations that include body composition parameters as assessed by bioelectrical impedance analysis do not increase the accuracy of prediction. Based on our results, we conclude that calculating REE by standard prediction equations does not represent a reliable alternative to indirect calorimetry for the assessment of REE in obese women. Copyright 2010 Elsevier Inc. All rights reserved.

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Year:  2009        PMID: 20045143     DOI: 10.1016/j.metabol.2009.11.011

Source DB:  PubMed          Journal:  Metabolism        ISSN: 0026-0495            Impact factor:   8.694


  8 in total

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Journal:  Am J Clin Nutr       Date:  2014-02-05       Impact factor: 7.045

2.  Comparison of five equations for estimating resting energy expenditure in Chinese young, normal weight healthy adults.

Authors:  Zhi-yong Rao; Xiao-ting Wu; Bin-miao Liang; Mao-yun Wang; Wen Hu
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Journal:  BMJ Open       Date:  2015-04-08       Impact factor: 2.692

4.  Validity of Predictive Equations for Resting Energy Expenditure Developed for Obese Patients: Impact of Body Composition Method.

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Journal:  Nutrients       Date:  2018-01-10       Impact factor: 5.717

5.  Prediction and evaluation of resting energy expenditure in a large group of obese outpatients.

Authors:  M Marra; I Cioffi; R Sammarco; C Montagnese; M Naccarato; V Amato; F Contaldo; F Pasanisi
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6.  Resting Energy Expenditure during Breastfeeding: Body Composition Analysis vs. Predictive Equations Based on Anthropometric Parameters.

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7.  New Predictive Equations for Resting Energy Expenditure in Normal to Overweight and Obese Population.

Authors:  Ali M Almajwal; Mahmoud M A Abulmeaty
Journal:  Int J Endocrinol       Date:  2019-12-18       Impact factor: 3.257

8.  Resting Energy Expenditure in the Elderly: Systematic Review and Comparison of Equations in an Experimental Population.

Authors:  Honoria Ocagli; Corrado Lanera; Danila Azzolina; Gianluca Piras; Rozita Soltanmohammadi; Silvia Gallipoli; Claudia Elena Gafare; Monica Cavion; Daniele Roccon; Luca Vedovelli; Giulia Lorenzoni; Dario Gregori
Journal:  Nutrients       Date:  2021-01-29       Impact factor: 5.717

  8 in total

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