Development and validation of new predictive equation for resting energy expenditure in adults with overweight and obesity.

Background & Aims: Accurate predictive equations of resting energy expenditure (REE) are crucial in devising nutritional strategies to manage overweight/obesity, especially in countries where these are highly prevalent. REE is the most common measurement used to estimate energy requirements in the nutritional context; the most accurate method of measuring REE is indirect calorimetry (IC). However, this method is costly and often rarely feasible in many clinical settings. The objective of the present study was to develop and validate a new equation for predicting REE in adults with overweight and obesity.
Methods: This was a cross-sectional study including 410 men and women with overweight and obesity (20-60 y). Participants were randomly assigned; the development group included 200 subjects and the validation group 210 subjects. The new predictive equation was derived using stepwise multiple linear regression analysis. The accuracy of the new equation was compared to several existing predictive equations (PEs). The accuracy rate was calculated as the percentage of subjects whose REE-PE was within ±10% of the REE-IC. REE was measured by IC and anthropometric measurements.
Results: One predictive equation was developed (NEQ) in which weight was the strongest predictor of REE. Compared with others predicted equations already using, the new designed equation showed the less mean bias (Kj/day): NEQ: 25.7, Valencia:129, WHO/FAO/United Nations University: 270, Mifflin-St Jeor: 308, Owen: -808, Carrasco: -1097, Korth: -36.4, Johnstone: -375, Livingstone: -315, De Lorenzo: -28.3, Lazzer: -123, Muller: -145, Huang: -399 and Bernstein: -1335.
Conclusions: The present equation had the highest predictive accuracy in subjects with overweight or obesity compared with the previous equations derived from different populations. Thus, these new equation can be used to assist the nutritional management of these subjects.
(Copyright © 2017 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.)