Anthropometric and body composition equations to predict resting energy expenditure in overweight and obese men and women living in a temperate climate

Abstract

The resting energy expenditure (REE) is commonly determined by indirect calorimetry. However, in clinical and nutrition settings, it is usually unfeasible and thus prediction equations are employed using anthropometric (ANT) and/or body composition (BC) data. Epidemiological evidence has shown an association between ambient temperature and body weight in humans, and particularly high prevalence of obesity when living in temperate climates. The aim was to develop equations to predict REE of overweight and obese living in a temperate climate all-year round and to determine the accuracy of traditional equations in this population. METHODS: Overweight and obese men and women (n=174) living permanently in Gran Canaria agreed to participate (age: 18-70 yr; BMI>27 kg.m2). REE was measured in fasting conditions by indirect calorimetry (Vmax N29). For anthropometric assessment, body weight and height were measured with a balance scale while body composition by DXA. Stepwise multiple regression analysis was used to determine the best predictors of REE in our population by two models (ANT and BC-based). The agreement of our measured REE was compared to the estimation by 20 widely employed ANT-based equations by calculating: bias (absolute values and %), the limit of agreement (LA) (upper LA=bias+1.96xSD; lower LA=bias-1.96xSD), concordance correlation coefficient (CCC). The % of subjects whose predicted REE fell within 10% of the measured REE was taken as a measure of accuracy. Statistical significance was set at p<0.05.