Assessing energy requirements is a fundamental activity in clinical dietetic practice. The aim of this study was to investigate which resting energy expenditure (REE) predictive equations are the best alternatives to indirect calorimetry before and after an interdisciplinary therapy in Brazilian obese women. In all, twelve equations based on weight, height, sex, age, fat-free mass and fat mass were tested. REE was measured by indirect calorimetry. The interdisciplinary therapy consisted of nutritional, physical exercise, psychological and physiotherapy support during the course of 1 year. The average differences between measured and predicted REE, as well as the accuracy at the ±10 % level, were evaluated. Statistical analysis included paired t tests, intraclass correlation coefficients and Bland-Altman plots. Validation was based on forty obese women (BMI 30-39·9 kg/m2). Our major findings demonstrated a wide variation in the accuracy of REE predictive equations before and after weight loss in non-morbid, obese women. The equations reported by Harris-Benedict and FAO/WHO/United Nations University (UNU) were the only ones that did not show significant differences compared with indirect calorimetry and presented a bias <5 %. The Harris-Benedict equation provided 40 and 47·5 % accurate predictions before and after therapy, respectively. The FAO equation provided 35 and 47·5 % accurate predictions. However, the Bland-Altman analysis did not show good agreement between these equations and indirect calorimetry. Therefore, the Harris-Benedict and FAO/WHO/UNU equations should be used with caution for obese women. The need to critically re-assess REE data and generate regional and more homogeneous REE databases for the target population is reinforced.
Keywords: FFM fat-free mass; FM fat mass; ICC intraclass correlation coefficient; REE resting energy expenditure; RMSE root mean sum of squared errors; Indirect calorimetry; Obesity; Predictive equations; Weight loss.