Comparison of Indirect Calorimetry and Predictive Equations in Estimating Resting Metabolic Rate in Underweight Females

Background: Underweight as a public health problem in young women is associated with nutritional deficiencies, menstrual irregularity, eating disorders, reduced fertility, etc. Since resting metabolic rate (RMR) is a necessary compo-nent in the development of nutrition support therapy, therefore we determined the accuracy of commonly used pre-dictive equations against RMR measured by indirect calorimetry among healthy young underweight females. Methods: This cross-sectional study was conducted on 104 underweight females aged 18-30 years old with body mass index (BMI) <18.5 kg/m2 in 2013 . After collecting anthropometric data, body composition was measured by bioelec-tric impedance analysis (BIA). RMR was measured by using indirect calorimetry (FitMate™) and was estimated by 10 commonly used predictive equations. Comparisons were conducted using paired t-test. The accuracy of the RMR equations was evaluated on the basis of the percentage of subjects’ predicted RMR within 10% of measured RMR. Results: The mean BMI of subjects was 17.3±1.3 kg/m2. The measured RMR ranged 736-1490 kcal/day (mean 1084.7±175 kcal/day). Findings indicated that except Muller and Abbreviation, other equations significantly over es-timated RMR, compared to measured value (P<0.05). As an individual prediction accuracy, these predictive equations showed poor performance with the highest accuracy rate of 54.8% for Muller equation (22.1% under and 23.1% over-prediction) and 43.3% for Abbreviation equation (31.7% under and 25% over-prediction), the percentage bias was 1.8% and 0.63% and RMSE was 162 and 173 kcal/d, respectively. Conclusion: Although Muller equation gave fairly acceptable prediction, more suitable new equations are needed to be developed to help better management of nutritional plans in young underweight people.