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

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 component in the development of nutrition support therapy, therefore we determined the accuracy of commonly used predictive equations against RMR measured by indirect calorimetry among healthy young underweight females. 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 bioelectric 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. 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 estimated 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. 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.