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.