Resting metabolic rate in healthy Singaporeans: Performance of the Harris-Benedict equation and a new predictive model

Prediction equations for resting metabolic rate (RMR) are valuable in managing patients’ weight; however, no accurate equation exists for Singaporeans. To develop and cross-validate a predictive regression equation for RMR in Singaporeans, using indirect calorimetry as the reference method. 104 healthy Singaporeans (34.3 ± 12.2 years) participated, comprising 34 men and 70 women. Anthropometric measurements and demographics information were obtained from participants. RMR was measured via indirect calorimetry (TrueOne 2400 system). Stepwise regression analysis was used to develop the most parsimonious predictive equation. Performance of the equation was evaluated using ordinary least products (OLP) regression and Bland–Altman analysis, whilst internal cross-validation was performed by use of the predicted residual sum of squares (PRESS) method. To compare the new equation with existing ones, the performance of the Harris-Benedict equation was also evaluated. The best predictive equation takes the form RMR(kcal) = 918 + 16.5(weight)-135.7(gender) - 1152(Waist-to-height-ratio) +0.014(International Physical Activity Questionnaire Score), where gender = 1 (female) or 0 (male). OLP regression revealed no systematic bias for the new equation. Bland–Altman analysis showed that its total (systematic and random) error was 212 kcal. Internal model validation using the PRESS method revealed minimal reduction in predictive accuracy. In contrast, OLP regression showed a significant pattern of over-prediction by the Harris-Benedict equation (y-intercept = −280 kcal; 95%CI, −100 to −461 kcal). Our new equation outperformed the Harris-Benedict equation in accurately predicting RMR in Singaporeans. Comprising easily obtained anthropometric and self-reported measures, we envisage its potential relevance in clinical and epidemiological settings.