Predicting the resting metabolic rate of 30–60-year-old Australian males

Objectives This study: (a) generated regression equations for predicting the resting metabolic rate (RMR) of 30-60-y-old Australian males from age, height, mass and fat-free mass (FFM); and (b) cross-validated RMR prediction equations which are currently used in Australia against our measured and predicted values.Design A power analysis demonstrated that 41 subjects would enable the detection of (alpha=0.05, power=0.80) statistically and physiologically significant differences of 8% between predicted/measured RMRs in this study and those predicted from the equations of other investigators.Subjects Forty-one males ([X]+/-s.d.:, 44.8+/-8.6 y; 83.50+/-11.32 kg; 179.1+/-5.0 cm) were recruited for this study.Interventions The following variables were measured: skinfold thicknesses; RMR using open circuit indirect calorimetry; and FFM via a four-compartment (fat mass, total body water, bone mineral mass and residual) body composition model.Results A multiple regression equation using mass, height and age as predictors correlated 0.745 with RMR and the s.e.e. was 509 kJ/day. Inclusion of FFM as a predictor increased both the correlation and the precision of prediction, but there was no difference between FFM via the four-compartment model (r=0.816, s.e.e.=429 kJ/day) and that predicted from skinfold thicknesses (r=0.805, s.e.e.=441 kJ/day).Conclusions Cross-validation analyses emphasised that equations need to be generated from a large database for the prediction of the RMR of 30-60-y-old Australian males.