Climate variables as predictors of basal metabolic rate: new equations

Abstract

Estimation of basal metabolic rate (BMR) and daily energy expenditure (DEE) in living humans and in fossil hominins can be used to understand the way populations adapt to different environmental and nutritional circumstances. One variable that should be considered in such estimates is climate, which may influence between-population variation in BMR. Overall, populations living in warmer climates tend to have lower BMR than those living in colder climates, even after controlling for body size and composition. Current methods of estimating BMR ignore climate, or deal with its effects in an insufficient manner. This may affect studies that use the factorial method to estimate DEE from BMR, when BMR is not measured but predicted using an equation. The present meta-analysis of published BMR uses stepwise regression to investigate whether the inclusion of climate variables can produce a generally applicable model for human BMR. Regression results show that mean annual temperature and high heat index temperature have a significant effect on BMR, along with body size, age and sex. Based on the regression analysis, equations predicting BMR from body size and climate variables were derived and compared with existing equations. The new equations are generally more accurate and more consistent across climates than the older ones. Estimates of DEE in living and fossil humans using the new equations are compared with estimates using previously published equations, illustrating the utility of including climate variables in estimates of BMR. The new equations derived here may prove useful for future studies of human energy expenditure.