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.

Ontogenetic scaling of the human nose in a longitudinal sample: Implications for genus Homo facial evolution

“…Scaling of basal metabolic rate (top) and fat-free mass (bottom) in males (gray) and females (black), ages 3 to 21 years. Each data point represents a sample mean obtained from published studies of BMR in children and was originally compiled as part of a meta-analysis by Froehle (2008). females, and was selected from the larger growth study sample based on the completeness of the individual radiographic sequences as well as the quality of the lateral cephalograms with respect to our variables of interest (Table 1). Measurements were collected at nine different observations beginning at 3.0 to 4.0 years of age through age 201 years.…”

“…Scaling of basal metabolic rate (top) and fat-free mass (bottom) in males (gray) and females (black), ages 3 to 21 years. Each data point represents a sample mean obtained from published studies of BMR in children and was originally compiled as part of a meta-analysis by Froehle (2008). …”

A Conceptual Modeling Approach to Health-Related Urban Well-Being

“…Therefore, habituation is the result of an ongoing adaption. On the one hand, with respect to the thermal environment, the adjustment can be both seasonal, e.g., changes in the comfort temperature between seasons [67,68], and long-term, e.g., adjustment of the basal metabolic rate of people living in different climate regions [69]. On the other hand, noise annoyance is significantly and positively correlated with confounding variables like the length of residence or the years of employment [70].…”

BMR in a Brazilian adult probability sample: the Nutrition, Physical Activity and Health Survey

“…The observed increase in the values of body mass of the population will represent greater estimated BMR and consequently higher energy requirement which will not be derived from actual higher energy expenditure. Before revisions in PAL values are implemented it is important to improve the prediction of BMR (9) because, even though the magnitude of these improvements may be small, it is well recognized that small positive energy balance over time may affect overweight and obesity (10) . Thus, more information on BMR in segments of the population from different regions of the world is necessary to better estimate the energy requirement in population-level nutritional studies.…”