Predict Resting Metabolic Rate: A Systematic Review

Background/Purpose: Resting metabolic rate (RMR) is the rate of energy expenditure when at rest. It represents the largest fraction of an individual’s daily energy expenditure. To be able to accurately predict or estimate RMR is one of the most important components in energy balance research and intervention practice. Since a metabolic chamber, the golden standard of RMR measure, is expensive and time consuming, economical easy-to-implement methods are needed.  The purpose of this study was, through a systematical review, to examine published prediction equations and explore other predictors that may help improve the predictions.  

Method: The databases of PubMed were searched for English language studies from 1960 to 2014 and search terms used were “resting metabolic rate (RMR)”, “prediction equation”, and “predictors”, etc.

Analysis/Results: A total of 23,968 articles were found through PubMed, but only 65 papers qualified for the review. A careful review indicated age, sex, weight, height, temperature (both body and external temperature), genetics, eating patterns, and exercising habits are related to one’s RMR. There were five commonly used equations for predicting RMR: the Harris-Benedict (1919), Mifflin (1989), Owen (1985), Schofield (weight) (1985), and Schofield (weight and height) (1985) equations. However, only several traits such as age, sex, height, and weight were included in these prediction equations, making the prediction equation less reliable. Future studies should examine if other traits could improve RMR predictions. 

Conclusions: Existing RMR prediction equations did not include all potential influencing traits; thus, indicating possible improvement in RMR predictions. Experimental studies are needed to examine this possibility.