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Simplified Resting Metabolic Rate—Predicting Formulas for Normal-Sized and Obese Individuals
Version of Record online: 6 SEP 2012
2005 North American Association for the Study of Obesity (NAASO)
Volume 13, Issue 7, pages 1255–1262, July 2005
How to Cite
Livingston, E. H. and Kohlstadt, I. (2005), Simplified Resting Metabolic Rate—Predicting Formulas for Normal-Sized and Obese Individuals. Obesity Research, 13: 1255–1262. doi: 10.1038/oby.2005.149
- Issue online: 6 SEP 2012
- Version of Record online: 6 SEP 2012
- Received for review May 11, 2004; Accepted in final form May 06, 2005
- body surface area;
- resting metabolic rate;
- allometric scaling;
- Harris-Benedict formula
Objective: Resting metabolic rate (RMR) is known to be proportional to body weight and to follow allometric scaling principles. We hypothesized that RMR can be predicted from an allometric formula with weight alone as an independent variable.
Research Methods and Procedures: An allometric, power-law scaling model was fit to RMR measurements obtained from a cohort of patients being treated for weight loss. This, as well as many of the commonly used RMR-predicting formulas, was tested for RMR prediction ability against a large publicly available RMR database. Bland-Altman analysis was used to determine the efficacy of the various RMR-predicting formulas in obese and non-obese subjects.
Results: Power law modeling of the RMR—body weight relationship yielded the following RMR-predicting equations: RMRWomen = 248 × Weight0.4356 − (5.09 × Age) and RMRMen = 293 × Weight0.4330 − (5.92 × Age). Partial correlation analysis revealed that age significantly contributed to RMR variance and was necessary to include in RMR prediction formulas. The James, allometric, and Harris-Benedict formulas all yielded reasonable RMR predictions for normal sized and obese subjects.
Discussion: A simple power formula relating RMR to body weight can be a reasonable RMR estimator for normal-sized and obese individuals but still requires an age term and separate formulas for men and women for the best possible RMR estimates. The apparent performance of RMR-predicting formulas is highly dependent on the methodology employed to compare the various formulas.