Objective: This study compared the accuracy of four commonly used RMR prediction equations to measured RMR obtained from the MedGem® metabolic analyzer. Design and Methods: Height, weight and RMR were measured in 362 healthy individuals [51% female; body mass index (BMI): 17.6–50.6 kg m−2; ages: 18–60 years; 17.4% non-white]. Following a 4 h fast, participants rested in the supine position after which RMR was measured. RMR was estimated using four commonly used prediction equations: Harris–Benedict, Mifflin–St. Jeor, Owen, and WHO/FAO/UNU. Accuracy was determined by calculating the percentage of predicted RMR values that were within ±10% of measured RMR values. Main effects of sex, BMI, age, and race/ethnicity were assessed using repeated measures ANCOVAs. Results: For all participants combined, the Harris–Benedict, Mifflin, and WHO/FAU/UNU equations similarly predicted RMR values within ±10% of measured RMR values (57.5, 56.4, and 55.2% of the sample, respectively). When participant data were stratified by sex, BMI, age, and race/ethnicity, the accuracy of each regression equation varied dramatically. The Harris–Benedict equation over-predicted RMR in 18–29 year olds. The Owen equation under-predicted RMR in both sexes, all three BMI categories, 18–49 year olds and White participants. The Mifflin under-predicted RMR in both sexes, normal weight individuals, 40–60 year olds, and non-Hispanic White participants. The WHO/FAO/UNU over-predicted RMR in males, overweight participants, and 50–60 year olds. Conclusions: When examining the entire sample, the Harris–Benedict, Mifflin, and WHO/FAU/UNU equations yielded similar levels of agreement with the MedGem® measured RMR. However, clinical judgment and caution should be used when applying these prediction equations to special populations or small groups.
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Published online: April 04, 2011
Accepted: February 26, 2011
Received in revised form: January 9, 2011
Received: September 5, 2010
© 2011 Sports Medicine Australia. Published by Elsevier Inc. All rights reserved.