Accuracy of four resting metabolic rate prediction equations: effects of sex, body mass index, age, and race/ethnicity

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 4h 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.