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

✍ Scribed by Rebecca E. Hasson; Cheryl A. Howe; Bryce L. Jones; Patty S. Freedson

• Book ID: 113756152
• Publisher: Elsevier Science
• Year: 2011
• Tongue: English
• Weight: 338 KB
• Volume: 14
• Category: Article
• ISSN: 1440-2440
• DOI: 10.1016/j.jsams.2011.02.010

✦ Synopsis

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.