Comparison of Harris Benedict and Mifflin-ST Jeor equations with indirect calorimetry in evaluating resting energy expenditure

Indian J Med Sci. 2008 Jul;62(7):283-90. doi: 10.4103/0019-5359.42024.

Abstract

Background: An understanding of energy expenditure in hospitalized patients is necessary to determine optimal energy supply. The metabolic rate can be measured or estimated by equations, but estimation is by far the most common method.

Aim: This study tests the degree of agreement between measured resting energy expenditure by indirect calorimetry and predicted resting energy expenditure by Harris Benedict and Mifflin-St Jeor equations. Patients were categorized according to sex and diagnosis.

Settings and design: Cross-sectional study.

Materials and methods: In 60 randomly selected patients, aged between 18 and 83 years, resting energy expenditure (REE) was measured by indirect calorimetry and compared with the predicted equations of Harris Benedict and Mifflin-St Jeor.

Statistical analysis: Statistical analysis was performed by using the method of Bland-Altman, one sample t-test and Pearson's correlation.

Results: There was no statistically significant difference between measured and predicted resting energy expenditure by both equations, in all cases as a whole and each group. The only statistically significant difference was seen between measured resting energy expenditure and its predicted equivalent by Mifflin-St equation when patients were categorized according to their sex. Limits of agreements were wide for both equations in all cases and each category so clinical significance was considerable.

Conclusions: At a group level Harris-Benedict equation is suitable for predicting REE but at an individual level, both equations have wide limits of agreement and clinically important differences in REE would be obtained.

Publication types

  • Comparative Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Adult
  • Aged
  • Aged, 80 and over
  • Calorimetry, Indirect*
  • Cross-Sectional Studies
  • Energy Metabolism*
  • Female
  • Humans
  • Inpatients
  • Iran
  • Male
  • Middle Aged
  • Statistics as Topic*