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Related Experiment Videos

Comparison of predictive equations for resting metabolic rate in healthy nonobese and obese adults: a systematic

David Frankenfield1, Lori Roth-Yousey, Charlene Compher

  • 1Department of Clinical Nutrition, Milton S. Hershey Medical Center, Hershey, PA, USA.

Journal of the American Dietetic Association
|May 11, 2005
PubMed
Summary

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Estimating resting metabolic rate (RMR) using predictive equations can lead to significant errors. The Mifflin-St Jeor equation is most accurate, but indirect calorimetry is recommended for precise RMR measurement in clinical practice.

Area of Science:

  • Nutrition Science
  • Metabolic Research
  • Clinical Practice Guidelines

Background:

  • Accurate energy needs assessment is crucial for nutrition care plans.
  • Metabolic rate is commonly estimated using predictive equations, but these may introduce significant errors.
  • A systematic review was conducted to evaluate the accuracy of predictive equations for resting metabolic rate (RMR).

Purpose of the Study:

  • To systematically review the literature on the accuracy of predictive equations for RMR.
  • To compare the validity of commonly used RMR predictive equations.
  • To inform decisions regarding the necessity of measuring RMR via indirect calorimetry.

Main Methods:

  • A systematic literature search identified studies validating RMR predictive equations in diverse populations.

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  • Inclusion criteria focused on studies reporting individual data for RMR estimation.
  • Evidence was evaluated using standardized tools, with conclusion statements and grades developed.

    • Main Results:

    • The Mifflin-St Jeor equation demonstrated the highest reliability, predicting RMR within 10% of measured values for more individuals than other equations.
    • The Mifflin-St Jeor equation also exhibited the narrowest error range.
    • Older adults and US-residing ethnic minorities were underrepresented in equation development and validation studies.

    Conclusions:

    • While Mifflin-St Jeor is the most reliable predictive equation, significant errors can occur when applied to individuals, particularly certain age and ethnic groups.
    • Indirect calorimetry, using evidence-based protocols, eliminates RMR estimation errors.
    • Clinical judgment is advised when using predictive equations; indirect calorimetry is recommended when estimations fail clinically relevant accuracy.