New Predictive Resting Metabolic Rate Equations for High-Level Athletes: A Cross-validation Study

Area of Science:

• Sports Science
• Human Physiology
• Metabolic Research

Background:

• Accurate estimation of resting metabolic rate (RMR) is crucial for athletes.
• Existing predictive equations for RMR may lack precision in athletic populations.

Purpose of the Study:

• To assess agreement between measured RMR and predicted RMR using various equations.
• To develop and validate two novel RMR predictive equations for high-level athletes.

Main Methods:

• Indirect calorimetry measured RMR in 102 athletes.
• Skinfolds assessed body composition.
• Statistical analyses including ANOVA, regression, and Bland-Altman plots evaluated agreement and accuracy.
• New equations were developed using multiple linear regression.

Main Results:

• The two new equations demonstrated good agreement and accuracy for RMR prediction in athletes.
• Cunningham's equation performed best among existing options for both sexes.
• Harris & Benedict's equation showed significant inaccuracy, particularly in males.

Conclusions:

• The newly developed equations provide accurate RMR estimation for high-level athletes.
• Cunningham's equation is a suitable alternative from existing methods.
• Harris & Benedict's equation should be avoided for RMR prediction in male athletes.