Predictive resting metabolic rate (RMR) equations are widely used to determine total daily energy expenditure (TDEE). However, it remains unclear whether these predictive RMR equations accurately predict TDEE in the athletic populations. This study published by the European Journal of Sport Science examines the accuracy of 10 commonly used RMR prediction equations in collegiate athletes, both men and women.
RMR was measured using indirect calorimetry and compared to the predicted RMR equations.
WHAT RMR EQUATIONS WERE INCLUDED IN THE STUDY?
This study examined 10 commonly used RMR prediction equations: Cunningham, De Lorenzo, Freire, Harris-Benedict, Mifflin St. Jeor, Nelson, Owen, Tinsley, Watson, and Schofield.
WHAT METHODS WERE USED?
One-hundred eighty-seven National Collegiate Athletic Association Division III men (n=97) and women (n = 90) athletes were recruited to participate in one day of metabolic testing. RMR was measured using indirect calorimetry and body composition was analyzed using air displacement plethysmography. A repeated measures ANOVA with Bonferroni post hoc analyses was selected to determine mean differences between measured and predicted RMR. Linear regression analysis was used to assess the accuracy of each RMR prediction method (p<0.05).
SO, ARE RMR PREDICTION EQUATIONS ACCURATE FOR ATHLETES?
In this particular group of collegiate athletes, all prediction equations significantly underestimated RMR (p<0.001), with the exception of the De Lorenzo and Watson equations (only for measuring RMR on athletic women only, p = 1.00). Because RMR equations may underestimate the actual energy requirements of athletes, the study suggests that “practitioners should interpret such values with caution”.
To download the full study from the European Journal of Sport Science, click here.