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ultra-endurance athletes, resting metabolic rate, predictive equation, indirect calorimetry, energy metabolism
Background/aims: Only a few studies determined some equations to predict resting metabolic rate (RMR) in endurance athletes, however the validity in ultra-endurance athletes, such as triathletes and ultra-marathoners, had not been examined previously. The aim of this study was to assess the accuracy of commonly used RMR predictive equations (Harris-Benedict, Mifflin-St. Jeor, Cunningham, WHO/FAO/UNU (calculated by using body mass and height and body mass alone), Wang, and Sabounchi (Structure 4, 5, and 11) equations) comparing with measured RMR in ultra-endurance athletes. Methods: Male (n=15) and female (n=15) ultra-endurance athletes age 23 to 55 years from Ankyra Sports Club were included. The Bland-Altman plot was performed to determine mean bias and limits of agreement between measured and predicted RMRs. Linear regression analysis was used to determine the accuracy of each predictive equation by computing the standard error of estimate and root-mean-squared prediction error (RMSPE). Results: Mifflin-St. Jeor equation was found to be the best predictive equation with lowest RMSPE (275.85 kcal/day for men and 388.34 kcal/day for women) and mean difference (3.04±285.51 kcal/day for men and 185.57±353.10 for women) in ultra-endurance athletes. The Cunningham equation could be used in estimating RMR in male athletes (RMSPE, 310.77 kcal/day, the bias between measured vs. predicted RMR, 147.68±283.04 kcal/day). Conclusions: The Mifflin- St. Jeor and Cunningham equations for men and the Mifflin-St. Jeor equation in women could be used with caution in the absence of indirect calorimetry in ultra-endurance athletes. All other predictions significantly underestimated RMR for both sexes.