Development and Validation of a Resting Metabolic Rate Equation for Elite Cyclists

Accurate determination of energy expenditure (EE) in elite endurance athletes is critical for personalised nutrition strategies aimed at maintaining health and optimising performance. The resting metabolic rate (RMR) constitutes a large portion of daily EE, but existing RMR predictive equations are not suitable for this population due to differences in body composition and energy intake and expenditure between the general population and elite endurance athletes.

The RMR of 48 male and 30 female elite cyclists (UCI ProTeam or WorldTour level) was measured with indirect calorimetry using a ventilated hood system. A new RMR predictive equation was developed using height, mass, and sex as predictors. Stepwise forward regression was used to select the independent variables to be included in the equation. The strength of the association between individual predictors and RMR was quantified through partial correlations. The new equation was validated with a leave-one-out cross-validation (LOOCV). Correlations between RMR estimated with existing equations and measured RMR were evaluated.

The final equation was RMR (kcal/day) = -288.98 + 5.77×height (cm) + 14.25×mass (kg) + 180.79×sex (male=1). Partial correlations of height, mass, and sex were 0.19, 0.41, and 0.42, respectively. Root mean squared error of the LOOCV was 134.78 kcal/day. The LOOCV model showed comparable absolute agreement between the newly developed equation and measured RMR (overestimation of 0.65 kcal/day) as the Ten Haaf equation (underestimation of 10.24 kcal/day), which both performed better than other existing equations (underestimations of 149.17-212.85 kcal/day.

This study provides RMR data for the largest cohort of elite cyclists to date. The newly developed RMR formula provides specificity to elite cyclists and can be readily applied to endurance athletes of similar age, body composition, and with similar energy intake and expenditure.