Related Experiment Video
Updated: Aug 20, 2025

Determining the Contribution of the Energy Systems During Exercise
Published on: March 20, 2012
Determination of energy expenditure in professional cyclists using power data: Validation against doubly labeled
Bas Van Hooren1, Maartje Cox1, Gerard Rietjens2
1Department of Nutrition and Movement Sciences, NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University Medical Centre+, Maastricht, The Netherlands.
Introduction:
Accurate determination of total daily energy expenditure (TDEE) in athletes is important for optimal performance and injury prevention, but current approaches are insufficiently accurate. We therefore developed an approach to determine TDEE in professional cyclists based on power data, basal metabolic rate (BMR), and a non-exercise physical activity level (PAL) value, and compared energy expenditure (EE) between multi-day and single-day races.
Methods:
Twenty-one male professional cyclists participated. We measured: (1) BMR, (2) the relationship between power output and EE during an incremental cycling test, which was used to determine EE during exercise (EEE ), and (3) TDEE using doubly labeled water (DLW). A non-exercise PAL-value was obtained by subtracting EEE from TDEE and dividing this by BMR.
Results:
Measured BMR was 7.9 ± 0.8 MJ/day, which was significantly higher than predicted by the Oxford equations. A new BMR equation for elite endurance athletes was therefore developed. Mean TDEE was 31.7 ± 2.8 and 27.3 ± 2.8 MJ/day during the Vuelta a España and Ardennes classics, while EEE was 17.4 ± 1.8 and 10.1 ± 1.4 MJ/day, respectively. Non-exercise PAL-values were 1.8 and 2.0 for the Vuelta and Ardennes classics, respectively, which is substantially higher than currently used generic PAL-values.
Conclusion:
We show that the proposed approach leads to a more accurate estimation of non-exercise EE than the use of a generic PAL-value in combination with BMR predictive equations developed for non-elite athletes, with the latter underestimating non-exercise EE by ~28%. The proposed approach may therefore improve nutritional strategies in professional cyclists.

