Association of energy availability with resting metabolic rates in competitive female teenage runners: a cross-sectional study. Issue 1 (16th November 2021) - Kinoshita, Norimitsu; Uchiyama, Eriko; Ishikawa-Takata, Kazuko; Yamada, Yuka; Okuyama, Kenta
Abstract: Background: Resting metabolic rate (RMR) has been examined as a proxy for low energy availability (EA). Previous studies have been limited to adult athletes, despite the serious health consequences of low EA, particularly during adolescence. This study aimed to explore the relationship between RMR and EA in competitive teenage girl runners. Methods: Eighteen girl runners (mean ± standard-deviation; age, 16.8 ± 0.9 years; body mass, 45.6 ± 5.2 kg, %fat, 13.5 ± 4.2 %) in the same competitive high-school team were evaluated. Each runner was asked to report dietary records with photos and training logs for seven days. Energy intake (EI) was assessed by Registered Dietitian Nutritionists. The runners were evaluated on a treadmill with an indirect calorimeter to yield individual prediction equations for oxygen consumption using running velocity and heart rate (HR). Exercise energy expenditure (EEE) was calculated by the equations based on training logs and HR. Daily EA was calculated by subtracting EEE from EI. The daily means of these variables were calculated. RMR was measured early in the morning by whole-room calorimetry after overnight sleep on concluding the final day of the seven-day assessment. The ratio of measured RMR to predicted RMR (RMR ratio) was calculated by race, age, sex-specific formulae, and Cunningham's equation. Body composition was measured using dual-energy X-ray absorptiometry. Bivariate correlation analyses were used to examine the relationship between variables. Results: RMR, EI, EEE, and EA were 26.9 ± 2.4, 56.8 ± 15.2, 21.7 ± 5.9, and 35.0 ± 15.0 kcal⋅kg −1 FFM⋅d −1, respectively. RMR reduced linearly with statistical significance, while EA decreased to a threshold level (30 kcal⋅kg −1 FFM⋅d −1 ) ( r= 0.58, p= 0.048). Further reduction in RMR was not observed when EA fell below the threshold. There was no significant correlation between RMR ratios and EA, irrespective of the prediction formulae used. Conclusions: These results suggest that RMR does not reduce with a decrease in EA among highly competitive and lean teenage girl runners. RMR remains disproportionally higher than expected in low EA states. Free-living teenage girl runners with low EA should be cautiously identified using RMR as a proxy for EA change.