ABSTRACT
BACKGROUND: Although resting metabolic rate (RMR) is crucial for understanding athletes' energy requirements, limited information is available on the RMR of Paralympic athletes. OBJECTIVE: The aim of this study was to determine RMR and its predictors in a diverse cohort of Paralympic athletes and evaluate the agreement between measured and predicted RMR from both newly developed and pre-existing equations. DESIGN: This cross-sectional study, conducted between September 2020 and September 2022 in the Netherlands and Norway, assessed RMR in Paralympic athletes by means of ventilated hood indirect calorimetry and body composition by means of dual-energy x-ray absorptiometry. PARTICIPANTS: Sixty-seven Paralympic athletes (male: n = 37; female: n = 30) competing in various sports, with a spinal cord disorder (n = 22), neurologic condition (n = 8), limb deficiency (n = 18), visual or hearing impairment (n = 7), or other disability (n = 12) participated. MAIN OUTCOME MEASURES: RMR, fat-free mass (FFM), body mass, and triiodothyronine (T3) concentrations were assessed. STATISTICAL ANALYSES: Multiple regression analyses were conducted with height, FFM, body mass, sex, T3 concentration, and disabilities as potential predictors of RMR. Differences between measured and predicted RMRs were analyzed for individual accuracy, root mean square error, and intraclass correlation. RESULTS: Mean ± SD RMR was 1386 ± 258 kcal/d for females and 1686 ± 302 kcal/d for males. Regression analysis identified FFM, T3 concentrations, and the presence of a spinal cord disorder, as the main predictors of RMR (adjusted R2 = 0.71; F = 50.3; P < .001). The novel prediction equations based on these data, as well as pre-existing equations of Chun and colleagues and Nightingale and Gorgey performed well on accuracy (>60% of participants within 10% of measured RMR), had good reliability (intraclass correlation >0.78), and low root mean square error (≤141 kcal). CONCLUSIONS: FFM, total T3 concentrations, and presence of spinal cord disorder are the main predictors of RMR in Paralympic athletes. Both the current study's prediction equations and those from Chun and colleagues and Nightingale and Gorgey align well with measured RMR, offering accurate prediction equations for the RMR of Paralympic athletes.
