Resting metabolic rate in female rugby players: differences in measured versus predicted values - O'Neill, J. E. R. G.; Walsh, C. S.; McNulty, S. J.; Gantly, H. C.; Corish, M. E.; Crognale, D.; Horner, K. (The Journal of Strength and Conditioning Research, 2022)
This study investigated (a) the accuracy of resting metabolic rate (RMR) prediction equations in female rugby players and (b) factors that might explain poor prediction accuracy in some individuals. Resting metabolic rate was assessed in 36 female elite and subelite rugby players (age: 18-35 years, fat-free mass (FFM): 43-63 kg, fat mass %: 15-41%). After pretest standardization (24-hour exercise avoidance and 12-hour overnight fast), RMR was measured by indirect calorimetry and compared with predicted values determined by Harris-Benedict, Cunningham, Ten Haaf, Jagim and Watson equations. Body composition was assessed by air displacement plethysmography, muscle damage indicated by creatine kinase, and risk of low energy availability (LEA) by LEA in Females Questionnaire. Measured RMR was 1,651 ± 167 kcal/d. The Cunningham, Ten Haaf, and Watson (body mass) predicted values did not differ from measured (p > 0.05), while all other predicted values differed significantly (p < 0.001). Individually, prediction accuracy to within 10% varied widely depending on the equation used (range 44% [n = 16] to 86% [n = 31]). Three of the 5 individuals whose values were outside 10% of the measured value using the best performing Ten Haaf FFM equation could be explained by muscle damage or LEA. These measures may be useful to assist in understanding why measured RMR may be lower or higher than predicted in some athletes. Overall, the Ten Haaf equations showed the best accuracy, suggesting these equations may be most suitable for this population. The findings demonstrate the importance of considering the population studied when determining the most appropriate prediction equation to use.