Evaluation of Different Equations for Resting Metabolic Rate Prediction in Female Combat Sports Athletes.

Autor: Tortu, Erkan, Birol, Abdulkadir, Aksarı, Meryem
Předmět:
Zdroj: Montenegrin Journal of Sports Science & Medicine; Oct2023, Vol. 12 Issue 2, p41-48, 8p
Abstrakt: Only a few studies have produced equations that can estimate resting metabolic rate (RMR) in female athletes, but the accuracy of these equations for combat athletes has not yet been tested. The aim of this study was to evaluate the 12 different equations which are commonly using to determine resting metabolite rate (RMR) in the literature. Twenty-three female combat sport athletes (24.23± 3.39 years; 166.8 ± 5.3 cm; 63.13±6.53 kg; 8.78±3.19 experience years.; 56.40±3.43 VO2 mL/kg/min) were participated this study in voluntarily basis. A cross-validation approach used to compare the accuracy of 12 commonly prediction equations with measured RMR by indirect calorimetry to determine RMR in female combat sports athletes. All the predictive equation was underestimated RMR when compared with the measured RMR (p < 0.05) and the smallest mean difference (92.46 ± 210.38 kcal·d-1) was observed for Altman & Dittmer equation amongst the 12 predictive equations. The Altman & Dittmer equation was accurately predicted 16 out of 30 subjects' RMR value within the range ±10%. However, based on the Bland-Altman plots, the prediction equations were not accurately nor precisely predicted RMR in the current sample of female combat sport athletes. The results in the present study showed that the Altman & Dittmer equation is most suitable equation to predict RMR amongst 12 equations. Although the Altman & Dittmer equation was resulted with smallest mean difference, it seems that there is need to further research with longitudinal approach to understand the effects of training intensity and body mass changes on RMR in order to develop the formulas already exist used commonly. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index