8/7/2023 0 Comments Mifflin st jeor equation![]() ![]() All other predictions significantly underestimated RMR for both sexes. Jeor equation in women could be used with caution in the absence of indirect calorimetry in ultra-endurance athletes. SETTINGS AND DESIGN:Cross-sectional study. Patients were categorized according to sex and diagnosis. Jeor and Cunningham equations for men and the Mifflin-St. AIM:This study tests the degree of agreement between measured resting energy expenditure by indirect calorimetry and predicted resting energy expenditure by Harris Benedict and Mifflin-St Jeor equations. The Cunningham equation could be used in estimating RMR in male athletes (RMSPE, 310.77 kcal/day, the bias between measured vs. Jeor equation was found to be the best predictive equation with lowest RMSPE (275.85 kcal/day for men and 388.34 kcal/day for women) and mean difference (3.04☒85.51 kcal/day for men and 185.57☓53.10 for women) in ultra-endurance athletes. Linear regression analysis was used to determine the accuracy of each predictive equation by computing the standard error of estimate and root-mean-squared prediction error (RMSPE). The Bland-Altman plot was performed to determine mean bias and limits of agreement between measured and predicted RMRs. Methods: Male (n=15) and female (n=15) ultra-endurance athletes age 23 to 55 years from Ankyra Sports Club were included. Jeor, Cunningham, WHO/FAO/UNU (calculated by using body mass and height and body mass alone), Wang, and Sabounchi (Structure 4, 5, and 11) equations) comparing with measured RMR in ultra-endurance athletes. A comparative study of four predictive equations found that the Mifflin-St Jeor equation is more likely than the other equations to predict RMR to within 10 of that measured. The aim of this study was to assess the accuracy of commonly used RMR predictive equations (Harris-Benedict, Mifflin-St. Background/aims: Only a few studies determined some equations to predict resting metabolic rate (RMR) in endurance athletes, however the validity in ultra-endurance athletes, such as triathletes and ultra-marathoners, had not been examined previously. ![]()
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