A new predictive equation to calculate resting metabolic rate in athletes

The purposes of the present study were: 1) to examine the accuracy and precision of seven published equations for predicting resting metabolic rate (RMR) in male athletes and 2) to develop a population-specific equation. Setting: The study occurred during a non-intensive training period. The measurements were performed at the Human Physiology laboratory. Participants: Fifty-one male athletes (22 waterpolo, 12 judo, 17 karate) who exercised regularly at least three hours per day. Measures: RMR was measured (mRMR) using indirect calorimetry (ventilated hood system). Besides, mRMR was compared with values predicted (pRMR) using equations of FAO/WHO/UNU, Harris and Benedict, Mifflin et al., Owen et al., Cunningham, Robertson and Reid, Fleisch. Statistical analyses. mRMR was compared with pRMR by means of Student's paired "t" tests, linear regression analysis and the Bland-Altman test. Relationships between mRMR and the different predictive variables were evaluated by Pearson correlation coefficients. The best subset was used to develop the predictive equation for RMR

A new predictive equation to calculate resting metabolic rate in athletes

The purposes of the present study were: 1) to examine the accuracy and precision of seven published equations for predicting resting metabolic rate (RMR) in male athletes and 2) to develop a population-specific equation. Setting: The study occurred during a non-intensive training period. The measurements were performed at the Human Physiology laboratory. Participants: Fifty-one male athletes (22 waterpolo, 12 judo, 17 karate) who exercised regularly at least three hours per day. Measures: RMR was measured (mRMR) using indirect calorimetry (ventilated hood system). Besides, mRMR was compared with values predicted (pRMR) using equations of FAO/WHO/UNU, Harris and Benedict, Mifflin et al., Owen et al., Cunningham, Robertson and Reid, Fleisch. Statistical analyses. mRMR was compared with pRMR by means of Student's paired "t" tests, linear regression analysis and the Bland-Altman test. Relationships between mRMR and the different predictive variables were evaluated by Pearson correlation coefficients. The best subset was used to develop the predictive equation for RMR