Determining the accuracy of predictive equations for resting metabolic rate in athletes

Abstract

The Resting Metabolic Rate (RMR) is an amount of energy that the body burns at complete rest and it is necessary for to maintaining the vital functions. It is most accurately determined by Indirect Calorimetry (IC), a method that measures oxygen intake and carbon dioxide output in order to estimate energy expenditure. Predictive equations for RMR are mathematical formulas based on factors such as age, sex, weight and height. The aim of this study is to compare the accuracy of six commonly used predictive equations for RMR with its’ measured value obtained by indirect calorimetry in athletes of both genders. Fifty-one male and 39 female athletes from different sports disciplines were included. The body composition analysis was performed by Bioelectrical impedance analyzer In Body 720, (Great Britain). RMR was measured by IC using Fit Mate, COSMED, (Italy) calorimeter. The predictive equations for RMR used for this study were Harris-Benedict, Mufflin-St Jeor, Katch-McArdle, Cunningham, Henry and Schofield equation. Male athletes showed higher values for weight, height, body mass index (BMI) and lean body mass (LBM) (p<0.05) and significantly lower values for body fat (BF) (p<0.05) compared to female athletes. All equations predict lower values of RMR, while the Cunningham equation has the least mean difference compared to measured RMR values. The equations applied to sports population predict lower RMR values than the real ones. The Cunningham equation which is based on the LBM is the most appropriate equation for calculating RMR in the sports population.