Rationale: Increased fat free mass is expected to increase the resting metabolic rate (RMR) of bodybuilders. However, it is currently unknown how to accurately predict the RMR of bodybuilders. Therefore,… Click to show full abstract
Rationale: Increased fat free mass is expected to increase the resting metabolic rate (RMR) of bodybuilders. However, it is currently unknown how to accurately predict the RMR of bodybuilders. Therefore, the aim of this study is to determine whether an increase in fat free mass correlates with an increased RMR in bodybuilders and to determine the best accurate formula to predict the RMR in male bodybuilders. Methods: After an overnight fast height (m), weight (kg) and fat free mass index (FFMI) in kg/m were measured in male bodybuilders. RMR was measured by indirect calorimetry (RMR) and compared to 11 predictive equations for RMR (RMR). Predictive equations were includedwhenbased on fat freemass. Accuracyof RMRwas evaluated as percentage of subjects predicted within ±10% of RMR. Root mean squared error (RMSE) and mean absolute difference (bias) between RMR and RMR were calculated. Relationship between FFMI and RMR was determined using Pearson’s correlation. Results: Twenty male bodybuilders (age: 25.5 yr, weight: 91.7 kg, BMI 25.1 kg/m, FFMI 24.2 kg/m) were selected and signed informed consent. FFMI was positively correlated with RMR (Pearson r = 0,71, p < 0,01). Most accurate equations were the Cunningham, Johnstone and Katch-McCardle with 70%, 65% and 60% accurate predictions, respectively. Bias of these equations was −2,4, −8,5 and −9,5% and RMSE was 284, 354 and 371 kcal/day, respectively. Conclusions: This study shows that an increased FFMI positively correlates with the RMR of bodybuilders. The Cunningham formula is the preferred equation for estimating the RMR of male bodybuilders.
               
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