Background

Resting metabolic rate (RMR) is a key determinant of daily caloric needs. Indirect calorimetry (IC) to measure RMR in the clinic is impractical. Formulas used to predict RMR do not include fat distribution and race, and may incorrectly estimate measured RMR (mRMR). In this study, we sought to determine additional factors that determine mRMR.

Methods

We measured RMR in 104 subjects (65% female, 34% African American (AA)) using IC. Height (HT), weight (WT), waist circumference (WC), and waist-to-hip ratio (WHR) were obtained. Dual-energy x-ray absorptiometry was used to obtain lean body mass (LBM), total fat mass, and estimated visceral adipose tissue. mRMR was compared to predicted RMR (pRMR) generated by Mifflin and Harris-Benedict (HB) equations. Linear regression models were used to determine anthropometrics that affected mRMR.

Results

Mean age, BMI, and RMR of subjects were 45±16 years (mean ± SD), 34.5±10.4 kg/m^2, and 1605±400 kilocalories/day (KCAL) respectively. mRMR was significantly overestimated by 102±194 KCAL and 197±208 KCAL using Mifflin and HB equations (p<0.0001). When stratified by race, Mifflin and HB overestimated KCAL expenditure in Whites by 58±191 KCAL (p<0.05) and 151±210 KCAL (p<0.0001) respectively, whereas, in AA by 190±170 KCAL and 286±173 KCAL (p<0.0001) respectively. After adjusting for age, gender, and anthropometrics, the two largest predictors of mRMR were race (p <0.0001) and LBM (p <0.0001). For every kg increase in LBM, RMR increased by 26 KCAL (p<0.0001). AA race was associated with 152 KCAL (p<0.0001) decrease in mRMR. Using only clinically measured variables, we found race, WC, and WHR to be significant predictors (p<0.05). For every cm increase in WC, mRMR decreased by 10 KCAL (p<0.05).

Conclusions

We found that formulas utilizing HT, WT, gender, and age overestimate mRMR and hence predict higher daily KCAL needs, especially among AA. Inclusion of WC and race in formulas may improve predictability of mRMR.