Abstract
[Purpose]This preliminary study aimed to develop a regression model to estimate the resting metabolic rate (RMR) of young and middle-aged Koreans using various easy-to-measure dependent variables.[Methods]The RMR and the dependent variables for its estimation (e.g. age, height, body mass index, fat-free mass; FFM, fat mass, % body fat, systolic blood pressure, diastolic blood pressure, mean arterial pressure, pulse pressure, and resting heart rate) were measured in 53 young (male n = 18, female n = 16) and middle-aged (male n = 5, female n = 14) healthy adults. Statistical analysis was performed to develop an RMR estimation regression model using the stepwise regression method.[Results]We confirmed that FFM and age were important variables in both the regression models based on the regression coefficients. Mean explanatory power of RMR1 regression models estimated only by FFM was 66.7% (R2) and 66.0% (adjusted R2), while mean standard errors of estimates (SEE) was 219.85 kcal/day. Additionally, mean explanatory power of RMR2 regression models developed by FFM and age were 70.0% (R2) and 68.8% (adjusted R2), while the mean SEE was 210.64 kcal/day. There was no significant difference between the measured RMR by the canopy method using a metabolic gas analyzer and the predicted RMR by RMR1 and RMR2 equations.[Conclusion]This preliminary study developed a regression model to estimate the RMR of young and middle-age healthy Koreans. The regression model was as follows: RMR1 = 24.383 × FFM + 634.310, RMR2 = 23.691 × FFM - 5.745 × age + 852.341.
Highlights
Resting metabolic rate (RMR) is the total number of calories burned when the body is completely at rest
The total energy expenditure in 24 hours consists of RMR, physical activity energy expenditure (PEE), and diet-induced thermogenesis (DIT)
Individual regression models for males and females could not be developed. This was due to the small sample size and the absence of a significant correlation between the dependent variables and the RMR which resulted in multicollinearity among all the dependent variables
Summary
Resting metabolic rate (RMR) is the total number of calories burned when the body is completely at rest. The RMR represents approximately 60-75% of daily energy expenditure (DEE) in a 70 kg person[2,3], accounting for the largest contribution to the 24-hour energy expenditure. Methods for measuring the RMR include direct and indirect calorimetry, with the latter being used commonly due to a more efficient measurement It is further divided into two methods, one using doubly labeled water; and the other using a human metabolic chamber, a hood-, or a mask system[7,8,9]. Previous attempts to overcome these shortcomings failed to show high regression rates[11,12,13,14], as they estimated RMR with only age, height, weight, and lean body mass. The present study was a preliminary study and it aimed to evaluate the Korean adults (males and females) to generate regression equations to predict the RMR from age, height, body mass index (BMI), FFM, fat mass, % body fat, systolic blood pressure (SBP), diastolic blood pressure (DBP), mean arterial pressure (MAP), pulse pressure (PP) and resting heart rate (HR)
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