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KMID : 1101720200240010009
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Physical Activity and Nutrition
2020 Volume.24 No. 1 p.9 ~ p.13
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Predicting the resting metabolic rate of young and middle-aged healthy Korean adults: A preliminary study
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Park Hun-Young
Jung Won-Sang
Hwang Hye-Jung
Kim Sung-Woo
Kim Ji-Su
Lim Ki-Won
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Abstract
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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.
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KEYWORD
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RMR, fat-free mass, age, regression coefficient, algorithm model, estimation equation
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