Abstract
Resting metabolic rate (RMR) is the key determinant of the energy requirement of an individual. Measurement of RMR by indirect calorimetry is not feasible in field settings and therefore equation-based calculations are used. Since a valid equation is not available for Sri Lankans, it is important to develop a new population-specific equation for field use. The study objective was to develop a new equation for the prediction of RMR in healthy Sri Lankans using a reference method, indirect calorimetry. RMR data were collected from fifty-seven (male 27) adults aged 19 to 60 years. They were randomly assigned to validation (n = 28) and cross-validation (n = 19) groups using the statistical package R (version 3.6.3). Height, weight, and RMR were measured. Multivariable fractional polynomials (MFP) were used to determine explanatory variables and their functional forms for the model. A variable shrinkage method was used to find the best fit predictor coefficients of the equation. The developed equation was cross-validated on an independent group. Weight and sex code (male = 1; female = 0) were identified as reliable independent variables. The new equation developed was RMR (kcal/day) = 284.5 + (13.2 x weight) + (133.0 x sex code). Independent variables of the prediction equation were able to predict 88.5% of the variance. Root mean square error (RMSE) of the prediction equation in validation and cross-validation was 88.11 kcal/day and 79.03 kcal/day, respectively. The equation developed in this study is suitable for predicting RMR in Sri Lankan adults.
Highlights
Materials and Methodsresting metabolic rate (RMR) measurement was repeated seven days later under similar condition for each participant and mean RMR was used for the analysis
resting metabolic rate (RMR) is the amount of energy the body expends at rest and it accounts for approximately 60% to 70% of the Total energy expenditure (TEE) [2]
Unsuitability of the existing equations for the prediction of RMR for Sri Lankan adults highlighted the need for development of a new population-specific equation [16]. is study aimed to develop a new equation for the prediction of RMR in healthy Sri Lankan adults using the reference method, indirect calorimetry
Summary
RMR measurement was repeated seven days later under similar condition for each participant and mean RMR was used for the analysis. Multivariable fractional polynomials (MFP) were fitted for continuous variables (height, weight, BMI, and age). E best prediction model among different penalty terms was selected by the measure of goodness-of-fit statistic. BMI, and age were not included in the prediction model and were not predictors of RMR in this population. Variable shrinkage (ridge, LASSO, and elastic net regression) with 10-fold repeated cross-validation method was used to estimate reliable predictor coefficients for the final model. Best model fit with least RMSE and highest R2 was obtained by elastic net method that linearly combines the L1 and L2 penalties of the LASSO and ridge methods. Prediction coefficients were obtained for best fit elastic net regression model where alpha was 0.1 and lambda was 1.
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