Title of article
Predicting the Basal Metabolic Rate in Adolescents: A Correlated (Re)-Analysis
Author/Authors
Mohd Din, Siti Haslinda Erasmus University - Medical Centre - Department of Biostatistics, Netherlands , Mohd Din, Siti Haslinda Department of Statistics, Malaysia , Koon, Poh Bee Universiti Kebangsaan Malaysia - School of Healthcare Sciences, Faculty of Health Sciences, Malaysia , Noor, Mohd Ismail MARA University of Technology - Faculty of Health Sciences, - Department of Nutrition and Dietetics, Malaysia , Henry, Christiani Jeya K. Oxford Brookes University - Functional Food Centre, UK , Henry, Christiani Jeya K. Singapore Institute for Clinical Sciences - Clinical Nutrition Research Centre, Singapore , Lesaffre, Emmanuel L-Biostat, KU Leuven, Belgium , Lesaffre, Emmanuel Erasmus University Medical Centre - Department of Biostatistics, Netherlands
From page
19
To page
32
Abstract
A basal metabolic rate(BMR) that is too low is an indicator of a poor physical condition, and could be one of the reasons for overweight. Measuring BMR though, is a time-consuming exercise, and there has long been interest in developing statistical models to predict BMR from demographic and anthropometric measurements. Poh et al. [1] developed ordinary linear regression models on a cohort of 139 Malaysian children measured three years bi-annually. However, since each child contributed six times to the total data set, these models ignore the correlated nature of the data. We re-analyzed these data using correlated linear models. We show that our approach taking correlation into account is important to establish important covariates, but does not improve prediction.
Keywords
Basal metabolic rate , correlated data linear model , linear mixed model
Journal title
Matematika
Journal title
Matematika
Record number
2570123
Link To Document