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Title: Statistical methods for body mass index: a selective review
Authors: Yu, K
Liu, X
Alhamzawi, R
Becker, F
Lord, J
Keywords: Body mass index;Obesity;Regression model;Risk factors;Statistical analysis
Issue Date: 2016
Publisher: SAGE
Citation: Statistical Methods in Medical Research, pp.1-37, (2016)
Abstract: Obesity rates have been increasing over recent decades, causing significant concern among policy makers. Excess body fat, commonly measured by body mass index, is a major risk factor for several common disorders including diabetes and cardiovascular disease, placing a substantial burden on health care systems. To guide effective public health action, we need to understand the complex system of intercorrelated influences on body mass index. This paper, based on all eligible articles searched from Global health, Medline and Web of Science databases, reviews both classical and modern statistical methods for body mass index analysis. We give a description of each of these methods, exploring the classification, links and differences between them and the reasons for choosing one over the others in different settings. We aim to provide a key resource and statistical library for researchers in public health and medicine to deal with obesity and body mass index data analysis.
ISSN: 1477-0334
Appears in Collections:Dept of Mathematics Research Papers

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