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dc.contributor.authorYu, K-
dc.contributor.authorLiu, X-
dc.contributor.authorAlhamzawi, R-
dc.contributor.authorBecker, F-
dc.contributor.authorLord, J-
dc.identifier.citationStatistical Methods in Medical Research, pp.1-37, (2016)en_US
dc.description.abstractObesity 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.en_US
dc.description.sponsorshipThe author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work has been supported in part by the National Institute for Health Research Method Grant (NIHR RMOFS-2013-03-09) and the National Natural Science Foundation of China (Grant No. 71490725, 11261048, 11371322).en_US
dc.subjectBody mass indexen_US
dc.subjectRegression modelen_US
dc.subjectRisk factorsen_US
dc.subjectStatistical analysisen_US
dc.titleStatistical methods for body mass index: a selective reviewen_US
dc.relation.isPartOfStatistical Methods in Medical Research-
pubs.publication-statusPublished online-
Appears in Collections:Dept of Mathematics Research Papers

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