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Statistical methods for body mass index: a selective review

Statistical methods for body mass index: a selective review
Statistical methods for body mass index: a selective review

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.

Body mass index, obesity, regression model, risk factors, statistical analysis
0962-2802
798-811
Yu, Keming
e125e6ab-bda4-4323-95eb-4475408efe14
Liu, Xi
9589a507-97cc-4672-845c-134499274338
Alhamzawi, Rahim
d493f736-a2ea-4d03-8ecf-c0a538b1f4b5
Becker, Frauke
bd2cb5fb-1a3b-42e4-92ae-a7ea5cb9e306
Lord, Joanne
fd3b2bf0-9403-466a-8184-9303bdc80a9a
Yu, Keming
e125e6ab-bda4-4323-95eb-4475408efe14
Liu, Xi
9589a507-97cc-4672-845c-134499274338
Alhamzawi, Rahim
d493f736-a2ea-4d03-8ecf-c0a538b1f4b5
Becker, Frauke
bd2cb5fb-1a3b-42e4-92ae-a7ea5cb9e306
Lord, Joanne
fd3b2bf0-9403-466a-8184-9303bdc80a9a

Yu, Keming, Liu, Xi, Alhamzawi, Rahim, Becker, Frauke and Lord, Joanne (2018) Statistical methods for body mass index: a selective review. Statistical Methods in Medical Research, 27 (3), 798-811. (doi:10.1177/0962280216643117).

Record type: Article

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.

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More information

e-pub ahead of print date: 11 April 2016
Published date: 1 March 2018
Keywords: Body mass index, obesity, regression model, risk factors, statistical analysis

Identifiers

Local EPrints ID: 433794
URI: http://eprints.soton.ac.uk/id/eprint/433794
ISSN: 0962-2802
PURE UUID: e1a3a4bb-c664-4c4b-91d8-f04207567b6c
ORCID for Joanne Lord: ORCID iD orcid.org/0000-0003-1086-1624

Catalogue record

Date deposited: 04 Sep 2019 16:30
Last modified: 18 Mar 2024 03:32

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Contributors

Author: Keming Yu
Author: Xi Liu
Author: Rahim Alhamzawi
Author: Frauke Becker
Author: Joanne Lord ORCID iD

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