A synthetic population dataset for estimating small area health and socio-economic outcomes in Great Britain

Wu, G., Heppenstall, A. , Meier, P. , Purshouse, R. and Lomax, N. (2022) A synthetic population dataset for estimating small area health and socio-economic outcomes in Great Britain. Scientific Data, 9, 19. (doi: 10.1038/s41597-022-01124-9) (PMID:35058471) (PMCID:PMC8776798)

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Abstract

In order to understand the health outcomes for distinct sub-groups of the population or across different geographies, it is advantageous to be able to build bespoke groupings from individual level data. Individuals possess distinct characteristics, exhibit distinct behaviours and accumulate their own unique history of exposure or experiences. However, in most disciplines, not least public health, there is a lack of individual level data available outside of secure settings, especially covering large portions of the population. This paper provides detail on the creation of a synthetic micro dataset for individuals in Great Britain who have detailed attributes which can be used to model a wide range of health and other outcomes. These attributes are constructed from a range of sources including the United Kingdom Census, survey and administrative datasets. It provides a rationale for the need for this synthetic population, discusses methods for creating this dataset and provides some example results of different attribute distributions for distinct sub-population groups and over different geographical areas.

Item Type:Articles
Additional Information:This work was supported by the UK Prevention Research Partnership (MR/S037578/1, Meier), which is funded by the British Heart Foundation, Cancer Research UK, Chief Scientist Office of the Scottish Government Health and Social Care Directorates, Engineering and Physical Sciences Research Council, Economic and Social Research Council, Health and Social Care Research and Development Division (Welsh Government), Medical Research Council, National Institute for Health Research, Natural Environment Research Council, Public Health Agency (Northern Ireland), The Health Foundation and Wellcome.
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Heppenstall, Professor Alison and Wu, Guoqiang and Meier, Professor Petra
Authors: Wu, G., Heppenstall, A., Meier, P., Purshouse, R., and Lomax, N.
College/School:College of Medical Veterinary and Life Sciences > Institute of Health and Wellbeing > MRC/CSO SPHSU
College of Social Sciences > School of Social and Political Sciences
College of Social Sciences > School of Social and Political Sciences > Urban Studies
Journal Name:Scientific Data
Publisher:Nature Publishing Group
ISSN:2052-4463
ISSN (Online):2052-4463
Published Online:20 January 2022
Copyright Holders:Copyright © The Author(s) 2022
First Published:First published in Scientific Data 9: 19
Publisher Policy:Reproduced under a Creative Commons licence

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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
313944System-science Informed Public Health and Economic Research for non-communicable Disease Prevention (the SIPHER consortium)Petra MeierMedical Research Council (MRC)MR/S037578/2HW - MRC/CSO Social and Public Health Sciences Unit
3048231Systems science research in public healthPetra MeierMedical Research Council (MRC)MC_UU_00022/5HW - MRC/CSO Social and Public Health Sciences Unit