Estimating the changing nature of Scotland's health inequalities using a multivariate spatiotemporal model

Jack, E. , Lee, D. and Dean, N. (2019) Estimating the changing nature of Scotland's health inequalities using a multivariate spatiotemporal model. Journal of the Royal Statistical Society: Series A (Statistics in Society), 182(3), pp. 1061-1080. (doi:10.1111/rssa.12447) (PMID:31217673) (PMCID:PMC6563432)

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Abstract

Health inequalities are the unfair and avoidable differences in people's health between different social groups. These inequalities have a huge influence on people's lives, particularly those who live at the poorer end of the socio‐economic spectrum, as they result in prolonged ill health and shorter lives. Most studies estimate health inequalities for a single disease, but this will give an incomplete picture of the overall inequality in population health. Here we propose a novel multivariate spatiotemporal model for quantifying health inequalities in Scotland across multiple diseases, which will enable us to understand better how these inequalities vary across disease and have changed over time. In developing this model we are interested in estimating health inequalities between Scotland's 14 regional health boards, who are responsible for the protection and improvement of their population's health. The methodology is applied to hospital admissions data for cerebrovascular disease, coronary heart disease and respiratory disease, which are three of the leading causes of death, from 2003 to 2012 across Scotland.

Item Type:Articles
Additional Information:Carnegie Trust for the Universities of Scotland (GrantNumber(s): Eilidh Jack - PHD060237; Grant recipient(s): EILIDH JACK) Medical Research Council (GrantNumber(s): MR/L022184/1; Grant recipient(s): DUNCAN LEE)
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Dean, Dr Nema and Lee, Professor Duncan and Jack, Dr Eilidh
Authors: Jack, E., Lee, D., and Dean, N.
College/School:College of Science and Engineering > School of Mathematics and Statistics > Statistics
Journal Name:Journal of the Royal Statistical Society: Series A (Statistics in Society)
Publisher:Wiley
ISSN:0964-1998
ISSN (Online):1467-985X
Published Online:09 April 2019
Copyright Holders:Copyright © 2019 The Authors
First Published:First published in Journal of the Royal Statistical Society: Series A (Statistics in Society) 182(3):1061-1080
Publisher Policy:Reproduced under a Creative Commons License

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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
647701A flexible class of Bayesian spatio-temporal models for cluster detection, trend estimation and forecasting of disease risk.Duncan LeeMedical Research Council (MRC)MR/L022184/1M&S - STATISTICS