Mind the Gap: A Study of Cause-Specific Mortality by Socioeconomic Circumstances

Alai, Daniel H., Arnold (-Gaille), Séverine, Bajekal, Madhavi, Villegas, Andrés M. (2018) Mind the Gap: A Study of Cause-Specific Mortality by Socioeconomic Circumstances. North American Actuarial Journal, . pp. 1-21. ISSN 1092-0277. (doi:10.1080/10920277.2017.1377621) (Access to this publication is currently restricted. You may be able to access a copy if URLs are provided)

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Abstract

Socioeconomic groups may be exposed to varying levels of mortality; this is certainly the case in the United Kingdom, where the gaps in life expectancy, differentiated by socioeconomic circumstances, are widening. The reasons for such diverging trends are yet unclear, but a study of cause-specific mortality may provide rich insight into this phenomenon. Therefore, we investigate the relationship between socioeconomic circumstances and cause-specific mortality using a unique dataset obtained from the U.K. Office for National Statistics. We apply a multinomial logistic framework; the reason is twofold. First, covariates such as socioeconomic circumstances are readily incorporated, and, second, the framework is able to handle the intrinsic dependence amongst the competing causes. As a consequence of the dataset and modeling framework, we are able to investigate the impact of improvements in cause-specific mortality by socioeconomic circumstances. We assess the impact using (residual) life expectancy, a measure of aggregate mortality. Of main interest are the gaps in life expectancy among socioeconomic groups, the trends in these gaps over time, and the ability to identify the causes most influential in reducing these gaps. This analysis is performed through the investigation of different scenarios: first, by eliminating one cause of death at a time; second, by meeting a target set by the World Health Organization (WHO), called WHO 25 × 25; and third, by developing an optimal strategy to increase life expectancy and reduce inequalities.

Item Type: Article
DOI/Identification number: 10.1080/10920277.2017.1377621
Subjects: Q Science > QA Mathematics (inc Computing science)
Divisions: Faculties > Sciences > School of Mathematics Statistics and Actuarial Science
Faculties > Sciences > School of Mathematics Statistics and Actuarial Science > Actuarial Science
Depositing User: Daniel Alai
Date Deposited: 19 Jan 2018 10:24 UTC
Last Modified: 29 May 2019 20:11 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/65755 (The current URI for this page, for reference purposes)
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