Inequalities in severe COVID-19 outcomes in Wales, UK

ObjectiveResearch evidence shows that COVID-19 has disproportionately affected people from more deprived backgrounds. In Wales (UK), there is strong evidence of a socioeconomic gradient in total hospitalisations, critical care admissions and deaths. This study focussed on a cohort of the Welsh population using anonymised individual-level linked population-scale data in the SAIL Databank. ApproachThis analysis examines the impact of confounding/mediating factors on severe health outcomes. We used logistic regression, considering the Welsh Index of Multiple Deprivation (WIMD) 2019 as a predictor, to investigate how the coefficient for WIMD is changed when other variables (such as comorbidities, smoking status, Body Mass Index) are added, aiming to understand whether inequalities are mediated by observed characteristics or related to other unobserved factors. ResultsInitial findings show that age-standardised rates of hospital admissions, Intensive Care Unit (ICU) admissions and deaths were roughly twice as high in the most deprived vs least deprived WIMD quintile in Wales. We estimated Years of Life Lost per 1,000 due to COVID-19 as 28.9, with variation between WIMD quintiles of 38.4 for the most deprived and 22.2 for the least deprived. The project also produced regression formulas to evaluate the contribution of the different confounding factors. ConclusionThis study built on existing research findings and further explored the potential reasons for known socioeconomic inequalities in relation to COVID-19 outcomes. Insights from this study have broadened the knowledge around the impact of mediating factors and may contribute to future pandemic preparedness and the formation of future policies.

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Publication Details

Journal
International Journal for Population Data Science
Published
2024-09-10
DOI
https://doi.org/10.23889/ijpds.v9i5.2558
Primary Topic
Employment and Welfare Studies
Type
article
Field-Weighted Citation Impact
0.00

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article

Inequalities in severe COVID-19 outcomes in Wales, UK

Ashley Akbari, Stuart Bedston, Hoda Abbasizanjani, Matthew Curds et al.
International Journal for Population Data Science
Employment and Welfare Studies
article

Inequalities in severe COVID-19 outcomes in Wales, UK

Ashley Akbari, Stuart Bedston, Hoda Abbasizanjani, Matthew Curds, Lucy Robinson
article en

Abstract

ObjectiveResearch evidence shows that COVID-19 has disproportionately affected people from more deprived backgrounds. In Wales (UK), there is strong evidence of a socioeconomic gradient in total hospitalisations, critical care admissions and deaths. This study focussed on a cohort of the Welsh population using anonymised individual-level linked population-scale data in the SAIL Databank. ApproachThis analysis examines the impact of confounding/mediating factors on severe health outcomes. We used logistic regression, considering the Welsh Index of Multiple Deprivation (WIMD) 2019 as a predictor, to investigate how the coefficient for WIMD is changed when other variables (such as comorbidities, smoking status, Body Mass Index) are added, aiming to understand whether inequalities are mediated by observed characteristics or related to other unobserved factors. ResultsInitial findings show that age-standardised rates of hospital admissions, Intensive Care Unit (ICU) admissions and deaths were roughly twice as high in the most deprived vs least deprived WIMD quintile in Wales. We estimated Years of Life Lost per 1,000 due to COVID-19 as 28.9, with variation between WIMD quintiles of 38.4 for the most deprived and 22.2 for the least deprived. The project also produced regression formulas to evaluate the contribution of the different confounding factors. ConclusionThis study built on existing research findings and further explored the potential reasons for known socioeconomic inequalities in relation to COVID-19 outcomes. Insights from this study have broadened the knowledge around the impact of mediating factors and may contribute to future pandemic preparedness and the formation of future policies.

International Journal for Population Data ScienceVol. 9(5)
Welsh Government (GB), Swansea University (GB)
Economic and Social Research Council
Openalex Percentile: Top 74%
Employment and Welfare Studies
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