Factors associated with excess all-cause mortality in the first wave of COVID-19 pandemic in the UK: a time-series analysis using the Clinical Practice Research Datalink
Objectives: Excess mortality captures the total effect of the COVID-19 pandemic on mortality and is not affected by mis-specification of cause of death. We aimed to describe how health and demographic factors have been associated with excess mortality during the pandemic. Design: Time-series analysis. Setting: UK primary care data from practices contributing to the Clinical Practice Research Datalink on July 31st 2020. Participants: We constructed a time-series dataset including 9,635,613 adults ([≥]40 years old) who were actively registered at the general practice during the study period. Main outcome measures: We extracted weekly numbers of deaths between March 2015 and July 2020, stratified by individual-level factors. Excess mortality during wave 1 of the UK pandemic (5th March to 27th May 2020) compared to pre-pandemic was estimated using seasonally adjusted negative binomial regression models. Relative rates of death for a range of factors were estimated before and during wave 1 by including interaction terms. Results: All-cause mortality increased by 43% (95% CI 40%-47%) during wave 1 compared with pre-pandemic. Changes to the relative rate of death associated with most socio-demographic and clinical characteristics were small during wave 1 compared with pre-pandemic. However, the mortality rate associated with dementia markedly increased (RR for dementia vs no dementia pre-pandemic: 3.5, 95% CI 3.4-3.5; RR during wave 1: 5.1, 4.87-5.28); a similar pattern was seen for learning disabilities (RR pre-pandemic: 3.6, 3.4-3.5; during wave 1: 4.8, 4.4-5.3), for Black or South Asian ethnicity compared to white, and for London compared to other regions. Conclusions: The first UK COVID-19 wave appeared to amplify baseline mortality risk by a relatively constant factor for most population subgroups. However disproportionate increases in mortality were seen for those with dementia, learning disabilities, non-white ethnicity, or living in London.
- Downloaded 182 times
- Download rankings, all-time:
- Site-wide: 137,975
- In epidemiology: 5,724
- Year to date:
- Site-wide: 50,077
- Since beginning of last month:
- Site-wide: 51,051
Downloads over time
Distribution of downloads per paper, site-wide
- 27 Nov 2020: The website and API now include results pulled from medRxiv as well as bioRxiv.
- 18 Dec 2019: We're pleased to announce PanLingua, a new tool that enables you to search for machine-translated bioRxiv preprints using more than 100 different languages.
- 21 May 2019: PLOS Biology has published a community page about Rxivist.org and its design.
- 10 May 2019: The paper analyzing the Rxivist dataset has been published at eLife.
- 1 Mar 2019: We now have summary statistics about bioRxiv downloads and submissions.
- 8 Feb 2019: Data from Altmetric is now available on the Rxivist details page for every preprint. Look for the "donut" under the download metrics.
- 30 Jan 2019: preLights has featured the Rxivist preprint and written about our findings.
- 22 Jan 2019: Nature just published an article about Rxivist and our data.
- 13 Jan 2019: The Rxivist preprint is live!