Risk factors for excess all-cause mortality during the first wave of the COVID-19 pandemic in England: A retrospective cohort study of primary care data
The COVID-19 pandemic's first wave in England during spring 2020 resulted in an approximate 50% increase in all-cause mortality. Previously, risk factors such as age and ethnicity, were identified by studying COVID-related deaths only, but these were under-recorded during this period. To use a...
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| Veröffentlicht in: | PloS one 2021-12, Vol.16 (12), p.e0260381-e0260381 |
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| description | The COVID-19 pandemic's first wave in England during spring 2020 resulted in an approximate 50% increase in all-cause mortality. Previously, risk factors such as age and ethnicity, were identified by studying COVID-related deaths only, but these were under-recorded during this period.
To use a large electronic primary care database to estimate the impact of risk factors (RFs) on excess mortality in England during the first wave, compared with the impact on total mortality during 2015-19.
Medical history, ethnicity, area-based deprivation and vital status data were extracted for an average of 4.8 million patients aged 30-104 years, for each year between 18-March and 19-May over a 6-year period (2015-2020). We used Poisson regression to model total mortality adjusting for age and sex, with interactions between each RF and period (pandemic vs. 2015-19). Total mortality during the pandemic was partitioned into "usual" and "excess" components, assuming 2015-19 rates represented "usual" mortality. The association of each RF with the 2020 "excess" component was derived as the excess mortality ratio (EMR), and compared with the usual mortality ratio (UMR).
RFs where excess mortality was greatest and notably higher than usual were age >80, non-white ethnicity (e.g., black vs. white EMR = 2.50, 95%CI 1.97-3.18; compared to UMR = 0.92, 95%CI 0.85-1.00), BMI>40, dementia, learning disability, severe mental illness, place of residence (London, care-home, most deprived). By contrast, EMRs were comparable to UMRs for sex. Although some co-morbidities such as cancer produced EMRs significantly below their UMRs, the EMRs were still >1. In contrast current smoking has an EMR below 1 (EMR = 0.80, 95%CI 0.65-0.98) compared to its UMR = 1.64.
Studying risk factors for excess mortality during the pandemic highlighted differences from studying cause-specific mortality. Our approach illustrates a novel methodology for evaluating a pandemic's impact by individual risk factor without requiring cause-specific mortality data. |
| doi_str_mv | 10.1371/journal.pone.0260381 |
| format | Article |
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To use a large electronic primary care database to estimate the impact of risk factors (RFs) on excess mortality in England during the first wave, compared with the impact on total mortality during 2015-19.
Medical history, ethnicity, area-based deprivation and vital status data were extracted for an average of 4.8 million patients aged 30-104 years, for each year between 18-March and 19-May over a 6-year period (2015-2020). We used Poisson regression to model total mortality adjusting for age and sex, with interactions between each RF and period (pandemic vs. 2015-19). Total mortality during the pandemic was partitioned into "usual" and "excess" components, assuming 2015-19 rates represented "usual" mortality. The association of each RF with the 2020 "excess" component was derived as the excess mortality ratio (EMR), and compared with the usual mortality ratio (UMR).
RFs where excess mortality was greatest and notably higher than usual were age >80, non-white ethnicity (e.g., black vs. white EMR = 2.50, 95%CI 1.97-3.18; compared to UMR = 0.92, 95%CI 0.85-1.00), BMI>40, dementia, learning disability, severe mental illness, place of residence (London, care-home, most deprived). By contrast, EMRs were comparable to UMRs for sex. Although some co-morbidities such as cancer produced EMRs significantly below their UMRs, the EMRs were still >1. In contrast current smoking has an EMR below 1 (EMR = 0.80, 95%CI 0.65-0.98) compared to its UMR = 1.64.
Studying risk factors for excess mortality during the pandemic highlighted differences from studying cause-specific mortality. Our approach illustrates a novel methodology for evaluating a pandemic's impact by individual risk factor without requiring cause-specific mortality data.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0260381</identifier><identifier>PMID: 34882700</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Adult ; Age ; Aged ; Aged, 80 and over ; Biology and Life Sciences ; Cause of Death - trends ; Cohort analysis ; Comorbidity ; Computer and Information Sciences ; Cook, David ; Coronaviruses ; COVID-19 ; COVID-19 - epidemiology ; COVID-19 - ethnology ; COVID-19 - mortality ; COVID-19 - virology ; Databases, Factual ; Dementia disorders ; Deprivation ; Electronic records ; England - epidemiology ; Ethnicity ; Female ; Health care ; Health risks ; Humans ; Male ; Management ; Medical records ; Medical research ; Medicine and Health Sciences ; Mental disorders ; Mental health ; Middle Aged ; Minority & ethnic groups ; Mortality ; Pandemics ; Patients ; People and places ; Population ; Primary care ; Registration ; Regression models ; Retrospective Studies ; Risk analysis ; Risk Factors ; SARS-CoV-2 - isolation & purification ; Severe acute respiratory syndrome coronavirus 2 ; Sex ; Statistical analysis</subject><ispartof>PloS one, 2021-12, Vol.16 (12), p.e0260381-e0260381</ispartof><rights>COPYRIGHT 2021 Public Library of Science</rights><rights>2021 Carey et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2021 Carey et al 2021 Carey et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c692t-c420aefc36e084193ee280061045f5c6787232e6f44f595f703c1d8842507d473</citedby><cites>FETCH-LOGICAL-c692t-c420aefc36e084193ee280061045f5c6787232e6f44f595f703c1d8842507d473</cites><orcidid>0000-0002-8671-1553 ; 0000-0003-1099-8460 ; 0000-0002-2618-9257</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8659693/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8659693/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,864,885,2102,2928,23866,27924,27925,53791,53793,79600,79601</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/34882700$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Tsuzuki, Shinya</contributor><creatorcontrib>Carey, Iain M</creatorcontrib><creatorcontrib>Cook, Derek G</creatorcontrib><creatorcontrib>Harris, Tess</creatorcontrib><creatorcontrib>DeWilde, Stephen</creatorcontrib><creatorcontrib>Chaudhry, Umar A R</creatorcontrib><creatorcontrib>Strachan, David P</creatorcontrib><title>Risk factors for excess all-cause mortality during the first wave of the COVID-19 pandemic in England: A retrospective cohort study of primary care data</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>The COVID-19 pandemic's first wave in England during spring 2020 resulted in an approximate 50% increase in all-cause mortality. Previously, risk factors such as age and ethnicity, were identified by studying COVID-related deaths only, but these were under-recorded during this period.
To use a large electronic primary care database to estimate the impact of risk factors (RFs) on excess mortality in England during the first wave, compared with the impact on total mortality during 2015-19.
Medical history, ethnicity, area-based deprivation and vital status data were extracted for an average of 4.8 million patients aged 30-104 years, for each year between 18-March and 19-May over a 6-year period (2015-2020). We used Poisson regression to model total mortality adjusting for age and sex, with interactions between each RF and period (pandemic vs. 2015-19). Total mortality during the pandemic was partitioned into "usual" and "excess" components, assuming 2015-19 rates represented "usual" mortality. The association of each RF with the 2020 "excess" component was derived as the excess mortality ratio (EMR), and compared with the usual mortality ratio (UMR).
RFs where excess mortality was greatest and notably higher than usual were age >80, non-white ethnicity (e.g., black vs. white EMR = 2.50, 95%CI 1.97-3.18; compared to UMR = 0.92, 95%CI 0.85-1.00), BMI>40, dementia, learning disability, severe mental illness, place of residence (London, care-home, most deprived). By contrast, EMRs were comparable to UMRs for sex. Although some co-morbidities such as cancer produced EMRs significantly below their UMRs, the EMRs were still >1. In contrast current smoking has an EMR below 1 (EMR = 0.80, 95%CI 0.65-0.98) compared to its UMR = 1.64.
Studying risk factors for excess mortality during the pandemic highlighted differences from studying cause-specific mortality. Our approach illustrates a novel methodology for evaluating a pandemic's impact by individual risk factor without requiring cause-specific mortality data.</description><subject>Adult</subject><subject>Age</subject><subject>Aged</subject><subject>Aged, 80 and over</subject><subject>Biology and Life Sciences</subject><subject>Cause of Death - trends</subject><subject>Cohort analysis</subject><subject>Comorbidity</subject><subject>Computer and Information Sciences</subject><subject>Cook, David</subject><subject>Coronaviruses</subject><subject>COVID-19</subject><subject>COVID-19 - epidemiology</subject><subject>COVID-19 - ethnology</subject><subject>COVID-19 - mortality</subject><subject>COVID-19 - virology</subject><subject>Databases, Factual</subject><subject>Dementia disorders</subject><subject>Deprivation</subject><subject>Electronic records</subject><subject>England - epidemiology</subject><subject>Ethnicity</subject><subject>Female</subject><subject>Health care</subject><subject>Health risks</subject><subject>Humans</subject><subject>Male</subject><subject>Management</subject><subject>Medical records</subject><subject>Medical research</subject><subject>Medicine and Health Sciences</subject><subject>Mental disorders</subject><subject>Mental health</subject><subject>Middle Aged</subject><subject>Minority & ethnic groups</subject><subject>Mortality</subject><subject>Pandemics</subject><subject>Patients</subject><subject>People and places</subject><subject>Population</subject><subject>Primary care</subject><subject>Registration</subject><subject>Regression models</subject><subject>Retrospective Studies</subject><subject>Risk analysis</subject><subject>Risk Factors</subject><subject>SARS-CoV-2 - 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Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Carey, Iain M</au><au>Cook, Derek G</au><au>Harris, Tess</au><au>DeWilde, Stephen</au><au>Chaudhry, Umar A R</au><au>Strachan, David P</au><au>Tsuzuki, Shinya</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Risk factors for excess all-cause mortality during the first wave of the COVID-19 pandemic in England: A retrospective cohort study of primary care data</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2021-12-09</date><risdate>2021</risdate><volume>16</volume><issue>12</issue><spage>e0260381</spage><epage>e0260381</epage><pages>e0260381-e0260381</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>The COVID-19 pandemic's first wave in England during spring 2020 resulted in an approximate 50% increase in all-cause mortality. Previously, risk factors such as age and ethnicity, were identified by studying COVID-related deaths only, but these were under-recorded during this period.
To use a large electronic primary care database to estimate the impact of risk factors (RFs) on excess mortality in England during the first wave, compared with the impact on total mortality during 2015-19.
Medical history, ethnicity, area-based deprivation and vital status data were extracted for an average of 4.8 million patients aged 30-104 years, for each year between 18-March and 19-May over a 6-year period (2015-2020). We used Poisson regression to model total mortality adjusting for age and sex, with interactions between each RF and period (pandemic vs. 2015-19). Total mortality during the pandemic was partitioned into "usual" and "excess" components, assuming 2015-19 rates represented "usual" mortality. The association of each RF with the 2020 "excess" component was derived as the excess mortality ratio (EMR), and compared with the usual mortality ratio (UMR).
RFs where excess mortality was greatest and notably higher than usual were age >80, non-white ethnicity (e.g., black vs. white EMR = 2.50, 95%CI 1.97-3.18; compared to UMR = 0.92, 95%CI 0.85-1.00), BMI>40, dementia, learning disability, severe mental illness, place of residence (London, care-home, most deprived). By contrast, EMRs were comparable to UMRs for sex. Although some co-morbidities such as cancer produced EMRs significantly below their UMRs, the EMRs were still >1. In contrast current smoking has an EMR below 1 (EMR = 0.80, 95%CI 0.65-0.98) compared to its UMR = 1.64.
Studying risk factors for excess mortality during the pandemic highlighted differences from studying cause-specific mortality. Our approach illustrates a novel methodology for evaluating a pandemic's impact by individual risk factor without requiring cause-specific mortality data.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>34882700</pmid><doi>10.1371/journal.pone.0260381</doi><tpages>e0260381</tpages><orcidid>https://orcid.org/0000-0002-8671-1553</orcidid><orcidid>https://orcid.org/0000-0003-1099-8460</orcidid><orcidid>https://orcid.org/0000-0002-2618-9257</orcidid><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1932-6203 |
| ispartof | PloS one, 2021-12, Vol.16 (12), p.e0260381-e0260381 |
| issn | 1932-6203 1932-6203 |
| language | eng |
| recordid | cdi_plos_journals_2608443255 |
| source | MEDLINE; DOAJ Directory of Open Access Journals; Public Library of Science (PLoS) Journals Open Access; EZB-FREE-00999 freely available EZB journals; PubMed Central; Free Full-Text Journals in Chemistry |
| subjects | Adult Age Aged Aged, 80 and over Biology and Life Sciences Cause of Death - trends Cohort analysis Comorbidity Computer and Information Sciences Cook, David Coronaviruses COVID-19 COVID-19 - epidemiology COVID-19 - ethnology COVID-19 - mortality COVID-19 - virology Databases, Factual Dementia disorders Deprivation Electronic records England - epidemiology Ethnicity Female Health care Health risks Humans Male Management Medical records Medical research Medicine and Health Sciences Mental disorders Mental health Middle Aged Minority & ethnic groups Mortality Pandemics Patients People and places Population Primary care Registration Regression models Retrospective Studies Risk analysis Risk Factors SARS-CoV-2 - isolation & purification Severe acute respiratory syndrome coronavirus 2 Sex Statistical analysis |
| title | Risk factors for excess all-cause mortality during the first wave of the COVID-19 pandemic in England: A retrospective cohort study of primary care data |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-25T04%3A00%3A47IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_plos_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Risk%20factors%20for%20excess%20all-cause%20mortality%20during%20the%20first%20wave%20of%20the%20COVID-19%20pandemic%20in%20England:%20A%20retrospective%20cohort%20study%20of%20primary%20care%20data&rft.jtitle=PloS%20one&rft.au=Carey,%20Iain%20M&rft.date=2021-12-09&rft.volume=16&rft.issue=12&rft.spage=e0260381&rft.epage=e0260381&rft.pages=e0260381-e0260381&rft.issn=1932-6203&rft.eissn=1932-6203&rft_id=info:doi/10.1371/journal.pone.0260381&rft_dat=%3Cgale_plos_%3EA686069986%3C/gale_plos_%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2608443255&rft_id=info:pmid/34882700&rft_galeid=A686069986&rft_doaj_id=oai_doaj_org_article_f36fb122b2b646b7b02ee3ea7a2707ff&rfr_iscdi=true |