Factors associated with deaths due to COVID-19 versus other causes: population-based cohort analysis of UK primary care data and linked national death registrations within the OpenSAFELY platform
Background: Mortality from COVID-19 shows a strong relationship with age and pre-existing medical conditions, as does mortality from other causes. We aimed to investigate how specific factors are differentially associated with COVID-19 mortality as compared to mortality from causes other than COVID-...
| Main Authors: | , , , , , , , , , , , , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2021-07-01
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| Series: | The Lancet Regional Health. Europe |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666776221000867 |
| _version_ | 1818577148047261696 |
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| author | Krishnan Bhaskaran Sebastian Bacon Stephen JW Evans Chris J Bates Christopher T Rentsch Brian MacKenna Laurie Tomlinson Alex J Walker Anna Schultze Caroline E Morton Daniel Grint Amir Mehrkar Rosalind M Eggo Peter Inglesby Ian J Douglas Helen I McDonald Jonathan Cockburn Elizabeth J Williamson David Evans Helen J Curtis William J Hulme John Parry Frank Hester Sam Harper David Spiegelhalter Liam Smeeth Ben Goldacre |
| author_facet | Krishnan Bhaskaran Sebastian Bacon Stephen JW Evans Chris J Bates Christopher T Rentsch Brian MacKenna Laurie Tomlinson Alex J Walker Anna Schultze Caroline E Morton Daniel Grint Amir Mehrkar Rosalind M Eggo Peter Inglesby Ian J Douglas Helen I McDonald Jonathan Cockburn Elizabeth J Williamson David Evans Helen J Curtis William J Hulme John Parry Frank Hester Sam Harper David Spiegelhalter Liam Smeeth Ben Goldacre |
| author_sort | Krishnan Bhaskaran |
| collection | DOAJ |
| description | Background: Mortality from COVID-19 shows a strong relationship with age and pre-existing medical conditions, as does mortality from other causes. We aimed to investigate how specific factors are differentially associated with COVID-19 mortality as compared to mortality from causes other than COVID-19. Methods: Working on behalf of NHS England, we carried out a cohort study within the OpenSAFELY platform. Primary care data from England were linked to national death registrations. We included all adults (aged ≥18 years) in the database on 1st February 2020 and with >1 year of continuous prior registration; the cut-off date for deaths was 9th November 2020. Associations between individual-level characteristics and COVID-19 and non-COVID deaths, classified according to the presence of a COVID-19 code as the underlying cause of death on the death certificate, were estimated by fitting age- and sex-adjusted logistic models for these two outcomes. Findings: 17,456,515 individuals were included. 17,063 died from COVID-19 and 134,316 from other causes. Most factors associated with COVID-19 death were similarly associated with non-COVID death, but the magnitudes of association differed. Older age was more strongly associated with COVID-19 death than non-COVID death (e.g. ORs 40.7 [95% CI 37.7-43.8] and 29.6 [28.9-30.3] respectively for ≥80 vs 50-59 years), as was male sex, deprivation, obesity, and some comorbidities. Smoking, history of cancer and chronic liver disease had stronger associations with non-COVID than COVID-19 death. All non-white ethnic groups had higher odds than white of COVID-19 death (OR for Black: 2.20 [1.96-2.47], South Asian: 2.33 [2.16-2.52]), but lower odds than white of non-COVID death (Black: 0.88 [0.83-0.94], South Asian: 0.78 [0.75-0.81]). Interpretation: Similar associations of most individual-level factors with COVID-19 and non-COVID death suggest that COVID-19 largely multiplies existing risks faced by patients, with some notable exceptions. Identifying the unique factors contributing to the excess COVID-19 mortality risk among non-white groups is a priority to inform efforts to reduce deaths from COVID-19. Funding: Wellcome, Royal Society, National Institute for Health Research, National Institute for Health Research Oxford Biomedical Research Centre, UK Medical Research Council, Health Data Research UK. |
| first_indexed | 2024-12-16T06:25:18Z |
| format | Article |
| id | doaj.art-859b247e4fe9428e89260c6627a0eb6f |
| institution | Directory Open Access Journal |
| issn | 2666-7762 |
| language | English |
| last_indexed | 2024-12-16T06:25:18Z |
| publishDate | 2021-07-01 |
| publisher | Elsevier |
| record_format | Article |
| series | The Lancet Regional Health. Europe |
| spelling | doaj.art-859b247e4fe9428e89260c6627a0eb6f2022-12-21T22:41:01ZengElsevierThe Lancet Regional Health. Europe2666-77622021-07-016100109Factors associated with deaths due to COVID-19 versus other causes: population-based cohort analysis of UK primary care data and linked national death registrations within the OpenSAFELY platformKrishnan Bhaskaran0Sebastian Bacon1Stephen JW Evans2Chris J Bates3Christopher T Rentsch4Brian MacKenna5Laurie Tomlinson6Alex J Walker7Anna Schultze8Caroline E Morton9Daniel Grint10Amir Mehrkar11Rosalind M Eggo12Peter Inglesby13Ian J Douglas14Helen I McDonald15Jonathan Cockburn16Elizabeth J Williamson17David Evans18Helen J Curtis19William J Hulme20John Parry21Frank Hester22Sam Harper23David Spiegelhalter24Liam Smeeth25Ben Goldacre26Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine; Corresponding author.The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UKFaculty of Epidemiology and Population Health, London School of Hygiene and Tropical MedicineThe Phoenix Partnership, TPP House, Horsforth, Leeds, UKFaculty of Epidemiology and Population Health, London School of Hygiene and Tropical MedicineThe DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UKFaculty of Epidemiology and Population Health, London School of Hygiene and Tropical MedicineThe DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UKFaculty of Epidemiology and Population Health, London School of Hygiene and Tropical MedicineThe DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UKFaculty of Epidemiology and Population Health, London School of Hygiene and Tropical MedicineThe DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UKFaculty of Epidemiology and Population Health, London School of Hygiene and Tropical MedicineThe DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UKFaculty of Epidemiology and Population Health, London School of Hygiene and Tropical MedicineFaculty of Epidemiology and Population Health, London School of Hygiene and Tropical MedicineThe Phoenix Partnership, TPP House, Horsforth, Leeds, UKFaculty of Epidemiology and Population Health, London School of Hygiene and Tropical MedicineThe DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UKThe DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UKThe DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UKThe Phoenix Partnership, TPP House, Horsforth, Leeds, UKThe Phoenix Partnership, TPP House, Horsforth, Leeds, UKThe Phoenix Partnership, TPP House, Horsforth, Leeds, UKWinton Centre for Risk and Evidence Communication, Statistical Laboratory Centre for Mathematical Sciences, Cambridge, UKFaculty of Epidemiology and Population Health, London School of Hygiene and Tropical MedicineThe DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UKBackground: Mortality from COVID-19 shows a strong relationship with age and pre-existing medical conditions, as does mortality from other causes. We aimed to investigate how specific factors are differentially associated with COVID-19 mortality as compared to mortality from causes other than COVID-19. Methods: Working on behalf of NHS England, we carried out a cohort study within the OpenSAFELY platform. Primary care data from England were linked to national death registrations. We included all adults (aged ≥18 years) in the database on 1st February 2020 and with >1 year of continuous prior registration; the cut-off date for deaths was 9th November 2020. Associations between individual-level characteristics and COVID-19 and non-COVID deaths, classified according to the presence of a COVID-19 code as the underlying cause of death on the death certificate, were estimated by fitting age- and sex-adjusted logistic models for these two outcomes. Findings: 17,456,515 individuals were included. 17,063 died from COVID-19 and 134,316 from other causes. Most factors associated with COVID-19 death were similarly associated with non-COVID death, but the magnitudes of association differed. Older age was more strongly associated with COVID-19 death than non-COVID death (e.g. ORs 40.7 [95% CI 37.7-43.8] and 29.6 [28.9-30.3] respectively for ≥80 vs 50-59 years), as was male sex, deprivation, obesity, and some comorbidities. Smoking, history of cancer and chronic liver disease had stronger associations with non-COVID than COVID-19 death. All non-white ethnic groups had higher odds than white of COVID-19 death (OR for Black: 2.20 [1.96-2.47], South Asian: 2.33 [2.16-2.52]), but lower odds than white of non-COVID death (Black: 0.88 [0.83-0.94], South Asian: 0.78 [0.75-0.81]). Interpretation: Similar associations of most individual-level factors with COVID-19 and non-COVID death suggest that COVID-19 largely multiplies existing risks faced by patients, with some notable exceptions. Identifying the unique factors contributing to the excess COVID-19 mortality risk among non-white groups is a priority to inform efforts to reduce deaths from COVID-19. Funding: Wellcome, Royal Society, National Institute for Health Research, National Institute for Health Research Oxford Biomedical Research Centre, UK Medical Research Council, Health Data Research UK.http://www.sciencedirect.com/science/article/pii/S2666776221000867COVID-19MortalityEpidemiology |
| spellingShingle | Krishnan Bhaskaran Sebastian Bacon Stephen JW Evans Chris J Bates Christopher T Rentsch Brian MacKenna Laurie Tomlinson Alex J Walker Anna Schultze Caroline E Morton Daniel Grint Amir Mehrkar Rosalind M Eggo Peter Inglesby Ian J Douglas Helen I McDonald Jonathan Cockburn Elizabeth J Williamson David Evans Helen J Curtis William J Hulme John Parry Frank Hester Sam Harper David Spiegelhalter Liam Smeeth Ben Goldacre Factors associated with deaths due to COVID-19 versus other causes: population-based cohort analysis of UK primary care data and linked national death registrations within the OpenSAFELY platform The Lancet Regional Health. Europe COVID-19 Mortality Epidemiology |
| title | Factors associated with deaths due to COVID-19 versus other causes: population-based cohort analysis of UK primary care data and linked national death registrations within the OpenSAFELY platform |
| title_full | Factors associated with deaths due to COVID-19 versus other causes: population-based cohort analysis of UK primary care data and linked national death registrations within the OpenSAFELY platform |
| title_fullStr | Factors associated with deaths due to COVID-19 versus other causes: population-based cohort analysis of UK primary care data and linked national death registrations within the OpenSAFELY platform |
| title_full_unstemmed | Factors associated with deaths due to COVID-19 versus other causes: population-based cohort analysis of UK primary care data and linked national death registrations within the OpenSAFELY platform |
| title_short | Factors associated with deaths due to COVID-19 versus other causes: population-based cohort analysis of UK primary care data and linked national death registrations within the OpenSAFELY platform |
| title_sort | factors associated with deaths due to covid 19 versus other causes population based cohort analysis of uk primary care data and linked national death registrations within the opensafely platform |
| topic | COVID-19 Mortality Epidemiology |
| url | http://www.sciencedirect.com/science/article/pii/S2666776221000867 |
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