Quantifying the association between COVID-19, ethnicity and mortality: A cohort study across three UK national databases
Lead Research Organisation:
University of Oxford
Department Name: Primary Care Health Sciences
Abstract
Purpose: Early evidence suggests increased severity of COVID-19 disease amongst Black, Asian and Ethnic minority (BAME) groups. There is limited evidence from population-based cohorts at scale across the UK or internationally that quantify within BAME group differences, or examine these in relation to modifiable risk factors.
Aim: To describe the prevalence of confirmed COVID-19 cases by ethnic group in a large and representative sample of UK adults, and to quantify the association between ethnicity and mortality stratified by COVID-19 infection and modifiable clinical and social risk factors (blood pressure, HbA1c level, total cholesterol, Body Mass Index, smoking status, co-morbidities, medication use, domicile and household number).
Methods: A cohort study of adults registered across three large national primary care databases in England, representing over 40% of the UK population. Participant sociodemographic, deprivation, clinical and domicile characteristics will be summarised and compared by higher level ethnic group (White, Black, Asian and Mixed Other) and their subgroups. For example, the Asian subgroup includes Pakistani, Indian, Bangladeshi or Chinese while the Black subgroup includes African or Carribean, as per the 2011 census. Hazard ratios and 95% confidence intervals for all-cause mortality and COVID-19 mortality, adjusted for potentially confounding factors will be calculated using Cox's proportional hazard regression.
Implication: Our findings could provide rapid evidence on patterns of COVID-19 and associated mortality across and within ethnic groups in the UK. This has the potential to inform targeted mitigation public health strategies, and could alter clinical thresholds for at-risk patients presenting with the infection.
Aim: To describe the prevalence of confirmed COVID-19 cases by ethnic group in a large and representative sample of UK adults, and to quantify the association between ethnicity and mortality stratified by COVID-19 infection and modifiable clinical and social risk factors (blood pressure, HbA1c level, total cholesterol, Body Mass Index, smoking status, co-morbidities, medication use, domicile and household number).
Methods: A cohort study of adults registered across three large national primary care databases in England, representing over 40% of the UK population. Participant sociodemographic, deprivation, clinical and domicile characteristics will be summarised and compared by higher level ethnic group (White, Black, Asian and Mixed Other) and their subgroups. For example, the Asian subgroup includes Pakistani, Indian, Bangladeshi or Chinese while the Black subgroup includes African or Carribean, as per the 2011 census. Hazard ratios and 95% confidence intervals for all-cause mortality and COVID-19 mortality, adjusted for potentially confounding factors will be calculated using Cox's proportional hazard regression.
Implication: Our findings could provide rapid evidence on patterns of COVID-19 and associated mortality across and within ethnic groups in the UK. This has the potential to inform targeted mitigation public health strategies, and could alter clinical thresholds for at-risk patients presenting with the infection.
Technical Summary
Purpose: Early evidence suggests increased severity of COVID-19 disease amongst Black, Asian and Ethnic minority (BAME) groups. There is limited evidence from population-based cohorts at scale across the UK or internationally that quantify within BAME group differences, or examine these in relation to modifiable risk factors.
Aim: To describe the prevalence of confirmed COVID-19 cases by ethnic group in a large and representative sample of UK adults, and to quantify the association between ethnicity and mortality stratified by COVID-19 infection and modifiable clinical and social risk factors (blood pressure, HbA1c level, total cholesterol, Body Mass Index, smoking status, co-morbidities, medication use, domicile and household number).
Methods: A cohort study of adults registered across three large national primary care databases in England, representing over 40% of the UK population. Participant sociodemographic, deprivation, clinical and domicile characteristics will be summarised and compared by higher level ethnic group (White, Black, Asian and Mixed Other) and their subgroups. For example, the Asian subgroup includes Pakistani, Indian, Bangladeshi or Chinese while the Black subgroup includes African or Carribean, as per the 2011 census. Hazard ratios and 95% confidence intervals for all-cause mortality and COVID-19 mortality, adjusted for potentially confounding factors will be calculated using Cox's proportional hazard regression.
Implication: Our findings could provide rapid evidence on patterns of COVID-19 and associated mortality across and within ethnic groups in the UK. This has the potential to inform targeted mitigation public health strategies, and could alter clinical thresholds for at-risk patients presenting with the infection.
Aim: To describe the prevalence of confirmed COVID-19 cases by ethnic group in a large and representative sample of UK adults, and to quantify the association between ethnicity and mortality stratified by COVID-19 infection and modifiable clinical and social risk factors (blood pressure, HbA1c level, total cholesterol, Body Mass Index, smoking status, co-morbidities, medication use, domicile and household number).
Methods: A cohort study of adults registered across three large national primary care databases in England, representing over 40% of the UK population. Participant sociodemographic, deprivation, clinical and domicile characteristics will be summarised and compared by higher level ethnic group (White, Black, Asian and Mixed Other) and their subgroups. For example, the Asian subgroup includes Pakistani, Indian, Bangladeshi or Chinese while the Black subgroup includes African or Carribean, as per the 2011 census. Hazard ratios and 95% confidence intervals for all-cause mortality and COVID-19 mortality, adjusted for potentially confounding factors will be calculated using Cox's proportional hazard regression.
Implication: Our findings could provide rapid evidence on patterns of COVID-19 and associated mortality across and within ethnic groups in the UK. This has the potential to inform targeted mitigation public health strategies, and could alter clinical thresholds for at-risk patients presenting with the infection.
Publications
Dambha-Miller H
(2021)
The Use of Primary Care Big Data in Understanding the Pharmacoepidemiology of COVID-19: A Consensus Statement From the COVID-19 Primary Care Database Consortium.
in Annals of family medicine
Clift A
(2021)
Sickle Cell Disorders and Severe COVID-19 Outcomes: A Cohort Study
in Annals of Internal Medicine
Dambha-Miller H
(2021)
Quantifying the association between ethnicity and COVID-19 mortality: a national cohort study protocol.
in BMJ open
Dambha-Miller H
(2022)
Mortality in COVID-19 among women on hormone replacement therapy: a retrospective cohort study.
in Family practice
Dambha-Miller H
(2023)
Mortality from angiotensin-converting enzyme-inhibitors and angiotensin receptor blockers in people infected with COVID-19: a cohort study of 3.7 million people
in Family Practice
Dambha-Miller H
(2022)
Primary care consultations for respiratory tract symptoms during the COVID-19 pandemic: a cohort study including 70,000 people in South West England.
in Family practice
Saatci D
(2021)
Association Between Race and COVID-19 Outcomes Among 2.6 Million Children in England.
in JAMA pediatrics
| Description | In the early phases of the COVID-19 pandemic, evidence began to emerge that there were ethnic inequalities in terms of the risks of being infected with SARS-CoV-2, and developing severe COVID-19 (i.e. either leading to hospital admission or death). In this study, we sought to assess these inequalities, quantify how severe they were, and look for any factors that may contribute to these. We undertook several analyses using data from the UK and Canada to provide international evidence about this, with the intention of informing public health strategy as the pandemic continued. In the main part of our study, we looked at ethnic differences in COVID-19 hospitalisation and death - we did this by using large databases in the UK (QResearch) and Canada (Ontario Health Database). We found that South Asians were at disproportionately higher risk of severe COVID-19, even when taking into account age, deprivation and medical conditions. Furthermore, we found that the contribution of other factors to these increased risks varied by ethnic group, and that only about 40%-60% of the excess risks in some groups can be explained by variation in clinical and demographic factors. Other analyses looked at COVID-19 risks in children (children from non-white ethnic groups were less likely to receive a COVID-19 test, and more likely to be admitted to intensive care than white children); found a 4-fold increased risk of COVID-19 hospitalisation in people with sickle cell disease; investigated how the uptake of existing vaccines (influenza, pneumococcal and shingles) differed across ethnic groups in older adults; and examined how these vaccines may have effect on risks of severe COVID-19. At the start of the COVID-19 pandemic, it appeared that people with specific medical conditions could have been at higher risk of developing severe infection, such as needing hospital treatment, or dying. People with these kinds of conditions were thought to be 'clinically extremely vulnerable', and were advised to 'shield'. This was referred to as the 'shielding list'. As part of the wider 'OX100' project, which developed a risk prediction equation called QCovid, we also looked at the risks of people with Down Syndrome. This is a genetic condition that is associated with heart and lung problems, and a weaker immune system. Therefore, people affected could have been at higher risk, but this was not known at the time. By using a type of study called a cohort study, which used the QResearch database, we found 4,053 people with Down Syndrome out of over 8 million adults. After taking into account factors such as age, ethnicity, body mass index, whether or not they lived in a care home, and a range of other medical conditions, we found that adults with Down syndrome had significantly higher risks of severe COVID-19 than people without the conditions. Adults with Down Syndrome had an almost 5-times higher risk of being hospitalised due to COVID-19, and a 10-times higher risk of dying due to COVID-19 in data from the first wave. Down Syndrome was included as a factor in the QCovid equations, and the results from this study led to the UK government adding this condition to the shielding list. |
| Exploitation Route | see above |
| Sectors | Healthcare |
| URL | https://www.qresearch.org/research/approved-research-programs-and-projects/quantifying-the-association-between-covid-19-ethnicity-and-mortality-a-cohort-study-across-three-uk-national-databases/ |
| Description | Engagement with policy colleagues |
| Geographic Reach | National |
| Policy Influence Type | Contribution to a national consultation/review |
| Description | Rapid funding call to use and enrich the data within the Data & Connectivity National Core Study (NCS) capability |
| Amount | £213,377 (GBP) |
| Funding ID | HDRUK2020.140 |
| Organisation | Health Data Research UK |
| Sector | Private |
| Country | United Kingdom |
| Start | 01/2021 |
| End | 12/2021 |
| Title | QResearch Database |
| Description | QWEB LOGIN QResearch GENERATING NEW KNOWLEDGE TO IMPROVE PATIENT CARE QResearch is a large consolidated database derived from the anonymised health records of over 35 million patients. QResearch is a large consolidated database derived from the anonymised health records from general practices using the EMIS clinical computer system. The practices are spread throughout the UK and include data from patients who are currently registered with the practices as well as historical patients who may have died or left. Historical records extend back to the 1989 making it one of the largest and richest general practice databases in the world. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2021 |
| Provided To Others? | Yes |
| Impact | QWEB LOGIN QResearch GENERATING NEW KNOWLEDGE TO IMPROVE PATIENT CARE QResearch is a large consolidated database derived from the anonymised health records of over 35 million patients. QResearch is a large consolidated database derived from the anonymised health records from general practices using the EMIS clinical computer system. The practices are spread throughout the UK and include data from patients who are currently registered with the practices as well as historical patients who may have died or left. Historical records extend back to the 1989 making it one of the largest and richest general practice databases in the world. |
| URL | http://www.qresearch.org |
| Description | Collaboration with Canada |
| Organisation | University of Toronto |
| Country | Canada |
| Sector | Academic/University |
| PI Contribution | contributing UK data for collaboration on population-level cohort studies and individual participant meta-analysis |
| Collaborator Contribution | contributing Canada data for collaboration on population-level cohort studies and individual participant meta-analysis |
| Impact | Publications |
| Start Year | 2020 |
| Description | Collaboration with University of Leicester |
| Organisation | University of Leicester |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | Lead on the project |
| Collaborator Contribution | Intellectual contributions to the project |
| Impact | Publication |
| Start Year | 2020 |