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Quantifying the association between COVID-19, ethnicity and mortality: A cohort study across three UK national databases

Title

Quantifying the association between COVID-19, ethnicity and mortality: A cohort study across three UK national databases

What is the aim of the study and why is it important?

Early on in the COVID-19 pandemic, scientists and doctors noticed that different ethnic groups seemed to have different risks of getting infected with COVID-19. They also noticed that the ethnic groups who were more likely to have the COVID-19 infection were more likely to get serious complications from having COVID-19 (like going to hospital or dying).

It was important to learn more about these patterns and inequalities, so that health services would know how to respond to them and make improvements. This included needing to learn more about these patterns (inequalities) including how big the differences are and why they might happen. This study set out to answer those questions by using information from the UK and Canada. This means that the information this study finds can tell readers about more than one country and health setting.

To do this, the researchers looked at large health databases in the UK and Canada. In the UK, the researchers used the QResearch database. The QResearch database contains information from millions of anonymised GP records (this means that individuals cannot be identified) so this database can be used to help answer these questions. In Canada, the researchers used the Ontario health database, which is an administrative healthcare database representing everyone in Ontario and covers about 40% of the Canadian population.
Using these databases, the researchers looked at whether there were differences across ethnic groups in the number of people who were admitted to hospital or died with COVID-19. To do this, this study used the ethnic group that was recorded on people’s health record. There are lots of these groups – some examples include: South Asian, Black African, or White.
Doing this, the researchers found that people with South Asian ethnicity on their health records were at a higher risk of serious complications from COVID-19. To try to understand this, the researchers looked at other things that can affect risk of serious complications, like having other medical conditions, age, and socio-economic status. Even when these were taken account of, the higher risk was still there for people with South Asian ethnicity. In fact, only about 40-60% of the higher risk in this group could be explained by those other factors, meaning that the rest of the higher risk is not fully explained by this study.

The study team also wanted to explore if these differences observed across ethnic groups in adults also were seen in children. They found that children from non-white backgrounds were less likely to be tested for COVID-19 but if they had a test which was positive, they were more likely to be admitted to hospital or intensive care compared to children from White backgrounds.

Finally, researchers also wanted to investigate if certain medical problems that are more commonly seen in ethnic minority groups, such as sickle cell disease, could be linked to serious COVID-19 complications. In fact, people who had sickle-cell disease had a 4 times higher risk of being admitted to hospital if they got COVID-19.

Chief Investigator

Julia Hippisley-Cox

Sponsor

Oxford University

Location of research

Oxford University

Date on which research approved

21-Oct-2020

Project reference ID

OX102

Generic ethics approval reference

18/EM/0400

Are all data accessed are in anonymised form?

Yes

Brief summary of the dataset to be released (including any sensitive data)

We will combine results from national primary care databases in England including QResearch (21 million records), CPRD (14 million records) and the publicly available OpenSAFELY platform (24 million records). A detailed description of each database has been published elsewhere.[7,9] We will remove duplicates so that each record only appears once in the dataset. The sample will represent over 40% of the UK population.

What were the main findings?

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.

Funding Source

MRC

Research Team

Defne Saatci (University of Oxford)

Kamlesh Khunti (University of Leicester)

Hajira Dambha-Miller (University of Southampton)

Simon Griffin (University of Cambridge)

Pui San Tan (University of Oxford)

Carol Coupland (University of Nottingham)

Baiju Shah (Institute of Health Policy, Management and Evaluation, Ontario)

Ashley Clift (University of Oxford)

Martina Patone (University of Oxford)

Francesco Zaccardi (University of Leicester)

Approval Letters

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