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Ethnic reporting and representation in UK COVID-19 consenting observational studies; a systematic review [version 1; peer review: awaiting peer review]
Дата публикации: 04-08-2026 09:06:03

Background Evidence suggests ethnic minority populations are disproportionately impacted by COVID-19, however ethnic minority groups are often under-represented in research with ethnicity associations not being investigated. Observational studies are an important tool for understanding the health inequalities of ethnic minority populations. We aimed to assess the reporting of ethnic composition and representation of ethnic minority groups in COVID-19 consented observational studies in the UK. Methods A systematic review of COVID-19 studies was conducted in OVID MedLine electronic database (1st January 2020-22nd November 2022). Observational, opt-in consenting studies of COVID-19 exposures and outcomes with a minimum of 96 participants in the UK only were eligible. Studies that were non-medical, COVID-19 vaccination studies and studies investigating the impact of COVID-19 policies were excluded as were studies that registered only children (

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Systematic Review

[version 1; peer review: awaiting peer review]

Naomi V Bradbury

https://orcid.org/0000-0002-8934-6301

1,2, Sarah Booth2, Laura J Gray1,2, [...] Angus Jennings2, Sangyu Lee2,3, Daniel S March4, Urvi Modha2, Elnaz Saeedi2,5, Rahma Said2, Aiden Smith2, Rachael Stannard2, Lucy Teece1,2,4

Naomi V Bradbury

https://orcid.org/0000-0002-8934-6301

1,2, Sarah Booth2, [...] Laura J Gray1,2, Angus Jennings2, Sangyu Lee2,3, Daniel S March4, Urvi Modha2, Elnaz Saeedi2,5, Rahma Said2, Aiden Smith2, Rachael Stannard2, Lucy Teece1,2,4

Author details Author details

1 Leicester NIHR Biomedical Research Centre (BRC), University of Leicester, Leicester, UK
2 School of Medical Sciences, University of Leicester, Leicester, UK
3 Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
4 Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
5 Oxford Clinical Trials Research Unit, Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK

Naomi V Bradbury
Roles: Data Curation, Formal Analysis, Investigation, Visualization, Writing – Original Draft Preparation

Sarah Booth
Roles: Investigation, Writing – Review & Editing

Laura J Gray
Roles: Supervision, Writing – Review & Editing

Angus Jennings
Roles: Investigation, Writing – Review & Editing

Sangyu Lee
Roles: Investigation, Writing – Review & Editing

Daniel S March
Roles: Investigation, Writing – Review & Editing

Urvi Modha
Roles: Investigation, Writing – Review & Editing

Elnaz Saeedi
Roles: Investigation, Writing – Review & Editing

Rahma Said
Roles: Investigation, Writing – Review & Editing

Aiden Smith
Roles: Investigation, Writing – Review & Editing

Rachael Stannard
Roles: Investigation, Writing – Review & Editing

Lucy Teece
Roles: Conceptualization, Data Curation, Funding Acquisition, Investigation, Methodology, Project Administration, Resources, Supervision, Writing – Review & Editing

OPEN PEER REVIEW

REVIEWER STATUS AWAITING PEER REVIEW

Keywords

COVID-19, literature review, observational studies, ethnicity, UK

Corresponding author: Laura J Gray Competing interests: No competing interests were disclosed.

Grant information: This study was funded by the National Institute for Health and Care Research (NIHR) Applied Research Collaboration East Midlands (ARC EM) and Leicester NIHR Biomedical Research Centre (BRC). The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care.
The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Copyright:  © 2026 Bradbury NV et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. How to cite: Bradbury NV, Booth S, Gray LJ et al. Ethnic reporting and representation in UK COVID-19 consenting observational studies; a systematic review [version 1; peer review: awaiting peer review]. F1000Research 2026, 15:1291 (https://doi.org/10.12688/f1000research.183931.1) First published: 04 Aug 2026, 15:1291 (https://doi.org/10.12688/f1000research.183931.1) Latest published: 04 Aug 2026, 15:1291 (https://doi.org/10.12688/f1000research.183931.1)

Background

With the emergence of the COVID-19 pandemic in the UK at the beginning of March 2020, it soon became clear that ethnic minority groups within the country were being disproportionally affected by the disease in terms of both levels of infection and poor outcomes including hospitalisation and death.1–3

Representativeness is essential for accurate, unbiased, generalisable, and relevant medical research but many studies have shown that ethnic minorities are poorly represented in research studies including clinical trials.4,5 For example, Murali et al found this to be the case for Asian, Black and mixed ethnic groups in UK based COVID-19 randomised controlled trials with only 1% of study participants having black ethnicity compared to 3.3% of individuals in the ONS census and 5.8% representation of individuals of Asian ethnicities compared to 7.5% in the census data.6 Representation is vital in medical research so that best practice and new treatments are offered to people who are disproportionally affected by disease burden and, therefore, have the most to gain.

Consented observational studies are epidemiological studies that require participants to give informed consent before taking part, in contrast to observational studies using routinely collected data where individual consent is usually not required. One such example is UK-Biobank, a prospective study of over 500,000 UK individuals aged between 40 and 69.7 One advantage that is often cited of observational studies is their representativeness as the study should reflect the population being observed. However, this may not necessary be true for consented observational studies as there is likely to be participation bias.8 For example, UK-Biobank had a response rate of only 5.5% and participants were found to be more likely to be of white ethnicity or female and less likely to have chronic health conditions or live in an area of social deprivation compared to the general UK population.9,10

Although previous systematic reviews have assessed the ethnic representation in consented observational studies in other disease areas (finding that few publications reported ethnicity data and, in those that did, ethnic minority groups were underrepresented),11,12 to date this has not been assessed in studies relating to COVID-19. Therefore, the objective of this systematic review was to assess the reporting of ethnic composition of COVID-19 consented observational research in the UK and where possible assess the representativeness. The primary research question is - what proportion of UK COVID-19 consented observational study publications described the ethnic composition of participants?

The review also aimed to answer the following secondary questions:

  • 1. How did these studies measure and report ethnicity?

  • 2. How does the ethnic composition of participant samples in UK COVID-19 consenting observational research compare to the UK general population?

  • 3. What proportion of studies considered selection bias and the ethnic representation of participants during the sample selection process?

  • 4. What proportion of studies included no ethnic minority participants?

  • 5. How often did this research actively address non-representative participant samples in the analysis stages? And how?

  • 6. What proportion of studies produced results that were specifically relevant to ethnic minority groups?

Methods
Review design

The review is reported according to the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines (Supplementary File 1).

Eligibility criteria

This review included observational medical research studies, which used opt-in consenting mechanisms to obtain patient data to investigate COVID-19 exposures and outcomes in the UK.

Observational studies included cohort, case-control and cross-sectional studies as well as case-series. Randomised trials and other interventional studies, including COVID-19 vaccination studies, were not considered due to their considerably different purpose and methodologies. Studies which were non-medical (e.g. economic or education), diagnostic and lab-based studies, or qualitative research were excluded.

The review focused on observational studies which used opt-in consenting mechanisms (i.e. participants were required to actively give informed consent for the use of their data) as there is a known difference in participant characteristics between those who consent to join research and those who do not.13

The review was restricted geographically to studies with participants from the United Kingdom (UK) only (i.e. not in combination with other countries) to enable comparisons to the general population via ONS census data. Included studies were required to investigate COVID-19, either as an outcome or as an exposure (including but not limited to COVID-19 infection, mortality, morbidity, hospitalisation, symptom resolution, or clinical improvement). Studies that evaluated the impact of COVID-19 policies during the pandemic (e.g. lockdown, social distancing, shielding, personal protective equipment) were excluded. The systematic review focused on ethnic reporting and representation in studies conducted in UK participants, thus only English language articles reporting on studies in humans were included. Studies in children (aged <18) only were also excluded.

As the review focused on studies investigating COVID-19, only articles published after January 2020 were included. Systematic reviews, cohort descriptions, protocols, pre-prints, letters and conference abstracts were excluded.

We imposed a minimum sample size of 96 participants to restrict the review to studies in which we could report the proportion of participants within each ethnic group with a 10% margin of error and 95% confidence interval, assuming the proportion of White ethnic group to be 85%.14

Search Strategy

Articles were identified using the OVID MedLine electronic database – a database with coverage greater than 90%.15 The search strategy focused on restricting articles with three components:

  • • COVID-19 studies: using the Medical Subject Headings (MeSH) term, which has been shown to give reasonable sensitivity and precision compared to other combination strategies.16

  • • UK studies: using a validated geographic search filter composed of combinations of free-text keywords.17

  • • Observational studies: a methodological search filter composed of combinations of free-text keywords18

The search strategy was further restricted to full text articles of human studies published in the English language between 1st January 2020 and 22nd November 2022. The criteria for studies to use opt-in consenting mechanisms was then assessed at the full-text article screening stage. A full search strategy is available in Supplementary File 2.

Selection process

The selection process and data extraction stages were conducted using Covidence software.19 Duplicates were removed and the titles and abstracts were independently screened for inclusion by at least two of the reviewers. Full text articles for those not excluded were retrieved and again independently screened by two reviewers. Any conflicts between reviewer decisions were resolved via a third reviewer. Reasons for exclusion at the full text stage were recorded.

Data extraction

Data were extracted independently from eligible articles by two reviewers using a standardized data collection form. Conflicts in extracted data were resolved by a third reviewer.

The following information was extracted:

  • 1. Bibliographic details: author, publication date (month/year), and journal name.

  • 2. Characteristics of included studies: observational study design (case-control, cohort, cross-sectional, other), data source, target population (including regional location, population setting, participant characteristic restrictions, and whether ethnic composition discussed), COVID-19 outcomes or exposures assessed, reporting of ethnicity-focused aims/objectives.

  • 3. Participant characteristics: number of participants, average age of participants, gender composition of participants.

  • 4. Ethnic composition: ethnic composition of participants, terms used (ethnicity, race, BAME, non-White), methods used to obtain participant ethnicity information (self-reported, linked health records, other), categorisation of ethnicities.

  • 5. Addressing representation through methodology: reference to selection bias or representativeness, ethnicity-related inclusion/exclusion criteria, considerations of representative sample selection procedure, methods of managing missing ethnicity information, analysis methods to address non-representativeness (Adjustment, Stratification, Weighting, Standardisation, Other), ethnicity disaggregated results reported.

Risk of bias assessment

A risk of bias assessment was judged not be needed for this review and this reasoning is explained within the discussion section.

Evidence synthesis

Data were extracted from the Covidence website and analysed in R v4.3.3 using summary statistics such as count (%) and visually using bar plots.20 Given the nature of the data extracted, meta-analyses were not appropriate.

The general population comparator data used was from the Office for National Statistics (ONS) England and Wales Census 2021 based on the five high-level ethnic groups of Asian, Black, Mixed or multiple, White and Other.21 As ethnicity was not reported consistently across studies, for each study ethnicity was converted into percentages based on either the ONS five high-level groups (when sufficient data was available) or into binary white and other groups. Ethnicity data at the study level was then compared to the ONS data using bar plots.

Results
Study characteristics

A total of 8973 unique studies were identified using the search strategy. Of these, 7505 were excluded during abstract screening and a further 1330 studies were excluded at the full text screening phase ( Figure 1). This left a total of 138 studies that were included in the systematic review (Table 1(extended data)). Most studies included participants from England, often alongside participants from other UK nations. Studies ranged in size from around 100 participants (as the minimum study size was 96) to over 1.5 million participants.

121a652c-ae78-47e9-a28d-7df8dfe22165_figure1.gif

Figure 1. PRISMA flow chart for the systematic review detailing the database search, screening and exclusion criteria.

The studies included in this review used data from a large variety of observational, longitudinal databases. By far the most common of which was UK-Biobank (69 studies, 50%). The second most used database was the Zoe Symptom Study app (7 studies, 5%). 17 studies (12.3%) collected their own data ( Figure 2).

121a652c-ae78-47e9-a28d-7df8dfe22165_figure2.gif

Figure 2. Databases used to conduct the observational studies included in this review.

ISARIC - International Severe Acute Respiratory Infection Consortium, REACT-1 - The REal-time Assessment of Community Transmission-1 study, SIREN- SARS-CoV-2 Immunity and Reinfection Evaluation study.

Ethnicity reporting and categorisation

Of the 138 studies in this systematic review, 100 (72.5%) reported the ethnicity of the participants while 38 studies did not. Eight (5.8%) studies reported ethnicity-focused aims or objectives. Twelve (8.7%) studies mentioned their consideration of selection bias pertaining to ethnic representation of participants. Nine studies (6.5%) had restrictions to the study participants based on their ethnicity, such as only including participants with European ancestry.22,23 34 studies (24.6%) addressed non-representative participant samples in some way in their statistical analysis through the use of techniques such as adjustment/regression or stratification.

A variety of words were used to describe ethnicity across the studies included within this systematic review. The term ‘ethnicity’ was used most frequently with many authors also using the phrases ‘ethnic minority’, ‘black’, ‘non-white or non-black’ or ‘race’. Ethnicity was categorised in a large variety of ways across studies. Only a small number of studies used the recognised ONS 5-level (14 (10.1%) studies) or 16-level (1 study) ethnicity categories. 28 (20.3%) studies reported ethnicity using binary categories (white and other).

For those studies that reported ethnicity, 79 (79%) obtained this information through participants self-reporting their ethnicity. Only one did not include any ethnic minority participants.24 The proportion of white participants in the other studies ranged from 45 – 96.9% (Table 2 (extended data) and Table 3). 56 studies (56%) reported ethnicity disaggregated results (Table 3).

Table 3. Ethnicity data used in this review.

Column 2 is the ONS 2021 5-level Census ethnicity data used as a comparator (both in the original format and converted to binary (white and other) ethnicity).21 Column 3 is the range of ethnicity percentages found amongst the studies included within this review subdivided into studies that reported sufficient ethnicity data for ONS 5-level or binary groups.

EthnicityONS Census (percentage)Studies in this review (percentage range)ONS 5-level Asian9.30.5 – 38.8Black4.00.6 – 8.6Mixed2.90.5 – 5.7White81.755.1 – 95.4Other2.10.3 – 4.5Binary White81.745.0 – 100.0Other18.30 – 55.0
Representation of ethnic minority groups

Study-level comparisons of the ethnic composition of participants (either 5-level or binary) for all studies that reported ethnicity compared to ONS Census data can be found at https://epimodelling.shinyapps.io/Ethnicity/.

63 studies (79.7%) over-represented white participants compared to the ONS census data and, therefore, under-represented participants of other ethnicities. 16 studies (20.3%) over-represented ethnic minority participants compared to ONS Census data. Typically, these were studies where the authors had collected their own data. One example of a study reporting ethnicity at ONS 5-level and having a higher percentage of ethnic minority participants than the ONS data was Evans et al 202125 ( Figure 3). This study sourced their data from the Post-hospitalisation COVID-19 study (PHOSP-COVID), a multicentre study of patients discharged from hospital after a diagnosis of COVID-19.

121a652c-ae78-47e9-a28d-7df8dfe22165_figure3.gif

Figure 3. An example of a study with a higher representation of ethnic minority groups from Evans et al 2021.25
Discussion

The majority of studies included in this systematic review (72.5%) reported the ethnicity of the participants within their observational study. However, this still left over a quarter of the studies not reporting participant ethnicity. This compares favourably to Ranganathan and Bhopal, a review of ethnicity reporting in cardiovascular cohort studies, where over half the studies included within their systematic review did not report participant ethnicity.11 This may be due to improved ethnicity reporting over time as Ranganathan and Bhopal included many older studies (prior to 1975) and the awareness of the effect of COVID-19 on ethnic minority populations from early in the pandemic. In COVID-19 systematic reviews investigating ethnic inequalities, Sze et al excluded 95 of 611 articles (15.5%) and Irizar et al 161 of 1,523 studies (10.6%) as they did not report ethnicity.2,26 Sze et al also noted that ethnic minority groups continued to be under-represented in COVID-19 studies.2

In contrast, ethnicity reporting appears to be more routine for clinical trials. This is likely because clinicaltrials.gov has required the reporting of ethnicity data for registered trials since 2017.27 Murali et al found only one UK based COVID-19 trial of 30 (3.3%) did not include data on ethnicity.6 However, coverage of ethnicity reporting is still lacking even in randomised controlled trials.28

Only one of the studies that reported participant ethnicity did not include any ethnic minority participants. The most common way for studies to obtain data on participant ethnicity was through self-reporting. Only a very small proportion (8.7%) of studies considered selection bias relating to the ethnicity of participants.

The studies in this systematic review either collected their own data or obtained their participant data from other research databases. By far the most used database was UK-Biobank, representing 50% of the studies included within this systematic review suggesting that large, prospective databases such as UK-Biobank provide a valuable resource for researchers wishing to conduct their own observational studies, despite the known issues with representativeness.29,30

As expected, with so many of the studies included in this review using data from UK-Biobank, ethnic minority participants were under-represented in many of the studies when compared to the overall ethnic composition of England and Wales as reported in the recent 2021 Census.10,21

Some studies had an over-representation of ethnic minority groups compared to the national data. Typically, these were studies that had collected their own data, for example Lanham et al 2021’s participants were comprised of patients from a single London hospital. Other larger, multicentre studies were also included within this group such as PHOSP-COVID and the United Kingdom Research study into Ethnicity and COVID-2019 Outcomes in Healthcare workers (UK-REACH). This over-representation of ethnic minority groups compared to the national data could be due to the study being representative of their target population (i.e. a study conducted in London should have a higher proportion of ethnic minority participants than England as London is a more ethnically diverse area) or because participants are selected from a COVID-19 patient population that contains a higher proportion of ethnic minority individuals than the general population.

This study is the first to consider ethnic reporting and representation in COVID-19 consented observational studies. There are some limitations to be considered. The comparator ethnicity data was taken from the ONS 2021 Census that was conducted in England and Wales.31 As studies included within this systematic review could also include participants from Scotland and Northern Ireland, the comparator data is likely to slightly overestimate the proportion of ethnic minority groups throughout the entire UK. However, as there is no census data available covering the entirety of the UK, as England has by far the largest population of the nations of the UK, and as most of the studies included within this systematic review included English participants, the ONS census data was judged to be the best comparator data available.

Ethnicity was reported in many ways across studies and, therefore, it was necessary create a more consistent way of reporting ethnicity in order to conduct this analysis. A small number of studies used the standard ONS 5-level groups and one study reported ethnicity using the 16-level ONS ethnic groups.21 It was much more common for only some of the ONS 5-level groups to be reported. For example, some studies reported the proportion of participants of white, black and other ethnicities. Several studies also reported the proportion of South Asian participants but not other Asian ethnicities.

A more consistent system for reporting participant ethnicity (such as the ONS 5-level groups) across studies would have made it possible to better investigate if study ethnicity was representative of the UK population.32 As half of the studies used UK-Biobank data and, therefore, presumably received the same detail on participant ethnicity it is discouraging that so much of this data is lost.

For this study only one database was searched (OVID MEDLINE) for studies published by November 2022 meaning that some studies may not have been included within this systematic review (MEDLINE has been found to have coverage of over 90%15). However, given the large number of studies that were found using the search strategy and included for data extraction, it is unlikely that any missing studies would change our findings significantly. Likewise, the cut-off date for the literature search being greater than one year ago does not make our findings out-of-date as this, in effect, provides a snapshot of the research effort during the pandemic phase of the disease as opposed to the ongoing endemic disease period.33

A risk of bias assessment was judged to not be appropriate for this systematic review. The design of this review was different to the ‘typical’ systematic review in that we were not assessing a particular intervention or outcome nor pooling data to estimate an effect size. The study aims were to investigate the bias surrounding ethnicity reporting in COVID-19 consented observational studies and, therefore, we are already explicitly acknowledging the bias present in these studies.

Conclusions

Despite findings from very early in the COVID-19 pandemic suggesting ethnic minority individuals were disproportionally affected by the disease,1,3 over a quarter of the observational, consented studies did not report the ethnicity of their study participants even though this data was often available to the authors. Improvements to the proportion and consistency of participant ethnicity reporting for all observational studies would make assessing the representation of ethnic minority participants more straightforward for future systematic reviews and promote more equitable healthcare.

Ethics approval and consent to participate

Not applicable

Registration

The review was not registered

For the purpose of open access, the author has applied a Creative Commons Attribution license (CC BY) to any Author Accepted Manuscript version arising from this submission.

Acknowledgements

Not applicable

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Grant information

This study was funded by the National Institute for Health and Care Research (NIHR) Applied Research Collaboration East Midlands (ARC EM) and Leicester NIHR Biomedical Research Centre (BRC). The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care.
The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Copyright

© 2026 Bradbury NV et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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