Evidence map›Paper›PMID 33303461›Full record

ArticleBMJ open2020

Evidence for ethnic inequalities in mortality related to COVID-19 infections: findings from an ecological analysis of England.

James Nazroo, Laia Becares

Abstract read
In one paragraph

Article in BMJ open, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

26 citing papers in PubMed, 1 synthesis or guideline pooled it.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

James NazrooSociology, The University of Manchester, Manchester, UK james.nazroo@manchester.ac.uk.ORCID http://orcid.org/0000-0001-6744-2207
Laia BecaresSocial Work and Social Care, University of Sussex, Falmer, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesIn the absence of robust direct data on ethnic inequalities in COVID-19-related mortality in the UK, we examine the relationship between ethnic composition of an area and rate of mortality in the area.

designEcological analysis of COVID-19-related mortality rates occurring by 24 April 2020 and ethnic composition of the population. Account is taken of age, population density, area deprivation and pollution.

settingLocal authorities in England.

resultsFor every 1% rise in proportion of the population who are ethnic minority, COVID-19-related deaths increased by 5·12, 95% CI (4·00 to 6·24), per million. This rise is present for each ethnic minority category examined, including the white minority group. The size of this increase is a little reduced in an adjusted model to 4·42, 95% CI (2·24 to 6·60), suggesting that some of the association results from ethnic minority people living in more densely populated, more polluted and more deprived areas.This estimate suggests that the average England COVID-19-related death rate would rise by 25% in a local authority with two times the average number of ethnic minority people.

conclusionsWe find clear evidence that rates of COVID-19-related mortality within a local authority increases as the proportion of the population who are ethnic minority increases. We suggest that this is a consequence of social and economic inequalities driven by entrenched structural and institutional racism and racial discrimination. We argue that these factors should be central to any investigation of ethnic inequalities in COVID-19 outcomes.

Indexed as

Healthcare DisparitiesHealth Status DisparitiesAdolescentAdultAgedAged, 80 and overChildChild, PreschoolCOVID-19EnglandEthnicityFemaleHumansInfantInfant, NewbornLinear Modelsepidemiologypublic health

Identifiers

PMID33303461
PMCPMC7733217

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.