Inequalities in COVID19 mortality related to ethnicity and socioeconomic deprivation
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Abstract
Background
Initial reports suggest that ethnic minorities may be experiencing more severe coronavirus disease 2019 (COVID19) outcomes. We therefore assessed the association between ethnic composition, income deprivation and COVID19 mortality rates in England.
Methods
We performed a cross-sectional ecological analysis across England’s upper-tier local authorities. We assessed the association between the proportion of the population from Black, Asian and Minority Ethnic (BAME) backgrounds, income deprivation and COVID19 mortality rates using multivariable negative binomial regression, adjusting for population density, proportion of the population aged 50–79 and 80+ years, and the duration of the epidemic in each area.
Findings
Local authorities with a greater proportion of residents from ethnic minority backgrounds had statistically significantly higher COVID19 mortality rates, as did local authorities with a greater proportion of residents experiencing deprivation relating to low income. After adjusting for income deprivation and other covariates, each percentage point increase in the proportion of the population from BAME backgrounds was associated with a 1% increase in the COVID19 mortality rate [IRR=1.01, 95%CI 1.01–1.02]. Each percentage point increase in the proportion of the population experiencing income deprivation was associated with a 2% increase in the COVID19 mortality rate [IRR=1.02, 95%CI 1.01–1.04].
Interpretation
This study provides evidence that both income deprivation and ethnicity are associated with greater COVID19 mortality. To reduce these inequalities, Government needs to target effective control and recovery measures at these disadvantaged communities, proportionate to their greater needs and vulnerabilities, during and following the pandemic.
Funding
National Institute of Health Research; Medical Research Council
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SciScore for 10.1101/2020.04.25.20079491: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Strengths and limitations: This study reveals, for the first time, ethnic and socioeconomic inequalities in COVID19 mortality rates across English upper-tier local authorities. We performed a comprehensive analysis of all COVID19 deaths of patients in English hospitals, using the most up-to-date data readily available, therefore our …
SciScore for 10.1101/2020.04.25.20079491: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Strengths and limitations: This study reveals, for the first time, ethnic and socioeconomic inequalities in COVID19 mortality rates across English upper-tier local authorities. We performed a comprehensive analysis of all COVID19 deaths of patients in English hospitals, using the most up-to-date data readily available, therefore our results are likely to be broadly generalisable to the English population, although caveats regarding the underreporting of deaths within official figures should be considered. Additionally, a number of robustness tests confirmed our results, using alternative models, less up-to-date but more comprehensive ONS death data, and models excluding London. Our research highlights an important emerging issue, and it is intended that the findings will prompt further investigation. Our results are nonetheless preliminary, and there are several limitations that should be considered when interpreting the results. In terms of study design, methodological limitations of ecological studies can include ecological bias whereby associations present at the group-level are not apparent at the individual-level, possibly due to unmeasured confounding or measurement error.30 Data were aggregated to relatively large areas (upper tier local authorities containing approximately 370,000 people on average) which may have increased the likelihood of ecological bias. Nevertheless, because ecological studies are able to capture risk factors and exposures that operate at the com...
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
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