Inequalities in excess premature mortality in England during the COVID-19 pandemic: a cross-sectional analysis of cumulative excess mortality by area deprivation and ethnicity
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Abstract
To examine magnitude of the impact of the COVID-19 pandemic on inequalities in premature mortality in England by deprivation and ethnicity.
Design
A statistical model to estimate increased mortality in population subgroups during the COVID-19 pandemic by comparing observed with expected mortality in each group based on trends over the previous 5 years.
Setting
Information on deaths registered in England since 2015 was used, including age, sex, area of residence and cause of death. Ethnicity was obtained from Hospital Episode Statistics records linked to death data.
Participants
Population study of England, including all 569 824 deaths from all causes registered between 21 March 2020 and 26 February 2021.
Main outcome measures
Excess mortality in each subgroup over and above the number expected based on trends in mortality in that group over the previous 5 years.
Results
The gradient in excess mortality by area deprivation was greater in the under 75s (the most deprived areas had 1.25 times as many deaths as expected, least deprived 1.14) than in all ages (most deprived had 1.24 times as many deaths as expected, least deprived 1.20). Among the black and Asian groups, all area deprivation quintiles had significantly larger excesses than white groups in the most deprived quintiles and there were no clear gradients across quintiles. Among the white group, only those in the most deprived quintile had more excess deaths than deaths directly involving COVID-19.
Conclusion
The COVID-19 pandemic has widened inequalities in premature mortality by area deprivation. Among those under 75, the direct and indirect effects of the pandemic on deaths have disproportionately impacted ethnic minority groups irrespective of area deprivation, and the white group the most deprived areas. Statistics limited to deaths directly involving COVID-19 understate the pandemic’s impact on inequalities by area deprivation and ethnic group at younger ages.
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SciScore for 10.1101/2021.05.18.21256717: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics not detected. Sex as a biological variable not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. 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:However, this study does have some limitations. The ethnic groups used in the analysis are broad and may hide important differences among ethnic sub-groups. This is particularly important for the Asian group, among whom there is evidence of variation in …
SciScore for 10.1101/2021.05.18.21256717: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics not detected. Sex as a biological variable not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. 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:However, this study does have some limitations. The ethnic groups used in the analysis are broad and may hide important differences among ethnic sub-groups. This is particularly important for the Asian group, among whom there is evidence of variation in Covid-19 outcomes between Bangladeshi, Pakistani and Indian groups (3, 6). Broad ethnic groups were analysed instead of more detailed groups to reduce bias caused by differences in the recording of ethnicity between the denominator data for populations (Census data) and information obtained on deaths using hospital activity data (HES data). The number of excess deaths among ‘Other’ ethnic groups should also be interpreted with some caution due to this potential mismatch. Accounting for deprivation using quintiles of small areas does not identify deprived individuals or households within areas, so there may be greater effects of deprivation on excess deaths than identified in this study. Finally, the relative impact of the pandemic on sub-groups of the population may have varied throughout the pandemic period; by presenting the cumulative estimates we are not able to identify this variation. Our findings need further investigation as to why these differences in mortality between ethnic groups independent of deprivation exist; a first step could be to look at underlying morbidities and aspects of deprivation not measured in the index used. Further work is also required to understand how the relationship between deprivation, ethn...
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We found bar graphs of continuous data. We recommend replacing bar graphs with more informative graphics, as many different datasets can lead to the same bar graph. The actual data may suggest different conclusions from the summary statistics. For more information, please see Weissgerber et al (2015).
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.
Results from scite Reference Check: We found no unreliable references.
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