Ethnicity, household composition and COVID-19 mortality: a national linked data study

  1. Vahé Nafilyan
  2. Nazrul Islam
  3. Daniel Ayoubkhani
  4. Clare Gilles
  5. Srinivasa Vittal Katikireddi
  6. Rohini Mathur
  7. Annabel Summerfield
  8. Karen Tingay
  9. Miqdad Asaria
  10. Ann John
  11. Peter Goldblatt
  12. Amitava Banerjee
  13. Myer Glickman
  14. Kamlesh Khunti

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Abstract

To estimate the proportion of ethnic inequalities explained by living in a multi-generational household.

Design

Causal mediation analysis.

Setting

Retrospective data from the 2011 Census linked to Hospital Episode Statistics (2017-2019) and death registration data (up to 30 November 2020).

Participants

Adults aged 65 years or over living in private households in England from 2 March 2020 until 30 November 2020 (n=10,078,568).

Main outcome measures

Hazard ratios were estimated for COVID-19 death for people living in a multi-generational household compared with people living with another older adult, adjusting for geographic factors, socioeconomic characteristics and pre-pandemic health.

Results

Living in a multi-generational household was associated with an increased risk of COVID-19 death. After adjusting for confounding factors, the hazard ratios for living in a multi-generational household with dependent children were 1.17 (95% confidence interval [CI] 1.06–1.30) and 1.21 (95% CI 1.06–1.38) for elderly men and women. The hazard ratios for living in a multi-generational household without dependent children were 1.07 (95% CI 1.01–1.13) for elderly men and 1.17 (95% CI 1.07–1.25) for elderly women. Living in a multi-generational household explained about 11% of the elevated risk of COVID-19 death among elderly women from South Asian background, but very little for South Asian men or people in other ethnic minority groups.

Conclusion

Elderly adults living with younger people are at increased risk of COVID-19 mortality, and this is a contributing factor to the excess risk experienced by older South Asian women compared to White women. Relevant public health interventions should be directed at communities where such multi-generational households are highly prevalent.

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  1. Version published to 10.1177/0141076821999973
  2. ScreenIT

    SciScore for 10.1101/2020.11.27.20238147: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variableWe estimated separate models for males and females, as the risk of death involving COVID19 differs markedly by sex [7].

    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: The primary strength of our study lies in the use of a unique linked population-level dataset which combine the 2011 Census with death registration data and hospital records. Unlike data based solely on health records, our study dataset contains a broad range of information on demographic, socio-economic, and household characteristics, including occupation. Unlike sample survey data, it contains millions of observations covering the entire population of interest, allowing us to examine both the association between household composition and COVID-19 mortality and also whether living in a multi-generational household explains some of the disparity in COVID-19 mortality between ethnic groups. We were able to examine differences between disaggregated ethnic minority groupings rather than high-level categories of South Asian, Black, and Other. The main limitation of our study is that household composition is likely to be imprecisely measured. Whilst household composition is based on a detailed and accurate measurement taken in 2011, we could only identify changes since then due to death of household members or a move to a care home. Whist we took several steps to limit the measurement error, such as focusing on older adults, including only adults aged 25 or over and children aged 0 to 9 at the time of the census in our definition of household composition, our household composition measure may not reflect current living circumstances of everybody in our p...

    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.

    About SciScore

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  3. Version published to 10.1101/2020.11.27.20238147 on medRxiv