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

OBJECTIVE: 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.

Gender gaps in life expectancy and expected years with activity limitations at age 50 in the European Union: associations with macro-level structural indicators.

Women generally live longer than men, but women's longer lives are not necessarily healthy lives. The aim of this article is to describe the pattern of gender differences in expected years with and without activity limitations across 25 EU countries and to explore the association between gender differences and macro-level factors. We applied to the Eurostat life table's data from the Statistics of Income and Living Conditions Survey to estimate gender differences in life expectancy with and without activity limitations at age 50 for 2005. We studied the relationship between the gender differences and structural indicators using meta-regression techniques. Differences in years with activity limitations between genders were associated with the life expectancy (LE) and the size of the gender difference in LE. Gender difference in years with activity limitations were larger as the gross domestic product, the expenditure on elderly care and the indicator of life-long learning decreased, and as the inequality in income distribution increased. There was evidence of disparity in the associations between the more established EU countries (EU15) and the newer EU10 countries. Among the EU15, gender differences were positively associated with income inequality, the proportion of the population with a low education and the men's mean exit age from labour force. Among the EU10, inequalities were smaller with increasing expenditure in elderly care, with decreasing poverty risk and with decreasing employment rate of older people. The association between structural indicators and the gender gap in years with activity limitations suggests that gender differences can be reduced.