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Aims: Socio-economic inequalities originate from several channels, one of which is family origins, with clear effects on people's health. This paper aims to evaluate the role played by social mobility in determining health inequalities, relying on Blau and Duncan's status attainment model and focusing specifically on two moments of social reproduction of inequalities: one inter-generational, based on the transmission of resources from the family of origin, the other intra-generational, related to the capitalisation of economic resources to maximise well-being. Methods: Multi-group models of structural equations were used to examine the direct and indirect effects of parental cultural background, education and economic conditions of respondents on self-perceived health in 28 countries, relying on the European Social Survey (N =38,879). Results: Overall, the results confirmed the presence of an inter-generational transmission of social and health status. Different models of transmission of health inequalities emerged among the countries considered. Countries characterised by a social democratic welfare regime showed higher social mobility and fewer health inequalities, although in correspondence with a prominent role of economic factors in determining health conditions. On the other hand, in countries where social mobility is lower, health inequalities are more pronounced, yet driven by factors others than economics, such as socio-cultural origins. Conclusions: The presence of a higher economic-health gradient in social democratic countries – notwithstanding their egalitarian and universal welfare policies – provides support for the existence of a Nordic paradox in relation to health inequalities. [ABSTRACT FROM AUTHOR]

Social inequalities in health are known to be influenced by the socioeconomic status of the territory in which people live. In the context of the ongoing coronavirus disease 2019 (COVID-19) pandemic, this study is aimed at assessing the role of 5 area-level indicators in shaping the risk of contagion in the provinces of Milan and Lodi (Lombardy, Italy), namely: educational disadvantage, unemployment, housing crowding, mobility, and population density. The study area includes the municipalities at the origin of the first Italian epidemic outbreak. Data on COVID-19 patients from the Integrated Datawarehouse for COVID Analysis in Milan were used and matched with aggregate-level data from the National Institute of Statistics Italy (Istat). Multilevel logistic regression models were used to estimate the association between the census block-level predictors and COVID-19 infection, independently of age, sex, country of birth, and preexisting health conditions. All the variables were significantly associated with the outcome, with different effects before and after the lockdown and according to the province of residence. This suggests a pattern of socioeconomic inequalities in the outbreak, which should be taken into account in the eventuality of future epidemics to contain their spread and its related disparities. [ABSTRACT FROM AUTHOR]