Conference Agenda

The COVID-19 pandemic led to an increase in mortality rates in Italy, together with a widening of social inequalities in mortality, usually measured by educational attainment. Also income is a significant predictor of adult mortality, because related to housing conditions, standard of living, access to healthcare and services. In this paper, we investigate if the relationship between individual economic resources and mortality changed during the pandemic. Specifically, we compare the disparities in mortality between the poorer and the wealthier individuals, during the 2019-2021, focusing on the elderly population, particularly hit by COVID-19. The analyses are based on an innovative database, achieved by integrating the Istat Population Register with the Income Statistical Register and other administrative data. Negative Binomial regression models are applied to the 65+ resident population by sex, to analyse mortality inequalities by income level, controlling for other socio-economic characteristics. Preliminary results show that the increase in mortality observed in 2020 is not significantly associated with the individual economic resources, for both sexes. Poorer individuals show an excess mortality compared to wealthier individuals, but differentials do not change significantly in 2020. Neither the protective effect of education changes noticeably in the elderly population during the pandemic.

The COVID-19 pandemic significantly impacted demographic dynamics, with mortality being the most directly affected. Variations in COVID-related excess mortality across regions have been linked to inequality, urbanization, healthcare quality, demographic composition, and political factors. To explore the causal impact of political selection, we apply a regression discontinuity design to close mayoral elections in Italy, estimating excess mortality during the pandemic's waves. Our findings reveal that mayoral characteristics, particularly education, had a significant causal effect on reducing excess mortality. This research underscores the critical role of local political selection in shaping public health outcomes during crises.

The study considers the impact of the COVID-19 pandemic on SRB. Given the pandemic's disruption of healthcare services, reduced access to abortion could lead to a decrease in SRB among populations with traditionally skewed ratios. Additionally, the Trivers-Willard hypothesis suggests that maternal stress caused by the pandemic may influence SRB. Comparing the 2018-2023 data with earlier periods helps assess changes in SRB patterns. This study builds on previous research by analyzing sex ratio at birth (SRB) among migrant populations in Italy, focusing on Albanian, Indian, Chinese, Tunisian, Sri Lankan, and Pakistani communities, where son preference is prominent. Italian newborns serve as a control group. The study also examines induced abortion rates by parity and maternal citizenship to assess abortion patterns in migrant groups with elevated SRBs. Using data from Italy's Longitudinal Register on Reproductive Histories (1999-2023), the analysis explores SRB trends by birth order, sex of previous children, and inter-birth interval. Overall, the study aims to determine if the pandemic has contributed to lower SRBs in both Italian and migrant populations, providing insights into reproductive behaviors and healthcare access during this challenging period.

The phenomena of mortality decline and morbidity expansion observed over the last decades have contributed to an increasing share of older individuals living with co-morbidities. This challenges the relationship between morbidity and mortality and may exacerbate inequalities across sub-population groups. Aim: To 1) describe income inequalities in diseases prevalence; 2) describe the relationship between prevalence at death and underlying causes of death for men and women and income groups; and 3) assess income inequalities in the prevalence at death and underlying causes of death for men and women. We use health and mortality data for adults living in Catalonia using primary care health records and underlying causes of death for the HEALIN 2005 cohort. Income groups are defined using co-pharmacy payment. A set preliminary list of 40 chronic conditions is used. We construct tables of correspondence, estimate prevalence, prevalence at death and proportions of underlying cause for each cause, sex and income group. Logistic and Cox regressions will be used to assess inequalities. Our results are expected to provide novel insights on sex and income inequalities in disease prevalence and on the relationship between prevalence at death and underlying causes, which may be relevant for policy making.