Leader: Luisa Frova (Istat)
This task integrates three Istat Registers: Population, Causes of Death, and National Income. Differences in mortality by area, income and education are analyzed for the older population. The project aims to operate a literature review, to identify the set of variables best suited to study inequalities and to build measures of mortality by socio-economic status (SES). This task aims at building a Mortality Indicator System useful for monitoring public health and evaluating social policies. By analyzing mortality changes over time by SES, it becomes possible to monitor the dynamics of observed inequalities and assess whether reduction in health disparities in Italy is or is not under way.
Brief description of the activities and of the intermediate results: The educational attainment information has been acquired from the Base Register of individuals, and data have been entered into the mortality data registry for the year 2020. The validation and the control phase of both indicators has been completed, and indicators by educational level for the year 2020 were calculated. On February 7, 2024, ISTAT released measures on mortality by causes of death and level of education for 2020 (https://www.istat.it/it/archivio/286642). Data on mortality by level of education for Covid-19 and other 25 causes of death categorized by sex and region of residence are now available. As of today, data for both 2019 and 2020 are available in easily searchable databases, detailing deaths, standardized rates, and population figures. Excel files can be downloaded.
In March 2024, activities linking mortality records (Year 2021) with the national population register have commenced. This link is crucial for acquiring information related to educational qualifications. Significant steps have also been taken in the data analysis, particularly in identifying within the Income Registry the components necessary for defining individual income. The database used for the analyses, integrates the Istat Income Statistical Register (providing income information for about 45 million individuals) and the Istat Population Register (PRI).
Negative binomial regression models and Poisson models were applied to estimate mortality rate ratios (MRR). The goal is to quantify the effect of income on the death risks, especially of the older population, accounting for other control variables such as age class, geographic area, number of household members, marital status, and educational attainment.
Further refinements will be carried out in a subsequent phase, in particular those aimed at taking data overdispersion into account.
Main policy, industrial and scientific implications Having a system of mortality indicators based on education levels and developing new measures of income-related mortality inequalities are crucial tools for supporting programming in socio-health public policies. Policies could focus on improving the accessibility of diagnostic and healthcare services, eliminating financial, geographical, and cultural barriers, all of which are considered major factors contributing to the higher mortality rates among socioeconomically disadvantaged elderly individuals today in Italy.
Furthermore, understanding the relationship between mortality and income could offer valuable insights for pension and elderly care policies. These policies should aim to ensure a decent standard of living for all elderly individuals, regardless of their socioeconomic status.
Finally, having an annually updated regional indicator system could serve as a significant tool for evaluating policy efficacy. By analyzing changes over time in these measures, it becomes possible to monitor the dynamics of observed inequalities and assess whether any reduction in health inequalities can be detected in Italy.
Brief description of the activities and of the intermediate results
In collaboration with Sapienza University (Rome), additional research was conducted to identify methods to investigate regional inequalities in mortality by cause of death and to assess whether they increased in 2020 compared to the previous year.
Using data from the ISTAT Mortality Indicator System (Latest release Feb/2024, https://www.istat.it/it/archivio/286642), years 2019 and 2020, we applied quantile regression models to analyse educational inequalities in cause-specific mortality by Italian regions.
The results were presented at the following national or international meetings:
We also analysed the results of the linkage between the Register on Deaths and Causes of Death and the National Register of Individuals. In September, we started the procedures for calculating indicators by educational level for 2021.
A paper (“Inequalities in mortality by individual income and the role of disability benefits: a register-based analysis on the elderly population in Italy,”) illustrating the relationships between individual income and general mortality (among the older population) was submitted to, and accepted for, the IARIW (International Association for Research in Income and Wealth) Conference on “Population Ageing: Implications for Economic Measurement and Economic Performance” (24-25 March 2025, Tokyo, Japan). The long abstract was uploaded in the repository.
Main policy/industry/practical implications
In 2020, an increase in mortality among the elderly was observed, not only due to COVID-19 mortality. During the pandemic, the overload of the health system made it difficult to provide adequate care not only for Covid-19 but also for other conditions. This increase was accompanied by a widening of social inequalities in mortality, with a greater increase among the less educated. Social inequalities in mortality vary by geographic area, suggesting the need for region-specific approaches.
Policy recommendations to reduce inequalities and reduce mortality for the elderly
The activities required for the third release of cross-sectional indicators for monitoring social inequalities in mortality in Italy have been successfully continued and completed.
Individual mortality data by cause of death were integrated with the National Register of the Italian Population (RBI) to calculate mortality rates by educational level. Indicators for the year 2021 were validated, and the corresponding tables have been uploaded to the ISTAT institutional website. The data titled “Inequalities in Cause-Specific Mortality in Italy by Demographic, Social, and Territorial Characteristics - Year 2021” were officially released on December 17, 2024, and are available at Disuguaglianze nella mortalità – Anno 2021 – Istat.
The dataset includes standardized mortality rates, absolute frequencies of death, and population data by cause of death for the three-year period 2019–2021. This comprehensive time frame allows users to conduct temporal evaluations. The databases are user-friendly and can be queried by year, region, age group, cause of death, and gender. (Tables uploaded Repository WP1_Task1.2)
From October 20 to 22, 2024, the “17th European Public Health Conference,” organized by EUPHA, took place in Lisbon. The conference aimed to exchange perspectives on the theme “Sailing the Waves of European Public Health: Exploring a Sea of Innovation.” It focused on sustainability, collaboration, and citizen empowerment to ensure that public health actions are inclusive and impactful, bridging science, policy, and communities for a healthier Europe.
During the conference, results on mortality and income were presented in a poster: “Inequalities in Mortality by Individual Income: A Register-Based Analysis on the Elderly Population in Italy,” by Lucia Coppola, Luisa Frova, Enrico Grande, Marilena Pappagallo, and Isabella Siciliani. (Abstract and poster uploaded Repository WP1_Task1.2)
Similar findings were also shared at the Workshop Age-it, titled “The Demography of Ageing,” held in Rome on October 3–4, 2024. The presentation, “Income Register-Based Analysis of Mortality Inequalities in the Elderly in Italy”. (Slides uploaded Repository WP1_Task1.2)
The key results highlighted income as a significant predictor of adult mortality. The choice of income definition is crucial for accurately assessing the relationship between income and mortality. Including disability benefits in the income definition increases economic resources for the most vulnerable groups, potentially biasing the observed income-mortality relationship.
Income is a significant predictor of adult mortality, reflecting living conditions, capabilities, and access to healthcare services. Addressing income-related disparities is critical to improving health outcomes for the elderly.
The following recommendations could help address these issues:
• Promote Health Equity: Consider developing and implementing health and social policies that aim to reduce inequalities and improve access to healthcare for elderly and disadvantaged populations, fostering more equitable health outcomes.
• Address Income Disparities: Lower income levels appear to be associated with higher mortality rates, with disparities particularly evident among men. Encouraging inclusive policies that support health equity, provide financial assistance, and protect vulnerable groups may contribute to reducing these disparities.
coming soon