Leader: Stefano Campostrini (UNIVE); Other collaborator(s): Lorenzo Schiavon (UNIVE)
Reports from the Italian National Statistical Institute (ISTAT) and other studies showed relevant social, demographical and geographical differences in life expectancy, morbidity and in healthy life expectancy in Italy. These inequalities can be partially explained in terms of socio-economic factors (gender, educational level, income) and behaviours (risk factors). Data also show that although great interest has been posed on health inequalities in the last years, inequalities are not reducing. Several could be the reasons for which the equity objectives clearly stated also in the most recent National (and Regional) Prevention Plan have not been reached. More in-depth analyses can be useful for better understanding the reasons for the present failure and for better addressing future policies and strategies.
Brief description of the activities and of the intermediate results
A new comorbidity indicator has been studied (first results already published) linking PASSI data and other sources (Global Burden of Disease weights). Further analyses are ongoin linking this indicator to other determinants.
Main policy, industrial and scientific implications
Our studies seem to confirm major differences among population sub-groups in several health outcome (morbidity and mortality related) suggesting tailored intervention more than those targeted to the general population.
Brief description of the activities and of the intermediate results
An analysis of comorbidity in Italy was conducted by regressing the novel comorbidity indicator, based on GBD weights, against socio-demographic determinants while accounting for regional heterogeneity. The findings were presented at the 'Age-It General Meeting' in Venice and the National Statistical Conference (SIS 2024). A critical discussion of the ongoing research using PASSI data occurred at the 'Quattro PASSI per Ca' Foscari' workshop, with contributions from the PASSI Technical Coordination Group.
Additionally, topic Modeling on documentation collected from regions have been conducted (in collaboration with UNIVE / Spoke 10 sociologists - WP 3). Focus: Piano Regionale della Prevenzione and ‘active ageing’.
Main policy, industrial and scientific implications
Our research reveals significant regional disparities in health outcomes, suggesting that interventions should be tailored to address regional or local needs, rather than applied uniformly to the general population.
Brief description of the activities and of the intermediate results
Topic Modeling on documentation collected from regions have been conducted (in collaboration with UNIVE / Spoke 10 sociologists - WP 3). Focus: Piano Regionale della Prevenzione and ‘active ageing’.
A new study has been initiated using PASSI data to examine how socio-economic factors and occupations influence the propensity for risk behaviors such as smoking, inadequate nutrition, risky alcohol consumption, and physical inactivity, which can have a significant impact on life expectancy, morbidity, and healthy life expectancy in aging.
Main policy, industrial and scientific implications
The initial results suggest that certain occupational groups are more prone to engaging in risky behaviors, highlighting the need for targeted policy interventions, workplace health programs, and further scientific research to address these disparities and improve health outcomes in aging populations.
Brief description of the activities and of the intermediate results
Our interdisciplinary team, composed of statisticians and sociologists (UNIVE / Spoke 10 - WP 3), is analyzing the results of topic modeling applied to regional Piani di Prevenzione, with a specific focus on active aging. This analysis aims to identify key themes and regional differences in prevention strategies recognizing multiple approaches in Italian regions.
Additionally, we are continuing our analysis, besed on data from the PASSI survey, on how socio-economic factors and occupations influence the likelihood of engaging in risk behaviors such as smoking, poor nutrition, excessive alcohol consumption, and physical inactivity. These behaviors significantly impact life expectancy, morbidity, and healthy life expectancy in aging populations. Initial findings from this research have been presented in a poster at the event "Lorenzo Bernardi e la statistica sociale, tra formazione, società e istituzioni" at the University of Padova, and with an oral presentation at the 18th International Joint Conference CFE-CMStatistics in London.
Main policy, industrial and scientific implications
Our topic modeling analysis indicates that different Italian regions emphasize distinct aspects of active aging and prevention policies. We identified two primary clusters of regions based on their focus on these topics.
Preliminary findings from the occupational analysis suggest that certain professional groups are more susceptible to engaging in risky behaviors. These insights highlight the need for targeted policy measures, workplace health programs, and further scientific research to address these disparities and promote healthier aging outcomes.
Lorenzo Schiavon (in press). Addressing topic modelling via reduced latent space clustering, Statistical Methods & Applications