Abstract
AbstractMorbidity is one of the key aspects for assessing populations’ well-being. In particular, chronic diseases negatively affect the quality of life in the old age and the risk that more years added to lives are years of disability and illness. Novel analysis, interventions and policies are required to understand and potentially mitigate this issue. In this article, we focus on investigating whether in Italy the compression of morbidity is in act in the recent years, parallely to an increase of life expectancy. Our analysis rely on large repeated cross-sectional data from the national surveillance system passi, providing deep insights on the evolution of morbidity together with other socio-demographical variables. In addition, we investigate differences in morbidity across subgroups, focusing on disparities by gender, level of education and economic difficulties, and assessing the evolution of these differences across the period 2013–2019.
Funder
Ministero dell’Istruzione, dell’Università e della Ricerca
Publisher
Springer Science and Business Media LLC
Subject
Statistics, Probability and Uncertainty,Statistics and Probability
Reference25 articles.
1. Baldissera S, Campostrini S, Binkin N, Minardi V, Minelli G, Ferrante G, Salmaso S. et al (2011) Features and initial assessment of the Italian behavioral risk factor surveillance system (passi), 2007–2008. Prev Chronic Dis 8(1)
2. Campostrini S, McQueen DV (2005) Institutionalization of social and behavioral risk factor surveillance as a learning system. Sozial-und Präventivmedizin 50(1):S9–S15
3. Campostrini S, McQueen DV (2014) Inequalities: The “gap’’ remains: can surveillance aid in closing the gap? Int J Public Health 59(2):219–220
4. Campostrini S, McQueen D, Taylor A, Daly A (2015) World alliance for risk factor surveillance white paper on surveillance and health promotion. AIMS Public Health 2(1):10
5. Caselli G, Egidi V, Strozza C (2021) L’Italia longeva: Dinamiche e diseguaglianze della sopravvivenza a cavallo di due secoli. Il mulino
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