Background/Objectives: In Italy, the ongoing reform of primary healthcare (Ministerial Decree 77/2022) requires Health Districts to shift towards proactive, need-based resource allocation. Despite evidence of their role in shaping citizens’ health, socioeconomic deprivation indices remain rarely integrated into territorial planning frameworks. This study develops and validates a population-weighted analytical model linking area-level socioeconomic deprivation, territorial accessibility, and all-cause mortality across the entire Italian territory, with the aim of supporting evidence-based planning. Methods: All 7899 Italian municipalities were aggregated into 1175 territorial units defined by Health District boundaries and SNAI (National Strategy for Inner Areas) classification. A population-weighted multivariable OLS regression model was used to examine the association between socioeconomic indicators (educational deprivation, employment, household isolation) and the Standardized Mortality Ratio (SMR) for 2023–2024. Results: The model explained 72.5% of the variance in SMR across territorial units (adjusted R2 = 0.719; F = 116.5; p < 0.0001). Region of residence emerged as the dominant predictor. Educational deprivation showed the strongest positive association with mortality. While employment-related deprivation was inversely associated with SMR, household isolation showed a positive independent association with mortality. Residual mapping identified spatial clusters of excess mortality unexplained by socioeconomic factors, pointing to unmeasured determinants including environmental exposures and healthcare quality differentials Conclusions: Our model provides a replicable, evidence-based framework for identifying territorial vulnerability and prioritising healthcare resources at the Health District level. By benchmarking observed mortality against socioeconomic predictions, it enables planners to distinguish structurally driven excess mortality from potentially amenable mortality, supporting proactive, equity-oriented planning consistent with the objectives of Ministerial Decree 77/2022.
Bridging the Gap Between Social Determinants and Health Profile: A New Stratification Tool for the Italian National Health Service
Elvira Massaro;Irene Schenone;Daniela Amicizia;Francesca Marchini;Matteo Astengo;Federico Grammatico;Andrea Fiorano;Alexander Domnich;Donatella Panatto;Giancarlo Icardi;Filippo Ansaldi
2026-01-01
Abstract
Background/Objectives: In Italy, the ongoing reform of primary healthcare (Ministerial Decree 77/2022) requires Health Districts to shift towards proactive, need-based resource allocation. Despite evidence of their role in shaping citizens’ health, socioeconomic deprivation indices remain rarely integrated into territorial planning frameworks. This study develops and validates a population-weighted analytical model linking area-level socioeconomic deprivation, territorial accessibility, and all-cause mortality across the entire Italian territory, with the aim of supporting evidence-based planning. Methods: All 7899 Italian municipalities were aggregated into 1175 territorial units defined by Health District boundaries and SNAI (National Strategy for Inner Areas) classification. A population-weighted multivariable OLS regression model was used to examine the association between socioeconomic indicators (educational deprivation, employment, household isolation) and the Standardized Mortality Ratio (SMR) for 2023–2024. Results: The model explained 72.5% of the variance in SMR across territorial units (adjusted R2 = 0.719; F = 116.5; p < 0.0001). Region of residence emerged as the dominant predictor. Educational deprivation showed the strongest positive association with mortality. While employment-related deprivation was inversely associated with SMR, household isolation showed a positive independent association with mortality. Residual mapping identified spatial clusters of excess mortality unexplained by socioeconomic factors, pointing to unmeasured determinants including environmental exposures and healthcare quality differentials Conclusions: Our model provides a replicable, evidence-based framework for identifying territorial vulnerability and prioritising healthcare resources at the Health District level. By benchmarking observed mortality against socioeconomic predictions, it enables planners to distinguish structurally driven excess mortality from potentially amenable mortality, supporting proactive, equity-oriented planning consistent with the objectives of Ministerial Decree 77/2022.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.



