Objectives: to document existing geographical inequalities in health in the city of Milan (Lombardy Region, Northern Italy), examining the association between area socioeconomic disadvantage and health outcomes, with the aim to suggest policy action to tackle them. Design: the analysis used an ecological framework; multiple health indicators were considered in the analysis; socioeconomic disadvantage was measured through indicators such as low education, unemployment, immigration status, and housing crowding. For each municipal statistical area, Bayesian Relative Risks of the outcomes (using the Besag-Yorkand-Mollié model) were plotted on the city map. To evaluate the association between social determinants and health outcomes, Spearman correlation coefficients were estimated. Setting and participants: residents in the City of Milan aged between 30 and 75 years who were residing in Milan as of 01.01.2019, grouped in 88 statistical areas. Main outcomes measures: all-cause mortality, type-2 diabetes mellitus, hypertension, neoplasms, respiratory diseases, metabolic syndrome, antidepressants use, polypharmacy, and multimorbidity. Results: the results consistently demonstrated a significant association between socioeconomic disadvantage and various health outcomes, with low education exhibiting the strongest correlations. Neoplasms displayed an inverse social gradient, while the relationship with antidepressant use varied. Conclusions: these findings provide valuable insights into the distribution of health inequalities in Milan and contribute to the existing literature on the social determinants of health. The study highlights the need for targeted interventions to address disparities and promote equitable health outcomes. The results can serve to inform the development of effective public health strategies and policies aimed at reducing health inequalities in the city.
Consolazio, D., Alsayed, A., Serini, M., Benassi, D., Sarti, S., Terraneo, M., et al. (2024). Social inequalities in health within the City of Milan (Lombardy Region, Northern Italy): An ecological assessment. EPIDEMIOLOGIA E PREVENZIONE, 48(4-5), 1-11 [10.19191/EP24.4-5.A741.072].
Social inequalities in health within the City of Milan (Lombardy Region, Northern Italy): An ecological assessment
Consolazio, D;AlSayed, A;Serini, M;Benassi, D;Sarti, S;Terraneo, M;Celata, C;
2024
Abstract
Objectives: to document existing geographical inequalities in health in the city of Milan (Lombardy Region, Northern Italy), examining the association between area socioeconomic disadvantage and health outcomes, with the aim to suggest policy action to tackle them. Design: the analysis used an ecological framework; multiple health indicators were considered in the analysis; socioeconomic disadvantage was measured through indicators such as low education, unemployment, immigration status, and housing crowding. For each municipal statistical area, Bayesian Relative Risks of the outcomes (using the Besag-Yorkand-Mollié model) were plotted on the city map. To evaluate the association between social determinants and health outcomes, Spearman correlation coefficients were estimated. Setting and participants: residents in the City of Milan aged between 30 and 75 years who were residing in Milan as of 01.01.2019, grouped in 88 statistical areas. Main outcomes measures: all-cause mortality, type-2 diabetes mellitus, hypertension, neoplasms, respiratory diseases, metabolic syndrome, antidepressants use, polypharmacy, and multimorbidity. Results: the results consistently demonstrated a significant association between socioeconomic disadvantage and various health outcomes, with low education exhibiting the strongest correlations. Neoplasms displayed an inverse social gradient, while the relationship with antidepressant use varied. Conclusions: these findings provide valuable insights into the distribution of health inequalities in Milan and contribute to the existing literature on the social determinants of health. The study highlights the need for targeted interventions to address disparities and promote equitable health outcomes. The results can serve to inform the development of effective public health strategies and policies aimed at reducing health inequalities in the city.File | Dimensione | Formato | |
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