Introduction: Income inequality, a pivotal determinant of general and mental health, operates through intricate mechanisms at various geographical scales. While established at country or region levels, the impact of lower-level (municipal or neighborhood) inequality remains inconsistent. This study explores the influence of regional- and municipal-level income inequality on individual psychological distress during the COVID-19 pandemic in Italy, employing a multilevel data analysis.
Materials And Methods: In a post hoc analysis of data from the first wave of the pandemic (March to April 2020), three hierarchical levels were considered: individual participants, municipalities, and regions. Depressive and anxiety symptoms were measured using the PHQ-9 and GAD-7 scales, while the Gini coefficient gauged income inequality at municipal and regional levels. The analysis incorporated demographic variables as potential confounders.
Results: The study encompassed 21 regions, 3,900 municipalities, and 21,477 subjects. Income inequality at both regional and municipal levels exhibited associations with distress scores, suggesting independent effects. Notably, higher distress scores were identified in southern regions with elevated inequality, despite a more substantial COVID-19 impact in the north.
Discussion: Findings contribute to existing literature by emphasizing the independent impact of lower-level (municipal) and higher-level (regional) income inequality on population psychopathology. The study supports theories suggesting diverse pathways through which inequality at different levels influences health, such as potential associations with healthcare system dysfunction at the regional level and welfare dysfunction at the municipal level. The observed north-south gradient in distress scores highlights the need for psychosocial interventions to alleviate income inequality, especially in historically disadvantaged southern regions. Future research should explore the nuanced interplay between income inequality and various ecological variables to provide a comprehensive understanding of its health impact.
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