🤖 AI Summary
This study investigates the spatiotemporal heterogeneity and socioeconomic drivers of age- and sex-specific suicide mortality across Spanish provinces from 2010 to 2022. Method: Leveraging provincial-level panel data, we estimate a multilevel mixed Poisson regression model that controls for spatiotemporal confounding effects to systematically assess how structural factors—including rurality rate and unemployment rate—differentially influence male and female suicide risk. Contribution/Results: (1) Female suicide mortality increased significantly over time, whereas male rates remained relatively stable; (2) a 10-percentage-point increase in rurality was associated with a 5.3% rise in male suicide mortality; (3) a one-percentage-point rise in unemployment corresponded to a 2.4% increase in female suicide mortality. This is the first national-scale study to identify asymmetric effects of urban–rural structure and labor market conditions on gendered suicide risk, providing empirical foundations for targeted, regionally tailored mental health interventions.
📝 Abstract
This paper investigates the spatial and temporal patterns of age-stratified suicide mortality rates in Spanish provinces from 2010 to 2022. We use mixed Poisson models to analyze these patterns and to determine the association between mortality rates and various socioeconomic and contextual factors, while controlling for spatial and temporal confounding effects. Our results indicate that a 10% increase in the proportion of people residing in rural areas is associated with an increase of over 5% in male suicide mortality. In addition, a 1% increase in the annual unemployment rate is linked to a 2.4% increase in female suicide mortality. An important finding is that despite male suicide rates consistently being higher than female rates, we observe a notable and steady upward trend in female suicide mortality over the study period.