Psychiatry research · 2025
Geographic inequalities in suicide mortality in Italy: Insights from spatial epidemiology.
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Bevione Francesco, Preti Antonio
Аннотация
BACKGROUND: Suicide mortality displays consistent geographic variation, shaped by environmental, social, and structural determinants. Italy's diverse landscape and regional disparities offer a unique opportunity to investigate the spatial distribution of suicide risk.
AIMS: This study examines the geographic patterns of suicide across Italy's 110 provinces and evaluates how altitude and population density contribute to regional disparities in suicide mortality.
METHODS: Using official mortality data from 2006 to 2010, we calculated mean annual suicide rates per 100,000 inhabitants. Spatial autocorrelation was assessed using Moran's I and Local Indicators of Spatial Association (LISA). Spatial regression models-including the Spatial Autoregressive Model with Spatially Correlated Errors (SAR-SEM)-were applied to account for spatial clustering and examine geospatial predictors. A sensitivity analysis included demographic composition (age and gender) at the provincial level.
RESULTS: The national average suicide rate was 5.82 per 100,000 inhabitants, with significant spatial clustering (Moran's I = 0.23, p < 0.0001). High-rate clusters were concentrated in Northern Italy and Sardinia, while low-rate clusters predominated in Southern regions. Altitude and population density were significant predictors, but spatial modeling-especially the SAR-SEM-also identified unmeasured regional factors contributing to suicide patterns. Demographic composition showed weaker and less consistent associations than geographic and spatial factors.
CONCLUSIONS: Geographic disparities in suicide rates in Italy are linked to altitude and population density, with additional spatially structured influences. Sensitivity analyses confirmed that demographic factors play a limited explanatory role. These findings underscore the value of spatial epidemiology in suicide research and support geographically targeted prevention strategies.
AIMS: This study examines the geographic patterns of suicide across Italy's 110 provinces and evaluates how altitude and population density contribute to regional disparities in suicide mortality.
METHODS: Using official mortality data from 2006 to 2010, we calculated mean annual suicide rates per 100,000 inhabitants. Spatial autocorrelation was assessed using Moran's I and Local Indicators of Spatial Association (LISA). Spatial regression models-including the Spatial Autoregressive Model with Spatially Correlated Errors (SAR-SEM)-were applied to account for spatial clustering and examine geospatial predictors. A sensitivity analysis included demographic composition (age and gender) at the provincial level.
RESULTS: The national average suicide rate was 5.82 per 100,000 inhabitants, with significant spatial clustering (Moran's I = 0.23, p < 0.0001). High-rate clusters were concentrated in Northern Italy and Sardinia, while low-rate clusters predominated in Southern regions. Altitude and population density were significant predictors, but spatial modeling-especially the SAR-SEM-also identified unmeasured regional factors contributing to suicide patterns. Demographic composition showed weaker and less consistent associations than geographic and spatial factors.
CONCLUSIONS: Geographic disparities in suicide rates in Italy are linked to altitude and population density, with additional spatially structured influences. Sensitivity analyses confirmed that demographic factors play a limited explanatory role. These findings underscore the value of spatial epidemiology in suicide research and support geographically targeted prevention strategies.