Visualizing neighbourhood health disparities: spatial epidemiology to map social vulnerability and mortality in an Italian city

Urbanization is rapidly increasing, with projections indicating that more than two-thirds of the global population will live in urban areas by 2050. Despite this trend, neighborhood-level health indicators remain underutilized in monitoring population health and detecting disparities. This study proposes and validates a methodological framework to assess spatial health disparities and socio-demographic vulnerability using disaggregated neighbourhood data. The framework was applied to Pisa, Italy, analysing 40 homogeneous elementary territorial units. A composite vulnerability index was created through principal component analysis, aggregating socioeconomic and demographic indicators. Mortality data for 2021 were georeferenced and standardized by age and sex for each unit. Spatial autoregressive models assessed associations between mortality rates and both individual indicators and the composite index. Standardized Mortality Ratios highlighted units with significantly higher mortality. Results showed spatial heterogeneity in vulnerability and mortality across the city. Both the composite vulnerability index and population density significantly predicted mortality, with density being the strongest predictor. Critical areas with high vulnerability and excess mortality were identified. The framework provides a replicable, interdisciplinary approach for visualizing and mapping urban health inequities and supports evidence-based public health interventions at fine geographic scales, with applications for urban planning, public health, and social policy in urban contexts.