District-Level Food Environment Indicators and Social Vulnerability in São Paulo

• URL: http://arxiv.org/abs/2608.26299v1
• Date: Wed, 26 Aug 2026 18:31:39 GMT
• Title: District-Level Food Environment Indicators and Social Vulnerability in São Paulo
• Abstract summary: Urban food environments may reflect broader socioeconomic inequalities, but district-level evidence remains limited in Brazilian cities.<n>This study examined whether indicators of food retail and street-market availability discriminate between levels of social vulnerability across the 96 districts of So Paulo.
• Score: 33.72751145910978
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Urban food environments may reflect broader socioeconomic inequalities, but district-level evidence remains limited in Brazilian cities. This study examined whether indicators of food retail and street-market availability discriminate between levels of social vulnerability across the 96 districts of São Paulo. We conducted an exploratory cross-sectional ecological analysis integrating the São Paulo Social Vulnerability Index (IPVS), establishment records from the Relação Anual de Informações Sociais (RAIS), and street-market data from CAISAN. Census-sector information was aggregated at the district level. Twenty districts without an IPVS classification were excluded, resulting in 76 observations. The outcome distinguished districts classified as IPVS level 1 from those classified as levels 2--7. Predictors described the densities of healthy and unhealthy food establishments, the number of street markets, and the availability of establishments selling fresh or in natura food. Eight conventional machine-learning classifiers were evaluated using leave-one-out cross-validation. Reported mean F-scores ranged from 0.62 to 0.75, with XGBoost obtaining the highest value. In the Random Forest model, the densities of healthy and unhealthy food establishments jointly accounted for approximately 60% of the total impurity-based feature importance. These findings indicate that publicly available food-environment indicators contain information associated with the district-level distribution of social vulnerability. However, the small ecological sample, class imbalance, outcome binarization, and cross-sectional design limit predictive generalization and preclude causal or household-level interpretations.

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