Spatial associations between personal hygiene practices and disease burden among slum communities in Midnapore Municipality, India

Personal hygiene practices are fundamental determinants of health outcomes among socioeconomically marginalized urban populations. However, neighbourhood-level assessments of hygiene inequalities and their relationship with disease burden in urban slum communities remain limited. This study investigates the spatial associations between personal hygiene practices and disease burden across 156 slum neighbourhoods of Midnapore Municipality, India, using data from a cross-sectional survey of 800 households. Fifteen hygiene-related variables were analysed using Principal Component Analysis (PCA) following reliability and sampling adequacy assessments. A composite Personal Hygiene Index (PHI) was constructed from seven retained components explaining 69.707% of the cumulative variance. Spatial patterns of hygiene conditions were examined using Cluster-Outlier Analysis (Anselin Local Moran’s I) and Hotspot Analysis (Getis-Ord Gi*) in ArcGIS, while a Disease Burden Index (DBI) was developed to assess community-level disease burden. The findings reveal substantial neighbourhood-level spatial inequalities in hygiene conditions. Local Moran’s I analysis identified statistically significant high and low clusters and spatial outliers, whereas Getis–Ord Gi* analysis identified 27 slum neighbourhoods (17.31%) as significant hotspots exhibiting favourable hygiene conditions and 29 slum neighbourhoods (18.59%) as significant coldspots characterized by poor hygiene conditions. Pearson’s correlation analysis demonstrated a statistically significant inverse relationship between the Personal Hygiene Index and Disease Burden Index ( r = − 0.3126, p < 0.01), indicating that better hygiene conditions are associated with lower disease burden. The findings underscore the importance of geographically targeted public health interventions and provide valuable evidence for neighbourhood-level urban health planning and equitable resource allocation in vulnerable slum communities.