Linking provider catchment patterns and SaTScan risk clusters to support evidence-based public health nursing in urban Japan - Ryo Horiike (The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2026)
Abstract. Municipal public health nurses require geographic evidence to identify concentrated health risks and understand where residents access preventive services. This study describes a reproducible workflow combining provider catchment analysis and spatial scan statistics using Japan’s Specific Health Checkups data from a single local government area in Japan. The protocol was approved by the institutional ethics review board (approval number 2024-053). Service use patterns were summarized across seven elementary school districts. Elevated glycated hemoglobin, defined as HbA1c ≥ 5.6%, was assessed at the chome level, using neighborhood scale address units. QGIS was used for spatial processing, R for statistical analysis, and SaTScan for Poisson spatial scan statistics. Residential district and provider location category were strongly associated (p < 0.01). Within district use ranged from 6.8% to 72.5%, out of area use from 11.2% to 37.3%, and group screening from 3.8% to 7.1%. The most likely high risk cluster included 9,577 adults, with 400 observed and 315.80 expected cases (observed/expected = 1.27; RR = 1.37; p < 0.01). Two secondary high risk clusters were detected but were not statistically significant. Linking catchment patterns with chome level risk clusters supports interpretation of local prevention needs and service use. The use of census based population denominators rather than chome specific participant counts may influence cluster detection. This reproducible workflow provides a transparent and adaptable basis for local public health planning.