Geographic variation of pediatric XXXX in a metropolitan area.

@entity1 @entity130
OBJECTIVES: To use a geographic information system (GIS) and spatial statistics to describe the geographic variation of @entity130 in @entity1 0-14 years of age in a major metropolitan area. METHODS: The authors reviewed @entity1 records for @entity130 treated during 1995 at the two @entity1 's hospitals in St. Louis. @entity1 addresses were matched to block groups using a GIS, and block group @entity130 rates were calculated. Mapping software and Bayesian analysis were used to create maps of @entity130 rates and risks in the city of St. Louis. RESULTS: Three hundred eleven @entity1 from the city of St. Louis were treated for @entity130 in 1995. The authors identified an area of high incidence for @entity130 in North St. Louis. The filtered rate contour was 6 per 1,000 @entity1 at risk, with block group rates within the area of 0 to 58.8 per 1,000 @entity1 at risk. Hierarchical Bayesian analysis of North St. Louis burn data revealed a relative risk range of 0.8771 to 1.182 for census tracts within North St. Louis, suggesting that there may be pockets of high risk within an already identified high-risk area. CONCLUSIONS: This study shows the utility of geographic mapping in providing information about injury patterns within a defined area. The combination of mapping injury rates and spatial statistical analysis provides a detailed level of injury surveillance, allowing for identification of small geographic areas with elevated rates of specific injuries.
