Geographic variation of pediatric burn injuries in a metropolitan area

Acad Emerg Med. 2003 Jul;10(7):743-52. doi: 10.1111/j.1553-2712.2003.tb00069.x.


Objectives: To use a geographic information system (GIS) and spatial statistics to describe the geographic variation of burn injuries in children 0-14 years of age in a major metropolitan area.

Methods: The authors reviewed patient records for burn injuries treated during 1995 at the two children's hospitals in St. Louis. Patient addresses were matched to block groups using a GIS, and block group burn injury rates were calculated. Mapping software and Bayesian analysis were used to create maps of burn injury rates and risks in the city of St. Louis.

Results: Three hundred eleven children from the city of St. Louis were treated for burn injuries in 1995. The authors identified an area of high incidence for burn injuries in North St. Louis. The filtered rate contour was 6 per 1,000 children at risk, with block group rates within the area of 0 to 58.8 per 1,000 children 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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Age Distribution
  • Bayes Theorem
  • Burn Units
  • Burns / diagnosis*
  • Burns / epidemiology*
  • Child
  • Child, Preschool
  • Confidence Intervals
  • Female
  • Humans
  • Incidence
  • Infant
  • Infant, Newborn
  • Injury Severity Score
  • Male
  • Minnesota / epidemiology
  • Retrospective Studies
  • Risk Factors
  • Sex Distribution
  • Socioeconomic Factors
  • Survival Rate
  • Urban Population