Targeting pediatric pedestrian injury prevention efforts: teasing the information through spatial analysis.

BACKGROUND

Pediatric pedestrian injuries remain a major cause of childhood death, hospitalization, and disability. To target injury prevention efforts, it is imperative to identify those children at risk. Racial disparities have been noted in the rates of pediatric pedestrian injury and death. Children from low-income families living in dense, urban residential neighborhoods have a higher risk of sustaining pedestrian injury. Geographic information systems (GIS) analysis of associated community factors such as child population density and median income may offer insights into prevention.

METHODS

Using trauma registry E-codes for pedestrian motor vehicle crashes, children younger than 16 years were identified, who received acute care and were hospitalized at the University of Chicago Medical Center, a Level I pediatric trauma center, after being struck by a motor vehicle from 2002 to 2009. By retrospective chart review and review of the Emergency Medical Services run sheets, demographic data and details of the crash site were collected. Crash sites were aggregated on a block by block basis. A "hot spot" analysis was performed to localize clusters of injury events. Using Gi* statistical method, spatial clusters were identified at different confidence intervals using a fixed distance band of 400 m (≈ ¼ mile). Maps were generated using GIS with 2000 census data to evaluate race, employment, income, density of public and private schools, and density of children living in the neighborhoods surrounding our medical center where crash sites were identified. Spatial correlation is used to identify statistically significant locations.

RESULTS

There were 3,521 children admitted to the University of Chicago Medical Center for traumatic injuries from 2002 to 2009; 27.7% (974) of these children sustained injuries in pedestrian motor vehicle injuries. From 2002 to 2009, there were a total of 106 traumatic deaths, of which 29 (27.4%) were due to pedestrian motor vehicle crashes. Pediatric pedestrian motor vehicle crash sites occurred predominantly within low-income, predominantly African-American neighborhoods. A lower prevalence of crash sites was observed in the predominantly higher income, non-African-American neighborhoods.

CONCLUSIONS

Spatial analysis using GIS identified associations between pediatric pedestrian motor vehicle crash sites and the neighborhoods served by our pediatric trauma center. Pediatric pedestrian motor vehicle crash sites occurred predominantly within low-income, African-American neighborhoods. The disparity in prevalence of crash sites is somewhat attributable to the lower density of children living in the predominantly higher income, non-African-American neighborhoods, including the community immediately around our hospital. Traffic volume patterns, as a denominator of these injury events, remain to be studied.