Youth violence prevention can be enhanced by geospatial analysis of trauma registry data

Background: Geographic information systems (GIS) have been used to understand relationships between trauma mechanisms, locations, and social determinants for injury prevention. We hypothesized that GIS analysis of trauma center registry data for assault patients aged 14 years to 29 years with census tract data would identify geospatial and structural determinants of youth violence.

Methods: Admissions to a Level I trauma center from 2010 to 2019 were retrospectively reviewed to identify assaults in those 14 years to 29 years. Prisoners were excluded. Home and injury scene addresses were geocoded. Cluster analysis was performed with the Moran I test for spatial autocorrelation. Census tract comparisons were done using American Communities Survey (ACS) data by t-test and linear regression.

Results: There were 1,608 admissions, 1,517 (92.4%) had complete addresses and were included in the analysis. Mean age was 23 ± 3.8 years, mean ISS was 7.5 ± 6.2, there were 11 (0.7%) in-hospital deaths. Clusters in six areas of the trauma catchment were identified with a Moran I value of 0.24 ( Z score = 17.4, p < 0.001). Linear regression of American Communities Survey demographics showed predictors of assault were unemployment (odds ratio, 4.5; 95% confidence interval, 2.7-6.4; p < 0.001), Spanish spoken at home (odds ratio, 6.6; 95% confidence interval, 3.4-9.8; p < 0.001) and poverty level (odds ratio, 1.9; 95% confidence interval, 1.1-2.7; p < 0.001). Education level of less than high school diploma, single parent households and race were not significant predictors.

Conclusion: GIS analysis of registry data can identify high-risk areas for youth violence and correlated social and structural determinants. Violence prevention efforts can be better targeted geographically and socioeconomically with better understanding of these risk factors.

Level of evidence: Prognostic/Epidemiological; Level III.