Social Vulnerability Index Predicts Violent Crime in Chicago

Abstract

INTRODUCTION: The Social Vulnerability Index (SVI), composed of 4 social factors, is used to predict communities most at risk for negative consequences during natural disasters and public health crises. Violence, especially with a firearm, is one such crisis previously shown to behave like a transmissible disease. We hypothesized that SVI could predict community risk for violence. METHODS: The CDC’s 2018 SVI data were merged by census tract with violent crimes (assault, battery, and homicide) from the Chicago Data Portal (Figure). Cubic regression was used to show correlations between crime rate, overall SVI, and each SVI social factor; univariate and multivariate negative binomial regression was performed to calculate risk ratios.SVI, Social Vulnerability Index.RESULTS: SVI predicted risk of violent crime in Chicago. Negative binomial regression found that each percentile increase in SVI resulted in a 7 times increase in violent crime (RR 7.09, 95% CI 6.06 to 8.29, p < 0.001). The factors most strongly associated with violence were socioeconomic status (RR 3.63, 95% CI 2.76 to 4.78, p < 0.001), household composition/disability (RR 2.59, 95% CI 2.09 to 3.22, p < 0.001) and housing type/transportation (RR 1.41, 95% CI 1.60 to 2.25, p < 0.001). Minority status/language was associated with a decreased risk of violent crime (RR 0.34, 95% CI 0.26 to 0.42, p < 0.001). CONCLUSION: This is the first study to demonstrate SVI may predict community risk for violence. SVI can identify geospatial areas of focus for violence intervention and prevention. Academic researchers and trauma surgeons should use SVI when demonstrating disparities related to violent injury risk and outcomes, because it encompasses the effect of social, economic, and built environments at a granular level that is standardized across the US.