Neighborhood characteristics of registered sex offender residential locations: Evidence from the state of ohio

Objective: The identification of neighborhoods where registered sex offenders (RSOs) reside may facilitate evidence-based service delivery and increase neighborhood capacity building. This study aims to determine if there is a patterned spatial aggregation of RSOs and to identify the neighborhood characteristics of RSO locations. Method: We used ArcGIS to match residential information from 938 Ohio ZIP Code areas with census data and conducted spatial autocorrelation analyses to explore and map spatial clustering of RSO residential locations. We used ordinary least squares and spatial regression models to estimate the association between neighborhood characteristics and the rate of RSOs. Results: The percentages of non-Hispanic Black population, Hispanic population, and poverty were positively associated with the rate of RSO residences; percentages of female-headed households, having a bachelor’s degree, and owner-occupied households were negatively associated with the rate of RSO residences. Overall, RSOs were spatially aggregated in socially disorganized areas. Conclusions: The findings can be used to promote evidence-informed policies to manage decarcerated RSOs, distribute limited resources to assist former offenders’ rehabilitation, and empower communities in disadvantaged neighborhoods to advance smart decarceration.