The relationship between social vulnerability and pedestrian injuries in Georgia
Abstract
This study used the Center for Disease Control’s Social Vulnerability Index (SVI) to measure vulnerability of neighborhoods, and to study that relationship with the incidence of motor vehicle crashes involving non-motorists, at the census tract level. The goals of this study were to describe the spatial relationship between SVI and pedestrian serious and fatal injuries across Georgia regions; compare the differences in the pedestrian serious and fatal injury crash rates by SVI quintiles across Georgia regions; and describe the association between the SVI and pedestrian serious injury and fatal crashes across Georgia regions. A combination of spatial analysis, comparison of crash rates among quintiles, and regression analysis was used to describe this relationship.
Results indicate that high SVI and non-motorist crashes are spatially clustered, that there is a positive relationship between rates of crashes and SVI quintiles, and that SVI and rate of crashes are correlated over all the Georgia regions.
Keywords
Pedestrian, Injuries, motor vehicle, spacial analysis, SVI
The relationship between social vulnerability and pedestrian injuries in Georgia
This study used the Center for Disease Control’s Social Vulnerability Index (SVI) to measure vulnerability of neighborhoods, and to study that relationship with the incidence of motor vehicle crashes involving non-motorists, at the census tract level. The goals of this study were to describe the spatial relationship between SVI and pedestrian serious and fatal injuries across Georgia regions; compare the differences in the pedestrian serious and fatal injury crash rates by SVI quintiles across Georgia regions; and describe the association between the SVI and pedestrian serious injury and fatal crashes across Georgia regions. A combination of spatial analysis, comparison of crash rates among quintiles, and regression analysis was used to describe this relationship.
Results indicate that high SVI and non-motorist crashes are spatially clustered, that there is a positive relationship between rates of crashes and SVI quintiles, and that SVI and rate of crashes are correlated over all the Georgia regions.
