Reducing Lead Exposure Risk to Vulnerable Populations: A Proactive Geographic Solution

Abstract

Recent headlines highlight disparities in childhood lead poisoning in urban areas yet discourse does not address the lack of primary prevention options. Previous geographic information systems (GIS) approaches, concentrated on census tracts or ZIP codes, miss contextual understanding of lead exposure and make intervention impractical. Through the combination of electronic medical record (EMR) data from an urban children's hospital and spatial video geonarrative (SVG), we show how blood lead level researchers, clinicians, and public health planners can become more proactive in prediction and intervention strategies through the development of an environmental lead index (ELI). Kernel density estimation (KDE) clusters of geocoded locations of children with elevated blood lead (EBL), from 2012 to 2014, were identified using GIS. Analyses identify an increased relative risk for African American and Asian patients compared to white patients and Nepali and non-English-speaking patients compared to English-speaking patients. Fine-scale analyses of EBL clusters reveal nuances of exposure and environmental characteristics that are not identifiable at an aggregate level. Initial testing of the ELI was conducted using identified locations of EBL and non-EBL test results. The mean ELI score was higher among EBL parcels, and comparison proportions of ELI variables between EBL and non-EBL parcels found a statistically significant increase in four variables. Preliminary results support the use of the ELI as a predictive tool; further validation is needed. The technology and the method are translatable to other environments and health conditions.