| A Framework for Widespread Replication of a Highly Spatially Resolved Childhood Lead Exposure Risk Model Dohyeong Kim, M. Alicia Overstreet Galeano, Andrew Hull, and Marie Lynn Miranda Nicholas School of the Environment, Duke University, Durham, North Carolina, USA Abstract
Background: Preventive approaches to childhood lead poisoning are critical for addressing this longstanding environmental health concern. Moreover, increasing evidence of cognitive effects of blood lead levels < 10 µg/dL highlights the need for improved exposure prevention interventions. Objectives: Geographic information system–based childhood lead exposure risk models, especially if executed at highly resolved spatial scales, can help identify children most at risk of lead exposure, as well as prioritize and direct housing and health-protective intervention programs. However, developing highly resolved spatial data requires labor- and time-intensive geocoding and analytical processes. In this study we evaluated the benefit of increased effort spent geocoding in terms of improved performance of lead exposure risk models. Methods: We constructed three childhood lead exposure risk models based on established methods but using different levels of geocoded data from blood lead surveillance, county tax assessors, and the 2000 U.S. Census for 18 counties in North Carolina. We used the results to predict lead exposure risk levels mapped at the individual tax parcel unit. Results: The models performed well enough to identify high-risk areas for targeted intervention, even with a relatively low level of effort on geocoding. Conclusions: This study demonstrates the feasibility of widespread replication of highly spatially resolved childhood lead exposure risk models. The models guide resource-constrained local health and housing departments and community-based organizations on how best to expend their efforts in preventing and mitigating lead exposure risk in their communities. Key words: children's health, environmental justice, exposure risk prevention, geocoding, GIS (geographic information systems) , lead. Environ Health Perspect 116:1735–1739 (2008) . doi:10.1289/ehp.11540 available via http://dx.doi.org/ [Online 14 August 2008]
Address correspondence to M.L. Miranda, Nicholas School of the Environment, Duke University, Box 90328, Levine Science Research Center Room A134, Durham, NC 27708-0328 USA. Telephone: (919) 613-8023. Fax (919) 684-3227. E-mail: mmiranda@duke.edu We thank E. Norman and T. Ward, North Carolina Children's Environmental Health Branch, for providing access to the lead surveillance data used in this work. This research was made possible by funding from the U.S. Centers for Disease Control and Prevention and the National Institute of Environmental Health Sciences (5P42-ES-010356-08) . The authors declare they have no competing financial interests. Received 4 April 2008 ; accepted 14 August 2008.
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