Back to Annual Meeting

Back to Annual Meeting

APHA Scientific Session and Event Listing

Dohyeong Kim, M. Alicia Overstreet, and Marie Lynn Miranda. Children's Environmental Health Initiative, Duke University, Box 90328, Durham, NC 27708-0328, 919-613-8137, dohyeong@duke.edu

A growing literature provides evidence that GIS is a powerful tool to integrate data from many sources in constructing childhood lead exposure risk models. Such models, especially if executed at highly resolved spatial scales, can help prioritize and direct housing and health preventive intervention programs. In general, the more resolved the spatial scale, the more public health and housing officials can target their activities. However, more highly resolved spatial scales also require more labor and time-intensive geocoding and analytical processes. Geocoding refers to the process where blood screening records are linked to geographic locations at which other socioeconomic and housing data are available. In this study, we evaluate to what extent increasing effort spent geocoding improves performance of childhood lead exposure risk models. We build models mapped at the individual tax parcel unit in eighteen counties in North Carolina. In so doing, we show the tradeoff curve between model performance and geocoding effort. This study provides key analysis to resource-constrained organizations and agencies like local health departments, local housing and community development departments, and community-based organizations on how best to expend their efforts in understanding the extent and distribution of lead exposure risk in their communities.

Learning Objectives: At the conclusion of the session, the participant in this session will be able to

• Articulate how child lead exposure risk models were constructed and mapped at the individual tax parcel unit in eighteen counties in North Carolina.
• Recognize how the model results change by intensity of geocoding process.
• Identify when the screening data from simple batch geocoding process would be acceptable for use in building models ensuring quality performance.

Keywords: Geographic Information Systems, Child Health

Presenting author's disclosure statement:

Any relevant financial relationships? No