Term of Award

Spring 2013

Degree Name

Doctor of Public Health in Community Health Behavior and Education (Dr.P.H.)

Document Type and Release Option

Dissertation (open access)

Copyright Statement / License for Reuse

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.


Jiann-Ping Hsu College of Public Health

Committee Chair

Simone Charles

Committee Member 1

John Luque

Committee Member 2

Robert Vogel

Committee Member 3

Robert Vogel


Lead poisoning is a significant public health problem with paint from old housing exposing thousands of children and leading to negative health and social outcomes. Identifying the highest risk children exposed to lead is important to public health agencies. The purpose of this study was to evaluate and assess the efficacy of a new geographically-based lead risk model that when combined with a child's physical address, predicts the extent of a child's risk of lead poisoning on a numeric risk scale. This model is unique because it calculates risk at the address level from parcel attributes of age and type of housing (rental or owner-occupied) combined and adjusted with historic blood lead surveillance data to create a final predictive risk map. If found efficacious, the model would assist lead poisoning prevention programs in being more cost effective by creating a verified approach for targeting prevention efforts. To assess the models efficacy, a pilot study was conducted using three years (N=2429) of blood lead records from Macon-Bibb County, which has the second highest prevalence rate of lead exposure in Georgia. Physical addresses obtained from the blood lead records were geocoded and assigned a risk by the model. The predictive risk was compared to blood lead results and statistically analyzed to determine if risk increased with increased blood lead results. Results demonstrated the risk model accurately estimated risk when compared to blood lead levels with statistical significance. This model can be used to target the highest risk homes and children for public health interventions and to identify low risk Medicaid children for exemption from lead testing.

Research Data and Supplementary Material


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