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.
","abstract_html":"<p>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.</p>","abstract_has_math":false,"creators":["Rustin, Christopher R."],"institution":null,"degree_name":"Doctor of Public Health in Community Health Behavior and Education (Dr.P.H.)","degree_level":"Dissertation (open access)","degree_discipline":"Jiann-Ping Hsu College of Public Health","degree_department":null,"school":null,"contributors":["John Luque","Robert Vogel"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2013,"date_issued":"2013-04-01T07:00:00Z","date_published":"2013-04-01T07:00:00Z","updated_at":"2026-07-24T02:26:17Z","subjects":["ETD","Lead poisoning","negative health and social outcomes","geographically-based lead risk","Public Health"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://digitalcommons.georgiasouthern.edu/etd/48","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["John Luque","Robert Vogel"]},{"key":"dc:creator","label":"Author","values":["Rustin, Christopher R."]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2013-07-22T07:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Jiann-Ping Hsu College of Public Health"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation (open access)"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Doctor of Public Health in Community Health Behavior and Education (Dr.P.H.)"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["ETD","Lead poisoning","negative health and social outcomes","geographically-based lead risk","Public Health"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://digitalcommons.georgiasouthern.edu/etd/48"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["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.
"]},{"key":"dc:title","label":"Title","values":["Evaluating the Efficacy of a Childhood Lead Poisoning Risk Model as an Accurate Predictor of Lead Exposure"]}]}],"canonical_facts":{"dc:contributor":["John Luque","Robert Vogel"],"dc:creator":["Rustin, Christopher R."],"dc:date.available":["2013-07-22T07:00:00Z"],"dc:description.abstract":["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.
"],"dc:identifier":["https://digitalcommons.georgiasouthern.edu/etd/48"],"dc:subject":["ETD","Lead poisoning","negative health and social outcomes","geographically-based lead risk","Public Health"],"dc:title":["Evaluating the Efficacy of a Childhood Lead Poisoning Risk Model as an Accurate Predictor of Lead Exposure"],"thesis:degree_discipline":["Jiann-Ping Hsu College of Public Health"],"thesis:degree_level":["Dissertation (open access)"],"thesis:degree_name":["Doctor of Public Health in Community Health Behavior and Education (Dr.P.H.)"]},"updated_at":"2026-07-24T02:26:17Z"}