Increased Risk of Sub-Clinical Blood Lead Levels in the 20-County Metro Atlanta, Georgia Area—A Laboratory Surveillance-Based Study

Carmen M. Dickinson-Copeland, Lilly Cheng Immergluck, Maria Britez, Fengxia Yan, Ruijin Geng, Mike Edelson, Salathiel R. Kendrick-Allwood and Katarzyna Kordas
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Carmen M. Dickinson-Copeland: Department of Microbiology, Biochemistry, and Immunology, Morehouse School of Medicine, Atlanta, GA 30310, USA
Lilly Cheng Immergluck: Department of Microbiology, Biochemistry, and Immunology, Morehouse School of Medicine, Atlanta, GA 30310, USA
Maria Britez: Department of Microbiology, Biochemistry, and Immunology, Morehouse School of Medicine, Atlanta, GA 30310, USA
Fengxia Yan: Department of Community Health and Preventive Medicine, Morehouse School of Medicine, Atlanta, GA 30310, USA
Ruijin Geng: Pediatric Clinical and Translational Research Unit, Clinical Research Center, Morehouse School of Medicine, Atlanta, GA 30310, USA
Mike Edelson: Geographic Information Systems, InterDev, Roswell, GA 30076, USA
Salathiel R. Kendrick-Allwood: Department of Pediatrics, Divisions of General Pediatrics & Neonatology, Emory University School of Medicine, Atlanta, GA 30303, USA
Katarzyna Kordas: Department of Epidemiology and Environmental Health, University at Buffalo, Buffalo, NY 14214, USA

IJERPH, 2021, vol. 18, issue 10, 1-15

Abstract: Lead (Pb) is a naturally occurring, highly toxic metal that has adverse effects on children across a range of exposure levels. Limited screening programs leave many children at risk for chronic low-level lead exposure and there is little understanding of what factors may be used to identify children at risk. We characterize the distribution of blood lead levels (BLLs) in children aged 0–72 months and their associations with sociodemographic and area-level variables. Data from the Georgia Department of Public Health’s Healthy Homes for Lead Prevention Program surveillance database was used to describe the distribution of BLLs in children living in the metro Atlanta area from 2010 to 2018. Residential addresses were geocoded, and “Hotspot” analyses were performed to determine if BLLs were spatially clustered. Multilevel regression models were used to identify factors associated with clinical BBLs (?5 µg/dL) and sub-clinical BLLs (2 to <5 µg/dL). From 2010 to 2018, geographically defined hotspots for both clinical and sub-clinical BLLs diffused from the city-central area of Atlanta into suburban areas. Multilevel regression analysis revealed non-Medicaid insurance, the proportion of renters in a given geographical area, and proportion of individuals with a GED/high school diploma as predictors that distinguish children with BLLs 2 to <5 µg/dL from those with lower (<2 µg/dL) or higher (?5 µg/dL) BLLs. Over half of the study children had BLLs between 2 and 5 µg/dL, a range that does not currently trigger public health measures but that could result in adverse developmental outcomes if ignored.

Keywords: lead poisoning; childhood exposure; multilevel regression analysis; GIS (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2021
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