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Housing age and sociodemographic characteristics as predictors of residential lead exposure and modeled child blood lead levels
Alde, A., Del Rio, M., Hoponick Redmon, J., Wood, E., Harrington, J. M., Obeng-Gyasi, E., Leung, T., & Gibson, J. M. (2026). Housing age and sociodemographic characteristics as predictors of residential lead exposure and modeled child blood lead levels. Science of the Total Environment, 1018. Advance online publication. https://doi.org/10.1016/j.scitotenv.2026.181515
Lead (Pb) exposure remains a persistent public health risk despite decades of regulations. This cross-sectional study evaluated household- and community-level predictors of measured and modeled Pb exposure across 264 homes in Indiana (IN) and North Carolina (NC). Participants self-collected water, soil, and dust samples and completed surveys. Child blood lead levels (BLLs) were estimated using the U.S. Environmental Protection Agency's Integrated Exposure Uptake Biokinetic (IEUBK) model. Regression models linked predictors to Pb in each medium and IEUBK-estimated BLLs. IN households consistently had higher Pb across media and higher IEUBK-estimated BLLs (mean 2.78 μg/dL) than NC households (mean 1.56 μg/dL). Notably, homes previously remediated for Pb in IN had 3× higher soil Pb and 2× higher modeled blood Pb than non-remediated homes, underscoring persistent exposure risks despite remediation efforts. Housing age remained a significant predictor across states, with newer homes associated with reductions in Pb concentrations. In IN, a higher percentage of Black residents was associated with higher water Pb, while in NC, poverty level and water source were stronger predictors. Private well use was linked to 4.4× higher water Pb concentrations compared with municipal systems. Population intervention modeling suggested that children's BLLs would be substantially higher today if housing construction and Pb use mirrored earlier eras, underscoring the public health benefit of Pb bans on paint and restrictions in plumbing. Findings highlight the continued influence of housing age, infrastructure, and sociodemographic context on Pb exposure and the need for locally calibrated, equity-focused predictive models and improved understanding of remediation outcomes.
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