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    Despite great progress in reducing environmental lead (Pb) levels, many children in the United States are still being exposed. Our aim was to develop a generalizable approach for systematically identifying, verifying, and analyzing locations with high prevalence of children's elevated blood Pb levels (EBLLs) and to assess available Pb models/indices as surrogates, using a Michigan case study. We obtained ∼1.9 million BLL test results of children <6 years of age in Michigan from 2006-2016; we then evaluated them for data representativeness by comparing two percentage EBLL (%EBLL) rates (number of children tested with EBLL divided by both number of children tested and total population). We analyzed %EBLLs across census tracts over three time periods and between two EBLL reference values (≥5 vs. ≥10μg/dL) to evaluate consistency. Locations with high %EBLLs were identified by a top 20 percentile method and a Getis-Ord Gi* geospatial cluster "hotspot" analysis. For the locations identified, we analyzed convergences with three available Pb exposure models/indices based on old housing and sociodemographics. Analyses of 2014-2016 %EBLL data identified 11 Michigan locations via cluster analysis and 80 additional locations via the top 20 percentile method and their associated census tracts. Data representativeness and consistency were supported by a 0.93 correlation coefficient between the two EBLL rates over 11 y, and a Kappa score of ∼0.8 of %EBLL hotspots across the time periods (2014-2016) and reference values. Many EBLL hotspot locations converge with current Pb exposure models/indices; others diverge, suggesting additional Pb sources for targeted interventions. This analysis confirmed known Pb hotspot locations and revealed new ones at a finer geographic resolution than previously available, using advanced geospatial statistical methods and mapping/visualization. It also assessed the utility of surrogates in the absence of blood Pb data. This approach could be applied to other states to inform Pb mitigation and prevention efforts.


    Jianping Xue, Valerie Zartarian, Rogelio Tornero-Velez, Lindsay W Stanek, Antonios Poulakos, Alan Walts, Kathy Triantafillou, Maryann Suero, Nicholas Grokhowsky. A Generalizable Evaluated Approach, Applying Advanced Geospatial Statistical Methods, to Identify High Lead Exposure Locations at Census Tract Scale: Michigan Case Study. Environmental health perspectives. 2022 Jul;130(7):77004

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    PMID: 35894594

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