Lead Data Mapping to Prioritize US Locations for Whole-of-Government Exposure Prevention Efforts: State of the Science, Federal Collaborations, and Remaining Challenges

Abstract

For this state-of-science overview of geospatial approaches for identifying US communities with high lead-exposure risk, we compiled and summarized public data and national maps of lead indices and models, environmental lead indicators, and children’s blood lead surveillance data. Currently available indices and models are primarily constructed from housing-age and sociodemographic data; differing methods, variables, data, weighting schemes, and geographic scales yield maps with different exposure risk profiles. Environmental lead indicators are available (e.g., air, drinking water, dust, soil) at different spatial scales, but key gaps remain. Blood lead level data have limitations as testing, reporting, and completeness vary across states. Mapping tools and approaches developed by federal agencies and other groups for different purposes present an opportunity for greater collaboration. Maps, data visualization tools, and analyses that synthesize available geospatial efforts can be evaluated and improved with local knowledge and blood lead data to refine identification of high-risk locations for prioritizing prevention efforts and targeting risk-reduction strategies. Remaining challenges are discussed along with a work-in-progress systematic approach for cross-agency data integration, toward advancing “whole-of-government” public health protection from lead exposures. (Am J Public Health. 2022;112(S7):S658–S669. https://doi.org/10.2105/AJPH.2022.307051 )

A U.S. Lead Exposure Hotspots Analysis

“…1. Statistically evaluated hotspots identified with lead indices against children's BLL surveillance data: (a) from Michigan (MI) and Ohio (OH), using the BLL data and statistical methods described in Xue et al 12 and Stanek et al, 13 respectively, and an expanded set of national lead indices; (b) from matching hotspots identified using lead indices with community hotspots identified in 9 state health department public reports (listed in Zartarian et al 5 ) and quantifying the percent; a match is defined here as a community with at least one census tract identified by the lead indices in our analyses; 2. Compared existing national indices against each other and against available BLL surveillance data using sensitivity, specificity, and Cohen's kappa score to determine which indices are the statistically strongest predictors of hotspots for the national-scale analysis; 3.…”

“…The 9 states used for evaluation were: Connecticut (city/town), Maine (city/town), Massachusetts (city/town, census tracts), Michigan (city/ town), New Hampshire (city/town, census tracts), New Jersey (municipality), Ohio (city/town, county), Pennsylvania (municipality), and Rhode Island (city). As Table D in Zartarian et al 5 shows, states used different criteria, geographic scales, time periods, and blood lead reference values for identifying higher risk locations.…”

“…However, source apportionment can vary by location and scenarios, 36,37 and quantification is challenging without an integrated database of multimedia environmental lead and BLL data. 5 Table 1 results, based on Pb indices constructed with old housing and sociodemographic data from the census, may potentially be skewed toward states with higher population densities because of significantly more old housing stock (i.e., in northeastern and north-central U.S. in comparison to the south and other parts of the U.S). Rural counties may appear less than urban areas in this analysis because of smaller populations and potentially lower quantity of census data from those counties used in the indices.…”

“…Examples include targeting HUD remediation grants, EPA environmental cleanup actions, and CDC primary prevention and enhanced blood lead testing programs for children. 5 The EPA, U.S. Department of Housing and Urban Development (HUD), Centers for Disease Control and Prevention (CDC), and other organizations are applying geospatial statistical methods with available data (blood lead surveillance data, lead indices, and environmental data) to identify locations that are disproportionately at risk. However, there are remaining gaps and challenges such as cross-agency data collection and integration.…”

“…However, there are remaining gaps and challenges such as cross-agency data collection and integration. 5 The interagency lead mapping state-of-the-science paper 5 presented a data integration roadmap to identify places for public health action: "For national scale, one could use lead indices and evaluate identified geographic locations by available BLL data and local knowledge...While the science is evolving to compare available lead indices and models against each other and evaluate or ground-truth them against states'-measured surveillance BLL data...an analyst or decision-maker may want to use them collectively to identify high-risk locations to cast a wider net or to use their intersecting locations for a more focused list...". This paper provides a next step in the research to identify U.S. lead exposure hotspots using existing data.…”