ArticleEnvironmental epidemiology (Philadelphia, Pa.)2025
Who is living near different types of US Superfund sites: A latent class analysis considering site contaminant profiles.
Article in Environmental epidemiology (Philadelphia, Pa.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Residential proximity to Superfund sites and breast cancer incidence in a nationwide cohort.Environmental epidemiology (Philadelphia, Pa.) · 2026Article
- Original research article: popexposure: An open-source Python package to find the number of people residing near environmental hazards quickly and efficiently.medRxiv : the preprint server for health sciences · 2025Article
- Association of social and environmental exposures at the neighborhood level with child brain volume.Environment international · 2025Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Background: Millions of people in the United States live near Superfund sites and may be exposed to hazardous chemicals from those sites. However, there is limited research on chemicals present at sites and the demographics of nearby communities. We aimed to identify subgroups of Superfund sites with similar contaminant profiles and evaluate whether sociodemographic characteristics vary by type of site. Methods: We used US Environmental Protection Agency Superfund data to identify sites active in the year 2000. Census tract centroids located within 3 miles of every Superfund site were identified and a weighted average of census tract-level sociodemographics using the 2000 US Census was calculated. Superfund sites with similar contaminant profiles were identified using latent class analysis. We compared the median sociodemographic characteristics, overall and by contaminant latent class, with those of the overall 2000 US Census. Results: We identified seven latent classes based on 12 contaminant categories from 1332 Superfund sites active in 2000. Overall, there were few differences in sociodemographics observed by the presence of any Superfund site compared with the overall US Census. After stratifying by contaminant profile, we observed evidence of disparities for two classes of sites, defined by (1) high diversity of chemical exposure and lumber industry and (2) batteries and metals, which were more likely to have higher hazard scores and to be near communities with higher proportions of non-White individuals, lower socioeconomic status, and higher social vulnerability. Conclusion: Disadvantaged communities, with higher social vulnerability, were more likely to be near certain Superfund sites with higher hazard scores.
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