Evidence map›Paper›PMID 40162038›Full record

ArticleEnvironmental justice (Print)2025

Disparities in demographic and health indicators among communities by frequency of hazardous waste sites in Indiana, USA: differences by Superfund vs. brownfield classification.

Sharon Kulali, Hannah Gallion, Christelene Jack Horton, Keturah Kiper, Jennifer L Freeman, Ellen M Wells

Abstract read
In one paragraph

Article in Environmental justice (Print), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

What it found

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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.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Sharon KulaliDepartment of Public Health, Purdue University, West Lafayette, IN 47906, USA.
Hannah GallionDepartment of Public Health, Purdue University, West Lafayette, IN 47906, USA.
Christelene Jack HortonSchool of Health Sciences, Purdue University, West Lafayette, IN 47906, USA.
Keturah KiperSchool of Health Sciences, Purdue University, West Lafayette, IN 47906, USA.
Jennifer L FreemanSchool of Health Sciences, Purdue University, West Lafayette, IN 47906, USA.
Ellen M WellsDepartment of Public Health, Purdue University, West Lafayette, IN 47906, USA.

Funding

Community-academic partnership to address environmental contamination and healthR01ES032463 · NIEHS · PURDUE UNIVERSITY · PI Ellen M Wells · 2022 to 2026
$2.2M
NIEHS NIH HHS R01 ES032463NIOSH CDC HHS T03 OH008615
6 · The paper itself

Abstract

Background: The location of hazardous sites is a known environmental justice issue, but impact of site classification (Superfund vs. brownfield) is less clear. The objective of this study is to determine whether demographic and health indicators are correlated with the prevalence of brownfield and/or Superfund sites in Indiana, USA. Methods: This is a cross-sectional, ecologic study using publicly available data on hazardous waste sites, demographics, and self-reported health status. Complete data were available for 1252 census tracts, with 2251 brownfield and 2264 Superfund sites. Adjusted Poisson and linear regression models were used to determine associations between hazardous site frequency with demographic and health characteristics. Results: Approximately 24% of census tracts had >3 Superfund or brownfield sites. Higher brownfield frequency was significantly associated with a higher nonwhite population (adjusted β=0.004, 95% confidence interval (CI): 0.002, 0.006); in contrast, more Superfund sites were significantly associated with a lower nonwhite population (adjβ=-0.006, 95% CI:-0.008, 0.004). Lower income was significantly associated with higher Superfund or brownfield site frequency. Results were consistent when limited to urban areas. Self-reported health measures were not associated with Superfund frequency. Census tracts with a higher number of brownfields were associated with a higher proportion of the population reporting poor general health (adjβ=0.057, 95% CI:0.010, 0.104) and poor mental health (adjβ=0.046, 95% CI:0.017, 0.075) compared to tracts without brownfield sites. Conclusions: These results concur with existing evidence on disparities related to the location of hazardous site; they additionally suggest these disparities may extent to how hazardous sites are classified.

Indexed as

Environmental justiceHazardous waste siteIncomeRacial groups

Identifiers

PMID40162038
PMCPMC11949464

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.