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Heavy Metal Index

Inequalities in Public Water Arsenic Concentrations in Counties and Community

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Cited by6 pages
Metals measured4
Evidence tierB
Year2006

Overview

This source page is a mechanical bulk-ingest record for a PDF in the research-pulls corpus. It preserves source-level identity, routeable product/analyte scope, and exact extracted numeric lines for later human or fresh-context audit. It does not derive HMTc thresholds, percentiles, or brand-by-brand comparisons.

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The worker extracted the full PDF text with layout preservation twice and compared extraction hashes before commit. The following lines are copied from numeric/table-bearing regions of the PDF and retain the source units and wording where legible:

  • METHODS: We estimated 3-y average arsenic concentrations for 36,406 CWSs (98%) and 2,740 counties (87%) and compared differences in means
  • RESULTS: From 2006–2008 to 2009–2011, mean and 95th percentile CWS arsenic (in micrograms per liter) declined by 10.3% (95% CI: 6.5%, 14.1%)
  • (61.1%), served by groundwater (94.7%), serving smaller populations (mean 1,102 persons), and serving Hispanic communities (38.3%).
  • (Awata et al. 2017a, 2017b; Cubadda et al. 2017; Jones et al. from Wisconsin and West Virginia that likely reported LODs in
  • water arsenic exposure for sociodemographic and geographic ter), we imputed the corrected LOD divided by the square root of 2
  • States, to inform future national- and state-level arsenic MCL the value of 0:35 lg=L (the U.S. EPA LOD of 0:5 lg=L divided
  • arsenic-related disease. remaining 5,437 records for which LODs were reported as
  • following subgroups in our analysis: a) U.S. region (CWS and sion criteria). The final sample size included 36,406 CWSs (98%
  • county level); b) sociodemographic county cluster (CWS and of CWSs in the SYR3) serving a total of 2,740 counties (87% of
  • Collection Request process (voluntarily sent in from states, territo- and varied substantially across CWSs (range: 1–1,506; mean: 4)
  • period (2006–2011), which included approximately 13 million ana- alytical decision, see Tables S1 and S2). Few CWSs reported
  • lion people annually. Data from 46 states, Washington DC, the the same year (N = 1,182). When the 3-y average of arsenic in fin-
  • 1, 4, 5, 8, and 9, representing 95% of all public water systems and (N = 336 CWSs), we calculated the 3-y average with only the fin-
  • 92% of the total population served by public water systems nation- ished water samples.
  • nondetections. CWSs serving that county reported serving at least 50% or more of
  • with the LOD divided by the square root of 2. Although the U.S. mated the public water–reliant population for each county using the
  • reported lower and higher LODs or did not report record-specific tap water source from the 1990 U.S. Census (Ruggles et al. 2019),
  • LODs. When records reported the laboratory LOD as <5 lg=L, which was also recently used by the U.S. Geologic Survey (USGS)
  • we replaced arsenic values below the LOD with the LOD divided (Ayotte et al. 2017). For descriptive purposes, we also calculated
  • by the square root of 2 (N = 30,256 records); for 1,202 records county-level 6-y average water arsenic concentrations as the
  • county-level estimates of water arsenic averages across the conter- root of 2), regardless of the LOD reported in each record.
  • minous United States using the maps package in R version 3.5.3 Second, we excluded records with a reported LOD of ≥5 lg=L.
  • Statistical Analysis: Water Arsenic Exposure Estimates reported serving at least 70% and 80% or more of the public
  • (N = 36,406) and county level (N = 2,740) for the entire United We assigned all CWSs and counties to one of four MCL compli-
  • States. We also compared mean differences between the two time ance categories using the 10 lg=L MCL cut point based on the
  • clusters (N = 8 distinct clusters) were derived by Wallace et al. age arsenic concentrations at the CWS and county level and a re-
  • sociodemographic county-clusters to identify characteristics of pop- Nationwide, the mean CWS arsenic concentrations (95% confi-
  • sure. These sociodemographic county-clusters are as follows: Semi- 1:89 lg=L (95% CI: 1.84, 1.94) and 1:7 lg=L (95% CI: 1.64,
  • Hispanic; Mostly Rural, Mid SES; Rural, Mid/Low SES; Young, sponding percentage decrease = 10:1% (95% CI: 14.1%, 6.5%)
  • Urban, Mid/High SES; Rural, American Indian; and Rural, High (Table 1)). By region, CWS arsenic concentrations for the first
  • (groundwater vs. surface water, as reported in SDWIS) and by the (mean = 3:59 lg=L (95% CI: 3.41, 3.76)), followed by Alaska/
  • We conducted sensitivity analyses for the comparison of Eastern Midwest (mean = 2:03 lg=L (95% CI: 1.92, 2.14)) (Table 1;
  • Table 1. Arithmetic means (95% CIs), mean differences (95% CIs), and corresponding percentage differences (95% CIs) of 3-y average water arsenic concen-
  • trations (lg=L) in community water systems (CWSs) from 2006–2008 and 2009–2011, stratified by CWS subgroup (total N = 36,406 CWSs).
  • graphic county-cluster analyses (N = 36,674).
  • 2006–2008 and 2009–2011 (mean difference = − 0:75 lg=L (95% corresponding percentage decrease = 45:3%), the Eastern Midwest
  • CI: −1:35, −0:15); corresponding percentage decrease = 36:8% (decline of 8:44 lg=L (95% CI: 11.83, 5.05); corresponding
  • (95% CI: 7.4%, 66.1%)), followed by the Southwest (mean percentage decrease = 40:5%), the Southwest (decline of 3:46 lg=L
  • difference = − 0:41 lg=L (95% CI: −0:65, −0:17); corresponding (95% CI: 9.00, 2.08); corresponding percentage decrease = 11:5%),
  • percentage decrease = 11:4% (95% CI: 4.7%, 18.1%)); and Eastern and the Mid-Atlantic (decline of 2:43 lg=L (95% CI: 4.46, 0.40); cor-
  • Midwest (mean difference = − 0:40 lg=L (95% CI: −0:54, responding percentage decrease = 23:1%) (Figure 2; Table S5).
  • −0:25); corresponding percentage decrease = 19:7% (95% CI: At the county level, nationwide weighted average water ar-

Methods (brief)

  • (Awata et al. 2017a, 2017b; Cubadda et al. 2017; Jones et al. from Wisconsin and West Virginia that likely reported LODs in
  • water arsenic exposure for sociodemographic and geographic ter), we imputed the corrected LOD divided by the square root of 2
  • States, to inform future national- and state-level arsenic MCL the value of 0:35 lg=L (the U.S. EPA LOD of 0:5 lg=L divided
  • water arsenic exposure by subgroup contributes to disparities in reported below the LOD without record-specific LOD; and b) the
  • arsenic-related disease. remaining 5,437 records for which LODs were reported as
  • following subgroups in our analysis: a) U.S. region (CWS and sion criteria). The final sample size included 36,406 CWSs (98%
  • lytical records from 139,000 public water systems serving 290 mil- records of both raw and finished (i.e., treated) water samples within
  • Navajo Nation, and American Indian tribes from U.S. EPA Regions ished water samples was lower than in raw concentrations
  • 92% of the total population served by public water systems nation- ished water samples.
  • We replaced arsenic values below the limit of detection (LOD) the public water–reliant population in the entire county. We esti-
  • with the LOD divided by the square root of 2. Although the U.S. mated the public water–reliant population for each county using the
  • EPA established the maximum LOD of 0:5 lg=L, many systems latest nationwide U.S. Census statistic on county-level household
  • reported lower and higher LODs or did not report record-specific tap water source from the 1990 U.S. Census (Ruggles et al. 2019),
  • LODs. When records reported the laboratory LOD as <5 lg=L, which was also recently used by the U.S. Geologic Survey (USGS)
  • we replaced arsenic values below the LOD with the LOD divided (Ayotte et al. 2017). For descriptive purposes, we also calculated
  • average of the two 3-y period estimations. We mapped 3- and 6-y 0:35 lg=L (the standard U.S. EPA LOD divided by the square
  • county-level estimates of water arsenic averages across the conter- root of 2), regardless of the LOD reported in each record.
  • minous United States using the maps package in R version 3.5.3 Second, we excluded records with a reported LOD of ≥5 lg=L.

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Update history

The five most recent substantive edits to this page, classified major (evidence or structure moved), correction (a published value or statement was wrong and has been fixed), or minor (narrative rewritten without changing the underlying evidence). Each description is derived from what the edit did to this page; the linked commit is the authoritative record, routine regeneration passes are excluded, and the full version history lives in git. When DOI minting comes online (see schema docs), each entry below will also link to a version-pinned DataCite DOI.

CommitDateChangeDescription
b01ec52c2026-08-04major2 sections added
d49e450f2026-08-03major5 sections added; narrative text revised