Evidence map›Paper›PMID 36795051›Full record

ArticleEnvironmental science & technology2023

Predictions of Arsenic in Domestic Well Water Sourced from Alluvial Aquifers of the Western Great Basin, USA.

Daniel M Saftner, Steven N Bacon, Monica M Arienzo, Erika Robtoy, Karen Schlauch, Iva Neveux, Joseph J Grzymski, Michele Carbone

Open access · greenAbstract read
In one paragraph

Article in Environmental science & technology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
2.5field-weighted citation impact, top 12% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 18 citations in OpenAlex.

  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

8 authors at 2 institutions in 1 country.

Daniel M SaftnerDivision of Hydrologic Sciences, Desert Research Institute, 2215 Raggio Parkway, Reno, Nevada 89512, United States.ORCID 0000-0002-7073-2747
Steven N BaconDivision of Hydrologic Sciences, Desert Research Institute, 2215 Raggio Parkway, Reno, Nevada 89512, United States.
Monica M ArienzoDivision of Hydrologic Sciences, Desert Research Institute, 2215 Raggio Parkway, Reno, Nevada 89512, United States.ORCID 0000-0003-3444-9810
Erika RobtoyDivision of Hydrologic Sciences, Desert Research Institute, 2215 Raggio Parkway, Reno, Nevada 89512, United States.
Karen SchlauchCenter for Genomic Medicine, Desert Research Institute, 2215 Raggio Parkway, Reno, Nevada 89512, United States.
Iva NeveuxCenter for Genomic Medicine, Desert Research Institute, 2215 Raggio Parkway, Reno, Nevada 89512, United States.
Joseph J GrzymskiCenter for Genomic Medicine, Desert Research Institute, 2215 Raggio Parkway, Reno, Nevada 89512, United States.
Michele CarboneUniversity of Hawai'i Cancer Center, 701 Ilalo Street, Honolulu, Hawaii 96813, United States.
Desert Research Institute · USUniversity of Hawaiʻi at Mānoa · US

Funding

Influence of germline mutations on susceptibility to environmental carcinogensR01ES030948 · NIEHS · UNIVERSITY OF HAWAII AT MANOA · PI CARBONE, MICHELE, GRZYMSKI, JOSEPH J · 2019 to 2021
$1.9M
NIEHS NIH HHS R01 ES030948
6 · The paper itself

Abstract

Chronic exposure to high levels of arsenic in drinking water can have wide-ranging health effects and is a global health concern. The domestic well population of the western Great Basin (WGB) is at increased risk of exposure to arsenic due to the hydrologic, geologic, and climatic setting of the region. A logistic regression (LR) model was developed to predict the probability of elevated arsenic (≥5 μg/L) in alluvial aquifers and assess the potential geologic hazard level posed to domestic well populations. Alluvial aquifers are susceptible to arsenic contamination, which is a concern because they are the primary source of water for domestic well users of the WGB. The probability of elevated arsenic at a domestic well is strongly influenced by tectonic and geothermal variables, including the total Quaternary fault length in the hydrographic basin and the distance between the sampled well and a geothermal system. The model had an overall accuracy of 81%, sensitivity of 92%, and specificity of 55%. Results show a >50% probability of elevated arsenic in untreated well water for approximately 49 thousand (64%) alluvial-aquifer domestic well users in northern Nevada, northeastern California, and western Utah.

Indexed as

ArsenicDrinking WaterGroundwaterWater Pollutants, ChemicalEnvironmental MonitoringArsenicDrinking WaterWater Pollutants, Chemicaldrinking water qualityenvironmental modelinggroundwater

Identifiers

PMID36795051
PMCPMC11587882
OpenAlexW4321004227

What OpenQuestion holds

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Read underepoch 390

Registered trials

None linked

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.