Evidence map›Paper›PMID 36992819›Full record

ArticlePNAS nexus2023

Low-cost informational intervention reduced drinking water arsenic exposure in Bangladesh.

Raghav R Reddy, Grace A van Velden, Md Joynul Abedin, Md Rezaul Karim, Kim F Hayes, Arun Agrawal, Lutgarde Raskin

Open access · goldFull text read
In one paragraph

Article in PNAS nexus, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.8field-weighted citation impact, top 31% 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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Review
  2. 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

7 authors at 1 institution in 1 country.

Raghav R ReddyDepartment of Civil and Environmental Engineering, University of Michigan, Ann Arbor, MI 48109,US.
Grace A van VeldenDepartment of Civil and Environmental Engineering, University of Michigan, Ann Arbor, MI 48109,US.
Md Joynul AbedinAsia Arsenic Network, 7400 Jessore, Bangladesh.
Md Rezaul KarimAsia Arsenic Network, 7400 Jessore, Bangladesh.
Kim F HayesDepartment of Civil and Environmental Engineering, University of Michigan, Ann Arbor, MI 48109,US.
Arun AgrawalSchool of Environment and Sustainability, University of Michigan, Ann Arbor, MI 48109,US.ORCID https://orcid.org/0000-0001-6796-2958
Lutgarde RaskinDepartment of Civil and Environmental Engineering, University of Michigan, Ann Arbor, MI 48109,US.ORCID https://orcid.org/0000-0002-9625-4034
University of Michigan · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Thirty million Bangladeshis continue to drink water with unacceptable levels of arsenic (>10 μg/L), resulting in a large public health burden. The vast majority of the Bangladeshi population relies on private wells, and less than 12% use piped water, increasing the complexity of mitigation efforts. While mass testing and informational campaigns were successful in the early 2,000 s, they have received little attention in recent years, even though the number of wells in the country has likely more than doubled. We investigated the effect of a low-cost (<USD 10/household) informational intervention on reducing arsenic exposure through a randomized control trial design. The sample size was ∼10% of the study area households, and the intervention provided exposure awareness material, the arsenic concentration of the household's drinking water, and information about alternate water sources nearby with improved water quality. The informational intervention lowered household arsenic exposure (

Identifiers

PMID36992819
PMCPMC10042277
OpenAlexW4360998325

What OpenQuestion holds

Textfull text, public
LicenceCC BY
measurements read104
identifiers read1
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.