Evidence map›Paper›PMID 36083997›Full record

ArticlePloS one2022

Arsenic exposure and respiratory outcomes during childhood in the INMA study.

Antonio J Signes-Pastor, Susana Díaz-Coto, Pablo Martinez-Camblor, Manus Carey, Raquel Soler-Blasco, Miguel García-Villarino, Ana Fernández-Somoano, Jordi Julvez, Paula Carrasco, Aitana Lertxundi and 5 more

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
0.8field-weighted citation impact, top 32% 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

5 citing papers in PubMed, 1 synthesis or guideline pooled it, 7 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. 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

15 authors at 9 institutions in 3 countries.

Antonio J Signes-PastorUnidad de Epidemiología de la Nutrición, Universidad Miguel Hernández, Alicante, Spain.ORCID 0000-0003-4898-2480
Susana Díaz-CotoDepartment of Epidemiology, Geisel School of Medicine, Dartmouth College, Lebanon, NH, United States of America.
Pablo Martinez-CamblorBiomedical Data Science Department, Geisel School of Medicine, Dartmouth College, Lebanon, NH, United States of America.
Manus CareyInstitute for Global Food Security, School of Biological Sciences Building, Queen's University Belfast, Belfast, Northern Ireland, United Kingdom.ORCID 0000-0002-1065-4943
Raquel Soler-BlascoEpidemiology and Environmental Health Joint Research Unit, FISABIO-Universitat Jaume I-Universitat de València, Valencia, Spain.
Miguel García-VillarinoCIBER de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III (ISCIII), Madrid, Spain.
Ana Fernández-SomoanoCIBER de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III (ISCIII), Madrid, Spain.ORCID 0000-0002-8135-9079
Jordi JulvezCIBER de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III (ISCIII), Madrid, Spain.
Paula CarrascoEpidemiology and Environmental Health Joint Research Unit, FISABIO-Universitat Jaume I-Universitat de València, Valencia, Spain.
Aitana LertxundiCIBER de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III (ISCIII), Madrid, Spain.
Loreto Santa MarinaCIBER de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III (ISCIII), Madrid, Spain.
Maribel CasasISGlobal- Instituto de Salud Global de Barcelona-Campus MAR, Parc de Recerca Biomèdica de Barcelona (PRBB), Barcelona, Spain.
Andrew A MehargInstitute for Global Food Security, School of Biological Sciences Building, Queen's University Belfast, Belfast, Northern Ireland, United Kingdom.
Margaret R KaragasBiomedical Data Science Department, Geisel School of Medicine, Dartmouth College, Lebanon, NH, United States of America.
Jesús Vioque-LopezUnidad de Epidemiología de la Nutrición, Universidad Miguel Hernández, Alicante, Spain.
Dartmouth College · USQueen's University Belfast · GBUniversidad de Oviedo · ESUniversitat de Miguel Hernández d'Elx · ESUniversitat Jaume I · ESBasque Government · ESInstituto de Salud Carlos III · ESUniversitat Pompeu Fabra · ESUniversity of the Basque Country · ES

Funding

Project 3: Placental Biomarkers of Exposure and Outcome (Marsit)P01ES022832 · NIEHS · DARTMOUTH COLLEGE · PI KARAGAS, MARGARET RITA · 2013 to 2018
$4.7M
Training Program for Quantitative Population Sciences in CancerR25CA134286 · NCI · DARTMOUTH COLLEGE · PI KARAGAS, MARGARET RITA, TOSTESON, TOR D · 2009 to 2018
$3.0M
NCI NIH HHS R25 CA134286NIEHS NIH HHS P01 ES022832
6 · The paper itself

Abstract

Ingested inorganic arsenic (iAs) is a human carcinogen that is also linked to other adverse health effects, such as respiratory outcomes. Yet, among populations consuming low-arsenic drinking water, the impact of iAs exposure on childhood respiratory health is still uncertain. For a Spanish child study cohort (INfancia y Medio Ambiente-INMA), low-arsenic drinking water is usually available and ingestion of iAs from food is considered the major source of exposure. Here, we explored the association between iAs exposure and children's respiratory outcomes assessed at 4 and 7 years of age (n = 400). The summation of 4-year-old children's urinary iAs, monomethylarsonic acid (MMA), and dimethylarsinic acid (DMA) was used as a biomarker of iAs exposure (∑As) (median of 4.92 μg/L). Children's occurrence of asthma, eczema, sneeze, wheeze, and medication for asthma and wheeze at each assessment time point (i.e., 4- and 7-year) was assessed with maternal interviewer-led questionnaires. Crude and adjusted Poisson regression models using Generalized Estimating Equation (GEE) were performed to account for the association between natural logarithm transformed (ln) urinary ∑As in μg/L at 4 years and repeated assessments of respiratory symptoms at 4 and 7 years of age. The covariates included in the models were child sex, maternal smoking status, maternal level of education, sub-cohort, and children's consumption of vegetables, fruits, and fish/seafood. The GEE-splines function using Poisson regression showed an increased trend of the overall expected counts of respiratory symptoms with high urinary ∑As. The adjusted expected counts (95% confidence intervals) at ln-transformed urinary ∑As 1.57 (average concentration) and 4.00 (99th percentile concentration) were 0.63 (0.36, 1.10) and 1.33 (0.61, 2.89), respectively. These exploratory findings suggest that even relatively low-iAs exposure levels, relevant to the Spanish and other populations, may relate to an increased number of respiratory symptoms during childhood.

Indexed as

ArsenicArsenicalsAsthmaDrinking WaterAnimalsBiomarkersCacodylic AcidChild, PreschoolEnvironmental ExposureHumansArsenicArsenicalsBiomarkersCacodylic AcidDrinking Water

Identifiers

PMID36083997
PMCPMC9462567
OpenAlexW4295027567

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.