Evidence map›Paper›PMID 35832257›Full record

ArticleExposome2022

Identification of occupations susceptible to high exposure and risk associated with multiple toxicants in an observational study: National Health and Nutrition Examination Survey 1999-2014.

Vy Kim Nguyen, Justin Colacino, Chirag J Patel, Maureen Sartor, Olivier Jolliet

Open access · hybridAbstract read
In one paragraph

Article in Exposome, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
1.5field-weighted citation impact, top 17% 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

14 citing papers in PubMed, 16 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Observational
  5. Article
  6. Review
  7. Review
  8. Article
  9. Global research trends on the human exposome: a bibliometric analysis (2005-2024).Environmental science and pollution research international · 2025
    Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. 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

5 authors at 2 institutions in 2 countries.

Vy Kim NguyenDepartment of Environmental Health Sciences, School of Public Health, University of Michigan, Ann Arbor, MI, USA.
Justin ColacinoDepartment of Environmental Health Sciences, School of Public Health, University of Michigan, Ann Arbor, MI, USA.
Chirag J PatelDepartment of Biomedical Informatics, Medical School, Harvard University, Boston, MA, USA.ORCID https://orcid.org/0000-0002-8756-8525
Maureen SartorDepartment of Computational Medicine and Bioinformatics, Medical School, University of Michigan, Ann Arbor, MI, USA.
Olivier JollietDepartment of Environmental Health Sciences, School of Public Health, University of Michigan, Ann Arbor, MI, USA.
University of Michigan · USHarvard University · US

Funding

XenograftP30CA046592 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Alexey I Nesvizhskii · 1988 to 2026
$178.2M
Strategic Vision & Impact on Environmental HealthP30ES017885 · NIEHS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Dana Dolinoy · 2011 to 2026
$21.3M
MI-CARES: The Michigan Cancer and Research on the Environment StudyUH3CA267907 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Dana Dolinoy, Bhramar Mukherjee · 2024 to 2026
$6.0M
Diversity SupplementR01ES028802 · NIEHS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Justin Adam Colacino · 2018 to 2026
$4.8M
Risk of Alzheimer's Disease and Related Dementias from Perinatal Lead Exposure: Brain Region and Cell Type EffectsR01AG072396 · NIA · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Kelly Bakulski, Justin Adam Colacino · 2022 to 2026
$3.7M
MI-CARES: The Michigan Cancer and Research on the Environment StudyUG3CA267907 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI DOLINOY, DANA, MUKHERJEE, BHRAMAR · 2021 to 2022
$2.2M
NCI NIH HHS P30 CA046592NCI NIH HHS UG3 CA267907NCI NIH HHS UH3 CA267907NIEHS NIH HHS P30 ES017885NIEHS NIH HHS R01 ES028802
6 · The paper itself

Abstract

Occupational exposures to toxicants are estimated to cause over 370 000 premature deaths annually. The risks due to multiple workplace chemical exposures and those occupations most susceptible to the resulting health effects remain poorly characterized. The aim of this study is to identify occupations with elevated toxicant biomarker concentrations and increased health risk associated with toxicant exposures in a diverse working US population. For this observational study of 51 008 participants, we used data from the 1999-2014 National Health and Nutrition Examination Survey. We characterized differences in chemical exposures by occupational group for 131 chemicals by applying a series of generalized linear models with the outcome as biomarker concentrations and the main predictor as the occupational groups, adjusting for age, sex, race/ethnicity, poverty income ratio, study period, and biomarker of tobacco use. For each occupational group, we calculated percentages of participants with chemical biomarker levels exceeding acceptable health-based guidelines. Blue-collar workers from "Construction," "Professional, Scientific, Technical Services," "Real Estate, Rental, Leasing," "Manufacturing," and "Wholesale Trade" have higher biomarker levels of toxicants such as several heavy metals, acrylamide, glycideamide, and several volatile organic compounds (VOCs) compared with their white-collar counterparts. Moreover, blue-collar workers from these industries have toxicant concentrations exceeding acceptable levels: arsenic (16%-58%), lead (1%-3%), cadmium (1%-11%), glycideamide (3%-6%), and VOCs (1%-33%). Blue-collar workers have higher toxicant levels relative to their white-collar counterparts, often exceeding acceptable levels associated with noncancer effects. Our findings identify multiple occupations to prioritize for targeted interventions and health policies to monitor and reduce toxicant exposures.

Indexed as

biomonitoring equivalentsenvironmental chemicalsoccupational epidemiologyoccupational exposuresrisk assessmentunsupervised learning

Identifiers

PMID35832257
PMCPMC9266352
OpenAlexW4283524955

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.