Evidence map›Paper›PMID 38872757›Full record

ArticleChronic diseases and translational medicine2024

A Bayesian network for estimating hypertension risk due to occupational aluminum exposure.

Le Zhao, Jinzhu Yin, Jiaping Huan, Xiao Han, Dan Zhao, Jing Song, Linping Wang, Huifang Zhang, Baolong Pan, Qiao Niu and 1 more

Abstract read
In one paragraph

Article in Chronic diseases and translational medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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

3 citing papers in PubMed.

  1. Article
  2. Hypertension and human health: Evidence and prospects.Chronic diseases and translational medicine · 2024
    Article
  3. 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

11 authors.

Le ZhaoDepartment of Occupational Health, School of Public Health, Shanxi Key Laboratory of Environmental Health Impairment and Prevention, MOE Key Laboratory of Coal Environmental Pathogenicity and Prevention Shanxi Medical University Taiyuan Shanxi China.ORCID 0009-0007-9756-904X
Jinzhu YinSinopharm Tongmei General Hospital Shanxi Health Commission Key Laboratory of Nervous System Disease Prevention and Treatment Datong Shanxi China.
Jiaping HuanDepartment of Occupational Health, School of Public Health, Shanxi Key Laboratory of Environmental Health Impairment and Prevention, MOE Key Laboratory of Coal Environmental Pathogenicity and Prevention Shanxi Medical University Taiyuan Shanxi China.
Xiao HanDepartment of Occupational Health, School of Public Health, Shanxi Key Laboratory of Environmental Health Impairment and Prevention, MOE Key Laboratory of Coal Environmental Pathogenicity and Prevention Shanxi Medical University Taiyuan Shanxi China.
Dan ZhaoDepartment of Occupational Health, School of Public Health, Shanxi Key Laboratory of Environmental Health Impairment and Prevention, MOE Key Laboratory of Coal Environmental Pathogenicity and Prevention Shanxi Medical University Taiyuan Shanxi China.
Jing SongDepartment of Occupational Health, School of Public Health, Shanxi Key Laboratory of Environmental Health Impairment and Prevention, MOE Key Laboratory of Coal Environmental Pathogenicity and Prevention Shanxi Medical University Taiyuan Shanxi China.
Linping WangDepartment of Occupational Health, School of Public Health, Shanxi Key Laboratory of Environmental Health Impairment and Prevention, MOE Key Laboratory of Coal Environmental Pathogenicity and Prevention Shanxi Medical University Taiyuan Shanxi China.
Huifang ZhangDepartment of Occupational Health, School of Public Health, Shanxi Key Laboratory of Environmental Health Impairment and Prevention, MOE Key Laboratory of Coal Environmental Pathogenicity and Prevention Shanxi Medical University Taiyuan Shanxi China.
Baolong PanDepartment of Occupational Health, School of Public Health, Shanxi Key Laboratory of Environmental Health Impairment and Prevention, MOE Key Laboratory of Coal Environmental Pathogenicity and Prevention Shanxi Medical University Taiyuan Shanxi China.
Qiao NiuDepartment of Occupational Health, School of Public Health, Shanxi Key Laboratory of Environmental Health Impairment and Prevention, MOE Key Laboratory of Coal Environmental Pathogenicity and Prevention Shanxi Medical University Taiyuan Shanxi China.
Xiaoting LuDepartment of Occupational Health, School of Public Health, Shanxi Key Laboratory of Environmental Health Impairment and Prevention, MOE Key Laboratory of Coal Environmental Pathogenicity and Prevention Shanxi Medical University Taiyuan Shanxi China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The correlation between metals and hypertension, such as sodium, zinc, potassium, and magnesium, has been confirmed, while the relationship between aluminum and hypertension is not very clear. This study aimed to evaluate the correlation between plasma aluminum and hypertension in electrolytic aluminum workers by the Bayesian networks (BN). Methods: In 2019, 476 male workers in an aluminum factory were investigated. The plasma aluminum concentration of workers was measured by inductively coupled plasma mass spectrometry. The influencing factors on the prevalence of hypertension were analyzed by the BN. Results: The prevalence of hypertension was 23.9% in 476 male workers. The risk of hypertension from plasma aluminum in the Q2, Q3, and Q4 groups was 5.20 (1.90-14.25), 6.92 (2.51-19.08), and 7.33 (2.69-20.01), respectively, compared with that in the Q1 group. The risk of hypertension from the duration of exposure to aluminum of >10 years was 2.23 (1.09-4.57), compared without aluminum exposure. Area under the curve was 0.80 of plasma aluminum and the duration of exposure to aluminum was based on covariates, indicating that aluminum exposure had important predictive value in the prevalence of hypertension in the occupational population. The results of the study using the BN model showed that if the plasma aluminum of all participants was higher than Q4 (≥47.86 µg/L) and the participants were drinking, smoking, diabetes, central obesity, dyslipidemia, and aged >50 years, the proportion of hypertension was 71.2%. Conclusions: The prevalence of hypertension increased significantly with the increase of plasma aluminum level.

Indexed as

Bayesian networkshypertensionoccupational aluminum exposure

Identifiers

PMID38872757
PMCPMC11166680

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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.