Evidence map›Paper›PMID 38346730›Full record

ArticleEnvironmental health and preventive medicine2024

Non-linear association between long-term air pollution exposure and risk of metabolic dysfunction-associated steatotic liver disease.

Wei-Chun Cheng, Pei-Yi Wong, Chih-Da Wu, Pin-Nan Cheng, Pei-Chen Lee, Chung-Yi Li

Abstract read
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Article in Environmental health and preventive medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
–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

10 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

6 authors.

Wei-Chun ChengDepartment of Public Health, College of Medicine, National Cheng Kung University.
Pei-Yi WongDepartment of Environmental and Occupational Health, National Cheng Kung University.
Chih-Da WuDepartment of Geomatics, National Cheng Kung University.
Pin-Nan ChengDepartment of Internal Medicine, College of Medicine, National Cheng Kung University.
Pei-Chen LeeDepartment of Public Health, College of Medicine, National Cheng Kung University.
Chung-Yi LiDepartment of Public Health, College of Medicine, National Cheng Kung University.ORCID http://orcid.org/0000-0002-0321-8908

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMetabolic Dysfunction-associated Steatotic Liver Disease (MASLD) has become a global epidemic, and air pollution has been identified as a potential risk factor. This study aims to investigate the non-linear relationship between ambient air pollution and MASLD prevalence.

methodIn this cross-sectional study, participants undergoing health checkups were assessed for three-year average air pollution exposure. MASLD diagnosis required hepatic steatosis with at least 1 out of 5 cardiometabolic criteria. A stepwise approach combining data visualization and regression modeling was used to determine the most appropriate link function between each of the six air pollutants and MASLD. A covariate-adjusted six-pollutant model was constructed accordingly.

resultsA total of 131,592 participants were included, with 40.6% met the criteria of MASLD. "Threshold link function," "interaction link function," and "restricted cubic spline (RCS) link functions" best-fitted associations between MASLD and PM

conclusionNon-linear associations were found between air pollutants and MASLD prevalence. PM

Indexed as

Air PollutantsAir PollutionLiver DiseasesCross-Sectional StudiesEnvironmental ExposureHumansNitrogen DioxideParticulate MatterAir PollutantsNitrogen DioxideParticulate MatterAir pollutantsEpidemiologic studyMetabolic dysfunction-associated steatotic liver disease (MASLD)Particular mattersRestricted cubic spline (RCS)Risk factors

Identifiers

PMID38346730
PMCPMC10898959

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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.