Evidence map›Paper›PMID 42228134›Full record

ArticleArchives of toxicology2026

Associations of serum per- and polyfluoroalkyl substances (PFAS) mixture with the risk of chronic diseases: evidence from single‑ , multi-pollutant, and machine learning models.

Mei Li, Liting Sheng, Zige Ding, Guangsheng Yu, Yichu Chen, Qitian Chen, Wei Shao, Bingxin Liu, Mulong Du, Dongying Gu and 3 more

Abstract read
PubMed Publisher
In one paragraph

Article in Archives of toxicology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

13 authors.

Mei Li *The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, 215002, China.
Liting Sheng *The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, 215002, China.
Zige Ding *The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, 215002, China.
Guangsheng YuThe Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, 215002, China.
Yichu ChenThe Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, 215002, China.
Qitian ChenThe Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, 215002, China.
Wei ShaoThe Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, 215002, China.
Bingxin LiuThe Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, 215002, China.
Mulong DuThe Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, 215002, China.
Dongying GuDepartment of Oncology, Nanjing First Hospital, Nanjing Medical University, Nanjing, 211166, China.
Silu ChenThe Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, 215002, China. siluchen@njmu.edu.cn.
Junyi XinDepartment of Bioinformatics, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, 211166, China. junyixin@njmu.edu.cn.
Meilin WangThe Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, 215002, China. mwang@njmu.edu.cn.ORCID 0000-0002-4996-958X

Funding

National Key R&D Program of China 2026YFE0104100National Natural Science Foundation of China 82504449National Undergraduate Training Program for Innovation and Entrepreneurship 202510312003Natural Science Foundation of the Jiangsu Higher Education Institutions of China 25KJB330001
6 · The paper itself

Abstract

Per- and polyfluoroalkyl substances (PFAS) are persistent chemicals commonly found in consumer products. Despite growing concern over their health effects, their associations with chronic diseases in humans are still unclear. We included 10,093 participants to examine the associations between 8 PFAS and 40 chronic diseases. Multivariable logistic regression and restricted cubic spline (RCS) models were applied to evaluate linear and nonlinear associations, and mixture effects were further assessed using weighted quantile sum regression (WQS), quantile-based g-computation (q g‑comp), and Bayesian kernel machine regression (BKMR). Overall, we identified 16 significant PFAS-chronic disease associations after false discovery rate (FDR) correction, involving 7 PFAS and 6 chronic diseases. Specifically, each 1 ng/mL increase in perfluoroundecanoic acid (PFUnA) was associated with higher odds of heart attack (OR = 1.32, P

Indexed as

Environmental ExposureEnvironmental PollutantsFluorocarbonsMachine LearningBayes TheoremChronic DiseaseFatty AcidsFemaleHumansMaleEnvironmental PollutantsFatty AcidsFluorocarbonsCancerChronic diseasesMachine learningMixture exposurePFAS

Identifiers

PMID42228134

What OpenQuestion holds

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Registered trials

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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.