Evidence map›Paper›PMID 40635894›Full record

ArticleFrontiers in nutrition2025

Association between urinary heavy metals and cardiovascular-kidney-metabolic syndrome: mediating roles of TyG, WWI, and eGFR.

Jianping Liu, Yuanying Song, Rong Luo, Sufang Wang, Pinglei Pan, Lijian Han

Abstract read
In one paragraph

Article in Frontiers in nutrition, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

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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.

Jianping Liu *Department of Neurology, Yancheng Third People's Hospital (The Sixth Affiliated Hospital of Nantong University, The Yancheng School of Clinical Medicine of Nanjing Medical University, The Affiliated Hospital of Jiangsu Vocational College of Medicine), Yancheng, Jiangsu, China.
Yuanying Song *Department of Neurology, Yancheng Third People's Hospital (The Sixth Affiliated Hospital of Nantong University, The Yancheng School of Clinical Medicine of Nanjing Medical University, The Affiliated Hospital of Jiangsu Vocational College of Medicine), Yancheng, Jiangsu, China.
Rong LuoDepartment of Neurology, Yancheng Third People's Hospital (The Sixth Affiliated Hospital of Nantong University, The Yancheng School of Clinical Medicine of Nanjing Medical University, The Affiliated Hospital of Jiangsu Vocational College of Medicine), Yancheng, Jiangsu, China.
Sufang WangDepartment of Neurology, Yancheng Third People's Hospital (The Sixth Affiliated Hospital of Nantong University, The Yancheng School of Clinical Medicine of Nanjing Medical University, The Affiliated Hospital of Jiangsu Vocational College of Medicine), Yancheng, Jiangsu, China.
Pinglei PanDepartment of Central Laboratory, The Yancheng School of Clinical Medicine of Nanjing Medical University (Yancheng Third People's Hospital), Yancheng, Jiangsu, China.
Lijian HanDepartment of Neurology, Yancheng Third People's Hospital (The Sixth Affiliated Hospital of Nantong University, The Yancheng School of Clinical Medicine of Nanjing Medical University, The Affiliated Hospital of Jiangsu Vocational College of Medicine), Yancheng, Jiangsu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Cardiovascular-kidney-metabolic (CKM) syndrome is a multistage disorder with significant global health and socioeconomic impact. Environmental factors are increasingly recognized as key risk factors in disease development. This study aims to assess the relationship between urinary heavy metals and CKM risk, as well as the mediating roles of triglyceride-glucose index (TyG), weight-adjusted waist index (WWI), and estimated glomerular filtration rate (eGFR). Methods: This cross-sectional analysis uses data from the National Health and Nutrition Examination Survey (NHANES). CKM stages 0-2 are classified as non-advanced, and stages 3-4 as advanced. Multivariable logistic regression, restricted cubic splines (RCS), weighted quantile sum (WQS) regression, quantile-based g-computation (Qgcomp) regression, and Bayesian kernel machine regression (BKMR) were applied to explore associations between metal exposure and advanced CKM. Mediation analysis examined the roles of TyG, WWI, and eGFR in heavy metal-induced advanced CKM. Results: Among 5,221 participants, 4,340 were non-advanced and 881 had advanced CKM. Both individual and mixed heavy metal exposures were positively linked to advanced CKM risk. Cobalt (Co) was identified as a primary contributor. TyG, WWI, and eGFR partially mediate the relationship between heavy metal exposure and advanced CKM prevalence. Conclusion: Heavy metal exposure is associated with increased CKM risk. TyG, WWI, and eGFR were found to partially mediate the association between heavy metal exposure and advanced CKM prevalence, suggesting potential pathways linking environmental exposures to CKM risk.

Indexed as

Bayesian kernel machine regressioncardiovascular-kidney-metabolic syndromeheavy metalsmediation analysisNHANES

Identifiers

PMID40635894
PMCPMC12237628

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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.