Evidence map›Paper›PMID 41934492›Full record

ArticleCardiovascular toxicology2026

Association Between Environmental Chemicals Phthalates and Stroke Among the US Adults: A Cross-Sectional Study.

Qiang Yang, Peirun Wu, Hongjie Li, Ruifeng Yang, Yuanhao Luo, Mingze Li, Shibo Yin, Xiangji Dang, Yan Liu

Abstract read
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In one paragraph

Article in Cardiovascular 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
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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

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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

9 authors.

Qiang YangDepartment of Neurosurgery, Lanzhou University Second Hospital, Cui Ying Men No. 80, Lanzhou, 730030, P.R. China.
Peirun WuThe Second Clinical Medical School, Lanzhou University, Donggang West Road No. 199, Lanzhou, 730020, P.R. China.
Hongjie LiThe Second Clinical Medical School, Lanzhou University, Donggang West Road No. 199, Lanzhou, 730020, P.R. China.
Ruifeng YangThe Second Clinical Medical School, Lanzhou University, Donggang West Road No. 199, Lanzhou, 730020, P.R. China.
Yuanhao LuoThe Second Clinical Medical School, Lanzhou University, Donggang West Road No. 199, Lanzhou, 730020, P.R. China.
Mingze LiThe Second Clinical Medical School, Lanzhou University, Donggang West Road No. 199, Lanzhou, 730020, P.R. China.
Shibo YinThe Second Clinical Medical School, Lanzhou University, Donggang West Road No. 199, Lanzhou, 730020, P.R. China.
Xiangji DangDepartment of Pharmacy, Lanzhou University Second Hospital, Cui Ying Men No. 80, Lanzhou, 730030, Gansu Province, P.R. China. dangxj1986@163.com.
Yan LiuSchool of Pharmacy, Lanzhou University, Donggang West Road No. 199, Lanzhou, 730020, P.R. China. liuyanly@lzu.edu.cn.

Funding

the Cuiying Scientific and Technological Innovation Program of Lanzhou University Second Hospital CY2024-MS-A15the Cuiying Scientific and Technological Innovation Program of Lanzhou University Second Hospital CY2024-MS-B17the High-level Key Research Project of Gansu Provincial Administration of Traditional Chinese Medicine GZKZ-2025-52the Key R&D Program of Gansu Provinc 24YFWA010the Science and Technology Program Project of Lanzhou Municipal Bureau of Science and Technology 2025-2-206the Talent Innovation and Entrepreneurship Project of Lanzhou City 2020-RC-43
6 · The paper itself

Abstract

Stroke has a multifactorial etiology, and phthalates, as widely used environmental chemicals, may play an underexplored role in cerebrovascular health. This study aimed to evaluate the association between urinary phthalate metabolites and stroke risk using data from the National Health and Nutrition Examination Survey (NHANES), complemented by network toxicology, molecular docking, and machine learning approaches. We analyzed data from 10,771 adult participants in NHANES (2003-2018) who had complete records of stroke status, urinary phthalates, and clinical covariates. Multivariable logistic regression and restricted cubic spline (RCS) models were used to assess associations. We constructed protein-protein interaction networks and performed molecular docking to identify potential toxicological targets. Five machine learning algorithms were employed to develop predictive models for phthalate-related stroke risk. Higher levels of MECPP, MCPP, MNBP, and MEOHP were significantly associated with increased stroke prevalence. Network toxicology identified SRC as a key target, and molecular docking confirmed strong binding affinity between MBZP and SRC. Among the machine learning methods, Random Forest achieved the highest predictive performance (AUC = 0.833). Notably, moderate coffee consumption (≤ 170 g/day) was significantly associated with a reduced risk of stroke (OR = 0.63, 95%CI: 0.51-0.77), suggesting potential dietary mitigation against phthalate-related stroke risk. Our findings demonstrate that certain phthalates may increase stroke risk via molecular pathways involving SRC. Furthermore, moderate coffee consumption may mitigate the adverse cerebrovascular effects of these environmental pollutants.

Indexed as

Environmental ExposureEnvironmental PollutantsPhthalic AcidsStrokeAdultAgedBiomarkersCross-Sectional StudiesFemaleHumansMachine LearningMaleMiddle AgedMolecular Docking SimulationNutrition SurveysPredictive Learning ModelsBiomarkersEnvironmental Pollutantsphthalic acidPhthalic Acidssrc-Family KinasesMachine learningMolecular dockingNetwork toxicologyPhthalatesStroke

Identifiers

PMID41934492

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.