ArticleToxics2025
Combined Effect of Metals, PFAS, Phthalates, and Plasticizers on Cardiovascular Disease Risk.
Article in Toxics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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.
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.
Who cites it
4 citing papers in PubMed.
- A Practical Framework for Incorporating Complex Survey Design in Bayesian Kernel Machine Regression.Stats · 2026Article
- An Exploration of Machine Learning Methods in Human Biomonitoring.International journal of environmental research and public health · 2026Review
- Review
- Uncovering Exposure Patterns of Metals, PFAS, Phthalates, and PAHs and Their Combined Effect on Liver Injury Markers.Journal of xenobiotics · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
This study assessed the relationship between environmental chemical mixtures-including metals, per- and polyfluoroalkyl substances (PFAS), phthalates, and plasticizers-and key cardiovascular health markers using data from the 2013-2014 National Health and Nutrition Examination Survey (NHANES). The combined effects of these pollutants on cardiovascular markers were evaluated using Bayesian Kernel Machine Regression (BKMR), a flexible, non-parametric modeling approach that accommodates nonlinear and interactive relationships among exposures. BKMR was applied to assess both the joint and individual associations of the chemical mixture with systolic blood pressure (SBP), high-density lipoprotein (HDL), low-density lipoprotein (LDL), diastolic blood pressure (DBP), total cholesterol, and triglycerides. As part of the BKMR analysis, posterior inclusion probabilities (PIPs) were estimated to identify the relative importance of each exposure within the mixture. These results highlighted phthalates as major contributors to LDL, SBP, total cholesterol, HDL, and triglycerides while plasticizers were associated with LDL, SBP, HDL, and triglycerides. Metals and PFAS were most strongly linked to LDL, DBP, total cholesterol, and SBP. The overall mixture effect indicated that cumulative exposures were associated with lower LDL and SBP and elevated DBP, suggesting an increased cardiovascular risk. Triglycerides exhibited a complex quantile-dependent trend, with higher exposures associated with reduced levels. These findings underscore the importance of mixture-based risk assessments that reflect real-world exposure scenarios.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.