Combined Effects of Metals, PCBs, Dioxins, and Furans on Cardiovascular Dysfunction

Bolanle Akinyemi, Emmanuel Obeng-Gyasi

Research output: Contribution to journalArticlepeer-review

Abstract

Environmental exposures to heavy metals, polychlorinated biphenyls (PCBs), dioxins, and furans have been associated with adverse cardiovascular outcomes, yet their combined effects remain underexplored. This study examined the joint influence of these contaminants on cardiovascular risk indicators in a representative sample of U.S. adults from the 2003–2004 National Health and Nutrition Examination Survey (NHANES). Biomarkers of exposure included lead, cadmium, mercury, twelve PCB congeners, seven dioxins, and ten furans. Cardiovascular outcomes were assessed using blood pressure, Framingham Risk Score (FRS), and lipid profiles. Associations were analyzed using multivariable linear regression and Bayesian Kernel Machine Regression (BKMR), adjusting for age, sex, ethnicity, body mass index, smoking, alcohol consumption, and income. The results demonstrated that metals, particularly mercury, were strongly associated with increased blood pressure and altered HDL cholesterol. PCBs were predominantly linked to elevated systolic blood pressure and FRS, with PCB156 and PCB126 identified as principal contributors. Furans exhibited the strongest associations with dyslipidemia, including elevated LDL cholesterol, total cholesterol, and triglycerides. Combined exposure analysis revealed a complex pattern, with increasing pollutant burdens associated with rising blood pressure and risk scores but declining lipid levels. These findings underscore the outcome-specific effects of pollutant mixtures and suggest that chronic low-level exposure to multiple environmental contaminants may contribute to cardiovascular dysfunction in the general population. Further longitudinal research is needed to confirm these associations and guide risk reduction strategies.

Original languageEnglish
Article number94
JournalJournal of Xenobiotics
Volume15
Issue number3
DOIs
StatePublished - Jun 2025

Keywords

  • Bayesian Kernel Machine Regression (BKMR)
  • cardiovascular disease
  • environmental pollutants
  • heavy metals
  • polychlorinated biphenyls (PCBs)

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