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Combined Effects of PFAS and Metals on Cognitive Function

  • North Carolina Agricultural and Technical State University

Research output: Contribution to journalArticlepeer-review

Abstract

Background: Heavy metals and per- and polyfluoroalkyl substances (PFAS) are widespread environmental pollutants that have been linked to worsening cognition, but how the two classes act together to shape cognitive function is still not well characterized. Drawing on data from the National Health and Nutrition Examination Survey (NHANES), this observational analysis evaluated how PFAS and metals are jointly related to performance across distinct cognitive domains in older adults. Methods: We analyzed 1447 adults aged 60 years and older from the 2011–2012 NHANES cycle in a cross-sectional design study. Metal levels in serum and whole blood were determined with standardized laboratory assays. Associations of single exposures and of the overall mixture with the CERAD word-learning and recall tasks, Animal Fluency, and the Digit Symbol Substitution Test were assessed using multivariable linear regression, together with Bayesian Kernel Machine Regression (BKMR). Results: Single-exposure models produced largely modest and inconsistent associations across the cognitive measures. Within the mixture models, PFAS, especially PFOA, PFDE, and PFOS, were repeatedly flagged as influential across several domains, whereas the metals tended to matter for specific outcomes only. The strongest negative signals at elevated joint exposure emerged for memory-related measures, notably CERAD Trials 1 and 2. Conclusions: Joint exposure to PFAS and heavy metals appears to influence cognitive domains unevenly, with memory-related measures seeming more responsive as combined exposure rises. These results reinforce the value of mixture-oriented analytic strategies when investigating environmental contaminants in relation to cognitive aging.
Original languageEnglish
Article number319
JournalEnvironments - MDPI
Volume13
Issue number6
DOIs
StatePublished - Jun 1 2026

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • Bayesian kernel machine regression
  • CERAD
  • PFAS
  • cognitive function
  • environmental mixtures
  • heavy metals
  • neurotoxicity

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