The Association of Combined Per- and Polyfluoroalkyl Substances and Metals with Allostatic Load Using Bayesian Kernel Machine Regression

Diseases · 2 authors, 2 centres

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TL;DR

This cross-sectional study used Bayesian Kernel Machine Regression on NHANES 2007–2014 data to examine associations between combined PFAS and metal exposures and allostatic load in U.S. adults. Cesium, molybdenum, PFHS, PFNA, and mercury showed the strongest associations with allostatic load based on posterior inclusion probabilities.

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Univariate exposure-response functions indicated that PFNA, PFUA, PFOA, PFHS, mercury, cesium, thallium, tungsten, and uranium were associated with AL. The findings suggest that cumulative environmental exposures contribute to physiological stress burden.

STUDY TYPE

cross-sectional

SPECIALTY

epidemiology

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ORIGINAL PAPER

PMC10047702

The Association of Combined Per- and Polyfluoroalkyl Substances and Metals with Allostatic Load Using Bayesian Kernel Machine Regression

Diseases

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ABSTRACT

Abstract Background/Objective: This study aimed to investigate the effect of exposure to per- and polyfluoroalkyl substances (PFAS), a class of organic compounds utilized in commercial and industrial applications, on allostatic load (AL), a measure of chronic stress. PFAS, such as perfluorodecanoic acid (PFDE), perfluorononanoic acid (PFNA), perfluorooctane sulfonic acid (PFOS), perfluoroundecanoic acid (PFUA), perfluorooctanoic acid (PFOA), and perfluorohexane sulfonic acid (PFHS), and metals, such as mercury (Hg), barium (Ba), cadmium (Cd), cobalt (Co), cesium (Cs), molybdenum (Mo), lead (Pb), antimony (Sb), thallium (TI), tungsten (W), and uranium (U) were investigated. This research was performed to explore the effects of combined exposure to PFAS and metals on AL, which may be a disease mediator. Methods : Data from the National Health and Nutrition Examination Survey (NHANES) from 2007 to 2014 were used to conduct this study on persons aged 20 years and older. A cumulative index of 10 biomarkers from the cardiovascular, inflammatory, and metabolic systems was used to calculate AL out of 10. If the overall index was ≥ 3, an individual was considered to be chronically stressed (in a state of AL). In order to assess the dose-response connections between mixtures and outcomes and to limit the effects of multicollinearity and other potential interaction effects between exposures, Bayesian kernel machine regression (BKMR) was used. Results : The most significant positive trend between mixed PFAS and metal exposure and AL was revealed by combined exposure to cesium, molybdenum, PFHS, PFNA, and mercury (posterior inclusion probabilities, PIP = 1, 1, 0.854, 0.824, and 0.807, respectively). Conclusions : Combined exposure to metals and PFAS increases the likelihood of being in a state of AL. Keywords: PFAS, metals, allostatic load, BKMR, mixtures

CITATION EXPORT

Tahir Bashir, Emmanuel Obeng-Gyasi. The Association of Combined Per- and Polyfluoroalkyl Substances and Metals with Allostatic Load Using Bayesian Kernel Machine Regression. Diseases. (2023). https://doi.org/10.3390/diseases11010052

AUTHORS

2 · 2 CENTRES

Tahir Bashir, Emmanuel Obeng-Gyasi

1Department of Built Environment, North Carolina A&T State University, Greensboro, NC 27411, USA
2Environmental Health and Disease Laboratory, North Carolina A&T State University, Greensboro, NC 27411, USA