Isomer-Specific Serum Concentrations of Perfluorooctane Sulfonic Acid among U.S. Adults: Results from the National Health and Nutrition Examination Survey (NHANES) and the Study of Women’s Health Across the Nation Multi-Pollutant Study (SWAN-MPS)

Drinking water contaminated by per- and polyfluoroalkyl substances (PFAS) is a widespread public health concern, and exposure–response relationships are known to vary across sociodemographic groups. However, research on disparities in drinking water PFAS exposures and the siting of PFAS sources in marginalized communities is limited. Here, we use monitoring data from 7873 U.S. community water systems (CWS) in 18 states to show that PFAS detection is positively associated with the number of PFAS sources and proportions of people of color who are served by these water systems. Each additional industrial facility, military fire training area, and airport in a CWS watershed was associated with a 10–108% increase in perfluorooctanoic acid and a 20–34% increase in perfluorooctane sulfonic acid in drinking water. Waste sector sources were also significantly associated with drinking water PFAS concentrations. CWS watersheds with PFAS sources served higher proportions of Hispanic/Latino and non-Hispanic Black residents compared to those without PFAS sources. CWS serving higher proportions of Hispanic/Latino and non-Hispanic Black residents had significantly increased odds of detecting several PFAS. This likely reflects disparities in the siting of PFAS contamination sources. Results of this work suggest that addressing environmental justice concerns should be a component of risk mitigation planning for areas affected by drinking water PFAS contamination.

Section: Resultsmentioning

confidence: 97%

“…However, these data reflect exposures from all PFAS sources rather than just drinking water. For example, fish consumption frequency has been identified as an important predictor of serum PFOS concentrations in NHANES, and freshwater fish contamination by PFAS may also be an environmental justice concern. , …”

Section: Resultsmentioning

confidence: 99%

Sociodemographic Factors Are Associated with the Abundance of PFAS Sources and Detection in U.S. Community Water Systems

Liddie

Schaider

Sunderland

2023

“…A major and current public health concern is exposure to per- and polyfluoroalkyl substances (PFAS), a family of ≥9000 synthetic chemicals used in a wide range of industrial and commercial applications, including food packaging, stain-resistant furniture, and firefighting foam . PFAS are persistent in the environment and human exposure is ubiquitous, though variable across the United States (US), in part due to long biological half-lives and bioaccumulation. − While concentrations of legacy PFAS, such as perfluorooctanesulfonic acid (PFOS) and perfluorooctanoic acid (PFOA), have gradually declined at the population level, replacement chemicals with similar structures continue to be introduced to the market and are associated with toxicity and exposure pathways. , …”

Section: Introductionmentioning

confidence: 99%

“… 1 PFAS are persistent in the environment and human exposure is ubiquitous, though variable across the United States (US), in part due to long biological half-lives and bioaccumulation. 2 − 4 While concentrations of legacy PFAS, such as perfluorooctanesulfonic acid (PFOS) and perfluorooctanoic acid (PFOA), have gradually declined at the population level, replacement chemicals with similar structures continue to be introduced to the market and are associated with toxicity and exposure pathways. 3 , 5 …”

Section: Introductionmentioning

confidence: 99%

Metabolic Perturbations Associated with an Exposure Mixture of Per- and Polyfluoroalkyl Substances in the Atlanta African American Maternal-Child Cohort

Liang,

Taibl,

Dunlop

et al. 2023

Prenatal exposure to single chemicals belonging to the per-and polyfluoroalkyl substances (PFAS) family is associated with biological perturbations in the mother, fetus, and placenta, plus adverse health outcomes. Despite our knowledge that humans are exposed to multiple PFAS, the potential joint effects of PFAS on the metabolome remain largely unknown. Here, we leveraged high-resolution metabolomics to identify metabolites and metabolic pathways perturbed by exposure to a PFAS mixture during pregnancy. Targeted assessment of perfluorooctanoic acid (PFOA), perfluorononanoic acid (PFNA), perfluorooctanesulfonic acid (PFOS), and perfluorohexanesulfonic acid (PFHxS), along with untargeted metabolomics profiling, were conducted on nonfasting serum samples collected from pregnant African Americans at 6−17 weeks gestation. We estimated the overall mixture effect and partial effects using quantile g-computation and single-chemical effects using linear regression. All models were adjusted for maternal age, education, parity, early pregnancy body mass index, substance use, and gestational weeks at sample collection. Our analytic sample included 268 participants and was socioeconomically diverse, with the majority receiving public health insurance (78%). We observed 13.3% of the detected metabolic features were associated with the PFAS mixture (n = 1705, p < 0.05), which was more than any of the single PFAS chemicals. There was a consistent association with metabolic pathways indicative of systemic inflammation and oxidative stress (e.g., glutathione, histidine, leukotriene, linoleic acid, prostaglandins, and vitamins A, C, D, and E metabolism) across all metabolome-wide association studies. Twenty-six metabolites were validated against authenticated compounds and associated with the PFAS mixture (p < 0.05). Based on quantile g-computation weights, PFNA contributed the most to the overall mixture effect for γ-aminobutyric acid (GABA), tyrosine, and uracil. In one of the first studies of its kind, we demonstrate the feasibility and utility of using methods designed for exposure mixtures in conjunction with metabolomics to assess the potential joint effects of multiple PFAS chemicals on the human metabolome. We identified more pronounced metabolic perturbations associated with the PFAS mixture than for single PFAS chemicals. Taken together, our findings illustrate the potential for integrating environmental mixture analyses and high-throughput metabolomics to elucidate the molecular mechanisms underlying human health.

“…Use of random effects models and the more general mixed models in analysis of measurement data is well established. These models can take measurement error into account appropriately, although its estimation may not be of interest, and many of these models incorporate replicates. − There are also many examples in the environmental measurement and biomonitoring data literature where descriptive statistics such as means, standard deviations, and confidence intervals are estimated as sample-based for the whole sample or for a subgroup. − We emphasize two key distinctions of our work. The first distinction is that established random effects and mixed models include variables for fixed or random effects (such as covariates), which our model does not.…”

Section: Introductionmentioning

confidence: 99%

Separating Measurement Error and Signal in Environmental Data: Use of Replicates to Address Uncertainty

Furman,

Thomas,

George

2023

Measurement uncertainty has long been a concern in the characterizing and interpreting environmental and toxicological measurements. We compared statistical analysis approaches when there are replicates: a Naı̈ve approach that omits replicates, a Hybrid approach that inappropriately treats replicates as independent samples, and a Measurement Error Model (MEM) approach in a random effects analysis of variance (ANOVA) model that appropriately incorporates replicates. A simulation study assessed the effects of sample size and levels of replication, signal variance, and measurement error on estimates from the three statistical approaches. MEM results were superior overall with confidence intervals for the observed mean narrower on average than those from the Naı̈ve approach, giving improved characterization. The MEM approach also featured an unparalleled advantage in estimating signal and measurement error variance separately, directly addressing measurement uncertainty. These MEM estimates were approximately unbiased on average with more replication and larger sample sizes. Case studies illustrated analyzing normally distributed arsenic and log-normally distributed chromium concentrations in tap water and calculating MEM confidence intervals for the true, latent signal mean and latent signal geometric mean (i.e., with measurement error removed). MEM estimates are valuable for study planning; we used simulation to compare various sample sizes and levels of replication.