Using Geospatial Data and Random Forest To Predict PFAS Contamination in Fish Tissue in the Columbia River Basin, United States.

Decision makers in the Columbia River Basin (CRB) are currently challenged with identifying and characterizing the extent of per- and polyfluoroalkyl substances (PFAS) contamination and human exposure to PFAS. This work aims to develop and pilot a methodology to help decision makers target and prioritize sampling investigations and identify contaminated natural resources. Here we use random forest models to predict ∑PFAS in fish tissue; understanding PFAS levels in fish is particularly important in the CRB because fish can be a major component of tribal and indigenous people diet. Geospatial data, including land cover and distances to known or potential PFAS sources and industries, were leveraged as predictors for modeling. Models were developed and evaluated for Washington state and Oregon using limited available empirical data. Mapped predictions show several areas where detectable concentrations of PFAS in fish tissue are predicted to occur, but prior sampling has not yet confirmed. Variable importance is analyzed to identify potentially important sources of PFAS in fish in this region. The cost-effective methodologies demonstrated here can help address sparsity of existing PFAS occurrence data in environmental media in this and other regions while also giving insights into potentially important drivers and sources of PFAS in fish.

Geographic and demographic variability in serum PFAS concentrations for pregnant women in the United States.

BACKGROUND: While major pathways of human PFAS exposure are thought to be drinking water and diet, other pathways and sources have also been shown to contribute to a person's cumulative exposure. However, the degree of contribution of these other sources to PFAS body burdens is still not well understood and occurrence data for PFAS in conssumer products and household materials are sparse. Questionnaire data concordant with biomonitoring may improve understanding of associations between other PFAS exposure pathways and exposure in human populations. OBJECTIVE: This study aims to better understand maternal and early-life exposures to PFAS from various potential sources and pathways in the context of household and community level characteristics. METHODS: PFAS data from the National Children's Study (NCS) Vanguard Data and Sample Archive Access System were analyzed from serum of 427 pregnant women residing in 7 counties throughout the United States. Location and self-reported questionnaire responses were used to analyze variability in serum concentrations based on demographics, housing characteristics, behaviors, and geography. Spatial mapping analyses incorporated publicly available data to further hypothesize potential sources of exposure in two NCS counties. RESULTS: Location was associated with serum concentrations for all PFAS chemicals measured. Questionnaire responses for race/ethnicity, income, education level, number of household members, drinking water source, home age, and fast-food consumption were associated with PFAS levels. Statistical differences were observed between participants with the same questionnaire responses but in different locations. Spatial mapping analyses suggested that participants' proximity to local point sources can overshadow expected trends with demographic information. SIGNIFICANCE: By increasing understanding of maternal and early-life PFAS exposures from various potential sources and pathways, as well as highlighting the importance of proximity to potential sources in identifying vulnerable populations and locations, this work reveals environmental justice considerations and contributes to risk management strategies that maximize public health protection. IMPACT: This work increases understanding of maternal and early-life PFAS exposures, reveals environmental justice considerations, and contributes to study design and risk management strategies.

Human exposure pathways to poly- and perfluoroalkyl substances (PFAS) from indoor media: A systematic review.

BACKGROUND: Human exposure to per- and polyfluoroalkyl substances (PFAS) has been primarily attributed to contaminated food and drinking water. There is information indicating other sources and pathways of exposure in residential environments, but few studies report relationships between these indoor media and human biomonitoring measurements. METHODS: This study adapts existing systematic review tools and methodologies to synthesize evidence for PFAS exposure pathways from indoor environment media including consumer products, household articles, cleaning products, personal care products, and indoor air and dust. Studies were identified using innovative machine learning approaches and pathway-specific search strings to reduce time needed for literature search and screening. The included studies and systematic review were evaluated using tools modified specifically for exposure studies. The systematic review was conducted following a previously published protocol (DeLuca et al., 2021) that describes the systematic review methodology used in detail. RESULTS: Only 7 studies were identified that measured the targeted subset of 8 PFAS chemicals in concordant household media (primarily house dust) and participant serum. Data extracted from the included studies were used to calculate exposure intake rates and estimate a percentage of occupant serum concentrations that could be attributed to the indoor exposure pathways. These calculations showed that exposure to PFOA, PFOS, PFNA, and PFHxS from contaminated house dust could account for 13%, 3%, 7%, and 25% of serum concentrations, respectively. Inhalation of PFAS in indoor air could account for less than 4% of serum PFOA concentrations and less than 2% of serum PFOS and PFNA concentrations. A risk of bias was identified due to participant profiles in most of the studies being skewed towards white, female, and higher socioeconomic status. CONCLUSIONS: Along with synthesizing evidence for estimated contributions to serum PFAS levels from indoor exposure media, this systematic review also identifies a consistent risk of bias across exposure study populations that should be considered in future studies. It highlights a major research gap and need for studies that measure concordant data from both indoor exposure media and participant serum and the need for continued research on exposure modeling parameters for many PFAS chemicals.

Demonstrating a systems approach for integrating disparate data streams to inform decisions on children's environmental health.

BACKGROUND: The use of systems science methodologies to understand complex environmental and human health relationships is increasing. Requirements for advanced datasets, models, and expertise limit current application of these approaches by many environmental and public health practitioners. METHODS: A conceptual system-of-systems model was applied for children in North Carolina counties that includes example indicators of children's physical environment (home age, Brownfield sites, Superfund sites), social environment (caregiver's income, education, insurance), and health (low birthweight, asthma, blood lead levels). The web-based Toxicological Prioritization Index (ToxPi) tool was used to normalize the data, rank the resulting vulnerability index, and visualize impacts from each indicator in a county. Hierarchical clustering was used to sort the 100 North Carolina counties into groups based on similar ToxPi model results. The ToxPi charts for each county were also superimposed over a map of percentage county population under age 5 to visualize spatial distribution of vulnerability clusters across the state. RESULTS: Data driven clustering for this systems model suggests 5 groups of counties. One group includes 6 counties with the highest vulnerability scores showing strong influences from all three categories of indicators (social environment, physical environment, and health). A second group contains 15 counties with high vulnerability scores driven by strong influences from home age in the physical environment and poverty in the social environment. A third group is driven by data on Superfund sites in the physical environment. CONCLUSIONS: This analysis demonstrated how systems science principles can be used to synthesize holistic insights for decision making using publicly available data and computational tools, focusing on a children's environmental health example. Where more traditional reductionist approaches can elucidate individual relationships between environmental variables and health, the study of collective, system-wide interactions can enable insights into the factors that contribute to regional vulnerabilities and interventions that better address complex real-world conditions.

Children's Environmental Health: A Systems Approach for Anticipating Impacts from Chemicals.

Increasing numbers of chemicals are on the market and present in consumer products. Emerging evidence on the relationship between environmental contributions and prevalent diseases suggests associations between early-life exposure to manufactured chemicals and a wide range of children's health outcomes. Using current assessment methodologies, public health and chemical management decisionmakers face challenges in evaluating and anticipating the potential impacts of exposure to chemicals on children's health in the broader context of their physical (built and natural) and social environments. Here, we consider a systems approach to address the complexity of children's environmental health and the role of exposure to chemicals during early life, in the context of nonchemical stressors, on health outcomes. By advancing the tools for integrating this more complex information, the scope of considerations that support chemical management decisions can be extended to include holistic impacts on children's health.