Toward Advancing Precision Environmental Health: Developing a Customized Exposure Burden Score to PFAS Mixtures to Enable Equitable Comparisons Across Population Subgroups, Using Mixture Item Response Theory

Per- and Polyfluoroalkyl Substances (PFAS) in Consumer Products: An Overview of the Occurrence, Migration, and Exposure Assessment

Per- and polyfluoroalkyl substances (PFASs) have been widely used in the production of consumer products globally due to the excellent water and oil resistance and anti-fouling properties. The multiple toxic effects of some PFASs also pose a threat to human health and ecosystem, and the frequent use of certain consumer products increased the risk of human exposure to PFASs. More data on the occurrence, concentration, and migration of PFASs in consumer products is urgently needed to address the possible risks posed by exposure to consumer products. This paper reviews the PFAS concentrations found, the migration characteristics known, and the exposure risks of PFASs arising from several types of consumer products over the last five years. The types of consumer products considered here include food contact materials, textiles, and disposable personal hygiene products. The influence of different factors on the migration process of PFASs from these products are summarized and discussed. Additionally, the main approaches and models of exposure assessment are evaluated and summarized. Current challenges and future research prospects in this field are discussed with a view to providing guidance for the future assessment and regulation of PFASs in consumer products.

Exposome Burden Scores to Summarize Environmental Chemical Mixtures: Creating a Fair and Common Scale for Cross-study Harmonization, Report-back and Precision Environmental Health

PURPOSE OF REVIEW

Environmental health researchers are increasingly concerned about characterizing exposure to environmental chemical mixtures (co-exposure to multiple chemicals simultaneously). We discuss approaches for quantifying an overall summary score or index that reflects an individual's total exposure burden to components of the mixture. We focus on unsupervised methods, in which the summary score is not computed in relation to a pre-specified health outcome.

RECENT FINDINGS

Sum-scores and principal components analysis (PCA) are common approaches for quantifying a total exposure burden metric but have several limitations: 1) they require imputation when using exposure biomarkers with high frequency of non-detection, 2) they do not account for exposure heterogeneity, 3) sum-scores assume the same measurement error for all people, while there is no error term inherent to the PCA model as its primary purpose is dimension reduction, and 4) in pooled analyses, both approaches are limited to analyzing the set of exposure variables that are in common across all studies, potentially discarding valuable information. Meanwhile, item response theory (IRT) is a novel and promising alternative to calculate an exposure burden score that addresses the above limitations. It allows for the inclusion of exposure analytes with high frequency of non-detects without the need for imputation. It can account for exposure heterogeneity to calculate fair metrics for all people, through assessment of differential item functioning and mixture IRT. IRT also quantifies measurement errors of the exposure burden score that are individual-specific, such that it appropriately assigns a larger standard error to an individual who has missing data on one or more exposure variables. Lastly, IRT enhances cross-study harmonization by enabling the creation of exposure burden calculators to set a common scale across studies, and allows for the inclusion of all exposure variables within a chemical class, even if they were only measured in a subset of participants. Summarizing total exposure burden, through the creation of fair and informative index scores, is a promising tool for environmental health research as environmental exposures are increasingly used for biomonitoring and clinical recommendations.

Associations of PFAS concentrations during pregnancy and midlife with bone health in midlife: Cross-sectional and prospective findings from Project Viva

BACKGROUND

PFAS may impair bone health, but effects of PFAS exposure assessed during pregnancy and the perimenopause-life stages marked by rapidly changing bone metabolism-on later life bone health are unknown.

METHODS

We studied 531 women in the Boston-area Project Viva cohort. We used multivariable linear, generalized additive, and mixture models to examine associations of plasma PFAS concentrations during early pregnancy [median (IQR) maternal age 32.9 (6.2) years] and midlife [age 51.2 (6.3)] with lumbar spine, total hip, and femoral neck areal bone mineral density (aBMD) and bone turnover biomarkersassessed in midlife. We examined effect modification by diet and physical activity measured at the time of PFAS exposure assessment and by menopausal status in midlife.

RESULTS

Participants had higher PFAS concentrations during pregnancy [1999-2000; e.g., PFOA median (IQR) 5.4 (3.8) ng/mL] than in midlife [2017-2021; e.g.

, PFOA

1.5 (1.2) ng/mL]. Women with higher PFOA, PFOS and PFNA during pregnancy had higher midlife aBMD, especially of the spine [e.g., 0.28 (95% CI: 0.07, 0.48) higher spine aBMD T-score, per doubling of PFOA], with stronger associations observed among those with higher diet quality. In contrast, higher concentrations of all PFAS measured in midlife were associated with lower concurrent aBMD at all sites [e.g., -0.21 (-0.35, -0.07) lower spine aBMD T-score, per doubling of PFOA]; associations were stronger among those who were postmenopausal. The associations of several PFAS with bone resorption (loss) were also stronger among postmenopausal versus premenopausal women.

DISCUSSION

Plasma PFAS measured during pregnancy versus in midlife had different associations with midlife aBMD. We found an adverse association of PFAS measured in midlife with midlife aBMD, particularly among postmenopausal women. Future studies with longer follow-up are needed to elucidate the effect of PFAS on bone health during the peri- and postmenopausal years.

Assessing the Impact and Cost-Effectiveness of Exposome Interventions on Alzheimer's Disease: A Review of Agent-Based Modeling and Other Data Science Methods for Causal Inference

Background: The exposome (e.g., totality of environmental exposures) and its role in Alzheimer's Disease and Alzheimer's Disease and Related Dementias (AD/ADRD) are increasingly critical areas of study. However, little is known about how interventions on the exposome, including personal behavioral modification or policy-level interventions, may impact AD/ADRD disease burden at the population level in real-world settings and the cost-effectiveness of interventions. Methods: We performed a critical review to discuss the challenges in modeling exposome interventions on population-level AD/ADRD burden and the potential of using agent-based modeling (ABM) and other advanced data science methods for causal inference to achieve this. Results: We describe how ABM can be used for empirical causal inference modeling and provide a virtual laboratory for simulating the impacts of personal and policy-level interventions. These hypothetical experiments can provide insight into the optimal timing, targeting, and duration of interventions, identifying optimal combinations of interventions, and can be augmented with economic analyses to evaluate the cost-effectiveness of interventions. We also discuss other data science methods, including structural equation modeling and Mendelian randomization. Lastly, we discuss challenges in modeling the complex exposome, including high dimensional and sparse data, the need to account for dynamic changes over time and over the life course, and the role of exposome burden scores developed using item response theory models and artificial intelligence to address these challenges. Conclusions: This critical review highlights opportunities and challenges in modeling exposome interventions on population-level AD/ADRD disease burden while considering the cost-effectiveness of different interventions, which can be used to aid data-driven policy decisions.

Mid-Childhood Plasma Concentrations of Per- and Polyfluoroalkyl Substances, Modifiable Lifestyle Factors, and Bone Mineral Density Through Late Adolescence

There is limited research on associations of per- and polyfluoroalkyl substances (PFAS) with areal bone mineral density (aBMD) through adolescence and whether bone-strengthening factors ameliorate effects. In the Project Viva cohort (N = 484; 50% female), we used sex-stratified linear regression and quantile g-computation mixture models to examine associations of mid-childhood (median: 7.8 years; 2007-2010) plasma PFAS concentrations with a dual-energy X-ray absorptiometry total-body aBMD Z-score in early and late adolescence (median: 12.9 and 17.6 years, respectively). We explored stratum-specific estimates by parent/self-reported physical activity and dairy intake. Using linear mixed models, we evaluated associations with aBMD accrual from mid-childhood through late adolescence. Females with higher perfluorooctanoate (PFOA) and perfluorodecanoate (PFDA) had lower early adolescent aBMD Z-score [e.g., β(95%CI)] per doubling PFOA: -0.19(-0.41, 0.03)]. Youth with higher PFOA and PFDA had lower late adolescent aBMD Z-score, but CIs were wide [e.g., PFOA: females, -0.12(-0.40, 0.16); males, -0.10(-0.42, 0.21)]. Mixture models generally corroborated single PFAS results, and in linear mixed models, females with higher PFAS concentrations, and males with higher PFOA, had slower aBMD accrual. Less active males with higher PFOA, PFDA, and the PFAS mixture had lower late adolescent aBMD Z-score. Some PFAS appeared more negatively associated with the aBMD Z-score among those who consumed less dairy, but there was not consistent evidence of effect modification. Exposure to select PFAS may affect bone accrual through adolescence, with possible resilience conferred by greater physical activity and dairy intake.

Applying Latent Variable Models to Estimate Cumulative Exposure Burden to Chemical Mixtures and Identify Latent Exposure Subgroups: A Critical Review and Future Directions

Environmental mixtures, which reflect joint exposure to multiple environmental agents, are a major focus of environmental health and risk assessment research. Advancements in latent variable modeling and psychometrics can be used to address contemporary questions in environmental mixtures research. In particular, latent variable models can quantify an individual's cumulative exposure burden to mixtures and identify hidden subpopulations with distinct exposure patterns. Here, we first provide a review of measurement approaches from the psychometrics field, including structural equation modeling and latent class/profile analysis, and discuss their prior environmental epidemiologic applications. Then, we discuss additional, underutilized opportunities to leverage the strengths of psychometric approaches. This includes using item response theory to create a common scale for comparing exposure burden scores across studies; facilitating data harmonization through the use of anchors. We also discuss studying fairness or appropriateness of measurement models to quantify exposure burden across diverse populations, through the use of mixture item response theory and through evaluation of measurement invariance and differential item functioning. Multi-dimensional models to quantify correlated exposure burden sub-scores, and methods to adjust for imprecision of chemical exposure data, are also discussed. We show that there is great potential to address pressing environmental epidemiology and exposure science questions using latent variable methods.

Elevated levels of serum per- and poly-fluoroalkyl substances (PFAS) in contact lens users of U.S. young adults

Despite evidence indicating the presence of per- and poly-fluoroalkyl substances (PFAS) in contact lenses (CL), it remains unclear whether CL use increases PFAS exposure in the general population. We aimed to determine whether CL users have higher serum concentrations of PFAS than non-users, using data of 1660 adults aged 20-39 years participating in the National Health and Nutrition Examination Survey 1999-2000 and 2003-2008. We classified the individuals into CL users and non-users using the record of vision correction types during a vision test. Serum concentrations of six individual PFAS were measured, and the overall PFAS burden was calculated by item response theory scoring. Survey-weighted linear models were used to compare serum PFAS levels between CL users and non-users after adjusting for covariates. Distributions of perfluorooctanoic acid (PFOA) and perfluorooctane sulfonic acid (PFOS) concentrations were compared with reference values (e.g., human biomonitoring [HBM]-II values) indicating potential for adverse health effects. Survey-weighted linear models revealed that covariate-adjusted serum PFOA concentration was higher in CL users (geometric mean [GM]: 3.68 ng/mL; 95% CI: 3.00, 4.50) than in non-users (GM: 3.27 ng/mL; 95% CI: 2.81, 3.80; p = 0.02). Similarly, CL users had a significantly higher serum PFHxS concentration (GM: 1.58 ng/mL; 95% CI: 1.13, 2.20) than non-users (GM: 1.30 ng/mL; 95% CI: 1.10, 1.66; p = 0.03). CL users also had a significantly higher overall burden of PFAS than non-users. The differences in PFAS concentrations between CL users and non-users were more pronounced in females than in males. Moreover, a larger proportion of lens users (4.5%), compared to non-users (3.9%), had PFOA concentrations above the HBM-II, where adverse health effects are expected from PFOA exposure. This study suggests that CL use in general U.S. young adults may contribute significantly to PFAS body burden, which can potentially lead to public health problem.