BACKGROUND: Charleston Harbor has elevated concentrations of PFAS in dolphins, but local human exposure data are limited. OBJECTIVES: We sought to describe PFAS serum concentrations temporal trends among Gullah African American residents of coastal South Carolina. METHODS: Longitudinal measures of PFAS in blood serum from a Gullah clinical sample, without lupus, were examined using spaghetti plots and visit-to-visit change scores (e.g., differences in concentrations between visits) among the 68 participants with repeated measures available. We also modeled population-level trends among the 71 participants with any data using proportionate percentile models, accounting for clustering through robust standard errors. In a post-hoc analysis we examined heterogeneity of temporal trends by age through mixed-effects models for the log-transformed PFAS compounds. RESULTS: Population concentrations of PFOS dropped approximately 9 (95% CI: 8, 10) percent each year over 2003-2013. This was concordant with individual PFOS trajectories (median PFOS change score -21.7 ng/g wet weight, interquartile range of PFOS change scores: -32.8, -14.9) and reports for other populations over this time period. Several other compounds including PFOA, PFHxS, and PFuNDA also showed a population-level decrease. However, examination of individual trajectories suggested substantial heterogeneity. Post-hoc analyses indicated that PFAS trajectories were heterogeneous by age. CONCLUSIONS: Many PFAS compounds are decreasing in a sample of Gullah African Americans from coastal South Carolina. There may be age differences in the elimination kinetics of PFASs. The possible role of age as a modifier of PFAS serum trends merits further research.

Young children may experience higher per- and polyfluoroalkyl substances (PFAS) exposure than adults due to breastfeeding, higher dust ingestion rates, and frequent hand-to-mouth activities. We explored temporal trends and determinants of child serum PFAS concentrations and their correlations with paired maternal PFAS concentrations. From 2009 to 2017, we collected one blood sample from each of 541 children aged 2-5 years participating in the Childhood Autism Risks from Genetics and Environment (CHARGE) study and quantified 14 PFAS in serum. For nine frequently detected PFAS (>65% of samples), we performed multiple regression adjusting for potential determinants to estimate mean percent concentration changes. For a subset of 327 children, we also quantified nine PFAS in their mother's serum collected at the same visit and computed Spearman correlation coefficients (r_sp) between maternal and child PFAS concentrations. During 2009-2017, child serum concentrations of all nine PFAS decreased by 6-25% annually. Several PFAS concentrations were higher among non-Hispanic white children and those with highly educated parents. Most maternal and child PFAS concentrations were moderately correlated (r_sp = 0.13-0.39), with a strong correlation for N-methyl perfluorooctane sulfonamido acetic acid (r_sp = 0.68). Breastfeeding duration appeared to contribute to higher child and lower maternal PFAS concentrations, resulting in relatively weak correlations between maternal and child PFAS concentrations for samples collected in early childhood. Considering that more than half of our study children had neurodevelopmental concerns, the generalizability of our findings might be limited.

BACKGROUND: Atopic disease may be influenced by prenatal and early life exposure to endocrine disrupting chemicals, including bisphenols, but results from epidemiological studies have been mixed. This study aimed to extend the epidemiological literature, hypothesizing that children with higher prenatal bisphenol exposure are more likely to have childhood atopic disease. METHODS: Urinary bisphenol A (BPA) and S (BPS) concentrations were measured in each trimester from 501 pregnant women in a multi-center, prospective pregnancy cohort. Ever asthma, current asthma, wheeze, and food allergy) were assessed at age six via standardized ISAAC questionnaire. We constructed generalized estimating equations to examine BPA and BPS exposure jointly at each trimester for each atopy phenotype. BPA was modeled as a log-transformed continuous variable, whereas BPS was modeled as detected versus not detected. We also modeled pregnancy-averaged BPA values and a categorical indicator for number of detectable BPS values over pregnancy (0-3) in logistic regression models. RESULTS: First trimester BPA was associated with inverse odds of food allergy among the entire study sample (OR = 0.78, 95% CI = 0.64-0.95, p = 0.01) and females only (OR = 0.69, 95% CI = 0.52-0.90, p = 0.006). The inverse relationship persisted in pregnancy-averaged models of BPA among females (OR = 0.56, 95% CI = 0.35-0.90, p = 0.006). Second trimester BPA was associated with greater odds of food allergy in the entire sample (OR = 1.27, 95% CI = 1.02-1.58, p = 0.03) and among males only (OR = 1.48, 95% CI = 1.02-2.14, p = 0.04). Odds of current asthma increased among males in the pregnancy-averaged BPS models (OR = 1.65, 95% CI = 1.01-2.69, p = 0.045). CONCLUSION: We saw opposite effects of BPA on food allergy that were trimester- and sex-specific. These divergent associations warrant further investigation. There is some evidence to suggest that prenatal BPS is associated with asthma among males, but further research is required in cohorts with a greater proportion of prenatal urine samples with detectable BPS to validate these results.

BACKGROUND: Consuming ultra-processed foods may increase exposure to phthalates, a group of endocrine disruptors prevalent in food contact materials. OBJECTIVES: Investigate associations between ultra-processed food intake and urinary phthalates during pregnancy, and evaluate whether ultra-processed foods mediate socioeconomic disparities in phthalate exposures. METHODS: In a socioeconomically diverse sample of 1031 pregnant women from the Conditions Affecting Neurocognitive Development and Learning in Early Childhood (CANDLE) Study in the urban South, the Block Food Frequency Questionnaire was administered and urinary phthalate metabolites were measured in the second trimester. Linear regressions modeled associations between phthalates and overall ultra-processed food consumption, individual ultra-processed foods, and exploratory factor analysis dietary patterns. Causal mediation analyses examined whether ultra-processed food intake mediates relationships between socioeconomic disparities and phthalate exposures. RESULTS: Ultra-processed foods constituted 9.8-59.0 % (mean = 38.6 %) of participants diets. 10 % higher dietary proportion of ultra-processed foods was associated with 13.1 % (95 %CI: 3.4 %-22.9 %) higher molar sum concentrations of di(2-ethylhexyl) phthalate metabolites (ΣDEHP). 10 % higher consumption of minimally-processed foods was associated with lower ΣDEHP (10.8 %: 3.4 %-22.9 %). Ultra- and minimally-processed food consumption were not associated with non-DEHP metabolites. Standard deviation higher consumptions of hamburger/cheeseburger, French fries, soda, and cake were associated with 10.5 % (4.2 %-17.1 %), 9.2 % (2.6 %-16.2 %), 7.4 % (1.4 %-13.6 %), and 6.0 % (0.0 %-12.4 %), respectively, higher ΣDEHP. Exploratory factor analysis corroborated positive associations of processed food with ΣDEHP, and uncovered a healthy dietary pattern associated with lower urinary ΣDEHP, mono(2-ethyl-5-hydroxyhexyl) (MEHHP), mono(2-ethyl-5-carboxypentyl) (MECPP), mono(2-carboxymethylhexyl) (MCMHP), and mono-isononyl (MINP) phthalates. Significant indirect effects indicated that lower income and education levels were associated with 1.9 % (0.2 %-4.2 %) and 1.4 % (0.1 %-3.3 %) higher ΣDEHP, respectively, mediated via increased ultra-processed food consumption. CONCLUSIONS: Consumption of ultra-processed foods may increase exposure to phthalates. Policies to reduce dietary phthalate exposures from food packaging and processing are needed, as socioeconomic barriers can preclude dietary recommendations as a sole means to reduce phthalate exposures.

Background

Findings from epidemiological studies of prenatal phthalate exposure and child cognitive development are inconsistent. Methods for evaluating mixtures of phthalates, such as weighted quantile sum (WQS) regression, have rarely been applied. We developed a new extension of the WQS method to improve specificity of full-sample analyses and applied it to estimate associations between prenatal phthalate mixtures and cognitive and language outcomes in a diverse pregnancy cohort.

Methods

We measured 22 phthalate metabolites in third trimester urine from mother-child dyads who completed early childhood visits in the Conditions Affecting Neurodevelopment and Learning in Early childhood (CANDLE) study. Language and cognitive ability were assessed using the Bayley Scales of Infant Development (age 3) and the Stanford Binet-5 (age 4-6), respectively. We used multivariable WQS regression to identify phthalate mixtures that were negatively and positively associated with language score and full-scale IQ, in separate models, adjusted for maternal IQ, race, marital status, smoking, BMI, socioeconomic status (SES), child age, sex, and breastfeeding. We evaluated effect modification by sex and SES. If full sample 95% WQS confidence intervals (which are known to be anti-conservative) excluded the null, we calculated a p-value using a permutation test (p_permutation). The performance of this new approach to WQS regression was evaluated in simulated data. We compared the power and type I error rate of WQS regression conducted within datasets split into training and validation samples (WQS_Split) and in the full sample (WQS_Nosplit) to WQS regression with a permutation test (WQS_permutation). Individual metabolite associations were explored in secondary analyses.

Results

The analytic sample (N = 1015) was 62.1% Black/31.5% White, and the majority of mothers had a high school education or less (56.7%) at enrollment. Associations between phthalate mixtures and primary outcomes (language score and full-scale IQ) in the full sample were null. Individual metabolites were not associated with IQ, and only one metabolite (mono-benzyl phthalate, MBzP) was associated with Bayley language score (β = -0.68, 95% CI: -1.37, 0.00). In analyses stratified by sex or SES, mixtures were positively and negatively associated with outcomes, but the precision of full-sample WQS regression results were not supported by permutation tests, with one exception. In the lowest SES category, a phthalate mixture dominated by mono-methyl phthalate (MMP) and mono-carboxy-isooctyl phthalate (MCOP) was associated with higher language scores (β_{low SES} = 2.41, full-sample 95%CI: 0.58, 4.24; p_permutation = 0.04). Performance testing in simulated data showed that WQS_permutation had improved power over WQS_Split (90% versus 56%) and a lower type I error rate than WQS_Nosplit (7% versus 47%).

Conclusions

In the largest study of these relationships to date, we observed predominantly null associations between mixtures of prenatal phthalates and both language and IQ. Our novel extension of WQS regression improved sensitivity to detect true associations by obviating the need to split the data into training and test sets and should be considered for future analyses of exposure mixtures.

A growing body of literature suggests that developmental exposure to individual or mixtures of environmental chemicals (ECs) is associated with autism spectrum disorder (ASD). However, investigating the effect of interactions among these ECs can be challenging. We introduced a combination of the classical exposure-mixture Weighted Quantile Sum (WQS) regression and a machine-learning method termed Signed iterative Random Forest (SiRF) to discover synergistic interactions between ECs that are (1) associated with higher odds of ASD diagnosis, (2) mimic toxicological interactions, and (3) are present only in a subset of the sample whose chemical concentrations are higher than certain thresholds. In a case-control Childhood Autism Risks from Genetics and Environment (CHARGE) study, we evaluated multiordered synergistic interactions among 62 ECs measured in the urine samples of 479 children in association with increased odds for ASD diagnosis (yes vs no). WQS-SiRF identified two synergistic two-ordered interactions between (1) trace-element cadmium (Cd) and the organophosphate pesticide metabolite diethyl-phosphate (DEP); and (2) 2,4,6-trichlorophenol (TCP-246) and DEP. Both interactions were suggestively associated with increased odds of ASD diagnosis in the subset of children with urinary concentrations of Cd, DEP, and TCP-246 above the 75th percentile. This study demonstrates a novel method that combines the inferential power of WQS and the predictive accuracy of machine-learning algorithms to discover potentially biologically relevant chemical-chemical interactions associated with ASD.

Background

A growing body of literature investigated childhood exposure to environmental chemicals in association with attention-deficit/hyperactivity disorder (ADHD) symptoms, but limited studies considered urinary mixtures of multiple chemical classes. This study examined associations of concurrent exposure to non-persistent chemicals with ADHD symptoms in children diagnosed with autism spectrum disorder (ASD), developmental delay (DD), and typical development (TD).

Methods

A total of 549 children aged 2-5 years from the Childhood Autism Risks from Genetics and Environment (CHARGE) case-control study were administered the Aberrant Behavior Checklist (ABC). This study focused on the ADHD/noncompliance subscale and its two subdomains (hyperactivity/impulsivity, inattention). Sixty-two chemicals from four classes (phenols/parabens, phthalates, organophosphate pesticides, trace elements) were quantified in child urine samples, and 43 chemicals detected in > 70% samples were used to investigate their associations with ADHD symptoms. Negative binomial regression was used for single-chemical analysis, and weighted quantile sum regression with repeated holdout validation was applied for mixture analysis for each chemical class and all chemicals. The mixture analyses were further stratified by diagnostic group.

Results

A phthalate metabolite mixture was associated with higher ADHD/noncompliance scores (median count ratio [CR] = 1.10; 2.5th, 97.5th percentile: 1.00, 1.21), especially hyperactivity/impulsivity (median CR = 1.09; 2.5th, 97.5th percentile: 1.00, 1.25). The possible contributors to these mixture effects were di-2-ethylhexyl phthalate (DEHP) metabolites and mono-2-heptyl phthalate (MHPP). These associations were likely driven by children with ASD as these were observed among children with ASD, but not among TD or those with DD. Additionally, among children with ASD, a mixture of all chemicals was associated with ADHD/noncompliance and hyperactivity/impulsivity, and possible contributors were 3,4-dihydroxy benzoic acid, DEHP metabolites, MHPP, mono-n-butyl phthalate, and cadmium.

Conclusions

Early childhood exposure to a phthalate mixture was associated with ADHD symptoms, particularly among children with ASD. While the diverse diagnostic profiles limited generalizability, our findings suggest a potential link between phthalate exposure and the comorbidity of ASD and ADHD.

Background

The National Institutes of Health's Environmental influences on Child Health Outcomes (ECHO) initiative aims to understand the impact of environmental factors on childhood disease. Over 40,000 chemicals are approved for commercial use. The challenge is to prioritize chemicals for biomonitoring that may present health risk concerns.

Objectives

Our aim was to prioritize chemicals that may elicit child health effects of interest to ECHO but that have not been biomonitored nationwide and to identify gaps needing additional research.

Methods

We searched databases and the literature for chemicals in environmental media and in consumer products that were potentially toxic. We selected chemicals that were not measured in the National Health and Nutrition Examination Survey. From over 700 chemicals, we chose 155 chemicals and created eight chemical panels. For each chemical, we compiled biomonitoring and toxicity data, U.S. Environmental Protection Agency exposure predictions, and annual production usage. We also applied predictive modeling to estimate toxicity. Using these data, we recommended chemicals either for biomonitoring, to be deferred pending additional data, or as low priority for biomonitoring.

Results

For the 155 chemicals, 97 were measured in food or water, 67 in air or house dust, and 52 in biospecimens. We found in vivo endocrine, developmental, reproductive, and neurotoxic effects for 61, 74, 47, and 32 chemicals, respectively. Eighty-six had data from high-throughput in vitro assays. Positive results for endocrine, developmental, neurotoxicity, and obesity were observed for 32, 11, 35, and 60 chemicals, respectively. Predictive modeling results suggested 90% are toxicants. Biomarkers were reported for 76 chemicals. Thirty-six were recommended for biomonitoring, 108 deferred pending additional research, and 11 as low priority for biomonitoring.

Discussion

The 108 deferred chemicals included those lacking biomonitoring methods or toxicity data, representing an opportunity for future research. Our evaluation was, in general, limited by the large number of unmeasured or untested chemicals. https://doi.org/10.1289/EHP5133.

The association between prenatal phthalate exposure and late preterm birth (LPTB) is unclear. We examined singleton pregnancies (2006-2011) from a racially and socioeconomically diverse sample of women in the CANDLE cohort of the ECHO-PATHWAYS Consortium. Urine collected in the second and third trimester was analyzed for 14 phthalate metabolites. Multivariate logistic and linear regressions were performed for LPTB, defined as delivery 34-37 weeks, and gestational week, respectively. Models were controlled for socio-demographics, behavioral factors, clinical measurements, medical history, and phthalates in the other trimester. Effect modification by race and pregnancy stress, indicated by intimate partner violence (IPV), was investigated. We conducted a secondary analysis in women with spontaneous preterm labor. The rate of LPTB among 1408 women (61% Black, 32% White) was 6.7%. There was no evidence of decreased gestational age (GA) in association with any phthalate metabolite. Each two-fold increase in third trimester mono-benzyl phthalate (MBzP) was associated with 0.08 weeks longer gestational age (95% CI: 0.03, 0.12). When restricting to women with spontaneous labor, second trimester mono-n-butyl phthalate (MBP) was associated with 54% higher odds (95% CI: 2%, 132%) of LPTB. Associations were not modified by maternal race or IPV exposure. In conclusion, we observed mixed evidence concerning our hypothesis that prenatal phthalate exposure increases risk of LPTB, though secondary analyses suggest increased risk of spontaneous LPTB associated with MBP, which is consistent with a recent pooled analysis of 16 cohorts.

Background

Per- and polyfluoroalkyl substances (PFAS) are persistent synthetic chemicals and are commonly found in everyday items. PFAS have been linked to disrupting glucose homeostasis, however, whether they are associated with gestational diabetes mellitus (GDM) risk remains inconclusive. We examined prospective associations of PFAS concentrations measured twice in pregnancy with GDM risk.

Methods

In the PETALS pregnancy cohort, a nested case-control study which included 41 GDM cases and 87 controls was conducted. PFAS analytes were measured in blood serum collected in both early and mid-pregnancy (mean [SD]: 13.9 [2.2] and 20.2 [2.2] gestational weeks, respectively), with cumulative exposure calculated by the area-under-the-curve (AUC) to integrate both the PFAS concentration and the timing of the exposure. Individual adjusted weighted unconditional logistic regression models examined seven PFAS in association with GDM risk. P-values were corrected using the false-discovery-rate (FDR). Mixture models were analyzed with Bayesian kernel machine regression (BKMR).

Results

PFDA, PFNA and PFOA were individually associated with higher GDM risk per interquartile range (IQR) in early pregnancy (OR [95% CI]: 1.23 [1.09, 1.38]), 1.40 [1.24, 1.58]), and 1.15 [1.04, 1.27], respectively), mid-pregnancy (1.28 [1.15, 1.43], 1.16 [1.05, 1.28], and 1.20 [1.09, 1.33], respectively), and with cumulative exposure (1.23 [1.09, 1.38], 1.21 [1.07, 1.37], and 1.19 [1.09, 1.31], respectively). PFOS in mid-pregnancy and with cumulative exposure was associated with increased GDM risk (1.41 [1.17, 1.71] and 1.33 [1.06, 1.58], respectively). PFUnDA in early pregnancy was associated with lower GDM risk (0.79 [0.64, 0.98]), whereas mid-pregnancy levels were associated with higher risk (1.49 [1.18, 1.89]). PFHxS was associated with decreased GDM risk in early and mid-pregnancy (0.48 [0.38, 0.60] and 0.48 [0.37, 0.63], respectively) and with cumulative exposure (0.49 [0.38,0.63]). PFPeA was not associated with GDM. Similar conclusions were observed in BKMR models; however, overall associations in these models were not statistically significant.

Conclusions

Higher risk of GDM was consistently observed in association with PFDA, PFNA, and PFOA exposure in both early and mid-pregnancy. Results should be corroborated in larger population-based cohorts and individuals of reproductive age should potentially avoid known sources of PFAS.