Prenatal exposure to per- and polyfluoroalkyl substances and early childhood adiposity and cardiometabolic health in the Healthy Start study.

BACKGROUND/OBJECTIVES: Observational and experimental studies have suggested that prenatal exposure to per- and polyfluoroalkyl substances (PFAS) can increase childhood adiposity and cardiometabolic disruption. However, most previous studies have used weight-based measures that cannot distinguish between fat mass and lean mass. We evaluated associations of prenatal PFAS exposure with precisely measured body composition and cardiometabolic biomarkers in early childhood. SUBJECTS: 373 eligible mother-infant pairs in the Healthy Start longitudinal cohort. METHODS: We used multiple linear regression and Bayesian kernel machine regression models to estimate associations between five PFAS in maternal mid-pregnancy serum, and early childhood adiposity via air displacement plethysmography. Secondary outcomes included body mass index, waist circumference, and fasting serum lipids, glucose, insulin and adipokines. Models were adjusted for potential confounders and effect modification by child sex was evaluated. RESULTS: The median age of children at assessment was 4.6 years. Prenatal concentration of perfluorooctanoate (PFOA) was positively associated with percent fat mass (0.89% per log2-unit increase, 95% CI: 0.15, 1.64), while perfluorononanoate (PFNA) was positively associated with fat mass index and body mass index. Cardiometabolic markers in blood were generally not associated with prenatal PFAS in this population. Mixture models confirmed the importance of PFNA and PFOA in predicting percent fat mass, while PFNA was most important for fat mass index, body mass index, and waist circumference. There were no significant effects of the five PFAS as a mixture, potentially due to opposing effects of different PFAS. CONCLUSIONS: Our results agree with previous studies showing that prenatal serum concentrations of certain PFAS are positively associated with early childhood adiposity. Notably, associations were stronger for measures incorporating precisely measured fat mass compared to measures of body size or weight. Early life increases in adiposity may precede the development of adverse cardiometabolic health outcomes in children exposed to PFAS during gestation.

Maternal educational attainment in pregnancy and epigenome-wide DNA methylation changes in the offspring from birth until adolescence.

Maternal educational attainment (MEA) shapes offspring health through multiple potential pathways. Differential DNA methylation may provide a mechanistic understanding of these long-term associations. We aimed to quantify the associations of MEA with offspring DNA methylation levels at birth, in childhood and in adolescence. Using 37 studies from high-income countries, we performed meta-analysis of epigenome-wide association studies (EWAS) to quantify the associations of completed years of MEA at the time of pregnancy with offspring DNA methylation levels at birth (n = 9 881), in childhood (n = 2 017), and adolescence (n = 2 740), adjusting for relevant covariates. MEA was found to be associated with DNA methylation at 473 cytosine-phosphate-guanine sites at birth, one in childhood, and four in adolescence. We observed enrichment for findings from previous EWAS on maternal folate, vitamin-B12 concentrations, maternal smoking, and pre-pregnancy BMI. The associations were directionally consistent with MEA being inversely associated with behaviours including smoking and BMI. Our findings form a bridge between socio-economic factors and biology and highlight potential pathways underlying effects of maternal education. The results broaden our understanding of bio-social associations linked to differential DNA methylation in multiple early stages of life. The data generated also offers an important resource to help a more precise understanding of the social determinants of health.

Associations of urinary biomarkers of phthalates, phenols, parabens, and organophosphate esters with glycemic traits in pregnancy: The Healthy Start Study.

BACKGROUND: Certain endocrine-disrupting chemicals (EDCs) are widespread in consumer products and may alter glucose metabolism. However, the impact of EDC exposures on glucose and insulin regulation during pregnancy is incompletely understood, despite potential adverse consequences for maternal and infant health. We estimated associations between 37 urinary biomarkers of EDCs and glucose-insulin traits among pregnant women. METHODS: Seventeen phthalate or phthalate substitute metabolites, six environmental phenols, four parabens, and ten organophosphate ester metabolites were quantified in mid-pregnancy urine from 298 participants in the Healthy Start Study. Fasting blood glucose, insulin, and hemoglobin A1c were assessed concurrently, and Homeostasis Model Assessment 2-Insulin Resistance (HOMA2-IR) was calculated. Gestational diabetes diagnoses and screening results were obtained from medical records for a subset of participants. We estimated associations between each EDC and outcome separately using linear and robust Poisson regression models and analyzed EDC mixture effects. RESULTS: The EDC mixture was positively associated with glucose, insulin, and HOMA2-IR, although overall associations were attenuated after adjustment for maternal BMI. Two mixture approaches identified di(2-ethylhexyl) phthalate (DEHP) metabolites as top contributors to the mixture's positive associations. In single-pollutant models, DEHP metabolites were positively associated with fasting glucose, fasting insulin, and HOMA2-IR even after adjustment for maternal BMI. For example, each interquartile range increase in log2-transformed mono(2-ethyl-5-oxohexyl) phthalate was associated with 2.4 mg/dL (95% confidence interval (CI): 1.1, 3.6) higher fasting glucose, 11.8% (95%CI: 3.6, 20.5) higher fasting insulin, and 12.3% (95%CI: 4.2, 21.1) higher HOMA2-IR. Few EDCs were associated with hemoglobin A1c or with a combined outcome of impaired glucose tolerance or gestational diabetes. DISCUSSION: Exposures to phthalates and particularly DEHP during pregnancy are associated with altered glucose-insulin regulation. Disruptions in maternal glucose metabolism during pregnancy may contribute to adverse pregnancy outcomes including gestational diabetes and fetal macrosomia, and associated long-term consequences for maternal and child health.

Urinary metabolite concentrations of phthalate and plasticizers in infancy and childhood in the UNC baby connectome project.

INTRODUCTION: Existing evidence suggests that exposure to phthalates is higher among younger age groups. However, limited knowledge exists on how phthalate exposure, as well as exposure to replacement plasticizers, di(isononyl) cyclohexane-1,2-dicarboxylate (DINCH) and di-2-ethylhexyl terephthalate (DEHTP), change from infancy through early childhood. METHODS: Urine samples were collected across the first 5 years of life from typically developing infants and young children enrolled between 2017 and 2020 in the longitudinal UNC Baby Connectome Project. From 438 urine samples among 187 participants, we quantified concentrations of monobutyl phthalate (MnBP), mono-3-carboxypropyl phthalate (MCPP), monoisobutyl phthalate (MiBP), monoethyl phthalate (MEP), monobenzyl phthalate (MBzP), and metabolites of di(2-ethylhexyl) phthalate (DEHP), diisonoyl phthalate (DiNP), DINCH and DEHTP. Specific gravity (SG) adjusted metabolite and molar sum concentrations were compared across age groups. Intraclass correlation coefficients (ICCs) were calculated among 122 participants with multiple urine specimens (373 samples). RESULTS: Most phthalate metabolites showed high detection frequencies (>80% of samples). Replacement plasticizers DINCH (58-60%) and DEHTP (>97%) were also commonly found. DiNP metabolites were less frequently detected (<10%). For some metabolites, SG-adjusted concentrations were inversely associated with age, with the highest concentrations found in the first year of life. ICCs revealed low to moderate reliability in metabolite measurements (ρ = 0.10-0.48) suggesting a high degree of within-individual variation in exposure among this age group. The first 6 months (compared to remaining age groups) showed an increased ratio of carboxylated metabolites of DEHP and DEHTP, compared to other common metabolites, but no clear age trends for DINCH metabolite ratios were observed. CONCLUSION: Metabolites of phthalates and replacements plasticizers were widely detected in infancy and early childhood, with the highest concentrations observed in the first year of life for several metabolites. Higher proportions of carboxylated metabolites of DEHP and DEHTP in younger age groups indicate potential differences in metabolism during infancy.

Maternal Diet Quality During Pregnancy and Offspring Hepatic Fat in Early Childhood: The Healthy Start Study.

BACKGROUND: Overnutrition in utero may increase offspring risk of nonalcoholic fatty liver disease (NAFLD), but the specific contribution of maternal diet quality during pregnancy to this association remains understudied in humans. OBJECTIVES: This study aimed to examine the associations of maternal diet quality during pregnancy with offspring hepatic fat in early childhood (median: 5 y old, range: 4-8 y old). METHODS: Data were from 278 mother-child pairs in the longitudinal, Colorado-based Healthy Start Study. Multiple 24-h recalls were collected from mothers during pregnancy on a monthly basis (median: 3 recalls, range: 1-8 recalls starting after enrollment), and used to estimate maternal usual nutrient intakes and dietary pattern scores [Healthy Eating Index-2010 (HEI-2010), Dietary Inflammatory Index (DII), and Relative Mediterranean Diet Score (rMED)]. Offspring hepatic fat was measured in early childhood by MRI. Associations of maternal dietary predictors during pregnancy with offspring log-transformed hepatic fat were assessed using linear regression models adjusted for offspring demographics, maternal/perinatal confounders, and maternal total energy intake. RESULTS: Higher maternal fiber intake and rMED scores during pregnancy were associated with lower offspring hepatic fat in early childhood in fully adjusted models [Back-transformed ß (95% CI): 0.82 (0.72, 0.94) per 5 g/1000 kcal fiber; 0.93 (0.88, 0.99) per 1 SD for rMED]. In contrast, higher maternal total sugar and added sugar intakes, and DII scores were associated with higher offspring hepatic fat [Back-transformed ß (95% CI): 1.18 (1.05, 1.32) per 5% kcal/d added sugar; 1.08 (0.99, 1.18) per 1 SD for DII]. Analyses of dietary pattern subcomponents also revealed that lower maternal intakes of green vegetables and legumes and higher intake of "empty calories" were associated with higher offspring hepatic fat in early childhood. CONCLUSIONS: Poorer maternal diet quality during pregnancy was associated with greater offspring susceptibility to hepatic fat in early childhood. Our findings provide insights into potential perinatal targets for the primordial prevention of pediatric NAFLD.

Power and sample size analysis for longitudinal mixed models of health in populations exposed to environmental contaminants: a tutorial.

BACKGROUND: When evaluating the impact of environmental exposures on human health, study designs often include a series of repeated measurements. The goal is to determine whether populations have different trajectories of the environmental exposure over time. Power analyses for longitudinal mixed models require multiple inputs, including clinically significant differences, standard deviations, and correlations of measurements. Further, methods for power analyses of longitudinal mixed models are complex and often challenging for the non-statistician. We discuss methods for extracting clinically relevant inputs from literature, and explain how to conduct a power analysis that appropriately accounts for longitudinal repeated measures. Finally, we provide careful recommendations for describing complex power analyses in a concise and clear manner. METHODS: For longitudinal studies of health outcomes from environmental exposures, we show how to [1] conduct a power analysis that aligns with the planned mixed model data analysis, [2] gather the inputs required for the power analysis, and [3] conduct repeated measures power analysis with a highly-cited, validated, free, point-and-click, web-based, open source software platform which was developed specifically for scientists. RESULTS: As an example, we describe the power analysis for a proposed study of repeated measures of per- and polyfluoroalkyl substances (PFAS) in human blood. We show how to align data analysis and power analysis plan to account for within-participant correlation across repeated measures. We illustrate how to perform a literature review to find inputs for the power analysis. We emphasize the need to examine the sensitivity of the power values by considering standard deviations and differences in means that are smaller and larger than the speculated, literature-based values. Finally, we provide an example power calculation and a summary checklist for describing power and sample size analysis. CONCLUSIONS: This paper provides a detailed roadmap for conducting and describing power analyses for longitudinal studies of environmental exposures. It provides a template and checklist for those seeking to write power analyses for grant applications.

Neighborhood Walkability, Historical Redlining, and Childhood Obesity in Denver, Colorado.

Childhood obesity is a precursor to future health complications. In adults, neighborhood walkability is inversely associated with obesity prevalence. Recently, it has been shown that current urban walkability has been influenced by historical discriminatory neighborhood disinvestment. However, the relationship between this systemic racism and obesity has not been extensively studied. The objective of this study was to evaluate the association of neighborhood walkability and redlining, a historical practice of denying home loans to communities of color, with childhood obesity. We evaluated neighborhood walkability and walkable destinations for 250 participants of the Healthy Start cohort, based in the Denver metropolitan region. Eligible participants attended an examination between ages 4 and 8. Walkable destinations and redlining geolocations were determined based on residential addresses, and a weighting system for destination types was developed. Sidewalks and trails in Denver were included in the network analyst tool in ArcMap to calculate the precise walkable environment for each child. We implemented linear regression models to estimate associations between neighborhood characteristics and child body mass index (BMI) z-scores and fat mass percent. There was a significant association between child BMI and redlining (ß: 1.36, 95% CI: 0.106, 2.620). We did not find an association between walkability measures and childhood obesity outcomes. We propose that cities such as Denver pursue built environment policies, such as inclusionary zoning and direct investments in neighborhoods that have been historically neglected, to reduce the childhood health impacts of segregated poverty, and suggest further studies on the influences that redlining and urban built environment factors have on childhood obesity.

Early-life exposure to residential black carbon and childhood cardiometabolic health.

BACKGROUND: Early life exposure to air pollution, such as particulate matter ≤2.5 µm (PM2.5), may be associated with obesity and adverse cardiometabolic health outcomes in childhood. However, the toxicity of PM2.5 varies according to its chemical composition. Black carbon (BC) is a constituent of PM2.5, but few studies have examined its impact on childhood cardiometabolic health. Therefore, we examined relationships between prenatal and early childhood exposure to BC and markers of adiposity and cardiometabolic health in early childhood. METHODS: This study included 578 mother-child pairs enrolled in the Healthy Start study (2009-2014) living in the Denver-metro area. Using a spatiotemporal prediction model, we assessed average residential black carbon levels during pregnancy and in the year prior to the early childhood follow-up visit at approximately 5 years old. We estimated associations between prenatal and early childhood BC and indicators of adiposity and cardiometabolic biomarkers in early childhood (mean 4.8 years; range, 4.0, 8.3), using linear regression. RESULTS: We found higher early childhood BC was associated with higher percent fat mass, fat mass index, insulin, and homeostatic model assessment for insulin resistance (HOMA-IR), and lower leptin and waist circumference at approximately 5 years old, after adjusting for covariates. For example, per interquartile range (IQR) increase in early childhood BC (IQR, 0.49 µg/m3) there was 3.32% higher fat mass (95% CI; 2.05, 4.49). Generally, we did not find consistent evidence of associations between prenatal BC and cardiometabolic health outcomes in early childhood, except for an inverse association between prenatal BC and adiponectin, an adipocyte-secreted hormone typically inversely associated with adiposity. CONCLUSIONS: Higher early childhood, but not in utero, ambient concentrations of black carbon, a component of air pollution, were associated with greater adiposity and altered insulin homeostasis at approximately 5 years old. Future studies should examine whether these changes persist later in life.

Prenatal exposures to per- and polyfluoroalkyl substances and epigenetic aging in umbilical cord blood: The Healthy Start study.

BACKGROUND: Per- and polyfluoroalkyl substances (PFAS) are ubiquitous, environmentally persistent chemicals, and prenatal exposures have been associated with adverse child health outcomes. Prenatal PFAS exposure may lead to epigenetic age acceleration (EAA), defined as the discrepancy between an individual's chronologic and epigenetic or biological age. OBJECTIVES: We estimated associations of maternal serum PFAS concentrations with EAA in umbilical cord blood DNA methylation using linear regression, and a multivariable exposure-response function of the PFAS mixture using Bayesian kernel machine regression. METHODS: Five PFAS were quantified in maternal serum (median: 27 weeks of gestation) among 577 mother-infant dyads from a prospective cohort. Cord blood DNA methylation data were assessed with the Illumina HumanMethylation450 array. EAA was calculated as the residuals from regressing gestational age on epigenetic age, calculated using a cord-blood specific epigenetic clock. Linear regression tested for associations between each maternal PFAS concentration with EAA. Bayesian kernel machine regression with hierarchical selection estimated an exposure-response function for the PFAS mixture. RESULTS: In single pollutant models we observed an inverse relationship between perfluorodecanoate (PFDA) and EAA (-0.148 weeks per log-unit increase, 95% CI: -0.283, -0.013). Mixture analysis with hierarchical selection between perfluoroalkyl carboxylates and sulfonates indicated the carboxylates had the highest group posterior inclusion probability (PIP), or relative importance. Within this group, PFDA had the highest conditional PIP. Univariate predictor-response functions indicated PFDA and perfluorononanoate were inversely associated with EAA, while perfluorohexane sulfonate had a positive association with EAA. CONCLUSIONS: Maternal mid-pregnancy serum concentrations of PFDA were negatively associated with EAA in cord blood, suggesting a pathway by which prenatal PFAS exposures may affect infant development. No significant associations were observed with other PFAS. Mixture models suggested opposite directions of association between perfluoroalkyl sulfonates and carboxylates. Future studies are needed to determine the importance of neonatal EAA for later child health outcomes.

Prenatal exposure to poly- and perfluoroalkyl substances and the incidence of asthma in early childhood.

EXPOSURE TO POLY: and perfluoroalkyl substances (PFAS) in early life may increase the risk of childhood asthma, but evidence has been inconsistent. We estimated associations between maternal serum concentrations of PFAS during pregnancy and clinician-diagnosed asthma incidence in offspring through age eight. We included 597 mother-child pairs with PFAS quantified in mid-pregnancy serum and childhood medical records reviewed for asthma diagnoses. We used separate Cox proportional hazards models to assess the relationship between log-transformed concentrations of five PFAS and the incidence of asthma. We estimated associations between the PFAS mixture and clinician-diagnosed asthma incidence using quantile-based g-computation. PFAS concentrations were similar to those among females in the US general population. Seventeen percent of children (N = 104) were diagnosed with asthma during follow-up. Median (interquartile range) duration of follow-up was 4.7 (4.0, 6.2) years, and median age at asthma diagnosis was 1.7 (0.9, 2.8) years. All adjusted hazard ratios (HRs) were elevated, but all 95% confidence intervals (CI) included the null. The HR (95% CI) of asthma for a one-quartile increase in the PFAS mixture was 1.17 (0.86, 1.61). In this cohort of children followed to eight years of age, prenatal PFAS concentrations were not significantly associated with incidence of clinician-diagnosed asthma.

An epigenome-wide association study of child appetitive traits and DNA methylation.

The etiology of childhood appetitive traits is poorly understood. Early-life epigenetic processes may be involved in the developmental programming of appetite regulation in childhood. One such process is DNA methylation (DNAm), whereby a methyl group is added to a specific part of DNA, where a cytosine base is next to a guanine base, a CpG site. We meta-analyzed epigenome-wide association studies (EWASs) of cord blood DNAm and early-childhood appetitive traits. Data were from two independent cohorts: the Generation R Study (n = 1,086, Rotterdam, the Netherlands) and the Healthy Start study (n = 236, Colorado, USA). DNAm at autosomal methylation sites in cord blood was measured using the Illumina Infinium HumanMethylation450 BeadChip. Parents reported on their child's food responsiveness, emotional undereating, satiety responsiveness and food fussiness using the Children's Eating Behaviour Questionnaire at age 4-5 years. Multiple regression models were used to examine the association of DNAm (predictor) at the individual site- and regional-level (using DMRff) with each appetitive trait (outcome), adjusting for covariates. Bonferroni-correction was applied to adjust for multiple testing. There were no associations of DNAm and any appetitive trait when examining individual CpG-sites. However, when examining multiple CpGs jointly in so-called differentially methylated regions, we identified 45 associations of DNAm with food responsiveness, 7 associations of DNAm with emotional undereating, 13 associations of DNAm with satiety responsiveness, and 9 associations of DNAm with food fussiness. This study shows that DNAm in the newborn may partially explain variation in appetitive traits expressed in early childhood and provides preliminary support for early programming of child appetitive traits through DNAm. Investigating differential DNAm associated with appetitive traits could be an important first step in identifying biological pathways underlying the development of these behaviors.

Prenatal exposure to ambient air pollution and traffic and indicators of adiposity in early childhood: the Healthy Start study.

BACKGROUND: Prenatal exposure to ambient air pollution and traffic have been related to a lower birth weight and may be associated with greater adiposity in childhood. We aimed to examine associations of maternal exposure to ambient air pollution and traffic during pregnancy with indicators of adiposity in early childhood. METHODS: We included 738 participants of the Colorado-based Healthy Start study whose height, weight, waist circumference and/or fat mass were measured at age 4-6 years. We estimated residential exposure to ambient concentrations of fine particulate matter (PM2.5) and ozone (O3) averaged by trimester and throughout pregnancy via inverse distance-weighted interpolation of central site monitoring data. We assessed the distance to the nearest major roadway and traffic density in multiple buffers surrounding the participants' homes. Associations of prenatal exposure to air pollution and traffic with overweight, waist circumference, percent fat mass and fat mass index (FMI) were assessed by logistic and linear regression. RESULTS: Associations of exposure to PM2.5 and O3 at the residential address during pregnancy with percent fat mass and FMI at age 4-6 years were inconsistent across trimesters. For example, second trimester PM2.5 was associated with a higher percent fat mass (adjusted difference 0.70% [95% CI 0.05, 1.35%] per interquartile range (IQR; 1.3 µg/m3) increase), while third trimester PM2.5 was associated with a lower percent fat mass (adjusted difference -1.17% [95% CI -1.84, -0.50%] per IQR (1.3 µg/m3) increase). Residential proximity to a highway during pregnancy was associated with higher odds of being overweight at age 4-6 years. We observed no associations of prenatal exposure to PM2.5 and O3 with overweight and waist circumference. CONCLUSIONS: We found limited evidence of associations of prenatal exposure to ambient PM2.5 and O3 with indicators of adiposity at age 4-6 years. Suggestive relationships between residential proximity to a highway during pregnancy and greater adiposity merit further investigation.

Ambient air pollution during pregnancy and DNA methylation in umbilical cord blood, with potential mediation of associations with infant adiposity: The Healthy Start study.

BACKGROUND: Prenatal exposure to ambient air pollution has been associated with adverse offspring health outcomes. Childhood health effects of prenatal exposures may be mediated through changes to DNA methylation detectable at birth. METHODS: Among 429 non-smoking women in a cohort study of mother-infant pairs in Colorado, USA, we estimated associations between prenatal exposure to ambient fine particulate matter (PM2.5) and ozone (O3), and epigenome-wide DNA methylation of umbilical cord blood cells at delivery (2010-2014). We calculated average PM2.5 and O3 in each trimester of pregnancy and the full pregnancy using inverse-distance-weighted interpolation. We fit linear regression models adjusted for potential confounders and cell proportions to estimate associations between air pollutants and methylation at each of 432,943 CpGs. Differentially methylated regions (DMRs) were identified using comb-p. Previously in this cohort, we reported positive associations between 3rd trimester O3 exposure and infant adiposity at 5 months of age. Here, we quantified the potential for mediation of that association by changes in DNA methylation in cord blood. RESULTS: We identified several DMRs for each pollutant and period of pregnancy. The greatest number of significant DMRs were associated with third trimester PM2.5 (21 DMRs). No single CpGs were associated with air pollutants at a false discovery rate <0.05. We found that up to 8% of the effect of 3rd trimester O3 on 5-month adiposity may be mediated by locus-specific methylation changes, but mediation estimates were not statistically significant. CONCLUSIONS: Differentially methylated regions in cord blood were identified in association with maternal exposure to PM2.5 and O3. Genes annotated to the significant sites played roles in cardiometabolic disease, immune function and inflammation, and neurologic disorders. We found limited evidence of mediation by DNA methylation of associations between third trimester O3 exposure and 5-month infant adiposity.

Using non-parametric Bayes shrinkage to assess relationships between multiple environmental and social stressors and neonatal size and body composition in the Healthy Start cohort.

BACKGROUND: Both environmental and social factors have been linked to birth weight and adiposity at birth, but few studies consider the effects of exposure mixtures. Our objective was to identify which components of a mixture of neighborhood-level environmental and social exposures were driving associations with birth weight and adiposity at birth in the Healthy Start cohort. METHODS: Exposures were assessed at the census tract level and included air pollution, built environment characteristics, and socioeconomic status. Prenatal exposures were assigned based on address at enrollment. Birth weight was measured at delivery and adiposity was measured using air displacement plethysmography within three days. We used non-parametric Bayes shrinkage (NPB) to identify exposures that were associated with our outcomes of interest. NPB models were compared to single-predictor linear regression. We also included generalized additive models (GAM) to assess nonlinear relationships. All regression models were adjusted for individual-level covariates, including maternal age, pre-pregnancy BMI, and smoking. RESULTS: Results from NPB models showed most exposures were negatively associated with birth weight, though credible intervals were wide and generally contained zero. However, the NPB model identified an interaction between ozone and temperature on birth weight, and the GAM suggested potential non-linear relationships. For associations between ozone or temperature with birth weight, we observed effect modification by maternal race/ethnicity, where effects were stronger for mothers who identified as a race or ethnicity other than non-Hispanic White. No associations with adiposity at birth were observed. CONCLUSIONS: NPB identified prenatal exposures to ozone and temperature as predictors of birth weight, and mothers who identify as a race or ethnicity other than non-Hispanic White might be disproportionately impacted. However, NPB models may have limited applicability when non-linear effects are present. Future work should consider a two-stage approach where NPB is used to reduce dimensionality and alternative approaches examine non-linear effects.

Unsaturated PFOS and Other PFASs in Human Serum and Drinking Water from an AFFF-Impacted Community.

Understanding how exposure to aqueous film-forming foam (AFFF)-impacted drinking water translates to bioaccumulation of per- and polyfluoroalkyl substances (PFASs) is essential to assess health risks. To investigate spatial variability of PFAS exposure in communities near an AFFF source zone, blood serum was collected in 2018 from 220 adult residents of El Paso County (Colorado), as were raw water samples from several wells. C6 and C8 perfluoroalkyl sulfonates (PFSAs) were predominant in serum and water. PFASs were most elevated in the water district nearest the source zone (median ∑PFSA of 618 ng/L in water and 33 ng/mL in serum). A novel PFAS, unsaturated perfluorooctane sulfonate, was detected in >80% of water and serum samples at low concentrations (≤1.9 ng/mL in serum). Drinking water wells nearest the source zone displayed increased prevalence of perfluoroalkyl sulfonamide precursors not detected in serum. Serum-to-water ratios were the greatest for long-chain PFASs and were elevated in the least impacted water district. Additional serum samples collected from a subset of study participants in June 2019 showed that PFAS concentrations in serum declined after exposure ceased, although declines for perfluoropentane sulfonate were minimal. Our findings demonstrate that AFFF-impacted communities are exposed to complex, spatially variable mixtures of PFASs.

A Spatiotemporal Prediction Model for Black Carbon in the Denver Metropolitan Area, 2009-2020.

Studies on health effects of air pollution from local sources require exposure assessments that capture spatial and temporal trends. To facilitate intraurban studies in Denver, Colorado, we developed a spatiotemporal prediction model for black carbon (BC). To inform our model, we collected more than 700 weekly BC samples using personal air samplers from 2018 to 2020. The model incorporated spatial and spatiotemporal predictors and smoothed time trends to generate point-level weekly predictions of BC concentrations for the years 2009-2020. Our results indicate that our model reliably predicted weekly BC concentrations across the region during the year in which we collected data. We achieved a 10-fold cross-validation R2 of 0.83 and a root-mean-square error of 0.15 µg/m3 for weekly BC concentrations predicted at our sampling locations. Predicted concentrations displayed expected temporal trends, with the highest concentrations predicted during winter months. Thus, our prediction model improves on typical land use regression models that generally only capture spatial gradients. However, our model is limited by a lack of long-term BC monitoring data for full validation of historical predictions. BC predictions from the weekly spatiotemporal model will be used in traffic-related air pollution exposure-disease associations more precisely than previous models for the region have allowed.

Exposure to ambient air pollution during pregnancy and inflammatory biomarkers in maternal and umbilical cord blood: The Healthy Start study.

BACKGROUND: Air pollution exposure during pregnancy has been associated with adverse pregnancy and birth outcomes. Inflammation has been proposed as a potential link. We estimated associations between air pollution exposure during pregnancy and inflammatory biomarkers in maternal and cord blood. We evaluated whether maternal inflammation was associated with infant outcomes. METHODS: Among 515 mother-infant dyads in the Healthy Start study (2009-2014), trimester-long, 7- and 30-day average concentrations of particulate matter ≤2.5 µm (PM2.5) and ozone (O3) during pregnancy were estimated, using inverse-distance-weighted interpolation. Inflammatory biomarkers were measured in maternal blood in mid-pregnancy (C-reactive protein [CRP], Interleukin [IL]-6, and tumor necrosis factor-α [TNFα]) and in cord blood at delivery (CRP, IL-6, IL-8, IL-10, monocyte chemoattractant protein-1 [MCP-1], and TNFα). We used linear regression to estimate associations between pollutants and inflammatory biomarkers and maternal inflammatory biomarkers and infant weight and body composition. RESULTS: There were positive associations between PM2.5 during certain exposure periods and maternal IL-6 and TNFα. There were negative associations between recent O3 and maternal CRP, IL-6, and TNFα and positive associations between trimester-long O3 exposure and maternal inflammatory biomarkers, though some 95% confidence intervals included the null. Patterns were inconsistent for associations between PM2.5 and O3 and cord blood inflammatory biomarkers. No consistent associations between maternal inflammatory biomarkers and infant outcomes were identified. CONCLUSIONS: Air pollution exposure during pregnancy may impact maternal inflammation. Further investigations should examine the health consequences for women and infants of elevated inflammatory biomarkers associated with air pollution exposure during pregnancy.

Prenatal Exposure to Tobacco and Offspring Neurocognitive Development in the Healthy Start Study.

OBJECTIVE: To explore the associations between prenatal exposure to tobacco and neurocognitive development, in the absence of prematurity or low birth weight. STUDY DESIGN: We followed mother-child pairs within Healthy Start through 6 years of age. Children were born at ≥37 weeks of gestation with a birth weight of ≥2500 g. Parents completed the Third Edition Ages and Stages Questionnaire (n = 246) and children completed a subset of the National Institutes of Health Toolbox Cognition Battery (n = 200). The Ages and Stages Questionnaire domains were dichotomized as fail/monitor and pass. Maternal urinary cotinine was measured at approximately 27 weeks of gestation. Separate logistic regression models estimated associations between prenatal exposure to tobacco (cotinine below vs above the limit of detection) and the Ages and Stages Questionnaire domains. Separate linear regression models estimated associations between prenatal exposure to tobacco and fully corrected T-scores for inhibitory control, cognitive flexibility, and receptive language, as assessed by the National Institutes of Health Toolbox. A priori covariates included sex, maternal age, maternal education, daily caloric intake during pregnancy, race/ethnicity, household income, maternal psychiatric disorders, and, in secondary models, postnatal exposure to tobacco. RESULTS: Compared with unexposed offspring, exposed offspring were more likely to receive a fail/monitor score for fine motor skills (OR, 3.9; 95% CI, 1.5-10.3) and decreased inhibitory control (B: -3.0; 95% CI, -6.1 to -0.7). After adjusting for postnatal exposure, only the association with fine motor skills persisted. CONCLUSIONS: Prenatal and postnatal exposures to tobacco may influence neurocognitive development, in the absence of preterm delivery or low birth weight. Increased developmental screening may be warranted for exposed children.

Prenatal exposure to traffic and ambient air pollution and infant weight and adiposity: The Healthy Start study.

BACKGROUND: Prenatal exposures to ambient air pollution and traffic have been associated with adverse birth outcomes, and may also lead to an increased risk of obesity. Obesity risk may be reflected in changes in body composition in infancy. OBJECTIVE: To estimate associations between prenatal ambient air pollution and traffic exposure, and infant weight and adiposity in a Colorado-based prospective cohort study. METHODS: Participants were 1125 mother-infant pairs with term births. Birth weight was recorded from medical records and body composition measures (fat mass, fat-free mass, and adiposity [percent fat mass]) were evaluated via air displacement plethysmography at birth (n = 951) and at ~5 months (n = 574). Maternal residential address was used to calculate distance to nearest roadway, traffic density, and ambient concentrations of fine particulate matter (PM2.5) and ozone (O3) via inverse-distance weighted interpolation of stationary monitoring data, averaged by trimester and throughout pregnancy. Adjusted linear regression models estimated associations between exposures and infant weight and body composition. RESULTS: Participants were urban residents and diverse in race/ethnicity and socioeconomic status. Average ambient air pollutant concentrations were generally low; the median, interquartile range (IQR), and range of third trimester concentrations were 7.3 µg/m3 (IQR: 1.3, range: 3.3-12.7) for PM2.5 and 46.3 ppb (IQR: 18.4, range: 21.7-63.2) for 8-h maximum O3. Overall there were few associations between traffic and air pollution exposures and infant outcomes. Third trimester O3 was associated with greater adiposity at follow-up (2.2% per IQR, 95% CI 0.1, 4.3), and with greater rates of change in fat mass (1.8 g/day, 95% CI 0.5, 3.2) and adiposity (2.1%/100 days, 95% CI 0.4, 3.7) from birth to follow-up. CONCLUSIONS: We found limited evidence of an association between prenatal traffic and ambient air pollution exposure and infant body composition. Suggestive associations between prenatal ozone exposure and early postnatal changes in body composition merit further investigation.

Longitudinal association of biomarkers of pesticide exposure with cardiovascular disease risk factors in youth with diabetes.

BACKGROUND: Cardiovascular disease (CVD) is the leading cause of death among individuals with diabetes, but little is known about the role of exposures to environmental chemicals such as pesticides in the early development of CVD risk in this population. OBJECTIVES: To describe changes over time in concentrations of pesticide biomarkers among youth with diabetes in the United States and to estimate the longitudinal association between these concentrations and established risk factors for CVD. METHODS: Pesticide biomarkers were quantified in urine and serum samples from 87 youth with diabetes participating in the multi-center SEARCH cohort study. Samples were obtained around the time of diagnosis (baseline visit, between 2006 and 2010) and, on average, 5.4 years later (follow-up visit, between 2012 and 2015). We calculated geometric mean (95% CI) pesticide biomarker concentrations. Eight CVD risk factors were measured at these two time points: body mass index (BMI) z-score, HbA1c, insulin sensitivity, fasting C-peptide (FCP), LDL cholesterol, HDL cholesterol, total cholesterol, and triglycerides. Linear regression models were used to estimate the associations between each pesticide biomarker at baseline and each CVD risk factor at follow-up, adjusting for baseline health outcome, elapsed time between baseline and follow up, sex, age, race/ethnicity, and diabetes type. RESULTS: Participants were, on average, 14.2 years old at their baseline visit, and most were diagnosed with type 1 diabetes (57.5%). 4-nitrophenol, 3-phenoxybenzoic acid, 2,4-dichlorophenoxyacetic acid (2,4-D), 3,5,6-trichloro-2-pyridinol, 2,2-bis(4-chlorophenyl)-1,1-dichloroethene, and hexachlorobenzene were detected in a majority of participants at both time points. Participants in the highest quartile of 2,4-D and 4-nitrophenol at baseline had HbA1c levels at follow-up that were 1.05 percentage points (95% CI: -0.40, 2.51) and 1.27 percentage points (0.22, 2.75) higher, respectively, than participants in the lowest quartile of these pesticide biomarkers at baseline. These participants also had lower log FCP levels (indicating reduced beta-cell function) compared to participants in the lowest quartile at baseline: beta (95% CI) for log FCP of -0.64 (-1.17, -0.11) for 2,4-D and -0.39 (-0.96, 0.18) for 4-nitrophenol. In other words, participants in the highest quartile of 2,4-D had a 47.3% lower FCP level compared to participants in the lowest quartile, and those in the highest quartile of 4-nitrophenol had a 32.3% lower FCP level than those in the lowest quartile. Participants with trans-nonachlor concentrations in the highest quartile at baseline had HbA1c levels that were 1.45 percentage points (-0.11, 3.01) higher and log FCP levels that were -0.28 (-0.84, 0.28) lower than participants in the lowest quartile at baseline, that is to say, participants in the highest quartile of trans-nonachlor had a 24.4% lower FCP level than those in the lowest quartile. While not all of these results were statistically significant, potentially due to the small same size, clinically, there appears to be quantitative differences. No associations were observed between any pesticide biomarker at baseline with BMI z-score or insulin sensitivity at follow-up. CONCLUSIONS: Exposure to select pesticides may be associated with impaired beta-cell function and poorer glycemic control among youth with diabetes.