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The appropriate use of human biomonitoring data to model population chemical exposures is challenging, especially for rapidly metabolized chemicals, such as agricultural chemicals. The objective of this study is to demonstrate a novel approach integrating model predicted dietary exposures and biomonitoring data to potentially inform regulatory risk assessments. We use lambda-cyhalothrin as a case study, and for the same representative U.S. population in the National Health and Nutrition Examination Survey (NHANES), an integrated exposure and pharmacokinetic model predicted exposures are calibrated to measurements of the urinary metabolite 3-phenoxybenzoic acid (3PBA), using an approximate Bayesian computing (ABC) methodology. We demonstrate that the correlation between modeled urinary 3PBA and the NHANES 3PBA measurements more than doubled as ABC thresholding narrowed the acceptable tolerance range for predicted versus observed urinary measurements. The median predicted urinary concentrations were closer to the median measured value using ABC than using current regulatory Monte Carlo methods.

(1) Background: American Indians are disproportionately affected by air pollution, an important risk factor for dementia. However, few studies have investigated the effects of air pollution on the risk of dementia among American Indians. (2) Methods: This retrospective cohort study included a total of 26,871 American Indians who were 55+ years old in 2007, with an average follow-up of 3.67 years. County-level average air pollution data were downloaded from land-use regression models. All-cause dementia was identified using ICD-9 diagnostic codes from the Indian Health Service’s (IHS) National Data Warehouse and related administrative databases. Cox models were employed to examine the association of air pollution with dementia incidence, adjusting for co-exposures and potential confounders. (3) Results: The average PM2.5 levels in the IHS counties were lower than those in all US counties, while the mean O3 levels in the IHS counties were higher than the US counties. Multivariable Cox regressions revealed a positive association between dementia and county-level O3 with a hazard ratio of 1.24 (95% CI: 1.02–1.50) per 1 ppb standardized O3. PM2.5 and NO2 were not associated with dementia risk after adjusting for all covariates. (4) Conclusions: O3 is associated with a higher risk of dementia among American Indians.

Animal studies have pointed at the liver as a hotspot for per- and polyfluoroalkyl substances (PFAS) accumulation and toxicity; however, these findings have not been replicated in human populations. We measured concentrations of seven PFAS in matched liver and plasma samples collected at the time of bariatric surgery from 64 adolescents in the Teen-Longitudinal Assessment of Bariatric Surgery (Teen-LABS) study. Liver:plasma concentration ratios were perfectly explained (r2 > 0.99) in a multilinear regression (MLR) model based on toxicokinetic (TK) descriptors consisting of binding to tissue constituents and membrane permeabilities. Of the seven matched plasma and liver PFAS concentrations compared in this study, the liver:plasma concentration ratio of perfluoroheptanoic acid (PFHpA) was considerably higher than the liver:plasma concentration ratio of other PFAS congeners. Comparing the MLR model with an equilibrium mass balance model (MBM) suggested that complex kinetic transport processes are driving the unexpectedly high liver:plasma concentration ratio of PFHpA. Intratissue MBM modeling pointed to membrane lipids as the tissue constituents that drive the liver accumulation of long-chain, hydrophobic PFAS, whereas albumin binding of hydrophobic PFAS dominated PFAS distribution in plasma. The liver:plasma concentration data set, empirical MLR model, and mechanistic MBM modeling allow the prediction of liver from plasma concentrations measured in human cohort studies. Our study demonstrates that combining biomonitoring data with mechanistic modeling can identify underlying mechanisms of internal distribution and specific target organ toxicity of PFAS in humans.

INTRODUCTION: Perfluorooctanoic acid (PFOA) has been associated with kidney cancer in human studies. METHODS: We conducted a pooled analysis of two large studies of PFOA and renal cell carcinoma (RCC, the most common type of kidney cancer); one from the National Cancer Institute (NCI) (324 cases and controls), and a second from the C8 Science Panel (103 cases and 511 controls). Serum PFOA levels were estimated a median of 8 years before diagnosis. Analyses were conducted via conditional logistic regression. Lifetime risk of kidney cancer per unit serum PFOA concentration and per unit dose were calculated. RESULTS: The 25th, 50th and 75th percentiles of serum PFOA levels were 4.8, 7.3, and 23.9 ng/ml for the pooled analysis. The preferred model for the pooled datawas a two-piece linear spline model (knot at 12.5 ng/ml serum PFOA); the log odds of RCC increased 0.1349 per 1 ng/ml increase in serum PFOA up to the knot (eg, an OR of 2.02 (1.45-2.80) from the median to the knot), and was flat thereafter. The estimated lifetime excess risk (cancer slope factor) with an exposure of 1 ng/ml was 0.0018, similar to the excess risk of 0.0026 recently reported by CalEPA based on different methods. Assuming a serum half-life of 2.3 years and a distribution volume of 170 ml/kg for PFOA, our results are equivalent to 0.0128 per ng/kg/d of PFOA intake. To limit excess lifetime kidney cancer risk to 1/1,000,000, our data suggest a limit of 0.0015 ng/L (0.0015 ppt) for PFOA in drinking water, similar to CalEPAs proposed Public Health Goal and the new US EPA Drinking Water Health Advisory. CONCLUSIONS: Our results correspond reasonably well with cancer slope factors developed by other investigators using published summary data, and suggest drinking water limits similar to new recommendations by the US EPA.

BackgroundPrenatal exposure to drinking water with arsenic concentrations >50 μg/L is associated with adverse birth outcomes, with inconclusive evidence for concentrations ≤50 μg/L. In a collaborative effort by public health experts, hydrologists, and geologists, we used published machine learning model estimates to characterize arsenic concentrations in private wells-federally unregulated for drinking water contaminants-and evaluated associations with birth outcomes throughout the conterminous U.S.MethodsUsing several machine learning models, including boosted regression trees (BRT) and random forest classification (RFC), developed from measured groundwater arsenic concentrations of ∼20,000 private wells, we characterized the probability that arsenic concentrations occurred within specific ranges in groundwater. Probabilistic model estimates and private well usage data were linked by county to all live birth certificates from 2016 (n = 3.6 million). We evaluated associations with gestational age and term birth weight using mixed-effects models, adjusted for potential confounders and incorporated random intercepts for spatial clustering.ResultsWe generally observed inverse associations with term birth weight. For instance, when using BRT estimates, a 10-percentage point increase in the probability that private well arsenic concentrations exceeded 5 μg/L was associated with a -1.83 g (95% CI: -3.30, -0.38) lower term birth weight after adjusting for covariates. Similarly, a 10-percentage point increase in the probability that private well arsenic concentrations exceeded 10 μg/L was associated with a -2.79 g (95% CI: -4.99, -0.58) lower term birth weight. Associations with gestational age were null.ConclusionIn this largest epidemiologic study of arsenic and birth outcomes to date, we did not observe associations of modeled arsenic estimates in private wells with gestational age and found modest inverse associations with term birth weight. Study limitations may have obscured true associations, including measurement error stemming from a lack of individual-level information on primary water sources, water arsenic concentrations, and water consumption patterns.

BackgroundPer- and polyfluoroalkyl substances (PFAS) widely exist in the environment and human bodies. Contaminated drinking water is one of the major exposure pathways for humans. Previous studies found weak or moderate associations between PFAS and hypertensive disorders of pregnancy (HDP).MethodsWe obtained the number of births and counts of HDP cases for singleton births multiply stratified by county, maternal age, race, education, smoking status, and parity from CDC WONDER, and PFAS water concentrations from EPA UCMR3 data in the United States during 2013-2015. We used binomial regression on the multiply stratified HDP data to produce equal effect estimates and standard errors to those that would be derived from using individual-level data on binary HDP status and demographic covariates in logistic regression.ResultsAfter adjusting for demographic covariates, we found small but statistically significant positive associations between HDP and population-weighted average water concentrations (ng/L) of all four PFAS: Odds ratio (OR) = 1.009, 95% CI = (1.001, 1.016) per IQR increase in perfluorooctanoic acid (PFOA); 1.030, 95% CI = (1.021, 1.040) per IQR increase in perfluorooctane sulfonate (PFOS); 1.008, 95% CI = (1.005, 1.011) per IQR increase in perfluoroheptanoic acid (PFHpA); 1.007, 95% CI = (1.004, 1.010) per IQR increase in perfluorohexane sulfonic acid (PFHxS), and 1.032, 95% CI = (1.022, 1.042) per IQR increase in the sum of four PFAS. Further adjustment for coexposures reversed the effect of PFOA from positive to inverse, and attenuated the effects of PFOS and PFHxS toward the null. After drinking water to serum concentration conversions, our effect estimates for PFOA, PFOS, and PFHxS are similar to previous studies.ConclusionsWe found a weak positive association between the PFAS mixture and HDP, although the generalizability is subject to inherent limitations of the public-available datasets.

We conducted a detailed analysis of coronavirus disease in a large population center in southern California, USA (Orange County, population 3.2 million), to determine heterogeneity in risks for infection, test positivity, and death. We used a combination of datasets, including a population-representative seroprevalence survey, to assess the actual burden of disease and testing intensity, test positivity, and mortality. In the first month of the local epidemic (March 2020), case incidence clustered in high-income areas. This pattern quickly shifted, and cases next clustered in much higher rates in the north-central area of the county, which has a lower socioeconomic status. Beginning in April 2020, a concentration of reported cases, test positivity, testing intensity, and seropositivity in a north-central area persisted. At the individual level, several factors (e.g., age, race or ethnicity, and ZIP codes with low educational attainment) strongly affected risk for seropositivity and death.

We conducted a detailed analysis of coronavirus disease in a large population center in southern California, USA (Orange County, population 3.2 million), to determine heterogeneity in risks for infection, test positivity, and death. We used a combination of datasets, including a population-representative seroprevalence survey, to assess the actual burden of disease and testing intensity, test positivity, and mortality. In the first month of the local epidemic (March 2020), case incidence clustered in high-income areas. This pattern quickly shifted, and cases next clustered in much higher rates in the north-central area of the county, which has a lower socioeconomic status. Beginning in April 2020, a concentration of reported cases, test positivity, testing intensity, and seropositivity in a north-central area persisted. At the individual level, several factors (e.g., age, race or ethnicity, and ZIP codes with low educational attainment) strongly affected risk for seropositivity and death.

BackgroundPer- and polyfluoroalkyl substances (PFAS) are ubiquitous in the serum of the general US population. Food, drinking water, consumer products, dust, and air have been assessed as PFAS exposure sources for humans. The effects of various types of carpeting on serum PFAS concentrations have been less studied, despite the known use of PFAS in stain-resistant carpet treatments.ObjectiveThis study aimed to examine the associations between serum PFAS concentrations and type of residential flooring among the general US population aged 12 years and older using the 2005-2006 National Health and Nutrition Examination Survey (NHANES).MethodsWe used multiple linear regressions adjusted for complex survey design and relevant covariates to analyze the relations between serum PFAS concentrations and type of floor covering (smooth surface, low pile carpet, medium to high pile carpet, and combination of carpet and smooth surface), as well as other potential exposure factors. We used multiple imputation to address missing values.ResultsWe found significantly higher serum concentrations of perfluorohexane sulfonic acid (PFHxS) and 2-(N-methyl-perfluorooctane sulfonamido) acetic acid (MeFOSAA) in US residents residing in homes with low pile carpeting compared with those residing in homes with smooth surface. We concluded that among US residents aged 12 years and older residing in homes with low pile carpeting in the home in 2005-2006, on average 24% and 19% of the PFHxS and MeFOSAA body burdens, respectively, could be attributed to carpeting. We found associations between other types of floor covering (medium to high pile carpet, combination of carpet and smooth surface) and some PFAS concentrations compared with the smooth surface, but these results were less consistent and generally not statistically significant. Additionally, a group Wald Chi-squared test showed a significant result for PFOS, indicating different contributions of various types of flooring to PFOS serum concentration.SignificanceOur results are representative of the general US population at the time of the survey, and potentially informative regarding ongoing PFAS exposure from a variety of sources including carpeting.

Clinic-based estimates of SARS-CoV-2 may considerably underestimate the total number of infections. Access to testing in the US has been heterogeneous and symptoms vary widely in infected persons. Public health surveillance efforts and metrics are therefore hampered by underreporting. We set out to provide a minimally biased estimate of SARS-CoV-2 seroprevalence among adults for a large and diverse county (Orange County, CA, population 3.2 million). We implemented a surveillance study that minimizes response bias by recruiting adults to answer a survey without knowledge of later being offered SARS-CoV-2 test. Several methodologies were used to retrieve a population-representative sample. Participants (n = 2979) visited one of 11 drive-thru test sites from July 10th to August 16th, 2020 (or received an in-home visit) to provide a finger pin-prick sample. We applied a robust SARS-CoV-2 Antigen Microarray technology, which has superior measurement validity relative to FDA-approved tests. Participants include a broad age, gender, racial/ethnic, and income representation. Adjusted seroprevalence of SARS-CoV-2 infection was 11.5% (95% CI: 10.5-12.4%). Formal bias analyses produced similar results. Prevalence was elevated among Hispanics (vs. other non-Hispanic: prevalence ratio [PR] = 1.47, 95% CI 1.22-1.78) and household income  $100,000: PR = 1.42, 95% CI: 1.14 to 1.79). Results from a diverse population using a highly specific and sensitive microarray indicate a SARS-CoV-2 seroprevalence of ~ 12 percent. This population-based seroprevalence is seven-fold greater than that using official County statistics. In this region, SARS-CoV-2 also disproportionately affects Hispanic and low-income adults.

COVID-19 is one of the largest public health emergencies in modern history. Here we present a detailed analysis from a large population center in Southern California (Orange County, population of 3.2 million) to understand heterogeneity in risks of infection, test positivity, and death. We used a combination of datasets, including a population-representative seroprevalence survey, to assess the true burden of disease as well as COVID-19 testing intensity, test positivity, and mortality. In the first month of the local epidemic, case incidence clustered in high income areas. This pattern quickly shifted, with cases next clustering in much higher rates in the north-central area which has a lower socio-economic status. Since April, a concentration of reported cases, test positivity, testing intensity, and seropositivity in a north-central area persisted. At the individual level, several factors (e.g., age, race/ethnicity, zip codes with low educational attainment) strongly affected risk of seropositivity and death.

ABSTRACT Background Clinic-based estimates of SARS-CoV-2 may considerably underestimate the total number of infections. Access to testing in the US has been heterogeneous and symptoms vary widely in infected persons. Public health surveillance efforts and metrics are therefore hampered by underreporting. We set out to provide a minimally biased estimate of SARS-CoV-2 seroprevalence among adults for a large and diverse county (Orange County, CA, population 3.2 million). Methods We implemented a surveillance study that minimizes response bias by recruiting adults to answer a survey without knowledge of later being offered a SARS-CoV-2 test. Several methodologies were used to retrieve a population-representative sample. Participants (n=2,979) visited one of 11 drive-thru test sites from July 10 th to August 16 th , 2020 (or received an in-home visit) to provide a finger pin-prick sample. We applied a robust SARS-CoV-2 Antigen Microarray technology, which has superior measurement validity relative to FDA-approved tests. Findings Participants include a broad age, gender, racial/ethnic, and income representation. Adjusted seroprevalence of SARS-CoV-2 infection was 11.5% (95% CI: 10.5% to 12.4%). Formal bias analyses produced similar results. Prevalence was elevated among Hispanics (vs. other non-Hispanic: prevalence ratio [PR]= 1.47, 95% CI: 1.22 to 1.78) and household income $100,000: PR= 1.42, 95% CI: 1.14 to 1.79). Interpretation Results: from a diverse population using a highly specific and sensitive microarray indicate a SARS-CoV-2 seroprevalence of ∼12 percent. This population-based seroprevalence is seven-fold greater than that using official County statistics. In this region, SARS-CoV-2 also disproportionately affects Hispanic and low-income adults. Funding Orange County Healthcare Agency

BackgroundAdvances in untargeted metabolomic technologies have great potential for insight into adverse metabolic effects underlying exposure to environmental chemicals. However, important challenges need to be addressed, including how biological response corresponds to the environmental chemical burden in different target tissues.AimWe performed a pilot study using state-of-the-art ultra-high-resolution mass spectrometry (UHRMS) to characterize the burden of lipophilic persistent organic pollutants (POPs) in metabolic tissues and associated alterations in the plasma metabolome.MethodsWe studied 11 adolescents with severe obesity at the time of bariatric surgery. We measured 18 POPs that can act as endocrine and metabolic disruptors (i.e. 2 dioxins, 11 organochlorine compounds [OCs] and 5 polybrominated diphenyl ethers [PBDEs]) in visceral and subcutaneous abdominal adipose tissue (vAT and sAT), and liver samples using gas chromatography with UHRMS. Biological pathways were evaluated by measuring the plasma metabolome using high-resolution metabolomics. Network and pathway enrichment analysis assessed correlations between the tissue-specific burden of three frequently detected POPs (i.e. p,p'-dichlorodiphenyldichloroethene [DDE], hexachlorobenzene [HCB] and PBDE-47) and plasma metabolic pathways.ResultsConcentrations of 4 OCs and 3 PBDEs were quantifiable in at least one metabolic tissue for > 80% of participants. All POPs had the highest median concentrations in adipose tissue, especially sAT, except for PBDE-154, which had comparable average concentrations across all tissues. Pathway analysis showed high correlations between tissue-specific POPs and metabolic alterations in pathways of amino acid metabolism, lipid and fatty acid metabolism, and carbohydrate metabolism.ConclusionsMost of the measured POPs appear to accumulate preferentially in adipose tissue compared to liver. Findings of plasma metabolic pathways potentially associated with tissue-specific POPs concentrations merit further investigation in larger populations.

BackgroundPer- and polyfluoroalkyl substances (PFAS) are ubiquitous in the serum of the general US population, and were detected in public water systems serving approximately 16.5 million US residents during 2013-2015. Low birthweight was associated with PFAS exposures in previous studies.MethodsBirthweights for singleton births during 2013-2015 were obtained from CDC WONDER, multiply stratified by county, maternal age, race, education, smoking status, and parity. PFAS water concentrations were obtained from EPA UCMR3 database and aggregated by county. Multiple regression weighted by inverse variance was used to produce effect estimates equivalent to those that would be obtained from individual-level data on birthweight and confounders.ResultsAdjusting for stratification demographic confounders (maternal age, race, education, smoking status, and parity), we found an average change in birthweight of 0.9 g (95% confidence interval [CI] = -0.5, 2.2), -1.3 g (-1.6, -0.9), -3.8 g (-4.9, -2.7), and -3.8 g (-4.3, -3.3) per ng/L increase in the population-weighted average perfluorooctanoic acid, perfluorooctane sulfonate, perfluoroheptanoic acid, and perfluorohexane sulfonic acid in public water supplies by county, respectively. We found an average change in birthweight of -1.0 g (95% CI = -1.2, -0.8) per ng/L increase in the sum of perfluorooctanoic acid, perfluorooctane sulfonate, perfluoroheptanoic acid, and perfluorohexane sulfonic acid concentrations in public water supplies.ConclusionsThe direction and magnitude of association between PFAS and birthweight varied by PFAS chemical in this study. Conclusions are tempered by inherent limitations of the 2 public-use datasets, and by the sensitivity of our results to alternative methods such as mutual adjustment for co-exposures.

Temporal trends in plasma concentrations of per- and polyfluoroalkyl substances (PFAS) in free-ranging bottlenose dolphins (Tursiops truncatus) inhabiting two geographic areas: Indian River Lagoon, Florida over the years 2003-2015 and the waters surrounding Charleston, South Carolina over 2003-2013, were examined. Nine PFAS met the inclusion criteria for analysis based on percent of values below level of detection and sampling years. Proportionate percentiles parametric quantile regression assuming lognormal distributions was used to estimate the average ratio of PFAS concentrations per year for each chemical. Plasma concentrations decreased over time for perfluorodecanoate (PFDA), perfluorohexane sulfonate (PFHxS), perfluorooctanoate (PFOA), perfluorooctane sulfonate (PFOS), and perfluoroundecanoate (PFUnDA) in both locations. Perfluorononanoate (PFNA) decreased with time in Indian River Lagoon dolphins. Perfluorododecanoate (PFDoDA) concentrations significantly increased over time among female Indian River Lagoon dolphins. Regulation and phaseout of specific PFAS groups may have led to the decreasing levels of those PFAS and increasing levels of other replacement PFAS.

BACKGROUND:More than 14,000 women in the United States die of ovarian cancer (OC) every year. Disparities in survival have been observed by race and socioeconomic status (SES), and vary spatially even after adjusting for treatment received. This study aimed to determine the impact of geographic location on receiving treatment adherent to the NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines) for OC, independent of other predictors. PATIENTS AND METHODS:Women diagnosed with all stages of epithelial OC (1996-2014) were identified through the California Cancer Registry. Generalized additive models, smoothing for residential location, were used to calculate adjusted odds ratios (ORs) and 95% CIs for receiving nonadherent care throughout California. We assessed the impact of distance traveled for care, distance to closest high-quality hospital, race/ethnicity, and SES on receipt of quality care, adjusting for demographic and cancer characteristics and stratifying by disease stage. RESULTS:Of 29,844 patients with OC, 11,419 (38.3%) received guideline-adherent care. ORs for nonadherent care were lower in northern California and higher in Kern and Los Angeles counties. Magnitudes of associations with location varied by stage (OR range, 0.45-2.19). Living farther from a high-quality hospital increased the odds of receiving nonadherent care (OR, 1.18; 95% CI, 1.07-1.29), but travel >32 km to receive care was associated with decreased odds (OR, 0.76; 95% CI, 0.70-0.84). American Indian/other women were more likely to travel greater distances to receive care. Women in the highest SES quintile, those with Medicare insurance, and women of non-Hispanic black race were less likely to travel far. Patients who were Asian/Pacific Islander lived the closest to a high-quality hospital. CONCLUSIONS:Among California women diagnosed with OC, living closer to a high-quality center was associated with receiving adherent care. Non-Hispanic black women were less likely to receive adherent care, and women with lower SES lived farthest from high-quality hospitals. Geographic location in California is an independent predictor of adherence to NCCN Guidelines for OC.

BackgroundChildren born near New Bedford, Massachusetts, have been prenatally exposed to multiple environmental chemicals, in part due to an older housing stock, maternal diet, and proximity to the New Bedford Harbor (NBH) Superfund site. Chemical exposure measures are not available for all births, limiting epidemiologic investigations and potential interventions.ObjectiveWe linked biomonitoring data from the New Bedford Cohort (NBC) and birth record data to predict prenatal exposures for all contemporaneous area births.MethodsWe used prenatal exposure biomarker data from the NBC, a population-based cohort of 788 mother-infant pairs born during 1993–1998 to mothers living near the NBH, linked to their corresponding Massachusetts birth record data, to build predictive models for cord serum polychlorinated biphenyls (expressed as a sum, [Formula: see text]), [Formula: see text] (DDE), hexachlorobenzene (HCB), cord blood lead (Pb), and maternal hair mercury (Hg). We applied the best fit models (highest pseudo [Formula: see text]), with multivariable smooths of continuous variables, to predict exposure biomarkers for all 10,270 births during 1993–1998 around the NBH. We used 10-fold cross validation to validate the exposure models and the bootstrap method to characterize sampling variability in the exposure predictions.ResultsThe 10-fold cross-validated [Formula: see text] for the [Formula: see text], DDE, HCB, Pb, and Hg exposure models were 0.54, 0.40, 0.34, 0.46, and 0.40, respectively. For each exposure model, multivariable smooths of continuous variables improved the fit compared with linear models. Other variables with significant effects on exposure estimates were paternal education, maternal race/ethnicity, and maternal ancestry. The resulting exposure predictions for all births had variability consistent with the NBC measured exposures.ConclusionsPredictive models using multivariable smoothing explained reasonable amounts of variance in prenatal exposure biomarkers. Our analyses suggest that prenatal chemical exposures can be predicted for all contemporaneous births in the same geographic area by modeling available biomarker data for a subset of that population. https://doi.org/10.1289/EHP4849.

BACKGROUND:Associations between ambient particulate matter

After publication of the article [1], it was brought to our attention that a number in Table 1 is incorrect.

Our aim is to estimate associations between acute increases in particulate matter with diameter of 2.5 µm or less (PM2.5) concentrations and risk of infant bronchiolitis and otitis media among Massachusetts births born 2001 through 2008.Our case-crossover study included 20,017 infant bronchiolitis and 42,336 otitis media clinical encounter visits. PM2.5 was modeled using satellite, remote sensing, meteorological and land use data. We applied conditional logistic regression to estimate odds ratios (ORs) and confidence intervals (CIs) per 10-µg/m3 increase in PM2.5. We assessed effect modification to determine the most susceptible subgroups. Infant bronchiolitis risk was elevated for PM2.5 exposure 1 day (OR = 1.07, 95% CI = 1.03-1.11) and 4 days (OR = 1.04, 95% CI = 0.99-1.08) prior to clinical encounter, but not 7 days. Non-significant associations with otitis media varied depending on lag. Preterm infants were at substantially increased risk of bronchiolitis 1 day prior to clinical encounter (OR = 1.17, 95% CI = 1.08-1.28) and otitis media 4 and 7 days prior to clinical encounter (OR = 1.09, 95% CI = 1.02-1.16 and OR = 1.08, 95% CI = 1.02-1.15, respectively). In conclusion, preterm infants are most susceptible to infant bronchiolitis and otitis media associated with acute PM2.5 exposures.

SummaryPerfluorooctanoic acid (PFOA) is a persistent environmental contaminant that has been detected in >100 public water systems in the United States alone. A variety of epidemiological investigations of PFOA have been published, mostly using measured or modeled serum PFOA concentrations as the exposure metric. Comparison of drinking water PFOA concentrations to those study findings or to typical serum concentrations requires pharmacokinetic modeling. This brief communication describes an online Javascript calculator that easily plots the expected serum PFOA concentration over time and at steady state for adults after starting or stopping consumption of PFOA-contaminated water. Two examples of usage are provided, including increasing serum PFOA after ongoing consumption of contaminated water at the federal limit, and decreasing serum PFOA after carbon filtration began in a contaminated water system. https://doi.org/10.1289/EHP2820.

Chronic particulate matter less than 2.5μm in diameter (PM2.5) exposure can leave infants more susceptible to illness. Our objective is to estimate associations of the chronic PM2.5 exposure with infant bronchiolitis and otitis media (OM) clinical encounters. We obtained all first time bronchiolitis (n=18,029) and OM (n=40,042) clinical encounters among children less than 12 and 36 months of age, respectively, diagnosed from 2001 to 2009 and two controls per case matched on birthdate and gestational age from the Pregnancy to Early Life Longitudinal data linkage system in Massachusetts. We applied conditional logistic regression to estimate odds ratios (OR) and confidence intervals (CI) per 2-μg/m3 increase in lifetime average satellite based PM2.5 exposure. Effect modification was assessed by age, gestational age, frequency of clinical encounter, and income. We examined associations between residential distance to roadways, traffic density, and infant bronchiolitis and OM risk. PM2.5 was not associated with infant bronchiolitis (OR=1.02, 95% CI=1.00, 1.04) and inversely associated with OM (OR=0.97, 95% CI=0.95, 0.99). There was no evidence of effect modification. Compared to infants living near low traffic density, infants residing in high traffic density had elevated risk of bronchiolitis (OR=1.23, 95% CI=1.14, 1.31) but not OM (OR=0.98, 95% CI=0.93, 1.02) clinical encounter. We did not find strong evidence to support an association between early-life long-term PM2.5 exposure and infant bronchiolitis or OM. Bronchiolitis risk was increased among infants living near high traffic density.

Type 2 diabetes (T2D), historically affecting primarily older individuals, now affects younger people. Few studies have analyzed diabetes risk factors among younger individuals, including college students. We investigated risk in that overlooked population. A 2-part diabetes risk assessment survey was administered to University of California Irvine (UCI) students, faculty, and staff for 2 months. Part I, including 26 questions, assessed participants' nutrition, physical activity, and stress management behaviors. Part II assessed risk according to American Diabetes Association (ADA) Risk Assessment's 8 demographic and lifestyle questions producing a risk score. Scores and behavioral factors analyzed risk on individual and community levels. Recruitment included emails and flyers promoting the UCI Electronic Educational Environment survey link. According to the ADA Risk Assessment scores of the 915 respondents, only 4% are at high risk of developing T2D. Although these scores indicate a small population at risk, our survey revealed a high prevalence of individuals practicing multiple unhealthy lifestyle behaviors associated with diabetes. These multiple behaviors may lead to high percentages of college students developing T2D, despite current low ADA risk status. We conclude the ADA Risk Assessment is geared toward an older demographic and may reflect short-term risk rather than longer-term risks.

Many epidemiology studies have investigated associations of perfluorooctanoate (PFOA) exposures with a variety of adverse health outcomes for participants in the C8 Health Project. The exposure concentrations (i.e., air and groundwater) used in these studies were determined primarily based on participant's residential locations. However, for residential addresses that could not be geocoded to the street level, the exposure concentrations were assigned based on population-weighted ZIP code centroid, which may result in exposure mischaracterization. The aim of this current study is to evaluate the potential impact of mischaracterized exposure concentrations due to geocoding uncertainty on the predicted serum PFOA concentrations and the epidemiological association between PFOA exposure and preeclampsia. For both workplace addresses and incompletely geocoded residential addresses, we used Monte Carlo (MC) simulation to assign alternate geographic locations within the reported ZIP code (instead of population-weighted ZIP code centroids) and the corresponding exposure concentrations. We found that mischaracterization of residential exposure due to population-weighted ZIP code centroid assignment had no significant impact on the serum PFOA concentration predictions and the epidemiological association of PFOA exposure with preeclampsia. In contrast, the uncertainty in workplace exposure moderately impacted the rank exposure among the participants. We observed a 41% increase in the average adjusted odds ratio of preeclampsia occurrence that may be due to differing proportions of cases (64.3%) and controls (54.5%) with workplace address geocodes during pregnancy. This finding suggests that differential exposure mischaracterization can be reduced by obtaining accurate exposure information such as street addresses and tap water consumption, for both workplaces and residences. The analysis we present is one approach for estimating the potential impacts of positional errors in a geocoding-based exposure assessment on exposure estimates and epidemiological study results.

BackgroundPreterm birth (PTB) has been associated with exposure to air pollution, but it is unclear whether effects might vary among air pollution sources and components.ObjectivesWe studied the relationships between PTB and exposure to different components of air pollution, including gases and particulate matter (PM) by size fraction, chemical composition, and sources.MethodsFine and ultrafine PM (respectively, PM2.5 and PM0.1) by source and composition were modeled across California over 2000-2008. Measured PM2.5, nitrogen dioxide, and ozone concentrations were spatially interpolated using empirical Bayesian kriging. Primary traffic emissions at fine scale were modeled using CALINE4 and traffic indices. Data on maternal characteristics, pregnancies, and birth outcomes were obtained from birth certificates. Associations between PTB (n = 442,314) and air pollution exposures defined according to the maternal residence at birth were examined using a nested matched case-control approach. Analyses were adjusted for maternal age, race/ethnicity, education and neighborhood income.ResultsAdjusted odds ratios for PTB in association with interquartile range (IQR) increases in average exposure during pregnancy were 1.133 (95% CI: 1.118, 1.148) for total PM2.5, 1.096 (95% CI: 1.085, 1.108) for ozone, and 1.079 (95% CI: 1.065, 1.093) for nitrogen dioxide. For primary PM, the strongest associations per IQR by source were estimated for onroad gasoline (9-11% increase), followed by onroad diesel (6-8%) and commercial meat cooking (4-7%). For PM2.5 composition, the strongest positive associations per IQR were estimated for nitrate, ammonium, and secondary organic aerosols (11-14%), followed by elemental and organic carbon (2-4%). Associations with local traffic emissions were positive only when analyses were restricted to births with residences geocoded at the tax parcel level.ConclusionsIn our statewide nested case-control study population, exposures to both primary and secondary pollutants were associated with an increase in PTB.CitationLaurent O, Hu J, Li L, Kleeman MJ, Bartell SM, Cockburn M, Escobedo L, Wu J. 2016. A statewide nested case-control study of preterm birth and air pollution by source and composition: California, 2001-2008. Environ Health Perspect 124:1479-1486; http://dx.doi.org/10.1289/ehp.1510133.

BackgroundPerfluorooctanoic acid (PFOA or C8) has hepatotoxic effects in animals. Cross-sectional epidemiologic studies suggest PFOA is associated with liver injury biomarkers.ObjectivesWe estimated associations between modeled historical PFOA exposures and liver injury biomarkers and medically validated liver disease.MethodsParticipants completed surveys during 2008-2011 reporting demographic, medical, and residential history information. Self-reported liver disease, including hepatitis, fatty liver, enlarged liver and cirrhosis, was validated with healthcare providers. Alanine aminotransferase (ALT), γ-glutamyltransferase (GGT) and direct bilirubin, markers of liver toxicity, were obtained from blood samples collected in the C8 Health Project (2005-2006). Historically modeled PFOA exposure, estimated using environmental fate and transport models and participant residential histories, was analyzed in relation to liver biomarkers (n = 30,723, including 1,892 workers) and liver disease (n = 32,254, including 3,713 workers).ResultsModeled cumulative serum PFOA was positively associated with ALT levels (p for trend < 0.0001), indicating possible liver toxicity. An increase from the first to the fifth quintile of cumulative PFOA exposure was associated with a 6% increase in ALT levels (95% CI: 4, 8%) and a 16% increased odds of having above-normal ALT (95% CI: odds ratio: 1.02, 1.33%). There was no indication of association with either elevated direct bilirubin or GGT; however, PFOA was associated with decreased direct bilirubin. We observed no evidence of an effect of cumulative exposure (with or without a 10-year lag) on all liver disease (n = 647 cases), nor on enlarged liver, fatty liver, and cirrhosis only (n = 427 cases).ConclusionResults are consistent with previous cross-sectional studies showing association between PFOA and ALT, a marker of hepatocellular damage. We did not observe evidence that PFOA increases the risk of clinically diagnosed liver disease.CitationDarrow LA, Groth AC, Winquist A, Shin HM, Bartell SM, Steenland K. 2016. Modeled perfluorooctanoic acid (PFOA) exposure and liver function in a Mid-Ohio Valley community. Environ Health Perspect 124:1227-1233; http://dx.doi.org/10.1289/ehp.1510391.

In toxicology studies hormesis refers to a dose-response relationship with a stimulatory response at low doses and an inhibitory response at high doses. In this manuscript, we particularly focus on a J-shaped dose-response relationship for binary cancer responses. We propose and examine two new flexible models for testing the hypothesis of hormesis in a Bayesian framework. The first model is parametric and enhances the flexibility of modeling a hormetic zone by using a non-linear predictor in a multistage model. The second model is non-parametric and allows multiple model specifications, weighting the contribution of each model via Bayesian model averaging (BMA). Simulation studies show that the non-parametric modeling approach with BMA provides robust sensitivity and specificity for detecting hormesis relative to the parametric approach, regardless of the shape of a hormetic zone.