Systematic evidence map (SEM) template: Report format and methods used for the US EPA Integrated Risk Information System (IRIS) program, Provisional Peer Reviewed Toxicity Value (PPRTV) program, and other "fit for purpose" literature-based human health analyses.

BACKGROUND: Systematic evidence maps (SEMs) are gaining visibility in environmental health for their utility to serve as problem formulation tools and assist in decision-making, especially for priority setting. SEMs are now routinely prepared as part of the assessment development process for the US Environmental Protection Agency (EPA) Integrated Risk Information System (IRIS) and Provisional Peer Reviewed Toxicity Value (PPRTV) assessments. SEMs can also be prepared to explore the available literature for an individual chemical or groups of chemicals of emerging interest. OBJECTIVES: This document describes the typical methods used to produce SEMs for the IRIS and PPRTV Programs, as well as "fit for purpose" applications using a variety of examples drawn from existing analyses. It is intended to serve as an example base template that can be adapted as needed for the specific SEM. The presented methods include workflows intended to facilitate rapid production. The Populations, Exposures, Comparators and Outcomes (PECO) criteria are typically kept broad to identify mammalian animal bioassay and epidemiological studies that could be informative for human hazard identification. In addition, a variety of supplemental content is tracked, e.g., studies presenting information on in vitro model systems, non-mammalian model systems, exposure-level-only studies in humans, pharmacokinetic models, and absorption, distribution, metabolism, and excretion (ADME). The availability of New Approach Methods (NAMs) evidence is also tracked (e.g., high throughput, transcriptomic, in silico, etc.). Genotoxicity studies may be considered as PECO relevant or supplemental material, depending on the topic and context of the review. Standard systematic review practices (e.g., two independent reviewers per record) and specialized software applications are used to search and screen the literature and may include the use of machine learning software. Mammalian bioassay and epidemiological studies that meet the PECO criteria after full-text review are briefly summarized using structured web-based extraction forms with respect to study design and health system(s) assessed. Extracted data is available in interactive visual formats and can be downloaded in open access formats. Methods for conducting study evaluation are also presented which is conducted on a case-by-case basis, depending on the usage of the SEM.

Use of systematic evidence maps within the US environmental protection agency (EPA) integrated risk information system (IRIS) program: Advancements to date and looking ahead.

Systematic evidence maps (SEMs) are increasingly used to inform decision-making and risk management priority-setting and to serve as problem formulation tools to refine the focus of questions that get addressed in full systematic reviews. Within the U.S. Environmental Protection Agency (EPA) Office of Research and Development (ORD) Integrated Risk Information System (IRIS), SEMs have been used to inform data gaps, determine the need for updated assessments, inform assessment priorities, and inform development of study evaluation considerations, among other uses. Increased utilization of SEMs across the environmental health field has the potential to increase transparency and efficiency for data gathering, problem formulation, read-across, and evidence surveillance. Use of the SEM templates published in the companion text (Thayer et al.) can promote harmonization in the environmental health community and create more opportunities for sharing extracted content.

Residential greenness, asthma, and lung function among children at high risk of allergic sensitization: a prospective cohort study.

BACKGROUND: While benefits of greenness to health have been reported, findings specific to child respiratory health are inconsistent. METHODS: We utilized a prospective birth cohort followed from birth to age 7 years (n = 617). Residential surrounding greenness was quantified via Normalized Difference Vegetation Index (NDVI) within 200, 400, and 800 m distances from geocoded home addresses at birth, age 7 years, and across childhood. Respiratory health outcomes were assessed at age 7 years, including asthma and lung function [percent predicted forced expiratory volume in the first second (%FEV1), percent predicted forced vital capacity (%FVC), and percent predicted ratio of forced expiratory volume in the first second to forced vital capacity (%FEV1/FVC)]. We assessed associations using linear and logistic regression models adjusted for community deprivation, household income, and traffic-related air pollution. We tested for effect measure modification by atopic status. RESULTS: We noted evidence of positive confounding as inverse associations were attenuated upon adjustment in the multivariable models. We found evidence of effect measure modification of NDVI and asthma within 400 m at age 7 years by atopic status (p = 0.04), whereby children sensitized to common allergens were more likely to develop asthma as exposure to greenness increased (OR = 1.3, 95% CI: 0.9, 2.0) versus children not sensitized to common allergens (OR = 0.8, 95% CI: 0.5, 1.2). We found consistently positive associations between NDVI and %FEV1 and %FVC which similarly evidenced positive confounding upon adjustment. In the adjusted regression models, NDVI at 7 years of age was associated with %FEV1 (200 m: ß = 2.1, 95% CI: 0.1, 3.3; 400 m: ß = 1.6, 95% CI: 0.3, 2.9) and %FVC (200 m: ß = 1.8, 95% CI: 0.7, 3.0; 400 m: ß = 1.6, 95% CI: 0.3, 2.8; 800 m: ß = 1.5, 95% CI: 0.1, 2.8). Adjusted results for %FEV1/FVC were non-significant except exposure at birth in the 400 m buffer (ß = 0.81, 95% CI: 0.1, 1.5). We found no evidence of effect measure modification of NDVI by atopic status for objective measures of lung function. CONCLUSION: Sensitivity to allergens may modify the effect of greenness on risk for asthma in children but greenness is likely beneficial for concurrent lung function regardless of allergic status.

Using the Key Characteristics of Carcinogens to Develop Research on Chemical Mixtures and Cancer.

BACKGROUND: People are exposed to numerous chemicals throughout their lifetimes. Many of these chemicals display one or more of the key characteristics of carcinogens or interact with processes described in the hallmarks of cancer. Therefore, evaluating the effects of chemical mixtures on cancer development is an important pursuit. Challenges involved in designing research studies to evaluate the joint action of chemicals on cancer risk include the time taken to perform the experiments because of the long latency and choosing an appropriate experimental design. OBJECTIVES: The objectives of this work are to present the case for developing a research program on mixtures of environmental chemicals and cancer risk and describe recommended approaches. METHODS: A working group comprising the coauthors focused attention on the design of mixtures studies to inform cancer risk assessment as part of a larger effort to refine the key characteristics of carcinogens and explore their application. Working group members reviewed the key characteristics of carcinogens, hallmarks of cancer, and mixtures research for other disease end points. The group discussed options for developing tractable projects to evaluate the joint effects of environmental chemicals on cancer development. RESULTS AND DISCUSSION: Three approaches for developing a research program to evaluate the effects of mixtures on cancer development were proposed: a chemical screening approach, a transgenic model-based approach, and a disease-centered approach. Advantages and disadvantages of each are discussed. https://doi.org/10.1289/EHP8525.

ExpoKids: An R-based tool for characterizing aggregate chemical exposure during childhood.

BACKGROUND: Aggregate exposure, the combined exposures to a single chemical from all pathways, is a critical children's health issue. OBJECTIVE: The primary objective is to develop a tool to illustrate potential differences in aggregate exposure at various childhood lifestages and the adult lifestage. METHODS: We developed ExpoKids (an R-based tool) using oral exposure estimates across lifestages generated by US EPA's Exposure Factors Interactive Resource for Scenarios Tool (ExpoFIRST). RESULTS: ExpoKids is applied to illustrate aggregate oral exposure, for ten media, as average daily doses (ADD) and lifetime average daily doses (LADD) in five graphs organized across seven postnatal childhood lifestages and the adult lifestage. This data visualization tool conveys ExpoFIRST findings, from available exposure data, to highlight the relative contributions of media and lifestages to chemical exposure. To evaluate the effectiveness of ExpoKids, three chemical case examples (di[2-ethylhexyl] phthalate [DEHP], manganese, and endosulfan) were explored. Data available from the published literature and databases for each case example were used to explore research questions regarding media and lifestage contributions to aggregate exposure. SIGNIFICANCE: These illustrative case examples demonstrate ExpoKids' versatile application to explore a diverse set of children's health risk assessment and management questions by visually depicting specific media and lifestage contributions to aggregate exposure.

A Cumulative Risk Perspective for Occupational Health and Safety (OHS) Professionals.

Cumulative risk assessment (CRA) addresses the combined risk associated with chemical and non-chemical exposures. Although CRA approaches are utilized in environmental and ecological contexts, they are rarely applied in workplaces. In this perspectives article, we strive to raise awareness among occupational health and safety (OHS) professionals and foster the greater adoption of a CRA perspective in practice. Specifically, we provide an overview of CRA literature as well as preliminary guidance on when to consider a CRA approach in occupational settings and how to establish reasonable boundaries. Examples of possible workplace co-exposures and voluntary risk management actions are discussed. We also highlight important implications for workplace CRA research and practice. In particular, future needs include simple tools for identifying combinations of chemical and non-chemical exposures, uniform risk management guidelines, and risk communication materials. Further development of practical CRA methods and tools are essential to meet the needs of complex and changing work environments.

Using high-resolution residential greenspace measures in an urban environment to assess risks of allergy outcomes in children.

Despite reported health benefits of urban greenspace (gs), the epidemiological evidence is less clear for allergic disease. To address a limitation of previous research, we examined the associations of medium- and high-resolution residential gs measures and tree and/or grass canopies with allergic outcomes for children enrolled in the longitudinal cincinnati childhood allergy and air pollution study (ccaaps). We estimated residential gs based on 400 m radial buffers around participant addresses (n = 478) using the normalized differential vegetation index (ndvi) and land cover-derived urban greenspace (ugs) (tree and grass coverage, combined and separate) at 30 m and 1.5-2.5 m resolution, respectively. Associations between outdoor aeroallergen sensitization and allergic rhinitis at age 7 and residential gs measures at different exposure windows were examined using multivariable logistic regression models. A 10% increase in ugs-derived grass coverage was associated with an increased risk of sensitization to grass pollens (adjusted odds ratio [aor]: 1.27; 95% confidence interval = 1.02-1.58). For each 10% increase in ugs-derived tree canopy coverage, nonstatistically significant decreased odds were found for grass pollen sensitization, tree pollen sensitization, and sensitization to either (aor range = 0.87-0.94). Results similar in magnitude to ugs-tree canopy coverage were detected for ndvi and allergic sensitizations. High-resolution (down to 1.5 m) gs measures of grass- and tree-covered areas showed associations in opposite directions for different allergy outcomes. These data suggest that measures strongly correlated with tree canopy (e.g., ndvi) may be insufficient to detect health effects associated with proximity to different types of vegetation or help elucidate mechanisms related to specific gs exposure pathways.

Ambient ozone and fine particulate matter exposures and autism spectrum disorder in metropolitan Cincinnati, Ohio.

BACKGROUND: Epidemiological studies report fairly consistent associations between various air pollution metrics and autism spectrum disorder (ASD), with some elevated risks reported for different prenatal and postnatal periods. OBJECTIVES: To examine associations between ASD and ambient fine particulate matter (PM2.5) and ozone concentrations during the prenatal period through the second year of life in a case-control study. METHODS: ASD cases (n = 428) diagnosed at Cincinnati Children's Hospital Medical Center were frequency matched (15:1) to 6420 controls from Ohio birth records. We assigned daily PM2.5 and ozone estimates for 2005-2012 from US EPA's Fused Air Quality Surface Using Downscaling model to each participant for each day based on the mother's census tract of residence at birth. We calculated adjusted odds ratios (aORs) using logistic regression across continuous and categorical exposure window averages (trimesters, first and second postnatal years, and cumulative measure), adjusting for maternal- and birth-related confounders, both air pollutants, and multiple temporal exposure windows. RESULTS: We detected elevated aORs for PM2.5 during the 2nd trimester, 1st year of life, and a cumulative period from pregnancy through the 2nd year (aOR ranges across categories: 1.41-1.44, 1.54-1.84, and 1.41-1.52 respectively), and for ozone in the 2nd year of life (aOR range across categories: 1.29-1.42). Per each change in IQR, we observed elevated aORs for ozone in the 3rd trimester, 1st and 2nd years of life, and the cumulative period (aOR range: 1.19-1.27) and for PM2.5 in the 2nd trimester, 1st year of life, and the cumulative period (aOR range: 1.11-1.17). DISCUSSION: We saw limited evidence of linear exposure-response relationships for ASD with increasing air pollution, but the elevated aORs detected for PM2.5 in upper exposure categories and per IQR unit increases were similar in magnitude to those reported in previous studies, especially for postnatal exposures.

How similar is similar enough? A sufficient similarity case study with Ginkgo biloba extract.

Botanical dietary supplements are complex mixtures that can be highly variable in composition and quality, making safety evaluation difficult. A key challenge is determining how diverse products in the marketplace relate to chemically and toxicologically characterized reference samples (i.e., how similar must a product be in order to be well-represented by the tested reference sample?). Ginkgo biloba extract (GBE) was used as a case study to develop and evaluate approaches for determining sufficient similarity. Multiple GBE extracts were evaluated for chemical and biological-response similarity. Chemical similarity was assessed using untargeted and targeted chemistry approaches. Biological similarity was evaluated using in vitro liver models and short-term rodent studies. Statistical and data visualization methods were then used to make decisions about the similarity of products to the reference sample. A majority of the 26 GBE samples tested (62%) were consistently determined to be sufficiently similar to the reference sample, while 27% were different from the reference GBE, and 12% were either similar or different depending on the method used. This case study demonstrated that approaches to evaluate sufficient similarity allow for critical evaluation of complex mixtures so that safety data from the tested reference can be applied to untested materials.

Characterizing Risk for Cumulative Risk Assessments.

In assessing environmental health risks, the risk characterization step synthesizes information gathered in evaluating exposures to stressors together with dose-response relationships, characteristics of the exposed population, and external environmental conditions. This article summarizes key steps of a cumulative risk assessment (CRA) followed by a discussion of considerations for characterizing cumulative risks. Cumulative risk characterizations differ considerably from single chemical- or single source-based risk characterization. CRAs typically focus on a specific population instead of a pollutant or pollutant source and should include an evaluation of all relevant sources contributing to the exposures in the population and other factors that influence dose-response relationships. Second, CRAs may include influential environmental and population-specific conditions, involving multiple chemical and nonchemical stressors. Third, a CRA could examine multiple health effects, reflecting joint toxicity and the potential for toxicological interactions. Fourth, the complexities often necessitate simplifying methods, including judgment-based and semi-quantitative indices that collapse disparate data into numerical scores. Fifth, because of the higher dimensionality and potentially large number of interactions, information needed to quantify risk is typically incomplete, necessitating an uncertainty analysis. Three approaches that could be used for characterizing risks in a CRA are presented: the multiroute hazard index, stressor grouping by exposure and toxicity, and indices for screening multiple factors and conditions. Other key roles of the risk characterization in CRAs are also described, mainly the translational aspect of including a characterization summary for lay readers (in addition to the technical analysis), and placing the results in the context of the likely risk-based decisions.

Swine exposure and methicillin-resistant Staphylococcus aureus infection among hospitalized patients with skin and soft tissue infections in Illinois: A ZIP code-level analysis.

BACKGROUND: Methicillin-resistant Staphylococcus aureus (MRSA), a bacterial pathogen, is a predominant cause of skin and soft tissue infections (SSTI) in the United States. Swine-production facilities have been recognized as potential environmental reservoirs of MRSA. To better understand how swine production may contribute to MRSA infection, we evaluated the association between MRSA infection among SSTI inpatients and exposure measures derived from national swine inventory data. METHODS: Based on adjusted odds ratios from logistic regression models, we evaluated the association between swine exposure metrics and MRSA infections among all Illinois inpatient hospitalizations for SSTI from January 2008 through July 2011. We also assessed if swine exposures had greater association with suspected community-onset MRSA (CO-MRSA) compared to suspected hospital-onset MRSA (HO-MRSA). Exposures were estimated using the Farm Location and Agricultural Production Simulator, generating the number of farms with greater than 1000 swine per residential ZIP code and the residential ZIP code-level swine density (swine/km2). RESULTS: For every increase in 100 swine/km2 within a residential ZIP code, the adjusted OR (aOR) for MRSA infection was 1.36 (95% CI: 1.28-1.45). For every additional large farm (i.e., >1000 swine) per ZIP code, the aOR for MRSA infection was 1.06 (95% CI: 1.04-1.07). The aOR for ZIP codes with any large farms compared to those with no large farms was 1.24 (95% CI: 1.19-1.29). We saw no evidence of an increased association for CO-MRSA compared to HO-MRSA with either continuous exposure metric (aORs=0.99), and observed inconsistent results across exposure categories. CONCLUSIONS: These publicly-available, ecological exposure data demonstrated positive associations between swine exposure measures and individual-level MRSA infections among SSTI inpatients. Though it is difficult to draw definitive conclusions due to limitations of the data, these findings suggest that the risk of MRSA may increase based on indirect environmental exposure to swine production. Future research can address measurement error related to these data by improving exposure assessment precision, increased specification of MRSA strain, and better characterization of specific environmental exposure pathways.

Method to assess component contribution to toxicity of complex mixtures: Assessment of puberty acquisition in rats exposed to disinfection byproducts.

A method based on regression modeling was developed to discern the contribution of component chemicals to the toxicity of highly complex, environmentally realistic mixtures of disinfection byproducts (DBPs). Chemical disinfection of drinking water forms DBP mixtures. Because of concerns about possible reproductive and developmental toxicity, a whole mixture (WM) of DBPs produced by chlorination of a water concentrate was administered as drinking water to Sprague-Dawley (S-D) rats in a multigenerational study. Age of puberty acquisition, i.e., preputial separation (PPS) and vaginal opening (VO), was examined in male and female offspring, respectively. When compared to controls, a slight, but statistically significant delay in puberty acquisition was observed in females but not in males. WM-induced differences in the age at puberty acquisition were compared to those reported in S-D rats administered either a defined mixture (DM) of nine regulated DBPs or individual DBPs. Regression models were developed using individual animal data on age at PPS or VO from the DM study. Puberty acquisition data reported in the WM and individual DBP studies were then compared with the DM models. The delay in puberty acquisition observed in the WM-treated female rats could not be distinguished from delays predicted by the DM regression model, suggesting that the nine regulated DBPs in the DM might account for much of the delay observed in the WM. This method is applicable to mixtures of other types of chemicals and other endpoints.

Estimating Inorganic Arsenic Exposure from U.S. Rice and Total Water Intakes.

BACKGROUND: Among nonoccupationally exposed U.S. residents, drinking water and diet are considered primary exposure pathways for inorganic arsenic (iAs). In drinking water, iAs is the primary form of arsenic (As), while dietary As speciation techniques are used to differentiate iAs from less toxic arsenicals in food matrices. OBJECTIVES: Our goal was to estimate the distribution of iAs exposure rates from drinking water intakes and rice consumption in the U.S. population and ethnic- and age-based subpopulations. METHODS: The distribution of iAs in drinking water was estimated by population, weighting the iAs concentrations for each drinking water utility in the Second Six-Year Review data set. To estimate the distribution of iAs concentrations in rice ingested by U.S. consumers, 54 grain-specific, production-weighted composites of rice obtained from U.S. mills were extracted and speciated using both a quantitative dilute nitric acid extraction and speciation (DNAS) and an in vitro gastrointestinal assay to provide an upper bound and bioaccessible estimates, respectively. Daily drinking water intake and rice consumption rate distributions were developed using data from the What We Eat in America (WWEIA) study. RESULTS: Using these data sets, the Stochastic Human Exposure and Dose Simulation (SHEDS) model estimated mean iAs exposures from drinking water and rice were 4.2 µg/day and 1.4 µg/day, respectively, for the entire U.S. population. The Tribal, Asian, and Pacific population exhibited the highest mean daily exposure of iAs from cooked rice (2.8 µg/day); the mean exposure rate for children between ages 1 and 2 years in this population is 0.104 µg/kg body weight (BW)/day. CONCLUSIONS: An average consumer drinking 1.5 L of water daily that contains between 2 and 3 ng iAs/mL is exposed to approximately the same amount of iAs as a mean Tribal, Asian, and Pacific consumer is exposed to from rice. https://doi.org/10.1289/EHP418. BACKGROUND: Among nonoccupationally exposed U.S. residents, drinking water and diet are considered primary exposure pathways for inorganic arsenic (iAs). In drinking water, iAs is the primary form of arsenic (As), while dietary As speciation techniques are used to differentiate iAs from less toxic arsenicals in food matrices. OBJECTIVES: Our goal was to estimate the distribution of iAs exposure rates from drinking water intakes and rice consumption in the U.S. population and ethnic- and age-based subpopulations. METHODS: The distribution of iAs in drinking water was estimated by population, weighting the iAs concentrations for each drinking water utility in the Second Six-Year Review data set. To estimate the distribution of iAs concentrations in rice ingested by U.S. consumers, 54 grain-specific, production-weighted composites of rice obtained from U.S. mills were extracted and speciated using both a quantitative dilute nitric acid extraction and speciation (DNAS) and an in vitro gastrointestinal assay to provide an upper bound and bioaccessible estimates, respectively. Daily drinking water intake and rice consumption rate distributions were developed using data from the What We Eat in America (WWEIA) study. RESULTS: Using these data sets, the Stochastic Human Exposure and Dose Simulation (SHEDS) model estimated mean iAs exposures from drinking water and rice were [Formula: see text] and [Formula: see text], respectively, for the entire U.S. population. The Tribal, Asian, and Pacific population exhibited the highest mean daily exposure of iAs from cooked rice ([Formula: see text]); the mean exposure rate for children between ages 1 and 2 years in this population is [Formula: see text] body weight (BW)/day. CONCLUSIONS: An average consumer drinking 1.5 L of water daily that contains between 2 and [Formula: see text] is exposed to approximately the same amount of iAs as a mean Tribal, Asian, and Pacific consumer is exposed to from rice. https://doi.org/10.1289/EHP418.

Causal inference in cumulative risk assessment: The roles of directed acyclic graphs.

Cumulative risk assessments (CRAs) address exposures to multiple chemical and nonchemical stressors and often focus on characterization of health risks in vulnerable populations. Evaluating complex exposure-response relationships in CRAs requires the use of formal and rigorous methods for causal inference. Directed acyclic graphs (DAGs) are graphical causal models used to organize and communicate knowledge about the underlying causal structure that generates observable data. Using existing graphical theories for causal inference with DAGs, risk analysts can identify confounders and effect measure modifiers to determine if the available data are both internally valid to obtain unbiased risk estimates and are generalizable to populations of interest. Conditional independencies implied by the structure of a DAG can be used to test assumptions used in a CRA against empirical data in a selected study and can contribute to the evidence evaluations related to specific causal pathways. This can facilitate quantitative use of these data, as well as help identify key research gaps, prioritize data collection activities, and evaluate risk management alternatives. DAGs also enable risk analysts to be explicit about sources of uncertainty and to determine whether a causal effect can be estimated from available data. Using a conceptual model and DAG for a hypothetical community located near a concentrated animal feeding operation (CAFO), we illustrate the advantages of using DAGs for evaluating causality in CRAs. DAGs also can be used in conjunction with weight of evidence (WOE) methodology to improve causal analysis for CRA, which could lead to more effective interventions to reduce population health risks.

Cumulative risk assessment lessons learned: a review of case studies and issue papers.

Cumulative risk assessments (CRAs) examine potential risks posed by exposure to multiple and sometimes disparate environmental stressors. CRAs are more resource intensive than single chemical assessments, and pose additional challenges and sources of uncertainty. CRAs may examine the impact of several factors on risk, including exposure magnitude and timing, chemical mixture composition, as well as physical, biological, or psychosocial stressors. CRAs are meant to increase the relevance of risk assessments, providing decision makers with information based on real world exposure scenarios that improve the characterization of actual risks and hazards. The U.S. Environmental Protection Agency has evaluated a number of CRAs, performed by or commissioned for the Agency, to seek insight into CRA concepts, methods, and lessons learned. In this article, ten case studies and five issue papers on key CRA topics are examined and a set of lessons learned are identified for CRA implementation. The lessons address the iterative nature of CRAs, importance of considering vulnerability, need for stakeholder engagement, value of a tiered approach, new methods to assess multiroute exposures to chemical mixtures, and the impact of geographical scale on approach and purpose.

Joint exposure to chemical and nonchemical neurodevelopmental stressors in U.S. women of reproductive age in NHANES.

Lead (Pb) and methyl mercury (MeHg) are well established neurodevelopmental toxicants (NDTs), but joint exposure to chemical and nonchemical (e.g., maternal stress) stressors has rarely been considered. We characterized exposure to Pb, MeHg and a measure of physiological dysregulation associated with chronic stress and examined race/ethnicity as a predictor of joint NDT exposure. Using data from the 2003-2004 NHANES, potential chronic stress exposure was estimated using allostatic load (AL), a quantitative measure of physiological dysregulation. A Hazard Index was calculated for joint exposure to Pb and MeHg (HI(NDT)). Logistic regression was used to assess the relationship between an indicator of elevated joint NDT exposures (HI(NDT) > 1) and race/ethnicity. The multivariate model was stratified by AL groups to examine effect measure modification. African American (adjusted odds ratio [OR] [95% confidence interval] = 2.2 [1.4, 3.3]) and Mexican American (1.4 [0.7, 2.6]) women were more likely to have an HI(NDT) > 1 compared to Caucasian women. Chronic stress was identified as an effect measure modifier with the largest ORs among women with high AL scores (African Americans = 4.3 [2.0, 9.5]; Mexican Americans = 4.2 [1.3, 14.1]). Chronic stress was found to modify the association between elevated joint NDT exposure and race/ethnicity, highlighting the importance of evaluating chemical and nonchemical stressor exposures leading to a common endpoint.

A sensitivity analysis using alternative toxic equivalency factors to estimate U.S. dietary exposures to dioxin-like compounds.

EPA recommends sensitivity analyses when applying the toxic equivalency factor (TEF) method to evaluate exposures to dioxin-like compounds (DLCs). Applying the World Health Organization's (WHO) 2005 TEF values and estimating average U.S. daily dietary intakes of 25 DLCs from eight food categories, we estimate a toxic equivalency (TEQ) intake of 23 pg/day. Among DLCs, PCB 126 (26%) and 1,2,3,7,8-PeCDD (23%) dominate TEQ intakes. Among food categories, milk (14%), other dairy (28%), beef (25%), and seafood (18%) most influenced TEQ intakes. We develop two approaches to estimate alternative TEF values. Based on WHO's assumption regarding TEF uncertainty, Approach1 estimates upper and lower TEFs for each DLC by multiplying and dividing, respectively, its individual TEF by ± half a log. Based on compiled empirical ranges of relative potency estimates, Approach2 uses percentile values for individual TEFs. Total TEQ intake estimates using the lower and upper TEFs based on Approach1 were 8 and 68 pg TEQ/day, respectively. The 25th and 75th percentile TEFs from Approach2 yielded 12 and 28 pg TEQ/day, respectively. The influential DLCs and food categories remained consistent across alternative TEFs, except at the 90th percentile using Approach2. We highlight the need for developing underlying TEF probability distributions.

Comprehensive assessment of a chlorinated drinking water concentrate in a rat multigenerational reproductive toxicity study.

Some epidemiological studies report associations between drinking water disinfection byproducts (DBPs) and adverse reproductive/developmental effects, e.g., low birth weight, spontaneous abortion, stillbirth, and birth defects. Using a multigenerational rat bioassay, we evaluated an environmentally relevant "whole" mixture of DBPs representative of chlorinated drinking water, including unidentified DBPs as well as realistic proportions of known DBPs at low-toxicity concentrations. Source water from a water utility was concentrated 136-fold, chlorinated, and provided as drinking water to Sprague-Dawley rats. Timed-pregnant females (P0 generation) were exposed during gestation and lactation. Weanlings (F1 generation) continued exposures and were bred to produce an F2 generation. Large sample sizes enhanced statistical power, particularly for pup weight and prenatal loss. No adverse effects were observed for pup weight, prenatal loss, pregnancy rate, gestation length, puberty onset in males, growth, estrous cycles, hormone levels, immunological end points, and most neurobehavioral end points. Significant, albeit slight, effects included delayed puberty for F1 females, reduced caput epidydimal sperm counts in F1 adult males, and increased incidences of thyroid follicular cell hypertrophy in adult females. These results highlight areas for future research, while the largely negative findings, particularly for pup weight and prenatal loss, are notable.