Cumulative risk assessment for combined health effects from chemical and nonchemical stressors

Cumulative risk assessment for combinations of environmental and psychosocial stressors: A systematic review

With the growing awareness of stressors, cumulative risk assessment (CRA) has been proposed as a potential method to evaluate possible additive and synergistic effects of multiple stressors on human health, thus informing environmental regulation and protecting public health. However, CRA is still in its exploratory stage due to the lack of generally accepted quantitative approaches. It is an ideal time to summarize the existing progress to guide future research. To this end, a systematic review of the literature on CRA issues dealing with combinations of environmental and psychosocial stressors was conducted in this study. Using typology and bibliometric analysis, the body of knowledge, hot topics, and research gaps in this field were characterized. It was found that research topics and objectives mainly focus on qualitative analysis and community settings; more attention should be paid to the development of quantitative approaches and the inclusion of occupational settings. Further, the roles of air pollution and vulnerability factors in CRA have attracted the most attention. This study concludes with views on future prospects to promote theoretical and practical development in this field; specifically, CRA is a multifaceted topic that requires substantial collaborations with various stakeholders and substantial knowledge from multidisciplinary fields. This study presents an overall review as well as research directions worth investigating in this field, which provides a historical reference for future study. Integr Environ Assess Manag 2024;20:602-615. © 2023 SETAC.

Integrating the social environment with an equity perspective into the exposome paradigm: A new conceptual framework of the Social Exposome

The importance of the social environment and social inequalities in disease etiology is well-known due to the profound research and conceptual framework on social determinants of health. For a long period, in exposome research with its classical orientation towards detrimental health effects of biological, chemical, and physical exposures, this knowledge remained underrepresented. But currently it gains great awareness and calls for innovations in rethinking the role of social environmental health determinants. To fill this gap that exists in terms of the social domain within exposome research, we propose a novel conceptual framework of the Social Exposome, to integrate the social environment in conjunction with the physical environment into the exposome concept. The iterative development process of the Social Exposome was based on a systematic compilation of social exposures in order to achieve a holistic portrayal of the human social environment - including social, psychosocial, socioeconomic, sociodemographic, local, regional, and cultural aspects, at individual and contextual levels. In order to move the Social Exposome beyond a mere compilation of exposures, three core principles are emphasized that underly the interplay of the multitude of exposures: Multidimensionality, Reciprocity, and Timing and continuity. The key focus of the conceptual framework of the Social Exposome is on understanding the underlying mechanisms that translate social exposures into health outcomes. In particular, insights from research on health equity and environmental justice have been incorporated to uncover how social inequalities in health emerge, are maintained, and systematically drive health outcomes. Three transmission pathways are presented: Embodiment, Resilience and Susceptibility or Vulnerability, and Empowerment. The Social Exposome conceptual framework may serve as a strategic map for, both, research and intervention planning, aiming to further explore the impact of the complex social environment and to alter transmission pathways to minimize health risks and health inequalities and to foster equity in health.

Ecological and human health risk assessments of cyanotoxins and heavy metals in a drinking water supply reservoir

Human beings are frequently exposed to a mixture of chemical pollutants through the ingestion of contaminated drinking water. The present study aimed to assess the ecological and human health risks associated with the contamination of cyanotoxins and heavy metals in a drinking water supply reservoir, the Tri An Reservoir (TAR), in Vietnam. Results demonstrated that the concentrations of individual heavy metals varied in the following order: iron (Fe) > lead (Pb) > arsenic (As) > zinc (Zn). Although the ecological potential risk of heavy metals was low during the study period, the concentration of Fe sometimes exceeded the Vietnamese standard for drinking water. Toxic cyanobacteria and microcystins (MCs) frequently occurred in the TAR with the highest density of 198.7 × 103 cells/mL and 7.8 μg/L, respectively, indicating a high risk of health impacts to humans. The results of the study indicate that exposure to heavy metals does not pose any non-carcinogenic health risks for both adults and children. However, the contamination of MCs in the surface water posed a serious disease enhancement to both adults and children through direct ingestion and dermal absorption.

Cumulative Risk Evaluation of Phthalates Under TSCA

The U.S. Environmental Protection Agency (EPA) is currently conducting separate Toxic Substances Control Act (TSCA) risk evaluations for seven phthalates: dibutyl phthalate (DBP), butyl benzyl phthalate (BBP), di(2-ethylhexyl) phthalate (DEHP), diisobutyl phthalate (DIBP), dicyclohexyl phthalate (DCHP), di-isodecyl phthalate (DIDP), and diisononyl phthalate (DINP). Phthalates are highly abundant plastic additives used primarily to soften materials and make them flexible, and biomonitoring shows widespread human exposure to a mixture of phthalates. Evidence supports biological additivity of phthalate mixture exposures, including the enhancement of toxicity affecting common biological targets. Risk estimates based on individual phthalate exposure may not be protective of public health. Thus, a cumulative risk approach is warranted. While EPA initially did not signal that it would incorporate cumulative risk assessment (CRA) as part of its current risk evaluation for the seven phthalates, the agency recently announced that it is reconsidering if CRA for phthalates would be appropriate. Based on our review of existing chemical mixtures risk assessment guidance, current TSCA scoping documents for the seven phthalates, and pertinent peer-reviewed literature, we delineate a CRA approach that EPA can easily implement for phthalates. The strategy for using CRA to inform TSCA risk evaluation for existing chemicals is based upon integrative physiology and a common adverse health outcome algorithm for identifying and grouping relevant nonchemical and chemical stressors. We recommend adjustments for how hazard indices (HIs) or margins of exposure (MOEs) based on CRA are interpreted for determining "unreasonable risk" under TSCA.

Addressing systemic problems with exposure assessments to protect the public's health

BACKGROUND

Understanding, characterizing, and quantifying human exposures to environmental chemicals is critical to protect public health. Exposure assessments are key to determining risks to the general population and for specific subpopulations given that exposures differ between groups. Exposure data are also important for understanding where interventions, including public policies, should be targeted and the extent to which interventions have been successful. In this review, we aim to show how inadequacies in exposure assessments conducted by polluting industries or regulatory agencies have led to downplaying or disregarding exposure concerns raised by communities; that underestimates of exposure can lead regulatory agencies to conclude that unacceptable risks are, instead, acceptable, allowing pollutants to go unregulated; and that researchers, risk assessors, and policy makers need to better understand the issues that have affected exposure assessments and how appropriate use of exposure data can contribute to health-protective decisions.

METHODS

We describe current approaches used by regulatory agencies to estimate human exposures to environmental chemicals, including approaches to address limitations in exposure data. We then illustrate how some exposure assessments have been used to reach flawed conclusions about environmental chemicals and make recommendations for improvements.

RESULTS

Exposure data are important for communities, public health advocates, scientists, policy makers, and other groups to understand the extent of environmental exposures in diverse populations. We identify four areas where exposure assessments need to be improved due to systemic sources of error or uncertainty in exposure assessments and illustrate these areas with examples. These include: (1) an inability of regulatory agencies to keep pace with the increasing number of chemicals registered for use or assess their exposures, as well as complications added by use of 'confidential business information' which reduce available exposure data; (2) the failure to keep assessments up-to-date; (3) how inadequate assumptions about human behaviors and co-exposures contribute to underestimates of exposure; and (4) that insufficient models of toxicokinetics similarly affect exposure estimates.

CONCLUSION

We identified key issues that impact capacity to conduct scientifically robust exposure assessments. These issues must be addressed with scientific or policy approaches to improve estimates of exposure and protect public health.

A science-based agenda for health-protective chemical assessments and decisions: overview and consensus statement

The manufacture and production of industrial chemicals continues to increase, with hundreds of thousands of chemicals and chemical mixtures used worldwide, leading to widespread population exposures and resultant health impacts. Low-wealth communities and communities of color often bear disproportionate burdens of exposure and impact; all compounded by regulatory delays to the detriment of public health. Multiple authoritative bodies and scientific consensus groups have called for actions to prevent harmful exposures via improved policy approaches. We worked across multiple disciplines to develop consensus recommendations for health-protective, scientific approaches to reduce harmful chemical exposures, which can be applied to current US policies governing industrial chemicals and environmental pollutants. This consensus identifies five principles and scientific recommendations for improving how agencies like the US Environmental Protection Agency (EPA) approach and conduct hazard and risk assessment and risk management analyses: (1) the financial burden of data generation for any given chemical on (or to be introduced to) the market should be on the chemical producers that benefit from their production and use; (2) lack of data does not equate to lack of hazard, exposure, or risk; (3) populations at greater risk, including those that are more susceptible or more highly exposed, must be better identified and protected to account for their real-world risks; (4) hazard and risk assessments should not assume existence of a "safe" or "no-risk" level of chemical exposure in the diverse general population; and (5) hazard and risk assessments must evaluate and account for financial conflicts of interest in the body of evidence. While many of these recommendations focus specifically on the EPA, they are general principles for environmental health that could be adopted by any agency or entity engaged in exposure, hazard, and risk assessment. We also detail recommendations for four priority areas in companion papers (exposure assessment methods, human variability assessment, methods for quantifying non-cancer health outcomes, and a framework for defining chemical classes). These recommendations constitute key steps for improved evidence-based environmental health decision-making and public health protection.

Cumulative Impacts of Diverse Land Uses in British Columbia, Canada: Application of the "EnviroScreen" Method

(1) Objectives: Cumulative impacts refer to the legacies of land use decisions on environmental, community and health values. New integrative impact assessment tools are required to assess cumulative impacts on diverse values to meet sustainability goals in the 21st century. In this contribution, the CalEnviroScreen methodology-a screening tool capable of merging environmental, socioeconomic and health data-is applied to Local Health Areas in British Columbia, Canada. (2) Methods: The CalEnviroScreen is a method that standardizes environmental, socioeconomic and health data to depict an indicator's percentile rank in the distribution of all units of analysis. The method combines indicators to measure four dimensions of pressure: environmental exposures, environmental effects, socioeconomic conditions, and sensitive populations (i.e., health outcomes). We create two versions of EnviroScreen: one following the CalEnviroScreen suite of indicators, and another that uses nuanced indicators to approximate the realities of industrial land uses present in British Columbia. BCEnviroScreen scores are plotted by race/ethnicity to understand potential racial inequities in cumulative exposures. (3) Results: The BCEnviroScreen has a greater likelihood of quantifying the cumulative impacts of diverse industries and land uses present across resource-dependent parts of the province, relative to the more urban-centric CalEnviroScreen indicator suite. Analyzing the distribution of BCEnviroScreen scores by race/ethnicity suggests that visible minority populations may be inequitably exposed to cumulative impacts in BC. (4) Conclusion: EnviroScreen tools hold significant potential to influence Canadian environmental health policy. This research demonstrates the applicability of the tool to British Columbia and other jurisdictions, illustrates how indicators can be tailored to better represent regional context, and shows how the tool can be used to screen for potential environmental health injustices.

Exposure monitoring toward environmental justice

Executive Order 14008, signed on 27 January 2021, established environmental justice (EJ) as a core priority of the Biden Administration. There is a need for state and federal regulators, as well as industry, to enhance risk assessment methods and exposure monitoring approaches to be more inclusive of EJ community involvement and more representative of EJ community exposures. Cumulative risk assessment models are critical for understanding the unique interaction between chemical exposures and nonchemical stressors that EJ communities encounter daily. Enhanced environmental monitoring with personal and portable sensors, especially when deployed using community partnerships, can capture chemical exposures with sufficient resolution to characterize exposures down to the neighborhood level. Use of internet-linked sensors will also require thoughtful advances in management of big data to inform meaningful and time-sensitive decisions. Integr Environ Assess Manag 2022;18:858-862. © 2021 SETAC.

Revealing the racial and spatial disparity in pediatric asthma: A Kansas City case study

Black and other socially disadvantaged children are disproportionately burdened by high rates of pediatric asthma. Intraurban variation in environmental risk factors and limited access to high-resolution health data make it difficult to identify vulnerable patients, communities, or the immediate exposures that may contribute to pediatric asthma exacerbation. This article presents a novel, interdisciplinary health disparities research and intervention strategy applied to the problem of pediatric asthma in Kansas City. First, address-level electronic health records from a major children's hospital in the Kansas City region are used to map the distribution of asthma encounters in 2012 at a high spatial resolution. Census tract Environmental Justice Screening Method (EJSM) indicators are then developed to scan for patterns in both the population health risks and vulnerabilities that may contribute to the burden of asthma in different communities. A Bayesian Profile Regression cluster analysis is used to systematically explore the complex relationships between census tract EJSM indicators and pediatric asthma incidence rates, helping to identify population characteristics and risk factors associated with both high and low rates of pediatric asthma throughout the region. The EJSM scanning exercise and BPR analysis demonstrate that each community faces a distinct set of risks and vulnerabilities that can contribute to the rate of acute pediatric asthma acute care encounters, providing targets for research and intervention. It is clear, however, that different forms of social disadvantage are driving high rates of pediatric asthma, which is closely tied to uneven development patterns and racial residential segregation. The results provide a starting point for designing place-based health disparities research and intervention strategies catered to the unique needs of vulnerable patients and communities; disparities-focused research and intervention strategies that leverage local knowledge and resources through community-based practices.

Honeybees as a biomonitoring species to assess environmental airborne pollution in different socioeconomic city districts

Honeybees have been used in Europe as environmental bioindicators for heavy metals and polycyclic aromatic hydrocarbons (PAHs). However, their potential has been little explored in North America, especially between environments which have similar pollution levels. Many urban residents and stakeholders are concerned with air quality, mainly in regard to gradients of exposure to industrial pollution between deprived and privileged subpopulation. Thus, the aim of this study was to evaluate the use of honeybees as bioindicators to assess exposure to heavy metals and PAHs in Québec City, Canada, in different socioeconomic districts of Quebec City (deprivation index). Honeybees were sampled over a 5-month period (May to September) at six locations distributed in two urban areas that are distinct geomorphologically and socioeconomically (lower town socio-economically deprived and upper town socioeconomically privileged) and two control rural locations. Six PAHs were analyzed by ultra-performance liquid chromatography (UPLC), while four heavy metals were analyzed by inductively coupled plasma mass spectrometry. Arsenic was the only measured pollutant that showed a significant gradient of exposure between rural and urban environments, but also between the two urban areas. Furthermore, we were able to detect significant differences at certain sampling times for heavy metals and PAHs. Overall, the results show that honeybees are sensitive enough to detect differences between the differential urban environments of a city presumed to have similar pollution levels and therefore could be used when potential socio-environmental inequalities are present.

Accounting for Health Risk Inequality in Regulatory Impact Analysis: Barriers and Opportunities

There has been increasing interest in accounting for inequality in health risks and benefits within regulatory impact analyses, both given more general interest in the distributions of benefits and growing concerns about inequity (defined as those inequalities deemed unjust or unfair) and environmental injustice (in this context, those health risk inequalities that are correlated with race/ethnicity and certain other sociodemographic factors). Although there has been growing literature on this topic, there has been limited progress in practice, and the lack of quantification limits consideration of inequality in the policy process. Controversy remains regarding the best approaches to formally incorporate inequality, when these approaches should be used, and even whether it makes sense to quantify inequality in this context. The objective of this article is to review the literature on approaches for incorporating estimates of, and concerns for, inequality into regulatory impact analyses, especially those where environmental justice considerations are relevant, and consider the interpretation of these approaches and the implications for decision making. Using the case example of the Transportation and Climate Initiative, a collaboration among Northeast and Mid-Atlantic states to reduce carbon emissions from the transportation sector, multiple strategies are described that could be used to shed light on health risk inequality and inequity, consider them in pending policy decisions, and evaluate their implications for the policy or instrument choice. Given appropriate contextualization and acknowledgment of the multidimensionality of equity, quantitative inequality indicators can provide meaningful insight about both inequality and inequity in health risks.

Evolving Science and Practice of Risk Assessment

Managing public health risks from environmental contaminants has historically relied on a risk assessment process defined by the regulatory context in which these risks are assessed. Risk assessment guidance follows a straightforward, chemical-by-chemical approach to inform regulatory decisions around the question "what is the risk-based concentration protective of human and ecological health outcomes?" Here we briefly summarize regulatory risk assessment in the context of innovative risk assessment approaches based on an evolving understanding of the underlying scientific disciplines that support risk analysis more broadly. We discuss scientific versus regulatory tensions in the application of these approaches for future risk assessments, and challenges in translating our improved understanding of the underlying scientific complexity to the regulatory landscape to better inform decision making that extends beyond conventional regulatory mandates.

Factors associated with self-reported exposure to chemical substances at work in Brazil: results from the National Health Survey, 2013

OBJECTIVE

To describe the prevalence of self-reported exposure to chemical substances at work and its associated factors in a sample of Brazilian adults that participated in the National Health Survey, conducted between 2013 and 2014.

METHODS

Our sample consisted of adults aged 18 years or older that answered question E1 of module E: “In the week of July 21-27, 2013 (reference week), did you work as regular employee or intern for at least an hour in any activity paid with cash?” Sociodemographic data, situation and health behaviors were analyzed with single and multivariate binary logistic regression. The model was adjusted by the variables of all groups, adopting a 5% significance level. The values of odds ratio (OR) and respective confidence intervals were obtained.

RESULTS

Women (OR = 0.74; 95%CI 0.66–0.82) had a lower chance of exposure to chemicals. The highest chances were observed in groups with no instruction or that attended up to middle-school (OR = 1.77; 95%CI 1.50–2.08), high school (OR = 1.62; 95%CI 1.37–1.91), age between 25 and 54 years (OR = 1.26; 95%CI 1.07–1.48), current smokers (OR = 1.21; 95%CI 1.07–1.37), who reported tiredness (OR = 1.35; 95%CI 1.21–1.50), hearing difficulties (OR = 1.24; 95%CI 1.04–1.48) and who reported having suffered an accident at work (OR = 2.00; 95%CI 1.57–2.54).

CONCLUSIONS

The unprecedented results cover the entire workforce. Positive associations with hearing loss, smoking and history of work accidents are consistent, as well as the inverse association with education level and gender differences. The absence of association with asthma was surprising. To fill gaps in investigations on chronic non-communicable diseases, we suggested improving the PNS collection instrument in the occupational dimension.

Independent and joint contributions of economic, social and physical environmental characteristics to mortality in the Detroit Metropolitan Area: A study of cumulative effects and pathways

OBJECTIVE

Previous studies have demonstrated associations between race-based residential segregation, neighborhood socioeconomic and physical environmental characteristics, and mortality. Relatively few studies have examined independent and joint effects of these multiple neighborhood characteristics and mortality, including potential mediating pathways. In this study we examine the extent to which associations between race-based residential segregation and all-cause mortality may be explained by multiple socioeconomic indicators and exposure to air pollutants.

METHODS

Drawing on data from multiple sources, we assessed bivariate associations between race-based residential segregation (operationalized as percent non-Hispanic Black), education (percent with graduate equivalency degree), poverty (percent below poverty), income inequality (GINI coefficient) and air pollution (ambient PM2.5) and age adjusted all-cause, all race mortality (henceforth all cause mortality) at the census tract level in the Detroit Metropolitan Area. We used inequality curves to assess the (in)equitable distribution of economic and environmental characteristics by census tract racial composition. Finally, we used generalized estimating equations (GEE) to examine independent and joint associations among percent NHB, education, income inequality, and air pollution to all-cause mortality, and test for mediating effects.

RESULTS

Bivariate associations between racial composition, education, poverty, income inequality, PM2.5 and all-cause mortality were statistically significant. Census tracts with higher concentrations of NHB residents had significantly lower educational attainment, higher poverty, and greater exposure to PM2.5. In multivariate models, education, income inequality and PM2.5 fully attenuated associations between racial composition and all-cause mortality.

CONCLUSIONS

Results are consistent with the hypothesis that race-based residential segregation is associated with heightened all-cause mortality, and that those effects are mediated by education, income inequality, and exposure to air pollution at the census tract level. Public health and cross-sector interventions to eliminate race-based residential segregation or to eliminate the maldistribution of educational and economic resources, and environmental exposures, across census tracts could substantially reduce regional inequities in all-cause mortality.

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.

Use of an Exposome Approach to Understand the Effects of Exposures From the Natural, Built, and Social Environments on Cardio-Vascular Disease Onset, Progression, and Outcomes

Obesity, diabetes, and hypertension have increased by epidemic proportions in recent years among African Americans in comparison to Whites resulting in significant adverse cardiovascular disease (CVD) disparities. Today, African Americans are 30% more likely to die of heart disease than Whites and twice as likely to have a stroke. The causes of these disparities are not yet well-understood. Improved methods for identifying underlying risk factors is a critical first step toward reducing Black:White CVD disparities. This article will focus on environmental exposures in the external environment and how they can lead to changes at the cellular, molecular, and organ level to increase the personal risk for CVD and lead to population level CVD racial disparities. The external environment is defined in three broad domains: natural (air, water, land), built (places you live, work, and play) and social (social, demographic, economic, and political). We will describe how environmental exposures in the natural, built, and social environments "get under the skin" to affect gene expression though epigenetic, pan-omics, and related mechanisms that lead to increased risk for adverse CVD health outcomes and population level disparities. We also will examine the important role of metabolomics, proteomics, transcriptomics, genomics, and epigenomics in understanding how exposures in the natural, built, and social environments lead to CVD disparities with implications for clinical, public health, and policy interventions. In this review, we apply an exposome approach to Black:White CVD racial disparities. The exposome is a measure of all the exposures of an individual across the life course and the relationship of those exposures to health effects. The exposome represents the totality of exogenous (external) and endogenous (internal) exposures from conception onwards, simultaneously distinguishing, characterizing, and quantifying etiologic, mediating, moderating, and co-occurring risk and protective factors and their relationship to disease. Specifically, it assesses the biological mechanisms and underlying pathways through which chemical and non-chemical environmental exposures are associated with CVD onset, progression and outcomes. The exposome is a promising approach for understanding the complex relationships among environment, behavior, biology, genetics, and disease phenotypes that underlie population level, Black: White CVD disparities.

Nephrotoxic effects caused by co-exposure to noise and toluene in New Zealand white rabbits: A biochemical and histopathological study

The biological and renal effects made by simultaneous and non-simultaneous exposure to toluene and noise were investigated. Twenty-four New Zealand white rabbits were exposed to 100 dB of white noise and 1000 ppm of toluene vapor for two weeks. The examined biochemical factors were urea, uric acid, creatinine, glucose, triglyceride, cholesterol, and albumin serum levels, measured on different days after the end of the exposure. Moreover, glutathione peroxidase activity (GPX), malondialdehyde dismutase activity (MDA), and superoxide dismutase (SOD) parameters were measured in the kidney tissue. The hematoxylin and eosin staining method was used for histopathological experiments. Overall, the noise increased albumin, uric acid, creatinine, and glucose levels, but it decreased urea, cholesterol, and triglyceride levels. Toluene decreased albumin, uric acid, and urea levels, while it increased creatinine, triglyceride, cholesterol, and glucose levels. Simultaneous exposure to noise and toluene decreased albumin, uric acid, cholesterol, and urea levels, whereas it increased creatinine, glucose, and triglyceride levels. GPX, MDA, and SOD levels increased by simultaneous and non-simultaneous exposure to noise and toluene. Furthermore, massive tubular degeneration, tubular cell vacuolization, glomerular disorganization, congestion, glomerular cell shrinkage, and unclear brush border were detected in the kidney tissue.

Systematic probabilistic risk assessment of pesticide residues in tea leaves

Multiple pesticide residues are frequently present in tea leaves and while the majority of residues satisfy Taiwan's current health regulations, there are potential health effects from pesticide exposure that are of great concern for tea drinkers. We undertook a systematic probabilistic risk assessment of 59 pesticides in tea leaves from 1629 tea leaf samples obtained by Taiwan's Food and Drug Administration in two monitoring surveys in 2015. Bayesian statistics used a Markov Chain Monte Carlo approach to estimate posterior distributions of pesticide residues in tea leaves, lifetime average daily doses and hazard quotients (HQs) of evaluated pesticides. We classified 95th percentile values of HQs into three categories: 0 < HQ < 0.5, 0.5 ≤ HQ ≤ 1 and 1 < HQ. The 95th percentiles of HQs for triazophos (3.39), carbofuran (2.04) and endosulfan (1.80) exceeded 1 in the adult population; the HQ for 3-OH carbofuran was 0.97 and was less than 0.5 for the remaining 55 pesticides. The health risk posed by pesticide residues for tea drinkers is negligible, if triazophos, carbofuran, endosulfan, and 3-OH carbofuran residues satisfy regulatory standards. However, five legacy pesticides, DDT, methomyl, carbofuran, dicofol and endosulfan, were identified. To reduce uncertainties, this study combined Bayesian statistics with a mode of action approach for systematic risk assessment of co-exposure to multiple pesticide residues in tea leaf samples. Measuring pesticide transfer rates will improve the quality of future risk assessments concerning residues in tea leaves. Appropriate management of pesticides in Taiwanese tea farms and monitoring of pesticide residues in imported tea is warranted to protect Taiwan's tea drinkers.

Associations between sociodemographic characteristics and exposures to PBDEs, OH-PBDEs, PCBs, and PFASs in a diverse, overweight population of pregnant women

Exposures to persistent organohalogen chemicals during pregnancy are associated with adverse health effects. Low-income, minority women with pre-existing co-morbidities may be particularly vulnerable to these exposures, but have historically been understudied. We aimed to characterize exposures to multiple chemical classes among a sample of ethnically diverse, lower income, overweight or obese pregnant women. Serum concentrations of polybrominated diphenyl ethers (PBDEs) and their hydroxylated metabolites (OH-PBDEs), polychlorinated biphenyls (PCBs), and poly- and perfluoroalkyl substances (PFASs) were measured in 98 pregnant women (California; 2011-2013). Aggregate exposures were evaluated using correlational clustering, a "chemical burden" score, and PCA. Associations between sociodemographic characteristics and individual and aggregate exposures were evaluated using multivariable linear regression. Clustering and PCA both produced four groupings: (PC1) PBDEs/OH-PBDEs, (PC2) PCBs, (PC3) PFNA/PFOA/PFDeA, (PC4) PFHxS/PFOS. Race/ethnicity and prepregnancy BMI were associated with PBDEs, OH-PBDEs and PC1. Maternal age was associated with PCBs and PC2. Parity was associated with PBDEs, OH-PBDEs and PC2. Poverty was negatively associated with PCBs, whereas food insecurity was positively associated with PFOS. We observed variations in sociodemographic profiles of exposures by chemical class and weak across-class correlations. These findings have implications for epidemiologic studies of chemical mixtures and for exposure reduction strategies.

The Use of Geographic Information Systems for Spatial Ecological Risk Assessments: An Example from the Athabasca Oil Sands Area in Canada

There is an acknowledged need in ecotoxicology for methods that integrate spatial analyses in risk assessment. This has resulted in the emergence of landscape ecotoxicology, a subdiscipline of ecotoxicology. However, landscape ecotoxicology has yet to become common practice in risk assessment due to the underdevelopment of techniques and a lack of standardized methods. In the present study, we demonstrate how geographic information systems (GISs) can serve as a standardized platform to integrate data, assess spatial patterns of ecotoxicological data for multiple species, and assess relationships between chemical mixture exposures and effects on biota for landscape ecotoxicological risks assessment. We use data collected under the Joint Oil Sands Monitoring Program in the Athabasca Oil Sands Region in Alberta, Canada. This dataset is composed of concentrations of contaminants including metals and polycyclic aromatic compounds, and health endpoints measured in 1100 biological samples, including tree swallows, amphibians, gull and tern eggs, plants, and mammals. We present 3 examples using a GIS as a platform and geospatial analysis to: 1) integrate data and assess spatial patterns of contaminant exposure in the region, 2) assess spatial patterns of exposures to complex mixtures, and 3) examine patterns of exposures and responses across the landscape. We summarize the methods used in the present study into a workflow for ease of use. The GIS methods allow researchers to identify hot spots of contamination, use georeferenced monitoring data to derive quantitative exposure-response relationships, and assess complex exposures with more realism. Environ Toxicol Chem 2019;38:2797-2810. © 2019 SETAC.

State-of-the-Science Review of Non-Chemical Stressors Found in a Child's Social Environment

Background: Children are exposed to chemical and non-chemical stressors from their built, natural, and social environments. Research is needed to advance our scientific understanding of non-chemical stressors, evaluate how they alter the biological response to a chemical stressor, and determine how they impact children’s health and well-being. To do this, we conducted a state-of-the-science review of non-chemical stressors found in a child’s social environment. Methods: Studies eligible for inclusion in this review were identified through a search of the peer-reviewed literature using PubMed and PsycINFO. Combinations of words associated with non-chemical stressors and children were used to form search strings. Filters were used to limit the search to studies published in peer-reviewed journals from 2000–2016 and written in English. Publications found using the search strings and filters went through two rounds of screening. Results: A total of 146 studies met the inclusion criteria. From these studies, 245 non-chemical stressors were evaluated. The non-chemical stressors were then organized into 13 general topic areas: acculturation, adverse childhood experiences, economic, education, family dynamics, food, greenspace, neighborhood, social, stress, urbanicity, violence, and other. Additional information on health outcomes, studies evaluating both chemical and non-chemical stressors, and animal studies are provided. This review provides evidence that non-chemical stressors found in a child’s social environment do influence their health and well-being in both beneficial (e.g., salutatory effects of greenspace and social support) and adverse (e.g., poor relationships between health and selected non-chemical stressors such as economics, educational attainment, exposure to violence, stress) ways. Conclusions: This literature review identified a paucity of studies addressing the combined effects of chemical and non-chemical stressors and children’s health and well-being. This literature review was further complicated by inconsistencies in terminology, methodologies, and the value of non-chemical stressor research in different scientific disciplines. Despite these limitations, this review showed the importance of considering non-chemical stressors from a child’s social environment when addressing children’s environmental health considerations.

The Cumulative Risk of Chemical and Nonchemical Exposures on Birth Outcomes in Healthy Women: The Fetal Growth Study

Metals, stress, and sociodemographics are commonly studied separately for their effects on birth outcomes, yet often jointly contribute to adverse outcomes. This study analyzes two methods for measuring cumulative risk to understand how maternal chemical and nonchemical stressors may contribute to small for gestational age (SGA). SGA was calculated using sex-specific fetal growth curves for infants of pregnant mothers (n = 2562) enrolled in the National Institute of Child Health and Human Development (NICHD) Fetal Growth Study. The exposures (maternal lead, mercury, cadmium, Cohen's perceived stress, Edinburgh depression scores, race/ethnicity, income, and education) were grouped into three domains: metals, psychosocial stress, and sociodemographics. In Method 1 we created cumulative risk scores using tertiles. Method 2 employed weighted quantile sum (WQS) regression. For each method, logistic models were built with three exposure domains individually and race/ethnicity, adjusting for age, parity, pregnancy weight gain, and marital status. The adjusted effect of overall cumulative risk with three domains, was also modeled using each method. Sociodemographics was the only exposure associated with SGA in unadjusted models ((odds ratio) OR: 1.35, 95% (confidence interval) CI: 1.08, 1.68). The three cumulative variables in adjusted models were not significant individually, but the overall index was associated with SGA (OR: 1.17, 95% CI: 1.02, 1.35). In the WQS model, only the sociodemographics domain was significantly associated with SGA. Sociodemographics tended to be the strongest risk factor for SGA in both risk score and WQS models.

Effects of environmental stressors on stem cells

Environmental toxicants are ubiquitous, and many are known to cause harmful health effects. However, much of what we know or think we know concerning the targets and long-term effects of exposure to environmental stressors is sadly lacking. Toxicant exposure may have health effects that are currently mischaracterized or at least mechanistically incompletely understood. While much of the recent excitement about stem cells (SCs) focuses on their potential as therapeutic agents, they also offer a valuable resource to give us insight into the mechanisms and risks of toxicant effects. Not only as a response to the increasing ethical pressure to reduce animal testing, SC studies allow us valuable insight into the true effects of human exposure to environmental stressors under controlled conditions. We present a review of the history of publications on the effects of environmental stressors on SCs, followed by a consolidation of the literature over the past five years on a subset of key environmental stressors of importance to human health and their effects on both embryonic and tissue SCs. The review will make constructive suggestions as to areas of toxicant research where further studies are needed, as well as making indications of the potential utility for advancing knowledge and directing research on environmental toxicology.

Epidemiologically-informed cumulative risk hypertension models simulating the impact of changes in metal, organochlorine, and non-chemical exposures in an environmental justice community

Blood pressure is a leading risk factor for cardiovascular disease, influenced by chemical and non-chemical stressors. Exposure reduction strategies can potentially improve public health, but there are analytical challenges in developing quantitative models of health benefits, including the need for detailed multi-stressor exposure models, corresponding health evidence, and methods to simulate changes in exposure and resultant health benefits. These challenges are pronounced in low-income urban communities, where residents are often simultaneously exposed to numerous chemical and non-chemical stressors. For New Bedford (Massachusetts, USA), a low-income community near a Superfund site, we simulated geographically-resolved individual data, and applied previously published structural equation models developed from National Health and Nutrition Examination Survey (NHANES) data. These models simultaneously predict exposures to multiple chemicals (e.g., lead (Pb), cadmium (Cd), and polychlorinated biphenyls (PCBs)) and non-chemical factors (e.g., socioeconomic status), and determine their combined effects on blood pressure. We then modeled counterfactual scenarios reducing exposures and estimated the resulting changes in blood pressure distribution in the community. Results indicated small shifts in mean blood pressure and percentage of normotensive individuals with a reduction of Pb and/or PCB exposure. For example, a reduction in PCB to the lowest 10th percentile exposure in the NHANES resulted in a 2.4 mm Hg shift in systolic blood pressure (SBP), corresponding with 3% fewer individuals with SBP in the Stage 2 hypertension category [SBP ≥140]. Our model also emphasized the importance of the multi-stressor framework by simulating benefits of reductions in smoking rates, given positive associations with Pb and Cd but inverse associations with body mass index and blood pressure. This research demonstrates the ability to jointly consider chemical and non-chemical exposures and their impact on cardiovascular health, using approaches generalizable to other cumulative risk assessment applications.

The utility of a system dynamics approach for understanding cumulative health risk from exposure to environmental hazards

The potential of system dynamics modeling to advance our understanding of cumulative risk in the service of optimal health is discussed. The focus is on exploring system dynamics modeling as a systems science methodology that can provide a framework for examining the complexity of real-world social and environmental exposures among populations-particularly those exposed to multiple disparate sources of risk. The discussion also examines how system dynamics modeling can engage a diverse body of key stakeholders throughout the modeling process, promoting the collective assessment of assumptions and systematic gathering of critical data. Though not a panacea, system dynamics modeling provides a promising methodology to complement traditional research methods in understanding cumulative health effects from exposure to multiple environmental and social stressors.

Hybrid Resiliency-Stressor Conceptual Framework for Informing Decision Support Tools and Addressing Environmental Injustice and Health Inequities

While structural factors may drive health inequities, certain health-promoting attributes of one's "place" known as salutogens may further moderate the cumulative impacts of exposures to socio-environmental stressors that behave as pathogens. Understanding the synergistic relationship between socio-environmental stressors and resilience factors is a critical component in reducing health inequities; however, the catalyst for this concept relies on community-engaged research approaches to ultimately strengthen resiliency and promote health. Furthermore, this concept has not been fully integrated into environmental justice and cumulative risk assessment screening tools designed to identify geospatial variability in environmental factors that may be associated with health inequities. As a result, we propose a hybrid resiliency-stressor conceptual framework to inform the development of environmental justice and cumulative risk assessment screening tools that can detect environmental inequities and opportunities for resilience in vulnerable populations. We explore the relationship between actual exposures to socio-environmental stressors, perceptions of stressors, and one's physiological and psychological stress response to environmental stimuli, which collectively may perpetuate health inequities by increasing allostatic load and initiating disease onset. This comprehensive framework expands the scope of existing screening tools to inform action-based solutions that rely on community-engaged research efforts to increase resiliency and promote positive health outcomes.

Cumulative Risk and Impact Modeling on Environmental Chemical and Social Stressors

PURPOSE OF REVIEW

The goal of this review is to identify cumulative modeling methods used to evaluate combined effects of exposures to environmental chemicals and social stressors. The specific review question is: What are the existing quantitative methods used to examine the cumulative impacts of exposures to environmental chemical and social stressors on health?

RECENT FINDINGS

There has been an increase in literature that evaluates combined effects of exposures to environmental chemicals and social stressors on health using regression models; very few studies applied other data mining and machine learning techniques to this problem. The majority of studies we identified used regression models to evaluate combined effects of multiple environmental and social stressors. With proper study design and appropriate modeling assumptions, additional data mining methods may be useful to examine combined effects of environmental and social stressors.

Towards environmental health equity in health impact assessment: innovations and opportunities

OBJECTIVES

As global environmental change drives inequitable health outcomes, novel health equity assessment methodologies are increasingly required. We review literatures on equity-focused HIA to clarify how equity is informing HIA practice, and to surface innovations for assessing health equity in relation to a range of exposures across geographic and temporal scales.

METHODS

A narrative review of the health equity and HIA literatures analysed English articles published between 2003 and 2017 across PubMed, PubMed Central, Biomed Central and Ovid Medline. Title and abstract reviews of 849 search results yielded 89 articles receiving full text review.

RESULTS

Considerations of equity in HIA increased over the last 5 years, but equity continues to be conflated with health disparities rather than their root causes (i.e. inequities). Lessons from six literatures to inform future HIA practice are described: HIA for healthy cities, climate change vulnerability assessment, cumulative health risk assessment, intersectionality-based policy analysis, corporate health impact assessment and global health impact assessment.

CONCLUSIONS

Academic reporting on incorporating equity in HIA practice has been limited. Nonetheless, significant methodological advancements are being made to examine the health equity implications of multiple environmental exposures.

A Case Study Application of the Aggregate Exposure Pathway (AEP) and Adverse Outcome Pathway (AOP) Frameworks to Facilitate the Integration of Human Health and Ecological End Points for Cumulative Risk Assessment (CRA)

Cumulative risk assessment (CRA) methods promote the use of a conceptual site model (CSM) to apportion exposures and integrate risk from multiple stressors. While CSMs may encompass multiple species, evaluating end points across taxa can be challenging due to data availability and physiological differences among organisms. Adverse outcome pathways (AOPs) describe biological mechanisms leading to adverse outcomes (AOs) by assembling causal pathways with measurable intermediate steps termed key events (KEs), thereby providing a framework for integrating data across species. In this work, we used a case study focused on the perchlorate anion (ClO4-) to highlight the value of the AOP framework for cross-species data integration. Computational models and dose-response data were used to evaluate the effects of ClO4- in 12 species and revealed a dose-response concordance across KEs and taxa. The aggregate exposure pathway (AEP) tracks stressors from sources to the exposures and serves as a complement to the AOP. We discuss how the combined AEP-AOP construct helps to maximize the use of existing data and advances CRA by (1) organizing toxicity and exposure data, (2) providing a mechanistic framework of KEs for integrating data across human health and ecological end points, (3) facilitating cross-species dose-response evaluation, and (4) highlighting data gaps and technical limitations.

Associations between socio-demographic characteristics and chemical concentrations contributing to cumulative exposures in the United States

Association rule mining (ARM) has been widely used to identify associations between various entities in many fields. Although some studies have utilized it to analyze the relationship between chemicals and human health effects, fewer have used this technique to identify and quantify associations between environmental and social stressors. Socio-demographic variables were generated based on U.S. Census tract-level income, race/ethnicity population percentage, education level, and age information from the 2010-2014, 5-Year Summary files in the American Community Survey (ACS) database, and chemical variables were generated by utilizing the 2011 National-Scale Air Toxics Assessment (NATA) census tract-level air pollutant exposure concentration data. Six mobile- and industrial-source pollutants were chosen for analysis, including acetaldehyde, benzene, cyanide, particulate matter components of diesel engine emissions (namely, diesel PM), toluene, and 1,3-butadiene. ARM was then applied to quantify and visualize the associations between the chemical and socio-demographic variables. Census tracts with a high percentage of racial/ethnic minorities and populations with low income tended to have higher estimated chemical exposure concentrations (fourth quartile), especially for diesel PM, 1,3-butadiene, and toluene. In contrast, census tracts with an average population age of 40-50 years, a low percentage of racial/ethnic minorities, and moderate-income levels were more likely to have lower estimated chemical exposure concentrations (first quartile). Unsupervised data mining methods can be used to evaluate potential associations between environmental inequalities and social disparities, while providing support in public health decision-making contexts.

Understanding the relationships between water quality, recreational fishing practices, and human health in Phoenix, Arizona

Across the United States, recreational freshwater fisheries are not only an important leisure activity, but can also provide a relatively inexpensive source of protein in local diets. However, recreational freshwater fisheries are generally not well-monitored in terms of fish consumption vs. catch and release, nor are all recreational surface waters regularly monitored for the presence of potentially harmful contaminants in water or fishes. In six urban lakes that support recreational fisheries in Phoenix, Arizona, a majority of surveyed anglers reported eating recreationally caught fishes, even though they thought the water might be polluted. Surface water samples collected from the six urban recreational fishery lakes showed varying levels of organic contaminants, including pesticides, polychlorinated biphenyls, polycyclic aromatic hydrocarbons, and phthalates. As many Phoenix urban recreational fisheries lakes and ponds are located in low income and high minority neighborhoods, the results of this pilot study could be used to inform urban fisheries management and other agencies of the potential need for fish consumption advisories, inform actions to improve water quality in urban lakes and ponds that support urban fisheries, and support further research and monitoring, in order to reduce potential risks to public health.

Connecting the Dots: Linking Environmental Justice Indicators to Daily Dose Model Estimates

Many different quantitative techniques have been developed to either assess Environmental Justice (EJ) issues or estimate exposure and dose for risk assessment. However, very few approaches have been applied to link EJ factors to exposure dose estimate and identify potential impacts of EJ factors on dose-related variables. The purpose of this study is to identify quantitative approaches that incorporate conventional risk assessment (RA) dose modeling and cumulative risk assessment (CRA) considerations of disproportionate environmental exposure. We apply the Average Daily Dose (ADD) model, which has been commonly used in RA, to better understand impacts of EJ indicators upon exposure dose estimates and dose-related variables, termed the Environmental-Justice-Average-Daily-Dose (EJ-ADD) approach. On the U.S. nationwide census tract-level, we defined and quantified two EJ indicators (poverty and race/ethnicity) using an EJ scoring method to examine their relation to census tract-level multi-chemical exposure dose estimates. Pollutant doses for each tract were calculated using the ADD model, and EJ scores were assigned to each tract based on poverty- or race-related population percentages. Single- and multiple-chemical ADD values were matched to the tract-level EJ scores to analyze disproportionate dose relationships and contributing EJ factors. We found that when both EJ indicators were examined simultaneously, ADD for all pollutants generally increased with larger EJ scores. To demonstrate the utility of using EJ-ADD on the local scale, we approximated ADD levels of lead via soil/dust ingestion for simulated communities with different EJ-related scenarios. The local-level simulation indicates a substantial difference in exposure-dose levels between wealthy and EJ communities. The application of the EJ-ADD approach can link EJ factors to exposure dose estimate and identify potential EJ impacts on dose-related variables.

Population-based comparison of biomarker concentrations for chemicals of concern among Latino-American and non-Hispanic white children

Differences in cultural and economic status may place ethnic subgroups of children at higher risk for exposure, leading to heightened health risks, and health inequities. Although Latino-Americans represent 22% of all children in the United States, few studies have explored within-group differences in their exposure to toxicants. Using socio-demographic and biomarker data from the National Health and Nutrition Examination Survey from 1999 to 2008, we characterized determinants of health and estimated geometric means of environmental contaminant biomarkers (blood concentrations of lead and mercury, serum concentrations of dichlorodiphenyldichloroethylene [p,p'-DDE] and cotinine, and urinary metabolites of organophosphate [OP] pesticides and polycyclic aromatic hydrocarbons [PAHs]) among 4,257 Mexican American (MA), 677 Other Latino-American (OL), and 3,370 Non-Hispanic White (NHW) children. MAs had the lowest levels of health insurance coverage and regular access to health care, and largest household size compared to NHWs and OLs. MAs had higher levels of p,p'-DDE, lead, and cadmium while OLs had higher estimates of mercury relative to other groups. MAs had higher urinary metabolite concentrations of 2-hydroxynaphthalene; otherwise MAs and OLs had lower concentrations of PAHs. NHWs had higher levels of cotinine and dimethylthiophosphate. For other OP metabolites, differences among groups were less clear. Lead and p,p'-DDE exposure differences likely reflect later and less regulatory control of these chemicals in Latin America. Additionally, poor quality housing with lead paint is more common in economically disadvantaged subpopulations. Dietary habits are possible sources of differential cadmium, mercury, and organophosphate exposure. Cotinine exposure differences by income and U.S.- vs. foreign-born may represent increased acculturation. These results, coupled with additional research on exposure sources may contribute to refinement of environmental health promotion programs for the fast-growing Latino-American population.

A developmental perspective on early-life exposure to neurotoxicants

BACKGROUND

Studies of early-life neurotoxicant exposure have not been designed, analyzed, or interpreted in the context of a fully developmental perspective.

OBJECTIVES

The goal of this paper is to describe the key principles of a developmental perspective and to use examples from the literature to illustrate the relevance of these principles to early-life neurotoxicant exposures.

METHODS

Four principles are discussed: 1) the effects of early-life neurotoxicant exposure depend on a child's developmental context; 2) deficits caused by early-life exposure initiate developmental cascades that can lead to pathologies that differ from those observed initially; 3) early-life neurotoxicant exposure has intra-familial and intergenerational impacts; 4) the impacts of early-life neurotoxicant exposure influence a child's ability to respond to future insults. The first principle is supported by considerable evidence, but the other three have received much less attention.

DISCUSSION

Incorporating a developmental perspective in studies of early-life neurotoxicant exposures requires prospective collection of data on a larger array of covariates than usually considered, using analytical approaches that acknowledge the transactional processes between a child and the environment and the phenomenon of developmental cascades.

CONCLUSION

Consideration of early-life neurotoxicant exposure within a developmental perspective reveals that many issues remain to be explicated if we are to achieve a deep understanding of the societal health burden associated with early-life neurotoxicant exposures.

Contributions of a Child's Built, Natural, and Social Environments to Their General Cognitive Ability: A Systematic Scoping Review

The etiology of a child’s cognitive ability is complex, with research suggesting that it is not attributed to a single determinant or even a defined period of exposure. Rather, cognitive development is the product of cumulative interactions with the environment, both negative and positive, over the life course. The aim of this systematic scoping review was to collate evidence associated with children’s cognitive health, including inherent factors as well as chemical and non-chemical stressors from the built, natural, and social environments. Three databases were used to identify recent epidemiological studies (2003–2013) that examined exposure factors associated with general cognitive ability in children. Over 100 factors were evaluated from 258 eligible studies. We found that recent literature mainly assessed the hypothesized negative effects of either inherent factors or chemical exposures present in the physical environment. Prenatal growth, sleep health, lead and water pollutants showed consistent negative effects. Of the few studies that examined social stressors, results consistently showed cognitive development to be influenced by both positive and negative social interactions at home, in school or the community. Among behavioral factors related to diet and lifestyle choices of the mother, breastfeeding was the most studied, showing consistent positive associations with cognitive ability. There were mostly inconsistent results for both chemical and non-chemical stressors. The majority of studies utilized traditional exposure assessments, evaluating chemical and non-chemical stressors separately. Collective evidence from a limited number of studies revealed that cumulative exposure assessment that incorporates multiple chemical and non-chemical stressors over the life course may unravel the variability in effect on cognitive development and help explain the inconsistencies across studies. Future research examining the interactions of multiple stressors within a child’s total environment, depicting a more real-world exposure, will aid in understanding the cumulative effects associated with a child’s ability to learn.

Area-level socioeconomic deprivation, nitrogen dioxide exposure, and term birth weight in New York City

Numerous studies have linked air pollution with adverse birth outcomes, but relatively few have examined differential associations across the socioeconomic gradient. To evaluate interaction effects of gestational nitrogen dioxide (NO2) and area-level socioeconomic deprivation on fetal growth, we used: (1) highly spatially-resolved air pollution data from the New York City Community Air Survey (NYCCAS); and (2) spatially-stratified principle component analysis of census variables previously associated with birth outcomes to define area-level deprivation. New York City (NYC) hospital birth records for years 2008-2010 were restricted to full-term, singleton births to non-smoking mothers (n=243,853). We used generalized additive mixed models to examine the potentially non-linear interaction of nitrogen dioxide (NO2) and deprivation categories on birth weight (and estimated linear associations, for comparison), adjusting for individual-level socio-demographic characteristics and sensitivity testing adjustment for co-pollutant exposures. Estimated NO2 exposures were highest, and most varying, among mothers residing in the most-affluent census tracts, and lowest among mothers residing in mid-range deprivation tracts. In non-linear models, we found an inverse association between NO2 and birth weight in the least-deprived and most-deprived areas (p-values<0.001 and 0.05, respectively) but no association in the mid-range of deprivation (p=0.8). Likewise, in linear models, a 10 ppb increase in NO2 was associated with a decrease in birth weight among mothers in the least-deprived and most-deprived areas of -16.2g (95% CI: -21.9 to -10.5) and -11.0 g (95% CI: -22.8 to 0.9), respectively, and a non-significant change in the mid-range areas [β=0.5 g (95% CI: -7.7 to 8.7)]. Linear slopes in the most- and least-deprived quartiles differed from the mid-range (reference group) (p-values<0.001 and 0.09, respectively). The complex patterning in air pollution exposure and deprivation in NYC, however, precludes simple interpretation of interactive effects on birth weight, and highlights the importance of considering differential distributions of air pollution concentrations, and potential differences in susceptibility, across deprivation levels.

Racial/Ethnic Disparities in Cumulative Environmental Health Impacts in California: Evidence From a Statewide Environmental Justice Screening Tool (CalEnviroScreen 1.1)

OBJECTIVES

We used an environmental justice screening tool (CalEnviroScreen 1.1) to compare the distribution of environmental hazards and vulnerable populations across California communities.

METHODS

CalEnviroScreen 1.1 combines 17 indicators created from 2004 to 2013 publicly available data into a relative cumulative impact score. We compared cumulative impact scores across California zip codes on the basis of their location, urban or rural character, and racial/ethnic makeup. We used a concentration index to evaluate which indicators were most unequally distributed with respect to race/ethnicity and poverty.

RESULTS

The unadjusted odds of living in one of the 10% most affected zip codes were 6.2, 5.8, 1.9, 1.8, and 1.6 times greater for Hispanics, African Americans, Native Americans, Asian/Pacific Islanders, and other or multiracial individuals, respectively, than for non-Hispanic Whites. Environmental hazards were more regressively distributed with respect to race/ethnicity than poverty, with pesticide use and toxic chemical releases being the most unequal.

CONCLUSIONS

Environmental health hazards disproportionately burden communities of color in California. Efforts to reduce disparities in pollution burden can use simple screening tools to prioritize areas for action.

Identifying Perceived Neighborhood Stressors Across Diverse Communities in New York City

There is growing interest in the role of psychosocial stress in health disparities. Identifying which social stressors are most important to community residents is critical for accurately incorporating stressor exposures into health research. Using a community-academic partnered approach, we designed a multi-community study across the five boroughs of New York City to characterize resident perceptions of key neighborhood stressors. We conducted 14 community focus groups; two to three in each borough, with one adolescent group and one Spanish-speaking group per borough. We then used systematic content analysis and participant ranking data to describe prominent neighborhood stressors and identify dominant themes. Three inter-related themes regarding the social and structural sources of stressful experiences were most commonly identified across neighborhoods: (1) physical disorder and perceived neglect, (2) harassment by police and perceived safety and (3) gentrification and racial discrimination. Our findings suggest that multiple sources of distress, including social, political, physical and economic factors, should be considered when investigating health effects of community stressor exposures and psychological distress. Community expertise is essential for comprehensively characterizing the range of neighborhood stressors that may be implicated in psychosocial exposure pathways.

Exposure to Mixtures of Metals and Neurodevelopmental Outcomes: A Multidisciplinary Review Using an Adverse Outcome Pathway Framework

Current risk assessment guidance calls for an individual chemical-by-chemical approach that fails to capture potential interactive effects of exposure to environmental mixtures and genetic variability. We conducted a review of the literature on relationships between prenatal and early life exposure to mixtures of lead (Pb), arsenic (As), cadmium (Cd), and manganese (Mn) with neurodevelopmental outcomes. We then used an adverse outcome pathway (AOP) framework to integrate lines of evidence from multiple disciplines based on evolving guidance developed by the Organization for Economic Cooperation and Development (OECD). Toxicological evidence suggests a greater than additive effect of combined exposures to As-Pb-Cd and to Mn with any other metal, and several epidemiologic studies also suggest synergistic effects from binary combinations of Pb-As, Pb-Cd, and Pb-Mn. The exposure levels reported in these epidemiologic studies largely fall at the high-end (e.g., 95th percentile) of biomonitoring data from the National Health and Nutrition Examination Survey (NHANES), suggesting a small but significant potential for high-end exposures. This review integrates multiple data sources using an AOP framework and provides an initial application of the OECD guidance in the context of potential neurodevelopmental toxicity of several metals, recognizing the evolving nature of regulatory interpretation and acceptance.

Meta-Analytic Approaches for Multistressor Dose-Response Function Development: Strengths, Limitations, and Case Studies

For many policy analyses, including but not limited to cumulative risk assessments, it is important to characterize the individual and joint health effects of multiple stressors. With an increasing focus on psychosocial and other nonchemical stressors, this often includes epidemiological meta-analysis. Meta-analysis has limitations if epidemiological studies do not include all of the stressors of interest or do not provide multivariable outputs in a format necessary for risk assessment. Given these limitations, novel analytical methods are often needed to synthesize the published literature or to build upon available evidence. In this article, we discuss three recent case studies that highlight the strengths and limitations of meta-analytic approaches and other research synthesis techniques for human health risk assessment applications. First, a literature-based meta-analysis within a risk assessment context informed the design of a new epidemiological investigation of the differential toxicity of fine particulate matter constituents. Second, a literature synthesis for an effects-based cumulative risk assessment of hypertension risk factors led to a decision to develop new epidemiological associations using structural equation modeling. Third, discrete event simulation modeling was used to simulate the impact of changes in the built environment on environmental exposures and associated asthma outcomes, linking literature meta-analyses for key associations with a simulation model to synthesize all of the model components. These case studies emphasize the importance of conducting epidemiology with a risk assessment application in mind, the need for interdisciplinary collaboration, and the value of advanced analytical methods to synthesize epidemiological and other evidence for risk assessment applications.

Community, state, and federal approaches to cumulative risk assessment: challenges and opportunities for integration

Community, state, and federal approaches to conventional and cumulative risk assessment (CRA) were described and compared to assess similarities and differences, and develop recommendations for a consistent CRA approach, acceptable across each level as a rigorous scientific methodology, including partnership formation and solution development as necessary practices. Community, state, and federal examples were described and then summarized based on their adherence to CRA principles of: (1) planning, scoping, and problem formulation; (2) risk analysis and ranking, and (3) risk characterization, interpretation, and management. While each application shared the common goal of protecting human health and the environment, they adopted different approaches to achieve this. For a specific project-level analysis of a particular place or instance, this may be acceptable, but to ensure long-term applicability and transferability to other projects, recommendations for developing a consistent approach to CRA are provided. This approach would draw from best practices, risk assessment and decision analysis sciences, and historical lessons learned to provide results in an understandable and accepted manner by all entities. This approach is intended to provide a common ground around which to develop CRA methods and approaches that can be followed at all levels.

Multifactorial Origin of Neurodevelopmental Disorders: Approaches to Understanding Complex Etiologies

A significant body of evidence supports the multifactorial etiology of neurodevelopmental disorders (NDDs) affecting children. The present review focuses on early exposure to environmental chemicals as a risk factor for neurodevelopment, and presents the major lines of evidence derived from epidemiological studies, underlying key uncertainties and research needs in this field. We introduce the exposome concept that, encompassing the totality of human environmental exposures to multiple risk factors, aims at explaining individual vulnerability and resilience to early chemical exposure. In this framework, we synthetically review the role of variable gene backgrounds, the involvement of epigenetic mechanisms as well as the function played by potential effect modifiers such as socioeconomic status. We describe laboratory rodent studies where the neurodevelopmental effects of environmental chemicals are assessed in the presence of either a “vulnerable” gene background or adverse pregnancy conditions (i.e., maternal stress). Finally, we discuss the need for more descriptive and “lifelike” experimental models of NDDs, to identify candidate biomarkers and pinpoint susceptible groups or life stages to be translated to large prospective studies within the exposome framework.

The shared pathoetiological effects of particulate air pollution and the social environment on fetal-placental development

Exposure to particulate air pollution and socioeconomic risk factors are shown to be independently associated with adverse pregnancy outcomes; however, their confounding relationship is an epidemiological challenge that requires understanding of their shared etiologic pathways affecting fetal-placental development. The purpose of this paper is to explore the etiological mechanisms associated with exposure to particulate air pollution in contributing to adverse pregnancy outcomes and how these mechanisms intersect with those related to socioeconomic status. Here we review the role of oxidative stress, inflammation and endocrine modification in the pathoetiology of deficient deep placentation and detail how the physical and social environments can act alone and collectively to mediate the established pathology linked to a spectrum of adverse pregnancy outcomes. We review the experimental and epidemiological literature showing that diet/nutrition, smoking, and psychosocial stress share similar pathways with that of particulate air pollution exposure to potentially exasperate the negative effects of either insult alone. Therefore, socially patterned risk factors often treated as nuisance parameters should be explored as potential effect modifiers that may operate at multiple levels of social geography. The degree to which deleterious exposures can be ameliorated or exacerbated via community-level social and environmental characteristics needs further exploration.

Social stressors and air pollution across New York City communities: a spatial approach for assessing correlations among multiple exposures

BACKGROUND

Recent toxicological and epidemiological evidence suggests that chronic psychosocial stress may modify pollution effects on health. Thus, there is increasing interest in refined methods for assessing and incorporating non-chemical exposures, including social stressors, into environmental health research, towards identifying whether and how psychosocial stress interacts with chemical exposures to influence health and health disparities. We present a flexible, GIS-based approach for examining spatial patterns within and among a range of social stressors, and their spatial relationships with air pollution, across New York City, towards understanding their combined effects on health.

METHODS

We identified a wide suite of administrative indicators of community-level social stressors (2008-2010), and applied simultaneous autoregressive models and factor analysis to characterize spatial correlations among social stressors, and between social stressors and air pollutants, using New York City Community Air Survey (NYCCAS) data (2008-2009). Finally, we provide an exploratory ecologic analysis evaluating possible modification of the relationship between nitrogen dioxide (NO2) and childhood asthma Emergency Department (ED) visit rates by social stressors, to demonstrate how the methods used to assess stressor exposure (and/or consequent psychosocial stress) may alter model results.

RESULTS

Administrative indicators of a range of social stressors (e.g., high crime rate, residential crowding rate) were not consistently correlated (rho = - 0.44 to 0.89), nor were they consistently correlated with indicators of socioeconomic position (rho = - 0.54 to 0.89). Factor analysis using 26 stressor indicators suggested geographically distinct patterns of social stressors, characterized by three factors: violent crime and physical disorder, crowding and poor access to resources, and noise disruption and property crimes. In an exploratory ecologic analysis, these factors were differentially associated with area-average NO2 and childhood asthma ED visits. For example, only the 'violent crime and disorder' factor was significantly associated with asthma ED visits, and only the 'crowding and resource access' factor modified the association between area-level NO2 and asthma ED visits.

CONCLUSIONS

This spatial approach enabled quantification of complex spatial patterning and confounding between chemical and non-chemical exposures, and can inform study design for epidemiological studies of separate and combined effects of multiple urban exposures.

Combined impact of lead, cadmium, polychlorinated biphenyls and non-chemical risk factors on blood pressure in NHANES

High blood pressure is associated with exposure to multiple chemical and non-chemical risk factors, but epidemiological analyses to date have not assessed the combined effects of both chemical and non-chemical stressors on human populations in the context of cumulative risk assessment. We developed a novel modeling approach to evaluate the combined impact of lead, cadmium, polychlorinated biphenyls (PCBs), and multiple non-chemical risk factors on four blood pressure measures using data for adults aged ≥ 20 years from the National Health and Nutrition Examination Survey (1999-2008). We developed predictive models for chemical and other stressors. Structural equation models were applied to account for complex associations among predictors of stressors as well as blood pressure. Models showed that blood lead, serum PCBs, and established non-chemical stressors were significantly associated with blood pressure. Lead was the chemical stressor most predictive of diastolic blood pressure and mean arterial pressure, while PCBs had a greater influence on systolic blood pressure and pulse pressure, and blood cadmium was not a significant predictor of blood pressure. The simultaneously fit exposure models explained 34%, 43% and 52% of the variance for lead, cadmium and PCBs, respectively. The structural equation models were developed using predictors available from public data streams (e.g., U.S. Census), which would allow the models to be applied to any U.S. population exposed to these multiple stressors in order to identify high risk subpopulations, direct intervention strategies, and inform public policy.

Community-wide health risk assessment using geographically resolved demographic data: a synthetic population approach

Background

Evaluating environmental health risks in communities requires models characterizing geographic and demographic patterns of exposure to multiple stressors. These exposure models can be constructed from multivariable regression analyses using individual-level predictors (microdata), but these microdata are not typically available with sufficient geographic resolution for community risk analyses given privacy concerns.

Methods

We developed synthetic geographically-resolved microdata for a low-income community (New Bedford, Massachusetts) facing multiple environmental stressors. We first applied probabilistic reweighting using simulated annealing to data from the 2006–2010 American Community Survey, combining 9,135 microdata samples from the New Bedford area with census tract-level constraints for individual and household characteristics. We then evaluated the synthetic microdata using goodness-of-fit tests and by examining spatial patterns of microdata fields not used as constraints. As a demonstration, we developed a multivariable regression model predicting smoking behavior as a function of individual-level microdata fields using New Bedford-specific data from the 2006–2010 Behavioral Risk Factor Surveillance System, linking this model with the synthetic microdata to predict demographic and geographic smoking patterns in New Bedford.

Results

Our simulation produced microdata representing all 94,944 individuals living in New Bedford in 2006–2010. Variables in the synthetic population matched the constraints well at the census tract level (e.g., ancestry, gender, age, education, household income) and reproduced the census-derived spatial patterns of non-constraint microdata. Smoking in New Bedford was significantly associated with numerous demographic variables found in the microdata, with estimated tract-level smoking rates varying from 20% (95% CI: 17%, 22%) to 37% (95% CI: 30%, 45%).

Conclusions

We used simulation methods to create geographically-resolved individual-level microdata that can be used in community-wide exposure and risk assessment studies. This approach provides insights regarding community-scale exposure and vulnerability patterns, valuable in settings where policy can be informed by characterization of multi-stressor exposures and health risks at high resolution.

Social Determinants of Health in Environmental Justice Communities: Examining Cumulative Risk in Terms of Environmental Exposures and Social Determinants of Health

Residents of environmental justice (EJ) communities may bear a disproportionate burden of environmental health risk, and often face additional burdens from social determinants of health. Accounting for cumulative risk should include measures of risk from both environmental sources and social determinants. This study sought to better understand cumulative health risk from both social and environmental sources in a disadvantaged community in Texas. Key outcomes were determining what data are currently available for this assessment, clarifying data needs, identifying data gaps, and considering how those gaps could be filled. Analyses suggested that the traditionally defined EJ community in Port Arthur may have a lower environmental risk from air toxics than the rest of the City of Port Arthur (although the entire city has a higher risk than the average for the state), but may have a larger burden from social determinants of health. However, the results should be interpreted in light of the availability of data, the definitions of community boundaries, and the areal unit utilized. Continued focus on environmental justice communities and the cumulative risks faced by their residents is critical to protecting these residents and, ultimately, moving towards a more equitable distribution and acceptable level of risk throughout society.