The role of cumulative risk assessment in decisions about environmental justice

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study presents an overall review as well as research directions worth investigating in this field, which provides a historical reference for future study.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.

Community-driven research and capacity building to address environmental justice concerns with industrial air pollution in Curtis Bay, South Baltimore

Introduction

Curtis Bay (CB) is an environmental justice (EJ) community in South Baltimore. With a high concentration of industrial polluters and compounding non-chemical stressors, CB has experienced socioeconomic, quality of life, and health burdens for over 100 years. Today, these polluters include the open-air CSX Coal Terminal, waste-to-energy incinerators, and heavy diesel traffic through residential areas. The Community of Curtis Bay Association, Free Your Voice, and South Baltimore Community Land Trust are local organizations enacting a vision for equitable, healthy, and community-led development without industrial encroachment. In response to community-identified EJ concerns and an explosion at the CSX Coal Terminal, CB community groups partnered with academic researchers to develop a community-driven hyperlocal air monitoring and capacity building approach. This paper describes this approach to characterizing hyperlocal air quality in CB, building bridges between community residents and regulatory agencies, and nurturing a cohesive and effective community-academic partnership toward EJ.

Methods

Using hyperlocal air monitoring, we are collecting real-time air pollution (particulate matter, black carbon, and ground-level gas species) and meteorological data from 15 low-cost sensors in residential and industrial areas of CB. We also use trail cameras to record activities at the CSX Coal Terminal. We merge air pollution and industrial activity data to evaluate the following: overall air quality in CB, multi-air pollutant profiles of elevated events, spatiotemporal changes in air quality in the community, patterns of industrial activity, and potential correlations between air quality and observed industrial activity. Members of our partnership also lead a high school course educating students about the history and ongoing efforts of the EJ movement in their community. Students in this course learn how to employ qualitative and quantitative data collection and analysis methods to bring scientific support to community EJ concerns.

Results and Discussion

Our hyperlocal air monitoring network and community-academic partnership are continuing to evolve and have already demonstrated the ability to respond to community-identified EJ issues with real-time data while developing future EJ leaders. Our reflections can assist other community and academic groups in developing strong and fruitful partnerships to address similar EJ issues.

A Framework for Interfacing and Partnering with Environmental Justice Communities as a Prelude to Human Health and Hazard Identification in the Vulnerable Census Tracts of Columbus, Ohio

Columbus, Ohio is one of the more prosperous, well-educated, and progressive cities in the United States. However, it ranks as the second worst life expectancy at birth, has a census tract wealth gap (27-year disparity), and one of the higher infant mortality rates in the country. These data suggest that there are likely several high-risk, vulnerable neighborhoods in Columbus with residents experiencing disparate and adverse outcomes. Illustrative of this fact are studies that have examined the social processes and mechanisms through which neighborhood contexts are at the forefront, including exposures to chemical stressors such as particulate matter (PM_2.5) as well as non-chemical stressors including violence, social determinants of health, zoning, and land use policies. It is documented that disparate and adverse outcomes are magnified in the vulnerable neighborhoods on the Near East Side as compared to Columbus city proper, Franklin County and/or the state of Ohio. As such, we developed a nuanced community engagement framework to identify potential environmental hazards associated with adverse pregnancy outcomes in those census tracts. The refined framework uses a blended version of traditional community-based participatory research (CBPR) models and is referred to as E⁶, Enhancing Environmental Endeavors via e-Equity, Education, and Empowerment.

The Co-occurrence of Specialty Vape Shops, Social Disadvantage, and Poor Air Quality in the United States: An Assessment of Cumulative Risks to Youth

Introduction: We conducted a cumulative environmental health risk assessment of whether specialty vape shops and poor air quality are more likely to co-occur in socially disadvantaged neighborhoods where racial/ethnic minority youth live.

Methods: We examined the population-adjusted incidence of specialty vape shops in relation to youth race/ethnicity, neighborhood socioeconomic status (SES), and air quality (nitrogen dioxide [NO₂]) at the census tract level across the conterminous United States for 2018.

Results: We did not find disparity in vape shop incidence related to minority youth race/ethnicity. Vape shop incidence was significantly negatively associated with all the youth race/ethnicities examined. The two lowest SES quintiles had nearly double the rate of specialty vape shop incidence compared with the highest SES quintile. Specialty vape shop incidence increased with NO₂ concentration, with more vape shops in poor air quality neighborhoods.

Conclusions: Specialty vape shops are disproportionately present in neighborhoods with poor air quality and where socially disadvantaged youth live. The increased incidence of vape shops in poor air quality neighborhoods, particularly in an urban context with increased traffic emissions, further points to potentially disproportionate impacts on disadvantaged populations due to cumulative social and environmental risks. This raises environmental justice and health equity concerns. Retailer-focused strategies aimed at limiting youth exposure to electronic cigarettes' labeling and advertising, preventing sales to minors, and limiting the number of retailers in low-SES neighborhoods may reduce initiation and help prevent tobacco-related health disparities among youth.

A cumulative-risk assessment method based on an artificial neural network model for the water environment

To analyze the cumulative risks to the water environment, the backpropagation artificial neural network (BP-ANN), a self-adapting algorithm, was proposed in this study. A new comprehensive indicator of cumulative risks was formed by combining the water risk assessment tool proposed by the World Wide Fund for Nature or World Wildlife Fund (WWF), Deutsche Investitions und Entwicklungsgesellschaft mbH (DEG), and the cumulative environmental risk assessment system proposed by the US Environmental Protection Agency (USEPA). Eleven training algorithms were selected and optimized based on the mean square error (MSE) of prediction results. Data concerning evaluating indicators and cumulative risk indexes of the Liao River collected from 2005 to 2017 in the cities of Tieling, Shenyang, and Panjin, China, were used as input and output data to train, validate, and test the BP-ANN. Levenberg Marquardt backpropagation was the most accurate algorithm, with an MSE of 3.33 × 10^-6. After optimization, there were six hidden layers in the model. The correlation coefficient of the BP-ANN with LM exceeded 80%. These findings suggest that the BP-ANN model is applicable to prediction of cumulative risks to the water environment. The model was sensitive to the number of wastewater treatment facilities and the wastewater treatment rate along the river. Based on the sensitivity analysis, the contributing factors can be controlled to reduce the cumulative risk.

Quantifying the Distribution of Environmental Health Threats and Hazards in Washington State Using a Cumulative Environmental Inequality Index

Background: Environmental racism, community stressors, and age-related susceptibility play a significant role in environmental inequality. The goal of this article was to use an inequality index (II) to assess the level of equality in environmental threats and hazards based on race, poverty, and age in Washington State. Methods: Using the Washington Environmental Health Disparities Map, we quantified the level of disproportionate burdens on communities with greater populations of people of color, people in poverty, children younger than 5, and people older than 65 using 3 cumulative environmental indices and 10 individual environmental indicators. Results: Census tracts with a higher proportion of people of color and those with people living below 185% federal poverty levels were found to be disproportionately burdened by environmental threats (II = -0.175 and II = -0.167, respectively, p < 0.001). Individual environmental indicators were found to disproportionately burden communities of color and low-income communities. Children younger than 5 were also disproportionately burdened by cumulative environmental indices (II = -0.076, p < 0.001) and individual indicators. Our analysis did not show disproportionate burden of environmental health threats based on the proportion of people older than 65 (II = 0.124, p < 0.001). Discussion: The disproportionate burden of the cumulative environmental threats on communities of color and low-income communities in this study corroborates similar analyses. These findings can be applied in policy and regulatory actions to correct the distributive environmental disparities. Conclusion: We found much higher burdens among historically marginalized communities and children who are more susceptible to environmental threats and hazards.

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.

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.

Modeling contamination conditions in small-scale industrial areas to estimate health savings benefits associated with remediation

Mercury and dioxin pollution associated with the China Petrochemical Development Corporation's An-shun plant is one of the most severe soil contamination incidents in Taiwan's history. Residents living nearby were exposed to heavy metals and dioxins that led to significant impacts on human health and safety. While many studies related to contamination in large-scale industrial areas have been conducted to evaluate the effects of occupational contaminant exposure, studies related to people who live near small-scale industry areas are less common. In this study, we use the system dynamics modeling to build a media flow pattern for mercury and dioxin in the vicinity of the An-shun plant, simulate the concentrations of the pollutants before and after remediation, and compare the simulated values with the measurements of actual conditions after remediation to evaluate the feasibility and accuracy of the model. This study also estimated the concentration of mercury and dioxin in each food medium to simulate the daily exposure of the human body to these contaminants. Finally, the reduction in mercury and dioxin levels in the study area was used to estimate the total health benefits to the local population. The objective of this study was to evaluate the application of this methodology to small-scale industrial areas as well as improve the decision-making process before, during, and after remediation of contaminated sites. The results of this study revealed the health benefits to residents living in the Annan District after remediation was completed at the An-shun plant were significant.

Integrating multivariate and geostatistical analyses for assessing the socio-environmental vulnerability of children in the vicinity of a contaminated site

Vulnerability assessments are commonly based on complex indices that may be inappropriate for characterizing risks in small groups of people exposed to environmental hazards. The aim was to present a multivariate and geostatistical approach to explore human health risks at the individual, household and community level. First, biological and socioeconomic characteristics from 179 children were used in a cluster analysis to find groups and identify vulnerability profiles. Then, both the exposure of children to arsenic and lead in soils and their accessibility to community resources were assessed using a geospatial analysis. The results identified three vulnerability profiles among children that were not in agreement with the environmental exposure and deficit of community resources. The proposed approach helps optimize strategies to manage both environmental and social risks based on the vulnerability of the exposed population.

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.

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.

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.

Arsenic in private well water part 3 of 3: Socioeconomic vulnerability to exposure in Maine and New Jersey

Arsenic is a naturally occurring toxic element often concentrated in groundwater at levels unsafe for human consumption. Private well water in the United States is mostly unregulated by federal and state drinking water standards. It is the responsibility of the over 13 million U.S. households regularly depending on private wells for their water to ensure it is safe for drinking. There is a consistent graded association with health outcomes at all levels of socioeconomic status (SES) in the U.S. Differential exposure to environmental risk may be contributing to this persistent SES-health gradient. Environmental justice advocates cite overwhelming evidence that income and other SES measures are consistently inversely correlated with exposure to suboptimal environmental conditions including pollutants, toxins, and their impacts. Here we use private well household surveys from two states to investigate the association between SES and risks for arsenic exposure, examining the potentially cumulative effects of residential location, testing and treatment behavior, and psychological factors influencing behavior. We find that the distribution of natural arsenic hazard in the environment is socioeconomically random. There is no evidence that higher SES households are avoiding areas with arsenic or that lower SES groups are disproportionately residing in areas with arsenic. Instead, disparities in exposure arise from differing rates of protective action, primarily testing well water for arsenic, and secondly treating or avoiding contaminated water. We observe these SES disparities in behavior as well as in the psychological factors that are most favorable to these behaviors. Assessment of risk should not be limited to the spatial occurrence of arsenic alone. It is important that social vulnerability factors are incorporated into risk modeling and identifying priority areas for intervention, which should include strategies that specifically target socioeconomically vulnerable groups as well as all the conditions which cause these disparities in testing and treatment behavior.

Mapping Environmental Inequalities Relevant for Health for Informing Urban Planning Interventions-A Case Study in the City of Dortmund, Germany

Spatial differences in urban environmental conditions contribute to health inequalities within cities. The purpose of the paper is to map environmental inequalities relevant for health in the City of Dortmund, Germany, in order to identify needs for planning interventions. We develop suitable indicators for mapping socioeconomically-driven environmental inequalities at the neighborhood level based on published scientific evidence and inputs from local stakeholders. Relationships between socioeconomic and environmental indicators at the level of 170 neighborhoods were analyzed continuously with Spearman rank correlation coefficients and categorically applying chi-squared tests. Reclassified socioeconomic and environmental indicators were then mapped at the neighborhood level in order to determine multiple environmental burdens and hotspots of environmental inequalities related to health. Results show that the majority of environmental indicators correlate significantly, leading to multiple environmental burdens in specific neighborhoods. Some of these neighborhoods also have significantly larger proportions of inhabitants of a lower socioeconomic position indicating hotspots of environmental inequalities. Suitable planning interventions mainly comprise transport planning and green space management. In the conclusions, we discuss how the analysis can be used to improve state of the art planning instruments, such as clean air action planning or noise reduction planning towards the consideration of the vulnerability of the population.

Neighborhood deprivation, race/ethnicity, and urinary metal concentrations among young girls in California

BACKGROUND

Although metals can adversely impact children's health, the distribution of exposures to many metals, particularly among vulnerable subpopulations, is not well characterized.

OBJECTIVES

We sought to determine whether neighborhood deprivation was associated with urinary concentrations of thirteen metals and whether observed relationships varied by race/ethnicity.

METHODS

We obtained neighborhood characteristics from the 2005-2009 American Community Survey. Demographic information and urine samples from 400 healthy young girls in Northern California were obtained during a clinical visit. Urine samples were analyzed for metals using inductively-coupled plasma-mass spectrometry and levels were corrected for creatinine. We ran analysis of variance and generalized linear regression models to estimate associations of urinary metal concentrations with neighborhood deprivation and race/ethnicity and stratified multivariable models to evaluate possible interactions among predictors on metals concentrations.

RESULTS

Urinary concentrations of three metals (barium, lead, antimony) varied significantly across neighborhood deprivation quartiles, and four (barium, lead, antimony, tin) varied across race/ethnicity groups. In models adjusted for family income and cotinine, both race/ethnicity (F3,224=4.34, p=0.01) and neighborhood deprivation (F3,224=4.32, p=0.01) were associated with antimony concentrations, but neither were associated with lead, barium, or tin, concentrations. Examining neighborhood deprivation within race/ethnicity groups, barium levels (pinteraction<0.01) decreased with neighborhood deprivation among Hispanic girls (ptrend<0.001) and lead levels (pinteraction=0.06) increased with neighborhood deprivation among Asian girls (ptrend=0.04).

CONCLUSIONS

Our results indicate that children's vulnerability to some metals varies by neighborhood deprivation quartile and race/ethnicity. These differential distributions of exposures may contribute to environmental health disparities later in life.

Application of Probabilistic Risk Assessment in Establishing Perchlorate and Goitrogen Risk Mitigation Strategies

This paper applies probabilistic risk assessment in quantifying risks from cumulative and aggregate risk pathways for selected goitrogens in water and food. Results show that the percentages of individuals with a Hazard Index (HI) value above 1 ranges between 30% and 50% both with and without serum half-life correction when a traditional regulatory assessment approach based on establishment of a No Observed Effects Level (NOEL) is used. When an exposure-response curve is instead used and a threshold of 50% inhibition is assumed, 1.1% or less of the population exceeds an HI value of 1 with no serum half-life correction, rising to as high as 11% when serum half-life correction is applied. If 0% to 5% threshold for iodide uptake inhibition is assumed for production of adverse effects, the percentage of the population with an HI above 1 is 46.2% or less with no serum half-life correction, and 47.2% or less when serum half-life correction is applied. The probabilistic analysis shows that while there are exposed groups for whom perchlorate exposures are the primary cause of individuals having HI values above 1, these constitute significantly less than 1% of the population. Instead, the potential risk from exposure to goitrogens is dominated by nitrates without serum half-life correction and thiocyanates with serum half-life correction, suggesting public health protection is better accomplished by a focus on these and other goitrogens expect in highly limited cases where waterborne perchlorate is at unusually high concentrations.

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.

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.

Integrated assessment of risk and sustainability in the context of regulatory decision making

Risk assessment is a decision-making tool used by the U.S. Environmental Protection Agency and other governmental organizations to organize and analyze scientific information so as to examine, characterize, and possibly quantify threats to human health and/or ecologic resources. Sustainability evaluation is a process for organizing and analyzing scientific and technical information about nature-society interactions in order to help decision-makers determine whether taking or avoiding certain actions will make society more sustainable. Although development and application of these two methodologies have progressed along distinct and unconnected pathways, the National Research Council recently recommended that the U.S. Environmental Protection Agency adopt the concept of "sustainability" as both a process and a goal, and that risk assessment be incorporated, when appropriate, as a key input into decision-making about sustainability. The following discussion briefly reviews these two analytic approaches and examines conceptual frameworks for integrating assessments of risk and sustainability as a component of regulatory decision-making.

The effect of social trust on citizens&#8217; health risk perception in the context of a petrochemical industrial complex

Perceived risk of environmental threats often translates into psychological stress with a wide range of effects on health and well-being. Petrochemical industrial complexes constitute one of the sites that can cause considerable pollution and health problems. The uncertainty around emissions results in a perception of risk for citizens residing in neighboring areas, which translates into anxiety and physiological stress. In this context, social trust is a key factor in managing the perceived risk. In the case of industrial risks, it is essential to distinguish between trust in the companies that make up the industry, and trust in public institutions. In the context of a petrochemical industrial complex located in the port of Castellón (Spain), this paper primarily discusses how trust—both in the companies located in the petrochemical complex and in the public institutions—affects citizens’ health risk perception. The research findings confirm that while the trust in companies negatively affects citizens’ health risk perception, trust in public institutions does not exert a direct and significant effect. Analysis also revealed that trust in public institutions and health risk perception are essentially linked indirectly (through trust in companies).

Biomarkers of maternal and fetal exposure to organochlorine pesticides measured in pregnant Hispanic women from Brownsville, Texas

Biomarkers of organochlorine pesticides were measured in both venous and umbilical cord blood from 35 pregnant Hispanic women living in Brownsville, Texas, USA. Gas chromatography with an electron capture detector was used to analyze specimens for 30 individual pesticides or their metabolites. Results indicate that blood concentrations were relatively low for most individual compounds, but that high-end (upper 10th percentile) values for total DDT were comparatively high. Although health effects associated with measured blood concentrations are uncertain, there is concern that fetal exposure to low levels of these OC compounds, either individually or in combination, might contribute to subsequent health problems, including neurodevelopmental effects, cancer, endocrine disruption, obesity and diabetes.

Biomarker measurements of prenatal exposure to polychlorinated biphenyls (PCB) in umbilical cord blood from postpartum Hispanic women in Brownsville, Texas

Biomarkers of polychlorinated biphenyls (PCB) were measured in both maternal and umbilical cord blood from 35 pregnant Hispanic women living in Brownsville, TX. Gas chromatography with an electron capture detector (GC/ECD) was used to analyze for 22 PCB analytes. Results indicated that both pregnant mothers and their fetuses were exposed to a variety of PCB at relatively low levels (≤ 0.2 ng/ml), and that concentrations in maternal and cord blood were similar. Concentrations of total PCB (sum or all PCB congeners) averaged more than 2.5 ng/ml, with highest values exceeding 3 ng/ml. Although health implications are uncertain, reports in the literature of PCB-related health effects raise concerns about possible future health consequences, especially obesity and diabetes, in this potentially vulnerable population.

U.S. EPA authority to use cumulative risk assessments in environmental decision-making

Conventionally, in its decision-making, the U.S. EPA has evaluated the effects and risks associated with a single pollutant in a single exposure medium. In reality, people are exposed to mixtures of pollutants or to the same pollutant through a variety of media, including the air, water, and food. It is now more recognized than before that environmental exposure to pollutants occurs via multiple exposure routes and pathways, including inhalation, ingestion, and dermal absorption. Moreover, chemical, biologic, radiologic, physical, and psychologic stressors are all acknowledged as affecting human health. Although many EPA offices attempt to consider cumulative risk assessment and cumulative effects in various ways, there is no Agency-wide policy for considering these risks and the effects of exposure to these risks when making environmental decisions. This article examines how U.S. courts might assess EPA's general authority and discretion to use cumulative risk assessment as the basis for developing data in support of environmental decision-making, and how courts might assess the validity of a cumulative risk assessment methodology itself.

Application of a novel method for assessing cumulative risk burden by county

The purpose of this study is to apply the Human Security Index (HSI) as a tool to detect social and economic cumulative risk burden at a county-level in the state of Texas. The HSI is an index comprising a network of three sub-components or "fabrics"; the Economic, Environmental, and Social Fabrics. We hypothesized that the HSI will be a useful instrument for identifying and analyzing socioeconomic conditions that contribute to cumulative risk burden in vulnerable counties. We expected to identify statistical associations between cumulative risk burden and (a) ethnic concentration and (b) geographic proximity to the Texas-Mexico border. Findings from this study indicate that the Texas-Mexico border region did not have consistently higher total or individual fabric scores as would be suggested by the high disease burden and low income in this region. While the Economic, Environmental, Social Fabrics (including the Health subfabric) were highly associated with Hispanic ethnic concentration, the overall HSI and the Crime subfabric were not. In addition, the Education, Health and Crime subfabrics were associated with African American racial composition, while Environment, Economic and Social Fabrics were not. Application of the HSI to Texas counties provides a fuller and more nuanced understanding of socioeconomic and environmental conditions, and increases awareness of the role played by environmental, economic, and social factors in observed health disparities by race/ethnicity and geographic region.

Cumulative risk assessment: an overview of methodological approaches for evaluating combined health effects from exposure to multiple environmental stressors

Systematic evaluation of cumulative health risks from the combined effects of multiple environmental stressors is becoming a vital component of risk-based decisions aimed at protecting human populations and communities. This article briefly examines the historical development of cumulative risk assessment as an analytical tool, and discusses current approaches for evaluating cumulative health effects from exposure to both chemical mixtures and combinations of chemical and nonchemical stressors. A comparison of stressor-based and effects-based assessment methods is presented, and the potential value of focusing on viable risk management options to limit the scope of cumulative evaluations is discussed. The ultimate goal of cumulative risk assessment is to provide answers to decision-relevant questions based on organized scientific analysis; even if the answers, at least for the time being, are inexact and uncertain.

Using exposure biomarkers in children to compare between-child and within-child variance and calculate correlations among siblings for multiple environmental chemicals

Longitudinal measurements of biomarkers for metals, phthalates, environmental tobacco smoke, organochlorine and organophosphate pesticides, polychlorinated biphenyls, and volatile organic compounds were made in blood and/or urine from a stratified, random sample of more than 100 elementary school-aged children living in an inner-city section of Minneapolis. Repeated measures of 31 exposure biomarkers indicate that between-child variance (B-CV) was greater than within-child variance (W-CV) for 8 compounds, B-CV was a significant proportion of total variance for 9 compounds, and variances were homogeneous for 14 compounds. Among siblings living in the same household, positive correlations were observed for biomarker concentrations of polychlorinated biphenyls, organochlorine pesticides, metals, and volatile organic chemicals in blood, and total cotinine in urine. Biologic markers confirm that children from a low-income, ethnically diverse neighborhood experienced concurrent exposure to a variety of hazardous environmental chemicals during their everyday activities. Future monitoring studies should examine the nature and magnitude of children's cumulative exposure to both chemical and non-chemical stressors, especially in disadvantaged populations.

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

Cumulative risk assessment is a science policy tool for organizing and analyzing information to examine, characterize, and possibly quantify combined threats from multiple environmental stressors. We briefly survey the state of the art regarding cumulative risk assessment, emphasizing challenges and complexities of moving beyond the current focus on chemical mixtures to incorporate nonchemical stressors, such as poverty and discrimination, into the assessment paradigm. Theoretical frameworks for integrating nonchemical stressors into cumulative risk assessments are discussed, the impact of geospatial issues on interpreting results of statistical analyses is described, and four assessment methods are used to illustrate the diversity of current approaches. Prospects for future progress depend on adequate research support as well as development and verification of appropriate analytic frameworks.

Conceptual models for cumulative risk assessment

In the absence of scientific consensus on an appropriate theoretical framework, cumulative risk assessment and related research have relied on speculative conceptual models. We argue for the importance of theoretical backing for such models and discuss 3 relevant theoretical frameworks, each supporting a distinctive "family" of models. Social determinant models postulate that unequal health outcomes are caused by structural inequalities; health disparity models envision social and contextual factors acting through individual behaviors and biological mechanisms; and multiple stressor models incorporate environmental agents, emphasizing the intermediary role of these and other stressors. The conclusion is that more careful reliance on established frameworks will lead directly to improvements in characterizing cumulative risk burdens and accounting for disproportionate adverse health effects.

Polycyclic aromatic hydrocarbons in maternal and umbilical cord blood from pregnant Hispanic women living in Brownsville, Texas

Venous blood was drawn from 35 pregnant Hispanic women living in Brownsville, Texas, and matched cord blood was collected at birth. Gas chromatography/mass spectrometry was used to measure concentrations of 55 individual PAHs or groups of PAHs. Results indicate that these women and their fetuses were regularly exposed to multiple PAHs at comparatively low concentrations, with levels in cord blood generally exceeding levels in paired maternal blood. While the possibility of related adverse effects on the fetus is uncertain, these exposures in combination with socioeconomically-disadvantaged and environmentally-challenging living conditions raise legitimate public health concerns.

Biomarker measurements of concurrent exposure to multiple environmental chemicals and chemical classes in children

Concern is mounting that children from disadvantaged, low-income neighborhoods are likely to be both more exposed to chemical hazards and more susceptible to related adverse health effects. This article reports measurements of >75 individual biomarkers spanning 7 chemical/pollutant classes in blood and urine from more than 100 children living in a socioeconomically disadvantaged and ethnically diverse area of south Minneapolis, MN. Results indicate that a significant proportion of children in the study were at the high end of the exposure distribution compared to national reference ranges for a variety of environmental chemicals and/or their metabolites, including phthalates, organochlorine pesticides, organophosphate pesticides, metals, polychlorinated biphenyls, and volatile organic compounds. In addition, levels of cotinine in urine indicate that more than half the children were regularly exposed to environmental tobacco smoke, with the upper 10th percentile exposed to relatively high concentrations.