Environmental Injustice and Industrial Chicken Farming in Maryland.

Maryland's growing chicken industry, including concentrated animal feeding operations (CAFOs) and meat processing plants, raises a number of concerns regarding public health and environmental justice. Using hot spot analysis, we analyzed the totality of Maryland's CAFOs and meat processing plants and those restricted to the Eastern Shore to assess whether communities of color and/or low socioeconomic status communities disproportionately hosted these types of facilities at the census tract level. We used zero-inflated regression modeling to determine the strength of the associations between environmental justice variables and the location of CAFOs and meatpacking facilities at the State level and on the Eastern Shore. Hot spot analyses demonstrated that CAFO hot spots on the Eastern Shore were located in counties with some of the lowest wealth in the State, including the lowest ranking county-Somerset. Zero-inflated regression models demonstrated that increases in median household income across the state were associated with a 0.04-unit reduction in CAFOs. For every unit increase in the percentage of people of color (POC), there was a 0.02-unit increase in meat processing facilities across the state. The distribution of CAFOs and meat processing plants across Maryland may contribute to poor health outcomes in areas affected by such production, and contribute to health disparities and health inequity.

Local Government Approaches to Combating COVID-19 Inequities: A Durham County Department of Public Health Perspective.

When a novel coronavirus disease (COVID-19) made major headlines in 2020, it further exposed an existing public health crisis related to inequities within our communities and health care delivery system. Throughout the COVID-19 pandemic, populations of color had higher infection and mortality rates, and even experienced greater disease severity compared to whites. Populations of color often bear the brunt of COVID-19 and other health inequities, due to the multifaceted relationship between systemic racism and the social determinants of health. As this relationship continues to perpetuate health inequities, the local health department is an agency that has the jurisdiction and responsibility to prevent disease and protect the health of the communities they serve. When equity is integrated into a health department's operational infrastructure as a disease prevention strategy, it can elevate the agency's response to public health emergencies. Collecting, reporting, and tracking demographic data that is necessary to identify inequities becomes a priority to facilitate a more robust public health response. The purpose of this paper is to present strategies of how a local health department operationalized equity in various stages of COVID-19 response and apply these methods to future public health emergencies to better serve vulnerable communities.

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.

Baseline Air Quality Assessment of Goods Movement Activities before the Port of Charleston Expansion: A Community-University Collaborative.

As the demand for goods continues to increase, a collective network of transportation systems is required to facilitate goods movement activities. This study examines air quality near the Port of Charleston before its expansion and briefly describes the establishment and structure of a community-university partnership used to monitor existing pollution. Particulate matter (PM) concentrations (PM2.5 and PM10) were measured using the Thermo Fisher Scientific Partisol 2000i-D Dichotomous Air Sampler, Thermo Scientific Dichotomous Sequential Air Sampler Partisol-Plus 2025-D, and Rupprecht & Patashnick TEOM Series 1400 Sampler at neighborhood (Union Heights, Rosemont, and Accabee) and reference (FAA2.5 and Jenkins Street) sites. Descriptive statistics were performed and an ANOVA (analysis of variance) was calculated to find the difference in overall mean 24-hour PM average concentrations in communities impacted by environmental injustice. PM2.5 (15.2 µg/m3) and PM10 (27.2 µg/m3) maximum concentrations were highest in neighborhoods such as Union Heights neighborhoods due to more goods movement activities. Nevertheless, there was no statistically significant difference in mean concentrations of PM2.5 and PM10 across neighborhood sites. In contrast, mean PM10 neighborhood concentrations were significantly lower than mean PM10 reference concentrations for Union Heights (p = 0.00), Accabee (p ≤ 0.0001), and Rosemont (p = 0.01). Although PM concentrations were lower than current National Ambient Air Quality Standards, this study demonstrated how community-university partners can work collectively to document baseline PM concentrations that will be used to examine changes in air quality after the port expansion brings additional goods movement activities to the area.

Environmental Justice Radar: A Tool for Community-Based Mapping to Increase Environmental Awareness and Participatory Decision Making.

BACKGROUND: As part of the Charleston Area Pollution Prevention Partnership (CAPs), studies have been performed to address environmental health issues using various techniques including Geographic Information Systems (GIS) mapping. Most of the mapping has been conducted by academic team members; however, there is a need for more community-based mapping to ensure the sustainability and effectiveness of community-driven efforts to eliminate environmental hazards and health disparities. The emergence of public participatory GIS (PPGIS) has been shown as a way to democratize science, build community capacity, and empower local citizens to address environmental health issues. PURPOSE: This article describes the development of the Environmental Justice (EJ) Radar, a PPGIS tool that provides stakeholders in South Carolina with a way to raise environmental awareness and improve citizen participation in local environmental decision-making. We describe the functionality of EJ Radar and discuss feedback received from stakeholders to improve the utility of the PPGIS tool.

Assessment of sociodemographic and geographic disparities in cancer risk from air toxics in South Carolina.

Populations of color and low-income communities are often disproportionately burdened by exposures to various environmental contaminants, including air pollution. Some air pollutants have carcinogenic properties that are particularly problematic in South Carolina (SC), a state that consistently has high rates of cancer mortality for all sites. The purpose of this study was to assess cancer risk disparities in SC by linking risk estimates from the U.S. Environmental Protection Agency's 2005 National Air Toxics Assessment (NATA) with sociodemographic data from the 2000 US Census Bureau. Specifically, NATA risk data for varying risk categories were linked by tract ID and analyzed with sociodemographic variables from the 2000 census using R. The average change in cancer risk from all sources by sociodemographic variable was quantified using multiple linear regression models. Spatial methods were further employed using ArcGIS 10 to assess the distribution of all source risk and percent non-white at each census tract level. The relative risk (RR) estimates of the proportion of high cancer risk tracts (defined as the top 10% of cancer risk in SC) and their respective 95% confidence intervals (CIs) were calculated between the first and latter three quartiles defined by sociodemographic factors, while the variance in the percentage of high cancer risk between quartile groups was tested using Pearson's chi-square. The average total cancer risk for SC was 26.8 people/million (ppl/million). The risk from on-road sources was approximately 5.8 ppl/million, higher than the risk from major, area, and non-road sources (1.8, 2.6, and 1.3 ppl/million), respectively. Based on our findings, addressing on-road sources may decrease the disproportionate cancer risk burden among low-income populations and communities of color in SC.

Use of segregation indices, Townsend Index, and air toxics data to assess lifetime cancer risk disparities in metropolitan Charleston, South Carolina, USA.

BACKGROUND: Studies have demonstrated a relationship between segregation and level of education, occupational opportunities, and risk behaviors, yet a paucity of research has elucidated the association between racial residential segregation, socioeconomic deprivation, and lifetime cancer risk. OBJECTIVES: We examined estimated lifetime cancer risk from air toxics by racial composition, segregation, and deprivation in census tracts in Metropolitan Charleston. METHODS: Segregation indices were used to measure the distribution of groups of people from different races within neighborhoods. The Townsend Index was used to measure economic deprivation in the study area. Poisson multivariate regressions were applied to assess the association of lifetime cancer risk with segregation indices and Townsend Index along with several sociodemographic measures. RESULTS: Lifetime cancer risk from all pollution sources was 28 persons/million for half of the census tracts in Metropolitan Charleston. Isolation Index and Townsend Index both showed significant correlation with lifetime cancer risk from different sources. This significance still holds after adjusting for other sociodemographic measures in a Poisson regression, and these two indices have stronger effect on lifetime cancer risk compared to the effects of sociodemographic measures. CONCLUSIONS: We found that material deprivation, measured by the Townsend Index and segregation measured by the Isolation index, introduced high impact on lifetime cancer risk by air toxics at the census tract level.

Spatial disparity in the distribution of superfund sites in South Carolina: an ecological study.

BACKGROUND: According to the US Environmental Protection Agency (EPA), Superfund is a federal government program implemented to clean up uncontrolled hazardous waste sites. Twenty-six sites in South Carolina (SC) have been included on the National Priorities List (NPL), which has serious human health and environmental implications. The purpose of this study was to assess spatial disparities in the distribution of Superfund sites in SC. METHODS: The 2000 US census tract and block level data were used to generate population characteristics, which included race/ethnicity, socioeconomic status (SES), education, home ownership, and home built before 1950. Geographic Information Systems (GIS) were used to map Superfund facilities and develop choropleth maps based on the aforementioned sociodemographic variables. Spatial methods, including mean and median distance analysis, buffer analysis, and spatial approximation were employed to characterize burden disparities. Regression analysis was performed to assess the relationship between the number of Superfund facilities and population characteristics. RESULTS: Spatial coincidence results showed that of the 29.5% of Blacks living in SC, 55.9% live in Superfund host census tracts. Among all populations in SC living below poverty (14.2%), 57.2% were located in Superfund host census tracts. Buffer analyses results (0.5mi, 1.0mi, 5.0mi, 0.5km, 1.0km, and 5.0km) showed a higher percentage of Whites compared to Blacks hosting a Superfund facility. Conversely, a slightly higher percentage of Blacks hosted (30.2%) a Superfund facility than those not hosting (28.8%) while their White counterparts had more equivalent values (66.7% and 67.8%, respectively). Regression analyses in the reduced model (Adj. R2 = 0.038) only explained a small percentage of the variance. In addition, the mean distance for percent of Blacks in the 90th percentile for Superfund facilities was 0.48mi. CONCLUSION: Burden disparities exist in the distribution of Superfund facilities in SC at the block and census tract levels across varying levels of demographic composition for race/ethnicity and SES.