Climate Change, Environmental Justice, and Vulnerability: An Exploratory Spatial Analysis

Research has demonstrated that vulnerable populations including disadvantaged populations of color live in areas that may place them at higher risk of exposure to social and environmental hazards. Due to climate change, these populations may experience worse health outcomes and environmental health disparities. The purpose of this project was to explore the use of Geographic Information Systems (GIS) to assess areas that may be vulnerable to climate change across the United States. We employed ArcGIS 9.3 to create vulnerability scores for areas across the country that may be that may be impacted by climate change at the county level in the United States using different social, environmental, and health indicators. We included data on race=ethnicity and socioeconomic status from the US Census. Data on pollution sources and pollution levels were obtained from the United States Environmental Protection Agency. Health data were obtained from the Behavioral Risk Factor Surveillance System (BRFSS), the National Vital Statistics System, and the National Center for Health Statistics. We also employed the Moran’s I statistic to assess any significant vulnerability clusters. We found the highest scores for counties in the South particularly the Deep South and in Metropolitan areas in the Northeast and Midwest. Our findings provide insight into the areas of the country that may be vulnerable to the impacts of climate-change. More work needs to be performed to improve the spatial resolution of the maps and include more physical data that will help target areas that need effective climate change related mitigation and adaptation policies

Environmental Injustice and the Mississippi Hog Industry

The recent growth and restructuring of the swine industry in the state of Mississippi has raised various environmental and socioeconomic concerns. We spatially examined the location and attributes of 67 industrial hog operations to determine if African American and low-income communities have a high prevalence of industrial hog operations located near their neighborhoods at the census block group level. We used spatial data and cross-classification analysis to compare the prevalence of industrial hog operations in neighborhoods that are primarily African American and low income with the prevalence in neighborhoods that are African American and affluent. We also used logistic regression to evaluate the relationship between the environmental justice variables and the location of the industrial hog operations. The block group characterization showed a high prevalence of hog operations in the four highest quintiles compared with the lowest quintile for percentage African American and percentage poverty. At increasing levels of percentage African Americans and percentage of persons in poverty, there are 2.4-3.6 times more operations compared with the referent group; additionally, scale adjustment to only the hog counties reduces this to 1.8-3.1 more operations compared with the referent group. The inequitable distribution of hog-confined agricultural feeding operations in these communities may have adverse environmental impacts associated with industrial hog production, such as increased health risks and quality of life degradation, as have occurred in other areas having similar facilities

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. R(2) = 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

Using photovoice as a tool for community engagement to assess the environment and explore environmental health disparities

Photovoice was used as a participatory research method to document perceived local environmental hazards, pollution sources, and potential impact on health among community members to address environmental health disparities. A convenience sample of 16 adults in Orangeburg, South Carolina participated in Photovoice. Photos depicted positive and negative implications of the environment across seven themes: recreation and leisure; food access; hazards and pollution; health, human, and social services; economic issues; beautification; and accommodation and accessibility. Positive and negative photos demonstrated a high level of interest among community members in considering how the environment influences health and health disparities

Should We Put Our Feet in the Water? Use of a Survey to Assess Recreational Exposures to Contaminants in the Anacostia River

Funding for Open Access provided by the UMD Libraries Open Access Publishing Fund.The Anacostia River, a tributary of the Potomac River that flows into the Chesapeake Bay, is highly contaminated with raw sewage, heavy metals, oil and grease, trash, pathogens, excessive sediments, and organic chemicals. Despite this contamination, recreation on the river is very popular, including kayaking, canoeing, rowing, and sport fishing. There is currently no information available on the potential health risks faced by recreational users from exposure to the river’s pollutants. A total of 197 recreational users of the Anacostia River were surveyed regarding general demographic information and their recreational behavior over the previous year, including frequency and duration of recreation and specific questions related to their water exposure. 84.1% of respondents who engaged in canoeing, kayaking, rowing, rafting, or paddling were exposed to water on their bodies during recreation. Some 27.2% of those exposed to water reported getting water in their mouth while recreating, and 60.7% of that group reported swallowing some of this water. This is the first study to examine the exposure to contaminants faced by the recreational population of the Anacostia River

Being overburdened and medically underserved: assessment of this double disparity for populations in the state of Maryland

Environmental justice research has shown that many communities of color and low-income persons are differentially burdened by noxious land uses including Toxic Release Inventory (TRI) facilities. However, limited work has been performed to assess how these populations tend to be both overburdened and medically underserved. We explored this “double disparity” for the first time in Maryland. We assessed spatial disparities in the distribution of TRI facilities in Maryland across varying levels of sociodemographic composition using 2010 US Census Health Professional Shortage Area (HPSA) data. Univariate and multivariate regression in addition to geographic information systems (GIS) were used to examine relationships between sociodemographic measures and location of TRI facilities. Buffer analysis was also used to assess spatial disparities. Four buffer categories included: 1) census tracts hosting one or more TRI facilities; 2) tracts located more than 0 and up to 0.5 km from the closest TRI facility; 3) tracts located more than 0.5 km and up to 1 km from a TRI facility; and 4) tracts located more than 1 km and up to 5 km from a TRI facility. We found that tracts with higher proportions of non-white residents and people living in poverty were more likely to be closer to TRI facilities. A significant increase in income was observed with an increase in distance between a census tract and the closest TRI facility. In general, percent non-white was higher in HPSA tracts that host at least one TRI facility than in non-HPSA tracts that host at least one TRI facility. Additionally, percent poverty, unemployment, less than high school education, and homes built pre-1950 were higher in HPSA tracts hosting TRI facilities than in non-HPSA tracts hosting TRI facilities. We found that people of color and low-income groups are differentially burdened by TRI facilities in Maryland. We also found that both low-income groups and persons without a high school education are both overburdened and medically underserved. The results of this study provide insight into how state agencies can better address the double disparity of disproportionate environmental hazards and limited access to health care resources facing vulnerable communities in Maryland.https://doi.org/10.1186/1476-069X-13-2

Association between an Internet-Based Measure of Area Racism and Black Mortality

Racial disparities in health are well-documented and represent a significant public health concern in the US. Racism-related factors contribute to poorer health and higher mortality rates among Blacks compared to other racial groups. However, methods to measure racism and monitor its associations with health at the population-level have remained elusive. In this study, we investigated the utility of a previously developed Internet search-based proxy of area racism as a predictor of Black mortality rates. Area racism was the proportion of Google searches containing the “N-word” in 196 designated market areas (DMAs). Negative binomial regression models were specified taking into account individual age, sex, year of death, and Census region and adjusted to the 2000 US standard population to examine the association between area racism and Black mortality rates, which were derived from death certificates and mid-year population counts collated by the National Center for Health Statistics (2004–2009). DMAs characterized by a one standard deviation greater level of area racism were associated with an 8.2% increase in the all-cause Black mortality rate, equivalent to over 30,000 deaths annually. The magnitude of this effect was attenuated to 5.7% after adjustment for DMA-level demographic and Black socioeconomic covariates. A model controlling for the White mortality rate was used to further adjust for unmeasured confounders that influence mortality overall in a geographic area, and to examine Black-White disparities in the mortality rate. Area racism remained significantly associated with the all-cause Black mortality rate (mortality rate ratio = 1.036; 95% confidence interval = 1.015, 1.057; p = 0.001). Models further examining cause-specific Black mortality rates revealed significant associations with heart disease, cancer, and stroke. These findings are congruent with studies documenting the deleterious impact of racism on health among Blacks. Our study contributes to evidence that racism shapes patterns in mortality and generates racial disparities in health

Public Infrastructure Disparities and the Microbiological and Chemical Safety of Drinking and Surface Water Supplies in a Community Bordering a Landfill

The historically African-American Rogers-Eubanks community straddles unincorporated boundaries of two municipalities in Orange County, North Carolina, and predates a regional landfill sited along its border in 1972. Community members from the Rogers-Eubanks Neighborhood Association (RENA), concerned about deterioration of private wells and septic systems and a lack of public drinking water and sewer services, implemented a community-driven research partnership with university scientists and community-based organizations to investigate water and sewer infrastructure disparities and the safety of drinking and surface water supplies. RENA drafted memoranda of agreement with partners and trained community monitors to collect data (inventory households, map water and sewer infrastructure, administer household water and sewer infrastructure surveys, and collect drinking and surface water samples). Respondents to the surveys reported pervasive signs of well vulnerability (100%) and septic system failure (68%). Each 100-m increase in distance from the landfill was associated with a 600 most probable number/100 mL decrease in enterococci concentrations in surface water (95% confidence interval = −1106, −93). Pervasive private household water and sewer infrastructure failures and poor water quality were identified in this community bordering a regional landfill, providing evidence of a need for improved water and sanitation services

Reflecting on Efforts to Design an Inclusive Citizen Science Project in West Baltimore

Citizen science (CS) has been an increasingly utilized means by which scientists leverage members of the public to increase the amount of data collected and analyzed. However, the underrepresentation of individuals from certain socio-cultural groups can have consequences that can manifest in the scientific outcomes of those CS projects such as biases in the data. Additionally, this underrepresentation can potentially affect long-term viability and support of CS as a community of practice. CS programs that promote greater inclusivity would likely provide opportunities for communities to define, investigate, and address pressing issues in collaboration with professional scientists. In this paper we discuss a CS project that sought to include underrepresented communities in Baltimore, Maryland using Pandya’s framework for inclusive CS. While the project met all of its scientific research goals, translating the CS for broader social outcomes in the community proved challenging. Here we highlight perspectives from local community members and research personnel about the barriers to CS engagement, challenges in translating scientific outcomes to social justice efforts, and opportunities to address these barriers in CS program development and design

The Public Health Exposome: A Population-Based, Exposure Science Approach to Health Disparities Research

The lack of progress in reducing health disparities suggests that new approaches are needed if we are to achieve meaningful, equitable, and lasting reductions. Current scientific paradigms do not adequately capture the complexity of the relationships between environment, personal health and population level disparities. The public health exposome is presented as a universal exposure tracking framework for integrating complex relationships between exogenous and endogenous exposures across the lifespan from conception to death. It uses a social-ecological framework that builds on the exposome paradigm for conceptualizing how exogenous exposures “get under the skin”. The public health exposome approach has led our team to develop a taxonomy and bioinformatics infrastructure to integrate health outcomes data with thousands of sources of exogenous exposure, organized in four broad domains: natural, built, social, and policy environments. With the input of a transdisciplinary team, we have borrowed and applied the methods, tools and terms from various disciplines to measure the effects of environmental exposures on personal and population health outcomes and disparities, many of which may not manifest until many years later. As is customary with a paradigm shift, this approach has far reaching implications for research methods and design, analytics, community engagement strategies, and research training