Recipient Organization
UNIVERSITY OF CALIFORNIA, DAVIS
410 MRAK HALL
DAVIS,CA 95616-8671
Performing Department
Human Ecology
Non Technical Summary
This project supports the mission of the Agricultural Experiment Station by addressing the Hatch Act area(s) of: home economics and family life; rural and community development.This research aims to investigate key linkages between environmental exposure and human health in Kettleman City, CA, a rural community in the San Joaquin Valley. Utilizing an innovative participatory process, the purpose of this study is to ascertain environmental exposure of a group of residents in the community of Kettleman City, CA relative to California's; establish feasibility for a larger study; and to produce a model for community engaged science that informs environmental policy and regulation. Working with community partners, we plan to conduct an environmental health survey of all households in Kettleman City, CA to identify important relationships among sociodemographics, health outcomes, and environmental risks. Working with experts at UCD, we will gather data and test for community concerns regarding possible exposure pathways. This monitoring will include collection of household water samples to test for mercury, arsenic, and chlorpyrifos; ambient air samples of individuals to test for benzene and diesel particles; and blood samples to test for PCBs. Findings will be shared with the community, and with national audiences. This project is important for understanding potential exposure pathways for residents of California when it comes to environmental risks to human health. Moreover, utilizing an innovative, participatory research design, communities are engaged from start to finish throughout the research process, in order to maximize community knowledge and relationships.
Animal Health Component
20%
Research Effort Categories
Basic
40%
Applied
20%
Developmental
40%
Goals / Objectives
(1) Determine key linkages among human health, sociodemographics, and environmental exposure for residents of Kettleman City, CA. (2) Characterize presence and concentrations of environmental exposure through collection and analysis of both environmental, i.e. household water and ambient air, and biological samples, i.e. blood, from households and residents respectively. (3) Apply this community-based participatory science as a model for other affected communities to better inform socio-environmental decision-making and policy.
Project Methods
This research is innovative in its proposed use of spatial, quantitative, qualitative, environmental, and biological data to identify and analyze socio-environmental interactions and health outcomes in a disadvantaged agricultural community. Taken together, these five types of data contribute their different analytic capabilities for fine robust detection of the processes, mechanisms, and outcomes of socio-environmental health linkages. For instance, spatial and quantitative analyses enable us to visually specify and statistically assess interrelationships among health concerns, socio-demographic features, and their distributions. Qualitative data will provide novel insight for theorizations on significant linkages between environmental degradation and human health (Brown, 2003), which, in turn, encourage further empirical analyses. Environmental and biological data will help establish the scope of human health impacts associated with hazards faced by the community (e.g. pesticides, hazardous waste facility). Such community engaged science as this benefits health sciences more broadly in advancing a cumulative risk assessment and explaining the distribution of human health impacts and environmental hazards, while dealing directly with community concerns around social inequality, negative health effects, and environmental risks (Brown, Brody, Morello-Frosch, Tovar, Zota, & Rudel, 2012; Balazs, & Morello-Frosch, 2013).Methodological contributions involve the triangulation of spatial, qualitative, quantitative, environmental, and biological data to maximize reliability and validity of findings. The application of cutting-edge analytic strategies (e.g. structural equation modeling; spatial statistics; biomonitoring, etc.) to isolate important linkages between environmental exposure and community health advances the fields of environmental health, environmental justice, and community development. Broader impacts include developing knowledge of key relationships between socio-demographics and environmental outcomes through analysis of multiple data types; development of community-based participatory environmental health study to engage community throughout the research process; translation of science to communicate findings effectively to the community; and applications to policy development on improving human health and environmental regulation. Given the objectives of this research, I propose a sequential mixed-method research design (e.g. Creswell & Clark, 2007; Small, 2011; Pearce, 2012), consisting of phase 1, in which I conduct structured in-depth interviews, survey development, deployment, and analysis, and phase 2, in which I conduct monitoring of both environmental and biological sources and analysis. Environmental monitoring includes a personal device to collect ambient air samples of the wearer and collection of water samples from participating households. Biological monitoring includes collecting and analyzing blood samples from residents (for more details see below). Such multi-method design brings together the strengths of each approach to compare, validate, and corroborate results (Small, 2011). The sequential and nested design allows us to address "how" questions that emerge from the collection and analysis of community health and environment perception data. Given the risks already experienced by this community, the highest standard of care will be implemented to ensure that all research activities, including biomonitoring, are performed with the community's well-being in mind. Part of this standard of care includes phase 1 research activities to build trust and ensure phase 2, development of process logic, methodology, and sampling, aligns with community priorities.In phase 1, I will examine prior health surveys conducted by community agencies, such as the Kings County Department of Public Health survey whose purpose was to inform facility operators and stakeholders about local environmental issues, to assess their value to the present study and identify gaps that can be filled. Second, using this analysis, working with community partners and two undergraduate research assistants, we will survey all households in Kettleman City to isolate key socio-economic characteristics, perceptions of environmental hazards, geolocation by block, and volunteered health data. Qualitative data, in the form of in-depth interviews into health histories and perceptions of environmental exposure with residents will deepen our understanding of community perceptions of relationships between environmental hazards and human health. For instance, these interviews, conducted with a structured interview guide, will serve to build trust with community members and to help inform the survey on what sources of environmental exposure are of paramount concern to the community. From this first phase of the study, we will have identified a sample of the affected community from which to engage in monitoring activities.Spatial data will be analyzed using geographic information systems (GIS) to map social demographics, volunteered health outcomes, and the location of environmental hazards (e.g. Class 1 hazardous waste facility). These data also will be analyzed using geographically weighted regression models to identify statistically significant relationships among space, health, and environmental indicators. Quantitative data will be analyzed for summary statistics, correlations, and estimations, utilizing OLS regression and logistic binary regression, which will be used with interaction terms to capture relationships among social-demographics, human health, and environmental outcomes. Structural equation modeling, an advanced statistical technique robust with a small case base and model fit indices (Bollen, 1989), will be employed in order to model direct and indirect effects of perceptions of environmental hazards on human health outcomes. Qualitative data will be transcribed and analyzed using content analysis (e.g. Atlas.Ti), specifically utilizing codes that emerge in the data to categorize themes of importance to community partners and research aims.In phase 2, we will utilize environmental techniques to collect samples of air and water, and biomonitoring techniques to collect blood to detect possible presence and concentration in community members of environmental elements of interest, particularly heavy metals, pesticides, and PCBs, which have been known to exist in both hazardous landfills and in leachate --the liquid that drains from the landfill consisting of both dissolved and suspended material --and may cause deleterious effects in human and environmental systems (EPA, 2017; Cal DTSC, 2017). Working with community partners, I will recruit residents to participate in air, water, and biological sample collection. Monitoring chemicals identified by community partners include benzene (see IARC; ATSDR) from the more than 4,000 diesel trucks that deliver waste to the fill every day; arsenic from contaminated water; PCBs (see Lauby-Secretan, Béatrice et al., 2016) from known mishandling of the substance at this facility; and, pesticides (e.g. phosmet, aluminum phosphide, chlorpyrifos) from almond orchards that surround the city.