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Mobile daily diaries to characterize stressors and acute health symptoms in an environmental justice neighborhood
Institution:1. Urban & Environmental Policy Department and Public Health Program, Occidental College, Los Angeles, CA, USA;2. Department of Environmental Health, Harvard T.H. Chan School of Public Health, 665 Huntington Ave., Bldg. 1, 14th Floor, Boston, MA, 02115, USA;3. LA Grit Media, Los Angeles, CA, 90007, USA;4. Division of Biostatistics, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA;5. Division of Environmental Health, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA;1. Healthy High Density Cities Lab, HKUrbanLab, The University of Hong Kong, Knowles Building, Pokfulam Road, Pokfulam, Hong Kong Special Administrative Region, PR China;2. School of Public Health, The University of Hong Kong, Patrick Manson Building, Sassoon Road, Pokfulam, Hong Kong Special Administrative Region, PR China;3. The State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong Special Administrative Region, PR China;1. Faculty of Medicine, University of Geneva, Geneva, Switzerland;2. Department and Division of Primary Care Medicine, Geneva University Hospitals, Geneva, Switzerland;3. Group of Geographic Information Research and Analysis in Population Health (GIRAPH), Geneva, Switzerland;4. Department of Medicine, Internal Medicine, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne, Switzerland;5. Department of Oncology, Geneva University Hospitals, Geneva, Switzerland;6. Laboratory of Geographic Information Systems (LASIG), School of Architecture, Civil and Environmental Engineering (ENAC), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland;7. Swiss Tropical and Public Health Institute, Basel, Switzerland;8. University of Basel, Basel, Switzerland;9. University Centre for General Medicine and Public Health, University of Lausanne, Lausanne, Switzerland;10. La Source, School of Nursing, University of Applied Sciences and Arts Western Switzerland (HES-SO), Lausanne, Switzerland;1. Department of Geography and Planning, University of Toronto, 100 St. George Street, Toronto, ON, M5S 3G3, Canada;2. Department of Geography, Geomatics and Environment, University of Toronto Mississauga, 3359 Mississauga Road, Mississauga, ON, L5L 1C6, Canada;1. School of Planning, Faculty of Environment, University of Waterloo, Waterloo, Ontario, Canada;2. Geographies of Health in Place, Planning, and Public Health Lab (GoHelP Lab), University of Waterloo, Waterloo, Ontario, Canada;3. School of Public Health and Health Sciences, Faculty of Applied Health Sciences, University of Waterloo, Waterloo, Ontario, Canada;1. Lee Kuan Yew School of Public Policy, National University of Singapore, 469C Bukit Timah Rd, National University of Singapore, 259772, Singapore;2. Department of Urban Studies and Planning, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA, 02139, USA;1. Department of Urban Planning, School of Architecture and Fine Art, Dalian University of Technology, Dalian, China;2. Department of Movement and Sports Sciences, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium
Abstract:Low-income communities and communities of color face multiple, cumulative environmental and social burdens. Methods development in environmental justice research has largely focused on spatial and quantitative approaches. Less attention has been paid to developing methodologies that help collect information on everyday stressors and quality of life experiences for residents in overburdened communities. Mixed methods approaches can be one way to structure study designs that help consider how residents experience environmental and socioeconomic impacts in a localized community context. In neighborhoods burdened by cumulative stressors, traditional cross-sectional epidemiological research designs can also be challenging, as well as limited or narrow in their application. However, repeat sampling of measures within a vulnerable population can approach a quasi-experimental design and help consider variations within residents in a single neighborhood as well as better parse relationships between exposures and outcomes. Through a community-academic partnership with university partners, local community partners, and a local promotores de salud (community health workers) network, we pilot tested a novel mobile daily diary approach in both English and Spanish in an urban, predominantly immigrant community in South Los Angeles as a potential method to collect information on daily stress, environmental quality, and health status/symptoms. We collected resident responses via a once per day 7-day SMS/text messaging survey. We sought to gather granular data on daily resident experiences of air pollution and environmental hazards. Residents reported acute health symptoms and stressors, with repeat measures demonstrating how residents might rank, categorize, or cope with stressors. We find that residents in environmental justice communities record variation in their daily diary responses and document changes in environmental quality, stressors, and odors. Refining this type of method could enable a more rigorous examination of co-occurrences of environmental quality and acute health symptoms. This approach supports the inclusion of residents in the research process and helps more systematically integrate open-ended environmental health relevant data in environmental justice efforts. Used with measured data such as air monitoring or health measures, mixed methods generated data can help support efforts that aim to alleviate sources of daily stress, alongside efforts to reduce overall pollution burdens. Mobile daily diaries can be one way to capture variable responses to environmental quality, acute health symptoms, and stressors.
Keywords:Environmental justice  Text messaging  Mobile  SMS  Daily diary  Environmental health  Cumulative impacts  Mixed methods  Qualitative data  Community based research  stress
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