Quantifying spatial misclassification in exposure to noise complaints among low-income housing residents across New York City neighborhoods: a Global Positioning System (GPS) study |
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| Affiliation: | 1. Department of Population Health, New York University School of Medicine, New York;2. Wagner Graduate School of Public Service, New York University, New York;3. Sorbonne Universités, UPMC Univ Paris 06, UMR_S 1136, Pierre Louis Institute of Epidemiology and Public Health, Paris, France;4. Inserm, UMR_S 1136, Pierre Louis Institute of Epidemiology and Public Health, Paris, France;1. Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas;2. Harold C. Simmons Comprehensive Cancer Center, Dallas, TX;1. Civil Engineering, University of Toronto, Canada;2. Direction régionale de santé publique du CIUSS du Centre-Sud-de-l′Île-de Montréal, Canada;3. Department of Geography and Environmental Studies, Faculty of Arts, Ryerson University, Canada;4. Department of Environmental Health and Occupational Health, School of Public Health, Universtiy of Montreal, Canada;5. Department of Epidemiology, Biostatistics and Occupational Health, Faculty of Medicine, McGill University, Canada;1. National Institute of Environmental Health Research Center, National Health Research Institutes, Taiwan;2. Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia;3. Department of Health Services Policy & Management, University of South Carolina, Columbia;4. South Carolina Rural Health Research Center, University of South Carolina, Columbia;5. Department of Family and Preventive Medicine, School of Medicine, University of South Carolina, Columbia;6. Cancer Prevention and Control Program, University of South Carolina, Columbia;1. Department of Public Health, Medical University of South Carolina, Charleston;2. Department of Community and Family Health, University of South Florida, Tampa;3. Interuniversity Institute for Statistics and Statistical Bioinformatics, Hasselt University, Agoralaan 1, Diepenbeek, Belgium;1. Department of Health Behavior & Health Education, University of Michigan School of Public Health, 1415 Washington Heights, Ann Arbor, MI 48109-2029, USA;2. Department of Health Systems Science, University of Illinois at Chicago College of Nursing, 845 S. Damen Ave., Chicago, IL 60612, USA;3. McAuley School of Health Professions, University of Detroit Mercy, 4001 W. McNichols Road, Detroit, MI 48221-3038, USA;1. MA Regional and Urban Planning, Université Laval, Québec, Québec G1V 0A6, Canada;2. Université Laval, Québec, Québec G1V 0A6, Canada;3. INRS-UCS, Montréal, Québec H2X 1E3, Canada;4. Direction de la planification et de la mobilité durable, Ministère des Transports du Québec (MTQ), Québec, Canada |
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| Abstract: | PurposeTo examine if there was spatial misclassification in exposure to neighborhood noise complaints among a sample of low-income housing residents in New York City, comparing home-based spatial buffers and Global Positioning System (GPS) daily path buffers.MethodsData came from the community-based NYC Low-Income Housing, Neighborhoods and Health Study, where GPS tracking of the sample was conducted for a week (analytic n = 102). We created a GPS daily path buffer (a buffering zone drawn around GPS tracks) of 200 m and 400 m. We also used home-based buffers of 200 m and 400 m. Using these “neighborhoods” (or exposure areas), we calculated neighborhood exposure to noisy events from 311 complaints data (analytic n = 143,967). Friedman tests (to compare overall differences in neighborhood definitions) were applied.ResultsThere were differences in neighborhood noise complaints according to the selected neighborhood definitions (P < .05). For example, the mean neighborhood noise complaint count was 1196 per square kilometer for the 400-m home-based and 812 per square kilometer for the 400-m activity space buffer, illustrating how neighborhood definition influences the estimates of exposure to neighborhood noise complaints.ConclusionsThese analyses suggest that, whenever appropriate, GPS neighborhood definitions can be used in spatial epidemiology research in spatially mobile populations to understand people's lived experience. |
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| Keywords: | Spatial epidemiology Spatial misclassification Neighborhoods Geographic information systems Global positioning systems Low-income housing residents Noise complaint exposure |
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