title: Quantifying spatial misclassification in exposure to noise complaints among low-income housing residents across New York City neighborhoods: a Global Positioning System (GPS) study.
abstract: To 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.
  
  
  
  Data 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.
  
  
  
  There 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.
  
  
  
  These 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.
authors.affiliation: Department of Population Health, New York University School of Medicine, New York. Electronic address: Dustin.Duncan@nyumc.org.
authors.forename: Dustin T
authors.initials: DT
authors.lastname: Duncan
authors.affiliation: Department of Population Health, New York University School of Medicine, New York.
authors.forename: Kosuke
authors.initials: K
authors.lastname: Tamura
authors.affiliation: Department of Population Health, New York University School of Medicine, New York.
authors.forename: Seann D
authors.initials: SD
authors.lastname: Regan
authors.affiliation: Department of Population Health, New York University School of Medicine, New York.
authors.forename: Jessica
authors.initials: J
authors.lastname: Athens
authors.affiliation: Department of Population Health, New York University School of Medicine, New York; Wagner Graduate School of Public Service, New York University, New York.
authors.forename: Brian
authors.initials: B
authors.lastname: Elbel
authors.affiliation: Sorbonne Universités, UPMC Univ Paris 06, UMR_S 1136, Pierre Louis Institute of Epidemiology and Public Health, Paris, France; Inserm, UMR_S 1136, Pierre Louis Institute of Epidemiology and Public Health, Paris, France.
authors.forename: Julie
authors.initials: J
authors.lastname: Meline
authors.affiliation: Department of Population Health, New York University School of Medicine, New York.
authors.forename: Yazan A
authors.initials: YA
authors.lastname: Al-Ajlouni
authors.affiliation: Sorbonne Universités, UPMC Univ Paris 06, UMR_S 1136, Pierre Louis Institute of Epidemiology and Public Health, Paris, France; Inserm, UMR_S 1136, Pierre Louis Institute of Epidemiology and Public Health, Paris, France.
authors.forename: Basile
authors.initials: B
authors.lastname: Chaix
mesh_terms: D004781:Environmental Exposure / Q000706:statistics & numerical data*; D005260:Female; D040362:Geographic Information Systems; D006801:Humans; D015994:Incidence; D008297:Male; D009519:New York City / Q000453:epidemiology; D009622:Noise / Q000009:adverse effects*; D010865:Pilot Projects; D011203:Poverty / Q000706:statistics & numerical data*; D012111:Residence Characteristics / Q000706:statistics & numerical data*; D018570:Risk Assessment; D062206:Spatial Analysis; D014505:Urban Population
keywords: Geographic information systems; Global positioning systems; Low-income housing residents; Neighborhoods; Noise complaint exposure; Spatial epidemiology; Spatial misclassification