title: Comparing children's GPS tracks with geospatial proxies for exposure to junk food.
abstract: Various geospatial techniques have been employed to estimate children's exposure to environmental cardiometabolic risk factors, including junk food. But many studies uncritically rely on exposure proxies which differ greatly from actual exposure. Misrepresentation of exposure by researchers could lead to poor decisions and ineffective policymaking. This study conducts a GIS-based analysis of GPS tracks--'activity spaces'--and 21 proxies for activity spaces (e.g. buffers, container approaches) for a sample of 526 children (ages 9-14) in London, Ontario, Canada. These measures are combined with a validated food environment database (including fast food and convenience stores) to create a series of junk food exposure estimates and quantify the errors resulting from use of different proxy methods. Results indicate that exposure proxies consistently underestimate exposure to junk foods by as much as 68%. This underestimation is important to policy development because children are exposed to more junk food than estimated using typical methods.
authors.affiliation: Department of Family Medicine, Michigan State University, 200 E 1st St, Flint, MI 48502, United States. Electronic address: rsadler4@gmail.com.
authors.forename: Richard C
authors.initials: RC
authors.lastname: Sadler
authors.affiliation: Department of Geography, Faculty of Health Sciences, and Department of Paediatrics, University of Western Ontario, 1151 Richmond St, London, ON N6A 5C2, Canada. Electronic address: jgillila@uwo.ca.
authors.forename: Jason A
authors.initials: JA
authors.lastname: Gilliland
mesh_terms: D000293:Adolescent; D015982:Bias; D002170:Canada / Q000453:epidemiology; D002648:Child; D000067576:Child Health / Q000706:statistics & numerical data; D004032:Diet / Q000706:statistics & numerical data*; D057140:Fast Foods / Q000706:statistics & numerical data; D005247:Feeding Behavior; D005260:Female; D040362:Geographic Information Systems; D006801:Humans; D008297:Male; D008659:Metabolic Diseases / Q000453:epidemiology; D009864:Ontario / Q000453:epidemiology; D012307:Risk Factors; D013029:Space-Time Clustering
keywords: Bias; Children’s health; Error estimation; GPS tracking; Geographic information systems; Junk food exposure