title: Improving data accuracy of commercial food outlet databases.
abstract: PURPOSE. Assessing food environments often requires using commercially available data. Disparate methods used for classifying food outlets in these databases call for creating a classification approach using common definitions. A systematic strategy for reclassifying food stores and restaurants, as they appear in commercial databases, into categories that differentiate the availability of healthy options is described here. DESIGN AND SETTING. Commercially available data on food outlets including names, addresses, North American Industry Classification System codes, and associated characteristics was obtained for five New Jersey communities. ANALYSIS. A reclassification methodology was developed using criteria and definitions from the literature to categorize food outlets based on availability of healthy options. Information in the database was supplemented by systematic Internet and key word searches, and from phone calls to food outlets. RESULTS. The methodology resulted in 622 supermarket/grocery stores, 183 convenience stores, and 148 specialty stores in the original data to be reclassified into 58 supermarkets, 30 grocery stores, 692 convenience stores, and 115 specialty stores. Outlets from the original list of 1485 full-service restaurants and 506 limited-service restaurants were reclassified as 563 full-service restaurants and 1247 limited-service restaurants. Reclassification resulted in less than one-seventh the number of supermarkets and grocery stores, more than three times the number of convenience stores, and twice as many limited-service restaurants-a much less healthy profile than the one generated by using exclusively the commercial databases. CONCLUSION. An explicit and replicable strategy is proposed for reclassifying food outlets in commercial databases into categories that differentiate on the basis of healthy food availability. The intent is to contribute towards building a consensus among researchers on definitions used in public health research for characterizing different types of food outlets.
authors: Center for State Health Policy, Rutgers University, NewBrunswick, New Jersey, USA. pohrivac@asu.edu
authors: Punam
authors: P
authors: Ohri-Vachaspati
authors: Diane
authors: D
authors: Martinez
authors: Michael J
authors: MJ
authors: Yedidia
authors: Nirvana
authors: N
authors: Petlick
mesh_terms: D003625:Data Collection / Q000145:classification*; D016208:Databases, Factual / Q000592:standards* / Q000706:statistics & numerical data; D005523:Food Supply / Q000145:classification*; D006293:Health Promotion / Q000379:methods; D006801:Humans; D009515:New Jersey; D009753:Nutritive Value; D010865:Pilot Projects; D012107:Research Design / Q000592:standards* / Q000706:statistics & numerical data; D012147:Restaurants / Q000145:classification* / Q000706:statistics & numerical data