title: Characterizing the food retail environment: impact of count, type, and geospatial error in 2 secondary data sources.
abstract: OBJECTIVE
  Commercial listings of food retail outlets are increasingly used by community members and food policy councils and in multilevel intervention research to identify areas with limited access to healthier food. This study quantified the amount of count, type, and geospatial error in 2 commercial data sources.
  
  
  METHODS
  InfoUSA and Dun and Bradstreet were compared with a validated field census and validity statistics were calculated.
  
  
  RESULTS
  Considering only completeness, Dun and Bradstreet data undercounted 24% of existing supermarkets and grocery stores, and InfoUSA, 29%. In addition, considering accuracy of outlet type assignment increased the undercount error to 42% and 39%, respectively. Marked overcount existed as well, and only 43% of existing supermarkets were correctly identified with respect to presence, outlet type, and location.
  
  
  CONCLUSIONS
  Relying exclusively on secondary data to characterize the food environment will result in substantial error. Whereas extensive data cleaning can offset some error, verification of outlets with a field census is still the method of choice.
authors.affiliation: Center for Research in Nutrition and Health Disparities, Arnold School of Public Health, University of South Carolina, Columbia, SC; Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, SC. Electronic address: liese@sc.edu.
authors.forename: Angela D
authors.initials: AD
authors.lastname: Liese
authors.forename: Timothy L
authors.initials: TL
authors.lastname: Barnes
authors.forename: Archana P
authors.initials: AP
authors.lastname: Lamichhane
authors.forename: James D
authors.initials: JD
authors.lastname: Hibbert
authors.forename: Natalie
authors.initials: N
authors.lastname: Colabianchi
authors.forename: Andrew B
authors.initials: AB
authors.lastname: Lawson
mesh_terms: D004777:Environment; D005523:Food Supply / Q000706:statistics & numerical data*; D006801:Humans; D011634:Public Health; D015203:Reproducibility of Results; D012147:Restaurants / Q000706:statistics & numerical data*; D012959:Socioeconomic Factors; D013022:South Carolina
keywords: food desert; geography; retail food environment; secondary data sources; validity