title: Using ZIP code business patterns data to measure alcohol outlet density.
abstract: Some states maintain high-quality alcohol outlet databases but quality varies by state, making comprehensive comparative analysis across US communities difficult. This study assesses the adequacy of using ZIP Code Business Patterns (ZIP-BP) data on establishments as estimates of the number of alcohol outlets by ZIP code. Specifically we compare ZIP-BP alcohol outlet counts with high-quality data from state and local records surrounding 44 college campus communities across 10 states plus the District of Columbia. Results show that a composite measure is strongly correlated (R=0.89) with counts of alcohol outlets generated from official state records. Analyses based on Generalized Estimation Equation models show that community and contextual factors have little impact on the concordance between the two data sources. There are also minimal inter-state differences in the level of agreement. To validate the use of a convenient secondary data set (ZIP-BP) it is important to have a high correlation with the more complex, high quality and more costly data product (i.e., datasets based on the acquisition and geocoding of state and local records) and then to clearly demonstrate that the discrepancy between the two to be unrelated to relevant explanatory variables. Thus our overall findings support the adequacy of using a conveniently available data set (ZIP-BP data) to estimate alcohol outlet densities in ZIP code areas in future research.
authors.affiliation: Department of Sociology, Penn State University, University Park, PA 16802, United States. sxm27@psu.edu
authors.forename: Stephen A
authors.initials: SA
authors.lastname: Matthews
authors.forename: John D
authors.initials: JD
authors.lastname: McCarthy
authors.forename: Patrick S
authors.initials: PS
authors.lastname: Rafail
mesh_terms: D000434:Alcoholic Beverages / Q000600:supply & distribution*; D003132:Commerce / Q000706:statistics & numerical data*; D040362:Geographic Information Systems; D006801:Humans; D008004:Licensure / Q000706:statistics & numerical data; D015233:Models, Statistical; D014481:United States; D014495:Universities