The availability of local, state, and national data on alcohol outlet density have important implications for policies and interventions aiming to reduce alcohol-related problems. High-quality data on locations of alcohol outlets is important to accurately inform community interventions and public health initiatives, but such data is often not maintained, readily available, or of sufficient quality. Objectives: This study aims to examine the discrepancies between alcohol outlet databases and how neighborhood characteristics (i.e. income, majority racial population, urbanicity) are associated with the discrepancies between databases. Methods: Data was collected from national (n = 1), local (n = 2), and state databases (n = 3). Negative binomial regression models were used to assess discrepancies in alcohol outlet count at the ZIP code level based on the data source. Results: The average density of alcohol outlets (per 1000 residents) ranged from 0.71 to 2.17 in Maryland, 1.65 to 5.17 in Wisconsin, and 1.09 to 1.22 in Oregon based on different sources of data. Findings suggest high income areas (>200% poverty level) have fewer discrepancies (IR = 0.775, p < 0.01), low income areas (below poverty level) have greater discrepancies (IR = 4.990, p < 0.01), and urban areas tend to have fewer discrepancies (IR = 0.378, p < 0.01) between datasets. Conclusion: Interventions and policies depend on valid and reliable data; researchers, policymakers, and local agencies need to collaborate to develop methods to maintain accurate and accessible data.
Keywords: Alcohol outlet databases; alcohol; alcohol outlet density; alcohol outlet listings; policy.