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Alcohol Outlet Clusters and Population Disparities.

Pamela J TrangensteinClaire GrayMatthew E RossheimRichard SadlerDavid H Jernigan
Published in: Journal of urban health : bulletin of the New York Academy of Medicine (2020)
Alcohol outlet clusters are an important social determinant of health in cities, but little is known about the populations exposed to them. If outlets cluster in neighborhoods comprised of specific racial/ethnic or economic groups, then they may function as a root cause of urban health disparities. This study used 2016 liquor license data (n = 1204) from Baltimore City, Maryland, and demographic data from the American Community Survey. We defined alcohol outlet clusters by combining SaTScan moving window methods and distances between outlets. We used multiple logistic regression to compare census block groups (CBGs) (n = 537) inside and outside of four types of outlet clusters: total, on-premise, off-premise, and LBD-7 (combined on-/off-premise). The most robust predictor of alcohol outlet cluster membership was a history of redlining, i.e., racially discriminatory lending policies. CBGs that were redlined had 7.32 times the odds of being in an off-premise cluster, 8.07 times the odds of being in an on-premise cluster, and 8.60 times the odds of being in a LBD-7 cluster. In addition, level of economic investment (marked by vacant properties) appears to be a key characteristic that separates CBGs in on- and off-premise outlet clusters. CBGs with racial/ethnic or socioeconomic advantage had higher odds of being in on-premise clusters and CBGs marked by disinvestment had higher odds of being in off-premise clusters. Off-premise clusters deserve closer examination from a policy perspective, to mitigate their potential role in creating and perpetuating social and health disparities. In addition to addressing redlining and disinvestment, the current negative effects of alcohol outlet clusters that have grown up in redlined and disinvested areas must be addressed if inequities in these neighborhoods are to be reversed.
Keyphrases
  • healthcare
  • mental health
  • public health
  • alcohol consumption
  • electronic health record
  • risk assessment
  • cross sectional
  • climate change
  • affordable care act
  • artificial intelligence