Neighborhood level spatial analysis of the relationship between alcohol outlet density and criminal violence

被引:84
作者
Britt H.R. [1 ]
Carlin B.P. [2 ]
Toomey T.L. [3 ]
Wagenaar A.C. [4 ]
机构
[1] Minnesota Department of Education, Safe and Healthy Learners Unit, Roseville, MN
[2] School of Public Health, Division of Biostatistics, University of Minnesota, Minneapolis
[3] School of Public Health, Division of Epidemiology, University of Minnesota, Minneapolis, MN
[4] College of Medicine, Department of Epidemiology and Health Policy Research, University of Florida, Gainesville, FL
关键词
Alcohol; Bayesian; Criminal violence; Markov chain Monte Carlo; Neighborhood;
D O I
10.1007/s10651-005-1518-3
中图分类号
学科分类号
摘要
Misuse of alcohol is a significant public health problem, potentially resulting in unintentional injuries, motor vehicle crashes, drownings, and, perhaps of greatest concern, serious acts of violence, including assaults, rapes, suicides, and homicides. Although previous research establishes a link between alcohol consumption increased levels of violence, studies relating the density of alcohol outlets (e.g., restaurants, bars, liquor stores) and the likelihood of violent crime have been less common. In this paper we test for such a relationship at the small area level, using data from 79 neighborhoods in the city of Minneapolis, Minnesota. We adopt a fully Bayesian point of view using Markov chain Monte Carlo (MCMC) computational methods as available in the popular and freely available WinBUGS language. Our models control for important covariates (e.g., neighborhood racial heterogeneity, age heterogeneity) and also account for spatial association in unexplained variability using conditionally autoregressive (CAR) random effects. Our results indicate a significant positive relationship between alcohol outlet density and violent crime, while also permitting easy mapping of neighborhood-level predicted and residual values, the former useful for intervention in the most at-risk neighborhoods and the latter potentially useful in identifying covariates still missing from the fixed effects portion of the model. © 2005 Springer Science+Business Media, Inc.
引用
收藏
页码:411 / 426
页数:15
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