significantly associated with either short (r=-0.001, p=0.86) or long-term (r=0.04, p=0.08) trends in violent crime or assault. Mair et al. used a similar technique to the Gruenewald and Remer study above by looking at AOD and violence in California using zip codes from 1995 to 2008.() To analyze the data they used Bayesian space-time conditional autoregressive models. Mair et al. found that an addition of one AOD per square mile was associated with 1.8% increase in assaults (RR=1.018, 95% CI: 1.011-1.025). When the types of outlets were separated a greater difference between outlets types were found. Lipton et al. compared restaurants selling any type of alcohol, restaurants selling only beer and wine, off-premise, and nonstore/nonrestaurant to violent crime in Boston, MA.() Using Poisson regression models, the authors found that number of restaurants selling any type of alcohol was significantly associated with a slight increase of violent crime (b=0.079, p<0.001) but on-premise outlets (b=-0.035, p>0.05) and off-premise outlets (b=0.067, p>0.05) were not statistically associated with violent crime. For weekday violence, the authors found that number of restaurants selling any type of alcohol was significantly associated with a slight increase of violent crime (b=0.071, p<0.001) but on-premise outlets (b=-0.036, p>0.05) and off-premise outlets (b=0.063, p>0.05) were not statistically associated with violent crime. For weekend violence, the authors found that number of restaurants selling any type of alcohol was significantly associated with a slight increase of violent crime (b=0.091, p<0.001) but on-premise
significantly associated with either short (r=-0.001, p=0.86) or long-term (r=0.04, p=0.08) trends in violent crime or assault. Mair et al. used a similar technique to the Gruenewald and Remer study above by looking at AOD and violence in California using zip codes from 1995 to 2008.() To analyze the data they used Bayesian space-time conditional autoregressive models. Mair et al. found that an addition of one AOD per square mile was associated with 1.8% increase in assaults (RR=1.018, 95% CI: 1.011-1.025). When the types of outlets were separated a greater difference between outlets types were found. Lipton et al. compared restaurants selling any type of alcohol, restaurants selling only beer and wine, off-premise, and nonstore/nonrestaurant to violent crime in Boston, MA.() Using Poisson regression models, the authors found that number of restaurants selling any type of alcohol was significantly associated with a slight increase of violent crime (b=0.079, p<0.001) but on-premise outlets (b=-0.035, p>0.05) and off-premise outlets (b=0.067, p>0.05) were not statistically associated with violent crime. For weekday violence, the authors found that number of restaurants selling any type of alcohol was significantly associated with a slight increase of violent crime (b=0.071, p<0.001) but on-premise outlets (b=-0.036, p>0.05) and off-premise outlets (b=0.063, p>0.05) were not statistically associated with violent crime. For weekend violence, the authors found that number of restaurants selling any type of alcohol was significantly associated with a slight increase of violent crime (b=0.091, p<0.001) but on-premise