Spatial relationships between alcohol-related road crashes and retail alcohol availability.

BACKGROUND This study examines spatial relationships between alcohol outlet density and the incidence of alcohol-related crashes. The few prior studies conducted in this area used relatively large spatial units; here we use highly resolved units from Melbourne, Australia (Statistical Area level 1 [SA1] units: mean land area=0.5 km(2); SD=2.2 km(2)), in order to assess different micro-scale spatial relationships for on- and off-premise outlets. METHODS Bayesian conditional autoregressive Poisson models were used to assess cross-sectional relationships of three-year counts of alcohol-related crashes (2010-2012) attended by Ambulance Victoria paramedics to densities of bars, restaurants, and off-premise outlets controlling for other land use, demographic and roadway characteristics. RESULTS Alcohol-related crashes were not related to bar density within local SA1 units, but were positively related to bar density in adjacent SA1 units. Alcohol-related crashes were negatively related to off-premise outlet density in local SA1 units. CONCLUSIONS Examined in one metropolitan area using small spatial units, bar density is related to greater crash risk in surrounding areas. Observed negative relationships for off-premise outlets may be because the origins and destinations of alcohol-affected journeys are in distal locations relative to outlets.

[1]  Paul J Gruenewald,et al.  Drinking, driving, and crashing: a traffic-flow model of alcohol-related motor vehicle accidents. , 2010, Journal of studies on alcohol and drugs.

[2]  Paul J Gruenewald,et al.  The impact of outlet densities on alcohol-related crashes: a spatial panel approach. , 2007, Accident; analysis and prevention.

[3]  H. Cutter,et al.  The relationship of beer consumption and state alcohol and motor vehicle policies to fatal accidents , 1983 .

[4]  D. Giacopassi,et al.  Alcohol availability and alcohol-related crashes: does distance make a difference? , 1995, The American journal of drug and alcohol abuse.

[5]  Christopher M Doran,et al.  Comparing the cost of alcohol-related traffic crashes in rural and urban environments. , 2010, Accident; analysis and prevention.

[6]  R. Jewell,et al.  Alcohol availability and alcohol-related motor vehicle accidents , 1995 .

[7]  K. Kelleher,et al.  Alcohol availability and motor vehicle fatalities. , 1996, The Journal of adolescent health : official publication of the Society for Adolescent Medicine.

[8]  Svetlana Popova,et al.  Hours and days of sale and density of alcohol outlets: impacts on alcohol consumption and damage: a systematic review. , 2009, Alcohol and alcoholism.

[9]  P. Diggle Applied Spatial Statistics for Public Health Data , 2005 .

[10]  P. Gruenewald,et al.  Spatial panel analyses of alcohol outlets and motor vehicle crashes in California: 1999-2008. , 2013, Accident; analysis and prevention.

[11]  Patrick McCarthy Alcohol-related crashes and alcohol availability in grass-roots communities , 2003 .

[12]  Karen Smith,et al.  The development of a data-matching algorithm to define the 'case patient'. , 2013, Australian health review : a publication of the Australian Hospital Association.

[13]  D. Chisholm,et al.  Effectiveness and cost-effectiveness of policies and programmes to reduce the harm caused by alcohol , 2009, The Lancet.

[14]  Jennifer Cook Middleton,et al.  The effectiveness of limiting alcohol outlet density as a means of reducing excessive alcohol consumption and alcohol-related harms. , 2009, American journal of preventive medicine.

[15]  P. Gruenewald,et al.  The geography of availability and driving after drinking. , 1996, Addiction.

[16]  I. Colón The influence of state monopoly of alcohol distribution and the frequency of package stores on single motor vehicle fatalities. , 1982, The American journal of drug and alcohol abuse.

[17]  S. Rubenzer Judging intoxication. , 2011, Behavioral sciences & the law.

[18]  C. Morrison Exposure to alcohol outlets in rural towns. , 2015, Alcoholism, clinical and experimental research.

[19]  D. Mackinnon,et al.  Alcohol outlet density and motor vehicle crashes in Los Angeles County cities. , 1994, Journal of studies on alcohol.

[20]  Andrew Thomas,et al.  WinBUGS - A Bayesian modelling framework: Concepts, structure, and extensibility , 2000, Stat. Comput..