title: Population drinking and homicide in Australia: a time series analysis of the period 1950-2003.
abstract: BACKGROUND
  Despite a significant amount of research on alcohol and homicide in Australia, as yet there has been no study of the association at the aggregate level to reveal where Australia fits in with respect to the cultural differences found in the international research of this association. Aims. To analyse the temporal association between population drinking and homicide in Australia and to put the results in an international comparative perspective.
  
  
  METHODS
  Using Autoregressive Integrated Moving Average (ARIMA) time series analysis, overall and gender-specific homicide rates from 1950 to 2003 were analysed in relation to alcohol consumption overall as well as to different beverages.
  
  
  RESULTS
  A one-litre increase in per capita consumption was followed by an 8% increase in overall and male homicide rates and a 6% increase in female homicide rates. The effect was mainly driven by beer consumption. In a comparative perspective, the importance of population drinking was similar to what has been found in Western Europe. Conclusions. Australia belongs to the group of countries where lowering population drinking is likely to be associated with lower homicide rates and reducing beer consumption seems to be the most efficient way to achieve this.
authors: Centre for Social Research on Alcohol and Drugs, Stockholm University, Stockholm, Sweden. mats.ramstedt@sorad.su.se
authors: Mats
authors: M
authors: Ramstedt
mesh_terms: D000293:Adolescent; D000328:Adult; D000428:Alcohol Drinking / Q000453:epidemiology* / Q000639:trends; D000434:Alcoholic Beverages / Q000706:statistics & numerical data*; D001315:Australia / Q000453:epidemiology; D001515:Beer / Q000706:statistics & numerical data; D003132:Commerce / Q000706:statistics & numerical data / Q000639:trends; D003431:Cross-Cultural Comparison; D005060:Europe / Q000453:epidemiology; D005260:Female; D006708:Homicide / Q000706:statistics & numerical data* / Q000639:trends; D006801:Humans; D008297:Male; D015233:Models, Statistical; D012737:Sex Factors; D013997:Time Factors; D055815:Young Adult