Swedish Institute for Social Research, Stockholm University, Stockholm, Sweden.
Drug Alcohol Rev. 2011 Sep;30(5):458-65. doi: 10.1111/j.1465-3362.2011.00295.x.
Several aggregate-level studies have suggested that the relationship between alcohol and homicide is stronger in countries with an intoxication-oriented drinking pattern than in countries where drinking is more tempered. The present paper extends this research tradition by analysing the alcohol-homicide link in various regions in the USA.
I used annual time-series data for the US states covering the period 1950-2002. Alcohol sales figures were used as proxy for alcohol consumption. Mortality data were used as indicators of homicide. The states were sorted into three groups labelled Dry, Moderate and Wet, where the last group has the highest prevalence of hazardous drinking according to survey data. Group-specific data were analysed using (i) autoregressive integrated moving average (ARIMA) modelling and (ii) fixed effects modelling. All modelling was based on differenced data, thus eliminating time trends and interstate correlations, both of which may bias estimates.
The ARIMA estimates displayed a statistically significant gradient in alcohol effects; the effect was strongest in Wet, and weakest and insignificant in Dry states. The fixed-effects estimates showed a corresponding pattern, although the gradient was less steep and insignificant. The gradient was also weakened if the effects were expressed in absolute rather than relative terms. The spatial pattern revealed no ecological correlation between alcohol and homicide.
Results provided mixed support for the hypothesis that the relationship between alcohol and homicide is stronger in wet than in dry states in the USA. Future research should probe more specific indicators of homicide as well as alcohol consumption.
一些总体水平的研究表明，在以醉酒为导向的饮酒模式的国家，酒精与凶杀之间的关系比在饮酒更为节制的国家更为密切。本文通过分析美国各地区的酒精与凶杀之间的关系，扩展了这一研究传统。
我使用了涵盖 1950-2002 年期间的美国各州的年度时间序列数据。酒精销售量被用作酒精消费的代理指标。死亡率数据被用作凶杀的指标。根据调查数据，各州被分为三个组，分别标记为 Dry、Moderate 和 Wet，其中最后一组有最高的危险饮酒率。使用（i）自回归综合移动平均（ARIMA）模型和（ii）固定效应模型对特定组的数据进行分析。所有模型都是基于差分数据，从而消除了时间趋势和州际相关性，这两者都可能会产生偏差。
ARIMA 估计显示出酒精效应的统计学显著梯度；在 Wet 州的效应最强，在 Dry 州的效应最弱且不显著。固定效应估计显示出相应的模式，尽管梯度较平缓且不显著。如果将效应表示为绝对值而不是相对值，则梯度会减弱。空间模式显示出酒精和凶杀之间没有生态学相关性。
结果为美国 Wet 州比 Dry 州之间酒精与凶杀之间的关系更强的假设提供了混合支持。未来的研究应该探究更具体的凶杀指标以及酒精消费。
