The effects of the 2006 Russian alcohol policy on alcohol-related mortality: an interrupted time series analysis.

BACKGROUND: The aim of this study was to determine the impact of a set of 2006 Russian alcohol policies on alcohol-related mortality in the country. METHODS: We used autoregressive integrated moving average interrupted time series techniques to model the impact of the policy on the number of sex-specific monthly deaths of those aged 15+ years due to alcohol poisoning, alcoholic cardiomyopathy, alcoholic liver cirrhosis, and alcohol-related mental and behavioral disorders. The time series began in January 2000 and ended in December 2010. The alcohol policy was implemented in January 2006. RESULTS: The alcohol policy resulted in a significant gradual and sustained decline in male deaths due to alcohol poisoning (ωo = -92.631, p < 0.008, δ1 = 0.883, p < 0.001) and in significant immediate and sustained declines in male (ω0 = -63.20, p < 0.05) and female (ω0 = -64.28, p < 0.005) deaths due to alcoholic liver cirrhosis. CONCLUSIONS: The 2006 suite of alcohol policies in Russia was responsible for an annual decline of about 6,700 male alcohol poisoning deaths and about 760 male and about 770 female alcoholic liver cirrhosis deaths. Without the alcohol policy, male alcohol poisoning deaths would have been 35% higher and male and female alcoholic liver cirrhosis deaths would have been 9 and 15% higher, respectively. We contextualize our findings in relation to declining mortality in Russia and to results from recent studies of the impact of this law on other causes of death.

The impact of a national alcohol policy on deaths due to transport accidents in Russia.

AIMS: To determine the impact of a suite of 2006 Russian alcohol control policies on deaths due to traffic accidents in the country. DESIGN, SETTING AND PARTICIPANTS: We used autoregressive integrated moving average (ARIMA) interrupted time-series techniques to model the impact of the intervention on the outcome series. The time-series began in January 2000 and ended in December 2010. The alcohol policy was implemented in January 2006, providing 132 monthly observations in the outcome series, with 72 months of pre-intervention data and 60 months of post-intervention data. MEASUREMENTS: The outcome variables were the monthly number of male- and female-specific deaths of those aged 15+ years due to transport accidents in Russia. FINDINGS: The 2006 set of alcohol policies had no impact on female deaths due to traffic accidents (ω0 = -50.31, P = 0.27). However, the intervention model revealed an immediate and sustained monthly decrease of 203 deaths due to transport accidents for males (ω0 = -203.40, P = 0.04), representing an 11% reduction relative to pre-intervention levels. CONCLUSION: The implementation of the suite of 2006 Russian alcohol control policies is partially responsible for saving more than 2400 male lives annually that would otherwise have been lost to traffic accidents.

Comparative modeling approaches for understanding urban violence.

The purpose of this paper is to provide a comparative analysis of three different modeling approaches for exploring structural theories of violence. Specifically, ordinary least squares regression, geographically weighted regression and data envelopment analysis will be utilized to evaluate violent crime. This type of analysis expands upon traditional theory testing by deepening our understanding of differences in crime generation and its underlying demographic and socio-economic stimuli via different methodological lenses. A case study for the city of Cincinnati, Ohio is presented and the results suggest that a combination of approaches is likely the best strategy for evaluating violence in urban areas.

A reassessment of the association between social disorganization and youth violence in rural areas.

OBJECTIVE: To study the association between social disorganization and youth violence rates in rural communities. METHOD: We employed rural Missouri counties (N = 106) as units of analysis, measured serious violent victimization data via hospital records, and the same measures of social disorganization as Osgood and Chambers (2000). Controlling for spatial autocorrelation, the negative binomial estimator was used to estimate the effects of social disorganization on youth violence rates. RESULTS: Unlike Osgood and Chambers, we found only one of five social disorganization measures, the proportion of female-headed households, to be associated with rural youth violent victimization rates. CONCLUSION: Although most research on social disorganization theory has been undertaken on urban areas, a highly cited Osgood and Chambers (2000) study appeared to extend the generalize ability of social disorganization as an explanation of the distribution of youth violence to rural areas. Our results suggest otherwise. We provide several methodological and theoretical reasons why it may be too early to draw strong conclusions about the generalize ability of social disorganization to crime rates in rural communities.