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毒品“热点地区”、酒精供应与暴力

Drug 'hot-spots', alcohol availability and violence.

作者信息

Gorman D M, Zhu Li, Horel Scott

机构信息

Department of Epidemiology and Biostatistics, Texas A&M Health Science Center, USA.

出版信息

Drug Alcohol Rev. 2005 Nov;24(6):507-13. doi: 10.1080/09595230500292946.

Abstract

Ecological studies have shown a relationship between alcohol outlet densities and violence and between the location of crimes related to illicit drug use (so-called 'hot spots') and violence. To date, no study has compared the effects of alcohol outlets and drug hot spots on rates of violence. The present study examined this relationship in the City of Houston, Texas. An ecological study design was employed, using a sample of 439 census tracts from Houston, Texas. Neighborhood socio-structural, alcohol outlet density, drug crime density and violent crime density data were collected from archival sources and analyzed using multivariate and spatial statistics. Using ordinary least-squares analysis, the neighborhood socio-structural covariates explained about 40% of the variability in violent crime. Adding alcohol outlet density in the target census tracts explained an additional 6%, while the addition of drug crime density explained an additional 32%. In the final model, that controlled for the effects of autocorrelated error, both drug crime density in the target and adjacent census tracts remained significant predictors of violent crime, while only off-sale density in the target census tract remained significant in the model. The findings indicate that drug crime density explained a greater amount of variance in violent crime rates than the alcohol outlet density. The methodological and policy implications of these findings are discussed, along with the shortcomings of the analysis presented.

摘要

生态学研究表明,酒类销售点密度与暴力行为之间存在关联,与非法药物使用相关犯罪的地点(即所谓的“热点地区”)和暴力行为之间也存在关联。迄今为止,尚无研究比较酒类销售点和毒品热点地区对暴力犯罪率的影响。本研究在得克萨斯州休斯顿市考察了这种关系。采用了生态学研究设计,样本来自得克萨斯州休斯顿市的439个人口普查区。从档案来源收集了邻里社会结构、酒类销售点密度、毒品犯罪密度和暴力犯罪密度数据,并使用多元和空间统计方法进行分析。使用普通最小二乘法分析,邻里社会结构协变量解释了暴力犯罪变异性的约40%。在目标人口普查区加入酒类销售点密度又解释了6%,而加入毒品犯罪密度则又解释了32%。在控制了自相关误差影响的最终模型中,目标普查区和相邻普查区的毒品犯罪密度仍然是暴力犯罪的重要预测因素,而模型中只有目标普查区的非酒类销售点密度仍然显著。研究结果表明,毒品犯罪密度比酒类销售点密度能解释暴力犯罪率中更大比例的方差。讨论了这些发现的方法学和政策意义,以及所呈现分析的不足之处。

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