Abstract
BackgroundEcologic studies have shown a relationship between alcohol outlet densities, illicit drug use and violence. The present study examined this relationship in the City of Houston, Texas, using a sample of 439 census tracts. Neighborhood sociostructural covariates, alcohol outlet density, drug crime density and violent crime data were collected for the year 2000, and analyzed using hierarchical Bayesian models. Model selection was accomplished by applying the Deviance Information Criterion.ResultsThe counts of violent crime in each census tract were modelled as having a conditional Poisson distribution. Four neighbourhood explanatory variables were identified using principal component analysis. The best fitted model was selected as the one considering both unstructured and spatial dependence random effects. The results showed that drug-law violation explained a greater amount of variance in violent crime rates than alcohol outlet densities. The relative risk for drug-law violation was 2.49 and that for alcohol outlet density was 1.16. Of the neighbourhood sociostructural covariates, males of age 15 to 24 showed an effect on violence, with a 16% decrease in relative risk for each increase the size of its standard deviation. Both unstructured heterogeneity random effect and spatial dependence need to be included in the model.ConclusionThe analysis presented suggests that activity around illicit drug markets is more strongly associated with violent crime than is alcohol outlet density. Unique among the ecological studies in this field, the present study not only shows the direction and magnitude of impact of neighbourhood sociostructural covariates as well as alcohol and illicit drug activities in a neighbourhood, it also reveals the importance of applying hierarchical Bayesian models in this research field as both spatial dependence and heterogeneity random effects need to be considered simultaneously.
Highlights
Ecologic studies have shown a relationship between alcohol outlet densities, illicit drug use and violence
The analysis presented suggests that activity around illicit drug markets is more strongly associated with violent crime than is alcohol outlet density
Level 2 modelled the log relative risk as a linear combination of three components which accounted for fixed effects of possible covariates, random effects of unstructured heterogeneity and spatial dependence
Summary
Ecologic studies have shown a relationship between alcohol outlet densities, illicit drug use and violence. Neighborhood sociostructural covariates, alcohol outlet density, drug crime density and violent crime data were collected for the year 2000, and analyzed using hierarchical Bayesian models. Waller et al [2] developed a Bayesian hierarchical model that accommodated covariates and spatial structure which evolved over time. International Journal of Health Geographics 2006, 5:54 http://www.ij-healthgeographics.com/content/5/1/54 and links to statistical packages have further encouraged spatial data analysis [3,4,5]. With the development of Markov Chain Monte Carlo (MCMC) methods and software such as WinBUGS [6,7], Bayesian approaches are being applied to the analysis of many social and health problems in addition to disease mapping and modelling. Poisson models require that mean and variance are equal, while in real data, overdispersion often results in larger variance than mean
Sign-in/Register to view highlights & summary 
Published Version (
Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call