Bayesian hierarchical spatial modeling of substance abuse patterns following a mass trauma: the role of time and place
- Bayesian hierarchical spatial modeling of substance abuse patterns following a mass trauma: the role of time and place
- DiMaggio, Charles J.
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- Substance Use and Misuse, vol. 44, no. 12 (October 2009), pp. 1725-1743.
- To illustrate how spatial modeling methods may provide insight about the relation between proximity to mass trauma and substance use, we examined the role of proximity to a terrorist event in determining risk of substance use-related diagnoses. Previous analyses that have assessed changes in substance use following mass traumas such as terrorist attacks have produced conflicting results. We used Bayesian hierarchical modeling methods to assess whether distance from the World Trade Center (WTC) site in the aftermath of the September 11, 2001 terrorist attacks was associated with risk of substance use-related diagnoses. In analyses controlling for age, gender, median household income and employment-related exposure to the terrorist attacks, we found that each two mile increment in distance away from the World Trade Center site was associated with 18% more substance use-related diagnoses in the population we studied; this relation between distance from the WTC and substance use-related disorder was the opposite of the relations observed one year before the same attacks in the same area. By accounting for spatial relationships that may influence the population risk of substance use health disorder, this approach helps explain some of the conflicting observations in the extant literature. These methods hold promise for the characterization of disease risk where spatial patterning of exposures and outcomes may matter.
- Public health
Spatial analysis (Statistics)
Bayesian statistical decision theory
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- Charles J. DiMaggio, Sandro Galea, David Vlahov, 2009, Bayesian hierarchical spatial modeling of substance abuse patterns following a mass trauma: the role of time and place, Columbia University Academic Commons, https://doi.org/10.7916/D8542VBJ.