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Space–Time Analyses of Alcohol Outlets and Related Motor Vehicle Crashes: Associations at City and Census Block‐Group Levels
Author(s) -
Lipton Robert,
Ponicki William R.,
Gruenewald Paul J.,
Gaidus Andrew
Publication year - 2018
Publication title -
alcoholism: clinical and experimental research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.267
H-Index - 153
eISSN - 1530-0277
pISSN - 0145-6008
DOI - 10.1111/acer.13758
Subject(s) - demography , relative risk , crash , geography , medicine , population , poison control , census , poisson regression , injury prevention , environmental health , confidence interval , sociology , computer science , programming language
Background Past research has linked alcohol outlet densities to drinking, drunken driving, and alcohol‐related motor vehicle crashes ( MVC s). Because impaired drivers travel some distances from drinking places to crash locations, spatial relationships between outlets and crashes are complex. We investigate these relationships at 3 geographic levels: census block groups ( CBG s), adjacent (nearby) areas, and whole cities. Methods We examined risks of all injury MVC s as well as “had been drinking” ( HBD ) and single‐vehicle‐nighttime ( SVN ) subgroups using data from the Statewide Integrated Traffic Records System across CBG s among 50 California cities from 2001 to 2008. Relationships between outlet densities at the city level, within CBG s, and in adjacent CBG s and crashes were examined using Bayesian Poisson space–time analyses controlling for population size income and other demographics (all as covariates). Results All injury MVC s were positively related to adjacent CBG population size (relative rate [RR] = 1.008, 95% credible interval ( CI ) = 1.004, 1.012), and outlet densities at CBG ( RR = 1.027, CI = 1.020, 1.035), nearby area ( RR = 1.084, CI = 1.060, 1.106) and city levels ( RR = 1.227, CI = 1.147, 1.315), and proportion of bars or pubs at the city level ( RR = 2.257, CI = 1.187, 4.125). HBD and SVN crashes were comparatively less frequent in high outlet density CBG (RR = 0.993, CI = 0.987, 0.999; RR = 0.963, CI = 0.951, 0.975) and adjacent areas (RR = 0.979, CI = 0.962, 0.996; RR = 0.909, CI = 0.883, 0.936), but positively associated with city‐level proportions of bars ( RR = 3.373, CI = 0.736, 15.644; RR = 10.322, CI = 1.704, 81.215). Overall, a 10% increase in all outlets was related to 2.8% more injury crashes ( CI = 2.3, 3.3) and 2.5% more HBD s ( CI = 1.7, 3.3). A 10% increase in bars was related to 1.4% more crashes, 4.3% more HBD s, and 10.3% more SVN s. Conclusions Population size and densities of bars or pubs were found to be associated with crash rates, with population effects appearing across cities and outlet effects appearing within dense downtown areas. Summary estimates of outlet and population impacts on MVC s must consider varying contributions at multiple spatial scales.