Methods for Evaluating the Association Between Alcohol Outlet Density and Violent Crime

Abstract

Background: The objective of this analysis was to compare measurement methods-counts, proximity, mean distance, and spatial access-of calculating alcohol outlet density and violent crime using data from Baltimore, Maryland.Methods: Violent crime data (n = 11,815) were obtained from the Baltimore City Police Department and included homicides, aggravated assaults, rapes, and robberies in 2016. We calculated alcohol outlet density and violent crime at the census block (CB) level (n = 13,016). We then weighted these CB-level measures to the census tract level (n = 197) and conducted a series of regressions. Negative binomial regression was used for count outcomes and linear regression for proximity and spatial access outcomes. Choropleth maps, partial R 2 , Akaike's Information Criterion, and root mean squared error guided determination of which models yielded lower error and better fit.Results: The inference depended on the measurement methods used. Eight models that used a count of alcohol outlets and/or violent crimes failed to detect an association between outlets and crime, and 3 other count-based models detected an association in the opposite direction. Proximity, mean distance, and spatial access methods consistently detected an association between outlets and crime and produced comparable model fits.Conclusions: Proximity, mean distance, and spatial access methods yielded the best model fits and had the lowest levels of error in this urban setting. Spatial access methods may offer conceptual strengths over proximity and mean distance. Conflicting findings in the field may be in part due to error in the way that researchers measure alcohol outlet density.

Outlet Type, Access to Alcohol, and Violent Crime

“…The primary contributions of this article are the novel application of routine activity theory and spatial access methods used to calculate alcohol outlet access and violent crime exposure. In particular, previous work by study authors and others has shown that spatial access methods are more sensitive, precise, and stable than commonly-used counts of alcohol outlets and crime (Grubesic et al, 2016, Trangenstein et al, 2018). Other strengths of this analysis are using CBGs as the unit of analysis instead of census tracts, which reduces aggregation bias by avoiding averaging across larger, more heterogeneous areas.…”

“…Thus, we calculated each SAI by summing the inverse distance from each CBG centroid to the 10 nearest outlets (Sacks et al, 2016). We did not restrict distance to the CBG borders to find the 10 closest outlets, and a set size of 10 outlets will smooth over three CBGs on average (Trangenstein et al, 2018). The final SAIs measured the exposure of CBGs to alcohol outlets and weighted alcohol outlets that are located closer to the CBG centroid more heavily than those that were further away.…”

“…The ideal choice set sizes for violent crime were different than for alcohol outlets because there are more violent crimes than alcohol outlets in Baltimore CBGs. Previous research concluded that the choice set size for violent crimes should equal roughly the median number of crimes in the CBG (Trangenstein et al, 2018). The median CBG contained 62 violent crimes, 30 aggravated assaults, 1 sexual assault, 1 homicide, and 25 robberies.…”

“…Recent guidance (Sacks et al, 2016) and analyses (Grubesic et al, 2016) highlight the limitations of count-based methods to measure spatial effects of alcohol outlets. In particular, counts are less sensitive (Grubesic et al, 2016), contain more systematic error than other methods (Trangenstein et al, 2018), and treat alcohol outlets as if they were evenly distributed within the geographic unit of analysis (Sacks et al, 2016). This assumption is problematic when investigating the role of alcohol outlets in violent crime, because alcohol outlets often concentrate in clusters and clustering is associated with violence (Grubesic and Pridemore, 2011, Gorman et al, 2013, Zhang et al, 2015).…”

Association between state‐level alcohol availability and taxation policies on the prevalence of alcohol‐related harms to persons other than the drinker in the USA, 2000–2015

“…For example, bars may lure drinking drivers to social locations away from their homes, and they may harm others along the way. However, we measured outlet density using counts of alcohol outlets in an area, which can introduce measurement error . These results should be interpreted with caution, and we encourage future research with more robust designs in this area.…”