Journal of Quantitative Criminology

, Volume 30, Issue 3, pp 527–548 | Cite as

Quantifying the Exposure of Street Segments to Drinking Places Nearby

  • Elizabeth R. GroffEmail author
Original Paper



Introduce and test the relative efficacy of two methods for modeling the impact of cumulative ‘exposure’ to drinking facilities on violent crime at street segments.


One method, simple count, sums the number of drinking places within a distance threshold. The other method, inverse distance weighted count, weights each drinking place within a threshold based on its distance from the street segment. Closer places are weighted higher than more distant places. Distance is measured as the street length from a street segment to a drinking place along the street network. Seven distance thresholds of 400, 800, 1,200, 1,600, 2,000, 2,400 and 2,800 feet are tested. A negative binomial regression model controlling for socio-economic characteristics, opportunity factors and spatial autocorrelation is used to evaluate which of the measure/threshold combinations produce a better fit as compared to a model with no exposure measures.


Exposure measured as an inverse distance weighted count produces the best fitting model and is significantly related to violent crime at longer distances than simple count (from 400 to 2,800 feet). Exposure to drinking places using a simple count is significantly related to violent crime up to 2,000 feet. Both models indicate the influence of drinking places is highest at shorter distance thresholds.


Both researchers and practitioners can more precisely quantify the influence of drinking places in multivariate models of street segment level violent crime by incorporating proximity in the development of a cumulative exposure measure. The efficacy of using exposure measures to quantify the influence of other types of facilities on crime patterns across street segments should be explored.


Drinking places Facilities Street segment Exposure Inverse distance weighting 



The author is grateful to Alex Piquero, Cathy Spatz Widom and the three anonymous reviewers for helpful comments on previous drafts as well as to Lauren Holt for editorial assistance. Data were collected under the “Understanding Developmental Crime Trajectories at Places: Social Disorganization and Opportunity Perspectives at Micro Units of Geography” led by David Weisburd, Elizabeth Groff and Sue-Ming Yang and funded by the National Institute of Justice (2005-IJ-CX-0006).


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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  1. 1.Department of Criminal JusticeTemple UniversityPhiladelphiaUSA

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