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Adding to the mix: a multilevel analysis of residential burglary

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Abstract

Environmental research on residential properties’ vulnerability to burglary usually focuses either on the houses that have been burgled or on the streets in which they are located. This research explores both house and street level in a fixed-effects model and, using tangible CPTED measures, takes a wider perspective to assess vulnerability to burglary. The results indicate that dwelling type, visibility and boundary height have significant effects, and that street type and indicators of antisocial behaviour also have strong effects. Furthermore, these street-level variables appear to strengthen some of the house-level vulnerabilities. We argue that both house and street levels should therefore be included in any assessment of the risk of burglary.

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Notes

  1. An initial sample of 650 houses was slightly reduced because 31 locations turned out not (or no longer) to be houses, or had been demolished by the time the research took place (2012–2013).

  2. A large initial sample of 1299 houses was drawn. It was reduced to 932, since some houses were burgled in 2010, and many addresses turned out not to be houses, or had been demolished by the time the observations took place (2012–2013).

  3. Inter-rater reliability was high, with scores above 0.800 and often above 0.900.

  4. The instrument is set up in the framework of a broader research project and also contains neighbourhood characteristics.

  5. Due to missing values, one observation is excluded. No multi-collinearity problems have been detected between the items.

  6. Despite the fact that the amount of variance at higher levels is limited (±8%), we have intrinsic reasons to account for nesting.

  7. The following regression equation was used for the final model: ηijk = γ000 + γ001*POPULATION_DENSITYk + γ002*ETHNIC_HETEROGENIETYk + γ003*RESIDENTIAL_MOBILITYIk + γ010*LITTERjk + γ020*GRAFFITIjk + γ030*DEADENDIjk + γ100*LOW_BOUNDARY1ijk + γ200*MEDIUM_BOUNDARYijk + γ300*HIGH_BOUNDARYijk + γ400*FORTRESSING_BOUNDARYijk + γ500*VISIBILITYRijk + γ600*SEMI-DETACHEDijk + γ700*TERRACEDijk + γ800*LOW_RISEijk + γ900*HIGH_RISEijk + r0jk + u00 k

  8. Preliminary analyses demonstrate that houses that are only visible from one other house do not differ from houses that are not visible from any other house (p = 0.97). Hence, we put them in the same group.

  9. The influence of bus stops and road sizes has been checked, and these do not have a significant influence in the model.

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Acknowledgements

This work was supported by the Research Foundation Flanders (FWO - grant number G007011N).

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Authors and Affiliations

  1. Institute of Criminal Law and Criminology, Leiden University, Leiden, The Netherlands

    M. P. Peeters

  2. University Hospital Ghent, Ghent, Belgium

    S. Van Daele

  3. Institute for International Research on Criminal Policy, Ghent University, Ghent, Belgium

    T. Vander Beken

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Peeters, M.P., Van Daele, S. & Vander Beken, T. Adding to the mix: a multilevel analysis of residential burglary. Secur J 31, 389–409 (2018). https://doi.org/10.1057/s41284-017-0106-1

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