IN-PERSON London. Section A

Abstract

Neighborhood crime is likely to influence individuals’ health and well-being. However, empirical studies have reported mixed results, which can be partly explained by conceptual issues, such as narrow definitions of crime, and methodological issues such as imprecise measurements. To overcome these limitations, this study aims to develop a method for measuring crime-related stressors at the neighbourhood level. Using data from the 2015 General Social Survey and the 2016 Canadian Census, regression kriging models were used to estimate the probabilities of crime-related variables (e.g., victimization, discrimination, social disorder, perceived safety, and strong police presence) at the dissemination area (DA) level for the city of Montreal. These estimates were validated by calculating Spearman’s correlation coefficients between each predicted variable and crime density using police data for 2014-2017. The results showed moderate to strong correlations between DA-level probabilities of victimisation, discrimination, social disorder and living in a welcoming community, on the one hand, and crime density, on the other. Multilevel logistic analyses were also performed to assess associations between crime-related stressors and Canadian Community Health Survey respondents’ level of perceived safety in 2015. There were significant associations between individuals’ perception of safety and crime-related variables at the DA level, except for victimisation. The findings suggest that regression kriging is a robust method that can be used to estimate crime-related stressor variables at the neighbourhood level. This measurement approach is recommended to assess the multiple components of neighbourhood crime, and to better understand the relationship between neighbourhood crime and individuals’ well-being.