The study proposes a new method of crime analysis combining data from multiple secondary data sources (census, open crime data, and social survey) to assess the risk of victimization and crime prevention behavior in resource-limited settings. Principal component analysis was performed on municipal-level census data ( n = 1,883) to generate a rural index that represents the ecological characteristics of each municipality across the urban–rural continuum. Multilevel logistic analyses were then applied to crime incident data ( n = 207,771) to assess the municipal-level effects on victims’ use of locks in motor vehicle and bicycle thefts. A linear pattern of victimization was found for bicycle theft (the risk was about one-thirtieth in the most rural municipalities than that in the most urban municipalities), while the pattern found was nonlinear for motor vehicle thefts. The analysis also revealed that victims in rural areas were less likely to have locked their vehicles before they were stolen than those living in urban areas. Using the rural index developed in this study, police forces can have a better understanding of crime problems in their jurisdiction across the urban–rural continuum. The study discusses the implications of the results for crime prevention and problem-solving policymaking in the urban–rural continuum.
