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.

该研究提出了一种新的犯罪分析方法，结合来自多个二级数据源（人口普查、公开犯罪数据和社会调查）的数据，以评估资源有限环境中的受害风险和预防犯罪行为。对市级人口普查数据 ( n  = 1,883)进行主成分分析以生成农村指数，该指数代表城乡连续体中每个城市的生态特征。然后将多级逻辑分析应用于犯罪事件数据 ( n = 207,771) 以评估市政层面对受害者在机动车和自行车盗窃中使用锁的影响。发现自行车盗窃受害的线性模式（大多数农村直辖市的风险约为大多数城市直辖市的三十分之一），而发现的机动车辆盗窃模式是非线性的。分析还显示，与城市地区的受害者相比，农村地区的受害者在车辆被盗前锁车的可能性较小。使用本研究中开发的农村指数，警察部队可以更好地了解其管辖范围内的城乡犯罪问题。该研究讨论了结果对城乡连续体中预防犯罪和解决问题的决策的影响。