Department of Social Psychology, Graduate School of Humanities and Sociology, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan.
Soc Sci Med. 2012 Nov;75(10):1895-902. doi: 10.1016/j.socscimed.2012.07.039. Epub 2012 Aug 10.
Crime is an important determinant of public health outcomes, including quality of life, mental well-being, and health behavior. A body of research has documented the association between community social capital and crime victimization. The association between social capital and crime victimization has been examined at multiple levels of spatial aggregation, ranging from entire countries, to states, metropolitan areas, counties, and neighborhoods. In multilevel analysis, the spatial boundaries at level 2 are most often drawn from administrative boundaries (e.g., Census tracts in the U.S.). One problem with adopting administrative definitions of neighborhoods is that it ignores spatial spillover. We conducted a study of social capital and crime victimization in one ward of Tokyo city, using a spatial Durbin model with an inverse-distance weighting matrix that assigned each respondent a unique level of "exposure" to social capital based on all other residents' perceptions. The study is based on a postal questionnaire sent to 20-69 years old residents of Arakawa Ward, Tokyo. The response rate was 43.7%. We examined the contextual influence of generalized trust, perceptions of reciprocity, two types of social network variables, as well as two principal components of social capital (constructed from the above four variables). Our outcome measure was self-reported crime victimization in the last five years. In the spatial Durbin model, we found that neighborhood generalized trust, reciprocity, supportive networks and two principal components of social capital were each inversely associated with crime victimization. By contrast, a multilevel regression performed with the same data (using administrative neighborhood boundaries) found generally null associations between neighborhood social capital and crime. Spatial regression methods may be more appropriate for investigating the contextual influence of social capital in homogeneous cultural settings such as Japan.
犯罪是公共卫生结果的一个重要决定因素，包括生活质量、心理健康和健康行为。大量研究记录了社区社会资本与犯罪受害之间的关联。社会资本与犯罪受害之间的关联已在多个空间聚集层次上进行了研究，范围从整个国家到州、大都市区、县和社区。在多层次分析中，第 2 级的空间边界通常来自行政边界（例如，美国的普查区）。采用邻里的行政定义存在的一个问题是，它忽略了空间溢出。我们在东京市的一个区进行了一项关于社会资本和犯罪受害的研究，使用空间 Durbin 模型和逆距离加权矩阵，根据所有其他居民的看法，为每个受访者分配一个独特的社会资本“暴露”水平。该研究基于向东京荒川区 20-69 岁居民发送的邮政问卷。回复率为 43.7%。我们检查了一般信任、互惠感知、两种类型的社会网络变量以及社会资本的两个主要成分（由上述四个变量构建）的背景影响。我们的结果衡量标准是过去五年内自我报告的犯罪受害情况。在空间 Durbin 模型中，我们发现邻里普遍信任、互惠、支持性网络和社会资本的两个主要成分都与犯罪受害呈反比。相比之下，使用相同数据（使用行政邻里边界）进行的多层次回归发现邻里社会资本与犯罪之间通常没有关联。空间回归方法可能更适合在日本等同质文化环境中调查社会资本的背景影响。
