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What calls for service tell us about suicide: A 7-year spatio-temporal analysis of neighborhood correlates of suicide-related calls

机译:需要服务的内容告诉我们有关自杀的信息:一项与自杀相关电话的邻域相关性的7年时空分析

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Previous research has shown that neighborhood-level variables such as social deprivation, social fragmentation or rurality are related to suicide risk, but most of these studies have been conducted in the U.S. or northern European countries. The aim of this study was to analyze the spatio-temporal distribution of suicide in a southern European city (Valencia, Spain), and determine whether this distribution was related to a set of neighborhood-level characteristics. We used suicide-related calls for service as an indicator of suicide cases (n?=?6,537), and analyzed the relationship of the outcome variable with several neighborhood-level variables: economic status, education level, population density, residential instability, one-person households, immigrant concentration, and population aging. A Bayesian autoregressive model was used to study the spatio-temporal distribution at the census block group level for a 7-year period (2010–2016). Results showed that neighborhoods with lower levels of education and population density, and higher levels of residential instability, one-person households, and an aging population had higher levels of suicide-related calls for service. Immigrant concentration and economic status did not make a relevant contribution to the model. These results could help to develop better-targeted community-level suicide prevention strategies.
机译:先前的研究表明,诸如社会剥夺,社会分裂或农村人口等邻里层面的变量与自杀风险有关,但这些研究大多数是在美国或北欧国家进行的。这项研究的目的是分析一个南部欧洲城市(西班牙瓦伦西亚)的自杀时空分布,并确定这种分布是否与一系列邻里级特征有关。我们使用与自杀相关的服务电话作为自杀案例的指标(n?=?6,537),并分析了结果变量与几个邻里水平变量的关系:经济状况,教育水平,人口密度,居住不稳定,一个人家庭,移民集中度和人口老龄化。贝叶斯自回归模型用于研究人口普查区组水平为期7年(2010-2016年)的时空分布。结果表明,教育程度和人口密度较低,居住区不稳定,单人家庭和人口老龄化较高的社区,其自杀相关的服务要求较高。移民集中度和经济地位并未对该模型做出相关贡献。这些结果可能有助于制定针对性更强的社区一级的自杀预防策略。

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