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Spatial clustering of suicide mortality and associated community characteristics in Kanagawa prefecture, Japan, 2011–2017

机译:日本神奈川县自杀死亡率及相关社区特征的空间聚类,2011-2017

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BACKGROUND:Suicide mortality is high in Japan and early interventional strategies to solve that problem are needed. An accurate evaluation of the regional status of current suicide mortality would be useful for community interventions. A few studies in Kanagawa prefecture, located next to Tokyo and with the second largest population in Japan, have identified spatial clusters of suicide mortality at regional levels. This study examined spatial clustering and clustering over time of such events using spatial data from regional statistics on suicide deaths.METHODS:Data were obtained from regional statistics (58 regions in Kanagawa prefecture) of the National Vital Statistics of Japan from 2011 to 2017. The standardized mortality ratio (SMR) and Empirical Bayes estimator for the SMR (EBSMR) were used as measures. Spatial clusters were examined by Kulldorff's circular spatial scan statistic, Tango-Takahashi's flexible spatial scan statistic and Tango's test. Linear regression and conditional autoregressive (CAR) models were used not only to adjust for covariates but also to estimate regional effects. The analyses were conducted for each year, inclusive.RESULTS:Among male suicide deaths, being unemployed (50%) was most frequently related to suicide while among female health problem (50%) were frequent. Spatial clusters with significance detected by FlexScan, SatScan and Tango's test were few and varied somewhat according to the method used. Spatial clusters were detected in some regions including Kawasaki ward after adjustment by covariates. By the linear regression models, selected variables with significance were different between the sexes. For males, unemployment, family size, and proportion of higher education were detected for several of the years studied while for females, family size and divorce rate were detected over this period. These variables were also observed by the CAR model with 5 covariates. Regional effects were much clearer by considering the spatial parameter for both males and females and especially, Kawasaki ward was detected as a high risk region in many years.CONCLUSION:The present results detected some spatial clustering of suicide deaths within certain regions. Factors related to suicide deaths were also indicated. These results would provide important information in policy making for suicide prevention.
机译:背景:日本的自杀死亡率高,需要提前的介入策略来解决这种问题。对当前自杀死亡率的区域地位的准确评估对于社区干预措施将是有用的。少数在东京旁边和日本第二大人口旁边的神奈川县的一些研究已经确定了区域一级的自杀死亡率的空间簇。本研究检查了使用来自自杀死亡区域统计数据的空间数据的空间聚类和聚类。方法:从2011年到2017年的国家重要统计数据从区域统计数据(卡奈瓦县58区)获得了数据。该SMR(EBSMR)的标准化死亡率(SMR)和经验贝叶斯估算用作措施。通过Kulldorff的圆形空间扫描统计,探戈-Kakahashi灵活的空间扫描统计和探戈的测试来检查空间簇。线性回归和条件自回归(汽车)模型不仅用于调整协变量,还用于估算区域效应。分析是每年进行的,包括含有:在男性自杀死亡中,失业(50%)最常与自杀相关,而女性健康问题(50%)频繁。由于FlexScan检测到的空间簇,SATSCan和探戈的测试很少,并且根据所用方法稍微变化。在通过协变量调整后,在包括川崎病的一些地区检测到空间簇。通过线性回归模型,性别之间具有显着性的选定变量不同。对于雌性,失业,家庭规模和高等教育的比例被检测到妇女的几年,在此期间检测到家庭规模和离婚率。汽车模型还观察到这些变量,其中有5个协变量。通过考虑男性和女性的空间参数,区域效应更加清晰,特别是,川崎病在多年内被检测为高风险地区。结论:目前的结果检测到某些地区内自杀死亡的一些空间聚类。还指出了与自杀死亡有关的因素。这些结果将在保护自杀预防方面提供重要信息。

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