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.

中文翻译：

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2011-2017年日本神奈川县自杀死亡率和相关社区特征的空间聚类

背景技术日本的自杀死亡率很高，因此需要早期干预策略来解决该问题。准确评估当前自杀死亡率的区域状况将有助于社区干预。在东京附近，日本人口第二大的神奈川县的一些研究确定了区域一级的自杀死亡率空间集群。这项研究使用了来自自杀死亡地区统计的空间数据，研究了此类事件在一段时间内的空间聚类和聚类情况。方法：数据来源于2011年至2017年日本国家生命统计局的地区统计数据（神奈川县的58个地区）。采用标准死亡率（SMR）和SMR的经验贝叶斯估计量（EBSMR）作为度量。通过Kulldorff的圆形空间扫描统计量，Tango-Takahashi的灵活空间扫描统计量和Tango检验检验了空间簇。线性回归和条件自回归（CAR）模型不仅用于调整协变量，而且还用于估计区域效应。每年（包括一年）进行分析。结果在男性自杀死亡中，失业（50％）与自杀最相关，而在女性健康问题中（50％）则很常见。通过FlexScan，SatScan和Tango检验检测到的具有重要意义的空间簇很少，并且根据所使用的方法有所不同。经协变量调整后，在川崎病房等区域发现了空间簇。通过线性回归模型，选择的具有重要意义的变量在性别之间是不同的。在研究的几年中，男性被发现失业，家庭规模和高等教育比例，而女性在此期间被发现家庭规模和离婚率。这些变量还通过5个协变量的CAR模型进行了观察。考虑到男性和女性的空间参数，区域效应更加明显，尤其是川崎病房已被检测为多年的高危地区。结论目前的结果检测到某些区域内自杀死亡的空间聚集。还指出了与自杀死亡有关的因素。这些结果将为预防自杀的决策提供重要信息。在所研究的几年中发现了高等教育的比例和比例，而在此期间，发现了女性的家庭规模和离婚率。这些变量还通过5个协变量的CAR模型进行了观察。考虑到男性和女性的空间参数，区域效应更加明显，尤其是川崎病房已被检测为多年的高危地区。结论目前的结果检测到某些区域内自杀死亡的空间聚集。还指出了与自杀死亡有关的因素。这些结果将为预防自杀的决策提供重要信息。在所研究的几年中发现了高等教育的比例和比例，而在此期间，发现了女性的家庭规模和离婚率。这些变量还通过5个协变量的CAR模型进行了观察。考虑到男性和女性的空间参数，区域效应更加明显，尤其是川崎病房已被检测为多年的高危地区。结论目前的结果检测到某些区域内自杀死亡的空间聚集。还指出了与自杀死亡有关的因素。这些结果将为预防自杀的决策提供重要信息。考虑到男性和女性的空间参数，区域效应更加明显，尤其是川崎病房已被检测为多年的高危地区。结论目前的结果检测到某些区域内自杀死亡的空间聚集。还指出了与自杀死亡有关的因素。这些结果将为预防自杀的决策提供重要信息。考虑到男性和女性的空间参数，区域效应更加明显，尤其是川崎病房已被检测为多年的高危地区。结论目前的结果检测到某些区域内自杀死亡的空间聚集。还指出了与自杀死亡有关的因素。这些结果将为预防自杀的决策提供重要信息。