Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan.
Institute of Health Behaviors and Community Sciences, College of Public Health, National Taiwan University, Taipei, Taiwan.
Epidemiol Psychiatr Sci. 2023 Jun 1;32:e37. doi: 10.1017/S2045796023000513.
Suicidal acts may cluster in time and space and lead to community concerns about further imitative suicidal episodes. Although suicide clusters have been researched in previous studies, less is known about the clustering of non-fatal suicidal behaviour (self-harm). Furthermore, most previous studies used crude temporal and spatial information, e.g., numbers aggregated by month and residence area, for cluster detection analysis. This study aimed to (i) identify space-time clusters of self-harm and suicide using daily incidence data and exact address and (ii) investigate the characteristics of cluster-related suicidal acts.
Data on emergency department presentations for self-harm and suicide deaths in Taipei City and New Taipei City, Taiwan, were used in this study. In all-age and age-specific analyses, self-harm and suicide clusters were identified using space-time permutation scan statistics. A cut-off of 0.10 for the value was used to identify possible clusters. Logistic regression was used to investigate the characteristics associated with cluster-related episodes.
A total of 5,291 self-harm episodes and 1,406 suicides in Taipei City (2004-2006) and 20,531 self-harm episodes and 2,329 suicides in New Taipei City (2012-2016) were included in the analysis. In the two cities, two self-harm clusters ( [number of self-harm episodes or suicide deaths in the cluster] = 4 and 8 in Taipei City), four suicide clusters ( = 3 in Taipei City and = 4, 11 and 4 in New Taipei City) and two self-harm and suicide combined clusters ( = 4 in Taipei City and = 8 in New Taipei City) were identified. Space-time clusters of self-harm, suicide, and self-harm and suicide combined accounted for 0.05%, 0.59%, and 0.08% of the respective groups of suicidal acts. Cluster-related episodes of self-harm and suicide were more likely to be male (adjusted odds ratio [aOR] = 2.22, 95% confidence interval [CI] 1.26, 3.89) and young people aged 10-29 years (aOR = 2.72, 95% CI 1.43, 5.21) than their cluster-unrelated counterparts.
Space-time clusters of self-harm, suicide, and self-harm and suicide combined accounted for a relatively small proportion of suicidal acts and were associated with some sex/age characteristics. Focusing on suicide deaths alone may underestimate the size of some clusters and/or lead to some clusters being overlooked. Future research could consider combining self-harm and suicide data and use social connection information to investigate possible clusters of suicidal acts.
自杀行为可能在时间和空间上聚集，并引发社区对进一步模仿性自杀事件的担忧。尽管之前的研究已经研究了自杀聚集，但对于非致命性自杀行为（自残）的聚集了解较少。此外，大多数先前的研究使用了粗略的时间和空间信息，例如按月份和居住区域汇总的数字，用于聚类检测分析。本研究旨在：（i）使用每日发病数据和确切地址识别自残和自杀的时空聚集；（ii）研究与聚集相关的自杀行为的特征。
本研究使用了台湾台北市和新北市的急诊科自残和自杀死亡数据。在全年龄段和特定年龄段分析中，使用时空置换扫描统计数据识别自残和自杀聚集。使用 值的 0.10 作为截断值来识别可能的聚集。使用逻辑回归来研究与聚集相关事件相关的特征。
在台北市（2004-2006 年）纳入了 5291 例自残发作和 1406 例自杀死亡，以及新北市（2012-2016 年）纳入了 20531 例自残发作和 2329 例自杀死亡。在这两个城市中，发现了两个自残聚集（[聚集中的自残发作或自杀死亡人数] = 4 和 8 在台北市）、四个自杀聚集（[聚集中的自杀死亡人数] = 3 在台北市和 [聚集中的自杀死亡人数] = 4、11 和 4 在新北市）和两个自残和自杀混合聚集（[聚集中的自残和自杀死亡人数] = 4 在台北市和 [聚集中的自杀死亡人数] = 8 在新北市）。自残、自杀和自残与自杀混合的时空聚集占各自自杀行为群体的 0.05%、0.59%和 0.08%。与聚集无关的自残和自杀相关事件更可能是男性（调整后的优势比[aOR] = 2.22，95%置信区间[CI] 1.26，3.89）和 10-29 岁的年轻人（aOR = 2.72，95% CI 1.43，5.21）。
自残、自杀和自残与自杀混合的时空聚集占自杀行为的比例相对较小，与某些性别/年龄特征相关。仅关注自杀死亡可能会低估一些聚集的规模，或导致一些聚集被忽视。未来的研究可以考虑将自残和自杀数据结合起来，并利用社会联系信息来调查自杀行为的可能聚集。
