Hsu Yu Cheng, Junus Alvin, Zhang Qingpeng, Wong Clifford, Lam Tsz Mei, Cheung Florence, Liu Joyce, Lui Ingrid D, Yip Paul S F
The Hong Kong Jockey Club Centre for Suicide Research and Prevention, Department of Social Work and Social Administration, Faculty of Social Sciences, The University of Hong Kong, Hong Kong.
Department of Social Work and Social Administration, Faculty of Social Sciences, The University of Hong Kong, Hong Kong.
Lancet Reg Health West Pac. 2023 Apr 10;36:100752. doi: 10.1016/j.lanwpc.2023.100752. eCollection 2023 Jul.
Suicide is a complex and multifaceted issue, and suicidal behaviors are often driven by multiple, interacting factors. It has been challenging to identify reasons for suicide using existing scientific methodologies. This study aims to identify critical reasons for suicide and suicidal behaviors through the application of novel network science methods.
Based on cases investigated by the Hong Kong Coroner's Court from 2002 to 2019, we modelled identified reasons for 13,001 suicide cases as a co-occurrence network, and calculated each reason's eigencentrality to determine their respective relative importance. We then analyzed the temporal and demographic changes in the structure and eigencentrality of the network. We further conducted simulation studies based on the United Nations population projection to assess potential burden of different reasons for suicide on the population in the coming years.
School-related issues had the highest eigencentrality (eigencentrality = 0.49) for individuals younger than 20 years of age. Financial issues were crucial for adults aged 20-59 years, but their importance differed between males (eigencentrality = 0.51) and females (eigencentrality = 0.14). Physical illness (eigencentrality = 0.80) was the core concern for adults over 60 years. Across the Hong Kong population, the reasons for suicide appear to have shifted from financial issues in the early 2000s (eigencentrality = 0.46) to issues related to physical illnesses since 2011 (eigencentrality = 0.58). Simulation findings indicate that, by 2050, most suicides in Hong Kong will be due to physical illness-related issues (eigencentrality = 0.69) due to the rapidly aging population.
There have been important sex and age differences over time, in reasons for suicide. Given the projected increasing age of the Hong Kong population over the next decades, older adults with physical illnesses appear to be the highest contributors to suicide cases in the overall population. This novel network analysis approach provides important data-driven information upon which to base effective proactive public health suicide prevention strategies and interventions.
Hong Kong Jockey Club Charities Trust, Collaborative Research Fund (C7151-20G), and General Research Fund (17606521).
自杀是一个复杂且多方面的问题，自杀行为往往由多种相互作用的因素驱动。利用现有的科学方法来确定自杀原因一直具有挑战性。本研究旨在通过应用新颖的网络科学方法来确定自杀及自杀行为的关键原因。
基于香港死因裁判法庭在2002年至2019年期间调查的案件，我们将13001起自杀案件中确定的原因建模为一个共现网络，并计算每个原因的特征向量中心性以确定它们各自的相对重要性。然后我们分析了网络结构和特征向量中心性的时间和人口统计学变化。我们还根据联合国人口预测进行了模拟研究，以评估未来几年不同自杀原因对人口的潜在负担。
对于20岁以下的个体，与学校相关的问题具有最高的特征向量中心性（特征向量中心性 = 0.49）。财务问题对20至59岁的成年人至关重要，但在男性（特征向量中心性 = 0.51）和女性（特征向量中心性 = 0.14）之间其重要性有所不同。身体疾病（特征向量中心性 = 0.80）是60岁以上成年人的核心关注点。在香港全体人口中，自杀原因似乎已从21世纪初的财务问题（特征向量中心性 = 0.46）转变为自2011年以来与身体疾病相关的问题（特征向量中心性 = 0.58）。模拟结果表明，到2050年，由于人口迅速老龄化，香港的大多数自杀将归因于与身体疾病相关的问题（特征向量中心性 = 0.69）。
随着时间推移，自杀原因存在重要的性别和年龄差异。鉴于预计未来几十年香港人口年龄增长，患有身体疾病的老年人似乎是总体自杀案件的最大贡献者。这种新颖的网络分析方法提供了重要的数据驱动信息，可据此制定有效的积极公共卫生自杀预防策略和干预措施。
香港赛马会慈善信托基金、协作研究基金（C7151 - 20G）和一般研究基金（17606521）。
