Chang Ze, Zhang Yunfan, Liang Xiao, Chen Yunmeng, Guo Chunyan, Chi Xiansu, Wang Liuding, Wang Xie, Chen Hong, Zhang Zixuan, Liu Longtao, Miao Lina, Zhang Yunling
Xiyuan Hospital of China Academy of Traditional Chinese Medicine, Beijing, 100091, China.
The First Affiliated Hospital of Anhui, University of Traditional Chinese Medicine, Hefei, 230031, China.
BMC Psychiatry. 2025 Jan 8;25(1):28. doi: 10.1186/s12888-024-06443-2.
Elderly individuals living alone represent a vulnerable group with limited family support, making them more susceptible to mental health issues such as depression and anxiety. This study aims to construct a network model of depression and anxiety symptoms among older adults living alone, exploring the correlations and centrality of different symptoms. The goal is to identify core and bridging symptoms to inform clinical interventions.
Using data from the 2018 Chinese Longitudinal Healthy Longevity Survey (CLHLS), this study constructed a network model of depression and anxiety symptoms among elderly individuals living alone. Depression and anxiety symptoms were assessed using the Center for Epidemiologic Studies Depression Scale-10 (CESD-10) and the Generalized Anxiety Disorder Scale-7 (GAD-7), respectively. A Gaussian Graphical Model (GGM) was employed to build the symptom network, and the Fruchterman-Reingold algorithm was used for visualization, with the thickness and color of the edges representing partial correlations between symptoms. To minimize spurious correlations, the Least Absolute Shrinkage and Selection Operator (LASSO) method was applied for regularization, and the optimal regularization parameters were selected using the Extended Bayesian Information Criterion (EBIC). We further calculated Expected Influence (EI) and Bridge Expected Influence (Bridge EI) to evaluate the importance of symptoms. Non-parametric bootstrap methods were used to assess the stability and accuracy of the network.
The Network centrality analysis revealed that GAD2 (Uncontrollable worry) and GAD4 (Trouble relaxing) exhibited the highest strength centrality (1.128 and 1.102, respectively), indicating their significant direct associations with other symptoms and their roles as core nodes in the anxiety symptom network. Other highly central nodes, such as GAD1 (Nervousness or anxiety) and GAD3 (Generalized worry), further underscore the dominance of anxiety symptoms in the overall network. Betweenness centrality results highlighted GAD1 (Nervousness or anxiety) and GAD2 (Uncontrollable worry) as critical bridge nodes facilitating information flow between different symptoms, while CESD3 (Feeling depressed) demonstrated a bridging role across modules. Weighted analyses further confirmed the central importance of GAD2 (Uncontrollable worry) and GAD4 (Trouble relaxing). Additionally, the analysis showed gender differences in the depression-anxiety networks of elderly individuals living alone.
This study, through network analysis, uncovered the complex relationships between depression and anxiety symptoms among elderly individuals living alone, identifying GAD2 (Uncontrollable worry) and GAD4 (Trouble relaxing) as core symptoms. These findings provide essential insights for targeted interventions. Future research should explore intervention strategies for these symptoms to improve the mental health of elderly individuals living alone.
独居老年人是一个家庭支持有限的弱势群体，使他们更容易出现抑郁和焦虑等心理健康问题。本研究旨在构建独居老年人抑郁和焦虑症状的网络模型，探索不同症状之间的相关性和中心性。目的是识别核心症状和桥梁症状，为临床干预提供依据。
利用2018年中国健康与养老追踪调查（CLHLS）的数据，本研究构建了独居老年人抑郁和焦虑症状的网络模型。分别使用流行病学研究中心抑郁量表-10（CESD-10）和广泛性焦虑障碍量表-7（GAD-7）评估抑郁和焦虑症状。采用高斯图形模型（GGM）构建症状网络，并使用Fruchterman-Reingold算法进行可视化，边的粗细和颜色表示症状之间的偏相关性。为了最小化虚假相关性，应用最小绝对收缩和选择算子（LASSO）方法进行正则化，并使用扩展贝叶斯信息准则（EBIC）选择最优正则化参数。我们进一步计算了预期影响（EI）和桥梁预期影响（Bridge EI）来评估症状的重要性。使用非参数自助法评估网络的稳定性和准确性。
网络中心性分析显示，GAD2（无法控制的担忧）和GAD4（难以放松）表现出最高的强度中心性（分别为1.128和1.102），表明它们与其他症状有显著的直接关联，并且在焦虑症状网络中作为核心节点发挥作用。其他高度中心的节点，如GAD1（紧张或焦虑）和GAD3（广泛性担忧），进一步强调了焦虑症状在整个网络中的主导地位。中介中心性结果突出了GAD1（紧张或焦虑）和GAD2（无法控制的担忧）作为促进不同症状之间信息流的关键桥梁节点，而CESD3（感到沮丧）在不同模块之间发挥了桥梁作用。加权分析进一步证实了GAD2（无法控制的担忧）和GAD4（难以放松）的核心重要性。此外，分析显示独居老年人抑郁-焦虑网络存在性别差异。
本研究通过网络分析，揭示了独居老年人抑郁和焦虑症状之间的复杂关系，确定GAD2（无法控制的担忧）和GAD4（难以放松）为核心症状。这些发现为有针对性的干预提供了重要见解。未来的研究应探索针对这些症状的干预策略，以改善独居老年人的心理健康。
