Network analysis of anxiety, depression and insomnia in the elderly in Jiangsu Province

Objectives: Mental health is an important indicator in the evaluation of healthy aging. As individuals age, they become increasingly susceptible to symptoms of anxiety, depression, and insomnia, which are often exacerbated by diminished daily functioning, reduced social engagement, and a decline in self-care capabilities. This study uses network analysis to examine the symptom interactions and applies clique percolation to detect overlapping items across the three symptom domains. Methods: This online survey was conducted in three cities in Jiangsu Province between September 2023 and March 2024. Using a cross-sectional design, anxiety, depression, and insomnia symptoms in elderly individuals were assessed with the Generalized Anxiety Disorder Scale (GAD-7), the Patient Health Questionnaire (PHQ-9), and the Insomnia Severity Index (ISI-7). The symptom network was constructed using the EBICglasso algorithm and the clique-percolation algorithm was employed to reveal cross-dimensional connections between symptoms. The study was approved by the Ethics Committee of Huashan Hospital, Fudan University (Approval No. 2022-057). Results: A total of 2,086 elderly individuals were included, with mean age of 72.5 years and 1,061 females (50.9%). The prevalence rates for anxiety, depression, and insomnia were 21.6%, 13.2%, and 46.3%, respectively. Based on clique percolation analysis, three symptom clusters were identified, revealing clear cross-dimensional symptom connectivity among anxiety, depression, and insomnia. Network analysis revealed that the central symptoms-namely "difficulty maintaining sleep," "the perceived impact of sleep disturbances on quality of life by others," and "sleep interference with daytime functioning"-were pivotal in the network. The bridging nodes linking anxiety, depression, and insomnia were identified as "sleep problems," "suicidal ideation," and "restlessness." Conclusion: The central nodes within this network are predominantly sleep-related, underscoring their significant role in the network's structural integrity. Notably, "sleep problems," as the principal bridging node, is important to the comorbidity of anxiety, depression, and insomnia. Addressing and preventing these key symptoms could substantially enhance the psychological well-being of the elderly, offering a promising direction for intervention strategies aimed at fostering healthier aging.

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Journal
PeerJ
Published
2026-03-31
DOI
https://doi.org/10.7717/peerj.20868
Primary Topic
Mental Health Research Topics
Type
article
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0.00
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article

Network analysis of anxiety, depression and insomnia in the elderly in Jiangsu Province

Huichao Chen, Jinshui Xu, Haoran Zhou, Zheng‐Kai Shen et al.
PeerJ
Mental Health Research Topics
article

Network analysis of anxiety, depression and insomnia in the elderly in Jiangsu Province

Huichao Chen, Jinshui Xu, Haoran Zhou, Zheng‐Kai Shen, Bingwei Chen, Mingwang Fu, Xiang Lu, Can Zhao, Hou-Guang Zhou
article en

Abstract

Objectives: Mental health is an important indicator in the evaluation of healthy aging. As individuals age, they become increasingly susceptible to symptoms of anxiety, depression, and insomnia, which are often exacerbated by diminished daily functioning, reduced social engagement, and a decline in self-care capabilities. This study uses network analysis to examine the symptom interactions and applies clique percolation to detect overlapping items across the three symptom domains. Methods: This online survey was conducted in three cities in Jiangsu Province between September 2023 and March 2024. Using a cross-sectional design, anxiety, depression, and insomnia symptoms in elderly individuals were assessed with the Generalized Anxiety Disorder Scale (GAD-7), the Patient Health Questionnaire (PHQ-9), and the Insomnia Severity Index (ISI-7). The symptom network was constructed using the EBICglasso algorithm and the clique-percolation algorithm was employed to reveal cross-dimensional connections between symptoms. The study was approved by the Ethics Committee of Huashan Hospital, Fudan University (Approval No. 2022-057). Results: A total of 2,086 elderly individuals were included, with mean age of 72.5 years and 1,061 females (50.9%). The prevalence rates for anxiety, depression, and insomnia were 21.6%, 13.2%, and 46.3%, respectively. Based on clique percolation analysis, three symptom clusters were identified, revealing clear cross-dimensional symptom connectivity among anxiety, depression, and insomnia. Network analysis revealed that the central symptoms-namely "difficulty maintaining sleep," "the perceived impact of sleep disturbances on quality of life by others," and "sleep interference with daytime functioning"-were pivotal in the network. The bridging nodes linking anxiety, depression, and insomnia were identified as "sleep problems," "suicidal ideation," and "restlessness." Conclusion: The central nodes within this network are predominantly sleep-related, underscoring their significant role in the network's structural integrity. Notably, "sleep problems," as the principal bridging node, is important to the comorbidity of anxiety, depression, and insomnia. Addressing and preventing these key symptoms could substantially enhance the psychological well-being of the elderly, offering a promising direction for intervention strategies aimed at fostering healthier aging.

PeerJVol. 14
Jiangsu Provincial Center for Disease Control and Prevention (CN), Huashan Hospital (CN), Southeast University (CN), Nanjing Medical University (CN)
Openalex Percentile: Top 36%
Mental Health Research Topics
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