Network analysis of sleep disorders, anxiety, and loneliness among the community-dwelling older adults
Bibliographic Data
| ID | 22069168 |
|---|---|
| Authors | Xiaonan Li (0000-0002-3033-3119, Guizhou Minzu University), Lin Mao (0009-0007-6544-2327, North Sichuan Medical University) |
| Year | 2026 |
| Volume | 14 |
| Pages | 1827779-1827779 |
| Publication date | 2026-06-10 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Frontiers in Public Health (JOURNAL) |
| Journal identifiers | ISSN: 2296-2565 • E-ISSN: 2296-2565 |
| Publisher | Frontiers Media SA (PUBLISHER • CH) |
| DOI | 10.3389/fpubh.2026.1827779 |
| PMID | 42359148 |
| OpenAlex | W7164205716 |
| Language | EN |
| References cited | 59 |
Objective: To explore the relationships among sleep disorders, loneliness, and anxiety in community-dwelling older adults, and to provide empirical evidence for developing targeted intervention strategies to improve their overall health. Methods: A total of 1,637 community-dwelling older adults were recruited from Nanchong through convenience sampling. Sleep disorders, anxiety, and loneliness were assessed using the Pittsburgh Sleep Quality Index (PSQI), the Generalized Anxiety Disorder 7-item Scale (GAD-7), and the short form of the UCLA Loneliness Scale (ULS-8), respectively. Network analysis was conducted using R 4.5.1 to examine the symptom-level associations among sleep disorders, anxiety, and loneliness. Results: Most symptoms of sleep disorders, anxiety, and loneliness were positively correlated, forming a highly interconnected Gaussian graphical model (GGM) comorbidity network. In the GGM network, PSQI4, GAD2, and PSQI2 were identified as core symptoms, while PSQI4, ULS5, and PSQI2 were identified as bridge symptoms. Bayesian network analysis showed that ULS3 was the upstream node in the directed acyclic graph and pointed to 10 nodes, while GAD1 did not point to any nodes. Network comparison analysis further revealed no significant gender differences in the comorbidity network among older adults. Conclusion: This study provides a deeper understanding of the symptom-level relationships among sleep disorders, loneliness, and anxiety in community-dwelling older adults. The core and bridge symptoms identified in the GGM network may serve as key targets for the prevention and treatment of this comorbidity. In addition, the upstream node identified in the Bayesian network may provide useful insights for future longitudinal research and the development of interventions aimed at improving the overall health of community-dwelling older adults
Anxiety · Comorbidity · Loneliness · Network analysis · Pittsburgh Sleep Quality Index · Psychological intervention · Functional Brain Connectivity Studies · Health disparities and outcomes · Mental Health Research Topics
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| Highly cited | No |
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