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Background <p>Subthreshold depression (SD) represents a critical public health concern, marked by clinically significant depressive symptoms below the diagnostic threshold for major depressive disorder. Despite frequent comorbidity with anxiety and insomnia, the symptom-level interactions remain poorly understood. Network analysis offers a novel framework to examine these dynamic relationships and identify central symptoms that may drive SD’s psychopathology. We hypothesize that the symptom network of SD may exhibit specific patterns of interconnectivity, with certain central and bridge symptoms potentially playing a key role in the development and maintenance of the disorder.</p> Methods <p>This study included a sample of 1,049 patients with SD. Zung Self-Rating Depression Scale (SDS), Zung Self-Rating Anxiety Scale (SAS), and Pittsburgh Sleep Quality Index (PSQI) were used to assess depression, anxiety and insomnia symptoms, respectively. Network analysis was used to estimate the symptom network, with centrality (expected influence, EI) and bridge symptoms (bridge EI) calculated to identify core and bridge symptoms. Additionally, the Network Comparison Test (NCT) was performed to examine potential gender-based differences.</p> Results <p>The results showed that SAS.1 “Anxiousness” emerged as the most central node (EI = 2.39), followed by SAS.2 “Fear” (EI = 2.30), SAS.3 “Panic” (EI = 2.15), and SDS.20 “Interest loss” (EI = 1.21). Bridge analysis identified PSQI.7 “Daily dysfunction” (bridge EI = 1.56) and PSQI.4 “Sleep efficiency” (bridge EI = 1.47) as key transdiagnostic links. Gender did not significantly affect the overall network structure.</p> Conclusion <p>This network analysis of SD represents the first comprehensive examination of depressive, anxiety, and sleep symptoms simultaneously within this population. The findings identify “Anxiousness”, “Fear”, “Panic”, and “Interest loss” as central symptoms and sleep-related dysfunction as a potential bridge between symptom domains. These symptoms may represent candidate targets for future longitudinal and intervention studies aimed at alleviating the symptom burden of SD.</p>

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Associations of depression, anxiety, and insomnia symptoms in subthreshold depression: a network analysis

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年10月10日

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  • Xiumin Jiang,
  • Xiaotong Wang,
  • Bodong Liu,
  • Lin Yu,
  • Jun He,
  • Shengwei Wu,
  • Yuanyuan Zhou,
  • Bingyan Zhang,
  • Qinghua Gao,
  • Lin Yao,
  • Yuanjia Zheng,
  • Jinglan Yan,
  • Yongjun Chen

摘要

Background

Subthreshold depression (SD) represents a critical public health concern, marked by clinically significant depressive symptoms below the diagnostic threshold for major depressive disorder. Despite frequent comorbidity with anxiety and insomnia, the symptom-level interactions remain poorly understood. Network analysis offers a novel framework to examine these dynamic relationships and identify central symptoms that may drive SD’s psychopathology. We hypothesize that the symptom network of SD may exhibit specific patterns of interconnectivity, with certain central and bridge symptoms potentially playing a key role in the development and maintenance of the disorder.

Methods

This study included a sample of 1,049 patients with SD. Zung Self-Rating Depression Scale (SDS), Zung Self-Rating Anxiety Scale (SAS), and Pittsburgh Sleep Quality Index (PSQI) were used to assess depression, anxiety and insomnia symptoms, respectively. Network analysis was used to estimate the symptom network, with centrality (expected influence, EI) and bridge symptoms (bridge EI) calculated to identify core and bridge symptoms. Additionally, the Network Comparison Test (NCT) was performed to examine potential gender-based differences.

Results

The results showed that SAS.1 “Anxiousness” emerged as the most central node (EI = 2.39), followed by SAS.2 “Fear” (EI = 2.30), SAS.3 “Panic” (EI = 2.15), and SDS.20 “Interest loss” (EI = 1.21). Bridge analysis identified PSQI.7 “Daily dysfunction” (bridge EI = 1.56) and PSQI.4 “Sleep efficiency” (bridge EI = 1.47) as key transdiagnostic links. Gender did not significantly affect the overall network structure.

Conclusion

This network analysis of SD represents the first comprehensive examination of depressive, anxiety, and sleep symptoms simultaneously within this population. The findings identify “Anxiousness”, “Fear”, “Panic”, and “Interest loss” as central symptoms and sleep-related dysfunction as a potential bridge between symptom domains. These symptoms may represent candidate targets for future longitudinal and intervention studies aimed at alleviating the symptom burden of SD.