Background <p>Rural older adults with type 2 diabetes mellitus (T2DM) commonly experience depressive symptoms, sleep disturbances, and cognitive impairment, which frequently co-occur and interact. However, the key symptoms linking these domains remain unclear, and network analysis may help identify central and bridge symptoms within this cross-domain system.</p> Methods <p>Rural older adults with T2DM were assessed for depressive symptoms using the Geriatric Depression Scale-15, cognitive performance using the Montreal Cognitive Assessment—Basic, and sleep quality using the Pittsburgh Sleep Quality Index. We constructed a network structure, and calculated index of strength and bridge expected influence for each symptom. Furthermore, a comparative analysis of the network structure across gender was conducted.</p> Results <p>A total of 885 participants were included. The estimated network revealed a stable and interconnected symptom system spanning depressive symptoms, sleep disturbances, and cognitive deficits. Symptoms related to abstraction and calculation and helplessness emerged as the most central nodes. Abstraction ability, perceived memory problems, and concentration difficulties functioned as key bridge symptoms linking cognitive, depressive, and sleep-related domains. Sensitivity analyses supported the robustness of the network, and no significant differences in edge weights were observed between male and female participants.</p> Conclusions <p>This study highlights a connected cross-domain symptom system underlying depression, sleep disturbance, and cognitive impairment in older adults with T2DM. Central and bridge symptoms may represent pivotal mechanisms through which affective and sleep-related problems interact with cognitive decline. Targeting these high-impact symptoms may offer a theoretically informed strategy for disrupting maladaptive symptom interactions and improving integrated mental and cognitive health outcomes.</p>

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Bridge symptoms connecting depressive, sleep, and cognitive domains in rural older adults with type 2 diabetes: a symptom network approach

  • Xueyan Liu,
  • Zhaotai Wang,
  • Yingjuan Cao

摘要

Background

Rural older adults with type 2 diabetes mellitus (T2DM) commonly experience depressive symptoms, sleep disturbances, and cognitive impairment, which frequently co-occur and interact. However, the key symptoms linking these domains remain unclear, and network analysis may help identify central and bridge symptoms within this cross-domain system.

Methods

Rural older adults with T2DM were assessed for depressive symptoms using the Geriatric Depression Scale-15, cognitive performance using the Montreal Cognitive Assessment—Basic, and sleep quality using the Pittsburgh Sleep Quality Index. We constructed a network structure, and calculated index of strength and bridge expected influence for each symptom. Furthermore, a comparative analysis of the network structure across gender was conducted.

Results

A total of 885 participants were included. The estimated network revealed a stable and interconnected symptom system spanning depressive symptoms, sleep disturbances, and cognitive deficits. Symptoms related to abstraction and calculation and helplessness emerged as the most central nodes. Abstraction ability, perceived memory problems, and concentration difficulties functioned as key bridge symptoms linking cognitive, depressive, and sleep-related domains. Sensitivity analyses supported the robustness of the network, and no significant differences in edge weights were observed between male and female participants.

Conclusions

This study highlights a connected cross-domain symptom system underlying depression, sleep disturbance, and cognitive impairment in older adults with T2DM. Central and bridge symptoms may represent pivotal mechanisms through which affective and sleep-related problems interact with cognitive decline. Targeting these high-impact symptoms may offer a theoretically informed strategy for disrupting maladaptive symptom interactions and improving integrated mental and cognitive health outcomes.