Background <p>Older adults with multiple chronic conditions represent a vulnerable group with health issues intricately intertwined, making them more susceptible to mental health issues such as depression and anxiety. To identify central and bridge symptoms to implement effective interventions, this study constructed a network model of depression and anxiety symptoms among older adults with MCCs, exploring the correlations among specific symptoms.</p> Methods <p>This study used the data from the 2018 Chinese Longitudinal Healthy Longevity Survey (CLHLS) to construct a network model for depression and anxiety symptoms among older people with MCCs. Depression and anxiety symptoms were assessed by using the Center for Epidemiologic Studies Depression Scale-10 (CESD-10) and the Generalized Anxiety Disorder Scale-7 (GAD-7). Network analysis was used to identify the central symptoms and bridge symptoms between the network of depression and anxiety symptoms. The network stability was examined by a case-dropping bootstrap procedure.</p> Results <p>Network analysis revealed that nodes GAD2 (Uncontrollable worry) and CESD3(Felt sadness) were the most primary symptoms and GAD1(Nervousness), CESD1 (Bother by things), CESD10 (Sleep quality), and GAD3 (Excessive worry) were bridge symptoms of the anxiety-depression network.</p> Conclusion <p>Central symptoms and bridge symptoms played a critical role in the anxiety-depression symptoms network. Future research should explore intervention strategies for these symptoms to improve the mental health of older adults with MCCs.</p>

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A network analysis of depression and anxiety symptoms among Chinese elderly with multiple chronic conditions: based on the 2017–2018 Chinese Longitudinal Healthy Longevity Survey (CLHLS)

  • Junqing Luo,
  • Jinsong Deng,
  • Wei Zhou,
  • Leiyu Shi,
  • Qiuli Zhu,
  • Zixian Huang,
  • Ruoyu Gui,
  • Xiangang Cai,
  • Guangli Hu,
  • Gang Sun

摘要

Background

Older adults with multiple chronic conditions represent a vulnerable group with health issues intricately intertwined, making them more susceptible to mental health issues such as depression and anxiety. To identify central and bridge symptoms to implement effective interventions, this study constructed a network model of depression and anxiety symptoms among older adults with MCCs, exploring the correlations among specific symptoms.

Methods

This study used the data from the 2018 Chinese Longitudinal Healthy Longevity Survey (CLHLS) to construct a network model for depression and anxiety symptoms among older people with MCCs. Depression and anxiety symptoms were assessed by using the Center for Epidemiologic Studies Depression Scale-10 (CESD-10) and the Generalized Anxiety Disorder Scale-7 (GAD-7). Network analysis was used to identify the central symptoms and bridge symptoms between the network of depression and anxiety symptoms. The network stability was examined by a case-dropping bootstrap procedure.

Results

Network analysis revealed that nodes GAD2 (Uncontrollable worry) and CESD3(Felt sadness) were the most primary symptoms and GAD1(Nervousness), CESD1 (Bother by things), CESD10 (Sleep quality), and GAD3 (Excessive worry) were bridge symptoms of the anxiety-depression network.

Conclusion

Central symptoms and bridge symptoms played a critical role in the anxiety-depression symptoms network. Future research should explore intervention strategies for these symptoms to improve the mental health of older adults with MCCs.