Network analysis of depressive and anxiety symptoms in older Chinese adults with diabetes mellitus

Author:

Zhang Yajuan1,Cui Yi1,Li Yijun1,Lu Hongliang1,Huang He2,Sui Jiaru1,Guo Zhihua1,Miao Danmin1

Affiliation:

1. Air Force Medical University

2. Air Force Hospital of Northern Theater Command

Abstract

Abstract Background: The move away from investigating mental disorders as whole using sum scores to the analysis of symptom-level interactions using network analysis has provided new insights into comorbidity.The current study explored the dynamic interactions between depressive and anxiety symptoms in older Chinese adults with diabetes mellitus (DM) and identified central and bridge symptoms in the depression-anxiety network to provide targets for prevention and intervention into depression and anxiety. Methods: This study used a cross-sectional design with data from the 2017–2018 wave of the Chinese Longitudinal Healthy Longevity Survey (CLHLS). A regularized partial correlation network for depression and anxiety was estimated based on self-reported scales completed by 1685 older adults with DM aged 65 years or older. Expected influence (EI) and bridge expected influence(BEI) indices were calculated for each symptom. Results: The prevalences of depression and anxiety in our sample were 52.9% and 12.8%, respectively. The comorbidity rate of depression and anxiety was 11.5%. The six edges with the strongest regularized partial correlations were between symptoms from the same disorder. “Feeling blue/depressed”, “Nervousness or anxiety”, “Uncontrollable worry”, “Trouble relaxing”, and “Worry too much” had the highest EI values. “Nervousness or anxiety” and “Everything was an effort” exhibited the highest BEI values. Conclusion: Central and bridge symptoms were highlighted in this study. Targeting these symptoms may be effective in preventing the comorbidity of depressive and anxiety symptoms and facilitate interventions in older Chinese adults with DM who are at risk for or suffer from depressive and anxiety symptoms.

Publisher

Research Square Platform LLC

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