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中国老年糖尿病患者抑郁和焦虑症状的网络分析

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

作者信息

Zhang Yajuan, Cui Yi, Li Yijun, Lu Hongliang, Huang He, Sui Jiaru, Guo Zhihua, Miao Danmin

机构信息

Department of Military Medical Psychology, Air Force Medical University, Xi'an, China.

Department of Nursing, Air Force Medical University, Xi'an, China.

出版信息

Front Psychiatry. 2024 Jan 29;15:1328857. doi: 10.3389/fpsyt.2024.1328857. eCollection 2024.

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 comorbidities. 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 potential targets for prevention and intervention for 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 depressive and anxiety symptoms was estimated based on self-reported scales completed by 1685 older adults with DM aged 65 years or older. Depressive and anxiety symptoms were assessed using the 10-item Center for Epidemiologic Studies Depression Scale (CESD-10) and the Seven-Item Generalized Anxiety Disorder Scale (GAD-7), respectively. Expected influence (EI) and bridge expected influence (BEI) indices were calculated for each symptom.

RESULTS

According to cutoff scores indicating the presence of depression and anxiety, 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 currently have depressive and anxiety symptoms.

摘要

背景

从使用总分对精神障碍进行整体研究转向使用网络分析来分析症状水平的相互作用,为共病研究提供了新的见解。本研究探讨了中国老年糖尿病患者抑郁症状和焦虑症状之间的动态相互作用,并确定了抑郁 - 焦虑网络中的核心症状和桥梁症状,为抑郁和焦虑的预防及干预提供潜在靶点。

方法

本研究采用横断面设计,数据来自2017 - 2018年中国老年健康长寿纵向调查(CLHLS)。基于1685名65岁及以上患有糖尿病的老年人填写的自我报告量表,估计了抑郁和焦虑症状的正则化偏相关网络。抑郁症状和焦虑症状分别使用10项流行病学研究中心抑郁量表(CESD - 10)和7项广泛性焦虑障碍量表(GAD - 7)进行评估。计算每个症状的预期影响(EI)和桥梁预期影响(BEI)指数。

结果

根据表明存在抑郁和焦虑的临界分数,我们样本中抑郁和焦虑的患病率分别为52.9%和12.8%。抑郁和焦虑的共病率为11.5%。正则化偏相关性最强的六条边存在于同一障碍的症状之间。“情绪低落/沮丧”“紧张或焦虑”“无法控制的担忧”“难以放松”和“过度担忧”的EI值最高。“紧张或焦虑”和“事事费力”的BEI值最高。

结论

本研究突出了核心症状和桥梁症状。针对这些症状可能有效预防抑郁和焦虑症状的共病,并有助于对有抑郁和焦虑症状风险或目前患有抑郁和焦虑症状的中国老年糖尿病患者进行干预。

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