Scholarlink

Objectives <p>This study aimed to investigate the network structure of depressive anxiety symptoms among Chinese community-dwelling older adults with physical multimorbidity and to identify specific symptom targets for preventive and treatment interventions aimed at aggravating and alleviating symptoms by patterns of physical multimorbidity.</p> Methods <p>Using data from the 2017/2018 wave of the Chinese Longitudinal Healthy Longevity Survey, latent class analysis (LCA) was conducted to identify physical multimorbidity patterns. Then, the NoeIdentifyR algorithm (NIRA) was employed to assess aggravating and alleviating specific symptoms by physical multimorbidity patterns.</p> Results <p>The study encompassed 4859 older adults with physical multimorbidity, and identified 4 patterns of physical multimorbidity (multisystem disease, gastrointestinal-musculoskeletal-urogenital disease, minimal disease, and cardiometabolic disease). GAD4 (trouble relaxing) served as the common aggravating symptom for the multisystem disease, minimal disease, and cardiometabolic disease groups, but GAD2 (uncontrollable worry) for the gastrointestinal-musculoskeletal-urogenital disease group. CESD5 (hopeful about the future) served as the common alleviating symptom for gastrointestinal-musculoskeletal-urogenital disease, minimal disease, and cardiometabolic disease groups, but CESD4 (everything was an effort) as the unique alleviating symptom for the multisystem disease group.</p> Conclusions <p>Aggravating and alleviating symptoms within the depressive-anxiety network differ by patterns of physical multimorbidity, which may imply that preventive and treatment targets should be tailored to patterns by physical multimorbidity for enhancing overall mental health among older adults.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Symptom-specific intervention targets for depression and anxiety among older adults by physical multimorbidity patterns: a simulation-based network analysis

  • 期刊论文

  • 发表日期：

    2025年7月16日

查看全文
  • Xue Wang,
  • Wendie Zhou,
  • Qinqin Liu,
  • Jiaqi Yu,
  • Yanyan Li,
  • Hejing Chen,
  • Cuili Wang

摘要

Objectives

This study aimed to investigate the network structure of depressive anxiety symptoms among Chinese community-dwelling older adults with physical multimorbidity and to identify specific symptom targets for preventive and treatment interventions aimed at aggravating and alleviating symptoms by patterns of physical multimorbidity.

Methods

Using data from the 2017/2018 wave of the Chinese Longitudinal Healthy Longevity Survey, latent class analysis (LCA) was conducted to identify physical multimorbidity patterns. Then, the NoeIdentifyR algorithm (NIRA) was employed to assess aggravating and alleviating specific symptoms by physical multimorbidity patterns.

Results

The study encompassed 4859 older adults with physical multimorbidity, and identified 4 patterns of physical multimorbidity (multisystem disease, gastrointestinal-musculoskeletal-urogenital disease, minimal disease, and cardiometabolic disease). GAD4 (trouble relaxing) served as the common aggravating symptom for the multisystem disease, minimal disease, and cardiometabolic disease groups, but GAD2 (uncontrollable worry) for the gastrointestinal-musculoskeletal-urogenital disease group. CESD5 (hopeful about the future) served as the common alleviating symptom for gastrointestinal-musculoskeletal-urogenital disease, minimal disease, and cardiometabolic disease groups, but CESD4 (everything was an effort) as the unique alleviating symptom for the multisystem disease group.

Conclusions

Aggravating and alleviating symptoms within the depressive-anxiety network differ by patterns of physical multimorbidity, which may imply that preventive and treatment targets should be tailored to patterns by physical multimorbidity for enhancing overall mental health among older adults.