Depressive symptoms and chronic disease trajectories and predictors in middle-aged and older adults in China: An eight-year multi-trajectory analysis
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View abstract on PubMed
Summary
This summary is machine-generated.This study identifies three distinct health trajectories for older Chinese adults, revealing that older age, disability, and poor health predict increased depression and chronic disease risk. These findings aid in developing targeted interventions for healthy aging.
Area Of Science
- Gerontology
- Public Health
- Computational Biology
Background
- Middle-aged and older adults face increasing risks of depression and chronic diseases.
- Identifying health trajectories is crucial for promoting healthy aging.
- China's aging population necessitates understanding disease progression patterns.
Purpose Of The Study
- To identify and predict latent trajectories of depression and chronic disease in Chinese middle-aged and older adults.
- To explore key factors influencing these health trajectories and promote healthy aging.
- To apply data-driven and interpretable machine learning methods for health outcome prediction.
Main Methods
- Analysis of longitudinal data from 13,073 participants in the China Health and Retirement Longitudinal Study (CHARLS).
- Application of Group-Based Multi-Trajectory Modeling (GBMTM) to identify distinct health trajectory groups.
- Utilized machine learning models and dynamic nomograms for prediction, with performance evaluated by AUROC and DCA.
Main Results
- Three latent trajectory groups were identified: normal healthy (26.9%), potential increase in depression/disease (55.6%), and high burden (17.5%).
- Older age, disability, shorter sleep, and poor self-reported health were significant predictors of adverse trajectories.
- Urban women showed particular vulnerability to these risk factors.
Conclusions
- GBMTM and machine learning effectively identify and predict depression and chronic disease trajectories in older adults.
- Identified predictors offer targets for developing interventions to promote healthy aging.
- Findings underscore the need for tailored strategies addressing specific risk factors in diverse populations.
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