Literature DB >> 27866046

Changes in depression among older adults in China: A latent transition analysis.

Yuhan Ni1, Jenn-Yun Tein2, Minqiang Zhang3, Yawei Yang1, Guoting Wu1.   

Abstract

BACKGROUND: Depression in late life is an important public health problem in developing countries. It is timely to investigate stability and transition patterns of depressive symptom subtypes.
METHODS: Longitudinal data were used from the China Health and Retirement Longitudinal Study (CHARLS). A total of 853 women and 930 men aged 60-96 years were recruited. Latent class and latent transition analysis (LCA/LTA) were used to identify meaningful subgroups, transitions between those classes across time, and baseline demographic features that help to predict and design tailored interventions.
RESULTS: Three depression subgroups were identified: Class 1 was labeled "Mild Depression"; Class 2 was labeled "Severe Depression" and class 3 was labeled "Lack of Positive Affect". A predominant tendency for stability appeared rather than change, meanwhile individual in Mild Depression and Severe Depression latent status both had a high probability to convert to the Lack of Positive Affect latent status. Social activities played a significant role in buffering the effect of depression, while individuals with chronic diseases, having difficulty with ADLs and smoking might be at-risk groups. LIMITATIONS: The limitations of the present study were inherent limitation in the LTA model and some small proportion of transitions.
CONCLUSIONS: This study demonstrated a transition pattern in older adult depression within a person-centered approach. Differential treatment effects were found across baseline depression class, suggesting the benefit for tailored intervention programs to improve depression outcomes among older adults.
Copyright © 2016 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Depression; Latent transition analysis; Older adults; Predictive factors

Mesh:

Year:  2016        PMID: 27866046     DOI: 10.1016/j.jad.2016.11.004

Source DB:  PubMed          Journal:  J Affect Disord        ISSN: 0165-0327            Impact factor:   4.839


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