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

Yuhan Ni, Jenn-Yun Tein, Minqiang Zhang, Yawei Yang, Guoting Wu

Research output: Contribution to journalArticle

21 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)3-9
Number of pages7
JournalJournal of Affective Disorders
Volume209
DOIs
StatePublished - Feb 1 2017

Keywords

  • Depression
  • Latent transition analysis
  • Older adults
  • Predictive factors

ASJC Scopus subject areas

  • Clinical Psychology
  • Psychiatry and Mental health

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