Volume 24 Issue 1
Jan.  2026
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Article Navigation >  Chinese Journal of General Practice  > 2026  >  24(1): 104-108
HUANG Juju, MA Li, LI Pengyao, PANG Jiaxue, LIU Qiankun, XU Yang, CHEN Dandan, XIE Hui. The trajectory of depression and its influencing factors among retired middle-aged and elderly individuals in China[J]. Chinese Journal of General Practice, 2026, 24(1): 104-108. doi: 10.16766/j.cnki.issn.1674-4152.004340
Citation: HUANG Juju, MA Li, LI Pengyao, PANG Jiaxue, LIU Qiankun, XU Yang, CHEN Dandan, XIE Hui. The trajectory of depression and its influencing factors among retired middle-aged and elderly individuals in China[J]. Chinese Journal of General Practice, 2026, 24(1): 104-108. doi: 10.16766/j.cnki.issn.1674-4152.004340
shu

The trajectory of depression and its influencing factors among retired middle-aged and elderly individuals in China

doi: 10.16766/j.cnki.issn.1674-4152.004340
  • 1.

    Nursing College, Bengbu Medical University, Bengbu, Anhui 233030, China

Funds:

 2022AH040212

  • Received Date: 2025-01-24
    Available Online: 2026-04-01
    Abstract
  •   Objective  To analyze the developmental trajectories of depressive symptoms in retired middle-aged and elderly individuals, to identify potential predictors, and to provide a scientific basis for mental health interventions.  Methods  This research utilized data from the China Health and Retirement Longitudinal Study spanning the period from 2015 to 2020. The study population comprised of 4 435 retired middle-aged and elderly individuals who were selected as participants. A latent variable growth mixture model was employed in order to classify the developmental trajectories of depressive symptoms in this population. Further analysis was conducted in order to identify the predictors influencing these trajectories.  Results  The developmental trajectories of depressive symptoms in retired middle-aged and elderly individuals were classified into four categories: depressive remission (9.85%); depressive worsening (18.85%); persistently high depressive symptoms (9.50%); and persistently non-depressive (61.80%). Logistic regression analysis revealed that factors such as gender, age, education level, marital status, place of residence, self-rated health, disability status, history of hospitalization, number of children in the family, employment as urban workers, hearing ability, cognitive impairment, level of social participation, and chronic disease status were influencing factors of depressive symptom trajectories.  Conclusion  This study underscores the heterogeneity of developmental trajectories of depressive symptoms and the diversity among groups within the retired middle-aged and elderly population. Healthcare providers can utilize these distinct trajectory characteristics to implement targeted health management strategies. By identifying the various developmental trajectories of depressive symptoms, a more nuanced understanding of the dynamic changes in these symptoms can be achieved. This, in turn, offers a scientific foundation for the development of effective prevention and intervention strategies.

     

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