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ORIGINAL RESEARCH article

Front. Psychiatry

Sec. Aging Psychiatry

Volume 16 - 2025 | doi: 10.3389/fpsyt.2025.1556054

Latent profile analysis of depression in elderly patients with cardio-and cerebrovascular diseases in China--Based on CLHLS data

Provisionally accepted
  • 1 First Affiliated Hospital of Jinzhou Medical University, Jinzhou, China
  • 2 Shanxi Bethune Hospital, Shanxi Medical University, Taiyuan, Shanxi Province, China

The final, formatted version of the article will be published soon.

    Background: This study explored the depressive status of elderly patients with cardioand cerebrovascular disease, using latent profile analysis to explore different profiles of depression. It also explored the factors influencing different profile of depression in patients with cardio-and cerebrovascular diseases to provide reference to healthcare workers to identify the high-risk group of anxiety and depression symptoms at an early stage.Methods: Data came from the Chinese Longitudinal Healthy Longevity Survey (CLHLS). In this study, we used latent profile analysis (LPA) to develop a latent profile model of elderly patients with cardio-and cerebrovascular disease combined with depression and to explore its influencing factors.Results: The 1890 study participants were divided into a low-level group (11%), a medium-level group (52%), and a high-level group (37%). The results of the univariate analysis showed statistically significant differences in the distribution of gender, age, co-residence, self-reported health, main source of financial support, marital status, diabetes, smoke, drank, exercise, level of anxiety, and IADL in the three profiles.Multiple logistic regression showed that good or fair self-reported health and exercise were associated with the low-level of depression; no spouse, and anxiety level were associated with moderately severe depressive conditions; and retirement wages, and local government or community predicted the appearance of low-level of depression compared to medium-level of depression.

    Keywords: latent profile analysis, Depression, Elderly, Cardio-and cerebrovascular, influencing factor

    Received: 17 Jan 2025; Accepted: 04 Mar 2025.

    Copyright: © 2025 Meng, Zheng and Hu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Qi Hu, First Affiliated Hospital of Jinzhou Medical University, Jinzhou, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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