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

Bibliographic Data

ID15524800
AuthorsMan Meng (First Affiliated Hospital of Liaoning Medical University), Zheng Chen (0000-0002-7695-1190, Shanxi Academy of Medical Sciences), Chen Zheng (0009-0009-0266-5309), Qi Hu (0000-0002-8676-2297, First Affiliated Hospital of Liaoning Medical University, corresponding author)
Year2025
Volume16
Pages1556054-1556054
Publication date2025-03-21
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueFrontiers in Psychiatry (JOURNAL)
Journal identifiersISSN: 1664-0640 • E-ISSN: 1664-0640
PublisherFrontiers Media (PUBLISHER • CH)
DOI10.3389/fpsyt.2025.1556054
PMID40191114
OpenAlexW4408717987
LanguageEN
References cited52

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

Anxiety · Depression (economics · Environmental health · Latent class model · Logistic regression · Marital status · Multivariate analysis · Population · Psychiatry · Spouse · Univariate analysis · Aging and Gerontology Research · Cardiac Health and Mental Health · Health disparities and outcomes · Medicine · Internal Medicine

Tools

Open DOIOpen Access