Observational studyBMC psychiatry2025
Trajectories of depressive symptoms in middle-aged and older Chinese adults: identifying subgroups, core symptoms and predictors.
Observational study in BMC psychiatry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Depressive Symptom Trajectories and Incident Pain: The Role of Nocturnal Sleep Duration in Two Prospective Cohort Studies.Journal of prevention (2022) · 2026Article
- Relationship between depressive symptom trajectories and cardiovascular disease risk in middle-aged and older adults with cardiovascular-kidney-metabolic syndrome stages 0-3.BMC cardiovascular disorders · 2026Article
- Religious Involvement and Depressive Symptoms in Mainland China: A Trend Analysis of Older Adults, 2012-2023.Journal of religion and health · 2026Article
- Depressive trajectories and their associations with chronic diseases among older adults: a national longitudinal cohort study from China.BMC geriatrics · 2025Article
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Authors and funding
9 authors.
Funding
Abstract
backgroundDepressive symptoms among middle-aged and older adults are a significant public health concern, with varying symptom trajectories over time. Understanding these trajectories and their predictors can inform targeted interventions.
objectivesTo identify subgroups of depressive symptom trajectories, determine predictors of these subgroups, and explore the core symptoms and their predictive relationships.
methodsThis study analyzed 7,166 participants aged ≥ 45 years from the China Health and Retirement Longitudinal Study across four waves (2011, 2013, 2015, 2018). Depressive symptoms were assessed using the 10-item Center for Epidemiologic Studies Depression Scale. Group-based trajectory modeling (GBTM) identified depressive symptom trajectories. Multivariate logistic regression explored influencing factors, while Cross-lagged panel network models (CLPN) were used to identify core symptoms.
resultsThree distinct trajectory groups were identified: "stable low" (66.4%), "decline followed by an increase" (27.8%), and "continuously rising" (5.8%). Females, those with lower education, poor self-reported health, unmarried status and rural residents were associated with worsening symptoms. CLPN analysis revealed "depressive mood" as the core symptom, with "feeling lonely" and "could not get going" predicting "depressive mood."
conclusionThis study identifies distinct trajectories of depressive symptoms in older adults and pinpoints "depressive mood" as a core symptom, which is dynamically predicted by loneliness and a lack of behavioral activation. Therefore, an effective public health strategy should involve not only identifying at-risk individuals based on their trajectory profiles but also targeting these specific precursor symptoms to prevent escalation.
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