Dynamic patterns of depression and their association with stroke: insights from CHARLS, ELSA, and HRS

BACKGROUND: Depression is highly prevalent among older adults and has consistently been identified as an independent risk factor for incident stroke. Most previous cohort studies have relied on a single baseline measure of depressive symptoms. However, accumulating evidence suggests that the dynamic progression of depression - its persistence, remission, or emergence over time - may differentially affect cerebrovascular risk. Furthermore, existing research has predominantly been limited to individual national cohorts, thereby restricting the generalizability of findings across diverse sociocultural and healthcare contexts. To address these limitations, we analyzed depressive symptom trajectories over multiple waves and their association with subsequent stroke onset in three large, prospective aging cohorts: the Health and Retirement Study (HRS), the English Longitudinal Study of Ageing (ELSA), and the China Health and Retirement Longitudinal Study (CHARLS). METHOD: In this study, depressive symptoms were evaluated biennially using the Center for Epidemiologic Studies Depression Scale (CES-D) for participants in HRS and ELSA and CHARLS. Through rule-based trajectory modeling, four distinct patterns of symptom burden trajectory were identified: no, decreasing, increasing, and consistently high. Stroke events were ascertained via self-reported physician diagnosis in HRS and ELSA, and through medical record linkage in CHARLS. For each cohort, logistic regression models were applied to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for stroke risk across the trajectory groups, using the persistent low group as the reference. The models were adjusted for potential confounders, including demographic variables, health behaviors, and history of chronic disorders. Furthermore, stratified analyses were performed across subgroups to explore potential heterogeneity in the associations between depressive symptom trajectories and stroke risk. RESULTS: The study included 4587 participants from HRS, 4879 from ELSA, and 7792 from CHARLS. During the follow-up period, there were 376, 137, and 133 incident strokes reported in the HRS, ELSA, and CHARLS cohorts, respectively. The "Consistently high" depressive-symptom trajectory was associated with a significantly increased risk of stroke across all three cohorts (CHARLS: OR 2.56, 95% CI: 1.62-4.04; ELSA: OR 2.96, 95% CI: 1.28-6.84; HRS: OR 1.56, 95% CI: 1.03-2.36) compared to the "No" group. The "decreasing" trajectory did not show a significant association with stroke, whereas the "increasing" trajectory was linked to a moderate elevation in stroke risk in the ELSA and HRS cohorts. CONCLUSION: Older adults exhibiting persistently high or increasing depressive symptoms are at a significantly elevated risk of stroke. Continuous monitoring and early intervention targeting these high-risk depression trajectories may offer a novel strategy for primary stroke prevention.