The association of eight-year trajectories in total, cognitive-affective, and somatic depressive symptoms with incident stroke: a 10-year follow-up study using HRS and ELSA cohorts

TL;DR

Long-term changes in depressive symptoms, especially increasing or fluctuating patterns, are linked to higher stroke risk in older adults.

Contribution

This study is the first to examine longitudinal trajectories of total and subtype depressive symptoms in relation to stroke risk using repeated assessments.

Findings

Increasing, fluctuating, and consistently high total depressive symptoms were associated with elevated stroke risk.

Cognitive-affective symptoms increasing over time and consistently high somatic symptoms showed the strongest stroke risk associations.

Decreasing depressive symptoms were not significantly linked to increased stroke risk.

Abstract

Earlier research has documented an association between depressive symptomatology and heightened stroke risk. However, prior work largely assessed depressive manifestations at isolated time points and failed to differentiate symptom subtypes. This investigation seeks to characterize the longitudinal progression of depressive symptoms via repeated measurement and explore their link to stroke risk by considering total depressive symptoms alongside cognitive-affective and somatic dimensions.

This prospective cohort study included individuals aged ≥ 45 years from the Health and Retirement Study (HRS) in the United States and the English Longitudinal Study of Ageing (ELSA) in the United Kingdom, excluding those with a history of stroke during the exposure period. Depressive symptoms were measured using the 8-item Center for Epidemiologic Studies Depression Scale (CES-D) across four biennial assessments. Individuals were categorized into five distinct depressive symptom trajectories: consistently low, decreasing, fluctuating, increasing, and consistently high, based on assessment scores. Over a subsequent decade of follow-up, incident strokes were identified through self-reported physician diagnoses. The analyses incorporated adjustments for demographic factors (sex, age, etc.), health-related behaviors (smoking, drinking, etc.), and health status covariates (hypertension, diabetes, etc.). Cox proportional hazards regression models generated hazard ratios (HRs) and 95% confidence intervals (CIs) to evaluate links between trajectories of total depressive symptoms, cognitive-affective and somatic subtypes, and stroke occurrence.

The final cohort included 10,011 participants (63.3% female; mean age 60.2 years). During the 10-year follow-up, 720 incident strokes were recorded. Analyses demonstrated that, after adjusting for the aforementioned demographic and health-related confounders, relative to the consistently low trajectory, participants with fluctuating (HR = 1.24, 95% CI: 1.01–1.52), increasing (HR = 1.31, 95% CI: 1.03–1.67), and consistently high (HR = 1.42, 95% CI: 1.03–1.97) total depressive symptom trajectories exhibited significantly elevated stroke risk. Conversely, the decreasing trajectory (HR = 1.11, 95% CI: 0.85–1.45) did not significantly impact stroke risk. Furthermore, an increasing trajectory of cognitive-affective depressive symptoms (HR = 1.43, 95% CI: 1.13–1.82), alongside fluctuating (HR = 1.27, 95% CI: 1.03–1.55) and consistently high (HR = 1.97, 95% CI: 1.42–2.74) somatic depressive symptom trajectories, were each significantly associated with heightened stroke risk. Critically, the consistently high somatic trajectory demonstrated the most robust association with stroke.

Trajectories of total depressive symptoms marked by escalation, instability, or sustained elevation exhibited significantly elevated stroke risk. In contrast, individuals displaying decreasing depressive symptoms exhibit stroke risk comparable to those maintaining consistently low levels. Specifically, an ascending trajectory of cognitive-affective symptoms, alongside unstable and persistently elevated trajectories of somatic symptoms, are linked to increased stroke risk. These findings emphasize the clinical importance of monitoring dynamic changes in depressive symptoms and their subtypes for stroke prevention. Future investigations should elucidate underlying mechanisms to refine identification and intervention strategies for high-risk populations.

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