As the second leading contributor to global mortality and the third primary cause of disability-adjusted life years (DALYs) (GBD 2017 Dalys and Hale Collaborators, 2018), stroke also ranks as the fifth leading cause of death within the United States (Virani et al., 2020). Epidemiological evidence indicates that the global lifetime probability of experiencing a stroke from age 25 has progressively risen over the past thirty years, currently approximating 24.9% (Meza et al., 2020). Amidst accelerating population aging and extended lifespans, the cumulative economic burden and societal consequences of stroke are anticipated to intensify (Marsh and Keyrouz, 2010). Consequently, pinpointing stroke risk determinants is essential for devising effective preventive and mitigation approaches. Established classical risk factors like smoking and diabetes are recognized (Liu et al., 2021); however, these factors alone do not comprehensively explain all stroke risk. Recent years have seen amplified focus on stroke risk factor inquiry, accumulating robust evidence suggesting that depressive symptoms can augment stroke vulnerability (Glymour et al., 2012; Meza et al., 2020). Meta-analyses consistently report associations between depression/depressive symptomatology and a 31% to 45% elevation in prospective stroke risk (Barlinn et al., 2014; Li et al., 2015). A meta-analysis including 17 prospective studies showed a significant positive association between depressive symptoms and subsequent stroke risk (pooled relative risk = 1.34, 95% CI: 1.17–1.54) after adjusting for potential confounders such as smoking, hypertension, and diabetes. This suggests that depressive symptoms are an independent risk factor for increased stroke risk, independent of confounders such as smoking and comorbid conditions (Dong et al., 2012). Moreover, research by Gilsanz et al. (2017) revealed that older adults enduring depression for a 2-year duration faced a 65% higher stroke risk relative to their non-depressed counterparts.

Contemporary research furnishes substantial evidence that depressive symptoms exhibit dynamic patterns across the lifespan, characterized by periods of remission and recurrence. Nevertheless, the majority of earlier investigations concentrated predominantly on the mere presence or short-term persistence (≤ 2 years) of depressive symptoms concerning incident stroke, frequently neglecting long-term dynamic fluctuations, specifically depressive symptom trajectories (Gilsanz et al., 2015, 2017; Glymour et al., 2012; Liu et al., 2021; Meza et al., 2020). Certain individuals experience persistent, chronic depression, while others may encounter transient symptom exacerbations precipitated by stressors. Additionally, some may suffer symptom relapse following a period of remission. Failure to longitudinally track depressive symptom progression may yield an incomplete comprehension of their association with incident stroke. Furthermore, depressive symptoms encompass multifaceted dimensions, including cognitive-affective and somatic subtypes (Iob et al., 2020). A scarcity of research probes the connection between distinct facets of depressive symptoms and cardiovascular/cerebrovascular diseases. Existing inquiries predominantly rely on static analyses conducted at discrete time points. Ongoing debate surrounds the relationship between cognitive-affective versus somatic depressive symptoms and cardiovascular/cerebrovascular disease risk (de Miranda Azevedo et al., 2014; Hoen et al., 2010a,b; Martens et al., 2010; Meijer et al., 2011; Norton et al., 2021; Wium-Andersen et al., 2019). Research specifically examining the correlation between particular depressive symptom dimensions and stroke incidence remains insufficient. Consequently, the impact of cognitive-affective and somatic depressive symptoms on stroke occurrence is not fully elucidated. Investigating potential associations between longitudinal depressive symptom trajectories and stroke events may yield more precise causal inference.

This study aims to address the existing research gap by examining the dynamic trajectories of depressive symptoms over time, including distinct subtypes, and exploring their association with stroke risk. Using data from the Health and Retirement Study (HRS) and the English Longitudinal Study of Ageing (ELSA), we conducted an 8-year foundational assessment of the trajectories of total, cognitive-affective, and somatic depressive symptoms, and their relationship with stroke risk over the following ten years. The analyses accounted for adjustments in key demographic factors (such as sex and age), health-related behaviors (including smoking and drinking), and health status covariates (such as hypertension and diabetes), providing a comprehensive evaluation of these associations.

Following exclusion criteria, 10,011 participants were included in the final analysis, with data spanning a 10-year follow-up. Within this cohort, 720 incident strokes were identified. Analyses focused on correlations between depressive symptom trajectories and incident stroke incidence, demonstrating significant impacts of various symptom subtypes and trajectories on stroke risk.

Tables 1, 2 present baseline demographic characteristics, health behaviors, and health conditions of the merged sample, stratified by total depressive symptom trajectory. At baseline, mean age was 60.2 years; 63.3% female; 88.8% White; 56.2% had high school education or less. Health behavior analysis: mean BMI 27.7 kg/m (Virani et al., 2020); 55.3% ever smokers; 66.7% ever drinkers; 53.9% reported no vigorous physical activity. During exposure, 62.5% exhibited a consistently low trajectory, with a notably higher proportion married/partnered (79.7%). Conversely, a substantial proportion (77.4%) within the consistently high trajectory had high school education or less. Regarding health conditions, prevalence of underlying issues was markedly higher among participants in the consistently high trajectory: 12.5% heart disease, 42.1% hypertension, 10.1% diabetes, 6.5% cancer.

Table 3 and Figure 3 illustrate longitudinal relationships between trajectories of total, cognitive-affective, and somatic depressive symptoms and incident stroke risk. In the fully adjusted Model 4 (demographics, health behaviors, health conditions), individuals with a consistently high total depressive symptom trajectory showed significantly elevated stroke risk versus consistently low (HR = 1.42, 95% CI: 1.03–1.97). Similarly, relative to reference, individuals with increasing (HR = 1.31, 95% CI: 1.03–1.67) and fluctuating (HR = 1.24, 95% CI: 1.01–1.52) trajectories also exhibited heightened risk. Conversely, the decreasing trajectory showed no statistically significant difference in risk (HR = 1.11, 95% CI: 0.85–1.45).

Stratifying total depressive symptoms into subtypes revealed distinct associations. In Model 4, individuals with an increasing cognitive-affective trajectory demonstrated significantly elevated stroke risk versus consistently low cognitive-affective (HR = 1.43, 95% CI: 1.13–1.82). Conversely, risks for decreasing (HR = 1.07, 95% CI: 0.82–1.40), fluctuating (HR = 1.19, 95% CI: 0.97–1.47), and consistently high (HR = 1.17, 95% CI: 0.79–1.73) cognitive-affective trajectories were non-significant relative to reference.

Similarly, using consistently low somatic trajectory as reference in Model 4, individuals with consistently high somatic trajectory demonstrated significantly elevated stroke risk (HR = 1.97, 95% CI: 1.42–2.74). Those with a fluctuating somatic trajectory also exhibited increased risk (HR = 1.27, 95% CI: 1.03–1.55). Conversely, increasing (HR = 1.21, 95% CI: 0.94–1.56) or decreasing (HR = 1.14, 95% CI: 0.89–1.47) somatic trajectories showed no statistically significant difference in risk.

Sensitivity analyses confirmed the consistency and robustness of primary findings. Six distinct methods were employed (detailed in Supplementary Tables 2–9). Analyses consistently showed that fluctuating, increasing, and consistently high total depressive symptom trajectories were associated with elevated stroke risk versus consistently low, while the decreasing trajectory showed no significant correlation. Additionally, increasing cognitive-affective symptoms, alongside fluctuating and consistently high somatic trajectories, were linked to heightened stroke risk, with consistently high somatic presenting the greatest risk.

This research examined the association between long-term depressive symptom patterns and incident stroke likelihood in US and UK middle-aged and older adults. The assessed trajectories were classified as: consistently low, decreasing, fluctuating, increasing, and consistently high. Results indicate that, irrespective of whether symptoms were categorized as total, cognitive-affective, or somatic, no significant association existed between stroke risk and the decreasing trajectory. Conversely, fluctuating, increasing, and consistently high total depressive symptom trajectories, along with the increasing cognitive-affective trajectory and fluctuating and consistently high somatic trajectories, were identified as significant stroke risk factors. Among these, the consistently high somatic trajectory demonstrated the strongest association. Critically, these findings persisted after adjusting for potential confounding variables affecting the trajectory-stroke relationship. Sensitivity analyses, incorporating modifications to models, trajectories, covariates, and extended follow-up, further substantiated result robustness. To our knowledge, this is the first study exploring the relationship between cognitive-affective and somatic depressive symptom trajectories and stroke risk.

Depressive symptoms exhibit dynamism and can persist long-term; consequently, longitudinal assessment of symptom progression and variation enables a more thorough evaluation of their impact on incident stroke. Our findings suggest that persistent depressive symptoms—whether progressively worsening, fluctuating, or chronically elevated—are linked to increased stroke risk. This association likely stems from cumulative cardiovascular damage inflicted by prolonged exposure to depressive states. Notably, if patients experience an extended remission period, their risk of stroke may not be elevated despite having previously undergone severe depressive states. Potential biological mechanisms linking recurrently elevated depressive symptoms to stroke include neuroendocrine dysregulation, platelet dysfunction, and immune-inflammatory responses (Pan et al., 2011). Specifically, this trajectory of depressive symptoms may activate the hypothalamic-pituitary-adrenal (HPA) axis, leading to sustained secretion of cortisol (Iob et al., 2020). This hormonal imbalance is hypothesized to drive metabolic dysregulation and long-term physiological changes, such as atherosclerosis and white matter hyperintensities (Gilsanz et al., 2017). Ultimately, these cumulative pathological processes contribute to a significantly increased risk of incident stroke. Meta-analyses indicate that depressive symptom alleviation post-treatment correlates with reduced inflammatory markers, notably interleukin-6 (IL-6) and C-reactive protein (CRP) (Hiles et al., 2012; Strawbridge et al., 2015). This implies inflammation may be a critical mediator between depression and stroke, suggesting that modulating inflammation via depression treatment could aid stroke prevention. Some studies suggest antidepressant therapies may reduce stroke risk by attenuating inflammation (Zuzarte et al., 2018). Furthermore, depressive symptoms can be categorized into cognitive-affective and somatic subtypes.

Cognitive-affective symptoms (e.g., mood disturbances, anxiety, emotional stress) may elevate stroke risk through diverse mechanisms. Psychological stress from environmental factors like noise significantly impacts cardiovascular health (Min et al., 2024; Patten, 2012; Pendlebury, 2012). Chronic stress induces hormonal imbalances causing oxidative stress, damaging vasculature and increasing stroke risk (Brooks et al., 2018; Hahad et al., 2019; Lian et al., 2025). Additionally, cognitive-affective symptoms may foster poor health behaviors (reduced activity, unhealthy diet, poor treatment adherence). Depression can also engender loneliness and social isolation, creating a vicious cycle of poor health behaviors and heightened stroke risk (Valtorta et al., 2016). Our study found that individuals with an increasing cognitive-affective symptom trajectory had a higher risk of stroke, indicating that compared to decreasing or fluctuating trajectories, sustained and escalating psychological stress is more likely to induce pathological cerebral vascular changes and promote unhealthy lifestyles. This progressively worsening psychological pressure may create an environment where recovery seems unattainable. The unremitting upward trajectory of cognitive-affective symptoms exerts a stronger negative impact on cerebrovascular health. Therefore, we should be especially vigilant about the increased risk of stroke associated with rising cognitive-affective depressive symptoms.

In contrast, somatic depressive symptoms (e.g., energy depletion, sleep disturbances, psychomotor retardation) appear to possess stronger predictive power for stroke risk. These symptoms may increase risk through multiple pathways. Somatic symptoms can precipitate unhealthy behaviors [smoking (Ambrose and Barua, 2004; Ding et al., 2019; Middlekauff et al., 2014), excessive alcohol consumption (Biddinger et al., 2022; Csengeri et al., 2021; Whitman et al., 2017)], detrimental to cardiovascular health. Prolonged somatic symptoms may disrupt autonomic nervous system function, particularly by activating the sympathetic nervous system (Penninx, 2017), elevating heart rate and blood pressure, ultimately raising stroke risk. Additionally, fatigue—common in somatic depression—has been linked to increased stroke risk (Barlas et al., 2020). Sleep disturbances associated with somatic symptoms can elevate inflammatory markers (CRP, IL-6) (Kappelmann et al., 2021; Mayer-Suess et al., 2024), contributing to vascular damage and atherosclerosis, thereby increasing stroke risk (Kong et al., 2022; Soehnlein and Libby, 2021). This aligns with prior research showing depression treatment reduces inflammation (Strawbridge et al., 2015). Our study found fluctuating and consistently high somatic trajectories were strongly associated with stroke risk, with consistently high showing the most significant link. This suggests long-term somatic depressive symptoms, especially those that fluctuate or persist, are more likely to detrimentally impact cardiovascular health compared to shorter-term trajectories like increasing or decreasing. We believe that multiple factors jointly mediate the increased stroke risk associated with somatic depressive symptoms. While the impact of increasing cognitive-affective symptoms on stroke risk may be attributed to their escalating psychological burden, the effect of somatic symptoms appears to depend more on duration. The longer the persistence of somatic depressive symptoms, the greater the risk of stroke.

Additional mechanisms may underlie the observed dynamic alterations in depressive symptom trajectories and their stroke risk association. For example, the fluctuating trajectory group might include individuals diagnosed with bipolar disorder or other episodic mood disorders, possessing genetic profiles distinct from unipolar depression (Wassertheil-Smoller et al., 2018). The relationship between these conditions and stroke risk may be attributed to factors like side effects of mood stabilizers (vs. the disorder itself), medication-induced weight gain/metabolic abnormalities, and healthcare access challenges (Chen et al., 2019; Prieto et al., 2014). Moreover, individuals classified into distinct trajectory groups often display differing baseline characteristics, indicative of subpopulations (Byers et al., 2012). Progressive depressive symptoms might signal early-stage specific diseases (e.g., dementia) or represent a delayed depressive response to other physical conditions (hypertension, hypercholesterolemia, diabetes), all significantly associated with subsequent stroke risk (Fiske et al., 2009; Mirza et al., 2014). Consequently, we posit that diverse depressive symptom trajectories reflect not only distinct clinical profiles and potential pathological pathways but also varied origins of stroke risk. Tailored prevention and intervention strategies for these subgroups are imperative.

Prior to this investigation, limited research explored the relationship between depressive symptom trajectories and incident stroke (Li et al., 2022; Loyal et al., 2025; Soh et al., 2022; Wu et al., 2022), with no studies differentiating subtypes. Moreover, existing studies typically defined trajectories based on only two assessment cycles. This study’s strength lies in integrating representative prospective cohorts (HRS, ELSA), utilizing repeated symptom assessments and long-term follow-up, while incorporating a comprehensive covariate set to control confounding. Extensive sensitivity analyses bolstered the findings’ robustness and generalizability. Additionally, distinguishing between depressive symptom subtypes and delineating long-term dynamic trajectories for both total and subtype-specific symptoms enabled identification of differential stroke risks associated with specific subtypes and trajectories, offering nuanced explanations for the depression-stroke association. Furthermore, participant selection was not contingent on mental health issues, enhancing sample representativeness relative to the general population. Nonetheless, limitations exist. First, while the somatic symptom classification derived from the CES-D scale is contextually appropriate, it may not perfectly align with definitions in other scholarly works or measurement tools (Shafer, 2006). Second, excluding individuals lacking CES-D scores or experiencing stroke pre-exposure limits generalizability to these populations. Third, focusing on individuals ≥ 45 years may limit applicability to younger cohorts. Fourth, reliance on self-reported questionnaires introduces potential recall bias, possibly compromising response accuracy. Fifth, medication adherence could influence the trajectory-stroke risk relationship; however, adherence data (accessible primarily via pharmacy records) were unavailable in this study. Therefore, results should be interpreted cautiously, acknowledging these unaccounted confounding factors.

This study’s findings suggest that recurrently elevated total depressive symptoms, characterized by increasing, fluctuating, or persistently high trajectories, are associated with heightened incident stroke risk. However, stroke risk appears modifiable with symptom changes, as individuals exhibiting decreasing symptoms show risk comparable to those with consistently low symptoms. Worsening, unstable, or chronically high total depressive symptoms may signal underlying cerebrovascular issues. Examining subtypes revealed that an ascending trajectory of cognitive-affective symptoms, alongside unstable and persistently elevated trajectories of somatic symptoms, are associated with increased stroke risk. These insights provide crucial clinical guidance for stroke prevention. Future research should delve into the overarching and trajectory-specific mechanisms underpinning these associations to enhance identification and protection of high-risk populations.