Joint longitudinal trajectories of depressive symptoms and cognitive function in relation to new-onset stroke among adults aged ≥ 50 years with diabetes or prediabetes: a multi-cohort study

Adults aged ≥ 50 years with diabetes or prediabetes frequently experience depressive symptoms and cognitive impairment, both of which may be associated with cerebrovascular vulnerability. However, little is known about whether their joint longitudinal patterns are associated with subsequent stroke risk. We analyzed data from three nationally representative aging cohorts: the Health and Retirement Study, the English Longitudinal Study of Ageing, and the China Health and Retirement Longitudinal Study. Participants with diabetes or prediabetes and without stroke during the trajectory assessment period were included. Group-based trajectory modeling was used to identify joint longitudinal profiles of depressive symptoms and a composite cognitive score comprising total word recall, temporal orientation, and Serial 7s. Associations with new-onset stroke were evaluated using Cox proportional hazards models, with competing-risk and discrete-time logistic models as sensitivity analyses. Machine learning models were developed to evaluate the importance of trajectory membership alongside other predictors. Distinct joint trajectory profiles were identified within each cohort. Relative to the most favorable profile, higher stroke risks were observed for the low-declining cognition/moderate-stable CES-D profile (HR = 1.52, 95% CI: 1.25–1.85) and the moderate-declining cognition/high-increasing CES-D profile (HR = 1.37, 95% CI: 1.24–1.51) in HRS; the low-declining cognition/high-increasing CES-D profile in ELSA (HR = 1.64, 95% CI: 1.39–1.94); and the low-declining cognition/high-decreasing CES-D profile in CHARLS (HR = 1.15, 95% CI: 1.01–1.31). The findings were consistent in sensitivity analyses. Trajectory membership contributed to model predictions but showed relatively low global SHAP importance. In adults aged ≥ 50 years with diabetes or prediabetes, adverse joint trajectories of depressive symptoms and cognitive function are associated with increased stroke risk. Further studies should determine whether trajectory information provides incremental predictive value beyond baseline cognitive and depressive symptom levels.

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Journal
Scientific Reports
Published
2026-09-04
DOI
https://doi.org/10.1038/s41598-026-69127-9
Primary Topic
Dementia and Cognitive Impairment Research
Type
article
Field-Weighted Citation Impact
0.00

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article

Joint longitudinal trajectories of depressive symptoms and cognitive function in relation to new-onset stroke among adults aged ≥ 50 years with diabetes or prediabetes: a multi-cohort study

Lijian Han, Yuanying Song, Jianping Liu, Yuan Shen et al.
Scientific Reports
Dementia and Cognitive Impairment Research
article

Joint longitudinal trajectories of depressive symptoms and cognitive function in relation to new-onset stroke among adults aged ≥ 50 years with diabetes or prediabetes: a multi-cohort study

Lijian Han, Yuanying Song, Jianping Liu, Yuan Shen, Gendi Wang, Shufang Wang
article en

Abstract

Adults aged ≥ 50 years with diabetes or prediabetes frequently experience depressive symptoms and cognitive impairment, both of which may be associated with cerebrovascular vulnerability. However, little is known about whether their joint longitudinal patterns are associated with subsequent stroke risk. We analyzed data from three nationally representative aging cohorts: the Health and Retirement Study, the English Longitudinal Study of Ageing, and the China Health and Retirement Longitudinal Study. Participants with diabetes or prediabetes and without stroke during the trajectory assessment period were included. Group-based trajectory modeling was used to identify joint longitudinal profiles of depressive symptoms and a composite cognitive score comprising total word recall, temporal orientation, and Serial 7s. Associations with new-onset stroke were evaluated using Cox proportional hazards models, with competing-risk and discrete-time logistic models as sensitivity analyses. Machine learning models were developed to evaluate the importance of trajectory membership alongside other predictors. Distinct joint trajectory profiles were identified within each cohort. Relative to the most favorable profile, higher stroke risks were observed for the low-declining cognition/moderate-stable CES-D profile (HR = 1.52, 95% CI: 1.25–1.85) and the moderate-declining cognition/high-increasing CES-D profile (HR = 1.37, 95% CI: 1.24–1.51) in HRS; the low-declining cognition/high-increasing CES-D profile in ELSA (HR = 1.64, 95% CI: 1.39–1.94); and the low-declining cognition/high-decreasing CES-D profile in CHARLS (HR = 1.15, 95% CI: 1.01–1.31). The findings were consistent in sensitivity analyses. Trajectory membership contributed to model predictions but showed relatively low global SHAP importance. In adults aged ≥ 50 years with diabetes or prediabetes, adverse joint trajectories of depressive symptoms and cognitive function are associated with increased stroke risk. Further studies should determine whether trajectory information provides incremental predictive value beyond baseline cognitive and depressive symptom levels.

Scientific Reports
Yancheng Third People's Hospital (CN), Nanjing Medical University (CN)
Nantong University, Yancheng Science and Technology Bureau
Good health and well-being
Openalex Percentile: Top 10%
Dementia and Cognitive Impairment Research
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