Department of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China; Guangdong Provincial Key Laboratory of Food, Nutrition and Health, Sun Yat-sen University, Guangzhou, China.
Department of Neurology, Shenzhen Shekou People's Hospital, Shenzhen, China.
J Affect Disord. 2022 Jul 15;309:229-235. doi: 10.1016/j.jad.2022.04.137. Epub 2022 Apr 28.
Depressive symptoms (DS) can increase the risk of stroke, but it is unclear whether long-term DS trajectories are associated with incident stroke. This study aimed to explore the association of long-term DS trajectories with incident stroke.
This prospective cohort study included 11,002 adults aged 50 and older from the Health and Retirement Study during 1994-2018. DS was assessed using the 8-item version of the Center for Epidemiologic Studies Depression Scale. Stroke was obtained through self-report of doctors' diagnosis. The group-based trajectory model was used to determine DS trajectories from 1994 to 2000. Cox proportional hazard model was applied to explore the correlation of DS trajectories with incident stroke from 2000 to 2018.
We identified five distinct 6-year DS trajectories. Compared with the persistent no DS trajectory, the full-adjusted HRs (95% CIs) for the persistent mild, improving, worsening, and persistent high DS trajectories were 1.15 (1.01, 1.30), 1.27 (0.88, 1.84), 1.41 (1.17, 1.71), and 1.61 (1.21, 2.16), respectively. In addition, the persistent mild DS trajectories had the largest population attributable risk percent (PAR%).
There was a lack of information on stroke subtypes.
This study suggests that compared with persistent no DS, persistent mild, worsening, and persistent high DS trajectories increase the risk of stroke in the elderly. Considering that the PAR% of stroke events in the persistent mild DS trajectory is the largest, we should pay attention not only to individuals with DS, but also to those being chronically close to the cut-off value of DS.
抑郁症状（DS）会增加中风的风险，但长期 DS 轨迹是否与中风事件相关尚不清楚。本研究旨在探讨长期 DS 轨迹与中风事件的关系。
本前瞻性队列研究纳入了 1994 年至 2018 年间来自健康与退休研究的 11002 名年龄在 50 岁及以上的成年人。使用中心流行病学研究抑郁量表的 8 项版本评估 DS。中风通过医生诊断的自我报告获得。使用基于群组的轨迹模型确定 1994 年至 2000 年的 DS 轨迹。应用 Cox 比例风险模型探讨 2000 年至 2018 年 DS 轨迹与中风事件的相关性。
我们确定了五个不同的 6 年 DS 轨迹。与持续无 DS 轨迹相比，持续轻度、改善、加重和持续高度 DS 轨迹的全调整 HR（95%CI）分别为 1.15（1.01，1.30）、1.27（0.88，1.84）、1.41（1.17，1.71）和 1.61（1.21，2.16）。此外，持续轻度 DS 轨迹的人群归因风险百分比（PAR%）最大。
缺乏中风亚型的信息。
本研究表明，与持续无 DS 相比，持续轻度、加重和持续高度 DS 轨迹会增加老年人中风的风险。考虑到持续轻度 DS 轨迹中风事件的 PAR%最大，我们不仅要关注有 DS 的个体，还要关注那些长期接近 DS 临界值的个体。
