Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Institute for Management in Medicine and Health Sciences, University of Bayreuth, Bayreuth, Germany.
J Affect Disord. 2024 Oct 1;362:126-133. doi: 10.1016/j.jad.2024.06.114. Epub 2024 Jun 28.
The association of a single time-point measure of sleep duration with cardio-metabolic disease has been extensively studied, but few studies have focused on the impact of sleep duration trajectory. This study aims to model the sleep duration trajectory as predictors for the subsequent development of cardio-metabolic disease.
This study recruited a notably large population (n = 9883) of subjects aged at least 45 years from the China Health and Retirement Longitudinal Study (CHARLS), who participated in sequential surveys conducted in 2011, 2013, 2015, and 2018. Sleep duration trajectories were plotted using data of night sleep duration recorded at intervals from 2011 to 2015 by latent class trajectory model. The onset of cardio-metabolic diseases from 2015 to 2018 were confirmed and then the risk of different sleep duration trajectories on incident cardio-metabolic disease was examined using cox proportional hazards regression model.
We identified four sleep duration trajectories. Compared to the normal-stable trajectory, the short-stable trajectory was significantly associated with higher risk of incident stroke (hazard ratio [HR], 1.32; 95 % confidence interval [CI], 1.02 to 1.70), dyslipidemia (HR, 1.22; 95%CI, 1.01 to 1.49), and diabetes (HR, 1.42; 95%CI, 1.13 to 1.78) within three years of follow-up, and the short-increasing trajectory predicted a higher risk of incident stroke (HR, 2.38; 95%CI, 1.25 to 4.55).
Short sleep trajectory could increase the risk of incident stroke, dyslipidemia, and diabetes, and an increasing sleep trajectory was associated with increased risk of incident stroke among middle-aged and older Chinese adults.
单次睡眠时间与心血管代谢疾病的关联已得到广泛研究，但很少有研究关注睡眠时间轨迹的影响。本研究旨在构建睡眠时间轨迹模型，以预测随后心血管代谢疾病的发生。
本研究招募了来自中国健康与退休纵向研究（CHARLS）的一个相当大的人群（n=9883），这些受试者年龄至少为 45 岁，并在 2011、2013、2015 和 2018 年参加了连续调查。使用 2011 年至 2015 年期间夜间睡眠时间记录的数据，通过潜在类别轨迹模型绘制睡眠时间轨迹。从 2015 年到 2018 年确认心血管代谢疾病的发病情况，然后使用 Cox 比例风险回归模型检查不同睡眠时间轨迹对新发心血管代谢疾病的风险。
我们确定了四个睡眠时间轨迹。与正常稳定轨迹相比，短稳定轨迹与三年内新发卒中（风险比 [HR]，1.32；95%置信区间 [CI]，1.02 至 1.70）、血脂异常（HR，1.22；95%CI，1.01 至 1.49）和糖尿病（HR，1.42；95%CI，1.13 至 1.78）的发病风险显著相关，而短增轨迹则预示着新发卒中的风险更高（HR，2.38；95%CI，1.25 至 4.55）。
短睡眠时间轨迹可增加新发卒中、血脂异常和糖尿病的风险，而睡眠时间增加轨迹与中国中老年人群新发卒中风险增加相关。
