National Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, Beijing, China.
School of Public Health, Peking University, Beijing, China.
JAMA Netw Open. 2020 May 1;3(5):e205246. doi: 10.1001/jamanetworkopen.2020.5246.
Single self-reported measures of sleep duration are associated with adverse health outcomes; however, long-term patterns of self-reported sleep duration and their association with cardiovascular events (CVEs) and all-cause mortality remain unknown.
To determine whether trajectories of long-term vs single-measure sleep duration are associated with subsequent risk of CVEs and all-cause mortality.
DESIGN, SETTING, AND PARTICIPANTS: The Kailuan study is a prospective, population-based cohort study that began in 2006. The present cohort included 52 599 Chinese adults without atrial fibrillation, myocardial infarction, stroke, or cancer to 2010. Trajectories in sleep duration from January 1, 2006, to December 31, 2010, were identified to investigate the association with risk of CVEs and all-cause mortality from January 1, 2010, to December 31, 2017. Data analysis was conducted from July 1 to October 31, 2019.
Habitual self-reported nocturnal sleep durations were collected in 2006, 2008, and 2010. Trajectories in sleep duration for 4 years were identified by latent mixture modeling.
All-cause mortality and first incident CVEs (atrial fibrillation, myocardial infarction, and stroke) from 2010 to 2017 were confirmed by medical records. Based on the baseline sleep duration and patterns over time, 4 trajectories were categorized (normal stable, normal decreasing, low increasing, and low stable).
Of the 52 599 adults included in the study (mean [SD] age at baseline, 52.5 [11.8] years), 40 087 (76.2%) were male and 12 512 (23.8%) were female. Four distinct 4-year sleep duration trajectory patterns were identified: normal stable (range, 7.4 to 7.5 hours [n = 40 262]), normal decreasing (mean decrease from 7.0 to 5.5 hours [n = 8074]), low increasing (mean increase from 4.9 to 6.9 hours [n = 3384]), and low stable (range, 4.2 to 4.9 hours [n = 879]). During a mean (SD) follow-up of 6.7 (1.1) years, 2361 individuals died and 2406 had a CVE. Compared with the normal-stable pattern and adjusting for potential confounders, a low-increasing pattern was associated with increased risk of first CVEs (hazard ratio [HR], 1.22; 95% CI, 1.04-1.43), a normal-decreasing pattern was associated with increased risk of all-cause mortality (HR, 1.34; 95% CI, 1.15-1.57), and the low-stable pattern was associated with the highest risk of CVEs (HR, 1.47; 95% CI, 1.05-2.05) and death (HR, 1.50; 95% CI, 1.07-2.10).
In this study, sleep duration trajectories with lower or unstable patterns were significantly associated with increased risk of subsequent first CVEs and all-cause mortality. Longitudinal sleep duration patterns may assist in more precise identification of different at-risk groups for possible intervention. People reporting consistently sleeping less than 5 hours per night should be regarded as a population at higher risk for CVE and mortality.
单一的自我报告的睡眠时长与不良健康结果有关;然而,自我报告的睡眠时长的长期模式及其与心血管事件(CVE)和全因死亡率的关联仍不清楚。
确定长期和单一测量的睡眠时长轨迹与随后发生 CVE 和全因死亡率的风险之间是否存在关联。
设计、地点和参与者:Kailuan 研究是一项前瞻性、基于人群的队列研究,始于 2006 年。本队列包括 52599 名没有心房颤动、心肌梗死、中风或癌症的中国成年人,随访至 2010 年。确定 2006 年 1 月 1 日至 2010 年 12 月 31 日期间的睡眠时长轨迹,以调查从 2010 年 1 月 1 日至 2017 年 12 月 31 日期间发生 CVE 和全因死亡率的风险。数据分析于 2019 年 7 月 1 日至 10 月 31 日进行。
2006 年、2008 年和 2010 年收集了习惯性夜间睡眠时间。通过潜在混合模型确定了 4 年的睡眠时长轨迹。
从 2010 年至 2017 年,通过医疗记录确定全因死亡率和首次发生的 CVE(心房颤动、心肌梗死和中风)。根据基线睡眠时长和随时间的变化模式,将 4 种轨迹分为(正常稳定、正常减少、低增加和低稳定)。
在这项研究中,纳入了 52599 名成年人(基线时的平均[标准差]年龄为 52.5[11.8]岁),其中 40087 名(76.2%)为男性,12512 名(23.8%)为女性。确定了 4 种独特的 4 年睡眠时长轨迹模式:正常稳定(范围为 7.4 至 7.5 小时[n=40262])、正常减少(平均从 7.0 小时减少至 5.5 小时[n=8074])、低增加(平均从 4.9 小时增加至 6.9 小时[n=3384])和低稳定(范围为 4.2 至 4.9 小时[n=879])。在平均(标准差)6.7(1.1)年的随访期间,有 2361 人死亡,2406 人发生 CVE。与正常稳定模式相比,并在调整了潜在混杂因素后,低增加模式与首次 CVE 的风险增加相关(危险比[HR],1.22;95%置信区间[CI],1.04-1.43),正常减少模式与全因死亡率的风险增加相关(HR,1.34;95% CI,1.15-1.57),而低稳定模式与 CVE(HR,1.47;95% CI,1.05-2.05)和死亡(HR,1.50;95% CI,1.07-2.10)的风险最高。
在这项研究中,较低或不稳定的睡眠时长轨迹模式与随后发生的首次 CVE 和全因死亡率的风险增加显著相关。纵向睡眠时长模式可能有助于更准确地识别可能需要干预的不同高危人群。报告持续每晚睡眠时间少于 5 小时的人群应被视为 CVE 和死亡率较高的人群。