Fudolig Mikaela Irene, Bloomfield Laura S P, Price Matthew, Bird Yoshi M, Hidalgo Johanna E, Kim Julia N, Llorin Jordan, Lovato Juniper, McGinnis Ellen W, McGinnis Ryan S, Ricketts Taylor, Stanton Kathryn, Dodds Peter Sheridan, Danforth Christopher M
Vermont Complex Systems Center, MassMutual Center of Excellence for Complex Systems and Data Science, University of Vermont, Burlington, VT, USA.
Department of Mathematics and Statistics, University of Vermont, Burlington, VT, USA.
Digit Biomark. 2024 Jul 1;8(1):120-131. doi: 10.1159/000539487. eCollection 2024 Jan-Dec.
Wearable devices are rapidly improving our ability to observe health-related processes for extended durations in an unintrusive manner. In this study, we use wearable devices to understand how the shape of the heart rate curve during sleep relates to mental health.
As part of the Lived Experiences Measured Using Rings Study (LEMURS), we collected heart rate measurements using the Oura ring (Gen3) for over 25,000 sleep periods and self-reported mental health indicators from roughly 600 first-year university students in the USA during the fall semester of 2022. Using clustering techniques, we find that the sleeping heart rate curves can be broadly separated into two categories that are mainly differentiated by how far along the sleep period the lowest heart rate is reached.
Sleep periods characterized by reaching the lowest heart rate later during sleep are also associated with shorter deep and REM sleep and longer light sleep, but not a difference in total sleep duration. Aggregating sleep periods at the individual level, we find that consistently reaching the lowest heart rate later during sleep is a significant predictor of (1) self-reported impairment due to anxiety or depression, (2) a prior mental health diagnosis, and (3) firsthand experience in traumatic events. This association is more pronounced among females.
Our results show that the shape of the sleeping heart rate curve, which is only weakly correlated with descriptive statistics such as the average or the minimum heart rate, is a viable but mostly overlooked metric that can help quantify the relationship between sleep and mental health.
可穿戴设备正在迅速提升我们以非侵入性方式长时间观察与健康相关过程的能力。在本研究中，我们使用可穿戴设备来了解睡眠期间心率曲线的形状与心理健康之间的关系。
作为“使用戒指测量生活体验研究”（LEMURS）的一部分，我们在2022年秋季学期，使用Oura戒指（第三代）收集了超过25000个睡眠时段的心率测量数据，并从大约600名美国大学一年级学生那里收集了自我报告的心理健康指标。通过聚类技术，我们发现睡眠心率曲线大致可分为两类，主要区别在于最低心率出现在睡眠时段的哪个阶段。
在睡眠后期达到最低心率的睡眠时段，也与较短的深度睡眠和快速眼动睡眠以及较长的浅睡眠相关，但总睡眠时间没有差异。在个体层面汇总睡眠时段，我们发现持续在睡眠后期达到最低心率是以下情况的重要预测指标：（1）因焦虑或抑郁导致的自我报告的功能损害，（2）先前的心理健康诊断，以及（3）创伤事件的亲身经历。这种关联在女性中更为明显。
我们的结果表明，睡眠心率曲线的形状与诸如平均心率或最低心率等描述性统计指标的相关性较弱，它是一个可行但大多被忽视的指标，有助于量化睡眠与心理健康之间的关系。
