The Two Fundamental Shapes of Sleep Heart Rate Dynamics and Their Connection to Mental Health in College Students.

Q1 Computer Science
Digital Biomarkers Pub Date : 2024-07-01 eCollection Date: 2024-01-01 DOI:10.1159/000539487
Mikaela Irene Fudolig, Laura S P Bloomfield, Matthew Price, Yoshi M Bird, Johanna E Hidalgo, Julia N Kim, Jordan Llorin, Juniper Lovato, Ellen W McGinnis, Ryan S McGinnis, Taylor Ricketts, Kathryn Stanton, Peter Sheridan Dodds, Christopher M Danforth
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Abstract

Introduction: 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.

Methods: 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.

Results: 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.

Conclusion: 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.

大学生睡眠心率动态的两种基本形态及其与心理健康的关系。
导言:可穿戴设备正在迅速提高我们以非侵入方式长时间观察健康相关过程的能力。在这项研究中,我们利用可穿戴设备来了解睡眠时心率曲线的形状与心理健康的关系:作为 "使用戒指测量生活经历研究"(LEMURS)的一部分,我们使用 Oura 戒指(Gen3)收集了 2022 年秋季学期美国约 600 名大学一年级学生超过 25000 次睡眠期间的心率测量数据和自我报告的心理健康指标。利用聚类技术,我们发现睡眠心率曲线可大致分为两类,主要以睡眠期达到最低心率的程度来区分:结果:以睡眠期间较晚达到最低心率为特征的睡眠期也与较短的深睡眠和快速眼动睡眠以及较长的浅睡眠有关,但总睡眠时间并无差异。在个人层面对睡眠时间进行汇总后,我们发现,在睡眠过程中持续较晚达到最低心率是以下因素的重要预测因素:(1)焦虑或抑郁导致的自我报告损伤;(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:我们的研究结果表明,睡眠心率曲线的形状与平均心率或最低心率等描述性统计数据的相关性很弱,但它是一个可行的指标,有助于量化睡眠与心理健康之间的关系,但这一指标大多被忽视了。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Digital Biomarkers
Digital Biomarkers Medicine-Medicine (miscellaneous)
CiteScore
10.60
自引率
0.00%
发文量
12
审稿时长
23 weeks
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