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

被引：0

作者：

Fudolig, Mikaela Irene ^{[1
,2
,3
]}

Bloomfield, Laura S.P. ^{[1
,2
,3
,4
]}

Price, Matthew ^{[1
,5
]}

Bird, Yoshi M. ^{[1
,3
]}

Hidalgo, Johanna E. ^{[5
]}

Kim, Julia N. ^{[6
,7
]}

Llorin, Jordan ^{[6
,7
]}

Lovato, Juniper ^{[1
,3
,8
]}

McGinnis, Ellen W. ^{[9
]}

McGinnis, Ryan S. ^{[9
]}

Ricketts, Taylor ^{[4
,10
]}

Stanton, Kathryn ^{[6
,7
]}

Dodds, Peter Sheridan ^{[1
,3
,8
,11
]}

Danforth, Christopher M. ^{[1
,2
,3
,4
]}

机构：

[1] Vermont Complex Systems Center, MassMutual Center of Excellence for Complex Systems and Data Science, University of Vermont, Burlington, VT

[2] Department of Mathematics and Statistics, University of Vermont, Burlington, VT

[3] Computational Story Lab, MassMutual Center of Excellence for Complex Systems and Data Science, University of Vermont, Burlington, VT

[4] Gund Institute for Environment, University of Vermont, Burlington, VT

[5] Department of Psychological Science, University of Vermont, Burlington, VT

[6] Project Lemurs, University of Vermont, Burlington, VT

[7] Department of Electrical and Biomedical Engineering, University of Vermont, Burlington, VT

[8] Department of Computer Science, University of Vermont, Burlington, VT

[9] Wake Forest University School of Medicine, Winston-Salem, NC

[10] Rubenstein School of Environment and Natural Resources, University of Vermont, Burlington, VT

[11] Santa Fe Institute, Santa Fe, NM

来源：

Digital Biomarkers | 2024年 / 8卷 / 01期

基金：

美国国家卫生研究院;

关键词：

Clustering; Heart rate; Mental health; Sleep; Sleep phenotypes; Wearable devices;

D O I：

10.1159/000539487

中图分类号：

学科分类号：

摘要：

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. © 2024 The Author(s). Published by S. Karger AG, Basel.

引用

页码：120 / 131

页数：11