Estimated Sleep-Wake Patterns Obtained From a Large U.S. Sample Using a Home-Based Under-Mattress Sleep-Monitoring Device

Objectives: This study aimed to characterize sleep-wake schedules in a large U.S. sample. Methods: Descriptive analyses were performed on data from 12,507 users (46.9% female; mean age, 48.5±13.4 years) of a home-based sleep-monitoring device. To understand sleep-wake schedules and sleep regularity, the total sleep time (TST) standard deviation (SD) and sleep onset (SO) SD were included as parameters. Inferential analyses were performed on additional sleep parameters, including physiological (heart rate and respiratory rate) and sleep architecture parameters (TST, sleep efficiency, and wake after SO), in typically regular (average TST SD <60 minutes) vs. irregular (≥60 minutes) users. Results: 4,175,260 recorded nights were analyzed. The overall estimated TST SD (SD) across users mean was 66.1 (18.7) minutes, and the SO SD (SD) was 55.6 (20.5) minutes. The population was divided into 6 groups according to age: Groups 1 (20–29), 2 (30–39), 3 (40–49), 4 (50–59), 5 (60–69), and 6 (70–79). The estimated TST SD were: 70.7 (20.0), 67.2 (18.0), 66.8 (18.5), 66.1 (18.4), 63.4 (18.2), and 60.5 (18.9) minutes, respectively. The estimated SO SD were: 62.1 (21.1), 57.4 (19.4), 57.0 (20.2), 55.7 (20.0), 51.6 (20.3), and 46.7 (20.8) minutes, respectively. When participants were divided into those with regular and irregular sleep schedules, 58.4% were found to have an irregular sleep-wake schedule. Conclusions: Irregular sleep-wake schedules were prevalent across all age categories in this population. Even though this does not implicate causality, sleep habits represent a potentially modifiable behavior with health implications.

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Journal
Journal of Sleep Medicine
Published
2024-12-31
DOI
https://doi.org/10.13078/jsm.240020
Primary Topic
Sleep and Work-Related Fatigue
Type
article
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article

Estimated Sleep-Wake Patterns Obtained From a Large U.S. Sample Using a Home-Based Under-Mattress Sleep-Monitoring Device

Venkat Easwar, Arthur Kinsolving, Philippe Kahn, Clete A. Kushida et al.
Journal of Sleep Medicine
Sleep and Work-Related Fatigue
article

Estimated Sleep-Wake Patterns Obtained From a Large U.S. Sample Using a Home-Based Under-Mattress Sleep-Monitoring Device

Venkat Easwar, Arthur Kinsolving, Philippe Kahn, Clete A. Kushida, Andrew Cotton-Clay, Jennifer Zitser
article en

Abstract

Objectives: This study aimed to characterize sleep-wake schedules in a large U.S. sample. Methods: Descriptive analyses were performed on data from 12,507 users (46.9% female; mean age, 48.5±13.4 years) of a home-based sleep-monitoring device. To understand sleep-wake schedules and sleep regularity, the total sleep time (TST) standard deviation (SD) and sleep onset (SO) SD were included as parameters. Inferential analyses were performed on additional sleep parameters, including physiological (heart rate and respiratory rate) and sleep architecture parameters (TST, sleep efficiency, and wake after SO), in typically regular (average TST SD <60 minutes) vs. irregular (≥60 minutes) users. Results: 4,175,260 recorded nights were analyzed. The overall estimated TST SD (SD) across users mean was 66.1 (18.7) minutes, and the SO SD (SD) was 55.6 (20.5) minutes. The population was divided into 6 groups according to age: Groups 1 (20–29), 2 (30–39), 3 (40–49), 4 (50–59), 5 (60–69), and 6 (70–79). The estimated TST SD were: 70.7 (20.0), 67.2 (18.0), 66.8 (18.5), 66.1 (18.4), 63.4 (18.2), and 60.5 (18.9) minutes, respectively. The estimated SO SD were: 62.1 (21.1), 57.4 (19.4), 57.0 (20.2), 55.7 (20.0), 51.6 (20.3), and 46.7 (20.8) minutes, respectively. When participants were divided into those with regular and irregular sleep schedules, 58.4% were found to have an irregular sleep-wake schedule. Conclusions: Irregular sleep-wake schedules were prevalent across all age categories in this population. Even though this does not implicate causality, sleep habits represent a potentially modifiable behavior with health implications.

Journal of Sleep MedicineVol. 21(3)
Tel Aviv Sourasky Medical Center (IL), Stanford University (US)
Good health and well-being
Openalex Percentile: Top 69%
Sleep and Work-Related Fatigue
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Estimated Sleep-Wake Patterns Obtained From a Large U.S. Sample Using a Home-Based Under-Mattress Sleep-Monitoring Device — Venkat Easwar, Arthur Kinsolving, et al. · Journal of Sleep Medicine (2024) | TGRS Research Map | TGRS