Estimated Sleep-Wake Patterns Obtained From a Large U.S. Sample Using a Home-Based Under-Mattress Sleep-Monitoring Device
0
조회
0
다운로드
0
인용
0
참고문헌
키워드
초록
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.
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.
참고문헌 (23)
- Itani O, "Short sleep duration and health outcomes : a systematic review, meta-analysis, and meta-regression", Sleep Med, 32, pp.246~256 (2017)[DOI]
- Jike M, "Long sleep duration and health outcomes : a systematic review, meta-analysis and meta-regression", Sleep Med Rev, 39, pp.25~36 (2018)[DOI]
- Kecklund G, "Health consequences of shift work and insufficient sleep", BMJ, 355, pp.i5210~ (2016)[DOI]
- Wang N, "Long-term night shift work is associated with the risk of atrial fibrillation and coronary heart disease", Eur Heart J, 42, pp.4180~4188 (2021)[DOI]
- Alterman T, "Prevalence rates of work organization characteristics among workers in the U. S. : data from the 2010 national health interview survey", Am J Ind Med, 56, pp.647~659 (2013)[DOI]
- Huang T, "Sleep irregularity and risk of cardiovascular events : the multi-ethnic study of atherosclerosis", J Am Coll Cardiol, 75, pp.991~999 (2020)[DOI]
- Watson NF, "Joint consensus statement of the American Academy of Sleep Medicine and Sleep Research Society on the recommended amount of sleep for a healthy adult : methodology and discussion", Sleep, 38, pp.1161~1183 (2015)[DOI]
- Hirshkowitz M, "National Sleep Foundation’s sleep time duration recommendations : methodology and results summary", Sleep Health, 1, pp.40~43 (2015)[DOI]
- Huang T, "Cross-sectional and prospective associations of actigraphy-assessed sleep regularity with metabolic abnormalities : the multi-ethnic study of atherosclerosis", Diabetes Care, 42, pp.1422~1429 (2019)[DOI]
- He F, "Habitual sleep variability, mediated by nutrition intake, is associated with abdominal obesity in adolescents", Sleep Med, 16, pp.1489~1494 (2015)[DOI]
- Ogilvie RP, "Actigraphy measured sleep indices and adiposity : the multi-ethnic study of atherosclerosis(MESA)", Sleep, 39, pp.1701~1708 (2016)[DOI]
- Hoopes EK, "Sleep duration regularity, but not sleep duration, is associated with microvascular function in college students", Sleep, 44, pp.zsaa175~ (2021)[DOI]
- Phillips AJK, "Irregular sleep", wake patterns are associated with poorer academic performance and delayed circadian and sleep, Sci Rep, pp.2017, 7[DOI]
- Ding F, "Polysomnographic validation of an under-mattress monitoring device in estimating sleep architecture and obstructive sleep apnea in adults", Sleep Med, 96, pp.20~27 (2022)[DOI]
- Johns MW, "The sleep habits, personality and academic performance of medical students", Med Educ, 10, pp.158~162 (1976)[DOI]
- Patel SR, "The association between sleep patterns and obesity in older adults", Int J Obes(Lond), 38, pp.1159~1164 (2014)[DOI]
- Lunsford-Avery JR, "Validation of the sleep regularity index in older adults and associations with cardiometabolic risk", Sci Rep, 8, pp.14158~ (2018)[DOI]
- Mazzotti DR, "Human longevity is associated with regular sleep patterns, maintenance of slow wave sleep, and favorable lipid profile", Front Aging Neurosci, 6, pp.134~ (2014)[DOI]
- Manfredini R, "Daylight saving time, circadian rhythms, and cardiovascular health", Intern Emerg Med, 13, pp.641~646 (2018)[DOI]
- Wong PM, "Social jetlag, chronotype, and cardiometabolic risk", J Clin Endocrinol Metab, 100, pp.4612~4620 (2015)[DOI]
- Lenneis A, "Intraindividual variability and temporal stability of mid-sleep on free and workdays", J Biol Rhythms, 36, pp.169~184 (2021)[DOI]
- Roenneberg T, "Social jetlag and obesity", Curr Biol, 22, pp.939~943 (2012)[DOI]
- Allen Gomes A, "Sleep-wake patterns in Portuguese undergraduates", Acta Med Port, 22, pp.545~552 (2009)
