0363 Racial/Ethnic Differences in Actigraphy, Questionnaire, and Polysomnography-Measured Indicators of Sleep Health and Sleep Quality: The Multi-Ethnic Study of Atherosclerosis. (27th May 2020)

• Record Type: Journal Article
• Authors: Chung, J; Goodman, M O; Huang, T; Wallace, M; Bertisch, S; Johnson, D; Redline, S
• Is Part Of: Sleep. Volume 43(2020)Supplement 1
• Page Start: A138
• Page End: A139
• Publication Date: 2020-05-27
• Subjects: Sleep -- Physiological aspects -- Periodicals; Sleep disorders -- Periodicals; Sommeil -- Aspect physiologique -- Périodiques; Sommeil, Troubles du -- Périodiques; Sleep disorders; Sleep -- Physiological aspects; Sleep -- physiological aspects; Sleep Wake Disorders; Psychophysiology; Electronic journals; Periodicals; 616.8498
• DOI: 10.1093/sleep/zsaa056.360
• Languages: English
• ISSNs: 0161-8105

Abstract

Abstract: Introduction: Paradigm shifts in sleep research suggest the importance of considering multi-dimensional sleep health, compared to single metrics, to promote physical and mental well-being and to understand racial/ethnic disparities in sleep. Methods: We used data from the Multi-Ethnic Study of Atherosclerosis (MESA; n = 1, 740) to create a Sleep Health Score (SHS), including questionnaire (quality, sleepiness); 7-day actigraphy (total sleep time, sleep continuity [sleep maintenance efficiency], timing consistency [midpoint variability], fragmentation, wake after sleep onset, sleep onset latency); and in-home polysomnography (%N3 sleep, %REM sleep, AHI). Sleep parameters were dichotomized based on prior literature or by healthiest quartile(s), with positive values denoting healthier sleep (e.g. Epworth scores < 10). All 11 dichotomized parameters were summed to calculate the SHS (mean=4.9, sd=1.58). We used modified Poisson and linear regression for individual sleep outcomes and the SHS, respectively, adjusting for age and sex. Results: The sample was older (mean age=68.28, sd=9.08) and 54% female. SHSs were associated with Black race (β=-0.60 [-0.78, -0.42]) and Hispanic ethnicity (β=-0.40 [-0.59, -0.21]), but not Chinese ethnicity (β=-0.16 [-0.41, 0.08]). Compared to Whites (n=644), Blacks (n=485) showed lower adjusted probability of obtaining favorable levels of: sleep continuity, fragmentation, timing consistency, alertness/sleepiness, and sleep depth (%N3 sleep). Chinese respondents (n=202) had lower probability of obtaining favorable levels of: sleep continuity and timing consistency, but higher probability of quality. Hispanics (n=409) had lower probability of obtaining healthy levels of: sleep continuity, timing consistency, and fragmentation. Neither healthy total sleep time (middle quartiles) nor AHI (<30) differed by race/ethnicity. Conclusion: Among MESA-Sleep participants, summary SHSs were lowest in Blacks, followed by Hispanics. Multiple dimensions of sleep - particularly related to continuity and timing consistency - were less favorable across race/ethnic minority groups. A summary SHS may help monitor sleep health across populations, while measurement of specific sleep components may help identify modifiable targets. Support: Joon Chung is supported by a T-32 NIH training grant.