Day-to-day deviations in sleep parameters and biological aging: Findings from the NHANES 2011-2014

Xiaoling Wang; Yanyan Xu; Xinyue Li; Asifhusen Mansuri; William V McCall; Yutao Liu; Shaoyong Su

doi:10.1016/j.sleh.2023.07.018

Day-to-day deviations in sleep parameters and biological aging: Findings from the NHANES 2011-2014

Sleep Health. 2023 Dec;9(6):940-946. doi: 10.1016/j.sleh.2023.07.018. Epub 2023 Aug 28.

Authors

Xiaoling Wang¹, Yanyan Xu², Xinyue Li³, Asifhusen Mansuri⁴, William V McCall⁵, Yutao Liu⁶, Shaoyong Su⁷

Affiliations

¹ Georgia Prevention Institute, Medical College of Georgia, Augusta University, Augusta, Georgia, USA; Center for Biotechnology and Genomic Medicine, Medical College of Georgia, Augusta University, Augusta, Georgia, USA. Electronic address: xwang@augusta.edu.
² Georgia Prevention Institute, Medical College of Georgia, Augusta University, Augusta, Georgia, USA; Center for Biotechnology and Genomic Medicine, Medical College of Georgia, Augusta University, Augusta, Georgia, USA.
³ School of Data Science, City University of Hong Kong, Hong Kong, China.
⁴ Division of Pediatric Nephrology and Hypertension, Children's Hospital of Georgia, Medical College of Georgia, Augusta University, Augusta, Georgia, USA.
⁵ Department of Psychiatry and Health Behavior, Medical College of Georgia, Augusta University, Augusta, Georgia, USA.
⁶ Department of Cellular Biology & Anatomy, Medical College of Georgia, Augusta University, Augusta, Georgia, USA.
⁷ Georgia Prevention Institute, Medical College of Georgia, Augusta University, Augusta, Georgia, USA.

PMID: 37648648
PMCID: PMC10843622 (available on 2024-12-01)
DOI: 10.1016/j.sleh.2023.07.018

Abstract

Objectives: The majority of the previous research has focused on the impact of average sleep parameters on longevity. In this study, we aimed to investigate the associations of day-to-day deviations in sleep parameters with biological ages among 6052 adults participating in the 2011-2014 waves of the US National Health and Nutrition Examination Survey.

Methods: Sleep parameters, including sleep duration, efficiency, midpoint, and day-to-day deviations in sleep parameters, including standard deviation of sleep duration (sleep variability), standard deviation of sleep midpoint (sleep irregularity), catch-up sleep, and social jetlag, were obtained from 4 to 7 days of 24-h accelerometer recording. We used physiological data to compute measurements of biological aging according to 3 published algorithms: PhenoAge, Klemera-Doubal method Biological Age, and homeostatic dysregulation.

Results: After adjustment of multiple covariates, we observed that all parameters of day-to-day deviations in sleep were significantly associated with biological aging with larger sleep variability, larger sleep irregularity, more catch-up sleep, and more social jetlag linked with more advanced biological aging. The significant associations of sleep irregularity, catch-up sleep, and social jetlag with biological aging indices remained even after adjustment for sleep duration, efficiency, and midpoint.

Conclusion: In this study, we found that day-to-day deviations in sleep parameters are independently associated with biological aging in US general population. Since day-to-day deviation in sleep is a modifiable behavioral factor, our finding suggests that intervention aiming at increasing regularity in sleep patterns may be a novel approach for extending a healthy life span.

Keywords: Biological aging; Circadian rhythm; NHANES; Sleep variability.

MeSH terms

Adult
Aging
Circadian Rhythm* / physiology
Humans
Jet Lag Syndrome
Nutrition Surveys
Sleep* / physiology

Abstract

MeSH terms

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