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Sleep. 2019 May 13. pii: zsz116. doi: 10.1093/sleep/zsz116. [Epub ahead of print]

Empirical derivation of cut-off values for the sleep health metric and its relationship to cardiometabolic morbidity: Results from the Midlife in the United States (MIDUS) study.

Author information

1
Deparment of Psychiatry, University of Pittsburgh School of Medicine.
2
Department of Psychology and Neuroscience Program, Washington and Lee University.

Abstract

STUDY OBJECTIVES:

Emerging evidence supports a multidimensional perspective of sleep in the context of health. The sleep health model, and composite sleep health score, are increasingly used in research. However, specific cut-off values that differentiate "good" from "poor" sleep, have not been empirically-derived and its relationship to cardiometabolic health is less-well understood. We empirically-derived cut-off values for sleep health dimensions and examined the relationship between sleep health and cardiometabolic morbidity.

METHODS:

Participants from two independent Biomarker Studies in the MIDUS II (N = 432, 39.8% male, age = 56.92±11.45) and MIDUS Refresher (N = 268, 43.7% male, age = 51.68±12.70) cohorts completed a 1-week study where sleep was assessed with daily diaries and wrist actigraphy. Self-reported physician diagnoses, medication use, and blood values were used to calculate total cardiometabolic morbidity. Receiver operating characteristic (ROC) curves were generated in the MIDUS II cohort for each sleep health dimension to determine cut-off values. Using derived cut-off values, logistic regression was used to examine the relationship between sleep health scores and cardiometabolic morbidity in the MIDUS Refresher cohort, controlling for traditional risk factors.

RESULTS:

Empirically-derived sleep health cut-off values aligned reasonably well to cut-off values previously published in the sleep health literature and remained robust across physical and mental health outcomes. Better sleep health was significantly associated with a lower odds of cardiometabolic morbidity [OR(95%CI) =0.901(0.814-0.997), p = .044].

CONCLUSIONS:

These results contribute to the ongoing development of the sleep health model and add to the emerging research supporting a multidimensional perspective of sleep and health.

KEYWORDS:

alertness; diabetes; heart disease; hypertension; sleep duration; sleep efficiency; sleep health; sleep quality; sleep regularity; sleeping timing

PMID:
31083710
DOI:
10.1093/sleep/zsz116

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