Objectives:
To identify the sleep duration associated with the lowest cardiometabolic risk score in adults and to determine if the association varies by subgroups (eg, sex, age groups, ethnicity, and smoking status).
Design:
Cross-sectional data from the 2005-2012 National Health and Nutrition Examination Survey.
Setting:
Non-institutionalized civil sample from the United States.
Participants:
Age ≥20 y (N=8827) with sleep and cardiometabolic health data.
Interventions:
N/A.
Measurements:
Sleep duration from the Sleep Disorders Questionnaire was categorized as ≤3, 4, 5, 6, 7, 8, 9, and ≥10 h per night. HDL cholesterol (HDL) and waist circumference (WC) were stratified by sex first, while fasting insulin, fasting plasma glucose (Glu), triglycerides (TG), body max index (BMI), systolic blood pressure (SBP) and diastolic blood pressure (DBP) were standardized without stratifications. The standardized scores were summed for each participant using the following formula: -zHDL + zInsulin + zGlu + zTG + (zBMI + zWC)/2+(zSBP + zDBP)/2.
Results:
Seven hours of sleep was associated with the lowest cardiometabolic risk score (-0.30 (95% CI: -0.43, -0.18)), which remained similar after adjusting for age, sex, ethnicity, education, family income, alcohol intake and smoking status. However, 8 hours of sleep was associated with the lowest score in non-Hispanic Blacks.
Conclusions:
This study supports recent sleep duration recommendations in adults, and provides evidence that in general 7 hours of sleep per night is associated with optimal cardiometabolic health of adults. Longitudinal studies using objective measures of sleep would help further clarify this association.
Citing Articles
Sleep onset time as a mediator in the association between screen exposure and aging: a cross-sectional study.
Lin S, Gao M, Zhang J, Wu Y, Yu T, Peng Y
Geroscience. 2024; 47(1):1239-1249.
PMID: 39190220
PMC: 11872958.
DOI: 10.1007/s11357-024-01321-x.
Clustering of health behaviors and their associations with cardiometabolic risk factors among adults at high risk for type 2 diabetes in India: A latent class analysis.
de Mello G, Thirunavukkarasu S, Jeemon P, Thankappan K, Oldenburg B, Cao Y
J Diabetes. 2024; 16(5):e13550.
PMID: 38708436
PMC: 11070839.
DOI: 10.1111/1753-0407.13550.
Objective sleep and cardiometabolic biomarkers: results from the community of mine study.
Zamora S, Full K, Ambeba E, Savin K, Crist K, Natarajan L
Sleep Adv. 2023; 4(1):zpad052.
PMID: 38107604
PMC: 10721447.
DOI: 10.1093/sleepadvances/zpad052.
Interplay of sleep patterns and oxidative balance score on total cardiovascular disease risk: Insights from the National Health and Nutrition Examination Survey 2005-2018.
Chen X, Wang C, Dong Z, Luo H, Ye C, Li L
J Glob Health. 2023; 13:04170.
PMID: 38085249
PMC: 10715456.
DOI: 10.7189/jogh.13.04170.
An mHealth-Supported antenatal lifestyle intervention may be associated with improved maternal sleep in pregnancy: Secondary analysis from the PEARS trial.
Bartels H, Kennelly M, Killeen S, Lindsay K, Crowley R, McAuliffe F
BJOG. 2022; 129(13):2195-2202.
PMID: 35876246
DOI: 10.1111/1471-0528.17267.
The Associations Between Objectively Measured Gait Speed and Subjective Sleep Quality in First-Year University Students, According to Gender.
Kasovic M, Stefan A, Stefan L
Nat Sci Sleep. 2021; 13:1663-1668.
PMID: 34594142
PMC: 8478338.
DOI: 10.2147/NSS.S328218.
How do associations between sleep duration and metabolic health differ with age in the UK general population?.
Arora A, Pell D, van Sluijs E, Winpenny E
PLoS One. 2020; 15(11):e0242852.
PMID: 33227026
PMC: 7682906.
DOI: 10.1371/journal.pone.0242852.
Associations between self-reported sleep duration and cardiometabolic risk factors in young African-origin adults from the five-country modeling the epidemiologic transition study (METS).
Rae D, Ruth Dugas L, Roden L, Lambert E, Bovet P, Plange-Rhule J
Sleep Health. 2020; 6(4):469-477.
PMID: 32321687
PMC: 7529682.
DOI: 10.1016/j.sleh.2020.03.003.
Gait can reveal sleep quality with machine learning models.
Liu X, Sun B, Zhang Z, Wang Y, Tang H, Zhu T
PLoS One. 2019; 14(9):e0223012.
PMID: 31553783
PMC: 6760789.
DOI: 10.1371/journal.pone.0223012.
Use of Compositional Data Analysis to Show Estimated Changes in Cardiometabolic Health by Reallocating Time to Light-Intensity Physical Activity in Older Adults.
Powell C, Browne L, Carson B, Dowd K, Perry I, Kearney P
Sports Med. 2019; 50(1):205-217.
PMID: 31350674
DOI: 10.1007/s40279-019-01153-2.
Evaluation of Allostatic Load as a Mediator of Sleep and Kidney Outcomes in Black Americans.
Lunyera J, Davenport C, Jackson C, Johnson D, Bhavsar N, Sims M
Kidney Int Rep. 2019; 4(3):425-433.
PMID: 30899870
PMC: 6409364.
DOI: 10.1016/j.ekir.2018.12.005.
Associations between sleep parameters, non-communicable diseases, HIV status and medications in older, rural South Africans.
Gomez-Olive F, Rohr J, Roden L, Rae D, von Schantz M
Sci Rep. 2018; 8(1):17321.
PMID: 30470764
PMC: 6251877.
DOI: 10.1038/s41598-018-35584-0.
Sleep duration and incidence of type 2 diabetes: the Multiethnic Cohort.
Maskarinec G, Jacobs S, Amshoff Y, Setiawan V, Shvetsov Y, Franke A
Sleep Health. 2018; 4(1):27-32.
PMID: 29332675
PMC: 5771414.
DOI: 10.1016/j.sleh.2017.08.008.