Literature DB >> 35509113

Associations of chronotype and sleep patterns with metabolic syndrome in the Hispanic community health study/study of Latinos.

Maryam Maghsoudipour1, Matthew A Allison2, Sanjay R Patel3, Gregory A Talavera4, Martha Daviglus5, Phyllis C Zee6, Kathryn J Reid6, Nour Makarem7, Atul Malhotra1.   

Abstract

Sleep duration, sleep efficiency, and sleep timing have been shown to have potential effects on metabolic functions relevant to circadian rhythms. It is not clear if the impact of sleep patterns on metabolic risk factors is through sociocultural and environmental factors or circadian misalignment. We investigated the associations of sleep patterns, chronotype, and social jet lag with metabolic syndrome among non-shift worker Hispanic/Latino adults. We used cross-sectional data from the Sueño Ancillary Study of The Hispanic Community Health Study/Study of Latinos (HCHS/SOL). Data from a subsample of 2189 participants aged 18-64 years were used in the analysis. Mean nightly sleep duration, mean sleep onset time, mean sleep offset time, mean sleep midpoint time, sleep efficiency, sleep variability (standard deviation (SD) of sleep duration, and SD of sleep midpoint), and time spent above light exposure threshold (1000 lux) in a day were assessed by wrist actigraphy (Acti-watch Spectrum). Chronotype was determined by the reduced Morningness-Eveningness Questionnaire. Medical conditions including dyslipidemia, hypertension, and diabetes mellitus were determined from a fasting blood specimen and physical exam at the baseline visit. To determine whether sleep patterns, light levels, chronotype, and social jetlag are associated with metabolic syndrome, multivariable logistic regression models were fitted, including variables with P < .15 in the univariate analysis. The results of the multivariable analysis demonstrated that in participants older than 40 years, intermediate chronotype (vs early) was significantly associated with a higher risk of metabolic syndrome (Odds ratio (95%CI): 1.33 (1.04,1.7)), while later chronotype (vs. early) in participants younger than 40 years was significantly associated with a lower risk of metabolic syndrome (Odds ratio (95%CI): 0.37 (0.14, 0.96)). Also, higher sleep efficiency was significantly associated with decreased odds of metabolic syndrome (Odds ratio (95%CI): 0.98 (0.96, 0.99)). Nightly sleep duration was not significantly different between two groups of participants with and without metabolic syndrome in multivariable analyses. There was no significant association between social jet lag and metabolic syndrome in multivariable analysis (p = .286). Moreover, there was no significant association between chronotype and social jet lag in multivariable analysis. The association between metabolic syndrome and chronotype is age-dependent. While early chronotype is associated with metabolic syndrome in younger individuals, it tended to be associated with lower odds for metabolic syndrome in older individuals.

Entities:  

Keywords:  Sleep patterns; chronotype; circadian misalignment; metabolic syndrome

Mesh:

Year:  2022        PMID: 35509113      PMCID: PMC9177706          DOI: 10.1080/07420528.2022.2069030

Source DB:  PubMed          Journal:  Chronobiol Int        ISSN: 0742-0528            Impact factor:   3.749


  50 in total

1.  Measuring sleep: accuracy, sensitivity, and specificity of wrist actigraphy compared to polysomnography.

Authors:  Miguel Marino; Yi Li; Michael N Rueschman; J W Winkelman; J M Ellenbogen; J M Solet; Hilary Dulin; Lisa F Berkman; Orfeu M Buxton
Journal:  Sleep       Date:  2013-11-01       Impact factor: 5.849

Review 2.  Circadian rhythms, sleep, and metabolism.

Authors:  Wenyu Huang; Kathryn Moynihan Ramsey; Biliana Marcheva; Joseph Bass
Journal:  J Clin Invest       Date:  2011-06-01       Impact factor: 14.808

3.  Sample design and cohort selection in the Hispanic Community Health Study/Study of Latinos.

Authors:  Lisa M Lavange; William D Kalsbeek; Paul D Sorlie; Larissa M Avilés-Santa; Robert C Kaplan; Janice Barnhart; Kiang Liu; Aida Giachello; David J Lee; John Ryan; Michael H Criqui; John P Elder
Journal:  Ann Epidemiol       Date:  2010-08       Impact factor: 3.797

4.  Associations between Obstructive Sleep Apnea, Sleep Duration, and Abnormal Fasting Glucose. The Multi-Ethnic Study of Atherosclerosis.

Authors:  Jessie P Bakker; Jia Weng; Rui Wang; Susan Redline; Naresh M Punjabi; Sanjay R Patel
Journal:  Am J Respir Crit Care Med       Date:  2015-09-15       Impact factor: 21.405

5.  Recruitment of healthy adults into a study of overnight sleep monitoring in the home: experience of the Sleep Heart Health Study.

Authors:  Bonnie K Lind; James L Goodwin; Joel G Hill; Tauqeer Ali; Susan Redline; Stuart F Quan
Journal:  Sleep Breath       Date:  2003-03       Impact factor: 2.816

6.  Seventh report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure.

Authors:  Aram V Chobanian; George L Bakris; Henry R Black; William C Cushman; Lee A Green; Joseph L Izzo; Daniel W Jones; Barry J Materson; Suzanne Oparil; Jackson T Wright; Edward J Roccella
Journal:  Hypertension       Date:  2003-12-01       Impact factor: 10.190

7.  Social jetlag, obesity and metabolic disorder: investigation in a cohort study.

Authors:  M J Parsons; T E Moffitt; A M Gregory; S Goldman-Mellor; P M Nolan; R Poulton; A Caspi
Journal:  Int J Obes (Lond)       Date:  2014-12-22       Impact factor: 5.095

8.  Association of Evening Chronotype with Poor Control of Type 2 Diabetes: Roles of Sleep Duration and Insomnia Level.

Authors:  Sima Hashemipour; Zohreh Yazdi; Niloofar Mahabad
Journal:  Int J Endocrinol Metab       Date:  2020-08-30

9.  Diagnosis and classification of diabetes mellitus.

Authors: 
Journal:  Diabetes Care       Date:  2010-01       Impact factor: 19.112

10.  Assessing Chronotypes by Ambulatory Circadian Monitoring.

Authors:  Antonio Martinez-Nicolas; Maria Jose Martinez-Madrid; Pedro Francisco Almaida-Pagan; Maria-Angeles Bonmati-Carrion; Juan Antonio Madrid; Maria Angeles Rol
Journal:  Front Physiol       Date:  2019-11-20       Impact factor: 4.566

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