Rest-Activity Rhythms Are Associated With Prevalent Cardiovascular Disease, Hypertension, Obesity, and Central Adiposity in a Nationally Representative Sample of US Adults

一项具有全国代表性的美国成年人样本研究表明,昼夜节律与心血管疾病、高血压、肥胖和中心性肥胖的患病率相关。

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Abstract

BACKGROUND: Rest-activity rhythms (RARs), a measure of circadian rhythmicity in the free-living setting, are related to mortality risk, but evidence is limited on associations with cardiovascular disease (CVD) and its risk factors. METHODS AND RESULTS: Participants included 4521 adults from the 2013 to 2014 National Health and Nutrition Examination Survey physical activity monitoring examination. Wrist-worn ActiGraph GT3X+ data were used to estimate RARs. Multivariable logistic models evaluated associations of RARs with prevalent CVD, hypertension, obesity, and central adiposity. Participants (mean age, 49 years) in the highest versus lowest tertile of relative amplitude (greater circadian rhythmicity) had 39% to 62% lower odds of prevalent CVD, hypertension, obesity, and central adiposity. A more active wake period was associated with 19% to 72% lower CVD, hypertension, obesity, and central adiposity odds. Higher interdaily stability (regular sleep-wake and rest-activity patterns) was related to 52% and 23% lower CVD and obesity odds, respectively. In contrast, participants in the highest versus lowest tertile of intradaily variability (fragmented RAR and inefficient sleep) had >3-fold and 24% higher CVD and obesity odds, respectively. A later and less restful sleep period was associated with 36% to 2-fold higher CVD, hypertension, obesity, and central adiposity odds. A statistically significant linear trend was observed for all associations (P-trend<0.05). CONCLUSIONS: A robust, stable, and less fragmented RAR, an active wake period, and an earlier and more restful sleep period are associated with lower prevalent CVD, hypertension, obesity, and central adiposity, with evidence of a dose-response relationship. The magnitude, timing, and regularity of sleep-wake and rest-activity patterns may be important targets for reducing cardiovascular risk.

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