Abstract

Introduction: Sleep characteristics have been independently linked to cardiometabolic health, but sleep dimensions do not occur in isolation. Multidimensional sleep health predicts CVD mortality; however, associations with cardiometabolic health have not been evaluated. Hypothesis: Favorable multidimensional sleep health would be related to lower odds for hypertension (HTN), type 2 diabetes (T2D), obesity, and central adiposity. Methods: Participants were 4,559 adults aged ≥20 y from the 2017-18 National Health and Nutrition Examination Survey. A multidimensional sleep health score was computed from self-reported sleep duration, timing/regularity, and latency, snoring habits, and daytime sleepiness (Table); scores of 0-1, 2-3, and 4-5 indicated poor, moderate, and ideal sleep health, respectively. Survey-weighted linear and logistic models examined associations of multidimensional sleep health with blood pressure (BP), fasting glucose, anthropometric measures, and odds of cardiometabolic disease. Results: Ideal vs. poor sleep health was related to 66%, 58%, 73%, and 69% lower odds of HTN, T2D, obesity, and central adiposity, respectively (Table), and a linear trend was detected across the gradients of sleep health. In linear models, those with ideal and moderate vs. poor sleep health had lower BP, fasting glucose, BMI, and waist size. When sleep dimensions were examined separately, never/rare snoring, not having difficulty falling asleep, and never/rare daytime sleepiness were related to up to 46%, 51%, 58%, and 54% lower odds of HTN, T2D, obesity, and central adiposity, respectively (p<0.05). Sufficient sleep duration (7-9 h vs. <7 h or ≥9 h) was related to 29% lower odds for HTN (OR (95%CI): 0.71 (0.56-0.92)). Conclusions: Poor sleep health was associated with prevalent HTN, T2D, obesity, and central adiposity in US adults. Prospective studies are needed to decipher the role of sleep health in lowering CVD risk and extending healthspan.

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