PURPOSE To illustrate 2 frameshifts of multidimensional sleep health: i) use of composite sleep metrics; and ii) the correlations among sleep dimensions. PARTICIPANTS 735 adults of diverse backgrounds aged Click to show full abstract
PURPOSE To illustrate 2 frameshifts of multidimensional sleep health: i) use of composite sleep metrics; and ii) the correlations among sleep dimensions. PARTICIPANTS 735 adults of diverse backgrounds aged <65 years who participated in the Multi-Ethnic Study of Atherosclerosis. MEASURES In-home polysomnography, 7-day wrist actigraphy, and validated questionnaires. METHODS The Buysse Ru SATED model-sleep regularity, satisfaction, alertness, timing, efficiency, duration-was operationalized, then extended by including additional measures of sleep architecture and sleep apnea from polysomnography and difficulties initiating sleep from questionnaire and sleep onset latency and duration [ir]regularity from actigraphy. We dichotomized sleep variables, operationalizing optimal and nonoptimal ranges as 1 and 0, respectively, summed into a sleep health score, and computed global sleep health scores via principal components analysis. FINDINGS Participants showed low prevalence of sleep regularity in timing (<30 minutes standard deviation [SD]; 21.4% favorable) and duration (<60 minutes SD; 36.9%). Although 62.7% of participants demonstrated favorable sleep duration by actigraphy, few met criteria for favorable levels of % N3 (11.4%) or %R (34.1%). The average Sleep Health Score was 5.6 of 13 (higher is better). Sleep variables were variably intercorrelated (r = 0 to r = -0.72). The first principal component for each operationalization of sleep health was interpretable as a "health" score; all summary scores captured variable but systematic shifts towards more favorable sleep in each sleep variable. CONCLUSIONS Multidimensional sleep health can be measured by complementary composite scores as well as consideration of multiple individual dimensions.
               
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