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OBJECTIVES: Previous studies conducted in mostly homogeneous sociodemographic samples have reported a relationship between weakened and/or disrupted rest-activity patterns and metabolic dysfunction. This study aims to examine rest-activity rhythm characteristics in relation to glycemic markers in a large nationally representative and diverse sample of American adults.

METHODS: This study used data from the National Health and Nutrition Examination Survey 2011-2014. Rest-activity characteristics were derived from extended cosine models using 24-hour actigraphy. We used multinomial logistic regression and multiple linear regression models to assess the associations with multiple glycemic markers (i.e., glycated hemoglobin, fasting glucose and insulin, homeostatic model assessment of insulin resistance, and results from the oral glucose tolerance test), and compared the results across different categories of age, gender, race/ethnicity, and body mass index.

RESULTS: We found that compared to those in the highest quintile of F statistic, a model-fitness measure with higher values indicating a stronger cosine-like pattern of daily activity, participants in the lowest quintile (i.e, those with the weakest rhythmicity) were 2.37 times more likely to be diabetic (OR Q1 vs. Q5 2.37 (95% CI 1.72, 3.26), p-trend < .0001). Similar patterns were observed for other rest-activity characteristics, including lower amplitude (2.44 (1.60, 3.72)), mesor (1.39 (1.01, 1.91)), and amplitude:mesor ratio (2.09 (1.46, 2.99)), and delayed acrophase (1.46 (1.07, 2.00)). Results were consistent for multiple glycemic biomarkers, and across different sociodemographic and BMI groups.

CONCLUSIONS: Our findings support an association between weakened and/or disrupted rest-activity rhythms and impaired glycemic control among a diverse US population.


Actigraphy, Adult, Biomarkers, Blood Glucose, Circadian Rhythm, Humans, Nutrition Surveys, Rest



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