Effects of Habitual Sleep on Glucose Regulation in Individuals at Risk for Type 2 Diabetes. (29th May 2020)

• Record Type: Journal Article
• Authors: Park, Heyjun; Metwally, Ahmed; Perelman, Dalia; Celli, Alessandra; Kirkpatrick, Susan; McLaughlin, Tracey; Snyder, Michael
• Is Part Of: Current developments in nutrition. Volume 4(2020)Supplement 2
• Page Start: 60
• Page End: 60
• Publication Date: 2020-05-29
• Subjects: Nutrition -- Periodicals; Nutritional Physiological Phenomena; Nutrition; Periodicals; Periodicals; Fulltext; Internet Resources; Periodicals; 612.3
• DOI: 10.1093/cdn/nzaa040_060
• Languages: English
• ISSNs: 2475-2991

Abstract

Abstract: Objectives: This study sought to advance understanding of the impact of habitual sleep patterns on glucose regulation in individuals at risk for type 2 diabetes (T2D). Methods: To achieve this aim, we examined associations between a comprehensive panel of sleep parameters and glucose metabolism marker among people with prediabetes ( n = 19, age = 60.0 y, male = 47.4%) using wearable technology. Briefly, participants underwent fasting plasma glucose (FPG) test and wore Fitbit Ionic band to assess their habitual sleep patterns. Sleep parameters were obtained for a median of 50 days per each participant such as total sleep duration, duration of each sleep stage per night, bed-time, wake-time, etc. To examine associations of sleep parameters with blood glucose levels, a least absolute shrinkage and selection operator (LASSO) regression was used to identify sleep parameters that predict FPG levels with the enhanced prediction accuracy. Mixed effects regression was also performed. Results: In LASSO regression of FPG levels, wake-time (β = −0.013) and percentage of the rapid eye movement (REM) sleep duration out of the total sleep duration (REM%; β = −0.231) were found to inversely predict FPG levels among participants. Mixed effects regression model also showed that REM% is inversely associated with FPG levels (R 2 = 0.61; β = −1.57, P = 0.058) after adjusting other covariates. In sum, people with prediabetes who have earlier wake-time and shorter REM proportion have shown higher FPG levels. Conclusions: Overall, these findings suggest that habitual sleep patterns may influence physiologic defect underlying dysglycemia and progression to T2D in individuals with prediabetes. Funding Sources: Precision Health and Integrated Diagnostic (PHIND) Center at Stanford University.