657-P: Association between Sleep and Glycemic Variability in People with Type 2 Diabetes in Real-Life Setting

Objective: Glucose variability (GV) is an important indicator for glycemic control. This study aimed to investigate the association between sleep and GV among people with T2D.

Methods: A correlational design was used. Data were collected during 7 days in real-life setting. Sleep and GV were assessed simultaneously using Actigraphy and CGM. Sleep parameters were derived from Actigraphy using default algorithm. GV was quantified as standard deviation (SD) and coefficient of variation (CV) of glucose, percentage of time in range (TIR), time above range (TAR), time below range (TBR), mean amplitude of glycemic excursion (MAGE) during rest interval at night. Associations were examined using linear mixed-effect models.

Results: Fifty participants (60.1 years, 27 females) were recruited and 295-night data were analyzed. Controlling for covariates, longer wake after sleep onset was associated with higher SD, CV, and MAGE (coefficient=0.003, p=0.023; coefficient=0.001, p=0.002; coefficient=0.009, p=0.006), and lower TIR (coefficient=-0.001, p=0.049). Higher sleep efficiency was associated with lower SD, CV, MAGE, and TAR (coefficient=-1.003, p=0.049; coefficient=-0.174, p=0.005; coefficient=-3.758, p=0.012; coefficient=-0.396, p=0.031), and higher TIR (coefficient=0.437, p=0.020). Higher sleep fragmentation index was associated with higher TAR (coefficient=0.002, p=0.045). Earlier sleep timing (sleep midpoint<4:00 am) compared to late sleep timing, was associated with lower nighttime TAR (coefficient=-0.092, p=0.017). Shorter sleep duration (<8h) compared to longer, was associated with lower SD and MAGE (coefficient=-0.609, p<0.001; coefficient=-1.624, p<0.001).

Conclusions: At the individual level, better sleep is associated with lower GV, supporting the importance of sleep in optimizing glycemic control. Interventional studies are needed to reveal the causal relationship.