Associations Between Sleep Quality and Continuous Glucose Monitoring‐Derived Metrics in Individuals With Type 2 Diabetes

Sleep is a critical component of cardiometabolic health, yet individuals with Type 2 diabetes (T2D) experience disproportionately poor sleep quality. While extensive research links sleep duration and quality with HbA1c, less is known about the relationship between sleep and continuous glucose monitoring (CGM)-derived metrics, which capture short-term glycemic variability (GV) and time in range (TIR). Growing evidence suggests that CGM-derived metrics, particularly GV and TIR, are strongly associated with diabetes-related complications and all-cause mortality, underscoring their clinical importance. We conducted a study to examine associations between self-reported sleep quality and CGM-derived metrics among 137 adults with T2D. Participants completed the Pittsburgh Sleep Quality Index (PSQI) and wore blinded CGM devices for 14 days. CGM-derived metrics included intraday- and interday-GV (coefficient of variation, J-index, high/low blood glucose indices, mean of daily differences [MODD]), TIR, time above range (TAR) and time below range (TBR). Multivariable linear regression adjusted for age, sex, body mass index, diabetes duration, depressive symptoms and race/ethnicity. Overall, 69% of participants reported poor sleep. Poor sleep quality was independently associated with higher TAR (daytime β = 0.18, p = 0.04; nighttime β = 0.13, p = 0.04), lower TIR (daytime β = -0.09, p = 0.04; nighttime β = -0.05, p = 0.04) and greater day-to-day GV (β = 0.22, p = 0.03) and higher hyperglycemia risk (β = 0.23, p = 0.04). These findings suggest that poor sleep quality in T2D is linked to increased hyperglycemia exposure, reduced TIR and unstable day-to-day GV, independent of clinical factors. Addressing sleep as a modifiable lifestyle factor and integrating sleep assessments with CGM may provide actionable insights to guide personalised diabetes management.