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.