INFLUENCE OF SLEEP ON COGNITIVE PERFORMANCE IN ADULTS WITH TYPE 1 DIABETES: FINDINGS FROM THE GLUCOG STUDY

Miranda S. Zuniga-Kennedy

doi:10.7273/000007203

Objective: Type 1 diabetes (T1D) is a chronic medical condition associated with deficits in cognitive functioning. Sleep is an additional factor that has a significant influence on multiple domains of cognitive functioning. There is evidence that individuals with T1D have an altered sleep architecture and are at higher risk for conditions such as obstructive sleep apnea (OSA). Despite these associations, the unique relationship between sleep and cognitive performance in the context of T1D is not well understood. Methods: The current project aimed to 1) characterize sleep in T1D and 2) examine whether sleep characteristics are related to cognitive performance in adults with T1D. These aims were explored via two studies: Study 1 utilized data from 210 participants from the Glycemic Variability and Fluctuations in Cognitive Status in Adults with Type 1 Diabetes (GluCog) study (M age = 45.64, SD = 15.59, % female =52.86%,) who completed the Pittsburgh Sleep Quality Index (PSQI) assessing sleep quality and the STOP-Bang questionnaire sleep apnea risk. Study 2 utilized data from a subset of this cohort (n = 29; M age = 42.62, SD 14.49, % female = 44.8%), who opted to wear wrist actigraphy throughout the study, allowing for an objective assessment of sleep characteristics. Participants completed self-administered cognitive assessments via a web-based remote cognitive assessment platform, TestMyBrain.org (TMB). Results: Findings demonstrated that participants reported elevated scores on both the PSQI (47.1%), and STOP-Bang (36.7%) compared to the general population. . When controlling for age, participants with T1D (N=29) who wore actigraphy had significantly shorter total sleep time (TST), lower sleep efficiency, and more fragmented sleep (all p’s < .05) compared to a healthy control group extracted from a separate study (Hansen et al., 2021). Bivariate correlations revealed an association between STOP-Bang and 7 out of the 11 cognitive tests, where higher scores were positively associated with slower reaction times, and lower accuracy. The PSQI was not associated with any cognitive test. After demographic correction, the STOP-Bang was not significantly associated with cognitive performance, except for Matrix Reasoning. However, this relationship no longer persisted after accounting for diabetes characteristics. Diabetes characteristics were significantly associated with cognition in final models for Matrix Reasoning, Flicker, and Digit Symbol Matching (DSM). In Study 2, findings revealed that shorter TST, measured via actigraphy, was associated with slower reaction time (r = -.39, p = .04) on a task of processing speed (Flicker).There was a medium effect size association between sleep fragmentation and the Paced Serial Addition Test (PSAT; r = -.33 p = .08), although it did not reach statistical significance. Conclusion: Individuals with T1D experience both subjective and objective sleep disturbances compared to the general population, and further investigation of the mechanisms of disordered sleep in this population is needed to better screen for sleep disturbances and potentially develop targeted clinical interventions. While these sleep problems are important, they do not appear to uniquely contribute to cognitive difficulties at a group level.

INFLUENCE OF SLEEP ON COGNITIVE PERFORMANCE IN ADULTS WITH TYPE 1 DIABETES: FINDINGS FROM THE GLUCOG STUDY

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