71 Sleep Quality and Measures of Attention and Learning in Middle-Aged Adults

Objective:Sleep has been shown to directly impact cognitive function throughout the lifespan; good quality sleep benefits and improves cognitive function, including processing speed and attention, while poor quality sleep can contribute to negative cognitive outcomes1. In particular, attention, learning, and memory have been demonstrated to be sensitive to sleeping changes, including fragmentation and restriction2. Subjective sleeping scales are utilized in both research and clinical practice, allowing sleep to be measured via self-report on various domains, including duration and factors that can contribute to sleep disruption and disturbances3. This study aims to examine the possible relation between subjective sleep quality and cognitive function among middle-aged adults to inform future research for early interventions of modifiable behaviors that can contribute to abnormal cognitive decline.Participants and Methods:Data for this analysis is part of the preliminary results of an ongoing pilot study. 29 middle-aged (40-65 years, inclusive), cognitively unimpaired individuals were recruited from the community. Subjective sleep quality was measured with the Pittsburgh Sleep Quality Index (PSQI). Attention and memory were measured using the California Verbal Learning Test, Third Edition (CVLT-III).Results:Multiple hierarchical regression analyses were conducted to evaluate if aspects of sleep quality were significantly correlated to complex attention and learning performance in this sample. First, correlation amylases showed significant relationships between PSQI Component 6 (Use of Sleeping Medication) and Trials 1 to 2 Learning Slope (R2 = -0.56, p =0.002) and CVLT-III Trials 1 through 5 Recall Discriminability (R2 = -0.42, p = 0.02), each with significant regression analyses outcomes (b =0.42, p = 0.04 and b = -0.46, p = 0.04, respectively). There were other variables that were found to be significantly correlated; however, after adjusting for relevant demographic variables (age, education, sex), the hierarchical regression analyses revealed no association between the aforementioned variables.Conclusions:While multiple aspects of sleep quality were expected to influence measures of attention and learning, only PSQI Component 6 was found to be statistically significantly associated with only two learning variables. Limitations of this study included a small sample size which was limited to cognitive and relatively physically healthy middle-aged adults. Further, sleep quality was measured with one subjective measure and no objective data was collected to support the hypotheses. Future analysis is needed to continue to explore the relation between subjective sleep quality and cognitive outcomes. As this is an ongoing study, we look forward to exploring this research question in more detail as the study progresses.