Relationships between respiratory and oromotor events differ between motor phenotypes in patients with obstructive sleep apnea.

Purpose: The present study investigated the relationship between sleep bruxism (SB) and obstructive sleep apnea (OSA) in relation to the sleep architecture. Methods: We conducted a cross-sectional study. Polysomnographic recordings were performed on 36 patients. Sleep, respiratory, and oromotor variables, such as rhythmic masticatory muscle activity (RMMA) and non-specific masticatory muscle activity (NSMA), were compared between OSA patients with or without SB. A correlation analysis of the frequency of respiratory and oromotor events in NREM and REM sleep was performed. The frequency of oromotor events following respiratory events was also assessed. Results: The proportion of REM sleep was higher in OSA patients with SB than in those without SB (p = 0.02). The apnea-hypopnea index (AHI) did not significantly differ between the two groups; however, AHI was approximately 8-fold lower during REM sleep in OSA patients with SB (p = 0.01) and the arousal threshold was also lower (p = 0.04). Although the RMMA index was higher in OSA patients with than in those without SB (p < 0.01), the NSMA index did not significantly differ. The percentage of RMMA following respiratory events was significantly higher in OSA patients with than in those without SB, whereas that of NSMA did not significantly differ. The frequency of oromotor events throughout the whole night positively correlated with AHI. However, regardless of the sleep state, AHI did not correlate with the RMMA index, but positively correlated with the NSMA index. Conclusion: In consideration of the limitations of the present study, the results obtained indicate that OSA patients with SB have a unique phenotype of OSA and also emphasize the distinct relationship of respiratory events with RMMA and NSMA.

Increased digital media use is associated with sleep problems among university students: A study during the COVID-19 pandemic in Japan.

This retrospective cohort study investigates the association between the incidence of sleep problems and changes in digital media use among university students during the COVID-19 pandemic. It used data from annual health check-ups performed at a Japanese university in 2019 and 2020. Students undergoing these check-ups were identified to respond to questions about sleep problems, digital media use, breakfast and exercise habits, and stress. In total, 3,869 students were included in the analysis. The association between the incidence of sleep problems in 2020 and the changes in digital media use between 2019 and 2020 was assessed using logistic regression models. The rate of long digital media use (≥ 2 hours) in 2019 was 42.6%, while in 2020 it was 53.6%. Incidence of sleep problems was observed in 244 students (6.3%) in 2020. There were 786 students (20.3%) who used digital media for ≤ 2 h in 2019 and ≥ 2 h in 2020. From the sample, 66 students (8.4%) reported incidence of sleep problems in 2020. Additionally, those respondents who specifically reported increased digital media use between 2019 and 2020 (increased use) where at greater risk (OR: 1.76; 95% CI: 1.21, 2.55) of reporting sleep problems in 2020, even after controlling for other study variables. Thus, this study provides evidence that the incidence of sleep problems has had a significant association with an increase in digital media use among university students throughout the COVID-19 pandemic. These findings highlight the importance of ensuring appropriate digital media use among students for improved quality of sleep.

Association of weekday-to-weekend sleep differences and stress response among a Japanese working population: a cross-sectional study.

OBJECTIVES: To investigate the relationship between differences in weekday-to-weekend sleep habits and stress responses in a working population. METHODS: This cross-sectional study used data from university workers on sleep habits, differences in sleep duration between weekdays and weekends, and each midpoint of the sleep phase on weekdays and weekends. Social jetlag was defined as the difference in the midpoint of the sleep phase between weekdays and weekends. In addition, the Brief Job Stress Questionnaire assessed stress responses and stress-related factors. To examine sleep-related factors affecting stress responses, regression analysis was performed with adjustments for age, sex, and stress-related factors. RESULTS: Analyzed were 2,739 participants. Sleep duration differences obtained by subtracting sleep duration on weekdays from that on weekends, social jetlag, and weekday sleep duration were significantly associated with an increased risk of stress responses in a univariate linear regression model. Adjusting for age, sex, job stressors, and stressor buffering factors did not change this trend. However, when additionally adjusting for all sleep parameters, only sleep duration differences and weekday sleep duration were significantly associated with stress responses (ß 0.67 [95% CI 0.24, 1.10], p = 0.002), (-0.66 [-1.20, -0.13], p = 0.015). CONCLUSIONS: This study provided further evidence that weekday sleep duration and weekday-to-weekend sleep duration differences were independently associated with stress responses even when considering stress-related factors. However, social jetlag was not clearly associated with stress responses. Our findings highlighted the necessity of securing sufficient sleep for stress management and mental health promotion in a working population.