Background and Purpose Obesity is known of one of the risk factors for obstructive sleep apnea (OSA). Although body mass index (BMI) can be an indicator for obesity, it does not represent the actual body composition of fat or muscle. We hypothesized that bioelectrical impedance analysis (BIA) can help analyze the fat and muscle distributions in males and females with OSA. Methods This study screened subjects who visited the Department of Neurology, Samsung Medical Center, Seoul, Korea due to sleep disturbances with symptoms suggestive of OSA from December 2017 to December 2019. All subjects underwent overnight type I polysomnography (PSG) and BIA. Results PSG and BIA were completed in 2,064 OSA patients who had an apnea-hypopnea index (AHI) of ≥5/hour (77.1% males and 22.9% females). The females had remarkably higher fat indicators and lower muscle indicators. The AHI was significant correlated with all BIA parameters in all OSA patients: body fat mass (ρ=0.286, p <0.001), percentage body fat (ρ=0.130, p <0.001), visceral fat area (VFA) (ρ=0.257, p <0.001), muscle mass (ρ=0.275, p <0.001), and skeletal muscle mass (SMM) (ρ=0.270, p <0.001). The correlations in males were similar to those in all patients, where those in females were not. In females with OSA, all of the BIA fat indicators were correlated with AHI, whereas the muscle indicators were not. Adjusting age and BMI when analyzing the SMM/VFA ratio showed a strong correlation in males with OSA ( p =0.015) but not in females with OSA ( p =0.354). Conclusions This study has revealed that the body composition of fat and muscle has different patterns in OSA patients. The SMM/VFA as measured using BIA is the factor most significantly associated with AHI in males but not in females after adjusting for age and BMI.

Objectives Many patients with obstructive sleep apnea syndrome (OSAS) have nocturia. However, the predictive index of nocturia in patients with OSAS is currently not well known. We aimed to investigate the prevalence of nocturia in patients with OSAS and determine the factors that could predict nocturia in these patients. Methods In this retrospective cross-sectional study, we enrolled 1,264 untreated patients with OSAS (Apnea-Hypopnea Index, AHI ≥5/h on polysomnography [PSG]) from January 2017 to January 2020. Participants completed the Beck Depression Inventory-II (BDI-II), Pittsburgh Sleep Quality Index (PSQI), Insomnia Severity Index (ISI), and Epworth Sleepiness Scale. Participants were divided by sex and then subdivided into nocturia and non-nocturia groups according to the following question, “Do you go to the bathroom two times or more during your sleep?” Participants’ characteristics and underlying disease were investigated, and all information, including PSG data, was compared between the two groups using the t-test or chi-square test. Results Overall, 35.2% (337/958) of male participants with OSAS and 59.8% (183/306) of female participants with OSAS had nocturia. The nocturia group was older; scored higher on the BDI-II, PSQI, and ISI; and had more underlying disease in both sexes. There was no difference in the AHI between the two groups among both sexes, but the hypoxia-related PSG parameters and sleep quality parameters, such as higher 90% oxygen desaturation index (90% ODI), lesser N3 sleep, and higher wakefulness after sleep onset, were worse among male participants with OSAS in the nocturia group than in the non-nocturia group. In multivariate logistic analysis, 90% ODI was an independent risk factor associated with nocturia in male participants with OSAS. Conclusions Considerable number of patients with OSAS had nocturia and poor sleep quality. Nocturia should be evaluated in male OSAS patients with severe hypoxia observed during sleep.

Objectives: Insomnia is a disorder that involves poor sleep quality at nighttime and various symptoms in the daytime. Although it is known to increase cardiovascular risk as well as psychiatric comorbidities such as depression and anxiety, less attention has been paid to daytime sleepiness in patients with insomnia. This study aimed to investigate clinical and polysomnographic characteristics and identify factors influencing excessive daytime sleepiness in patients with insomnia.Methods: Between 2014 and 2022, 1,241 patients with insomnia as the primary symptom who underwent polysomnography were included in the study. Patients with an Epworth sleepiness scale ≥10 were classified as having insomnia accompanied by daytime sleepiness, and sleep-related questionnaire responses and polysomnography findings were utilized for analysis.Results: A total of 327 patients (26.3%) had daytime sleepiness, and a higher prevalence was observed in younger and male individuals. Poor sleep quality, severe depression, and insomnia were identified through the questionnaire. Polysomnography showed longer total sleep times, a higher proportion of stage N3 sleep, and higher sleep efficiency. The variables related to the Epworth sleepiness scale identified in multiple regression analysis were age, the Korean Beck Depression Inventory-II, sleep latency, and the apnea-hypopnea index on polysomnography.Conclusions: Insomnia with excessive daytime sleepiness was more affected by depression than indicated by polysomnography findings. The pathophysiology is presumed to be related to sleep misperception, and further studies are needed to elucidate the discrepancy between excessive daytime sleepiness and polysomnography findings.