The association between inadequate sleep and type 2 diabetes has garnered much attention, but little is known about sleep and type 1 diabetes (T1D). Our objectives were to conduct a systematic review and meta-analysis comparing sleep in persons with and without T1D, and to explore relationships between sleep and glycemic control in T1D. Studies were identified from Medline and Scopus. Studies reporting measures of sleep in T1D patients and controls, and/or associations between sleep and glycemic control, were selected. A total of 22 studies were eligible for the meta-analysis. Children with T1D had shorter sleep duration (mean difference [MD] = -26.4 minutes; 95% confidence interval [CI] = -35.4, -17.7) than controls. Adults with T1D reported poorer sleep quality (MD in standardized sleep quality score = 0.51; 95% CI = 0.33, 0.70), with higher scores reflecting worse sleep quality) than controls, but there was no difference in self-reported sleep duration. Adults with TID who reported sleeping >6 hours had lower hemoglobin A1c (HbA1c) levels than those sleeping ≤6 hours (MD = -0.24%; 95% CI = -0.47, -0.02), and participants reporting good sleep quality had lower HbA1c than those with poor sleep quality (MD = -0.19%; 95% CI = -0.30, -0.08). The estimated prevalence of obstructive sleep apnea (OSA) in adults with TID was 51.9% (95% CI = 31.2, 72.6). Patients with moderate-to-severe OSA had a trend toward higher HbA1c (MD = 0.39%, 95% CI = -0.08, 0.87). T1D was associated with poorer sleep and high prevalence of OSA. Poor sleep quality, shorter sleep duration, and OSA were associated with suboptimal glycemic control in T1D patients.

Background. Data in the literature has shown poor sleep quality to be frequently observed in hospitalized patients and known to be associated with poor treatment outcome. Many factors may impact poor sleep quality, and there is currently limited available data. We aim to determine the prevalence of poor sleep quality and associated factors in patients admitted to internal medicine wards as well as the change of sleep quality over time after admission. Methods. An analytic observational study was conducted at the internal medicine wards at the King Chulalongkorn Memorial Hospital, Bangkok, Thailand. Patients were personally interviewed to evaluate the history of sleep quality at home, sleep quality after the first and the third days of admission, and potential associated factors. The Pittsburgh Sleep Quality Index and screening questionnaires for the common diseases associated with poor sleep quality were also utilized. The logistic regression analysis was used to determine the independent factors which led to poor sleep quality. Results. Data were collected from 96 patients during the period of June 2015 to February 2016. The mean age of the patients was 50.8±16.7 years, and 51% were male. Infectious disease was the most common principal diagnosis accounted for 29.2%. The results show high prevalence of poor sleep quality after the first night of admission compared to baseline sleep quality at home (50% vs. 18.8%; p<0.001). After 3 days of admission, the prevalence of poor sleep quality was reduced to the level close to baseline sleep quality at home (28.1% vs. 18.8%; p=0.13). Multivariate analysis demonstrated that light exposure and pain were the main independent factors for poor sleep quality on the first day (odds ratio 6.68; 95% CI 2.25-19.84) and on the third day (odds ratio 3.47; 95% CI 1.24-9.71), respectively. Conclusions. This is the first study conducted on the sleep quality of hospitalized patients that included the follow-up period during hospital admission. Our study demonstrated high prevalence of poor sleep quality in hospitalized patients on the first day. Interestingly, the sleep quality was partly improved during hospitalization. Light exposure and pain were demonstrated to be the factors associated with poor sleep quality.

Epidemiological associations have demonstrated the effects of long-term air pollution to obstructive sleep apnea (OSA) through a physiological mechanism linking particulate matter exposure to OSA. This study aimed to determine the relationship between bedroom environmental conditions, OSA severity, and sleep quality. Sixty-three participants were enrolled for an overnight polysomnography; OSA was diagnosed between May to August 2016. Personal characteristics and sleep quality were obtained by a face-to-face interview. Bedroom environments, including data on particulate matter with an aerodynamic diameter less than 10 μm (PM₁₀), temperature, and relative humidity, were collected by personal air sampling and a HOBO tempt/RH data logger. Sixty-eight percent of the participants experienced poor sleep. An elevation in 1-year mean PM₁₀ concentration was significantly associated with an increase in apnea-hypopnea index (beta = 1.04, P = .021) and respiratory disturbance index (beta = 1.07, P = .013). An increase of bedroom temperature during sleep was significantly associated with poorer sleep quality (adjusted odds ratio 1.46, 95% confidence interval 1.01-2.10, P = .044). Associations between PM₁₀ concentration and respiratory disturbance index were observed in the dry season (beta = 0.59, P = .040) but not in the wet season (beta = 0.39, P = .215). PM₁₀ was not associated with subjective sleep quality. Elevation of PM₁₀ concentration is significantly associated with increased OSA severity. Our findings suggest that reduction in exposure to particulate matter and suitable bedroom environments may lessen the severity of OSA and promote good sleep.

Unlike Caucasians, many Asians with obstructive sleep apnea (OSA) are non-obese but are affected by the disease due to predisposing craniofacial structure. Therefore, non-obese and obese OSA may represent different disease entities. The associated risk factors for developing cardiovascular-related diseases, consequently, may be considered separately for the two types of OSA. We reviewed polysomnographic studies performed in adults (aged ≥ 18 years) diagnosed with OSA (respiratory disturbance index [RDI] ≥ 5). We divided the patients into obese (body mass index [BMI] ≥ 25) and non-obese (BMI < 25) groups. We aimed to determine the differences between these two groups in terms of clinical presentations, polysomno-graphic findings, and association with cardiovascular-related diseases including hypertension, diabetes mellitus, coronary artery disease, and/or cerebrovascular disease. Among 194 patients with OSA (RDI ≥ 5), 63.4% were non-obese and 36.6% were obese. Compared with obese OSA patients, non-obese OSA patients were noted to have smaller neck size, less prevalence of hypertension, and less history of frequent nocturia (> 3-4/week), with equal prevalence of excessive daytime sleepiness. Overall, non-obese OSA patients were noted to have milder disease indicated by lower total, supine, and non-supine, NREM RDI and higher mean and nadir oxygen saturations. In the non-obese group, only total obstructive apnea index (OAI) was noted to be a predictor for developing any of the cardiovascular-related diseases after controlling for age, sex, and RDI (odds ratio = 9.7). However, in the obese OSA group, frequent snoring (> 50% of total sleep time), low sleep efficiency (≤ 90%), and low mean oxygen saturation (< 95%) were noted to be significant predictors of cardiovascular-related diseases (odds ratios = 12.3, 4.2, and 5.2, respectively). Among Asians, most OSA patients were not obese. Compared to obese OSA patients, non-obese OSA patients were noted to have less prevalence of hypertension and less history of nocturia. They were also noted to have overall milder OSA. Only OAI was noted to be a significant predictor for cardiovascular-related disease in the non-obese OSA group.