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Sleep-disordered breathing (SDB) is common in type 2 diabetes (T2D). This study aimed to develop a screening tool to detect SDB in T2D. Method: SDB was screened in 95 patients by an overnight monitor and diagnosed if apnea-hypopnea index ≥ 5. Anthropometric and HbA1c data, and SDB risk by questionnaire were obtained. Quantitative NMR experiment was performed on a Bruker AVANCE 400 Ascend NMR spectrometer. Carr−Purcell−Meiboom−Gill (CPMG) pulse sequence at 310 K was applied to serum samples to enhance signal-to-noise ratio and hence detect low-molecular weight metabolites. Models based on six machine learning methods (e.g., learned vector quantization, stochastic gradient boosting model, support vector machines, decision tree, partial least squares, generalized linear model, and logistic regression) were constructed to predict SDB, tuned with the CARET R package, and evaluated using three repeats of 10-fold cross validation. Results: Seventy-six patients (80.0%) had SDB. Compared with those without, those with SDB were more likely to be male, have SDB risk, higher BMI and neck circumferences, longer diabetes duration, and higher HbA1c. NMR-based metabolic profiling identified significantly lower levels of branched-chain amino acids (BCAAs) (e.g., L-leucine and L-isoleucine), lactate and threonine metabolites in those with SDB, while level of D-glucose-6 phosphatase was higher than those without SDB. Accuracies for predicting SBD using clinical data alone were ∼80% for each machine learning model. L-leucine and D-glucose-6-phosphatase were identified as being independently associated with SDB using a logistic regression, in addition to clinical factors, with an improved accuracy of 86.3%, and a Cohen’s kappa of 0.429. Conclusions: Due to its high prevalence, clinical factors alone were not sufficient in predicting SDB in T2D. The discovery of metabolic profiles, including BCAAs and those involved in glucose metabolism, could facilitate a more precise and specific SDB prediction. Disclosure K. Lertdetkajorn: None. P. Poungsombat: None. S. Khoomrung: None. J. Phetcharaburanin: None. S. Hongthong: None. C. Kuhakarn: None. N. Siwasaranond: None. A. Manodpitipong: None. H. Ninitphong: Speaker’s Bureau; Self; AstraZeneca, Boehringer Ingelheim Pharmaceuticals, Inc., Merck Sharp & Dohme Corp., Novo Nordisk Inc., Takeda Pharmaceutical Company Limited. S. Saetung: None. B. Ongphiphadhanakul: None. V. Reutrakul: None. S. Reutrakul: None. Funding Endocrine Society of Thailand; Ramathibodi Hospital; Mahidol University; Thailand Center of Excellence for Innovation in Chemistry

Currently it is not known whether morningness-eveningness preference in non-night shift working population is associated with systemic inflammation. This study investigated the relationship between morningness-eveningness and systemic inflammation, as measured by high-sensitivity C-reactive protein (hs-CRP) in 163 non-night shift working patients with abnormal glucose tolerance (86 type 2 diabetes and 77 prediabetes). Morningness-eveningness was assessed by Composite Scale of Morningness, and participants were screened for Obstructive sleep apnea (OSA). Sleep duration, efficiency, and variability were obtained using actigraphy, and depressive symptoms and dietary patterns were also captured. Participants’ mean age was 54.7 ± 10.4 years and median hs-CRP was 1.39 (interquartile range 0.82, 3.33) mg/L. More evening preference was significantly associated with higher natural log transformed (ln) hs-CRP (B = −0.051, p = 0.001). Diabetes status, glycemic control, OSA severity, sleep duration, caloric consumption and timing were not related to hs-CRP. After adjusting for age, sex, body mass index, depressive symptoms, sleep efficiency, sleep variability, percentage of daily caloric intake from protein, and statin use, more evening preference was independently associated with higher ln hs-CRP (B = −0.032, p = 0.014). In summary, in non-night shift working patients with abnormal glucose tolerance, more evening preference was independently associated with higher systemic inflammation. This finding underscore the importance of circadian regulation on cardiovascular health.

Diabetes is linked to cognitive impairment. Sleep plays a role in memory consolidation. Sleep disturbances, commonly found in patients with diabetes, were shown to be related to cognitive dysfunction. This study explored the role of sleep in cognitive function of patients with abnormal glucose tolerance. A total of 162 patients (81 type 2 diabetes and 81 prediabetes) participated. Sleep duration and sleep efficiency (an indicator of sleep quality) were obtained using 7-day actigraphy recordings. Obstructive sleep apnea (OSA) was screened using an overnight in-home monitor. Cognitive function was assessed using the Montreal Cognitive Assessment (MoCA). Three sub-scores of MoCA, visuoexecutive function, attention and delayed recall, were also analyzed. Mean age was 54.8 (10.2) years. OSA was diagnosed in 123 participants (76.9%). Mean sleep duration was 6.0 (1.0) h and sleep efficiency was 82.7 (8.1) %. Sleep duration and OSA severity were not related to MoCA scores. Higher sleep efficiency was associated with higher MoCA scores (p = 0.003), and having diabetes (vs. prediabetes) was associated with lower MoCA scores (p = 0.001). After adjusting covariates, both having diabetes (vs. prediabetes) (B = − 1.137, p = 0.002) and sleep efficiency (B = 0.085, p

Objective: We analyzed two cohorts of people with type 2 diabetes to evaluate the relationships between depression, sleep quality, and history of hypoglycemia. Research design and methods: Two adult cohorts from Chicago (n = 193) and Bangkok, Thailand (n = 282) with type 2 diabetes completed questionnaires to assess sleep quality, depressive symptoms, and hypoglycemia frequency. Proportional odds logistic regression models for each cohort adjusted for duration of therapy, insulin and sulfonylurea management, and other factors. Results: Those with hypoglycemia in both cohorts had a longer duration of diabetes, greater use of insulin, and worse sleep quality. The Chicago cohort used less sulfonylureas but had higher depressive symptom scores. The Thailand cohort had greater sulfonylurea use. In the final Thailand regression model, depressive symptoms were independently associated with hypoglycemia frequency. In both final Chicago and Thailand models, sleep quality was not associated with hypoglycemia frequency. Conclusions: In the Thailand cohort, depressive symptoms were associated with hypoglycemia frequency. Keywords: Diabetes mellitus, Type 2, Hypoglycemia, Depression, Sleep

Eveningness is associated with greater depressive symptoms in the general population. Depression and type 2 diabetes (T2D) commonly coexist. We aimed to explore the association between morningness-eveningness and depressive symptoms in T2D patients in the United States and in Thailand.T2D patients (n = 182) from an endocrinology clinic in Chicago, Illinois, and six hospitals in Thailand (n = 251) were enrolled.Diabetes history was collected. Depressive symptoms were assessed by the Center for Epidemiologic Studies Depression scale (CES-D). The Chicago cohort completed the Morningness-Eveningness Questionnaire (MEQ) and the Thai cohort completed the Composite Scale of Morningness (CSM). Sleep quality was assessed using the Pittsburg Sleep Quality Index (PSQI).The mean (SD) CES-D score was 13.7 (9.1) in Chicago and 11.9 (6.4) in Thailand. In Chicago participants, after adjusting for age, sex, ethnicity, hemoglobin A1c, insulin use, and PSQI score, greater eveningness (lower MEQ scores) was associated with higher CESD scores (B = -0.117, p = 0.048). In Thai participants, after adjusting for age, sex, and PSQI score, eveningness (lower CSM score) was associated with higher CES-D score (B = -0.147, p = 0.016). In both cohorts, however, eveningness was not independently associated with the likelihood of being in the at-risk range for clinical depression (CES-D ≥ 16).Eveningness is independently associated with greater depressive symptoms in T2D in two different ethnic cohorts. The results support the association between individual differences in circadian rhythms and psychological functioning in T2D.

Reduced nocturnal secretion of melatonin, a pineal hormone under circadian control, and obstructive sleep apnea have been both identified as risk factors for the development of type 2 diabetes mellitus. Whether they interact to impact glycemic control in patients with existing type 2 diabetes is not known. Therefore, this study explores the relationships between obstructive sleep apnea, melatonin and glycemic control in type 2 diabetes. As diabetic retinopathy may affect melatonin secretion, we also explore the relationship between retinopathy, melatonin and glycemic control. Fifty-six non-shift workers with type 2 diabetes, who were not using beta-blockers, participated. Most recent hemoglobin A1c (HbA1c) levels and the results of ophthalmologic examinations were obtained from medical records. Obstructive sleep apnea was diagnosed using an ambulatory device. Sleep duration and fragmentation were recorded by 7-day wrist actigraphy. The urinary 6-sulfatoxymelatonin/creatinine ratio, an indicator of nocturnal melatonin secretion, was measured in an overnight urine sample. Mediation analyses were applied to explore whether low nocturnal urinary 6-sulfatoxymelatonin/creatinine ratio could be a causal link between increasing obstructive sleep apnea severity [as measured by an Apnea Hypopnea Index (AHI)] and poorer glycemic control, and between the presence of retinopathy and glycemic control. AHI and HbA1c were log-scale (ln) transformed. Obstructive sleep apnea was found in 76.8%, and 25.5% had diabetic retinopathy. The median (interquartile range) of urinary 6-sulfatoxymelatonin/creatinine ratio was 12.3 (6.0, 20.1) ng/mg. Higher lnHbA1c significantly correlated with lower 6-sulfatoxymelatonin/creatinine ratio (p = 0.04) but was not directly associated with OSA severity. More severe obstructive sleep apnea (lnAHI, p = 0.01), longer diabetes duration (p = 0.02), retinopathy (p = 0.01) and insulin use (p = 0.03) correlated with lower urinary 6-sulfatoxymelatonin/creatinine ratio, while habitual sleep duration and fragmentation did not. A mediation analysis revealed that lnAHI negatively correlated with urinary 6-sulfatoxymelatonin/creatinine ratio (coefficient = -2.413, p = 0.03), and urinary 6-sulfatoxymelatonin/creatinine negatively associated with lnHbA1c (coefficient = -0.005, p = 0.02), after adjusting for covariates. Mediation analysis indicated that the effect of lnAHI on lnHbA1c was indirectly mediated by urinary 6-sulfatoxymelatonin/creatinine ratio (B = 0.013, 95% CI: 0.0006, 0.0505). In addition, having retinopathy was significantly associated with reduced nocturnal urinary 6-sulfatoxymelatonin/creatinine ratio, and an increase in HbA1c by 1.013% of its original value (B = -0.013, 95% CI: -0.038, -0.005). In conclusion, the presence and severity of obstructive sleep apnea as well as the presence of diabetic retinopathy were associated with lower nocturnal melatonin secretion, with an indirect adverse effect on glycemic control. Intervention studies are needed to determine whether melatonin supplementation may be beneficial in type 2 diabetes patients with obstructive sleep apnea.

Aims: Type 2 diabetes mellitus (T2DM) and obstructive sleep apnea (OSA) may adversely affect bone. Gender is a well-established factor influencing bone health. We investigated the impact of OSA on bone mineral density (BMD) and trabecular bone score (TBS) in T2DM. Methods: Eighty-one T2DM patients [33 men and 48 women] participated. OSA was diagnosed using an overnight monitor, with its severity assessed by an apnea hypopnia index (pAHI). The measurements of hypoxia, including the percentage of total sleep time in which oxygen saturation remains below 90% (pT90), the oxygen desaturation index (pODI) and minimum O2 (min O2), were reported. Lumbar spine (L1-4) and femoral neck (FN) BMD were measured using dual-energy X-ray absorptiometry (DXA). TBS was computed from DXA images. Results: Sixty-five patients (80.2%) had OSA. pAHI, pT90, pODI and min O2 were not correlated to L1-4 BMD, FN BMD or TBS in all participants by multiple regression analyses adjusting for age, gender and BMI. However, an interaction between gender and pAHI, and gender and pODI were significantly associated with TBS (b = 0.003, p = 0.034 and b = 0.004, p = 0.046, respectively). We therefore reassessed an association between pAHI or pODI and TBS separately between men and women. After adjusting for age and BMI, more severe OSA (higher pAHI) and higher pODI significantly associated with lower TBS (b = −0.002, p = 0.034 and b = −0.003, p = 0.021, respectively) in men. On the other hand, higher pAHI non-significantly associated with better trabecular microarchitecture as indicated by higher TBS (b = 0.002, p = 0.059) in women. When considered only postmenopausal (n = 33), higher pAHI and higher pODI were significantly associated with higher TBS (b = 0.004, p = 0.003 and b = 0.004, p = 0.008, respectively). Conclusions: In T2DM patients, there is a complex interrelationship among OSA severity, gender and TBS. More severe OSA predicted lower TBS in men, but predicted higher TBS in postmenopausal women. Keywords: Apnea–hypopnea index (AHI), BMD/TBS, Menopausal status, Obstructive sleep apnea, Gender, Type 2 diabetes

Introduction. Most nutritional guidelines for diabetes management emphasize the importance of having individualized goals, away from a one-size-fits-all approach. However, there is a dearth of information on the dietary intakes and nutritional knowledge of Thai patients with type 2 diabetes mellitus (T2DM). This study is aimed at clarifying dietary intakes in relationship to glycemic control and at examining nutritional knowledge among Thai patients with T2DM. Materials and Methods. A cross-sectional study of outpatients with T2DM at Theptarin Hospital and Ramathibodi Hospital (Bangkok, Thailand) was performed to assess dietary intakes by food records. Diabetes nutritional knowledge and dietary self-care behavior was also evaluated. Results. A total of 304 Thai patients with T2DM (female 52.6%, mean age 57.4 ± 10.9 years, body mass index (BMI) 27.3 ± 4.8 kg/m2, and baseline A1C 7.2 ± 1.3%) participated in the study. The mean daily calorie intake was 1427 ± 425 kcal, and mean intake for each macronutrient was acceptable (carbohydrate 52%, protein 17%, and fat 31%). However, the intake of free sugar was much higher (12.1 ± 5.8% of total daily energy intake) and dietary fiber intake (9 grams per day) was much lower than recommended. There were no correlations between dietary intake and glycemic control. A subset of patients (N=213) completed the diabetes nutritional knowledge survey. There was no association between diabetes nutritional knowledge and the actual dietary self-care behavior. Conclusion. These results indicate that compliance of Thai patients with T2DM to dietary recommendations is not completely satisfactory, especially for free sugar and dietary fiber intakes. Addressing the reality of how patients with T2DM eat in their daily lives and their knowledge gaps would enable them to adhere to medical nutrition therapy.

AIMS Obesity is prevalent and related to poor outcomes in Type 2 diabetes. Evening preference and late meal times have been shown to be associated with obesity, but data are lacking in people with Type 2 diabetes. This study examined the relationship among meal timing, morningness-eveningness preference and BMI in Type 2 diabetes, using a mediation analysis. METHODS Some 210 non-shift workers with Type 2 diabetes participated in the study. Morningness-eveningness preference was assessed using a standard questionnaire, the Composite Scale of Morningness (CSM). Meal timing and daily calorie intake were obtained from 1-day food recall. A mediation analysis adjusting for relevant covariables was performed to explore whether morningness-eveningness had a direct effect on BMI, or whether the effect was mediated through the intermediate variable of meal timing. RESULTS Mean BMI was 28.4 ± 4.8 kg/m2 . A higher BMI was associated with greater evening preference (P = 0.019), and non-significantly associated with late breakfast time (P = 0.053). BMI was not associated with other mealtimes or calorie intake. In addition, evening preference was associated with late breakfast time (P

This study explored the relationship between obstructive sleep apnea (OSA) and the presence of any diabetes-related complications in type 2 diabetes and whether this was mediated by hypertension. Secondly, the relationship between OSA severity and estimated glomerular filtration rate (eGFR) was investigated. A total of 131 patients participated. OSA was diagnosed using a home monitor, and severity was measured by apnea-hypopnea index (AHI) and oxygen desaturation index (ODI). OSA was found in 75.6% of the participants, 40.5% with moderate-to-severe degree. Any diabetes-related complications (retinopathy, neuropathy, nephropathy, or coronary artery disease) were present in 55.5%, and 70.2% of the participants had hypertension. Mediation analysis indicated that, compared to those with mild or no OSA, those with moderate-to-severe OSA were 3.05 times more likely to have any diabetes-related complications and that this relationship was mediated by the presence of hypertension. After adjusting for confounders, ODI (B = −0.036,p=0.041), but not AHI, was significantly associated with lower eGFR. In conclusion, moderate-to-severe OSA was related to the presence of any diabetes-related complications in type 2 diabetes, and the relationship was mediated by hypertension. The severity of intermittent hypoxia was associated with lower eGFR. Whether OSA treatment will delay or reduce diabetes-related complications should be investigated.

Summary The circadian system plays a role in regulating metabolism. Night-shift work, a form of circadian misalignment, is associated with increased type 2 diabetes risk. This study aimed to determine if night-shift workers with type 2 diabetes experience poorer glycaemic control than non-shift workers. Patients with type 2 diabetes (104 unemployed, 85 day workers and 60 night-shift workers) participated. Sleep duration, sleep quality, morningness–eveningness preference, depressive symptoms and dietary intake were assessed using standardized questionnaires. Haemoglobin A1c levels were measured. Night-shift workers had significantly higher haemoglobin A1c levels compared with others, while there were no differences between day workers and unemployed participants (median 7.86% versus 7.24% versus 7.09%, respectively). Additionally, night-shift workers were younger, had a higher body mass index, and consumed more daily calories than others. Among night-shift workers, there were no significant differences in haemoglobin A1c levels between those performing rotating versus non-rotating shifts (P = 0.856), or those with clockwise versus counterclockwise shift rotation (P = 0.833). After adjusting for age, body mass index, insulin use, sleep duration, morningness–eveningness preference and percentage of daily intake from carbohydrates, night-shift work, compared with day work, was associated with significantly higher haemoglobin A1c (B = 0.059, P = 0.044), while there were no differences between unemployed participants and day workers (B = 0.016, P = 0.572). In summary, night-shift work is associated with poorer glycaemic control in patients with type 2 diabetes.

There is evidence that the sleep and circadian systems play a role in glucose metabolism. In addition to physiological factors, sleep is also affected by behavioral, environmental, cultural and social factors. In this study, we examined whether morning or evening preference, sleep timing and sleep duration are associated with glycemic control in patients with type 2 diabetes residing in Thailand. Two hundred and ten type 2 diabetes patients who were not shift workers completed an interview and questionnaires to collect information on diabetes history, habitual sleep duration and sleep timing. Chronotype, an individual's tendency for being a "morning" or "evening" person, was assessed using the Composite Score of Morningness (CSM), which reflects an individual's subjective preference for activities in the morning or evening, as well as mid-sleep time on weekend nights (MSF), which reflects their actual sleep behavior. Most recent hemoglobin A1c (HbA1c) values were retrieved from medical records. Evening preference (as indicated by lower CSM), later bedtime on weekends, and shorter sleep duration correlated with higher HbA1c (r = -0.18, p = 0.01; r = 0.17, p = 0.01 and r = -0.17, p = 0.01, respectively), while there was no association between MSF or wake up time and glycemic control. In addition, later bedtime on weekends significantly correlated with shorter sleep duration (r = -0.34, p

The purpose of this study is to explore the impact of sleep duration on glycemic control in type 2 diabetes patients with untreated sleep-disordered breathing (SDB).Ninety type 2 diabetes patients participated in the study. SDB was diagnosed using an overnight in-home monitoring device (WatchPAT200). Sleep duration was recorded by wrist actigraphy for 7 days. Medical records were reviewed for hemoglobin A1c (HbA1c) values.Seventy-one patients (78.8 %) were diagnosed with SDB [apnea-hypopnea index (AHI) ≥ 5]. In patients with SDB, there was no significant relationship between AHI and glycemic control. In addition, oxygen desaturation index, minimum oxygen saturation, and time spent below oxygen saturation of 90 % were not significantly correlated with glycemic control. Sleep duration, however, was inversely correlated with HbA1c (r = -0.264, p 0.026). Multiple regression analysis adjusting for age, sex, body mass index, insulin use, diabetes duration, and AHI revealed that sleep duration was significantly associated with HbA1c (p = 0.005). Each hour reduction in sleep duration was associated with a 4.8 % increase in HbA1c of its original value (95 % CI 1.5-8.0).In type 2 diabetes patients with untreated SDB, shorter sleep duration was independently associated with poorer glycemic control. Sleep duration optimization may lead to improved glycemic control in this population.