Association of usual sleep quality and glycemic control in type 2 diabetes in Japanese: A cross sectional study. Sleep and Food Registry in Kanagawa (SOREKA). PLoS One. 2018;13:e0191771. [PMID: 29364963 PMCID: PMC5783416 DOI: 10.1371/journal.pone.0191771]

Quality of Sleep and Its Determinants Among People with Diabetes Mellitus in Sub-Saharan Africa: A Systematic Review and Meta-Analysis

BACKGROUND

Poor sleep quality is a serious concern among diabetes mellitus patients, adversely affecting glycemic management and the prognosis of diabetic patients. Therefore, the main aim of this study was to estimate the overall pooled prevalence of poor sleep quality and its associated factors among diabetic patients in Sub-Saharan Africa.

METHODS

Several search databases were employed to retrieve the eligible studies. A standardized data extraction format was used to extract the data, and the analysis was conducted using STATA version 14. To determine heterogeneity, the I2 test was conducted, and both the funnel plot and Egger's regression test were used to assess the publication bias. A random effects model meta-analysis was performed to estimate the overall prevalence and associated factors of poor sleep quality.

RESULTS

In the current meta-analysis, a total of 11 studies with 3,766 study participants were included. The overall pooled prevalence of poor sleep quality among diabetic patients was 53.22% (95% CI: 36.26, 70.19). Poor sleep quality was significantly associated with longer duration of diabetes (OR = 2.94, 95% CI: 1.85, 4.67), poor glycemic control (OR = 2.24, 95% CI: 1.51, 3.32), depression (OR = 4.09, 95% CI: 2.07, 8.05) and comorbidity (OR = 1.94, 95% CI: 1.31, 2.88).

CONCLUSION

In this study, more than half of diabetic patients in Sub-Saharan Africa had poor sleep quality. Therefore, healthcare providers should give more attention to sleep disorders when screening diabetic patients to improve their poor sleep quality.

Relationship between sleep quality and depression in people with type 2 diabetes

Background

sleep quality disorder is both a risk factor for diabetics and a symptom of depression. This study aimed to determine the relationship between sleep quality and depression in people with type 2 diabetes in Delijan city in 2022.

Methods

The present study was a descriptive-analytical study conducted on 245 people with Type 2 Diabetes Mellitus(T2DM). The data were collected from health centers and homes, diabetes clinics in the city of Delijan. The sampling method in this study was Convenienc. Inclusion criteria include people over 30 years old, people with a history of diabetes for more than six months and and people with no known mental disorders. Data collection tools included the Pittsburgh Sleep Quality Index (PSQI), the Beck questionnaire, clinical information about diabetes(FBS, %HbA1c level and duration of diabetes), and a checklist of demographic information. SPSS 23 software was used for data analysis. Data were analyzed using independent t-tests, Chi-square, ANOVA and logistic regression. A significance level of P < 0.05 was considered significant.

Results

The mean (SD) age of the participants was 57.58 (10.58) years. Regarding gender, 162 subjects (66.1%) were female. A statistically significant relationship was observed between the quality of sleep in people with type 2 diabetes with gender, education, Family history T2DM, age, and between depression with gender and FBG. a statistically significant relationship was observed between sleep quality and depression. Also, according to the logistic regression, sleep quality (dependent variable) showed a significant relationship with depression, age, sex, and education.

Conclusion

According to the results, there is a significant relationship between sleep quality and depression In people with T2DM, so it can be used in periodic care of diabetic people to screen for depression, which could improve their sleep quality to some extent.

Glycemic control and associated factors among type 2 diabetes mellitus patients: a cross-sectional study of Azar cohort population

BACKGROUND

Despite the growing prevalence of diabetes and its complications, there is a dearth of data regarding factors associated with glycemic control. Therefore, in this cross-sectional study, we aimed to identify factors influencing glycemic control in patients with type 2 diabetes mellitus (T2DM) in the Iranian population.

METHODS

This cross-sectional study was conducted among the Azar cohort population and the glycemic control status of patients with T2DM was investigated. Possible risk factors including age, sex, marital status, educational level, smoking status, sleep duration, family history of diabetes and hypertension, socioeconomic status, physical activity level, and co-existence of other chronic diseases and their relationship with glycemic control status were also assessed. Multivariate logistic regression analysis was used to identify determinants of glycemic control.

RESULTS

Among 1,710 T2DM patients (60.2% female), the overall prevalence of poor glycemic control was 56.8%. In the unadjusted logistic regression analysis model, a low wealth score index significantly increased the risk of poor glycemic control (OR: 1.49;1.10-2.02). Variables significantly associated with poor glycemic control even after adjusting for confounding factors were first-degree family history of diabetes (OR: 1.34; 1.08-1.65), and sleep duration (OR: 1.29 ;1.02-1.62 for 6.6-8 h/d; OR:1.42;1.10-1.88 for > 8 h/d). Interestingly, we found that the co-existence of ≥ 3 chronic diseases with diabetes decreased the risk of poor glycemic control.

CONCLUSIONS

In the current study, most of the patients with T2DM had uncontrolled glycemic control. Due to the individual and social costs of diabetes complications, it is necessary to suggest tailored and effective interventions for controlling blood glucose levels in people with diabetes.

Glycemic Variability in Patients with Type 2 Diabetes Mellitus (T2DM): The Role of Melatonin in a Crossover, Double-Blind, Placebo-Controlled, Randomized Study

BACKGROUND

Glycemic variability in patients with type 2 diabetes mellitus (T2DM) may be associated with chronic complications of the disease. Melatonin is a hormone that plays a crucial role in biological rhythms. Previous studies have indicated that individuals with T2DM often exhibit reduced melatonin production. In this study, our objective was to investigate whether nighttime melatonin supplementation could mitigate glycemic variability in these patients.

METHODS

Crossover, double-blind, placebo-controlled, randomized study. A total of 30 patients were enrolled in this study. The study included 15 participants who followed the intervention sequence of placebo (7 days)-washout (7 days)-melatonin (3 mg) (7 days), and another 15 participants who followed the sequence of melatonin (3 mg) (7 days)-washout (7 days)-placebo (7 days). During the final three days of the first and third weeks, the participants measured their pre- and postprandial capillary blood glucose levels. This study was reported according to the CONSORT 2010 statement: extension to randomized crossover trials.

RESULTS

There was a significant absolute difference in the breakfast blood glucose levels (p = 0.016) on Day 7. The use of melatonin determined a greater positive variation between pre- and postprandial glycemia than the placebo. The difference in glycemic amplitude between post-dinner Day 6 and pre-breakfast Day 7 was also significantly higher in the melatonin group (p = 0.032).

CONCLUSIONS

Melatonin increased glycemic variability in individuals with type 2 diabetes mellitus (T2DM). These results can be attributed to the residual daytime effects of melatonin, prospective proximal effects, and damage to the prospective distal effects of exogenous melatonin. Therefore, caution should be exercised when administering melatonin supplementation to patients with T2DM, taking into consideration factors such as dosage, duration of use and genetic considerations.

Poor quality of sleep in Mexican patients with type 2 diabetes and its association with lack of glycemic control

AIMS

To determine the association between sleep quality and lack of glycemic control in a Mexican population of type 2 diabetes patients.

METHODS

Cross-sectional study. Two hundred two patients between 20 and 60 years old with a previous diagnosis of diabetes were included. Sleep quality was assessed with the Pittsburgh Sleep Quality Index and lack of glycemic control as a glycated hemoglobin A1c level ≥ 7 %. Univariate and multivariate analyses using logistic regression were performed.

RESULTS

The study population showed poor sleep quality and a lack of glycemic control of 70.3 % and 69.8 %, respectively. The prevalence of patients with both conditions was 52.5 %. In multivariate analysis, poor sleep quality was significantly associated with a lack of glycemic control (OR = 2.3, p = 0.030). Other associated variables were napping (p = 0.015), diabetes duration (p = 0.011), insulin use (p = 0.024), and diastolic blood pressure ≥ 85 mmHg (p = 0.029).

CONCLUSIONS

The prevalence of lack of glycemic control in the study population is high. Poor sleep quality significantly doubles the risk of lack of glycemic control, even in the presence of other risk factors.

Associations of sleep quality with the skeletal muscle strength in patients with type 2 diabetes with poor glycemic control

AIMS/INTRODUCTION

Patients with type 2 diabetes mellitus are reported to be at a high risk for sarcopenia, and are known to have a poorer sleep quality. However, the association between sleep quality and skeletal muscle in patients with type 2 diabetes mellitus is not yet precisely understood.

MATERIALS AND METHODS

A total of 110 inpatients with type 2 diabetes mellitus aged 40-90 years were enrolled. The sleep quality was assessed using the Pittsburgh sleep quality index (PSQI). Skeletal muscle mass was measured using bioelectrical impedance analysis. Muscle strength was evaluated by measuring the grip strength. We also performed dietary surveys and measurements of the plasma amino acid levels.

RESULTS

A high total score on the PSQI was significantly associated with reduced muscle strength, and the association persisted even after adjustments for confounders. On the other hand, adjusted analysis did not reveal any significant associations between the PSQI total score and the skeletal muscle mass. In regard to the associations with subscores of the PSQI, the scores for sleep latency, sleep efficiency, and daytime dysfunction were significantly negatively associated with the muscle strength. Although poor sleep quality was associated with a high confectionery intake and low plasma arginine, citrulline, and ornithine levels, neither confectionery intake levels nor the plasma levels of these amino acids was associated with the muscle strength.

CONCLUSIONS

Our study revealed a significant association between the sleep quality and muscle strength in patients with type 2 diabetes mellitus. These results suggest that poor sleep quality is an important risk factor for sarcopenia in patients with type 2 diabetes mellitus.

Relation between sleep quality and glycemic control among type 2 diabetic patients

Objective: To investigate the relation between sleep quality and glycemic control among type 2 diabetic patients.

Methods: Across sectional descriptive design was used; the study sample including 125 diabetic patients was recruited at diabetic clinics in Zagazig University hospitals. The interview questionnaire sheet consists of 4 parts: (1) demographic data, (2) medical history, (3) an Arabic version of the Pittsburgh sleep quality index (PSQI), and (4) glycated hemoglobin A1c (HbA1c) analysis test.

Results: The mean of sleep duration was the highest score of PSQI components, 96.8% of diabetic patients had poor sleep quality, and 90.4% of diabetic patients had poor glycemic control. A highly statistically significant relationship was found between HbA1c and sleep quality. Moreover, income, duration of disease and smoking were independent positive predictors of HbA1c level, while the female gender was a statistically significant negative predictor. Additionally, female gender and income were statistically significant independent positive predictors of PSQI score.

Conclusions: Poor sleep quality and poor glycemic control were very common among type 2 diabetic patients. There was a highly significant relation between sleep quality and glycemic control.

Sleep duration and food intake in people with type 2 diabetes mellitus and factors affecting confectionery intake

AIMS/INTRODUCTION

We carried out a cross-sectional study of people with type 2 diabetes mellitus to elucidate the association between sleep duration and food intake.

MATERIALS AND METHODS

Overall, 2,887 participants with type 2 diabetes mellitus (mean age 63.0 years; 61.1% men; mean glycated hemoglobin level 7.5%) were included in this study. The participants' self-reported dietary habits and sleep duration were evaluated using a brief self-administered dietary history questionnaire and Pittsburgh Sleep Quality Index, respectively. The participants were categorized into the following four groups based on sleep duration: <6, 6-6.9, 7-7.9 (reference) and ≥8 h.

RESULTS

No significant differences were observed between the groups regarding energy intake (kcal/day), absolute intake (g/day) or relative intake (% energy) of carbohydrates, total fat, proteins and fibers. However, confectionery intake was higher in the <6 h group and lower in the ≥8 h group than in the reference group after adjustment for confounding factors. In multivariate analysis, sleep durations <6 h and ≥8 h significantly correlated with increased (95% confidence interval 0.55 to 3.6; P = 0.0078) and decreased (95% confidence interval -4.0 to -0.32; P = 0.021) confectionery intake, respectively. Confectionery intake was positively correlated with female sex, glycated hemoglobin level and dyslipidemia, whereas it was negatively correlated with alcohol consumption and current smoking status.

CONCLUSIONS

Short sleep duration is associated with high confectionery intake in people with type 2 diabetes mellitus; this might disturb their glycemic control. Therefore, short sleepers with type 2 diabetes mellitus could improve their glycemic control by avoiding confectionery intake and maintaining adequate sleep duration.

A cross-sectional study of the relationship between quality of life and sleep quality in Japanese patients with type 1 diabetes mellitus

This study aimed to reveal the relationship between quality of life (QOL) and sleep quality in patients with type 1 diabetes mellitus (T1DM). Overall, 202 patients with T1DM were registered in our study, and 192 were eligible for analysis. Baseline characteristics and laboratory values were determined. Patients completed the Japanese versions of the Pittsburgh Sleep Quality Index (PSQI) and Diabetes Therapy-Related QOL (DTR-QOL) questionnaires. We investigated the relationship between the global PSQI and DTR-QOL total scores by using linear regression analysis. In univariate regression analysis, DTR-QOL total scores were associated with body mass index, alcohol consumption, hypertension, hemoglobin A1c (HbA1c), and global PSQI score (all p-value <0.05) but not with sleep duration. When the association between PSQI subscales and DTR-QOL total scores was examined, DTR-QOL total scores were significantly related to subjective sleep quality and daytime dysfunction. In a multivariate regression analysis, the global PSQI score was negatively related to DTR-QOL total scores. Patients with an HbA1c concentration ≥8.0% had significantly lower DTR-QOL total scores. We revealed a relationship between QOL and sleep quality in T1DM patients and showed that the relationship between QOL and PSQI subscales in T1DM patients may be different from that in patients with type 2 diabetes mellitus. Assessing and managing sleep quality may be necessary for patients with diabetes to improve QOL.

Relación de la calidad de sueño, adherencia al tratamiento, hemoglobina glucosilada en mujeres con diabetes

Introducción: La Diabetes Tipo 2 es considerado un problema de salud pública que afecta principalmente a las mujeres, que sumado a una mala adherencia al tratamiento terapéutico y, a una falta de calidad de sueño, aumentan la problemática de salud. Objetivo: Determinar las interrelaciones existentes entre la Calidad de Sueño, la Adherencia al Tratamiento Terapéutico y los valores de HbA1c en Mujeres con DT2, perteneciente a una comunidad de la ciudad de Puebla. Materiales y Métodos: El diseño del estudio fue de tipo descriptivo, correlacional y de corte transversal. La muestra se calculó con un nivel de significancia de .05, un coeficiente de correlación .30 y un poder estadístico del 90%, obteniendo una n=110. Los instrumentos utilizados fueron: una cédula de datos personales, el Índice de calidad de sueño de Pittsburgh (PSQI), el Cuestionario de Adherencia Terapéutica MBG (Martín-Bayarre-Grau) y el dispositivo Eclipse A1c. Resultados: Se encontró una relación negativa y significativa para la calidad de sueño con los niveles de HbA1c (rs=-.355; p=.001); no así para con la variable de adherencia al tratamiento terapéutico. Discusión: La información obtenida concuerda con otros estudios, al reafirmar de manera indirecta, las reacciones bioquimicas que ocurren durante la privación del sueño. Conclusiones: Los resultados descubiertos contribuyen al fortalecimiento científico de enfermería, orientando en la mejora de cuidados, que servirá para el diseño de intervenciones que favorezcan a la salud de las mujeres con Diabetes Tipo 2.

Is there a relationship between the ketogenic diet and sleep disorders?

Sleep disorders are very often underestimated and, consequently, not treated with due priority. Common sleep disorders include insomnia disorders, sleep-related breathing disorders, central disorders of hypersomnolence, circadian rhythm sleep-wake disorders, sleep-related movement disorders, parasomnias, and other sleep disorders. The ketogenic diet (KD) is rich in fat, low in carbohydrates (CHO), and adequate in protein. The KD has shown several applications in treating medical conditions, such as epilepsy, neurodegenerative disorders, obesity with its comorbidities, and sleep disorders, with encouraging results. Therefore, the purpose of this review is to address the primary sleep disorders and their respective standard therapeutic approaches, analyse the effect of ketone bodies (KBs) on sleep homeostasis, and the effects of KD on sleep disorders and in particular on obstructive sleep apnoea (OSA) syndrome. The goal is to summarise the evidence existing up to now on the subject, to provide a starting point for further investigations.

Sleeping Duration, Napping and Snoring in Association with Diabetes Control among Patients with Diabetes in Qatar

BACKGROUND

Poor glycemic control is associated with chronic life-threatening complications. Several studies have revealed that sleep status is associated with glycemic control.

AIM

to examine the association between sleep duration, quality and glycemic control among adults with diabetes.

METHODS

Data on 2500 participants aged 18-60 years were collected from the Qatar Biobank (QBB). Sleep duration and quality were assessed by a self-completed health and lifestyle questionnaire, and glycemic control was assessed using HbA1c. Logistic regression was used to assess the association between sleep duration, napping, snoring and poor glycemic control.

RESULTS

After adjusting for age and gender, sleep duration was not associated with poor glycemic control. Lack of association persisted after controlling for smoking, physical activity, education, BMI, fruit and vegetable intake, insulin and medication use. However, sleeping for long hours at night (≥8 h) had a trend in increasing the risk of poor glycemic control (OR = 1.28; 95% CI: 0.94-1.74). Napping was positively associated with poor glycemic control. After adjusting for age and gender, patients who reported "sometimes, frequently, or always" napping had more than 30% increased risk of poor control as compared to patients who reported "never/rarely" napping. Snoring was not associated with poor glycemic control among the study sample when adjusted for age and gender (p = 0.61). Other factors were found to be associated with a better glycemic control such as female, high educational and high physical activity level.

CONCLUSIONS

our results suggest that napping may be an independent risk factor for a poor glycemic control in diabetes; further investigations are required.

The impact of sleep disorders on microvascular complications in patients with type 2 diabetes (SLEEP T2D): the protocol of a cohort study and feasibility randomised control trial

BACKGROUND

Obstructive sleep apnoea (OSA) is very common in patients with type 2 diabetes (T2D). We and others have shown that OSA was associated with diabetes-related microvascular complications in patients with T2D in cross-sectional and longitudinal studies and that compliance with continuous positive airway pressure (CPAP) reduced the progression of microvascular complications. Hence, we hypothesised that adequate CPAP reduces the development of microvascular complication in patients with T2D.

METHODS

SLEEP T2D is a cohort study with embedded feasibility, open-label, parallel-arm, randomised control trial (RCT) over 2 years. The primary aim is the feasibility of conducting a definitive RCT assessing the impact of CPAP on chronic kidney disease and other microvascular complications in patients with T2D. The main parameters are to assess willingness of participants to be randomised, follow-up rates, CPAP adherence/compliance, to optimise the choice of outcome measures for a substantive trial, and to identify the parameters for sample size calculations. The secondary aims of the study are related to the impact of CPAP, sleep-related disorders, and sleep chronotype on a variety of diabetes-related end points. The study participants were recruited from the T2D services in multiple NHS trusts across England. The main exclusion criteria for the cohort study are as follows: T1D, eGFR < 15 mL/min/1.73 m², known OSA, active malignancy or chronic kidney disease from reasons other than diabetes, pregnancy, professional drivers, and a history of falling asleep whilst driving within last 2 years. The main exclusion criteria from the RCT were as follows: Apnoea-Hypopnoea Index < 10 and Epworth Sleepiness Score ≥ 11. Study participants were extensively phenotyped clinically and biochemically. The OSA diagnosis was based on multichannel portable device (ApneaLink Air^TM, Resmed).

DISCUSSION

The feasibility RCT will help us design the future RCT to assess the impact of CPAP on diabetes-related microvascular complications. The cohort study will generate preliminary data regarding the impact of sleep quality, duration, and chronotype on diabetes-related outcomes which could lead to further mechanistic and interventional studies.

TRIAL REGISTRATION

ISRCTN, ISRCTN12361838 . Registered 04 April 2018, Protocol version: v5.0 02.12.19.

Effectiveness of cognitive behavior therapy for sleep disturbance and glycemic control in persons with type 2 diabetes mellitus: A community-based randomized controlled trial in China

BACKGROUND

Poor sleep quality is a common clinical feature in patients with type 2 diabetes mellitus (T2DM), and often negatively related with glycemic control. Cognitive behavioral therapy (CBT) may improve sleep quality and reduce blood sugar levels in patients with T2DM. However, it is not entirely clear whether CBT delivered by general practitioners is effective for poor sleep quality in T2DM patients in community settings.

AIM

To test the effect of CBT delivered by general practitioners in improving sleep quality and reducing glycemic levels in patients with T2DM in community.

METHODS

A cluster randomized controlled trial was conducted from September 2018 to October 2019 in communities of China. Overall 1033 persons with T2DM and poor sleep quality received CBT plus usual care or usual care. Glycosylated hemoglobin A1c (HbAlc) and sleep quality [Pittsburgh Sleep Quality Index (PSQI)] were assessed. Repeated measures analysis of variance and generalized linear mixed effects models were used to estimate the intervention effects on hemoglobin A1c and sleep quality.

RESULTS

The CBT group had 0.64, 0.50, and 0.9 lower PSQI scores than the control group at 2 mo, 6 mo, and 12 mo, respectively. The CBT group showed 0.17 and 0.43 lower HbAlc values than the control group at 6 mo and 12 mo. The intervention on mean ΔHbAlc values was significant at 12 mo (t = 3.68, P < 0.01) and that mean ΔPSQI scores were closely related to ΔHbAlc values (t = 7.02, P < 0.01). Intention-to-treat analysis for primary and secondary outcomes showed identical results with completed samples. No adverse events were reported.

CONCLUSION

CBT delivered by general practitioners, as an effective and practical method, could reduce glycemic levels and improve sleep quality for patients with T2DM in community.

Protein intake in inhabitants with regular exercise is associated with sleep quality: Results of the Shika study

STUDY OBJECTIVES

Although associations between sleep quality and environmental factors and nutrient intake have been reported, interactions between these factors have not been elucidated in detail. Therefore, this cross-sectional study examined the effects of regular exercise and nutrient intake on sleep quality using the Pittsburgh Sleep Quality Index (PSQI), which is the most frequently used index for sleep evaluation.

METHODS

The participants included 378 individuals aged 40 years or older living in Shika Town, Ishikawa Prefecture. Of these individuals, 185 met the inclusion criteria. The participants completed a self-administered questionnaire assessing lifestyle habits and frequency and duration of exercise, the PSQI, and the brief-type self-administered diet history questionnaire (BDHQ) on nutrient intake.

RESULTS

A two-way analysis of covariance on regular exercise and PSQI scores indicated that protein intake (17.13% of energy) was significantly higher in the regular exercise and PSQI ≤10 groups than in the non-regular exercise or PSQI ≥11 groups (p = 0.002). In a multiple logistic regression analysis with PSQI scores (≤10 and ≥11), protein intake was a significant independent variable in any of the models adjusted for confounding factors such as age, sex, body mass index, current smoker, and current drinker (OR: 1.357, 95% CI: 1.081, 1.704, p = 0.009) in the regular exercise group but not in the non-regular exercise group.Conclusions We identified a positive relationship between sleep quality and protein intake in the regular exercise group. These findings suggest that regular exercise at least twice a week for 30 minutes or longer combined with high protein intake contributes to good sleep quality.

Does treatment with sodium-glucose co-transporter-2 inhibitors have an effect on sleep quality, quality of life, and anxiety levels in people with Type 2 diabetes mellitus?

Background/aim

To evaluate the impact of treatment with sodium-glucose co-transporter-2 (SGLT2) Inhibitors on quality of life (QoL), sleep quality (SQ), and anxiety levels in patients with Type 2 diabetes mellitus (T2DM).

Materials and methods

Ninety-seven patients with type 2 diabetes admitted to tertiary care hospital diabetes clinic were included. Fifty patients were randomized to receive SGLT2 inhibitors in addition to baseline treatment (Group A), 47 subjects continued with their baseline treatment or were added other medications as needed (Group B). Thirty healthy controls (HC) were recruited (Group C). All groups were subjected to the Turkish version of Short Form-36 (SF-36), Pittsburgh Sleep Quality (PSQ), and Beck Anxiety Inventory (BAI) scales both at baseline and final visit.

Results

Physical function, emotional role limitation, vitality, mental health, pain, general health perception scores of SF-36 were significantly improved in Group A, at the end of the follow-up period. There was no significant change in terms of PSQ, BAI scores, and hypoglycaemia documented in all groups. The intervention-related change in HbA1c level, body weight, and body mass index were significantly higher in Group A.

Conclusion

The QoL was improved in people with diabetes who were taking SGLT2 inhibitors. This may be explained by weight loss observed in participants.

Sleep Characteristics in Diabetic Patients Depending on the Occurrence of Neuropathic Pain and Related Factors

This study aims to compare the sleep characteristics (structure and quality) in patients with type-2 diabetes mellitus with and without diabetic neuropathic pain (DNP), and to investigate the relationship of sensory phenotypes, anxiety, and depression with sleep quality in DNP patients. A cross-sectional study was performed in patients with type-2 diabetes mellitus and neuropathy. Patients were classified into two groups—with or without neuropathic pain—according to the “Douleur Neuropathique-4 (DN4)” scale. Sleep characteristics and quality (Medical Outcomes Study—MOS-sleep), pain phenotype (Neuropathic Pain Symptom Inventory—NPSI), mood status (Hospital Anxiety and Depression scale—HADS), pain intensity (Visual Analogue Scale—VAS), and quality of life (SF-12v2) were measured. The sample included 130 patients (65 with DNP). The mean scores in all the dimensions of the MOS-sleep scale were higher (more disturbances) in the DNP patients. Higher scores in anxiety or depression, greater intensity of pain or a higher score in the paroxysmal pain phenotype were associated with lower sleep quality in DNP patients. A shorter duration of the diabetes and lower levels of glycated hemoglobin were also associated with lower sleep quality. The results show the relationship between DNP and sleep quality, and the importance of assessing sensory phenotypes and mental comorbidities in these patients. Taking these factors into consideration, to adopt a multimodal approach is necessary to achieve better clinical results.

Chronotherapeutic efficacy of suvorexant on sleep quality and metabolic parameters in patients with type 2 diabetes and insomnia

AIMS

This study aimed to assess the chronotherapeutic efficacy of suvorexant on subjective sleep parameters and metabolic parameters in patients with type 2 diabetes and insomnia.

METHODS

Thirteen patients with type 2 diabetes who met the Pittsburg Sleep Quality index criteria for primary insomnia took suvorexant 20 mg/day (15 mg/day for ≥65 years) for 14 ± 2 weeks. The following parameters were assessed before and after the treatment: sleep diary for sleep duration and quality (i.e., sleep onset latency, waking after sleep onset, and sleep efficiency [sSE]), Insomnia Severity Index, clinical and biochemical data, continuous glucose monitoring (CGM), and validated self-administered questionnaire on food intake.

RESULTS

Suvorexant significantly improved sSE, abdominal circumference, and sucrose intake (all p < 0.05), but did not change HbA1c, CGM parameters, or body weight. Correlation analysis revealed that changes in sSE were associated with those in HbA1c and body weight (r = -0.61 and r = -0.66, respectively; both p < 0.05).

CONCLUSIONS

Suvorexant significantly improved sleep quality and obesity-associated parameters in patients with type 2 diabetes in 14 weeks. Improvements in sleep quality were associated with improvements in glycemic control. Sleep disorder treatment using suvorexant may provide metabolic benefits for patients with type 2 diabetes.

Sleeping disturbances and predictor risk factors among type 2 diabetic mellitus patients

Background

Sleep disturbance is a major health issue among people with type 2 diabetes mellitus (T2DM). The Pittsburgh Sleep Quality Index (PSQI) has been the most widely used instrument to measure subjective sleep disturbance.

Aim

The aim of this study was to determine the impact of sleeping factor structure of the PSQI as potential predictor for glycosylated hemoglobin A1c (HbA1C) among people living with T2DM in the Turkish community to facilitate its use in the clinical practice and research.

Subjects and Methods

This is a cross-sectional study and participants were between the age group of 25 and 65 years old who visited the diabetes and endocrinology department of Mega Medipol University Teaching Hospital, Istanbul. The PSQI was conducted on 871 patients with T2DM. Good sleep quality was defined as PSQI score <5. Multivariate logistic regression analysis was used to estimate the associated risk factors for the T2DM.

Results

The current study showed significant differences between male and female patients with respect to their age in years, body mass index (BMI) (kg/m2), physical activity, smoking habit, sheesha smoking, income, family history of metabolic syndrome, coronary heart disease (CHD), and PSQI. The results revealed significant differences between HbA1c ≤7 and females and HbA1c >7 T2DM patients with respect to gender, BMI (kg/m2), CHD, and PSQI. The study demonstrated significant differences between sleeping categories PSQI as good, average, and poor sleeping among T2DM patients with respect to age and gender. Meanwhile, significant differences were reported between sleeping categories among T2DM patients with respect to their: number of sleeping hours, wake-up time, sleeping time, HbA1c, fasting blood glucose, uric acid, and systolic and diastolic blood pressure. This study showed very strong statistically significant correlations between low HbA1c and poor sleep quality in patients with T2DM patients, including subjective sleep quality r = 0.763, sleep latency r = 0.327, sleep duration r = 0.472, habitual sleep efficiency r = 0.575, sleep disturbances r = 0.564, use of sleep medication r = 0.728, and daytime dysfunction r = 0.734. Multivariate stepwise logistic regression analysis revealed that Vitamin D (mmol/L) (P < 0.001), HbA1c (P < 0.001), duration of DM (P < 0.001), uric acid (mmol/L) (P < 0.001), systolic blood pressure mmHg (P = 0.006), diastolic blood pressure mmHg (P = 0.015), and BMI (P = 0.024) were considered at higher risk as the predictors for sleeping quality among T2DM patients.

Conclusion

The results suggest a strong positive correlation between PSQI with HbA1c levels, systolic and diastolic blood pressure, age, BMI, among type 2 diabetic patients. This study ascertains that poor sleep quality may be due to elevated level of HbA1c, metabolic syndrome, diabetes, obesity, and/or hypertension.

Association between sleep disorder and quality of life in patients with type 2 diabetes: a cross-sectional study

BACKGROUND

We investigated the association between sleep symptoms, which cause sleep disorder, and quality of life (QoL) among people with type 2 diabetes (T2D).

METHODS

In this cross-sectional study of 342 people with T2D, the Japan National Health and Wellness Survey (NHWS) database 2016 were used. We treated the respondents who reported experiencing any of the sleep symptoms as having sleep disorders. To examine health-related QoL (HRQoL), we used the physical component summary (PCS) and the mental component summary (MCS) from the 36-Item short-form and the EuroQol 5 Dimension (EQ-5D) survey instruments. Overall activity impairment was used for assessment of the effect on the individual's ability to perform regular daily activities. We used t-test and one-way ANOVA test for comparison QoL scores between the participants with and without sleep disorders.

RESULTS

66.4% of the participants with T2D reported having a sleep disorder. The PCS, MCS, EQ-5D, and overall activity impairment of people with sleep disorder was significantly poorer than those of the people without. Specific sleep symptoms, such as waking up to go to the bathroom, daytime sleepiness, and waking up too early (before the alarm clock), had high prevalence (35.4, 27.8 and 20.2%). The participants who experienced waking up to go to the bathroom or daytime sleepiness demonstrated significantly poorer QoL on all scores related to QoL, but those who experienced waking up too early only demonstrated significantly poorer QoL on the EQ-5D.

CONCLUSIONS

Two-thirds of people with T2D in this study suffer from sleep disorders. The people who experience waking up to go to the bathroom or daytime sleepiness had significantly poorer QoL than those without these symptoms. Thus, sleep disorders, especially the symptoms of waking up to go to the bathroom or daytime sleepiness, might be the treatment targets for QOL of people with T2DM.

The incidence of diabetes among the non-diabetic residents in Kawauchi village, Fukushima, who experienced evacuation after the 2011 Fukushima Daiichi nuclear power plant disaster

Objectives

After the Fukushima Daiichi nuclear power plant disaster in 2011, residents of Kawauchi village who experienced evacuation had a high risk of suffering from diabetes and metabolic syndrome compared with non-evacuees. In addition to evacuation, lifestyle characteristics can be important factors influencing the development and prognosis of diabetes or glucose tolerance. The current study aimed to evaluate the effects of evacuation (i.e., lifestyle changes) on the incidence of diabetes among the non-diabetic residents of Kawauchi village.

Methods

Design is retrospective cohort study. Annual health examination data of residents of Kawauchi village and control area (Ono town) in Fukushima prefecture from 2008 to 2017, as available from the Japanese National Health Insurance system. Participants were classified into three groups: “Diabetes (DM)” (FBG ≥ 126 mg/dL or HbA1c ≥ 6.5% or hospital visit for DM or usage of diabetic medication), “Borderline DM” (126 mg/dL > FBG ≥ 110 mg/dL or 6.5% > HbA1c ≥ 6.0%, and without hospital visit, and without diabetic medication), and “Normoglycemic” (FBG < 110 mg/dL and HbA1c < 6.0%, and without hospital visit, and without diabetic medication). New onset of diabetes was evaluated and the events or missing data were occurred at health checkup. For this survival analysis, 339 residents in Kawauchi and 598 residents in Ono were included. Average follow-up periods after 2010 were 3.9 years in Kawauchi village and 3.6 years in Ono town.

Results

Compared with the normoglycemic group, incidence of DM was much greater in the borderline DM group, where DM occurred among 38.2% of the group in 2012 and increased to over 60% cumulatively through 2017 in Kawauchi village. DM had a prevalence of 16.3% in 2012, and below 30% in 2017 in borderline DM group of Ono town. Cox proportional hazard regression analysis was applied to non-DM groups at both study sites separately to evaluate the effects of lifestyle changes at each site. While BMI, BMI change, and the lack of regular exercise (HR = 1.29, 1.72, and 5.04, respectively) showed significant associations with the onset of diabetes in Ono town, only BMI and late-night dinner (HR = 1.21 and 4.86, respectively) showed significant associations with diabetes onset in Kawauchi village.

Conclusions

The current results confirmed that diabetes incidence was increased 6 years after the Daiichi nuclear power plant disaster in Kawauchi. We also found changes in lifestyle habits, suggesting that diabetes prevention with promotion of healthy lifestyle behaviors is an urgent priority.

Sleep quality among type 2 diabetes mellitus patients in a private hospital setting in Yangon, Myanmar

Purpose

This study aimed to assess the sleep quality and its associated factors among patients with type 2 diabetes mellitus (T2DM) in a private hospital in Yangon, Myanmar.

Design/methodology/approach

A cross-sectional study was conducted. A total of 289 T2DM patients were interviewed using a structured questionnaire. An English version of the Pittsburgh Sleep Quality Index (PSQI) was translated into Myanmar and used for assessing sleep quality.

Findings

Approximately 48.4% of T2DM patients had poor sleep quality (PSQI score > 5). The mean ± SD of the PSQI global score was 5.97 ± 3.45. About 36.0% of participants reported the presence of diabetes complications, and 14.9% used sleep medication. About 27.7% had depression and 8.3% had poor family relationships. Multiple logistic regression analysis revealed that the presence of complications (AOR = 1.86; 95%CI; 1.04–3.35), poor family relationships (AOR = 5.09; 95%CI; 1.55–16.68) and depression (AOR = 7.52; 95%CI; 3.83–14.76) were significantly associated with poor sleep quality.

Originality/value

The prevalence of poor sleep quality is rather high among T2DM patients. Healthcare personnel and hospital administrators should focus on the complication status, family relationships and depression status of T2DM patients by providing regular screening for sleep quality and depression and by providing a program of sleep health education and counselling at diabetic clinics

Prevalence of Insomnia (Symptoms) in T2D and Association With Metabolic Parameters and Glycemic Control: Meta-Analysis

OBJECTIVE

We aimed to determine the prevalence of insomnia and insomnia symptoms and its association with metabolic parameters and glycemic control in people with type 2 diabetes (T2D) in a systematic review and meta-analysis.

DATA SOURCES

A systematic literature search was conducted in PubMed/Embase until March 2018.

STUDY SELECTION

Included studies described prevalence of insomnia or insomnia symptoms and/or its association with metabolic parameters or glycemic control in adults with T2D.

DATA EXTRACTION

Data extraction was performed independently by 2 reviewers, on a standardized, prepiloted form. An adaptation of Quality Assessment Tool for Quantitative Studies was used to assess the methodological quality of the included studies.

DATA SYNTHESIS

When possible, results were meta-analyzed using random-effects analysis and rated using Grading of Recommendations Assessment, Development and Evaluation (GRADE).

RESULTS

A total of 11 329 titles/abstracts were screened and 224 were read full text in duplicate, of which 78 studies were included. The pooled prevalence of insomnia (symptoms) in people with T2D was 39% (95% confidence interval, 34-44) with I2 statistic of 100% (P < 0.00001), with a very low GRADE of evidence. Sensitivity analyses identified no clear sources of heterogeneity. Meta-analyses showed that in people with T2D, insomnia (symptoms) were associated with higher hemoglobin A1c levels (mean difference, 0.23% [0.1-0.4]) and higher fasting glucose levels (mean difference, 0.40 mmol/L [0.2-0.7]), with a low GRADE of evidence. The relative low methodological quality and high heterogeneity of the studies included in this meta-analysis complicate the interpretation of our results.

CONCLUSIONS

The prevalence of insomnia (symptoms) is 39% (95% confidence interval, 34-44) in the T2D population and may be associated with deleterious glycemic control.

Clinical and psychological characteristics of liraglutide treatment among patients with type 2 diabetes

Aim:

This study aimed to evaluate the glycemic control, quality of life (QOL), and sleep quality in type 2 diabetes mellitus (T2DM) patients who are treated with liraglutide and to investigate whether the QOL and sleep quality were correlated with the glycemic control of this population.

Methods:

A cross-sectional study was carried out on T2DM patients who were treated with liraglutide. Data on body weight and glycemic control were recorded while the QOL and sleep quality were assessed using the Short-Form Health Survey (SF-36), the 5-item World Health Organization Well-Being Index (WHO-5), and the Pittsburgh Sleep Quality Index (PSQI) questionnaires.

Results:

Eighty-four T2DM patients who initiated liraglutide with a mean age of 46.7 years were included in the study. The mean hemoglobin A1c (HbA1c) was 7.76% (standard deviation [SD] =0.62), and about 88.1% of patients had HbA1c > 7%. The PSQI score showed not too bad sleep quality (mean 4.3 ± 1.9). The mean WHO-5 score of the study population showed a “moderate” QOL (12.4 ± 3). Patients had lowest SF-36 score (mean = 52.3) in the subscale of “energy and fatigue.” There was a significant positive correlation between HbA1C and the “energy and fatigue” (r = 0.232, P = 0.034) but not with the other subscales.

Conclusion:

Patients with T2DM taking liraglutide have moderate sleep difficulty and QOL score. Nonetheless, none of these outcomes was significantly correlated with glycemic control. Further well-designed studies with long-term follow-up and larger population sizes are needed to confirm our findings.

Effect of Educational Strategies on the Sleep Quality of People with Diabetes: Randomized Clinical Trial

Objective: To evaluate the effect of educational strategies on sleep quality and its relation to diabetes-related distress and glycemic control in people with type 2 diabetes mellitus (DM2). Materials and methods: Randomized clinical trial involving two groups. Group 1 (G1, n = 45) received verbal guidance and leaflets on sleep hygiene strategies and group 2 (G2, n = 46) received usual health care guidelines on self-care with the feet. Sleep was assessed by the Pittsburgh Sleep Quality Inventory and diabetes-related distress by the Diabetes Distress Scale. Linear mixed-effects models and linear regression model were used for the statistical analysis. Results: At the end of the follow-up, sleep quality improvement (p = 0.02) was verified in G1. Low diabetes-related distress score (p = 0.03), being male (p = 0.02), belonging to G1 (p = 0.002), and age (p = 0.04) contributed to better sleep quality. Conclusion: Educational guidelines on sleep hygiene in patients with DM2 were effective in improving sleep quality, measured by the PSQI instrument and emotional stress related to diabetes as assessed by the Diabetes Distress Scale.

Gender differences in the associations between insomnia and glycemic control in patients with type 2 diabetes: a cross-sectional study

STUDY OBJECTIVES

Insomnia is associated with insulin resistance and type 2 diabetes (T2D) in the general population. However, the associations between insomnia and glycemic control in T2D population are not consistently reported. In this study, we aimed to examine the associations between insomnia and glycemic control, and gender differences in these associations among Hong Kong Chinese patients with T2D.

METHODS

This was a cross-sectional study involving T2D patients recruited from the Hong Kong Diabetes Registry between July 2010 and June 2015. Glycemic control was estimated by fasting plasma glucose (FPG) and glycated hemoglobin (HbA1c). Participants with the Insomnia Severity Index score > 14 were considered as having insomnia.

RESULTS

A total of 3753 patients were recruited. Compared with patients without insomnia, patients with insomnia had higher levels of FPG and HbA1c. After adjustment for potential confounding factors, insomnia was associated with higher FPG and HbA1c in the entire cohort. There were significant interactions between insomnia and gender for FPG (p = 0.001) and HbA1c (p = 0.025) in the full model. Subgroup analyses found that men with insomnia had higher FPG [8.23 (7.85-8.61) mmol/L versus 7.50 (7.39-7.61) mmol/L, p < 0.001] and HbA1c [7.79 (7.57-8.02)% versus 7.45 (7.39-7.52)%, p = 0.005] than men without insomnia after adjusted for confounding factors, whereas such difference was not observed in women.

CONCLUSIONS

T2D patients with insomnia had worse glycemic control than the patients without insomnia. The associations were particularly pronounced in men.

The Interlinked Rising Epidemic of Insufficient Sleep and Diabetes Mellitus

For healthy existence, humans need to spend one-third of their time sleeping. Any qualitative or quantitative disturbances in sleep would result in an increased prevalence of obesity, metabolic disorders, diabetes, cardiovascular diseases, and hypertension. The paper aims to highlight the growing global problem of insufficient sleep and its significant impact on the rising incidence of diabetes mellitus. An extensive literature search was done in all major databases for "insufficient sleep" and "Diabetes Mellitus" for this review. Shorter (<6 h) and longer (>9 h) durations of sleep have been adversely related to insulin resistance. Though the relation between insufficient sleep and diabetes mellitus is more or less understood, little is known about how oversleeping or hypersomnia (10⁻12 h) increases the risk of diabetes. The relationship between sleep disturbances and diabetes is dual-sided, as chronic sleep disturbances would elevate the risk of developing insulin resistance, while diabetes would worsen the quality of sleep. Both the qualitative and quantitative disturbances in sleep significantly increase the risk of developing diabetes, which is supported by numerous community-based and hospital-based epidemiological studies discussed in this review. Obstructive sleep apnea is one of the most common sleep disorders and is characterized by chronic intermittent hypoxia and increased sympathetic activity, thus leading to a higher prevalence of diabetes. Sleep therapy may serve as a low-cost method for fighting against the rising epidemic of diabetes.

Real-World Data in Support of Short Sleep Duration with Poor Glycemic Control, in People with Type 2 Diabetes Mellitus

AIMS

Sleep duration (SD) has been associated with metabolic outcomes. Is there an independent association between short/long SD and glycemic control (GC) in type 2 diabetes mellitus (T2DM) outpatients, compared to intermediate SD? Employing up-to-date definitions of SD, we comprehensively considered, simultaneously, all known confounding/mediating factors that recently emerged in the literature: age, gender, diet, physical activity, obesity, night pain, nocturnal diuresis, sleep quality, chronotype, sleep apnea, depressive symptoms, alcohol, caffeine, tobacco, number of endocrinologist appointments, T2DM family history, and sleep medication.

METHODS

A cross-sectional study of 140 consecutive T2DM outpatients, ages 40-65, glycohemoglobin (HbA _1c ) goal ≤ 7. We searched for variables (including HbA_1c) significantly associated with short (<6 hours) or long (>8 hours) SD, in comparison to intermediate SD (6-8 hours).

RESULTS

Higher HbA_1c levels increased the chance of belonging to the group that sleeps <6 hours (p ≤ 0.001). Better sleep quality, nocturnal diuresis, and morningness increased the chance of belonging to the group that sleeps >8 hours (p < 0.05).

CONCLUSIONS

There is an independent association between short SD and elevated HbA_1c, in real-world T2DM outpatients. Future interventional studies could evaluate weather consistent, long-term sleep extension, from <6 hours to 7-9 hours per 24 hours, improves GC in T2DM outpatients.

Circadian dysrhythmia-linked diabetes mellitus: Examining melatonin’s roles in prophylaxis and management

Diabetes mellitus is a chronic, life-threatening metabolic disorder that occurs worldwide. Despite an increase in the knowledge of the risk factors that are associated with diabetes mellitus, its worldwide prevalence has continued to rise; thus, necessitating more research into its aetiology. Recent researches are beginning to link a dysregulation of the circadian rhythm to impairment of intermediary metabolism; with evidences that circadian rhythm dysfunction might play an important role in the aetiology, course or prognosis of some cases of diabetes mellitus. These evidences thereby suggest possible relationships between the circadian rhythm regulator melatonin, and diabetes mellitus. In this review, we discuss the roles of the circadian rhythm in the regulation of the metabolism of carbohydrates and other macronutrients; with emphasis on the importance of melatonin and the impacts of its deficiency on carbohydrate homeostasis. Also, the possibility of using melatonin and its analogs for the “prophylaxis” or management of diabetes mellitus is also considered.