Effects of Sleep Disorders on Hemoglobin A1c Levels in Type 2 Diabetic Patients

To determine melatonin, cytokines, and sleep index in type 2 diabetes mellitus individuals

Introduction

The pathogenesis of type 2 diabetes mellitus (T2DM) is influenced by inflammation and oxidative stress. People with T2DM show evidence of sleep disruption, and their melatonin rhythm, which regulates sleep, is aberrant. It is still uncertain, nevertheless, whether inflammation in this group contributes to the inhibition of melatonin synthesis and sleep problems. Hence, the study aimed to correlate and characterize the biological variables of melatonin levels, inflammatory cytokine levels, and sleep parameters in patients with T2DM.

Material and Methods

ELISA was used to analyze melatonin and cytokine levels in blood samples, and the Pittsburgh Sleep Quality Index (PSQI) questionnaire was utilized to determine sleep quality.

Results

In the global sleep quality measure (PSQI questionnaire), the control group did better than the T2DM group, indicating lower sleep quality and a greater incidence of sleep problems. Melatonin production lacked rhythmicity and was lower in patients with T2DM than in controls both during the day and at night. The T2DM group showed greater levels of chemerin, IL-1, and a negative connection between melatonin and chemerin levels than the control group.

Conclusion

The results suggest that the low melatonin production seen in the T2DM group was most likely the underlying cause of the sleep pathology seen there. It is most probable that high levels of chemerin, which have been linked to other pathologies in the past, are to blame for the blocking of melatonin production in T2DM.

The association between insomnia (related symptoms) and glycaemic control: a systematic review and meta-analysis

Background

Insomnia characterised by difficulties in falling asleep and maintaining sleep, and early awaking, is a prevalent worldwide sleep disorder. While previous studies have suggested an association between insomnia and adverse glycaemic control, the evidence remains inconclusive. Therefore, this meta-analysis aims to explore this association.

Methods

Insomnia was assessed based on defined criteria, including related symptoms such as poor sleep quality and low sleep efficiency. Glycaemic control was evaluated using indicators such as fasting plasma glucose, haemoglobin A1c, and the presence of diabetes. A literature search was performed in PubMed, Web of Science, and Scopus. The quality of the included studied was assessed using The Newcastle-Ottawa Scale. Effect sizes, including odds ratio, relative risk, mean difference, and standard mean difference, were chosen based on data type. Forest plots visually displayed pooled effect sizes and corresponding 95% confidence intervals, while the I2 test calculated heterogeneity. Meta-regression and subgroup analysis explored potential sources of heterogeneity. Leave-one-out sensitivity analysis assessed result robustness, and Begg's and Egger's tests evaluated publication bias.

Results

Ninety-one articles, comprising 84 are cross-sectional studies, (five are case-control studies, and two are cohort studies) with 2 217 521 participants, were included. Ten separate meta-analyses were conducted based on variable type (binary/continuous), study design (cross-sectional, case-control, or cohort), and measurement of exposures/outcomes. All meta-analyses indicated a positive association between insomnia (related symptoms) and adverse glycaemic control. However, three meta-analyses showed significant heterogeneity, and three lacked robustness. No publication bias was detected across any of the analyses.

Conclusions

Insomnia is likely associated with adverse glycaemic control. As the included studies are observational, future research should prioritise diverse methodologies and robust study designs to further explore this complex relationship.

Keywords

insomnia, insomnia related symptoms, glycaemic control, systematic review, meta-analysis.

Registration

PROSPERO CRD42024491688.

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.

Evaluation of Sleep Quality Among People Living With Type 2 Diabetes Mellitus in Taif, Saudi Arabia: A Cross-Sectional Study

BACKGROUND

 Type 2 diabetes mellitus (T2DM) is characterized by high blood glucose levels, which are highly associated with poor sleep quality, cardiovascular disease, and pathological changes. This research examines the relationship between sleep quality and T2DM and compares it with nondiabetics within the Taif community. The findings of this study will provide valuable insights and recommendations to enhance the overall health quality in Taif, Saudi Arabia.

METHODOLOGY

 A cross-sectional study was conducted on 547 patients with T2DM between December 1, 2023, and April 1, 2024, in Taif. The sleep quality was assessed using the Sleep Quality Questionnaire (SQQ). Data were collected using an online questionnaire with two parts: primary demographic data and an assessment of sleep quality using the SQQ.

RESULTS

 Our study enrolled 814 participants, including 547 with T2DM and 267 nondiabetics. Participants with T2DM had poorer sleep quality, with a median score of 21 vs. 25 (P < 0.001). Significant factors affecting sleep quality included gender (P = 0.002), marital status (P = 0.023), and job status (P = 0.023). Nondiabetics had better sleep quality (76%) than participants with T2DM (61.1%). Males, married, and employed individuals reported higher sleep quality scores.

CONCLUSIONS

 Research indicates that individuals with T2DM experience lower sleep quality than the general population, particularly among female, unmarried, and unemployed individuals. To enhance sleep quality in patients with T2DM, it is essential to increase awareness, provide education on proper sleep habits, and highlight the importance of effective diabetes management, screening for sleep disorders, and consistent monitoring.

The Prevalence of Sleep Disorders in People with Type 2 Diabetes and Obesity in Saudi Arabia: A Cross-Sectional Study

Purpose

Difficulty falling or staying asleep are considered sleep disorders, and these are common among people with type 2 diabetes mellitus (T2DM) and obesity. The presence of sleep disorders may cause poor glycemic control among this population. We therefore designed this study to assess sleep disorders among patients with T2DM and obesity.

Patients and Methods

This cross-sectional study examined the prevalence of sleep disorders in 148 patients with T2DM and obesity at a hospital in Taif, Saudi Arabia using a validated questionnaire.

Results

Among those patients who have been involved in this study, we found a moderate level of sleep disorders and disturbances. The average sleep disorder assessment score for the patients with T2DM and obesity was 2.8 ± 1.4. Additionally, the average score for the sleep pattern assessment was 2.7 ± 1.3 and 2.9 ± 1.5 for symptoms of lack of sleep. Our study also revealed that those patients also had suboptimal weight and glycemic control.

Conclusion

These findings demonstrate that patients with T2DM and obesity are at a higher risk of developing sleep disorders. Therefore, these patients need to be screened for sleep disorders to avoid further diabetes-related complications and to have an early lifestyle intervention.

Impact of the State of Emergency Declaration for Severe Acute Respiratory Syndrome Coronavirus-2 Pandemic Suppression on Individuals with Type 1 Diabetes Mellitus

Objective To examine the impact of lifestyle changes caused by the first emergency declaration issued in 2020 on glycemic control and body weight changes in Japanese individuals with type 1 diabetes mellitus. Methods This study included Japanese individuals with type 1 diabetes mellitus who visited Tokyo Women's Medical University Hospital between January 2019 and September 2020 (n=278). Seasonal changes in glycated hemoglobin (HbA1c) levels and the body mass index (BMI) were compared. A self-administered questionnaire regarding changes in treatment, diet, exercise, sleep, and telecommuting was used to assess lifestyle changes. Results Although HbA1c levels decreased from winter to summer in 2019 and 2020, the annual change was slightly but significantly greater in 2020 than in 2019. Seasonal changes in the BMI between 2019 and 2020 were also significantly different. An increase in the daily insulin dose, overall blood glucose level, diurnal change in blood glucose level, and food intake were significantly associated with increased HbA1c levels. Furthermore, HbA1c levels decreased with increasing moderate physical activity and sleep duration. The change in the BMI increased with increasing insulin dose, overall high blood glucose levels, and food intake. However, an increase in moderate physical activity was associated with a decrease in the BMI. HbA1c levels were significantly lower after the first emergency declaration in individuals with type 1 diabetes mellitus than that before the emergency declaration, even after accounting for seasonal variations. Conclusion Decreased HbA1c levels were associated with a decreased food intake, increased moderate exercise, and increased sleep duration during the state of emergency. The BMI remained relatively unchanged.

Association between Perceived Protection Motivation, Preventive Behaviors, and Biomarkers among Diabetic Patients in Rural Areas of Thailand

The prevalence of diabetes mellitus (DM) is increasing rapidly worldwide. Without proper management, DM can have serious complications. We aimed to investigate the association between protection motivation theory (PMT) constructs, self-care behaviors, and biomarkers among diabetic patients in a community in northern Thailand. A cross-sectional study was conducted. Simple random sampling was used to select 422 subjects from patients enrolled in primary care in Chiang Rai Province. Data were collected using questionnaires and blood sampling to measure fasting blood sugar (FBS) and glycated hemoglobin (HbA1c). Pearson's correlation and multiple linear regression were used to analyze the data. The diabetic subjects' age was 62.25 years (standard deviation [SD] = 8.90), and the duration of diabetes was 9.07 years (SD = 7.23). Positive correlations were found between the DM knowledge score and the PMT score (r = 0.812, p < 0.01) and between the PMT score and the preventive behavior score (r = 0.817, p < 0.01). The preventive behavior score was negatively correlated with FBS (r = -0.319, p < 0.01) and HbA1c (r = -0.625, p < 0.01) and significantly associated with income (B = 0.15) and the PMT score (B = 0.71), accounting for 67.0% of the variance. Age (B = -0.73), sleep problems (B = 10.71), and the preventive behavior score (B = -1.15) were statistically significantly associated with FBS (R2 = 14.3%). Four variables, the female gender (B = -0.26), being married (B = -0.24), sleep problems (B = 0.42), and the preventive behavior score (B = -0.09), were statistically significantly associated with HbA1c levels (R2 = 41.6%). Health education programs should primarily target awareness of disease severity, complications, and self-efficacy enhancement to generate intention and behavior change. This may delay or reduce the occurrence of diabetes-related complications in people with type 2 diabetes.

The association between OSA and glycemic control in diabetes

BACKGROUND

Obstructive sleep apnea (OSA) is the most common sleep-realted respiratory disorder. It is frequently comorbid with cardiovascular, cerebrovascular, and metabolic diseases and is commonly observed in populations with these comorbidities. Investigators aimed to assess the effect of OSA on glycemic control in patients with diabetes.

METHODS

In this cross-sectional study, 266 adult patients with diabetes mellitus (DM) attending the outpatient endocrinology clinic at the Guilan University of Medical Sciences were enrolled. Patients completed a checklist that included demographic characteristics, factors, and laboratory results in addition to Berlin and STOP-BANG questionnaires to evaluate the risk of OSA. Data were analyzed by independent t-test, Mann-Whitney U test, and Chi-squared or Fisher's exact tests using the Statistical Package for the Social Sciences (SPSS) version 17.

RESULTS

A total of 266 patients with DM were enrolled in this study (34.6% males, mean age 47.00 ± 19.04 years). Based on the Berlin Questionnaire, 38.6% of all participants were at high risk of developing OSA. Based on the STOP-BANG Questionnaire (SBQ), 45.1% were at moderate and high risks. Additionally, this questionnaire showed a significant difference between low and moderate-to-severe groups regarding sex, age, body mass index (BMI), neck size, other chronic diseases, types of DM, use of insulin, Berlin Questionnaire, fasting blood sugar (FBS), and mean HbA1c.

CONCLUSIONS

Based on the SBQ, our results indicated a significant relationship between OSA and glycemic control according to mean HbA1c and FBS. Therefore, by controlling the OSA, we may find a way to acheieve better glycemic control in diabetic patients.

Consequences of Sleep Deprivation in Adult Diabetes Mellitus Type 2 Patients: An Integrative Review

BACKGROUND: Sleep deprivation in individuals with diabetes mellitus type 2 is more prevalent than in ordinary people. At present, the adverse effects of diabetes type 2 people with sleep disorders and sleep deprivation on blood sugar control are irrefutable. Thorough assessments covering the whole structure should be of concern in health-care treatment. It is precipitated and delivered to the physical, mental health, and social environment, but no systematic review or minimal data were published. Furthermore, it may significantly affect the system more than existing research. AIM: An integrative review aims to clarify the results or consequences of sleep disturbance/deprivation or insomnia symptoms among diabetes mellitus type 2 patients. METHODS: The writers implemented a literature search in PubMed, CINAHL, and Medline using the terms DM type 2, insomnia, adult, effect, DM, sleep disturbance, sleep disorder, and a consequence between 2012 and 2022. Inclusion criteria selected through considering the entire article, and providing an abstract, were 20 articles. RESULTS: Integrative data extraction and information were analyzed thematically. Identified were nine ideas: Association with blood sugar control, blood pressure control, risk of CVD, diabetes self-care behavior, weight gained and Obstructive Sleep Apnea (OSA), lifestyle and physical activity, mood/depression and anxiety symptoms, daily calories distribution, cholesterol/triglyceride, and liver enzyme levels. CONCLUSION: The adverse effects of sleep deprivation in type 2 diabetes significantly affect all pathophysiologically, mentally, and lifestyle modifications, including diabetes self-care. Therefore, to highlight the importance of promoting optimum sleep in diabetes type2 patients, a health-care system is inevitably as necessary as diet and exercise management.

Assessing related factors to fasting blood sugar and glycosylated hemoglobin in patients with type 2 diabetes simultaneously by a multivariate longitudinal marginal model

The multivariate marginal model can be used to simultaneously examine the factors affecting both FBS and HbA1c using longitudinal data. The model fitted to multivariate longitudinal data should prevent redundant parameter estimation in order to have greater efficiency. In this study, a multivariate marginal model is used to simultaneously investigate the factors affecting both FBS and HbA1c with longitudinal data for patients with type 2 diabetes in Northern Iran. The present research is a retrospective cohort study. Overall, 500 medical records with complete information were reviewed. The multivariate marginal model is used to determine the factors associated with FBS and HbA1c using longitudinal data. Data have been analyzed in R-3.4.0 using ‘mmm2’ package. Given that the coefficients for the interactions of rtype with the intercept, time, family history of diabetes, history of hypertension, history of smoking, insulin therapy, systolic/diastolic blood pressure and duration of disease at first visit are significantly different from zero (P < 0.05), the effect of the independent variables on the two response variables is different and different coefficients should be used for each. Therefore, the interactions of these variables with rtype are kept in the final model. The coefficients for the interactions of rtype with sex, age at first visit, history of high cholesterol, and weight are not significantly different from zero (P > 0.05), indicating that their effect on the two response variables is similar and only one coefficient should be used for each. We examined the similarity of coefficients when fitting the longitudinal multivariate model for the relationship between FBS/HbA1c and sex, age, history of high blood cholesterol, and body weight. If an independent variable has similar effects on both responses, only one coefficient should be estimated, which will increase the efficiency of the model and the reliability of the results.

Sleep impairment: Is it an overlooked burden in painful diabetic peripheral neuropathy? A single-centre, cross-sectional study from south India

BACKGROUND AND AIMS

Painful diabetic peripheral neuropathy (PDPN) is a common complication of type 2 diabetes. The unrelenting pain associated with PDPN adversely affects a patient's quality of life. Recognizing the crucial role that sleep plays in the metabolic control of diabetes, this study aims to estimate the prevalence of sleep impairment in painful diabetic peripheral neuropathy (PDPN) and identify the factors associated with it.

METHODS

We conducted a cross-sectional study among 156 patients in a tertiary care hospital in south India. We recruited consenting adults with PDPN. Sleep quality was analyzed using the Pittsburg sleep quality index (PSQI), a self-rating scale. Hba1c served as a measure of glycemic control. Anxiety and depression were assessed using the hospital anxiety and depression (HAD) scale. Data were analyzed in SPSS 26.0.

RESULTS

A total of 156 patients were included in the study with a mean age of 58.39 ± 9.12 years. In 151 (96.79%) patients demonstrated sleep impairment with a global PSQI score of 10.92 ± 2.87. Female sex, ischemic heart disease (IHD), high anxiety levels and use of insulin, pregabapentin, and duloxetine; were significantly associated with poor sleep quality (p < 0.05). The median Hba1c was high (9% [7.46-11.1]). However, there was no statistical correlation between the degree of sleep impairment and glycemic control.

CONCLUSION

We found a high prevalence of sleep impairment in patients with PDPN. Female sex, IHD, high anxiety levels and use of neuropathic drugs were predictors of poor sleep quality.

The role of Recent Pharmacotherapeutic Options on the Management of Treatment Resistant Type 2 Diabetes

INTRODUCTION

Type 2 diabetes mellitus is a complex progressive disease leading to chronic hyperglycemia due to insulin resistance and pancreatic beta-cell failure. Intensification of treatment regimens is often necessary due to the overall decline in insulin secretion. Unfortunately, many patients are unable to achieve optimal glycemic control despite the standard of care and thus may be classified as 'treatment resistant'.

AREAS COVERED

Newer pharmacotherapeutic agents, either injectable or oral, such as Glucagon-like-peptide-1 receptor agonists (GLP-1RA) and Sodium-glucose Cotransporter-2 (SGLT2) inhibitors are, herein, described. These agents can be used as single agents or fixed combinations that reduce glycemia while lessening the risk for hypoglycemia and renal and cardiovascular diseases.

EXPERT OPINION

If individualized target HbA1c is not obtained despite diet, lifestyle, and metformin therapy, then additional oral and injectable therapies should be considered. This may include newer agents such as GLP-1RA and SGLT2 inhibitors alone or in combination that provide renal protection and reduce cardiovascular and hypoglycemic risks. These newer agents have substantial potential for lowering HbA1c through differing but complementary mechanisms. Use of new insulin analogs with GLP-1RA preparations either alone or in fixed-ratio combinations, such as glargine/lixisenatide and degludec/liraglutide, can also reduce the multiple drug adherence burden while improving glycemic control.

Association Between Poor Sleep Quality and Glycemic Control in Adult Patients with Diabetes Referred to Endocrinology Clinic of Guilan: A Cross-sectional Study

BACKGROUND

Diabetes is a prevalent chronic medical comorbid condition worldwide. Diabetes mellitus is associated with various sleep disorders.

OBJECTIVES

We aimed to determine the prevalence of poor sleep and the main factors of sleep interruptions in patients with diabetes mellitus. We further evaluated the association of sleep interruptions with glycemic control in this cohort.

METHODS

We conducted a cross-sectional study on 266 patients with type 1 and type 2 diabetes recruited from a university outpatient endocrinology clinic. Patients completed a checklist including demographic and disease-related characteristics in addition to the Pittsburgh Sleep Quality Index (PSQI) to evaluate sleep quality. Using the PSQI cutoff score of 5, we created two subgroups of good sleepers (GS) and poor sleepers (PS).

RESULTS

Our results showed that good sleeper and poor sleeper patients with diabetes were significantly different regarding sex, employment status, BMI, presence of diabetes-related complications, HbA1c, and 2-hour postprandial blood sugar (2HPPBS) (all significant at P < 0.05). The most prevalent factors of sleep interruptions were "waking up to use a bathroom", "feeling hot", "pain", "having coughs or snores", and "bad dreams". Among the subjective factors of sleep interruption, problems with sleep initiation, maintenance, or early morning awakenings in addition to having pain or respiratory problems such as coughing or snoring had the most significant associations with HbA1c.

CONCLUSIONS

Our study showed significant subjective sleep disturbances (both quality and quantity) in patients with diabetes mellitus (both type I and II) and its association with diabetes control. We further identified the main factors that led to sleep interruptions in this cohort.

Relationship Between Diabetes-Related Complications and Sleep Complaints in Older Mexican Americans

INTRODUCTION/OBJECTIVE

The prevalence of Type 2 Diabetes Mellitus is increasing in the older American population, especially Mexican Americans. Sleep disorders are common in older adults with T2DM. This study examined the relationship between T2DM-related complications and sleep complaints in older Mexican Americans over 9 years of follow-up.

METHODS

Study included 310 participants aged 77 years or older with self-reported diabetes from the Hispanic Established Population for the Epidemiological Study of the Elderly (2007/08-2016).

RESULTS

Of the 310 participants, the mean age was 82.04 years. The cohort had significantly more females (69.03%) than males (30.97%). A substantial number of participants had trouble falling asleep (16.13%), waking up several times (36.45%), trouble staying asleep (15.16%), and feeling tired and worn out after waking up (12.90%). The percent of diabetes complications were 70.2% for circulation problems, 58.2% for eye disorders, 15.9% for kidney disease, and 4.4% for amputation. Participants who experienced sleep complaints for 15 or more days in a month were more likely to experience diabetic complications.

DISCUSSION

This study demonstrated a significant relationship between T2DM macro- and micro-vascular complications and increased risk of sleep disorders in older Mexican Americans.

Comorbid obstructive sleep apnea and insomnia and its associations with mood and diabetes-related distress in type 2 diabetes mellitus

STUDY OBJECTIVES

Previous research suggests that obstructive sleep apnea (OSA) and insomnia frequently co-exist and are prevalent in persons with type 2 diabetes mellitus (T2DM). This study compared mood and diabetes-related distress among OSA, insomnia, and comorbid OSA and insomnia (OSA+I) groups in persons with T2DM.

METHODS

A secondary analysis was conducted with baseline data from two independent randomized controlled trials evaluating the efficacy of OSA and insomnia treatment. The pooled sample (N=224) included participants with OSA only (n=68 [30.4%]), insomnia only (n=107 [47.8%]), and OSA and insomnia (OSA+I; n=49 [21.9%]). OSA was defined as an apnea-hypopnea index ≥ 15 events per hour; insomnia defined as an Insomnia Severity Index score ≥ 15. Mood was measured by the Profile of Mood States total and subscale scores; diabetes-related distress was assessed by the Problem Areas in Diabetes. One-way analysis of covariance and multivariate analysis of covariance were conducted, controlling for demographic characteristics and restless leg syndrome.

RESULTS

The insomnia group had on average significantly higher scores for total mood disturbance (insomnia vs. OSA= 45.32 vs. 32.15, p=.049), tension-anxiety (insomnia vs. OSA= 12.64 vs. 9.47, p=.008), and confusion-bewilderment (insomnia vs. OSA= 9.45 vs. 7.46, p=.036) than OSA group. The OSA+I group had on average significantly greater diabetes-related distress than OSA group (OSA+I vs. OSA= 40.61 vs. 30.97, p=.036).

CONCLUSIONS

Insomnia may have greater impact on mood disturbance and diabetes-related distress than OSA in persons with T2DM. In particular, comorbid insomnia may contribute to greater diabetes-related distress in persons with T2DM and OSA.

Sleep quality and heart rate variability in adolescents with type 1 or type 2 diabetes

INTRODUCTION

Decreased sleep quality and lower heart rate variability (HRV) have both independently been associated with diabetes and may contribute to risks for cardiovascular disease. Although poor sleep quality has been associated with lower HRV in adults with type 2 diabetes (T2D), studies of sleep quality in adolescents with (T2D) or studies examining the possible association of poor sleep quality with lower HRV in adolescents with T2D or T1D are not available.

AIM

Thus, we conducted a secondary analysis of data from an existing study to determine if there were associations between sleep quality and HRV in adolescents with T1D or T2D.

METHODS

Adolescents with T1D (n = 101) or T2D (n = 37) completed 24-h HRV Holter monitoring and analysis and a self-reported global measure of sleep quality.

RESULTS

Poor sleep quality was significantly associated with lower HRV, a known predictor for CV risk. Those with T2D had lower measures of HRV.

CONCLUSIONS

The evaluation of sleep quality and early signs of cardiovascular autonomic changes should be considered in routine assessments of adolescents with diabetes. Future research is warranted to examine more robust measures of sleep and HRV in adolescents with diabetes.

Prevalence of Depression and Sleep Disorders in Patients on Dialysis: A Cross-Sectional Study in Qatar

Patients with end-stage renal disease treated with dialysis have poor quality of life (QOL). Improving QOL in these patients with multiple comorbidities is a large challenge. We performed a cross-sectional study to evaluate the prevalence and associated factors of depression and sleep disorders in this population. Our primary aim was to evaluate QOL measures in dialysis patients in Qatar through a series of validated questionnaires mainly concerning depression and sleep disorders. Our secondary aim was to study the associations of age, sex, and comorbid conditions with the QOL measures. We hypothesized that end-stage renal disease (ESRD) patients on dialysis would have disturbed QOL due to both ESRD and dialysis and comorbidities. This prospective cross-sectional study included adult ESRD patients receiving either hemodialysis (HD) or peritoneal dialysis (PD) in the main tertiary dialysis unit in Qatar. We administered two surveys to evaluate depression (the Center for Epidemiologic Studies Depression Scale, http://www.bmedreport.com/archives/7139) and sleep disorders (the Pittsburgh Sleep Quality Index, https://www.sleep.pitt.edu/instruments/). We also reviewed patient demographics, comorbidities, and laboratory test results to evaluate any associated factors. We randomly studied 253 patients (62% on HD and 38% on PD). Overall, 48% of patients had depression, while 83.8% had sleep disorders. The PD had more poor sleepers than the HD group (89.1% versus (vs.) 75%, p=0.003). Most of our dialysis patients had poor sleep, but it was more significant in the elderly group 109 (90%) than in the young group 103 (78%) (p=0.009). Patients with diabetes mellitus (DM) had significantly more prevalence of poor sleep (131 (88.5%)) than those without DM (81 (77.1%), p=0.01). More female patients had depression than male patients (52% vs. 25%, p < 0.0001; odds ratio: 3.27 (95% confidence interval: 1.9-5.6), p < 0.0001). This is the first study in Qatar to evaluate depression and sleep disorders in patients on dialysis therapy.

Evaluation of the Prevalence of Sleep Disorder Among Patients with Type 2 Diabetes Mellitus Referring to Ghaem Hospital from 2016 to 2017

OBJECTIVE

Diabetes is the most common metabolic disease in primary health care. The prevalence and severity of diabetes can be influenced through lifestyle modification. This study was aimed to identify the prevalence of sleep disorders as a modifiable lifestyle factor among diabetic patients.

MATERIALS AND METHODS

This cross-sectional study was conducted on 190 patients with type 2 diabetes mellitus who referred to the Internal Medicine Clinic of the Ghaem Hospital, Mashhad, Iran from 2016 to 2017. A demographic questionnaire and the Pittsburgh Sleep Quality Assessment questionnaire (with sleep disorder defined as scores higher than 5) was filled for each subject. Blood tests including haemoglobin A1 C (Hb A1C), fasting blood sugar (FBS) and 2 hour post prandial glucose as well as the assessment of blood pressure and body mass index (BMI) were performed for all patients. Data were analysed using the statistical package for social sciences (SPSS) version 16.

RESULTS

Age of the patients (with male to female ratio being 71/119s) was 56.31 ± 7.37 years. BMI of more than 25 kg/m2was observed in 145 (76.3%) of patients. Mean Pittsburgh Sleep Quality Assessment score was 7.48 ± 4.11. Fifty-one (26.8%) patients were good sleepers and 139 (73.2%) were poor sleepers. There was a significant relationship between sleep disorder and age (p=0.019) and female gender (p=0.017), but no other variables which included level of education, occupation, HbA1 C, FBS, 2-hour post prandial glucose, systolic and diastolic blood pressure.

CONCLUSION

Sleep disorders are common among type 2 diabetic patients especially women. It is recommended that sleep disorders should be screened in diabetic patients. Treatment and prevention of sleep disorders through sleep hygiene education including recommendation to have normal nocturnal sleep should be focused by practitioners in type 2 diabetic patients, especially women. Appropriate measures should be taken to manage sleep disorders by weight control in this population.

Lipid accumulation product (LAP) was independently associatedwith obstructive sleep apnea in patients with type 2 diabetes mellitus

BACKGROUND

Lipid accumulation product (LAP) is a new index based on a combination of waist circumference (WC) and serum triglycerides (TG) reflecting lipid accumulation. In this cross-sectional study, we aimed to explore whether LAP was independently associated with obstructive sleep apnea (OSA) in Type 2 diabetes mellitus (T2DM) patients.

METHODS

A cross-sectional study of 317 T2DM patients who underwent overnight polysomnography (PSG) tests was conducted. The clinical data between non-OSA group and OSA group were compared. Multivariable linear regression and multivariable logistic regression analyses were performed to determine associations of LAP, with apnea-hypopnea index (AHI) and OSA.

RESULTS

Among 317 patients, 219 (69.1%) were men, and the mean ages (±SD) were 51.4 (±13.5) years for men and 54.6 (±15.1) years for women (p = 0.067). The prevalence rates of OSA were 63.0% for men and 68.4% for women (p = 0.357). LAP (log-transformed) was significantly correlated with AHI (log-transformed), with the Pearson's correlation coefficient of 0.170 (p = 0.002). With adjustment for potential confounding factors, multivariate linear regression analyses showed the association of LAP with AHI was not statistically significant, with the adjusted linear regression coefficients (95% CI) of per SD increase of LAP for AHI (log-transformed) was 0.092 (- 0.011-0.194, p = 0.080). Multivariate logistic regression analyses showed LAP was significantly associated with increased risk of OSA, with the adjusted OR (95%CI) of per SD increase of LAP of 1.639 (1.032-2.604, p = 0.036). However, as constituents of LAP, neither TG nor WC was significantly associated with AHI and OSA.

CONCLUSION

LAP was independently associated with OSA and might be used as a potential OSA risk marker in T2DM patients, beyond the general index of obesity.

Sleep Quality and Associated Factors Among Diabetes Mellitus Patients in a Follow-Up Clinic at the University of Gondar Comprehensive Specialized Hospital in Gondar, Northwest Ethiopia: A Cross-Sectional Study

INTRODUCTION

Diabetic mellitus has a negative impact on the quality of sleep. It is one of the leading public health conditions which can result in poor sleep quality. Poor sleep quality is an unreported and unrecognized problem which can affect the prognosis of diabetes patients.

OBJECTIVE

The aim of this study is to assess the prevalence of poor sleep quality and its associated factors among patients with diabetes mellitus attending follow-up clinics at the University of Gondar Comprehensive Specialized Hospital, Northwest Ethiopia, 2019.

METHODS

An institution-based cross-sectional study was conducted among 430 diabetes mellitus patients at the University of Gondar Comprehensive Specialized Hospital from February 1, 2020 to March 28, 2020. A systematic random sampling method was used to reach the study subjects. An interviewer-administered questionnaire was used for data collection. Pittsburgh sleep quality index was used for assessing sleep quality. To explain study variables, frequency tables and percentages were used. A binary logistic regression was conducted to see the relation between dependent and independent variables.

RESULTS

A total of 430 diabetes mellitus patients participated in the study with a response rate of 100%. The overall prevalence of poor sleep quality was 47.2%. Drinking alcohol (AOR = 2.45, 95% CI: 1.28-4.69), smokers (AOR = 6.26, 95% CI: 2.04-19.21), comorbidity (AOR = 1.80, 95% CI: 1.10-2.96), BMI ≥ 30 (AOR = 4.87, 95% CI: 1.07-22.09), having type 2 diabetes mellitus (AOR = 2.16, 95% CI: 1.04-4.50), poor glycemic control (AOR = 2.61, 95% CI: 1.81-4.81) and having depression (AOR = 9.95, 95% CI: 4.85-20.38) were associated with poor sleep quality.

CONCLUSION

In this study, nearly half of the patients had poor sleep quality. Drinking alcohol, smoking, comorbidities, higher BMI, type 2 diabetes mellitus, poor glycemic control and having depression were factors in poor sleep quality. Creating awareness of the need for weight reduction, minimizing alcohol intake, cessation of smoking, and improving sleep hygiene for DM patients would be effective management for improving poor sleep quality.

The Phenotype of Elderly Patients with Type 2 Diabetes Mellitus and Poor Sleep Quality

BACKGROUND

Sleep disturbances are a common problem among patients with Type 2 diabetes mellitus (T2DM). The aim of the study was to identify the phenotype of T2DM patients with poor sleep quality.

METHODS

An observational, cross-sectional study was conducted between May 2013 and August 2015. One hundred and sixty consecutive patients with T2DM: 74 women and 86 men, with a median age of 69.50 years (59.00; 79.50 years) were enrolled in the study. Sleep quality was evaluated using the Pittsburgh Sleep Quality Index (PSQI) questionnaire.

RESULTS

Poor sleep quality was noted in 85 (53%) patients. Sleep disorders were associated with older age, as well as female gender, longer duration of diabetes, lower level of fasting plasma glucose, glycated hemoglobin A1c, estimated glomerular filtration rate, triglycerides, waist-to-hip ratio, and the presence of nephropathy. A multivariate logistic regression revealed that sleep disorders were associated with older age (Odd Ratio (OR) = 1.11, 95% Confidence Interval (CI) 1.07-1.15). Fifty-one patients (31.87%) were treated with sleeping pills. We found that older age, female gender, longer duration of diabetes, lower level of fasting plasma glucose, glycated hemoglobin A1c, estimated glomerular filtration rate, triglycerides, and the presence of nephropathy were linked with more frequent usage of hypnotics. A multivariate logistic regression demonstrated that older age (OR = 1.09, 95% CI 1.05-1.14) and nephropathy (OR = 2.79, 95% CI 1.24-6.28) were associated with a more frequent receiving the hypnotics, whereas male gender (OR = 0.30, 95% CI 0.13-0.71) has less frequent hypnotics usage.

CONCLUSION

Although, we assessed a wide range of patients' characteristics, age had the most negative impact on the quality of sleep in patients with T2DM. We detected more frequent use of hypnotics in older females, with coexisting nephropathy.

Depressive symptoms mediate the relationship between sleep disturbances and type 2 diabetes mellitus

BACKGROUND

The current study aimed at examining whether individuals diagnosed with type 2 diabetes mellitus (T2DM) have more severe sleep disturbances compared to individuals who are healthy or have prediabetes and whether depressive symptoms mediate the relationship between sleep disturbances and having T2DM.

METHODS

T2DM patients (n = 107) were compared to individuals with prediabetes (n = 48) and healthy individuals (n = 154) regarding the severity of depressive symptoms, measured via the Beck Depression Inventory-II (BDI-II), and sleep disturbances, measured via the Mini Sleep Questionnaire (MSQ). Mediation analysis examined whether depressive symptoms mediated the relationship between sleep disturbances and T2DM.

RESULTS

Compared to healthy individuals and individuals with prediabetes, T2DM patients had more depressive symptoms and higher levels of insomnia, hypersomnia, and overall more sleep disturbances. The prediabetes group did not differ from the healthy control group on these measures, and these groups were thus combined for further analysis. Sleep disturbances were correlated with severity of depressive symptoms (r =0.43). After controlling for age, gender, and ethnic background, both severity of sleep disturbances (odds ratio [OR]: 1.04; 95% CI: 1.01-1.07, P <.001) and severity of depressive symptoms (OR: 8.54, 95% CI: 3.37-21.69, P <.001) predicted T2DM. Depression symptoms mediated the relationship between sleep disturbances and T2DM, whereas the direct relationship between sleep disturbances and T2DM was nonsignificant.

CONCLUSIONS

The findings imply that sleep disturbances may contribute to the development and progression of T2DM by promoting depressive symptoms. Thus, treatments for the emotional distress associated with sleep disturbances may help reduce the risk for T2DM and the progression of the disease.

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.

Psychological resilience moderates influence of depression on sleep dysfunction of people living with diabetes

OBJECTIVES

The study examined the influence of depression on sleep dysfunction in people living with diabetes mellitus and investigated the moderating role of psychological resilience on the influence of depression on sleep dysfunction of patients.

METHODS

A cross-sectional survey was carried out among 380 (age 25-77 years; mean = 38.6; SD = 6.07) people living with diabetes who are registered patients and were attending the clinic in Department of Endocrinology, Ondo State Specialist Hospital, Akure.

RESULTS

Results showed that depression significantly influence sleep dysfunction of people living with diabetes, β = 0.3991, 95% CI (0.5393, 0.2588), t = 21.5010, p < 0.005. Results also showed significant moderating role of psychological resilience on the influence depression on sleep dysfunction of people living with diabetes, β = 0.7805, 95% CI (0.7091, 0.8519), t = 21.5010, p < 0.005.

CONCLUSIONS

Sleep dysfunction of individuals living with diabetes as result of their level of depression could be moderated by patient's level of psychological resilience. Along these lines, the study concludes that experts should focus more on diabetes patient's psychological resilience adequacy in their management, guidance and modification programs.

Relationship between subjective sleep disturbances and glycaemia in Chinese adults with type 2 diabetes: findings from a 1.5-year follow-up study

We wanted to determine whether subjective sleep disturbance was associated with serum glycated hemoglobin (HbA1c) in people with type 2 diabetes mellitus. In total, 944 randomly-selected people with diabetes completed the Chinese version of the Pittsburgh Sleep Quality Index (PSQI). Participants' glycaemia was assessed using HbA1c in March 2016 and September 2017. The PSQI score and the change in score(△PSQI), and the HbA1c and its change (△HbAlc) were analysed by sex and age (30-45, 46-60, 61-75, and 76-89 years). Associations between time point PSQI and △PSQI with static HbA1c and △HbA1c were analysed using multiple linear regression. The results showed subjective sleep disturbance among people with diabetes was not correlated with serum HbAlc (β coefficient = 0.032, P = 0.103). However, cross-sectional multiple linear regression showed the relationship was present in women (β coefficient = 0.163, P < 0.01). In multiple linear regression, △PSQI score was correlated with △HbAlc value (β coefficient = 0.142, P < 0.01). The regression coefficient (β) for the relationship between △PSQI score and △HbA1c in men was greater than that in women, and for age was β_61-75years < β_46-60years < β_30-45years. The strongest relationship between △PSQI and △HbA1c was in men aged 30-45 years (β = 0.452, P < 0.01). Subjective sleep disturbance among people with diabetes was not related to glycaemic status in the whole sample, but there was a correlation in women. The change in subjective sleep disturbance correlated with the change in glycaemia, most strongly in younger participants, especially men aged 30-45 years.

Epidemiological and pathophysiological evidence supporting links between obstructive sleep apnoea and Type 2 diabetes mellitus

Obstructive sleep apnoea (OSA) and Type 2 diabetes mellitus (T2DM) are common diseases. The global prevalence of OSA is between 2% and 7% in general population cohorts. The worldwide prevalence of T2DM among adults (aged 20-79 years) was estimated to be 6.4%. The concurrent presence of OSA and T2DM can be expected in the same patient, given their high prevalence and similar predisposition. We reviewed the overlapping pathophysiology of OSA and T2DM in this article.

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.

Obstructive Sleep Apnea, Sleepiness, and Glycemic Control in Type 2 Diabetes

STUDY OBJECTIVES

Self-reported sleepiness is common in patients with obstructive sleep apnea (OSA) and is being increasingly recognized as an effect modifier of the association between OSA and cardiovascular outcomes. However, data on whether sleepiness modifies the association between OSA and glycemic outcomes are lacking. The current study sought to characterize the association between glycemic control and sleepiness in people with OSA and type 2 diabetes.

METHODS

Adults with non-insulin requiring type 2 diabetes and undiagnosed moderate to severe OSA were recruited from the community. Demographic data, Epworth Sleepiness Scale (ESS), hemoglobin A1c (HbA1c), as well a type III home sleep test were obtained. The association between self-reported sleepiness and glycemic control was examined using quantile regression.

RESULTS

The study cohort included 311 participants with 56% of the sample being men. Stratified analyses by sex demonstrated that self-reported sleepiness was associated with a higher HbA1c level, but this association was present only in men with a body mass index (BMI) < 35 kg/m². Mean HbA1c levels were higher by 0.57% (95% confidence interval: 0.11, 1.02) in men with an ESS ≥ 11 compared to men with an ESS < 11. No such association was observed in men with a BMI ≥ 35 kg/m² or in women of any BMI category.

CONCLUSIONS

The association between self-reported sleepiness and glycemic control in people with type 2 diabetes and moderate to severe OSA varies a function of BMI and sex. The noted differences in association should be considered when assessing possible treatment effects of therapy for OSA on metabolic outcomes.

Interactions between and Shared Molecular Mechanisms of Diabetic Peripheral Neuropathy and Obstructive Sleep Apnea in Type 2 Diabetes Patients

Type 2 diabetes (T2D) accounts for about 90% of all diabetes patients and incurs a heavy global public health burden. Up to 50% of T2D patients will eventually develop neuropathy as T2D progresses. Diabetic peripheral neuropathy (DPN) is a common diabetic complication and one of the main causes of increased morbidity and mortality of T2D patients. Obstructive sleep apnea (OSA) affects over 15% of the general population and is associated with a higher prevalence of T2D. Growing evidence also indicates that OSA is highly prevalent in T2D patients probably due to diabetic peripheral neuropathy. However, the interrelations among diabetic peripheral neuropathy, OSA, and T2D hitherto have not been clearly elucidated. Numerous molecular mechanisms have been documented that underlie diabetic peripheral neuropathy and OSA, including oxidative stress, inflammation, endothelin-1, vascular endothelial growth factor (VEGF), accumulation of advanced glycation end products, protein kinase C (PKC) signaling, poly ADP ribose polymerase (PARP), nitrosative stress, plasminogen activator inhibitor-1, and vitamin D deficiency. In this review, we seek to illuminate the relationships among T2D, diabetic peripheral neuropathy, and OSA and how they interact with one another. In addition, we summarize and explain the shared molecular mechanisms involved in diabetic peripheral neuropathy and OSA for further mechanistic investigations and novel therapeutic strategies for attenuating and preventing the development and progression of diabetic peripheral neuropathy and OSA in T2D.

The relationship between sleep disturbance and glycaemic control in adults with type 2 diabetes: An integrative review

AIMS AND OBJECTIVES

To explore and synthesise current research to assess the state of science about the relationship between sleep disturbance and glycaemic control in adults with type 2 diabetes.

BACKGROUND

Sleep disturbance is suggested a risk factor for type 2 diabetes. Diabetes alone is a leading cause of death, but when coupled with sleep disturbance poses additional health risks. However, little is known about the relationship between sleep disturbance and glycaemic control in people with overt diabetes.

DESIGN

An integrative review.

METHODS

Whittemore and Knafl's methodology guided this integrative review. Original studies published before October 2016 were identified through systematic searches of seven databases using terms: diabet*; sleep or insomnia; glycem* or glucose or A1C or HbA1c or sugar; and their combinations. The matrix and narrative synthesis were employed to organise and synthesise the findings, respectively. The Crowe Critical Appraisal Tool was used to evaluate the study quality.

RESULTS

A total of 26 studies were identified; 17 of which reported significant relationships between sleep measures and glycaemic control. In 13 studies, sleep duration was associated with glycaemic control in both linear (n = 2) and nonlinear (n = 3) relationships; however, eight studies reported no significant relationships. Sleep quality was significantly related to glycaemic control in 14 of 22 studies. Nine studies found no relationship between any measure of sleep and glycaemic control.

CONCLUSIONS

There is strong evidence supporting the relationship between sleep quality and glycaemic control but further examination of the relationship between sleep duration and glycaemic control is warranted. Sleep disturbance, particularly impaired sleep quality, could potentially influence glycaemic control in adults with type 2 diabetes.

RELEVANCE TO CLINICAL PRACTICE

Nurses who treat patients with diabetes should include assessment of sleep, education for healthy sleep, and referral for treatment of sleep disturbance in order to maximise the potential for achieving good glycaemic control.

Sleep disturbance in people with diabetes: A concept analysis

AIMS AND OBJECTIVES

To clarify the meaning of sleep disturbance in people with diabetes and examine its antecedents, attributes and consequences through concept analysis.

BACKGROUND

Sleep is crucial for health, and people with diabetes are frequently beset with disturbances in their sleep. The concept of sleep disturbance in people with diabetes has not been clearly defined. The inconsistent use of sleep disturbance has created confusion and impeded our understanding of the sleep in people with diabetes. This analysis will provide a conceptual foundation of sleep disturbance in diabetes, thereby facilitating more effective means for assessment and treatment.

DESIGN

Concept analysis.

METHODS

A systematic search without time restriction on the publication year was carried out using PubMed, CINAHL, PsycINFO, Web of Science and ProQuest Dissertations and Theses. Rodgers's method of evolutionary concept analysis guided the analysis. Inductive thematic analysis was conducted to identify the attributes, antecedents and consequences.

RESULTS

Based on the 26 eligible studies, two major attributes are that sleep disturbance is a symptom and is characterised by impaired sleep quality and/or abnormal sleep duration. Two antecedents are diabetes-related physiological change and psychological well-being. Sleep disturbance can result in impaired daytime functioning, glucose regulation and quality of life.

CONCLUSIONS

Defining the concept of sleep disturbance in people with diabetes facilitates consistent use and effective communication in both practice and research. Sleep disturbance in people with diabetes is a complex symptom that includes impaired sleep quality and/or abnormal sleep duration. This paper contributes to the current knowledge of sleep in people with diabetes. Future research on antecedents and consequences of sleep disturbance is necessary for further clarifications.

RELEVANCE TO CLINICAL PRACTICE

Findings from this paper underscore the need for nursing education, clinical assessment and effective management of sleep disturbance in people with diabetes.

Factors associated with diabetes-related distress over time among patients with T2DM in a tertiary hospital in Singapore

BACKGROUND

Persistent diabetes-related distress (DRD) is experienced by patients with Type 2 Diabetes Mellitus. Knowing factors associated with persistent DRD will aid clinicians in prioritising interventions efforts.

METHODS

A total of 216 patients were recruited from a tertiary hospital in Singapore, an Asian city state, and followed for 1.5 years (2011-2014). Data was collected by self-completed questionnaires assessing DRD (measured by the Problem Areas in Diabetes score) and other psychosocial aspects such as social support, presenteeism, depression, health-related quality of life (HRQoL) and excessive daytime sleepiness (EDS) at three time points. Clinical data (body-mass-index and glycated haemoglobin) was obtained from medical records. Change score was calculated for each clinical and psychosocial variable to capture changes in these variables from baseline. Generalized Linear Model with Generalized Estimating Equation method was used to assess whether baseline and change scores in clinical and psychosocial are associated with DRD over time.

RESULTS

Complete data was available for 73 patients, with mean age 44 (SD 12.5) years and 67% males. Persistent DRD was experienced by 21% of the patients. In the final model, baseline HRQoL (OR = 0.56, p < 0.05) and change score of EDS (OR = 1.22, p < 0.05) was significantly associated with DRD over time.

CONCLUSIONS

EDS might be a surrogate marker for persistent DRD and should be explored in larger samples of population to confirm the findings from this study.

HbA1c levels are associated with severity of hypoxemia and not with apnea hypopnea index in patients with type 2 diabetes: Results from a cross-sectional study

BACKGROUND

The aim of the present study was to evaluate the effect of untreated sleep apnea syndrome (SAS) on glycemic control, evaluated by HbA1c, in patients with type 2 diabetes (T2D).

METHODS

The study sample consisted of 100 consecutive adult (≥18 years) patients with T2D without a prior diagnosis of sleep apnea recruited from an outpatient diabetes clinic. All patients underwent an in-hospital cardiorespiratory study using a three-channel portable sleep diagnostic tool; 64 were found to have sleep apnea, 36 were not. Information on medical history, body weight, height, sleep apnea symptoms, Epworth Sleepiness Scale scores, and HbA1c and fasting plasma glucose levels were recorded.

RESULTS

After adjusting for factors known to affect HbA1c (gender, age, diabetes duration, diabetes treatment, body mass index [BMI], and waist circumference), HbA1c was higher in patients with than without SAS (8.4 % vs 7.6 %, respectively; P = 0.04). A positive correlation was found between the presence of sleep apnea and HbA1c (r = 0.24; P = 0.02). After adjusting for confounding factors (including BMI), only mean and lowest O2 saturation during sleep were significantly associated with HbA1c (β = -0.23 [P = 0.03] and β = -0.24 [P = 0.007], respectively). After further adjusting for waist circumference, only lowest O2 saturation during recording remained independently associated with HbA1c (β = -0.21; P = 0.05).

CONCLUSIONS

The presence of sleep apnea is associated with poorer glycemic control in patients with T2D. In patients with sleep apnea and T2D, greater levels of oxygen desaturation are associated with poorer glycemic control.

Pharmacotherapy of 'treatment resistant' type 2 diabetes

INTRODUCTION

Despite type 2 diabetes (T2D) management offers a variety of pharmacological interventions targeting different defects, numerous patients remain with persistent hyperglycaemia responsible for severe complications. Unlike resistant hypertension, treatment resistant T2D is not a classical concept although it is a rather common observation in clinical practice. Areas covered: This article proposes a definition for 'treatment resistant diabetes', analyses the causes of poor glucose control despite standard therapy, briefly considers the alternative approaches to glucose-lowering pharmacotherapy and finally describes how to overcome poor glycaemic control, using innovative oral or injectable combination therapies. Expert opinion: Before considering intensifying the pharmacotherapy of a patient with poorly controlled T2D, it is important to verify treatment adherence, target obesity and consider various non pharmacological improvement quality interventions. If treatment resistant diabetes is defined as not achieving glycated haemoglobin target despite oral triple therapy with a third glucose-lowering agent added to metformin-sulfonylurea dual treatment, the combination of a dipeptidyl peptidase-4 (DPP-4) inhibitor and a sodium glucose cotransporter type 2 (SGLT2) inhibitor may offer new opportunities before considering injectable therapies. Insulin basal therapy (± metformin) may be optimized by the addition of a SGLT2 inhibitor or a glucagon-like peptide-1 (GLP-1) receptor agonist.

Torque and Muscle Activation Impairment Along With Insulin Resistance Are Associated With Falls in Women With Fibromyalgia

Góes, SM, Stefanello, JMF, Homann, D, Lodovico, A, Hubley-Kozey, CL, and Rodacki, ALF. Torque and muscle activation impairment along with insulin resistance are associated with falls in women with fibromyalgia. J Strength Cond Res 30(11): 3155-3164, 2016-Fibromyalgia (FM) is a chronic pain condition associated with reduced muscle strength, which can lead to functional incapacity and higher risk of falls. The purpose of the study was to compare maximal ankle joint torque, muscle activation, and metabolic changes between women with and without FM. In addition, the relationship between those aspects and retrospectively reported falls in women with FM was determined. Twenty-nine middle-aged women with FM and 30 controls were recruited. Fall history, pain intensity, and pain threshold were assessed. Plasma glucose levels and insulin resistance (IR) were determined. Peak torque and rate of torque development (RTD) were calculated, and muscle activation was assessed from maximum isometric voluntary ankle dorsiflexion and plantar flexion contractions. In addition, voluntary muscle activation failure of the anterior tibialis muscle during maximal dorsiflexion was calculated. When compared to controls, women with FM reported higher number of retrospectively reported falls, exhibited higher IR, showed reduced plantar flexion and dorsiflexion RTD, had lower plantar flexion peak torque, and demonstrated more antagonist coactivation and higher muscle activation failure (p ≤ 0.05). Higher muscle activation failure was explained by glucose level and pain intensity (adj R = 0.28; p ≤ 0.05). Reduced plantar flexion and dorsiflexion peak torque explained 80% of retrospectively reported falls variance; also, high antagonist coactivation (odds ratio [OR] = 1.6; p ≤ 0.05) and high IR (OR = 1.8; p ≤ 0.05) increased the chance of falls in the FM group. A combination of metabolic factors and muscle function increased the odds of retrospectively reporting a fall in FM. Both aspects may be considered in interventions designed for reducing falls in this population.