Sleep characteristics and HbA1c in patients with type 2 diabetes on glucose-lowering medication

Egg consumption, sleep, and mental health status among women with type II diabetes

To evaluate if egg consumption is associated with sleep quality and psychological health (depression, anxiety, and stress) in women with type 2 diabetes. A cross-sectional study was conducted on women with type 2 diabetes (n = 230). Weight, height, waist circumference (WC), and blood pressure were measured. A Food Frequency Questionnaire (FFQ) was used to obtain dietary intake data and estimate total egg consumption, which was presented in tertiles. The Pittsburgh Sleep Quality Index (PSQI) and Depression, Anxiety, and Stress Scale (DASS-21) were used to evaluate sleep and mental health outcomes, respectively. Dietary intake of carbohydrates, sodium, saturated fatty acids, and cholesterol was greater in the highest tertile of egg consumption (P < 0.05). Dietary intake of fat, monounsaturated, and polyunsaturated fatty acids was lower in the highest tertile of egg consumption (P < 0.05). WC was greater in the highest tertile of egg consumption in the crude model (p = 0.03), however, there was no evidence of this association in the adjusted model. There was no evidence of an association between egg consumption and the odds of poor psychological health or sleep quality in unadjusted or adjusted models. There was no association between egg consumption and poor sleep or mental disorders. Future studies are needed to confirm these findings and to identify the mechanism of action.

Sex and Age Differences in the Effects of Food Frequency on Metabolic Parameters in Japanese Adults

Owing to differences in dietary preferences between men and women, the associations between dietary intake frequency and metabolic parameters may differ between the sexes. A retrospective observational study of the checkup findings of 3147 Japanese individuals (968 men, 2179 women) aged 20-59 years was conducted to examine differences in dietary habits and associations between food frequency and blood parameters (eGFR, HbA1c, uric acid, and lipids) by sex and age. Males were more likely to consume meat, fish, soft drinks, and alcohol, whereas women were more likely to consume soybeans, dairy products, vegetables, fruits, and snacks. Multivariate linear regression models adjusted for age and BMI revealed that meat intake frequency was positively associated with HbA1c (β = 0.007, p = 0.03) and negatively associated with eGFR (β = -0.3, p = 0.01) only in males, whereas fish intake frequency was positively associated with eGFR (β = 0.4, p = 0.005) only in females. Egg and soy intake frequencies were positively and negatively associated with non-HDL-C (egg: β = 0.6, p = 0.02; soy: β = -0.3, p = 0.03) only in females. Alcohol consumption frequency was associated with uric acid (M: β = 0.06, p < 0.001; F: β = 0.06, p < 0.001) and HDL-C (M: β = 1.0, p < 0.001; F: β = 1.3, p < 0.001) in both sexes. Future research is needed to determine whether varying the emphasis of dietary guidance by sex and age group is effective, since the effects of dietary preferences on metabolic parameters vary by age and sex.

Obstructive sleep apnea: Overlooked comorbidity in patients with diabetes

In this review article, we explore the interplay between obstructive sleep apnea (OSA) and type 2 diabetes mellitus (T2DM), highlighting a significant yet often overlooked comorbidity. We delve into the pathophysiological links between OSA and diabetes, specifically how OSA exacerbates insulin resistance and disrupts glucose metabolism. The research examines the prevalence of OSA in diabetic patients and its role in worsening diabetes-related complications. Emphasizing the importance of comprehensive management, including weight control and positive airway pressure therapy, the study advocates integrated approaches to improve outcomes for patients with T2DM and OSA. This review underscores the necessity of recognizing and addressing OSA in diabetes care to ensure more effective treatment and better patient outcomes.

The risk factors for mental health disorders in patients with type 2 diabetes: An umbrella review of systematic reviews with and without meta-analysis

Background

Patients with type 2 diabetes have a nearly twofold higher rate of diagnosed mental disorders than those without diabetes. The association between type 2 diabetes and mental disorders is well established in the literature and recognized as a bidirectional relationship. This study aims to conduct an umbrella review of risk and protective factors for mental health disorders in patients with type 2 diabetes and assess the credibility of the evidence for the association between each factor and mental health disorders.

Methods

A comprehensive search was conducted of Medline via PubMed, Web of Science, EMBASE, CINHAL, and PsycINFO from inception to November 17, 2022, to identify systematic reviews with and without meta-analyses examining associations of factors with mental health disorders in patients with type 2 diabetes. For each association, we recalculated the summary effect size and 95% confidence intervals using random-effects models. We also reported the 95% prediction interval and between-group heterogeneity.

Results

The study included 11 systematic reviews that met the inclusion criteria, comprising eight meta-analyses and three without meta-analyses. This involved approximately 489,930 participants and encompassed 26 unique factors. Six factors were rated as having suggestive evidence at the Class III level. These factors were obesity (n = 18,456, OR 1.75 [1.2 to 2.59], I2 97.7%), neuropathy (n = 3898, OR 2.01 [1.60 to 2.54], I2 44.5%), diabetes complications (n = 1769, OR 1.90 [1.53 to 2.36], I2 39.3%), peripheral blood concentrations of CRP (n = 1742, SMD 0.31 [0.16 to 0.45], I2 84.1%), female sex (n = 35,162, OR 1.36 [1.19 to 1.54], I2 64.5%), and social support (n = 3151, OR 2.02 [1.51 to 2.70], I2 87.2%).

Conclusions

Several factors associated with mental health disorders in patients with type 2 diabetes were identified with varying degrees of supporting evidence. Significantly, obesity, neuropathy, complications, peripheral blood CRP concentrations, female sex, and social support emerged with suggestive evidence. An investigation of these factors should be conducted to target interventions accordingly. It may be helpful to prioritize patients who have these risk factors as high-risk groups and to implement plans and policies to enhance support before mental health disorders occur.

Diabetes status, genetic susceptibility, and incident arrhythmias: A prospective cohort study of 457,151 participants

AIMS

The association of diabetes onset age and duration with incident arrhythmias remains unclear. This study evaluates the association of diabetes onset age and duration with incident arrhythmias and assesses modifications by the genetic predisposition to atrial fibrillation (AF).

METHODS

We included 457,151 participants from the UK Biobank study. Multivariable Cox regression models to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) were used for the association between diabetes status, genetic predisposition, and risk of incident arrhythmias. The polygenic risk score (PRS) for AF comprised 142 single-nucleotide variants.

RESULTS

Over 12 years of follow-up, we documented 23,518 AF, 9079 bradyarrhythmia, 9280 conduction system diseases, 3358 supraventricular arrhythmias, and 3095 ventricular arrhythmias. Compared with non-diabetes, the risks of AF increased by 19%, 25%, and 36% for those with diabetes durations <5, 5-9, and ≥10 years, respectively. After multivariate adjustment, with the increase in diabetes onset age, the HRs of outcomes were gradually attenuated. The multivariable-adjusted HRs (95% CI) of diabetes for AF were 1.46 (1.24-1.71) in early middle age (<55 years), 1.21 (1.12-1.30) in late middle age (55-64 years), and 1.15 (1.06-1.24) in the elderly population (≥65 years). A significant interaction between diabetes status and AF-PRS for incident AF was observed (P for interaction <0.001). The same trends were observed for the other arrhythmias.

CONCLUSIONS

Diabetes was associated with higher risks of incident arrhythmias, and younger age at onset of diabetes was significantly associated with higher risk of subsequent arrhythmias.

Eating habit of adding salt to foods and incident sleep apnea: a prospective cohort study

BACKGROUND

Previous studies have revealed that sodium-restricted diet intervention significantly decreased apnea frequency among patients with sleep apnea. However, the longitudinal association between the habit of adding salt to foods and sleep apnea in general populations is uncertain.

METHODS

The UK Biobank cohort study includes more than 500,000 participants aged 40 to 69 across the United Kingdom from 2006 to 2010. The frequency of adding salt to foods was collected through a touch screen questionnaire. Incident sleep apnea was ascertained by hospital inpatient records, death registries, primary care, and self-reported diagnosis. The association between the habit of adding salt to foods and incident sleep apnea was estimated using Cox proportional hazard regression models.

RESULTS

Among the 488,196 participants (mean age 56.5 years; 55.0% female) in this study. During a median follow-up of 12.3 years, 6394 sleep apnea events occurred. Compared to participants who never/rarely added salt to foods, those who sometimes, usually, and always added salt to foods had an 11% (hazard ratio [HR] 1.11, 95% confidence interval [CI]: 1.04 to 1.17), 15% (HR 1.15, 95% CI: 1.07 to 1.24), and 24% (HR 1.24, 95% CI: 1.12 to 1.37) higher risk for incident sleep apnea, respectively.

CONCLUSIONS

In this large prospective study, the habit of adding salt to foods was associated with a higher risk of incident sleep apnea. The findings support the benefits of a salt reduction program in preventing sleep apnea.

Mendelian randomization reveals no associations of genetically-predicted obstructive sleep apnea with the risk of type 2 diabetes, nonalcoholic fatty liver disease, and coronary heart disease

BACKGROUND

Obstructive sleep apnea (OSA) has been reported to affect cardiometabolic diseases. However, whether such association is causal is still unknown. Here, we attempt to explore the effect of OSA on type 2 diabetes (T2D), nonalcoholic fatty liver disease (NAFLD) and coronary heart disease (CHD).

METHODS

Genetic variants associated with OSA were requested from a published genome-wide association study (GWAS) and those qualified ones were selected as instrumental variables (IV). Then, the IV-outcome associations were acquired from T2D, NAFLD and CHD GWAS consortia separately. The Mendelian randomization (MR) was designed to estimate the associations of genetically-predicted OSA on T2D, NAFLD and CHD respectively, using the inverse-variance weighted (IVW) method. We applied the Bonferroni method to adjust the p-value. Besides, MR-Egger regression and weighted median methods were adopted as a supplement to IVW. The Cochran's Q value was used to evaluate heterogeneity and the MR-Egger intercept was utilized to assess horizontal pleiotropy, together with MR-PRESSO. The leave-one-out sensitivity analysis was carried out as well.

RESULTS

No MR estimate reached the Bonferroni threshold (p < 0.017). Although the odds ratio of T2D was 3.58 (95% confidence interval (CI) [1.06, 12.11], IVW-p-value = 0.040) using 4 SNPs, such causal association turned insignificant after the removal of SNP rs9937053 located in FTO [OR = 1.30 [0.68, 2.50], IVW p = 0.432]. Besides, we did not find that the predisposition to OSA was associated with CHD [OR = 1.16 [0.70, 1.91], IVW p = 0.560] using 4 SNPs.

CONCLUSION

This MR study reveals that genetic liability to OSA might not be associated with the risk of T2D after the removal of obesity-related instruments. Besides, no causal association was observed between NAFLD and CHD. Further studies should be carried out to verify our findings.

No association between a common type 2 diabetes risk gene variant in the melatonin receptor gene (MTNR1B) and mortality among type 2 diabetes patients

The minor G risk allele in the common melatonin receptor gene (MTNR1B, rs10830963) has been associated with an increased risk of myocardial infarction among patients with type 2 diabetes (T2D). Furthermore, activating the melatonin receptor 1B through melatonin has been shown to promote cell proliferation, which could be hypothesized to increase cancer risk. Cardiovascular disease (CVD) and cancer are common causes of death among patients with T2D. Using data from 14 736  patients with T2D who participated in the UK Biobank investigation, we hypothesized an additive effect of the G risk allele on all-cause mortality, CVD mortality, and cancer mortality. As shown by Cox regression adjusted for confounders such as age, glucose-lowering medication, and socioeconomic status, no significant trend between the number of G risk alleles and mortality outcomes was found during the follow-up period of 11.1 years. Our negative findings do not speak against the role of this gene variant in the development of T2D, as repeatedly shown by previous large-scale studies. Instead, they may suggest that rs10830963 is less relevant for mortality risk in patients with T2D.

Association of Sleep Patterns and Lifestyles With Incident Hypertension: Evidence From a Large Population-Based Cohort Study

Background

Adherence to a healthy lifestyle (no smoking, consuming a healthy diet, engaging in physical activity, and maintaining a healthy weight) is recommended in current guidelines for hypertension prevention. However, evidence regarding the association between sleep behaviors, independently and jointly with traditional lifestyle factors, and the risk of hypertension is limited.

Methods

This prospective study included 165,493 participants who are free of hypertension at baseline from the UK Biobank. Sleep behaviors, including chronotype, sleep duration, insomnia, snoring, and daytime sleepiness were used to construct a healthy sleep score. We also derived a healthy lifestyle score based on smoking status, diet quality, physical activity, and body mass index (BMI). Cox proportional hazards regression models and competing risk analyses were used to estimate the associations of the healthy sleep score and healthy lifestyle score with the risk of hypertension. The population attributable risk percent (PAR%) was estimated for increased cases of hypertension due to poor adherence to a healthy sleep pattern or a healthy lifestyle.

Results

A total of 10,941 incident hypertension cases were documented during a median of 11.8 years of follow-up. The multivariable-adjusted hazard ratio (HR) for hypertension was 0.58 [95% confidence interval (CI): 0.52, 0.65] for participants with a sleep score of 5 compared with 0-1, and 0.48 (95% CI: 0.43, 0.54) for participants with a lifestyle score of 4 compared with those who scored 0. For joint association, those with a poor sleep pattern and a poor lifestyle had the highest risk of hypertension [HR: 2.41 (95% CI: 2.12, 2.74)]. PAR% was 14.7% (95% CI: 12.3%, 17.1%), 20.1% (95% CI: 17.6%, 22.6%), and 31.7% (95% CI: 27.6%, 35.6%) for poor adherence to a healthy sleep pattern, a healthy lifestyle, and the combination of a healthy sleep pattern and a healthy lifestyle.

Conclusion

Both a healthy sleep pattern and a healthy lifestyle were associated with a lower risk of hypertension, and the benefits of adhering to a healthy sleep pattern complement the well-established lifestyle for the optimal primary prevention of hypertension. These findings support the current perspective that a healthy sleep pattern is an important part of a healthful and productive lifestyle for hypertension prevention.

Associations of Insomnia With Hypertension and Coronary Artery Disease Among Patients With Type 2 Diabetes Mellitus

Purpose: This study aimed to determine whether insomnia is associated with hypertension (HBP) and coronary artery disease (CAD) in a hospital-based sample of patients with type 2 diabetes mellitus (T2DM).

Methods: Our present study included 354 patients with T2DM. According to the diagnostic criteria of insomnia, the participants were assigned to three groups based on the duration of T2DM and insomnia diagnosis. Patients with T2DM alone were placed in group A; patients with T2DM longer than insomnia were placed in group B; and patients with insomnia longer than T2DM were placed in group C. Medical history was collected from all the patients in detail. Besides, the participants underwent thorough physical examinations and laboratory measurements. Propensity score matching (PSM) was applied to evaluate the associations of insomnia with HBP and CAD. The univariate and multivariate logistic regression analysis was used to explore whether insomnia was a risk factor for HBP and CAD in patients with T2DM.

Results: Of 354 patients, 225 patients were included in group A, 62 patients were included in group B, and 67 patients were included in group C. Compared with groups B and C, group A showed a lower prevalence of HBP and CAD (p < 0.05). In addition, compared with group B, group C showed no difference in the prevalence of HBP and CAD (p > 0.05). After PSM was performed, groups B and C had a higher prevalence of HBP and CAD (p < 0.05) than group A with no significant difference between groups B and C (p > 0.05). In the univariate and multivariate logistic regression analysis, insomnia was a risk factor for HBP [univariate: odds ratio (OR) = 3.376, 95% CI 2.290–6.093, p < 0.001; multivariate: OR = 2.832, 95% CI 1.373–5.841, p = 0.005] and CAD (univariate: OR = 5.019, 95% CI 3.148–8.001, p < 0.001; multivariate: OR = 5.289, 95% CI 2.579–10.850, p < 0.001).

Conclusion: T2DM combined with insomnia was related to HBP and CAD and insomnia was a risk factor for HBP and CAD in patients with T2DM. However, larger, prospective studies are required to confirm our findings.

Postprandial glucose and HbA1c are associated with severity of obstructive sleep apnoea in non-diabetic obese subjects

INTRODUCTION

Obstructive sleep apnoea (OSA) is an underdiagnosed condition frequently associated with glycaemic control impairment in patients with type 2 diabetes.

AIM

To assess the relationship between glycometabolic parameters and OSA in obese non-diabetic subjects.

METHODS

Ninety consecutive subjects (mean age 44.9 ± 12 years, mean BMI 42.1 ± 9 kg/m²) underwent polysomnography and a 2-h oral glucose tolerance test (OGTT).

RESULTS

OSA was identified in 75% of subjects, with a higher prevalence of males compared to the group of subjects without OSA (62% vs 32%, p = 0.02). Patients with OSA had comparable BMI (42.8 kg/m² vs 39.4 kg/m²), a higher average HbA1c (5.8% vs 5.4%, p < 0.001), plasma glucose at 120 min during OGTT (2 h-PG; 123 mg/dl vs 97 mg/dl, p = 0.009) and diastolic blood pressure (81.1 mmHg vs 76.2 mmHg, p = 0.046) than obese subjects without OSA. HbA1c and 2 h-PG were found to be correlated with the apnoea-hypopnoea index (AHI; r = 0.35 and r = 0.42, respectively) and with percent of sleep time with oxyhaemoglobin saturation < 90% (ST90; r = 0.44 and r = 0.39, respectively). Further, in a linear regression model, ST90 and AHI were found to be the main determinants of 2 h-PG (β = 0.81, p < 0.01 and β = 0.75, p = 0.02, respectively) after controlling for age, sex, waist circumference, physical activity, and C-reactive protein. Similarly, ST90 and AHI persisted as independent determinants of HbA1c (β = 0.01, p = 0.01 and β = 0.01, p = 0.01, respectively).

CONCLUSION

Beyond the traditional clinical parameters, the presence of a normal-high value of 2 h-PG and HbA1c should raise suspicion of the presence of OSA in obese subjects.

Factors associated with stroke among patients with type 2 diabetes mellitus in China: a propensity score matched study

OBJECTIVE

This study aimed to examine the prevalence of stroke and associated factors of stroke in patients with type 2 diabetes(T2DM) in China.

METHODS

Participants were 18,013 T2DM patients recruited with stratified random cluster sampling method from December 2013 to January 2014 in China. Propensity score matching was used to eliminate confounding effects between groups and logistic regression analysis was used to examine factors associated with stroke among T2DM patients.

RESULTS

Overall, the prevalence of stroke in the subjects with T2DM was 9.5%. After nearest neighbor matching, smoking (OR = 1.60, 95%CI: 1.26-2.03), hypertension (OR = 2.96, 95%CI: 2.55-3.43), dyslipidemia (OR = 2.00, 95%CI: 1.71-2.33), family history of stroke (OR = 2.02, 95%CI: 1.61-2.54), obesity (OR = 1.21, 95%CI: 1.01-1.45) and sleep duration < 6 h/day (OR = 1.44, 95%CI: 1.20-1.73) or > 8 h/day (OR = 1.22, 95%CI: 1.05-1.42) were positively associated with stroke, whereas drinking 1-3 days/week (OR = 0.64, 95%CI: 0.45-0.90) or daily (OR = 0.45, 95%CI: 0.33-0.60), effective exercise (OR = 0.65, 95%CI: 0.57-0.73) and underweight (OR = 0.30, 95%CI: 0.13-0.71) were negatively related to stroke. Besides, the risk of stroke increased substantially with accumulation of above seven modified risk factors. The odds ratio values of stroke in patients having ≥ 5 of the above seven risk factors was 14.39 (95% CI: 8.87-23.26).

CONCLUSIONS

The prevalence of stroke was high among T2DM in China. It is of great significance to strengthen comprehensive management of health-related behaviors including smoking cessation, moderate alcohol consumption, effective exercise, 6-8 h of sleep duration, keeping normal weight and the prevention of hypertension and dyslipidemia to have sustained beneficial effects on improvements of stroke risk factors.

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.

Oral Antidiabetics and Sleep Among Type 2 Diabetes Patients: Data From the UK Biobank

Previous small-scale studies have found that oral antidiabetic therapy is associated with sleep difficulties among patients with type 2 diabetes (T2D). Here, we used data from 11 806 T2D patients from the UK Biobank baseline investigation to examine the association of oral antidiabetic therapy with self-reported difficulty falling and staying asleep and daily sleep duration. As shown by logistic regression adjusted for, e.g., age, T2D duration, and HbA_1c, patients on non-metformin therapy (N=815; 86% were treated with sulphonylureas) had a 1.24-fold higher odds ratio of reporting regular difficulty falling and staying asleep at night compared to those without antidiabetic medication use (N=5 366, P<0.05) or those on metformin monotherapy (N=5 625, P<0.05). Non-metformin patients reported about 8 to 10 minutes longer daily sleep duration than the other groups (P<0.05). We did not find significant differences in sleep outcomes between untreated and metformin patients. Our findings suggest that non-metformin therapy may result in sleep initiation and maintenance difficulties, accompanied by a small but significant sleep extension. The results of the present study must be replicated in future studies using objective measures of sleep duration and validated questionnaires for insomnia. Considering that most T2D patients utilize multiple therapies to manage their glycemic control in the long term, it may also be worth investigating possible interactions of antidiabetic drugs on sleep.