Disturbed sleep in type 2 diabetes mellitus independent of chronic complications, pain, and nocturia

The prevalence of obstructive sleep apnea in patients with type 2 diabetes: a systematic review and meta-analysis

Background

Obstructive Sleep Apnea (OSA) is one of the diseases related to diabetes. Considering the varying prevalence of OSA in patients with type 2 diabetes in different parts of the world, in order to aggregate the results and come to a general review about the topic mentioned, the current study performed a systematic review and meta-analysis of OSA in patients with type 2 diabetes.

Methods

In this study, the international databases (PubMed, Scopus, Web of science, and Cochran library) were searched without time limit using keywords diabetes, obstructive sleep apnea, and prevalence or epidemiology. Homogeneity was investigated among studies using Cochran Q test and I2 index. Given the heterogeneity of studies, random effect model was used to estimate the prevalence of OSA. Meta-regression was used to investigate the effect of quantitative variables on the prevalence of OSA. Comprehensive Meta-analysis (CMA) software was used for data analysis.

Results

Twenty studies were included in the meta-analysis. In these 19 studies, the total number of patients with type 2 diabetes was 10,754, with a mean age of 58.6 ± 4.1 years. Final estimation of OSA prevalence was calculated to be 56.0%. The results of meta-regression showed the prevalence of OSA increased with a rise in the mean age, the percentage of male sex, body mass index, and sample size.

Conclusion

Given the high prevalence of OSA in patients with type 2 diabetes, weight control can partly mitigate their problems and possibly reduce OSA prevalence.

Sleep Quality among Patients with Type 2 Diabetes: A Cross-Sectional Study in the East Coast Region of Peninsular Malaysia

Poor sleep is related to type 2 diabetes and adversely influences a person’s quality of life. This study aimed to evaluate sleep quality in patients with type 2 diabetes (T2DM), its associated factors, and its relationship with quality of life. A cross-sectional study was conducted at a primary care clinic in a tertiary hospital on the east coast of Malaysia. This study included 350 participants (175 men and 175 women). Data were collected using the Malay version of the Pittsburgh Sleep Quality Index (PSQI-M) with a cut-off point of >5 as poor sleep, the Malay version of Diabetes Distress Scale (MDDS-17) and the revised Malay version of T2DM-related quality of life (Rv-DQOL). Statistical analysis was conducted using the SPSS software version 26.0. The respondents’ median (interquartile range (IQR)) age was 62.0 (11.0) years, and poor sleep was reported in 32% (95% confidence interval (CI) = 27.1, 36.9) of the participants. Multivariate logistic regression analysis revealed that poor sleep quality was significantly associated with nocturia (odds ratio (OR) = 2.04; 95% CI = 1.24, 3.35), restless legs syndrome (OR = 2.17; 95% CI = 1.32−3.56) and emotional burden (OR = 2.37; 95% CI = 1.41−3.98). However, no statistically significant association was observed between sleep quality and quality of life among our participants.

Intra-individual variability in sleep is related to glycaemic control in adults with type 2 diabetes

AIMS

To examine whether there were significant differences in sleep during weekdays/weekends and whether the intra-individual variability in sleep was related to glycaemic control in patients with type 2 diabetes.

DESIGN

Correlational, longitudinal design.

METHODS

Data were collected between February 2017-January 2018. In all, 56 adults with type 2 diabetes were included (60.7 years, 55.4% female). Sleep was measured using the Consensus Sleep Diary over 8 days. Intra-individual variability of sleep was calculated as the standard deviation of sleep variables. Standard deviations of sleep duration, sleep efficiency, sleep quality, and mid-sleep time were obtained. Glycaemic control was measured by haemoglobin A1C. Paired t test and multiple regression analysis were used.

RESULTS

Overall, there were no differences in sleep parameters between weekdays and weekends. Participants slept 20 min more over the weekends than during weekdays. The mid-sleep time during weekends was about 35 min later than during weekdays. Intra-individual variability of sleep duration and mid-sleep ranged from 27.6-167.4 min and 13-137 min, respectively. Controlling for covariates (e.g., distress, symptoms, and self-care), larger variability in sleep duration, and mid-sleep were significantly related to higher A1C levels.

CONCLUSION

Diabetes educators are recommended to include the assessment of intra-individual variability in sleep. Maintaining a regular sleep habit (e.g., sleep duration and sleep timing) should be highlighted during patient education.

IMPACT

Intra-individual variability in sleep is an alternative dimension for sleep assessment. This study examined whether intra-individual variability in sleep was related to glycaemic control in an older sample of type 2 diabetes patients using a sleep diary across 8 days. This sample had a similar sleep pattern during weekdays and weekends. Larger intra-individual variabilities in sleep duration and mid-sleep time were independently related to worse glycaemic control. Diabetes patients are recommended to maintain a regular sleep routine.