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

Association of sleep quality with glycemic variability assessed by flash glucose monitoring in patients with type 2 diabetes

BACKGROUND

Deterioration of sleep quality has been reported to contribute to the incidence of diabetes and may be responsible for glycemic status in diabetes. The present study explored the relationship between sleep quality and glycemic variability in patients with type 2 diabetes (T2D).

METHODS

We recruited 111 patients with T2D for this cross-sectional study. Each patient underwent flash glucose monitoring for 14 days to obtain glycemic variability parameters, such as standard deviation of glucose (SD), coefficient of variation of glucose (CV), mean amplitude of glycemic excursions (MAGE), mean of daily differences (MODD), and time in glucose range of 3.9-10 mmol/L (TIR_3.9-10). After 14 days of flash glucose monitoring, each patient received a questionnaire on the Pittsburgh Sleep Quality Index (PSQI) to evaluate subjective sleep quality. HbA1c was also collected to assess average glucose.

RESULTS

HbA1c was comparable among the subgroups of PSQI score tertiles. Across ascending tertiles of PSQI scores, SD, CV and MAGE were increased, while TIR_3.9-10 was decreased (p for trend  <  0.05), but not MODD (p for trend  =  0.090). Moreover, PSQI scores were positively correlated with SD, CV, MODD and MAGE (r =  0.322, 0.361, 0.308 and 0.354, respectively, p  <  0.001) and were inversely correlated with TIR_3.9-10 (r  =  - 0.386, p  <  0.001). After adjusting for other relevant data by multivariate linear regression analyses, PSQI scores were independently responsible for SD (β  =  0.251, t  =  2.112, p  =  0.041), CV (β  =  0.286, t  =  2.207, p  =  0.033), MAGE (β  =  0.323, t  =  2.489, p  =  0.018), and TIR_3.9-10 (β  =  - 0.401, t  =  - 3.930, p  <  0.001) but not for MODD (β  =  0.188, t  =  1.374, p  =  0.177).

CONCLUSIONS

Increased glycemic variability assessed by flash glucose monitoring was closely associated with poor subjective sleep quality evaluated by the PSQI in patients with T2D.

Effects of cognitive behavioral therapy on sleep disturbances and quality of life among adults with type 2 diabetes mellitus: A randomized controlled trial

BACKGROUND AND AIMS

Cognitive behavioral therapy (CBT) is recommended as the first-line nonpharmacotherapy for sleep complaints. However, there are no studies that tested CBT for improving sleep quality and increasing quality of life (QOL) in patients with type 2 diabetes mellitus (T2DM). Therefore, this study aims to test the effect of CBT on sleep disturbances and QOL in patients with T2DM.

METHODS AND RESULTS

In total, 187 participants with T2DM and comorbid poor sleep quality were included in the analysis with the control group of 93 receiving usual care (UC) only and the intervention group of 94 receiving CBT with aerobic exercise plus UC, The Pittsburgh Sleep Quality Index (PSQI), the Diabetes-Specific Quality of Life Scale (DSQLS) and the glycated hemoglobin (HbA1C) values were collected at baseline, after the 2-month intervention, and 6 months of follow-up. The CBT group had 3.03 points lower PSQI scores (95% confidence interval [CI]: 2.07-4.00, P < 0.001) and 7.92 points lower total DSQLS scores (95% CI: 4.98-10.87, P < 0.001) than the control group after 6-month follow-up. No difference was found in HbAlc between the two groups (t = -0.47, P = 0.64) after 2-month intervention, while the CBT group had 0.89 units lower HbAlc (95% CI: 0.49-1.28, P < 0.001) than the control group after 6-month follow-up.

CONCLUSION

CBT is effective for sleep disturbances and can also improve sleep quality, increase QOL, and decrease glycemic levels in participants with T2DM.

TRIAL REGISTRATION

Chinese Clinical Trials Registration (Practical study of the appropriate technique for improvement of quality of life of the patients with type 2 diabetes in communities: ChiCTR-IOP-16008045).