The association between sleep efficiency and diabetes mellitus in community-dwelling individuals with or without sleep-disordered breathing

Waking Up to the Importance of Sleep in Type 2 Diabetes Management: A Narrative Review

For the first time, the latest American Diabetes Association/European Association for the Study of Diabetes (ADA/EASD) consensus guidelines have incorporated a growing body of evidence linking health outcomes associated with type 2 diabetes to the movement behavior composition over the whole 24-h day. Of particular note, the importance of sleep as a key lifestyle component in the management of type 2 diabetes is promulgated and presented using three key constructs: quantity, quality, and timing (i.e., chronotype). In this narrative review we highlight some of the key evidence justifying the inclusion of sleep in the latest consensus guidelines by examining the associations of quantity, quality, and timing of sleep with measures of glycemia, cardiovascular disease risk, and mortality. We also consider potential mechanisms implicated in the association between sleep and type 2 diabetes and provide practical advice for health care professionals about initiating conversations pertaining to sleep in clinical care. In particular, we emphasize the importance of measuring sleep in a free-living environment and provide a summary of the different methodologies and targets. In summary, although the latest ADA/EASD consensus report highlights sleep as a central component in the management of type 2 diabetes, placing it, for the first time, on a level playing field with other lifestyle behaviors (e.g., physical activity and diet), the evidence base for improving sleep (beyond sleep disorders) in those living with type 2 diabetes is limited. This review should act as a timely reminder to incorporate sleep into clinical consultations, ongoing diabetes education, and future interventions.

Sleep Efficiency and Sleep Onset Latency in One Saskatchewan First Nation

BACKGROUND

Sleep efficiency and sleep onset latency are two measures that can be used to assess sleep quality. Factors that are related to sleep quality include age, sex, sociodemographic factors, and physical and mental health status. This study examines factors related to sleep efficiency and sleep onset latency in one First Nation in Saskatchewan, Canada.

METHODS

A baseline survey of the First Nations Sleep Health project was completed between 2018 and 2019 in collaboration with two Cree First Nations. One-night actigraphy evaluations were completed within one of the two First Nations. Objective actigraphy evaluations included sleep efficiency and sleep onset latency. A total of 167 individuals participated, and of these, 156 observations were available for analysis. Statistical analysis was conducted using logistic and linear regression models.

RESULTS

More females (61%) than males participated in the actigraphy study, with the mean age being higher for females (39.6 years) than males (35.0 years). The mean sleep efficiency was 83.38%, and the mean sleep onset latency was 20.74 (SD = 27.25) minutes. Age, chronic pain, ever having high blood pressure, and smoking inside the house were associated with an increased risk of poor sleep efficiency in the multiple logistic regression model. Age, chronic pain, ever having anxiety, heart-related illness, and smoking inside the house were associated with longer sleep onset latency in the multiple linear regression model.

CONCLUSIONS

Sleep efficiency and sleep onset latency were associated with physical and environmental factors in this First Nation.

Associations of Slow-Wave Sleep With Prevalent and Incident Type 2 Diabetes in the Multi-Ethnic Study of Atherosclerosis

CONTEXT

N3 sleep (i.e., slow-wave sleep), a marker of deep restorative sleep, is implicated in hormonal and blood pressure regulation and may impact cardiometabolic health.

OBJECTIVE

We conducted cross-sectional and prospective analyses to test whether a higher proportion and longer duration of N3 sleep are associated with reduced type 2 diabetes risk.

METHODS

A subsample of participants from the Multi-Ethnic Study of Atherosclerosis completed 1-night polysomnography at Exam 5 (2010-2013) and were prospectively followed until Exam 6 (2016-2018). We used modified Poisson regression to examine the cross-sectional associations of N3 proportion and duration with prevalent diabetes and Cox proportional hazards models to estimate risk of diabetes according to N3 measures.

RESULTS

In cross-sectional analyses (n = 2026, mean age: 69 years), diabetes prevalence was 28% (n = 572). Compared with the first quartile (Q1) of the N3 proportion (<2.0%), participants in Q4 (≥15.4%) were 29% (95% CI 0.58, 0.87) less likely to have prevalent diabetes (P trend = .0016). The association attenuated after adjustment for demographics, lifestyles, and sleep-related factors (P trend = .3322). In prospective analyses of 1251 participants and 129 incident cases over 6346 person-years of follow-up, a curvilinear relationship was observed between N3 proportion and incident diabetes risk. In the fully adjusted model, the hazard ratio (95% CI) of developing diabetes vs Q1 was 0.47 (0.26, 0.87) for Q2, 0.34 (0.15, 0.77) for Q3, and 0.32 (0.10, 0.97) for Q4 (P nonlinearity = .0213). The results were similar for N3 duration.

CONCLUSION

Higher N3 proportion and longer N3 duration were prospectively associated with lower type 2 diabetes risk in a nonlinear fashion among older American adults.

Coordinated human sleeping brainwaves map peripheral body glucose homeostasis

Insufficient sleep impairs glucose regulation, increasing the risk of diabetes. However, what it is about the human sleeping brain that regulates blood sugar remains unknown. In an examination of over 600 humans, we demonstrate that the coupling of non-rapid eye movement (NREM) sleep spindles and slow oscillations the night before is associated with improved next-day peripheral glucose control. We further show that this sleep-associated glucose pathway may influence glycemic status through altered insulin sensitivity, rather than through altered pancreatic beta cell function. Moreover, we replicate these associations in an independent dataset of over 1,900 adults. Of therapeutic significance, the coupling between slow oscillations and spindles was the most significant sleep predictor of next-day fasting glucose, even more so than traditional sleep markers, relevant to the possibility of an electroencephalogram (EEG) index of hyperglycemia. Taken together, these findings describe a sleeping-brain-body framework of optimal human glucose homeostasis, offering a potential prognostic sleep signature of glycemic control.

Association Between Sleep Efficiency and Hypertension in Chinese Obstructive Sleep Apnea Patients

Objective

We aimed to explore the relationship of sleep efficiency (SE) with the prevalence of hypertension in Chinese obstructive sleep apnea (OSA) patients based on polysomnography (PSG) records.

Methods

We studied 2360 patients with OSA and 764 primary snorers who underwent PSG in our hospital. SE was divided into three grades, including ≥85%, 80%~84.9%, and <80%. Hypertension was defined based either on direct blood pressure measurements, under anti-hypertensive treatments or on physician diagnosis. Multivariate logistic regression models were conducted to investigate the association between SE and hypertension.

Results

After adjusting for potential confounding factors, OSA patients with <80% SE and those with 80% to 84.9% SE were significantly associated with the prevalence of hypertension (OR = 1.248, 95% CI 1.018~1.531, P=0.033; OR = 1.380, 95% CI 1.040~1.832, P=0.026). Compared to primary snorers, OSA combined with <85% SE increased the odds of hypertension. In stratified analysis by SE, risk of hypertension only in those with <80% SE was significantly different between OSA and primary snorers. Furthermore, this relationship between reduced SE and hypertension was evident especially in female, younger ages, obese, moderate and severe OSA patients. No significant relationship between reduced SE and hypertension was found in primary snores group.

Conclusion

We found that poor SE was correlated with the prevalence of hypertension in Chinese OSA patients, but not in those with primary snoring. Moreover, this relationship was evident especially in female, younger ages, obese, moderate and severe OSA patients.

Associations of siesta and total sleep duration with hypertension or cardiovascular diseases in middle-aged and older adults

BACKGROUND

Whether the ratio of siesta duration in the total sleep duration was associated with the occurrence of hypertension or cardiovascular diseases (CVDs) was unclear.

HYPOTHESIS

To explore the associations of siesta, and siesta ratio with hypertension or CVDs in middle-aged and older adults.

METHODS

This cohort study collected the data of 9247 middle-aged and older adults. The associations of siesta, and siesta ratio with hypertension were analyzed in 7619 participants while the associations of siesta, and siesta ratio with CVDs were analyzed in 8685 participants via univariate and multivariate logistic regression analysis.

RESULTS

Total sleep duration < 6 h (odd ratio [OR] = 1.168, 95% confidence interval [CI]: 1.023-1.335) and siesta ratios ≥ 0.4 (OR = 1.712, 95% CI: 1.129-2.594) were associated with increased risk of hypertension in middle-aged and older adults. Siesta ratio ≥ 0.4 was linked with higher risk of hypertension in males aged ≥ 60 years and total sleep duration < 6 h was correlated with elevated risk of hypertension in males < 60 years. The risk of CVDs was elevated in people with siesta duration < 0.5 h (OR = 2.053, 95% CI: 1.323-3.185). In females ≥60 years, the sleep duration at night < 6 h was associated with increased risk of CVDs. In females < 60 years, increased risk was observed in those with siesta duration < 0.5 h and sleep duration at night < 6 h.

CONCLUSION

Short sleep duration or high siesta ratio were associated with higher risk of hypertension. Short siesta duration, sleep duration at night or total sleep duration were correlated with an elevated risk of CVDs.

Sleep characteristic profiles and the correlation with spectrum of metabolic syndrome among older adult: a cross-sectional study

BACKGROUND

Metabolic Syndrome (MetS) is a common health problem among older adults. Previous studies have revealed the relationship between sleep duration as well as global sleep status and MetS.

OBJECTIVES

This study aims to examine the association between the specific sleep characteristic and MetS as well as MetS components among community-dwelling old adults.

METHODS

This cross-sectional study included 1499 community residents aged ≥ 60 years. Sleep characteristics were assessed using the Pittsburgh Sleep Quality Index (PSQI) and bed/rise time of the residents. Logistic regression analysis and multiple linear regression analysis were used to examine the associations between sleep characteristics and MetS as well as MetS components. A generalized additive model was built to assess the smooth relationship between triglyceride (TG) levels and sleep duration.

RESULTS

Of the 1499 participants, 449 (30.0%) had MetS, and 443 (29.6%) had poor sleep quality. The rise time was found to be associated with MetS (> 6:00 vs. 5:00 ~ 6:00: adjusted OR (95%) = 1.77 (1.17-2.69), P = 0.007). For the MetS components, a U-shaped relationship was first revealed for sleep duration and TG levels (EDF = 1.85, P < 0.001). Furthermore, significant associations also included the associations of subjective sleep quality and daytime dysfunction with hypertension, the associations of sleep efficiency and rise time with hyperglycemia, the associations of rise time with TG levels, and the association of bedtime with waist circumference.

CONCLUSIONS

The different sleep characteristics were associated with different MetS components.

Increased Rapid Eye Movement Sleep Is Associated With a Reduced Risk of Heart Failure in Middle-Aged and Older Adults

Objectives

Rapid eye movement (REM) sleep is closely related to all-cause mortality. The aim of this study is to explore the role of REM sleep on the incident heart failure (HF).

Methods

We selected 4490 participants (2480 women and 2010 men; mean age, 63.2 ± 11.0 years) from the Sleep Heart Health Study. HF was identified as the first occurrence during a mean follow-up period of 10.9 years. REM sleep including percentage of REM sleep and total REM sleep time were monitored using in-home polysomnography at baseline. Multivariable Cox regression analysis was utilized to explore the relationship between REM sleep and HF.

Results

In total, 436 (9.7%) cases of HF were observed during the entire follow-up period. After adjusting for potential covariates, an increased percentage of REM sleep (per 5%) was independently associated with a reduced incidence of HF [hazard ratio (HR) 0.88, 95% confidence interval (CI) 0.82–0.94, P < 0.001]. A similar result was also found between total REM sleep time (increased per 5 min) and incident HF (HR 0.97, 95% CI 0.95–0.99, P < 0.001). Moreover, the fourth quartile of both percentage of REM sleep (HR 0.65, 95% CI 0.48–0.88, P = 0.005) and total REM sleep time (HR 0.64, 95% CI 0.45–0.90, P = 0.010) had lower risk of incident HF when compared with the first quartile.

Conclusion

An increased percentage of REM sleep and total REM sleep time were associated with a reduced risk of HF. REM sleep may be a predictor of the incident HF.

Clinical Trial Registration

[ClinicalTrials.gov], identifier [NCT00005275].

Sleep Quality and Its Determinants Among Type 2 Diabetes Patients with Comorbid Metabolic Syndrome

PURPOSE

The prevalence of poor sleep quality in patients with diabetes was higher than the general population. This study aimed to explore risk factors for not only poor sleep quality, but also long sleep latency, short sleep duration and low sleep efficiency, in type 2 diabetes patients (T2DM) with comorbid metabolic syndrome (MS).

PATIENTS AND METHODS

A total of 281 patients aged 18-75 years were enrolled from Ningbo First Hospital during October 2021 to March 2022. Sleep quality was evaluated by the Pittsburgh Sleep Quality Index (PSQI). Sleep latency, sleep duration and sleep efficiency were obtained by a response to the questionnaire. Descriptive, independent two-sample t-test, Chi-square test and multiple logistic regression were conducted using SPSS Version 28.

RESULTS

The prevalence of poor sleep quality in T2DM with comorbid MS patients was 59.10%. The factors significantly associated with poor sleep quality were depression symptoms (OR = 3.10, 95% CI: 1.38 to 6.96, P = 0.006), poor quality of life (OR = 2.49, 95% CI: 1.24 to 4.99, P = 0.010), and age (OR = 1.07, 95% CI: 1.04 to 1.10, P < 0.001). The factor significantly associated with long sleep latency was depression symptoms (OR = 2.19, 95% CI: 1.15 to 4.16, P = 0.017). The factors significantly related to short sleep duration were depression symptoms (OR = 2.56, 95% CI: 1.31 to 5.00, P = 0.006) and age (OR = 1.05, 95% CI: 1.02 to 1.08, P = 0.002). The factor significantly related to short sleep efficiency was age (OR = 1.03, 95% CI: 1.01 to 1.06, P = 0.019).

CONCLUSION

This study found that depression symptoms, together with poor quality of life, and increasing age were associated with poor sleep quality. Symptoms of depression were related to long sleep latency and short sleep duration. The increasing age was associated with short sleep duration and low sleep efficiency.

Sleep Efficiency May Predict Depression in a Large Population-Based Study

OBJECTIVES

The purpose of our study was to investigate the effect of objective sleep characteristics on the incidence of depression.

METHODS

The participants of our study (1,595 men and 1,780 women with 63.1 ± 10.7 years) were selected from the Sleep Heart Health Study (SHHS) datasets. Depression was defined as the first occurrence between SHHS visit 1 and visit 2. Objective sleep characteristics, including sleep efficiency (SE), wake after sleep onset (WASO), sleep fragmentation index (SFI) and arousal index (ArI), were monitored by polysomnography. Multivariable logistic regression was used to explore the relationship between sleep characteristics and depression.

RESULTS

A total of 248 patients with depression (7.3%) were observed between SHHS visits 1 and 2. After adjusting for covariates, SE (odds ratio [OR], 0.891; 95% confidence interval [CI] 0.811-0.978; P = 0.016) and WASO (OR, 1.021; 95% CI 1.002-1.039; P = 0.026) were associated with the incidence of depression. Moreover, the relationship between SE and depression was more pronounced in men (OR, 0.820; 95% CI 0.711-0.946; P = 0.007) than in women (OR, 0.950; 95% CI 0.838-1.078; P = 0.429) in subgroup analysis (P _interaction < 0.05).

CONCLUSIONS

SE and WASO may be markers for the incidence of depression. The association between SE and depression was intensified in men.

Quality of Sleep in Elderly Patients with Diabetes Mellitus from Turkey: A Cross-Sectional Observational Study

BACKGROUND

Elderly patients frequently experience poor sleep quality. We aimed to determine its prevalence and risk factors in diabetic elderly patients from Turkey.

METHODS

An observational cross-sectional study of 220 diabetic elderly patients with a mean age of 70.4 ± 5.9 was conducted between June 2019 and December 2019. Pittsburgh Sleep Quality Index (PSQI) questionnaire was used. Patients were divided based on sleep quality into poor (PSQI> 5) and good (PSQI≤ 5) sleep quality groups. Geriatric Depression Scale, Beck Anxiety Inventory, and Hendrich II Fall Risk Model were adopted. The prevalence of poor sleep quality and risk factors were evaluated.

RESULTS

Prevalence of poor sleep quality was 58.6%. Poor sleepers were significantly older, were more likely to be divorced, had more comorbidities, and used more medicines (ps<0.05). Longer duration of diabetes, higher incidence of hypoglycemic events, and diabetic complications were significantly associated with poor sleep quality (ps<0.05). Poor sleepers had higher levels of blood glucose and HbA1c levels (ps<0.05). PSQI was significantly correlated with age, HbA1c, duration of diabetes, higher depression, anxiety, and falling risk (ps<0.05). Severe depression, anxiety, and higher falling risk were independent risk factors.

CONCLUSION

Most patients experienced poor sleep quality. It was associated with a longer duration of diabetes, chronic diabetes-related complications, and higher HbA1c levels. Severe depression, anxiety, and higher falling risk were risk factors for poor sleep quality.

Multi-Scale Permutation Entropy: A Potential Measure for the Impact of Sleep Medication on Brain Dynamics of Patients with Insomnia

Insomnia is a common sleep disorder that is closely associated with the occurrence and deterioration of cardiovascular disease, depression and other diseases. The evaluation of pharmacological treatments for insomnia brings significant clinical implications. In this study, a total of 20 patients with mild insomnia and 75 healthy subjects as controls (HC) were included to explore alterations of electroencephalogram (EEG) complexity associated with insomnia and its pharmacological treatment by using multi-scale permutation entropy (MPE). All participants were recorded for two nights of polysomnography (PSG). The patients with mild insomnia received a placebo on the first night (Placebo) and temazepam on the second night (Temazepam), while the HCs had no sleep-related medication intake for either night. EEG recordings from each night were extracted and analyzed using MPE. The results showed that MPE decreased significantly from pre-lights-off to the period during sleep transition and then to the period after sleep onset, and also during the deepening of sleep stage in the HC group. Furthermore, results from the insomnia subjects showed that MPE values were significantly lower for the Temazepam night compared to MPE values for the Placebo night. Moreover, MPE values for the Temazepam night showed no correlation with age or gender. Our results indicated that EEG complexity, measured by MPE, may be utilized as an alternative approach to measure the impact of sleep medication on brain dynamics.

Objective and subjective sleep measures are associated with HbA1c and insulin sensitivity in the general population: Findings from the ORISCAV-LUX-2 study

AIM

To analyze the association of objective and subjective sleep measures with HbA1c and insulin sensitivity in the general population.

METHODS

Using a cross-sectional design, data from 1028 participants in the ORISCAV-LUX-2 study from the general population in Luxembourg were analyzed. Objective sleep measures were assessed using accelerometers whereas subjective measures were assessed using the Pittsburgh Sleep Quality Index (PSQI) questionnaire. Sleep measures were defined as predictors, while HbA1c and quantitative insulin sensitivity check index (QUICKI) scores were considered outcomes. Linear and spline regression models were fitted by progressively adjusting for demographic and lifestyle variables in the total sample population as well as by stratified analyses using gender, obesity status, depressive symptoms and diabetes status.

RESULTS

In fully adjusted models, total and deep sleep durations were associated with lower HbA1c (mmol/mol) levels, whereas sleep coefficients of variation (%) and poor sleep efficiency, as measured by PSQI scores (units), were associated with higher HbA1c levels. In stratified models, such associations were observed mainly in men, and in subjects who had depressive symptoms, were overweight and no diabetes. In addition, total sleep, deep sleep, coefficients of variation and poor sleep efficiency as measured by PSQI revealed non-linear associations. Similarly, greater insulin sensitivity was associated with longer total sleep time and with PSQI-6 (use of sleep medication).

CONCLUSION

Associations were more frequently observed between sleep characteristics and glycaemic control with the use of objective sleep measures. Also, such associations varied within subgroups of the population. Our results highlight the relevance of measuring sleep patterns as key factors in the prevention of diabetes.

Sleep fragmentation and incidence of congestive heart failure: the Sleep Heart Health Study

STUDY OBJECTIVES

Sleep fragmentation (SF) has been reported to be associated with cardiovascular risk. The aim of this study was to explore the relationship between SF and congestive heart failure (CHF).

METHODS

A total of 4,887 participants (2,256 males and 2,631 females, mean age of 63.6 ± 11.0 years) from the Sleep Heart Health Study (SHHS) were included in this study. Incident CHF was defined as the first occurrence of CHF between baseline in-home polysomnography (PSG) and the end of follow-up. Objective assessments for SF, including sleep fragmentation index (SFI), arousal index (ArI), sleep efficiency (SE), and wake after sleep onset (WASO), were determined based on in-home polysomnography records. Multivariate Cox regression analysis was used to investigate the relationship between SF and incident CHF.

RESULTS

During an average of 10 years of follow-up, 543 participants with CHF (11.1%) were observed. Individuals with CHF had a significantly higher SFI, total ArI, and WASO and a lower SE than controls. After multivariate Cox regression analysis, SE (odds ratio [OR], 0.967; 95% confidence interval [CI] 0.955-0.978; P < 0.001), WASO (OR, 1.009; 95% CI 1.006-1.012; P < 0.001), SFI (OR, 1.046; CI 1.007-1.086; P = 0.021), and total ArI (OR, 1.018; 95% CI 1.000-1.035; P = 0.044) were found to be associated with the incidence of CHF in participants without hypertension.

CONCLUSIONS

Objectively measured SF was associated with the incidence of CHF. The role of SFI, total ArI, SE, and WASO deserves further investigation.

Fragmented Sleep and the Prevalence of Hypertension in Middle-Aged and Older Individuals

OBJECTIVE

We aimed to investigate the association between fragmented sleep and the prevalence of hypertension in middle-aged and older individuals.

METHODS

This study included 5804 participants with an average age of 63.1±11.2 years from the Sleep Heart Health Study. Fragmented sleep parameters including arousal index in total sleep (ArI-Total), rapid eye movement sleep (ArI-REM), non-rapid eye movement sleep (ArI-NREM), fragmented sleep index (SFI), sleep efficiency (SE) and wake after sleep onset (WASO) were monitored using polysomnography. The information on hypertension, defined as systolic blood pressure (SBP) ≥140 mmHg and/or diastolic blood pressure (DBP) ≥90 mmHg or under antihypertensive treatment, was collected at baseline. We conducted multivariable logistic regression to explore the cross-sectional association between fragmented sleep and the prevalence of hypertension.

RESULTS

After adjusting for potential confounders, fragmented sleep parameters (per 5-unit change) including SE (odds ratio [OR] 0.904; 95% confidence interval [CI] 0.877-0.932; P < 0.001), WASO (OR 1.019; 95% CI 1.012-1.027; P < 0.001), ArI-Total (OR, 1.036; 95% CI, 1.005-1.068; P = 0.024), and ArI-NREM (OR 1.032; 95% CI 1.004-1.062; P = 0.027) were significantly associated with the prevalence of hypertension. In addition, ArI-Total, ArI-NREM, and ArI-REM were positively correlated with both systolic blood pressure and diastolic blood pressure.

CONCLUSION

We found a high prevalence of hypertension among middle-aged and older individuals with fragmented sleep. The causal association between fragmented sleep and hypertension warrants further investigation.