Characterization of sleep breathing pattern in patients with type 2 diabetes: sweet sleep study

Potential Therapeutic Targets in Obesity, Sleep Apnea, Diabetes, and Fatty Liver Disease

Obesity and metabolic syndrome affect the majority of the US population. Patients with obesity are at increased risk of developing type 2 diabetes (T2DM), obstructive sleep apnea (OSA), and metabolic dysfunction-associated steatotic liver disease (MASLD), each of which carry the risk of further complications if left untreated and lead to adverse outcomes. The rising prevalence of obesity and its comorbidities has led to increased mortality, decreased quality of life, and rising healthcare expenditures. This phenomenon has resulted in the intensive investigation of exciting therapies for obesity over the past decade, including more treatments that are still in the pipeline. In our present report, we aim to solidify the relationships among obesity, T2DM, OSA, and MASLD through a comprehensive review of current research. We also provide an overview of the surgical and pharmacologic treatment classes that target these relationships, namely bariatric surgery, the glucagon-like peptide-1 (GLP-1), glucose-dependent insulinotropic polypeptide (GIP), and glucagon receptor agonists.

Shorter respiratory event duration is related to prevalence of type 2 diabetes

BACKGROUND

Obstructive sleep apnea (OSA) is a heterogeneous sleep disorder often comorbid with metabolic diseases, and type 2 diabetes (T2DM) is one of them. Although apnea hypopnea index (AHI) is currently the diagnostic criteria for OSA severity, a controversial relationship between AHI and T2DM has been found. On the other hand, the duration of apnea-hypopnea events has been shown to be a useful metric for predicting mortality. This study aimed to test whether average respiratory event duration was associated with prevalence of T2DM.

METHODS

Patients referred to the sleep clinic were recruited in the study. Baseline clinical characteristics and polysomnography parameters including average respiratory event duration were collected. The association of average respiratory event duration with the prevalence of T2DM was evaluated by univariate and multivariate logistic regression analyses.

RESULTS

A total of 260 participants were enrolled, and 92 (35.4%) had T2DM. Univariate analysis revealed that age, body mass index (BMI), total sleep time, sleep efficiency, history of hypertension, and shorter average respiratory event duration were associated with T2DM. In multivariate analysis, only age and BMI remained significant. While average respiratory event duration was insignificant in multivariate analysis, subtype event analysis showed that shorter average apnea duration was both significant in univariate (OR, 0.95; 95% CI, 0.92-0.98) and multivariate analyses (OR, 0.95; 95% CI, 0.91-0.99). Neither average hypopnea duration nor AHI was associated with T2DM. Significant association (OR, 1.19; 95% CI, 1.12-1.25) was observed between shorter average apnea duration and lower respiratory arousal threshold after multivariate adjustment. However, causal mediation analysis revealed no mediating effect of arousal threshold on average apnea duration and T2DM.

CONCLUSION

The average apnea duration may be a useful metric in the diagnosis of OSA comorbidity. Shorter average apnea duration indicating poor sleep quality and augmented autonomic nervous system responses might be the potential pathological mechanisms leading to T2DM.

Role of chemosensitivity: Possible pathophysiological mediator of obstructive sleep apnea and type 2 diabetes

Obstructive sleep apnea (OSA) and type 2 diabetes show some mutual promotion of disease development. Variation in chemosensitivity is a key contributor to the pathophysiological mechanisms causing OSA and type 2 diabetes. According to studies conducted thus far, people with OSA or type 2 diabetes may have higher chemoreflex levels, but it is challenging to identify the precise changes because of variations in participant characteristics, the severity of the disease at the time of recruitment, and the small sample sizes in each study. Lowering chemosensitivity may also be viewed as a new issue for individuals with OSA and type 2 diabetes who require personalized care. The purpose of this review was to give an overview of chemosensitivity changes in OSA and glucose metabolism, as well as prospective therapeutic treatments for patients with OSA and type 2 diabetes.

Prediabetes Is Associated with Increased Prevalence of Sleep-Disordered Breathing

Type 2 diabetes leads to severe nocturnal hypoxemia, with an increase in apnea events and daytime sleepiness. Hence, we assessed sleep breathing parameters in the prediabetes stage. A cross-sectional study conducted on 966 middle-aged subjects without known pulmonary disease (311 patients with prediabetes and 655 controls with normal glucose metabolism) was conducted. Prediabetes was defined by glycated hemoglobin (HbA1c), and a nonattended overnight home sleep study was performed. Participants with prediabetes (n = 311) displayed a higher apnea−hypopnea index (AHI: 12.7 (6.1;24.3) vs. 9.5 (4.2;19.6) events/h, p < 0.001) and hypopnea index (HI: 8.4 (4.0;14.9) vs. 6.0 (2.7;12.6) events/h, p < 0.001) than controls, without differences in the apnea index. Altogether, the prevalence of obstructive sleep apnea was higher in subjects with prediabetes than in controls (78.1 vs. 69.9%, p = 0.007). Additionally, subjects with prediabetes presented impaired measurements of the median and minimum nocturnal oxygen saturation, the percentage of time spent with oxygen saturations below 90%, and the 4% oxygen desaturation index in comparison with individuals without prediabetes (p < 0.001 for all). After adjusting for age, sex, and the presence of obesity, HbA1c correlated with the HI in the entire population (r = 0.141, p < 0.001), and the presence of prediabetes was independently associated with the AHI (B = 2.20 (0.10 to 4.31), p = 0.040) as well as the HI (B = 1.87 (0.61 to 3.14), p = 0.004) in the multiple linear regression model. We conclude that prediabetes is an independent risk factor for an increased AHI after adjusting for age, sex, and obesity. The enhanced AHI is mainly associated with increments in the hypopnea events.

Medications and medical costs for diabetes patients with or without chronic respiratory disease in Beijing, China: A retrospective study

AIMS

The cost of drug regimens prescribed to Chinese patients has not been evaluated. This study aims to evaluate the medical costs and hypoglycemic agents for diabetes mellitus patients with or without chronic respiratory disease in Beijing, and to investigate the changes in the costs and number of antidiabetic medications used for diabetes patients with chronic respiratory disease from 2016 to 2018.

METHODS

This observational, retrospective study included diabetes patients with outpatient medication records from Beijing Medical Insurance between 2016 and 2018. The medications, including hypoglycemic and nonhypoglycemic drugs, insulin dosage, comorbidities, diabetes-related complications, treatment strategies, and annual medical costs, were recorded.

RESULTS

This study included 2,853,036 diabetes patients from 2016 to 2018. About 18.95%-20.53% of patients with chronic respiratory disease were predominantly distributed among those aged 45-84 years (88.7%-89.1%). Diabetes patients with chronic respiratory disease used more medications (4.48 ± 2.41 vs. 3.76 ± 2.33) and had higher total annual drug costs (¥12,286 ± 10,385 vs. ¥9700 ± 9202) to treat more comorbidities (2.52 ± 1.53 vs. 2.05 ± 1.85) than those without chronic respiratory disease (p <.0001, respectively). From 2016 to 2018, diabetes patients with chronic respiratory disease had a 4.2% increase in medication, a 1.9% decrease in comorbidities, and a 5.4% decrease in total annual drug costs.

CONCLUSIONS

In summary, diabetes patients with chronic respiratory disease had more comorbidities, required more hypoglycemic drugs, and had higher medical costs. During 2016-2018, diabetes patients with chronic respiratory disease used more medications and spent less money on medical care.

Sleep Disturbances and Cognitive Impairment in the Course of Type 2 Diabetes-A Possible Link

There is an increasing number of patients worldwide with sleep disturbances and diabetes. Various sleep disorders, including long or short sleep duration and poor sleep quality of numerous causes, may increase the risk of diabetes. Some symptoms of diabetes, such as painful peripheral neuropathy and nocturia, or associated other sleep disorders, such as sleep breathing disorders or sleep movement disorders, may influence sleep quality and quantity. Both sleep disorders and diabetes may lead to cognitive impairment. The risk of development of cognitive impairment in diabetic patients may be related to vascular and non-vascular and other factors, such as hypoglycemia, hyperglycemia, central insulin resistance, amyloid and tau deposits and other causes. Numerous sleep disorders, e.g., sleep apnea, restless legs syndrome, insomnia, and poor sleep quality are most likely are also associated with cognitive impairment. Adequate functioning of the system of clearance of the brain from toxic substances, such as amyloid β, i.e. glymphatic system, is related to undisturbed sleep and prevents cognitive impairment. In the case of coexistence, sleep disturbances and diabetes either independently lead to and/or mutually aggravate cognitive impairment.

The Risk of Obstructive Sleep Apnea among Patients with Type 2 Diabetes Mellitus

Context/Aims

Obstructive sleep apnea (OSA) and Type 2 diabetes mellitus share obesity as a common risk factor. The presence of OSA may contribute to increased morbidity and mortality of diabetes. Despite their close association, OSA is not routinely evaluated in diabetic patients. This study was conducted to determine the risk of OSA among Type 2 diabetes mellitus patients.

Methods

Type 2 diabetic patients attending a tertiary hospital in Nigeria were evaluated for OSA risk using the Berlin Questionnaire. Other parameters measured included anthropometry and blood pressure (BP).

Results

Three hundred and twenty-seven patients participated in this survey: 177 (54.1%) were female and 150 (45.9%) were male. The average age of the patients was 56.2 ± 9.3 years. Seventy-eight (44.8%) females were obese compared to 30 (20.0%) males,P < 0.001. Two hundred and one (61.5%) patients were previously known hypertensives with only 48 (23.9%; 95% confidence interval [CI]: 18.2-30.4) of them having good BP control. One hundred and sixty-two (49.5%, 95% CI; 44.0-55.1) patients had a high risk for OSA: 96 (54.2%; 95% CI: 44.6-61.7) females and 66 (44.0%; 95% CI: 35.9-52.3) males. The strongest predictor for a high risk of OSA was poorly controlled BP with an odds ratio of 2.6 (95% CI: 1.6-4.3).

Conclusion

This study has demonstrated that there is a high risk of OSA among Type 2 diabetic patients and that OSA risk is significantly associated with poor BP control and obesity. We recommend that diabetic patients should be assessed for OSA risk as part of their routine evaluation.

Effect of Glucose Improvement on Nocturnal Sleep Breathing Parameters in Patients with Type 2 Diabetes: The Candy Dreams Study

Type 2 diabetes exerts a negative impact on sleep breathing. It is unknown whether a long-term improvement in glycemic control ameliorates this effect. We conducted an interventional study with 35 patients with type 2 diabetes and obstructive sleep apnea (OSA) to explore this. At home, sleep breathing parameters were assessed at baseline and after a 4-month period in which antidiabetic therapy was intensified. Patients who decreased their body mass index ≥2kg/m² were excluded. Those with an HbA1c reduction ≥0.5% were considered good responders (n = 24). After the follow-up, good responders exhibited an improvement in the apnea–hypopnea index (AHI: 26-1 (95% IC: 8.6–95.0) vs. 20.0 (4.0–62.4) events/hour, p = 0.002) and in time with oxygen saturation below 90% (CT90: 13.3 (0.4–69.0) vs. 8.1 (0.4–71.2) %, p = 0.002). No changes were observed in the group of non–responders (p = 0.722 and p = 0.138, respectively). The percentage of moderate and severe OSA decreased among good responders (p = 0.040). In the wider population, the change in HbA1c correlated positively to decreases in AHI (r = 0.358, p = 0.035) and negatively to increases in the minimum arterial oxygen saturation (r = −0.386, p = 0.039). Stepwise multivariate regression analysis showed that baseline AHI and the absolute change in HbA1c independently predicted decreased AHI (R² = 0.496). The improvement of glycemic control exerts beneficial effects on sleep breathing parameters in type 2 diabetes, which cannot be attributed merely to weight loss.

Sleep questionnaires for the screening of obstructive sleep apnea in patients with type 2 diabetes mellitus compared with non-diabetic patients

BACKGROUND

Several tools have been used to screen for obstructive sleep apnea (OSA). Evaluation of the predictive performance of different questionnaires is essential in patients with type 2 diabetes mellitus (T2DM) because the prevalence of OSA in this population is high. The aim of this study was to evaluate different sleep questionnaires to identify T2DM patients with OSA, and to compare the predictive values of these questionnaires with a matched sample of non-diabetic patients.

METHODS

The study was a retrospective study of two patients groups (n = 350 with T2DM, n = 350 without T2DM) visiting a sleep clinic and matched by age, gender, body mass index, and the apnea-hypopnea index (AHI). Symptoms of OSA and Epworth Sleepiness Scale (ESS), STOP-Bang, Berlin questionnaire, and Athens insomnia scale (AIS) scores were compared, and sleep studies were performed.

RESULTS

Diabetic patients with OSA complained more frequently of nocturia (P = 0.025), morning headaches (P = 0.04), restless sleep (P = 0.002), and leg movements (P = 0.01) than non-diabetic patients with OSA. Most predictive values of the sleep questionnaires did not differ significantly between the two groups; however, the AIS was higher only in T2DM women (P = 0.01). In both groups, the Berlin and STOP-Bang questionnaires had the highest sensitivity. The ESS had the highest specificity in T2DM patients and the STOP and S-B questionnaires had the highest specificity in non-diabetics.

CONCLUSIONS

The predictive performance of the questionnaires was similar in both groups, especially in the case of moderate and severe OSA.

Weekly sleep trajectories and their associations with obesity and hypertension in the Hispanic/Latino population

Study Objectives

To identify weekly sleep trajectories (sleep pattern changing by day over a course of week) of specific characteristics and examine the associations between trajectory classes and obesity and hypertension.

Methods

A total of 2043 participants (mean age 46.9, 65.5% female) completed at least 7 days of actigraphy aged 18-64 from the Sueño ancillary study of the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). Weekly sleep trajectories for three daily level measures (wake after sleep onset [WASO], daytime napping duration, and intranight instability index) were identified using latent class growth models. The outcomes were obesity and hypertension.

Results

Using the trajectory with low-stable WASO as reference, the trajectory classes with increasing and high-concave patterns had significantly higher odds for obesity (OR 3.64 [1.23-10.84]) and hypertension (OR 5.25 [1.33, 20.82]), respectively. Compared with individuals with a low-stable napping duration trajectory, those with the high-concave pattern class were associated with hypertension (OR 2.27 [1.10-4.67]), and the association was mediated in part by obesity (OR 1.11 [1.00-1.22]). Individuals in the high intranight instability index trajectory had significantly larger likelihood for both obesity (OR 1.90 [1.26-2.86]) and hypertension (OR 1.86 [1.13-3.06]) compared with those in the low intranight instability index trajectory.

Conclusions

Weekly trajectories varied for WASO, daytime napping duration, and intranight instability index. The trajectories with relatively larger values for these three measures were associated with greater risk for obesity and hypertension. These findings suggest that a stable pattern with relatively small weekly and nightly variability may be beneficial for cardiovascular health.

Characteristics of Obstructive Sleep Apnea Across the Spectrum of Glucose Tolerance in Obese Adolescents

BACKGROUND

It is not known if dysglycemia and sleep-disordered breathing are linked in adolescents, as in adults.

OBJECTIVE

To perform a pilot study evaluating measures of sleep-disordered breathing across the spectrum of glucose tolerance in obese adolescents. We hypothesized that dysglycemia would be associated with sleep-disordered breathing.

PARTICIPANTS/METHODS

This was a prospective, cross-sectional clinical pilot study that included 57 adolescents [body mass index (BMI) 38.9 ± 8.4 kg/m²] aged 12-18 years (14.5 ± 1.6) with normal glucose tolerance (NGT), or dysglycemia [impaired glucose tolerance (IGT) or type 2 diabetes (T2D)].

MEASURES

Anthropometrics, overnight polysomnogram, and oral glucose tolerance tests were performed. Participant characteristics and outcome measures were compared by glucose tolerance status. Correlational analyses were conducted to assess the associations between variables of interest.

RESULTS

Participants with dysglycemia (n = 21) were not different from those with NGT (n = 36) for BMI, waist circumference, body fat, or sleep characteristics. Nocturnal oxygen desaturation was associated with higher BMI (r = -0.334, p = 0.012). The apnea-hypopnea index (AHI) was not associated with physical and metabolic parameters. Although participants with dysglycemia tended to have higher AHIs (median 3.2, 2.2, and 1.6 events/h for T2D, IGT, and NGT, respectively), there was not a linear relationship between measures of glycemia and AHI.

CONCLUSION

Further study with a larger proportion of youth with prediabetes and T2D is necessary to determine whether evaluation for sleep-disordered breathing is uniformly warranted.

Pulmonary Function and Sleep Breathing: Two New Targets for Type 2 Diabetes Care

Population-based studies showing the negative impact of type 2 diabetes (T2D) on lung function are overviewed. Among the well-recognized pathophysiological mechanisms, the metabolic pathways related to insulin resistance (IR), low-grade chronic inflammation, leptin resistance, microvascular damage, and autonomic neuropathy are emphasized. Histopathological changes are exposed, and findings reported from experimental models are clearly differentiated from those described in humans. The accelerated decline in pulmonary function that appears in patients with cystic fibrosis (CF) with related abnormalities of glucose tolerance and diabetes is considered as an example to further investigate the relationship between T2D and the lung. Furthermore, a possible causal link between antihyperglycemic therapies and pulmonary function is examined. T2D similarly affects breathing during sleep, becoming an independent risk factor for higher rates of sleep apnea, leading to nocturnal hypoxemia and daytime sleepiness. Therefore, the impact of T2D on sleep breathing and its influence on sleep architecture is analyzed. Finally, the effect of improving some pathophysiological mechanisms, primarily IR and inflammation, as well as the optimization of blood glucose control on sleep breathing is evaluated. In summary, the lung should be considered by those providing care for people with diabetes and raise the central issue of whether the normalization of glucose levels can improve pulmonary function and ameliorate sleep-disordered breathing. Therefore, patients with T2D should be considered a vulnerable group for pulmonary dysfunction. However, further research aimed at elucidating how to screen for the lung impairment in the population with diabetes in a cost-effective manner is needed.

[Intermittent hypoxia due to sleep apnea syndrome in patients with type 2 diabetes mellitus]

OBJECTIVES

To evaluate the possible association between intermittent hypoxia (IH) and HbA1c in patients with insufficient control type of 2 diabetes mellitus (T2DM).

MATERIAL AND METHODS

In this cross-sectional study 183 patients with HbAc1≥7% underwent three-channel overnight monitoring (ApneaLink) and completed Berlin Questionnaire, Epworth Sleepiness Scale and Pittsburgh Sleep Quality Index. Patients were divided in two groups, based on the cut-off value of oxygen desaturation index≥15.

RESULTS AND CONCLUSION

There were 79 (43%) patients with intermittent hypoxia, which was associated with poorer glycaemic control, defined as HbA1c>8.7% (sample median) in the univariate analysis and after adjustment for body mass index OR 2,40 (CI 1.21-4.95, p=0.021). Neither of three questionnaires yielded satisfactory results as a screening method in patients with T2DM. There is a need to implement instrumental screening of sleep-disordered breathing in this population and to study the effects of CPAP-therapy on glycaemic control and carbohydrate metabolism.

Obstructive Sleep Apnea and Diabetes: A State of the Art Review

OSA is a chronic treatable sleep disorder and a frequent comorbidity in patients with type 2 diabetes. Cardinal features of OSA, including intermittent hypoxemia and sleep fragmentation, have been linked to abnormal glucose metabolism in laboratory-based experiments. OSA has also been linked to the development of incident type 2 diabetes. The relationship between OSA and type 2 diabetes may be bidirectional in nature given that diabetic neuropathy can affect central control of respiration and upper airway neural reflexes, promoting sleep-disordered breathing. Despite the strong association between OSA and type 2 diabetes, the effect of treatment with CPAP on markers of glucose metabolism has been conflicting. Variability with CPAP adherence may be one of the key factors behind these conflicting results. Finally, accumulating data suggest an association between OSA and type 1 diabetes as well as gestational diabetes. This review explores the role of OSA in the pathogenesis of type 2 diabetes, glucose metabolism dysregulation, and the impact of OSA treatment on glucose metabolism. The association between OSA and diabetic complications as well as gestational diabetes is also reviewed.

Sleep biosignature of Type 2 diabetes: a case-control study

AIM

To determine whether or not the sleep disturbances associated with Type 2 diabetes affect the structure of sleep.

METHODS

We designed a case-control study in 76 patients with Type 2 diabetes and 76 control subjects without Type 2 diabetes, matched by age, gender, BMI and waist and neck circumferences. A subgroup of 32 patients with Type 2 diabetes was also matched with 64 control subjects without Type 2 diabetes according to apnoea-hypopnoea index score. Examination included an overnight full polysomnography.

RESULTS

No differences in the percentage of time spent in either rapid eye movement or non-rapid eye movement sleep were observed between groups; however, patients with Type 2 diabetes had more microarousal events during sleep than control subjects [41.4 (total range 4.0-104.4) vs 20.7 (total range 1.3-94.5) events/h; P < 0.001]. These differences were mainly observed during the non-rapid eye movement sleep [7.4 (total range 0-107.2) vs 0.2 (total range 0-65.2) events/h; P < 0.001]. In addition, sleep variables related to oxygen saturation measures, such as the percentage of time spent with oxygen saturation ≤90%, were significantly greater during the rapid eye movement sleep in patients with Type 2 diabetes [20.3 (total range 0-99.2) vs. 10.5 (total range 0-94.0)%; P = 0.047]. This pattern was maintained in the subgroup of patients matched by apnoea-hypopnaea index. Finally, stepwise regression analyses showed that apnoea-hypopnoea index, the presence of Type 2 diabetes and fasting plasma glucose value were independently associated with the number of microarousals (R² =0.667).

CONCLUSIONS

Type 2 diabetes is associated with an altered sleep structure, with different effects according to rapid eye movement (increase in nocturnal hypoxia) or non-rapid eye movement (increase in sleep fragmentation) sleep.

Global Assessment of the Impact of Type 2 Diabetes on Sleep through Specific Questionnaires. A Case-Control Study

Abstract

Type 2 diabetes (T2D) is an independent risk factor for sleep breathing disorders. However, it is unknown whether T2D affects daily somnolence and quality of sleep independently of the impairment of polysomnographic parameters.

Material and Methods

A case-control study including 413 patients with T2D and 413 non-diabetic subjects, matched by age, gender, BMI, and waist and neck circumferences. A polysomnography was performed and daytime sleepiness was evaluated using the Epworth Sleepiness Scale (ESS). In addition, 135 subjects with T2D and 45 controls matched by the same previous parameters were also evaluated through the Pittsburgh Sleep Quality Index (PSQI) to calculate sleep quality.

Results

Daytime sleepiness was higher in T2D than in control subjects (p = 0.003), with 23.9% of subjects presenting an excessive daytime sleepiness (ESS>10). Patients with fasting plasma glucose (FPG ≥13.1 mmol/l) were identified as the group with a higher risk associated with an ESS>10 (OR 3.9, 95% CI 1.8–7.9, p = 0.0003). A stepwise regression analyses showed that the presence of T2D, baseline glucose levels and gender but not polysomnographic parameters (i.e apnea-hyoapnea index or sleeping time spent with oxigen saturation lower than 90%) independently predicted the ESS score. In addition, subjects with T2D showed higher sleep disturbances [PSQI: 7.0 (1.0–18.0) vs. 4 (0.0–12.0), p<0.001].

Conclusion

The presence of T2D and high levels of FPG are independent risk factors for daytime sleepiness and adversely affect sleep quality. Prospective studies addressed to demonstrate whether glycemia optimization could improve the sleep quality in T2D patients seem warranted.