A strong association exists between sleep duration and glycemic control in patients with type 2 diabetes (T2D), yet convincing evidence of a causal link remains lacking. Improving sleep is increasingly emphasized in clinical T2D treatment guidance, highlighting the need for effective, scalable sleep interventions that can affordably serve large populations through mobile health (mHealth).

This study aims to pilot an intervention that extends sleep duration by modifying bedtime behavior, assessing its efficacy among short-sleeping (≤6 hours per night) patients with T2D, and establishing robust evidence that extending sleep improves glycemic control.

This randomized, single-blinded, multicenter study targets 70 patients with T2D from 9 institutions in Japan over a 12-week intervention period. The sleep extension intervention, BedTime, is developed using the Theory of Planned Behavior (TPB) and focuses on TPB's constructs of perceived and actual behavioral control (ABC). The pilot intervention combines wearable actigraphy devices with SMS text messaging managed by human operators. Both the intervention and control groups will use an actigraphy device to record bedtime, sleep duration, and step count, while time in bed (TIB) will be assessed via sleep diaries. In addition, the intervention group will receive weekly bedtime goals, daily feedback on their bedtime performance relative to those goals, identify personal barriers to an earlier bedtime, and select strategies to overcome these barriers. The 12-week intervention period will be followed by a 12-week observational period to assess the sustainability of the intervention's effects. The primary outcome is the between-group difference in the change in hemoglobin A1c (HbA1c) at 12 weeks. Secondary outcomes include other health measures, sleep metrics (bedtime, TIB, sleep duration, total sleep time, and sleep quality), behavioral changes, and assessments of the intervention's usability. The trial commenced on February 8, 2024, and is expected to conclude in February 2025.

Patient recruitment ended on August 29, 2024, with 70 participants enrolled. The intervention period concluded on December 6, 2024, and the observation period ended on February 26, 2025, with 70 participants completing the observation period. The data analysis is currently underway, and results are expected to be published in July 2025.

This trial will provide important evidence on the causal link between increased sleep duration and improved glycemic control in short-sleeping patients with T2D. It will also evaluate the efficacy of our bedtime behavior change intervention in extending sleep duration, initially piloted with human operators, with the goal of future implementation via an mHealth smartphone app. If proven effective, this intervention could be a key step toward integrating sleep-focused mHealth into the standard treatment for patients with T2D in Japan.

Japan Registry of Clinical Trials jRCT1030230650; https://jrct.niph.go.jp/latest-detail/jRCT1030230650.

DERR1-10.2196/64023.

Sleep insufficiency is known to negatively impact on glucose metabolism. Consequently, there is interest in determining the impact of improving sleep on glucose metabolism. We conducted a meta-analysis of studies that aimed at improving sleep using cognitive behavioural therapy for insomnia (CBT-I) and/or sleep hygiene or sleep extension on glucose metabolism.

Searches were performed on MEDLINE, EMBASE, CINAHL and Cochrane. We included studies featuring adults≥18years, a sleep intervention and glycaemic measurements. The pooled mean differences were calculated by the inverse variance method.

24 studies (15 CBT-I and/or sleep hygiene; 9 sleep extension) were included. Meta-analysis of 12 studies (n = 2,044) of CBT-I and/or sleep hygiene demonstrated a significant reduction in HbA1c of 0.27% (95% CI 0.07, 0.47, I2 74%, p = 0.008) compared to control. In T2DM (n = 1,911; 9 studies), HbA1c level decrease was 0.43% (0.19, 0.67, I2 59%, p = 0.0004). There were no significant changes in fasting blood glucose analyses nor in any sleep extension intervention. For quality assessment, only 9 studies had low concern.

Using CBT-I and/or sleep hygiene interventions led to significant reductions in HbA1c levels, which were clinically meaningful in T2DM. Addressing sleep insufficiency should be an integral part of diabetes care.

PROSPERO Identification number: CRD42022376606.

Investigate whether aiding sleep by online cognitive behavioral therapy for insomnia (CBT-I) can improve glycemic and metabolic control, mood, quality of life (QoL) and insomnia symptoms in people with type 2 diabetes and assess the mediating role of lifestyle factors.

Adults with type 2 diabetes and insomnia symptoms were randomly assigned to CBT-I or care as usual. At baseline, three and six months we assessed HbA1c as primary outcome and glycemic control, metabolic outcomes, sleep, mood and QoL as secondary outcomes. Mixed models were used to determine within-person and between-persons differences in outcomes and mediation analysis for lifestyle factors.

We randomized 29 participants to CBT-I and 28 to care as usual. Intention-to-treat analysis showed no significant differences in glycemic control, metabolic outcomes, anger, distress or QoL, but showed a significantly larger decrease in insomnia (-1.37(2.65: 0.09)) and depressive symptoms (-0.92(-1.77: 0.06)) and increase in BMI (0.29 kg/m2(0.00:0.57)) in the intervention compared to the control group. Only half of the intervention participants completed the CBT-I. Per protocol analysis showed a not statistically significant decrease in HbA1c (-2.10 mmol/l(-4.83:0.63)) and glucose (-0.39 mmol/l(-1.19:0.42)), metabolic outcomes and increase in QoL. Furthermore, the intervention group showed a significant decrease in insomnia (-2.22(-3.65: 0.78)) and depressive symptoms (-1.18(-2.17: 0.19)) compared to the control group. Lifestyle factors partially mediated the effect of the intervention.

CBT-I might improve insomnia symptoms and mood, and perhaps improves glycemic control, albeit not significant, in people with type 2 diabetes and insomnia symptoms, compared to care as usual.

To determine the prevalence of insomnia and the effectiveness of its treatment in patients with a painful form of diabetic polyneuropathy (DPN).

Fifty patients with the painful form of DPN were randomly divided into 2 groups: the standard therapy group (ST) and the extended therapy group (ET). In the ST group, a single lesson on sleep hygiene was conducted, in the ET group there were 3-4 face-to-face individual sessions for the treatment of insomnia for two weeks. Both groups were interviewed at the time of hospitalization, after 3 and 6 months. The severity of polyneuropathy and the nature of neuropathic pain were assessed using the Neuropathic Neuropathy Impairment Score in the Lower Limbs (NIS-LL) and the Neuropathy Total Symptom Score - 9 (NTSS-9); the intensity of pain was assessed using a Visual Analog Scale (VAS). Sleep disorders were analyzed using the Pittsburgh Sleep Quality Index (PSQI) and the Insomnia Severity Index (ISI).

Sleep disorders of varying severity were observed in 82% of patients in the initial survey. In both groups, improvement in sleep quality was noted during treatment, but significantly better results were in the ET group, the ISI score after 6 months was 7.15±2.08 for the ST group and 3.07±2.49 for the ET group (p<0.0001). In the ST group, there was no significant decrease in the intensity of pain and the severity of polyneuropathy in dynamics. In the ET group, a significant decrease in NTSS-9 and VAS scores was found during the initial survey and after 6 months (p<0.0001). The intensity of pain also significantly decreased in the ET group compared with the ST group (p<0.0001) at the end of follow-up, which indicates the importance of sleep normalization in the treatment of neuropathic pain.

Most patients with the painful form of DPN have insomnia. Treatment of insomnia has shown its effectiveness as part of a multimodal approach to the managing of neuropathic pain in DPN and improving the quality of life of patients.

Short sleep duration and poor sleep quality are important risk factors for atherosclerosis. The use of smart bracelets that measure sleep parameters, such as sleep stage, can help determine the effect of sleep quality on lower-extremity atherosclerosis in patients with type 2 diabetes.

To investigate the correlation between sleep disorders and lower-extremity atherosclerosis in patients with type 2 diabetes.

After admission, all patients were treated with lower-extremity arterial ultrasound and graded as having diabetic lower-extremity vascular lesions according to the results. A smart bracelet was used to obtain the patient sleep data. The correlation between sleep patterns and diabetic lower-extremity atherosclerosis, diabetic foot, and various metabolic indices was verified.

Between August 2021 and April 2022, we screened 100 patients with type 2 diabetes, with 80 completing sleep monitoring. Univariate ordered logistic regression analysis indicated that patients with a sleep score below 76 (OR = 2.707, 95%CI: 1.127-6.488), shallow sleep duration of 5.3 h or more (OR=3.040, 95 CI: 1.005-9.202), wakefulness at night of 2.6 times or more (OR = 4.112, 95%CI: 1.513-11.174), and a deep sleep continuity score below 70 (OR = 4.141, 95%CI: 2.460-615.674) had greater risk of high-grade lower limb atherosclerosis. Multivariate ordinal logistic regression analysis revealed that the risk of high-grade lower limb atherosclerosis was higher in patients with 2.6 or more instances of nighttime wakefulness (OR = 3.975, 95%CI: 1.297-12.182) compared with those with fewer occurrences. The sleep duration curve of patients with different grades of diabetic lower-extremity atherosclerosis was U-shaped. According to the results of the one-way analysis of variance, the higher the deep sleep continuity score, the lower the Wagner scale score for diabetic foot (P < 0.05).

Sleep disorders (long, shallow sleep duration, frequent wakefulness at night, and poor continuity of deep sleep) can worsen lower limb atherosclerosis in patients with type 2 diabetes. This finding can provide a new method for medical professionals to prevent and treat diabetic lower-extremity vascular lesions.

Sleep and circadian disturbances emerge as novel factors influencing glycemic control in type 1 diabetes (T1D). We aimed to explore the associations among sleep, behavioral circadian parameters, self-care, and glycemic parameters in T1D.

Seventy-six non-shift-working adult T1D patients participated. Blinded 7-day continuous glucose monitoring (CGM) and hemoglobin A1C (A1C) were collected. Percentages of time-in-range (glucose levels 70-180 mg/dL) and glycemic variability (measured by the coefficient of variation [%CV]) were calculated from CGM. Sleep (duration and efficiency) was recorded using 7-day actigraphy. Variability (standard deviation) of midsleep time was used to represent sleep variability. Nonparametric behavioral circadian variables were derived from actigraphy activity recordings. Self-care was measured by diabetes self-management questionnaire-revised. Multiple regression analyses were performed to identify independent predictors of glycemic parameters.

Median (interquartile range) age was 34.0 (27.2, 43.1) years, 48 (63.2%) were female, and median (interquartile range) A1C was 6.8% (6.2, 7.4). Sleep duration, efficiency, and nonparametric behavioral circadian variables were not associated with glycemic parameters. After adjusting for age, sex, insulin delivery mode/CGM use, and ethnicity, each hour increase in sleep variability was associated with 9.64% less time-in-range (B = -9.64, 95% confidence interval [-16.29, -2.99], p ≤ .001). A higher diabetes self-management questionnaire score was an independent predictor of lower A1C (B = -0.18, 95% confidence interval [-0.32, -0.04]).

Greater sleep timing variability is independently associated with less time spent in the desirable glucose range in this T1D cohort. Reducing sleep timing variability could potentially lead to improved metabolic control and should be explored in future research.

Data are available upon a reasonable request to the corresponding author.

To assess the effectiveness of Cognitive Behavioral Therapy for Insomnia (CBT-I) on cardiometabolic health biomarkers.

Cochrane CENTRAL, Embase, Medline, and PsycINFO were searched, and records were screened by two independent reviewers. Inclusion criteria were adult population, delivery of CBT-I, randomized controlled trial design, ≥1 cardiometabolic health outcome, and peer-review. Hedge's g effect sizes were calculated, and the quality of the evidence was appraised using the Cochrane Risk of Bias 2 tool.

After screening 1649 records, 15 studies were included (total N = 2067). Inflammatory markers (CRP, IL-6, TNF-α), blood pressure (SBP, DBP), and glycemic regulation (HbA1c) were most frequently reported (in ≥3 studies each). HbA1c and CRP were reduced in the CBT-I group compared to the control group (in 3 studies each). Effects varied or were null for IL-6, TNF-α, SBP, and DBP. Six studies were judged as low, four as moderate, and five as high risk of bias.

CBT-I was most consistently associated with improved HbA1c and CRP, which are relatively temporally stable, suggesting influences on enduring habits rather than short-term behavior changes. High risk of bias limits the interpretation of findings. Methodologically adequate studies are needed to better understand cardiometabolic effects of CBT-I.

Glycemic control is an important issue in the treatment of diabetic patients. However, traditional methods, such as medication (the usual treatment), have limitations. Cognitive behavioral therapy (CBT) might be a useful option to help control the glycemic condition. The effects can be revealed by systemic review or meta-analysis of randomized clinical trials (RCT).

A systematic search and a meta-analysis for the RCT were done of the short- and long-term effects of CBT on the glycemic control of diabetic patients in a comparison with the usual treatment. Nineteen RCT studies and 3,885 diabetic patients were enrolled in this meta-analysis. Subgroup analyses of types 1 and 2 diabetes and individual and group CBT were also performed.

Patients treated with CBT showed no significant difference in HbA1c when compared to the usual treatment within six months. However, CBT was more effective in reducing HbA1c when compared to usual treatment with at least six months of treatment duration [standardized mean difference: -0.44 (95% confidence interval (CI): -0.63 ~ -0.25), Z = 4.49]. Subgroup analysis of type 1 and 2 diabetic patients supported a long-term effect of CBT on glycemic control [standardized mean difference: -0.85 (95% CI: -1.19 ~ -0.10), Z = 2.23, standardized mean difference: -0.33 (95% CI:-0.47 ~ -0.19), Z = 4.52, respectively].

CBT would be a useful option for improving the glycemic control of diabetic patients undergoing long-term treatment. The advantages of the long-term effects of CBT should be considered by clinicians and staff.

The global epidemic of obesity and type 2 diabetes parallels the rampant state of sleep deprivation in our society. Epidemiological studies consistently show an association between insufficient sleep and metabolic dysfunction. Mechanistically, sleep and circadian rhythm exert considerable influences on hormones involved in appetite regulation and energy metabolism. As such, data from experimental sleep deprivation in humans demonstrate that insufficient sleep induces a positive energy balance with resultant weight gain, due to increased energy intake that far exceeds the additional energy expenditure of nocturnal wakefulness, and adversely impacts glucose metabolism. Conversely, animal models have found that sleep loss-induced energy expenditure exceeds caloric intake resulting in net weight loss. However, animal models have significant limitations, which may diminish the clinical relevance of their metabolic findings. Clinically, insomnia disorder and insomnia symptoms are associated with adverse glucose outcomes, though it remains challenging to isolate the effects of insomnia on metabolic outcomes independent of comorbidities and insufficient sleep durations. Furthermore, both pharmacological and behavioral interventions for insomnia may have direct metabolic effects. The goal of this review is to establish an updated framework for the causal links between insufficient sleep and insomnia and risks for type 2 diabetes and obesity.

Sleep and circadian rhythm disturbances are less-known risk factors for the development and suboptimal outcomes of diabetes. The goal of this narrative review is to highlight the importance of sleep and circadian rhythm disturbances in the development and outcomes of type 1 diabetes (T1D) and type 2 diabetes (T2D), assess current treatment options and the possible mediating mechanisms. We performed a literature search using PubMed and selected relevant English and Dutch papers. Disturbances of sleep and circadian rhythm are common in people with diabetes. They are associated with an increased risk of developing T2D as well as with suboptimal diabetes outcomes (including higher HbA1c levels and reduced quality of life) for T1D and T2D. Preliminary data suggest that treatment of sleep and circadian rhythm disturbances could improve diabetes outcomes in people with T1D and T2D. Finally, the association with medical parameters appears to be mediated by disturbance in hormones, and by suboptimal self-care including forgetting or postponing glucose monitoring or medication use as well as higher consumption of high fat/high sugary foods. Diabetes may also disturb sleep, for example through nocturnal hypoglycemia and nocturia. We concluded that sleep and circadian rhythm disturbances are closely linked with diabetes. More attention to sleep in regular diabetes care is warranted, while further research is needed on treatment of sleep and circadian rhythm disturbances in the prevention of diabetes and its suboptimal outcomes.

This meta-analysis aims to update former meta-analyses from randomized controlled trials (RCT) focused on the efficacy of CBT for diabetes.

Five databases were searched for RCTs. Primary outcomes were glycated hemoglobin (HbA1c), fasting blood glucose (FBS), systolic blood pressure (SBP), diastolic blood pressure (DBP), and body mass index (BMI). Secondary outcomes were depression, anxiety and distress symptoms, quality of life, sleep quality.

32 RCTs were included. Results revealed that CBT could reduce HbA1c: -0.14% (95% CI: -0.25 to -0.02%, P = 0.020); FBS: -15.48 mg/dl (95% CI: -30.16 to -0.81 mg/dl, P = 0.040); DBP: -2.88 mmHg (95% CI: -4.08 to -1.69 mmHg, P < 0.001); depression symptoms: -0.90 (95% CI: -1.22 to -0.57, P < 0.001); anxiety symptoms: -0.28 (95% CI: -0.50 to -0.07, P = 0.009); improve sleep quality: -0.92 (95% CI: -1.77 to -0.07, P = 0.030). Subgroup analysis indicated that CBT has siginificantly reduced HbA1c when delivered as a group-based and face-to-face method, and psycho-education, behavioral, cognitive, goal-setting, homework assignment strategies were applied as central strategies.

CBT was an effective treatment for diabetes patients, significantly reduced their HbA1c, FBS, DBP, depression and anxiety symptoms, and improved sleep quality.

Almost 50% of people with heart failure (HF) experience chronic insomnia and must perform self-care to manage their day-to-day healthcare needs. Understanding multifactorial influences on self-care, including demographic, clinical, and sleep characteristics, and mood and somatic symptoms will help identify people at highest risk for poor self-care. However, past research focused only on the associations of single symptoms and self-care. Multivariate approaches are needed to account for the synergistic associations of self-care with sleep, mood, and somatic symptoms among people with HF.

The aims of the study were to (a) evaluate the levels of self-care maintenance and self-care confidence among people with stable HF and chronic insomnia; (b) identify the clinical and demographic correlates of self-care maintenance and confidence among people with stable HF and chronic insomnia; and (c) identify the associations between sleep characteristics, mood and somatic symptoms, and self-care maintenance and confidence among people with stable HF and chronic insomnia.

We utilized a cross-sectional design with 195 adult participants who had chronic HF and insomnia. We assessed for symptoms of anxiety; depression; dyspnea; fatigue; stress; insomnia severity; and sleep disturbance, impairment, and quality. Self-care was measured using the Self-Care for Heart Failure Index v6.2. We used generalized linear models to test the associations between the demographic and clinical factors and self-care maintenance and confidence; exploratory and confirmatory factor analysis to identify the factor structure underlying the symptoms; and structural equation modeling to test the combined associations of the demographic and clinical factors and latent factors with self-care maintenance and confidence.

Self-care maintenance, confidence, and management were inadequate in most participants. We identified three latent factors among the nine symptoms: "sleep characteristics," "mood," and "somatic symptoms." In the structural equation model, "sleep characteristics," White race, and having a left ventricular ejection fraction of <45 were associated with self-care maintenance. Age was negatively associated with self-care confidence.

Poor sleep characteristics negatively influence the ability of people with HF and insomnia to perform self-care behaviors. Knowledge of the associations among age, left ventricular ejection fraction, and race with self-care will help clinicians and future researchers identify those at risk for poor self-care.

Insomnia is a common diseases of the elderly, tuina is a widely used treatment. At present, there is a lack of supportive evidence on efficacy and safety of tuina for senile insomnia. The purpose of this systematic review is to assess the effectiveness and safety of tuina therapy in the treatment of senile insomnia.

Literature on tuina for senile insomnia in the PubMed, EMBASE, Web of Science, Cochrane, China National Knowledge Infrastructure Database, Wanfang, Chinese Scientific and Journal Database, Japanese medical database, Korean Robotics Institute Summer Scholars, and Thai-Journal Citation Index Center will be conducted to search from the creation of these databases. We will search the databases from the beginning to January 2022. The primary outcome was the Pittsburgh Sleep Quality Index score, and the secondary outcomes included clinical efficacy and safety. RevMan 5.4.1 will be used for the meta-analysis.

This study aimed to will prove the effectiveness and safety of tuina therapy for the treatment of insomnia in the elderly.

This study provides up-to-date evidence of the effectiveness and safety of tuina for the treatment of senile insomnia.

INPLASY2021110063.

This systematic review will evaluate the effectiveness and safety of massage therapy for insomnia in the elderly population. As all the included data have been published, systematic reviews do not require ethical approval.

Previous research suggests that obstructive sleep apnea (OSA) and insomnia frequently co-exist and are prevalent in persons with type 2 diabetes mellitus (T2DM). This study compared mood and diabetes-related distress among OSA, insomnia, and comorbid OSA and insomnia (OSA+I) groups in persons with T2DM.

A secondary analysis was conducted with baseline data from two independent randomized controlled trials evaluating the efficacy of OSA and insomnia treatment. The pooled sample (N=224) included participants with OSA only (n=68 [30.4%]), insomnia only (n=107 [47.8%]), and OSA and insomnia (OSA+I; n=49 [21.9%]). OSA was defined as an apnea-hypopnea index ≥ 15 events per hour; insomnia defined as an Insomnia Severity Index score ≥ 15. Mood was measured by the Profile of Mood States total and subscale scores; diabetes-related distress was assessed by the Problem Areas in Diabetes. One-way analysis of covariance and multivariate analysis of covariance were conducted, controlling for demographic characteristics and restless leg syndrome.

The insomnia group had on average significantly higher scores for total mood disturbance (insomnia vs. OSA= 45.32 vs. 32.15, p=.049), tension-anxiety (insomnia vs. OSA= 12.64 vs. 9.47, p=.008), and confusion-bewilderment (insomnia vs. OSA= 9.45 vs. 7.46, p=.036) than OSA group. The OSA+I group had on average significantly greater diabetes-related distress than OSA group (OSA+I vs. OSA= 40.61 vs. 30.97, p=.036).

Insomnia may have greater impact on mood disturbance and diabetes-related distress than OSA in persons with T2DM. In particular, comorbid insomnia may contribute to greater diabetes-related distress in persons with T2DM and OSA.

Recently, the efficacy of cognitive behavioral therapy (CBT)-based intervention on health outcomes in patients with coronary heart disease (CHD) has been recognized in randomized controlled trials (RCTs), but no comprehensive systematic review has been conducted. To address this research gap, our study aimed to evaluate whether comprehensive CBT-based interventions positively affect health outcomes in CHD patients. It was hypothesized that CBT-based interventions are effective in: (1) Reducing depression, anxiety, and stress symptoms; (2) Reducing body mass index, blood pressure, and lipid levels; and (3) Improving quality of life, and exercise endurance.

To verify the effectiveness of CBT-based interventions on CHD patients through a meta-analysis of previous publications.

Relevant RCTs published in English were obtained by searching electronic databases, including PubMed, Embase, Cochrane Central Register of Controlled Trials, Scopus, and Proquest, with the retrieval time from inception to August 2020. The primary outcomes were psychological factors (depression, anxiety, and stress symptoms), physiological factors (body mass index, blood pressure, blood lipids). The secondary outcomes included quality of life and exercise endurance. We used Review Manager 5.3 to conduct the meta-analysis and used the Physiotherapy Evidence Database tool to evaluate the quality of studies.

A total of 22 RCTs comprising 4991 patients with CHD were included in the systematic review and meta-analysis. The main analysis revealed that CBT-based intervention can reduce depression symptoms: -2.00 [95% confidence interval (CI): -2.83 to -1.16, P < 0.001]; anxiety symptoms: -2.07 (95%CI: -3.39 to -0.75, P = 0.002); stress symptoms: -3.33 (95%CI: -4.23 to -2.44, P < 0.001); body mass index: -0.47 (95%CI: -0.81 to -0.13, P = 0.006); and improve physical functioning: 3.36 (95%CI: 1.63 to 5.10, P = 0.000) and mental functioning: 6.91 (95%CI: 4.10 to 9.73, P < 0.001). Moreover, subgroup analysis results showed that CBT-based interventions were more effective for symptoms of depression and anxiety in CHD patients when individual, as opposed to group treatment, and psycho-education, behavioral and cognitive strategies were applied as the core treatment approaches.

CBT-based interventions are effective treatment strategies for CHD patients, significantly improving their symptoms of depression, anxiety and stress, body mass index, and health-related quality of life.

Sleep disorders are linked to development of type 2 diabetes and increase the risk of developing diabetes complications. Treating sleep disorders might therefore play an important role in the prevention of diabetes progression. However, the detection and treatment of sleep disorders are not part of standardised care for people with type 2 diabetes. To highlight the importance of sleep disorders in people with type 2 diabetes, we provide a review of the literature on the prevalence of sleep disorders in type 2 diabetes and the association between sleep disorders and health outcomes, such as glycaemic control, microvascular and macrovascular complications, depression, mortality and quality of life. Additionally, we examine the extent to which treating sleep disorders in people with type 2 diabetes improves these health outcomes. We performed a literature search in PubMed from inception until January 2021, using search terms for sleep disorders, type 2 diabetes, prevalence, treatment and health outcomes. Both observational and experimental studies were included in the review. We found that insomnia (39% [95% CI 34, 44]), obstructive sleep apnoea (55-86%) and restless legs syndrome (8-45%) were more prevalent in people with type 2 diabetes, compared with the general population. No studies reported prevalence rates for circadian rhythm sleep-wake disorders, central disorders of hypersomnolence or parasomnias. Additionally, several cross-sectional and prospective studies showed that sleep disorders negatively affect health outcomes in at least one diabetes domain, especially glycaemic control. For example, insomnia is associated with increased HbA1c levels (2.51 mmol/mol [95% CI 1.1, 4.4]; 0.23% [95% CI 0.1, 0.4]). Finally, randomised controlled trials that investigate the effect of treating sleep disorders in people with type 2 diabetes are scarce, based on a small number of participants and sometimes inconclusive. Conventional therapies such as weight loss, sleep education and cognitive behavioural therapy seem to be effective in improving sleep and health outcomes in people with type 2 diabetes. We conclude that sleep disorders are highly prevalent in people with type 2 diabetes, negatively affecting health outcomes. Since treatment of the sleep disorder could prevent diabetes progression, efforts should be made to diagnose and treat sleep disorders in type 2 diabetes in order to ultimately improve health and therefore quality of life.

"Why treat insomnia?" This question grows out of the perspective that insomnia is a symptom that should only receive targeted treatment when temporary relief is needed or until more comprehensive gains may be achieved with therapy for the parent or precipitating medical or psychiatric disorders. This perspective, however, is untenable given recent data regarding the prevalence, course, consequences, and costs of insomnia. Further, the emerging data that the treatment of insomnia may promote better medical and mental health (alone or in combination with other therapies) strongly suggests that the question is no longer "why treat insomnia," but rather "when isn't insomnia treatment indicated?" This perspective was recently catalyzed with the American College of Physicians' recommendation that chronic insomnia should be treated and that the first line treatment should be cognitive-behavioral therapy for insomnia (CBT-I).