Relationship and variation of diabetes related symptoms, sleep disturbance and sleep-related impairment in adults with type 2 diabetes

Evaluation of Complications, Peripheral Neuropathic Pain, and Sleep Quality in Patients With Diabetes Mellitus

BACKGROUND

Most patients with diabetic peripheral neuropathy (DPN) suffer from problems such as neuropathic pain, sleep disturbance, anxiety, and depression, which negatively affect their quality of life. Painful DPN is one of the most common grounds for seeking medical attention. The aim of this study is to evaluate the complications, peripheral neuropathic pain, and sleep quality in diabetic patients.

METHODS

This descriptive, cross-sectional, and correlational study included 300 patients with neuropathic pain. Data were obtained using the Descriptive Information Form, Self-Administered Leeds Assessment of Neuropathic Symptoms and Signs Scale (S-LANSS), and Richards-Campbell Sleep Questionnaire (RSQ).

RESULTS

The mean level of peripheral neuropathic pain that the patients suffered in the last week, according to the VAS, was 4.143 ± 2.983. The S-LANSS mean score of the patients was 16.493 ± 7.536, and their total mean score on the RSQ was 39.986 ± 33.150. There was a statistically significant negative correlation between the mean scores of the S-LANSS and the RSQ (r = -0.489, p < 0.001). There was also a statistically significant negative correlation between the mean scores of the Neuropathic Pain VAS and the RSQ (r = -0.401, p < 0.001). Total S-LANSS Score, duration of diabetes diagnosis, HbA1c%, neuropathic pain VAS severity, and age accounted for 36.1% of the variance in the quality of sleep score of patients.

CONCLUSION

Neuropathic pain and poor sleep quality were prevalent in diabetic patients. It was found that the duration of DM and microvascular complications, particularly neuropathy, impaired sleep quality.

Psychosocial factors influencing dietary management in patients with type 2 diabetes and healthy adults: an ecological momentary assessment approach

Background

Dietary management in diabetic patients is affected by psychosocial factors and the social-environmental context. Ecological momentary assessment (EMA) allows patients to consistently report their experiences in real-time over a certain period and across different contexts. Despite the importance of dietary management, only a few EMA studies have been conducted on dietary management and psychosocial factors in patients with type 2 diabetes; further evidence must be gathered. Therefore, this study examined dietary management and psychosocial factors using EMA, comparing type 2 diabetes patients with healthy adults.

Methods

A total of 20 patients with type 2 diabetes and 16 healthy adults underwent EMA. Relying on event-contingent recordings, this study evaluated the participants' mood (e.g., anxiety, anger, vigor), appetite (hunger, craving), meal types (e.g., breakfast), location (e.g., eating out), companions (e.g., family), and dietary lapses (e.g., I ate a larger portion of a meal or snack than I intended) before and after meals. Dietary lapse recording after meals was paired with psychosocial data before meals. Only the type 2 diabetes patients used a sensor-based glucose monitoring system (Freestyle Libre Pro, Abbot) and wearable activity monitors (GT3X-BT, ActiGraph).

Results

The EMA produced a total of 4,254 responses. Dietary lapse predicted two-hour postprandial glucose through a sensor-based glucose monitoring system. Multilevel logistic regression analyses were performed. For diabetes patients, dietary lapse was affected by vigor, fatigue, and cravings before eating. Meanwhile, for healthy adults, only fatigue before meals affected dietary lapse, and increased vigor from dietary intake was associated with dietary lapse. In both type 2 diabetes patients and healthy adults, eating-out situations were linked to dietary lapse.

Conclusion

The results suggest differences in psychosocial factors influencing dietary lapse between patients with type 2 diabetes and healthy adults. EMA is well suited to assess psychosocial factors that drive dietary management in diabetic patients. This study further discussed the possibility of individual approaches using EMA data.

Sleep Architecture Changes in Diabetes

Data on the relationship between sleep architecture and diabetes are limited. However, some evidence suggests that slow-wave sleep (SWS) plays a crucial role in maintaining normal glucose homeostasis and influences insulin secretion capacity. Diabetes is often associated with reduced SWS, even in the absence of sleep-disordered breathing. Notably, selective suppression of SWS-without reducing total sleep time-can lead to significant increases in insulin resistance, decreased glucose tolerance, and a higher risk of diabetes. Given the growing interest in non-pharmacological lifestyle interventions, such as modifying sleep architecture, it is important to understand how sleep patterns differ in individuals with diabetes and whether these alterations impact diabetes risk and glycemic control. This review aims to provide a concise overview of the current findings on sleep architecture changes in people with diabetes.

Symptom Burden Contributes to Sleep Problems Through Depressive Symptoms in Middle-Aged and Older Adults With Type 2 Diabetes: A Multigroup Analysis

PURPOSE

The purpose of this study was to examine the relationships between symptom burden and sleep problems and the role of depressive symptoms on these relationships in middle-aged and older adults with type 2 diabetes.

METHODS

The study employed a cross-sectional, correlational design with secondary analysis. De-identified data sets from three original studies were combined. A total of 189 men and women with type 2 diabetes were recruited using convenience sampling in midwestern United States. Symptom burden, sleep impairment and sleep disturbance, depressive symptoms, demographics, and diabetes-related variables were assessed. The participants were grouped into glucose-controlled and -uncontrolled groups to examine a multigroup effect. Multigroup path analyses were conducted.

RESULTS

The results indicated that symptom burden had direct and indirect effects through depressive symptoms on sleep disturbance in the controlled group, whereas only a direct effect was found in the uncontrolled group. For sleep-related impairment, significant direct and indirect effects of symptom burden were found via depressive symptoms in both groups, and the strength of the effects on each path differed between the groups.

CONCLUSIONS

Diabetes symptom burden was associated with sleep disturbance and sleep-related impairment in middle-aged and older adults with diabetes. A different approach should be considered for sleep management according to their A1C levels, and depressive symptoms can be a therapeutic target to treat sleep problems in the population.

Deteriorated sleep quality and associate factors in patients with type 2 diabetes mellitus complicated with diabetic peripheral neuropathy

Objectives

To understand the sleep quality and its influencing factors in patients with type 2 diabetes mellitus (T2DM) who suffered diabetic peripheral neuropathy (DPN), and provide evidence for clinicians to carry out comprehensive intervention measures to improve the sleep quality of patients.

Methods

Patients who were admitted to the Endocrinology Department of Affiliated Hospital of Zunyi Medical University were recruited from May to December 2022, and the investigation were conducted by face-to-face interview. The questionnaires included PSQI questionnaire and influencing factors, such as lifestyle and health status.

Results

Among the 193 patients, 40.4% of the patients never took physical examination, 56.5% of the patients had duration of illness greater than 5 years, 61.7% of the patients had had an operation, 10.4% of the patients had bad dietary status, and 55.4% of the patients had physical pain. In addition, the PSQI general score was 8.34 ± 3.98, the occurrence rate of poor sleep quality (PSQI ≥ 8) was 54.4%, and the results showed that sleep quality of the physical pain group was worse than the no pain group. Moreover, the results of multivariate analysis revealed that the factors affecting sleep quality were lower frequency of exercise, bad dietary status, lower frequency of physical examination, longer duration of illness, and smoking, and the OR and 95% CI were [1.40, 1.04∼1.89], [3.42, 1.86∼6.29], [1.49, 1.01∼2.20], [1.78, 1.09∼2.92], [2.38, 1.17∼4.88], respectively.

Conclusion

Patients with DPN have higher risk of poor sleep quality. Moreover, there were many risk factors associated with poor sleep quality, clinicians and health policymakers should timely detect and effectively intervene in these factors to improve the sleep quality, which is important to enhance the quality of life of T2DM patients complicated with DPN.

Altered sleep architecture in diabetes and prediabetes: findings from the Baependi Heart Study

STUDY OBJECTIVES

People with diabetes and prediabetes are more likely to have sleep-disordered breathing (SDB), but few studies examined sleep architecture in people with diabetes or prediabetes in the absence of moderate-severe SDB, which was the aim of our cross-sectional study.

METHODS

This cross-sectional sample is from the Baependi Heart Study, a family-based cohort of adults in Brazil. About 1074 participants underwent at-home polysomnography (PSG). Diabetes was defined as fasting glucose >125 mg/dL or HbA1c > 6.4 mmol/mol or taking diabetic medication, and prediabetes was defined as HbA1c ≥ 5.7 & <6.5 mmol/mol or fasting glucose ≥ 100 & ≤125 mg/dl. We excluded participants with an apnea-hypopnea index (AHI) ≥ 30 in primary analyses and ≥ 15 in secondary analysis. We compared sleep stages among the 3 diabetes groups (prediabetes, diabetes, neither).

RESULTS

Compared to those without diabetes, we found shorter REM duration for participants with diabetes (-6.7 min, 95%CI -13.2, -0.1) and prediabetes (-5.9 min, 95%CI -10.5, -1.3), even after adjusting for age, gender, BMI, and AHI. Diabetes was also associated with lower total sleep time (-13.7 min, 95%CI -26.8, -0.6), longer slow-wave sleep (N3) duration (+7.6 min, 95%CI 0.6, 14.6) and higher N3 percentage (+2.4%, 95%CI 0.6, 4.2), compared to those without diabetes. Results were similar when restricting to AHI < 15.

CONCLUSIONS

People with diabetes and prediabetes had less REM sleep than people without either condition. People with diabetes also had more N3 sleep. These results suggest that diabetes and prediabetes are associated with differences in sleep architecture, even in the absence of moderate-severe sleep apnea.

Sleep disturbance exacerbates atherosclerosis in type 2 diabetes mellitus

Background

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.

Objective

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

Methods

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.

Results

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).

Conclusions

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.

Altered sleep architecture in diabetes and prediabetes: findings from the Baependi Heart Study

Objective

People with diabetes are more likely to have obstructive sleep apnea, but there are few studies examining sleep architecture in people with diabetes, especially in the absence of moderate-severe sleep apnea. Therefore, we compared sleep architecture among people with diabetes, prediabetes or neither condition, whilst excluding people with moderate-severe sleep apnea.

Research design and methods

This sample is from the Baependi Heart Study, a prospective, family-based cohort of adults in Brazil. 1,074 participants underwent at-home polysomnography (PSG). Diabetes was defined as 1) FBG>125 OR 2) HbA1c>6.4 OR 3) taking diabetic medication, and prediabetes was defined as 1) [(5.7≤HbA1c≤6.4) OR (100≤FBG≤125)] AND 2) not taking diabetic medication. We excluded participants that had an apnea-hypopnea index (AHI)>30 from these analyses to reduce confounding due to severe sleep apnea. We compared sleep stages among the 3 groups.

Results

Compared to those without diabetes, we found shorter REM duration for participants with diabetes (-6.7min, 95%CI -13.2, -0.1) or prediabetes (-5.9min, 95%CI -10.5, -1.3), even after adjusting for age, gender, BMI, and AHI. Diabetes was also associated with lower total sleep time (-13.7min, 95%CI -26.8, -0.6), longer slow-wave sleep (N3) duration (+7.6min, 95%CI 0.6, 14.6) and higher N3 percentage (+2.4%, 95%CI 0.6, 4.2), compared to those without diabetes.

Conclusions

People with diabetes and prediabetes had less REM sleep after taking into account potential confounders, including AHI. People with diabetes also had more N3 sleep. These results suggest that diabetes is associated with different sleep architecture, even in the absence of moderate-severe sleep apnea.

Financial Hardship and its Associations with Perceived Sleep Quality in Participants with Type 2 Diabetes and Obstructive Sleep Apnea

OBJECTIVES

The purpose of this study was to explore social determinants of health (SDoH), and disease severity as predictors of sleep quality in persons with both Obstructive Sleep Apnea (OSA) and type 2 diabetes (T2D).

METHODS

Disease severity was measured by Apnea-Hypopnea Index [(AHI) ≥ 5] and HbA1c for glycemic control. SDoH included subjective and objective financial hardship, race, sex, marital status, education, and age. Sleep quality was measured by Pittsburgh Sleep Quality Index (PSQI).

RESULTS

The sample (N = 209) was middle-aged (57.6 ± 10.0); 66% White and 34% African American; and 54% men and 46% women. Participants carried a high burden of disease (mean AHI = 20.7 ± 18.1, mean HbA1c = 7.9% ± 1.7%). Disease severity was not significantly associated with sleep quality (all p >.05). Worse sleep quality was associated with both worse subjective (b = -1.54, p = .015) and objective (b = 2.58, p <.001) financial hardship. Characteristics significantly associated with both subjective and objective financial hardship included being African American, female, ≤ 2 years post high school, and of younger ages (all p < .01).Discussion: Financial hardship is a more important predictor of sleep quality than disease severity, age, sex, race, marital status, and educational attainment, in patients with OSA and T2D.

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.

New Advances on Pathophysiology of Diabetes Neuropathy and Pain Management: Potential Role of Melatonin and DPP-4 Inhibitors

Pre-diabetes and diabetes are growing threats to the modern world. Diabetes mellitus (DM) is associated with comorbidities such as hypertension (83.40%), obesity (90.49%), and dyslipidemia (93.43%), creating a substantial burden on patients and society. Reductive and oxidative (Redox) stress level imbalance and inflammation play an important role in DM progression. Various therapeutics have been investigated to treat these neuronal complications. Melatonin and dipeptidyl peptidase IV inhibitors (DPP-4i) are known to possess powerful antioxidant and anti-inflammatory properties and have garnered significant attention in the recent years. In this present review article, we have reviewed the recently published reports on the therapeutic efficiency of melatonin and DPP-4i in the treatment of DM. We summarized the efficacy of melatonin and DPP-4i in DM and associated complications of diabetic neuropathy (DNP) and neuropathic pain. Furthermore, we discussed the mechanisms of action and their efficacy in the alleviation of oxidative stress in DM.

Poor Sleep Quality Linked to Decreased Brain Gray Matter Density in Adults with Type 2 Diabetes

BACKGROUND

Poor sleep is common in adults with Type 2 Diabetes Mellitus (T2DM), which may contribute to brain tissue changes. However, the impact of sleep quality on brain tissue in T2DM individuals is unclear. We aimed to evaluate differential sleep quality with brain changes, and brain tissue integrity in T2DM patients.

METHODS

Data were collected from 34 patients with T2DM and included sleep quality (assessed by the Pittsburgh Sleep Quality Index [PSQI], and high-resolution T1-weighted brain images using a 3.0-Tesla MRI scanner. Gray matter density (GMD) maps were compared between subjects with good vs poor sleep quality as assessed by PSQI (covariates: age, sex, BMI).

RESULTS

Of 34 T2DM patients, 17 showed poor sleep quality. Multiple brain sites, including the hippocampus, cerebellum, prefrontal, amygdala, thalamus, hypothalamus, insula, cingulate, and temporal areas, showed reduced gray matter in T2DM patients with poor sleep quality over patients with good sleep quality. Negative associations emerged between PSQI scores and gray matter density in multiple areas.

CONCLUSIONS

T2DM patients with poor sleep quality show brain tissue changes in sites involved in sleep regulation. Findings indicate that improving sleep may help mitigate brain tissue damage, and thus, improve brain function in T2DM patients.

An integrative review of fatigue in adults with type 2 diabetes mellitus: Implications for self-management and quality of life

AIMS AND OBJECTIVES

To synthesise empirical studies on factors related to fatigue and its impact on diabetes self-management (DSM) and quality of life (QOL) in adults with type 2 diabetes mellitus (T2DM).

BACKGROUND

Fatigue is commonly reported in people with T2DM, a chronic condition that is highly prevalent worldwide. However, a holistic understanding of the consequences and factors related to fatigue in adults with T2DM is not well synthesised.

DESIGN

This integrative review used Whittemore and Knafl's methodology and was reported according to the Preferred Reporting for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and checklist.

METHODS

The theory of unpleasant symptoms (TOUS) was used as a conceptual model to guide the review. The PubMed, PsychINFO and CINAHL databases were searched to identify studies that recruited adults with T2DM, were peer-reviewed, written in English and investigated fatigue as a primary or secondary outcome. Two investigators independently appraised the quality of the studies and extracted the data.

RESULTS

Twenty-nine articles met the inclusion criteria: 23 observational studies, two randomised controlled trials, one quasi-experimental study and three qualitative studies. All articles were of high quality. Physiological (e.g. T2DM duration, complications and inflammatory biomarkers), psychological (e.g. diabetes distress, depression and sleep quality) and situational factors (e.g. race/ethnicity, education and social support) were related to fatigue. Studies reported fatigue as a barrier to physical activity, healthy eating behaviours and the physical aspect of QOL.

CONCLUSIONS

Multiple factors are related to fatigue in adults with T2DM. Gaps in the literature include the multiple dimensions of fatigue, the effectiveness of interventions to alleviate fatigue and fatigue experiences in under-represented populations.

RELEVANCE TO CLINICAL PRACTICE

This integrative review supports the complex origin of fatigue and its impact on adults with T2DM. Nurses should evaluate modifiable factors related to fatigue and provide support to help improve DSM and QOL in this population.

Contributing factors of fatigue in patients with type 2 diabetes: A systematic review

Remarkable evidence supports the link between type 2 diabetes (T2DM) and fatigue. However, a unifying recommendation to identify and prevent fatigue or to prevent its clinical consequences in T2DM is not available at present. Therefore, this study aimed to conduct a systematic review to summarize the definition, measurement tools, and contributing factors of fatigue in T2DM. Nine articles were included for analysis, and results showed that T2DM fatigue was associated with five major factors, including sociodemographic factors, clinical disease factors, inflammatory factors, psychological factors, and behavior and lifestyle. The contributing factors of T2DM fatigue are reviewed, and clinical benefits provide a theoretical basis for further clinical intervention to prevent the occurrence of fatigue and improve the patient's treatment compliance and self-management ability and may be beneficial to their quality of life.

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.

Sleep Characteristics in Diabetic Patients Depending on the Occurrence of Neuropathic Pain and Related Factors

This study aims to compare the sleep characteristics (structure and quality) in patients with type-2 diabetes mellitus with and without diabetic neuropathic pain (DNP), and to investigate the relationship of sensory phenotypes, anxiety, and depression with sleep quality in DNP patients. A cross-sectional study was performed in patients with type-2 diabetes mellitus and neuropathy. Patients were classified into two groups-with or without neuropathic pain-according to the "Douleur Neuropathique-4 (DN4)" scale. Sleep characteristics and quality (Medical Outcomes Study-MOS-sleep), pain phenotype (Neuropathic Pain Symptom Inventory-NPSI), mood status (Hospital Anxiety and Depression scale-HADS), pain intensity (Visual Analogue Scale-VAS), and quality of life (SF-12v2) were measured. The sample included 130 patients (65 with DNP). The mean scores in all the dimensions of the MOS-sleep scale were higher (more disturbances) in the DNP patients. Higher scores in anxiety or depression, greater intensity of pain or a higher score in the paroxysmal pain phenotype were associated with lower sleep quality in DNP patients. A shorter duration of the diabetes and lower levels of glycated hemoglobin were also associated with lower sleep quality. The results show the relationship between DNP and sleep quality, and the importance of assessing sensory phenotypes and mental comorbidities in these patients. Taking these factors into consideration, to adopt a multimodal approach is necessary to achieve better clinical results.

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).

A randomized controlled trial of cognitive behavioral therapy compared with diabetes education for diabetic peripheral neuropathic pain

A randomized controlled trial compared cognitive behavioral therapy (CBT) and diabetes education (ED) as an adjunctive treatment for diabetic peripheral neuropathic pain (DPNP). We examined change from baseline to 12- and 36-week follow-up in overall pain intensity (NRS), neuropathic pain intensity/quality, pain interference, and mental health functioning, among others. Although CBT participants demonstrated improvement in pain intensity NRS, there were no between-condition differences at either follow-up. CBT reduced neuropathic pain intensity at 12-weeks more than ED. At 36-weeks, CBT was superior to ED for improving pain interference and mental health functioning. Results provide evidence of benefit of CBT for DPNP.

ClinicalTrials.gov Identifier: NCT00830011

Sleep Efficiency and Total Sleep Time in Individuals with Type 2 Diabetes with and without Insomnia Symptoms

There is increasing awareness of the high prevalence of insomnia symptoms in individuals with type 2 diabetes (T2D). Past studies have established the importance of measuring sleep parameters using measures of central tendency and variability. Additionally, subjective and objective methods involve different constructs due to the discrepancies between the two approaches. Therefore, this study is aimed at comparing the averages of sleep parameters in individuals with T2D with and without insomnia symptoms and comparing the variability of sleep parameters in these individuals. This study assessed the between-group differences in the averages and variability of sleep efficiency (SE) and total sleep time (TST) of 59 participants with T2D with and without insomnia symptoms. Actigraph measurements and sleep diaries were used to assess sleep parameter averages and variabilities calculated by the coefficient of variation across 7 nights. Mann-Whitney U tests were utilized to compare group differences in the outcomes. Validated instruments were used to assess the symptoms of depression, anxiety, and pain as covariates. Objective SE was found to be statistically lower on average (85.98 ± 4.29) and highly variable (5.88 ± 2.57) for patients with T2D and insomnia symptoms than in those with T2D only (90.23 ± 6.44 and 3.82 ± 2.05, respectively). The subjective average and variability of SE were also worse in patients with T2D and insomnia symptoms, with symptoms of depression, anxiety, and pain potentially playing a role in this difference. TST did not significantly differ between the groups on averages or in variability even after controlling for age and symptoms of depression, anxiety, and pain. Future studies are needed to investigate the underlying mechanisms of worse averages and variability of SE in individuals with T2D and insomnia symptoms. Additionally, prompting the associated risk factors of insomnia symptoms in individuals with T2D might be warranted.

Changes in Patient-Reported Outcome Measures With a Technology-Supported Behavioral Lifestyle Intervention Among Patients With Type 2 Diabetes: Pilot Randomized Controlled Clinical Trial

BACKGROUND

In the United States, more than one-third of the adult population is obese, and approximately 25.2% of those aged ≥65 years have type 2 diabetes (T2D), which is the seventh leading cause of death. It is important to measure patient-reported outcomes and monitor progress or challenges over time when managing T2D to understand patients' perception of health and quantify the impact of disease processes or intervention effects. The evaluation of patient-reported outcome measures (PROMs) is especially important among patients with multiple chronic conditions in which clinical measures do not provide a complete picture of health.

OBJECTIVE

This study examined the feasibility of collecting Patient-Reported Outcome Measurement Information System (PROMIS) measures, and preliminarily evaluated changes in PROMIS scores and compared the scores with standard scores of the general US population. The parent study is a pilot randomized controlled clinical trial testing three different modes (mobile health [mHealth], paper diary, and control) of self-monitoring in a behavioral lifestyle intervention among overweight or obese patients with T2D.

METHODS

Patients with comorbid overweight or obesity and a diagnosis of T2D for at least 6 months were recruited from a diabetes education program. Participants were randomized to the following three groups: mHealth, paper diary, and control (standard of care) groups. Paper diary and mHealth experimental groups received additional behavioral lifestyle intervention education sessions, as well as tools to self-monitor weight, physical activity, diet, and blood glucose. All participants completed PROMIS-57 and PROMIS-Global Health (GH) version 1.0 questionnaires during visits at baseline, 3 months, and 6 months. The PROMIS-57 includes the following seven domains: anxiety, depression, fatigue, pain interference, physical function, satisfaction with participation in social roles, and sleep disturbance. The PROMIS-GH is composed of the following two domains: global mental health and global physical health.

RESULTS

A total of 26 patients (mHealth, 11; paper diary, 9; control, 6) were included in our analysis. The study sample was predominantly African American (68%) and female (57%), with a mean age of 54.7 years and a mean BMI of 37.5 kg/m2. All patients completed the PROMIS-57 and PROMIS-GH questionnaires, and we compared the mean scores of the three groups to investigate potential differences. No relevant differences were noted across the groups. However, positive trends were noted in both intervention (mHealth and paper diary) groups in the middle (month 3) and end (month 6) of the study.

CONCLUSIONS

Our pilot study provides evidence for the feasibility of using PROMIS questionnaires to record important components of T2D-related symptoms among overweight or obese individuals. The results from our study support the use of PROMIS questionnaires to provide clinicians and researchers with a benchmark for assessing the overall need for symptom management and determining the success or challenges of an intervention.

TRIAL REGISTRATION

ClinicalTrials.gov NCT02858648; https://clinicaltrials.gov/ct2/show/NCT02858648.

Prevalence of Insomnia (Symptoms) in T2D and Association With Metabolic Parameters and Glycemic Control: Meta-Analysis

OBJECTIVE

We aimed to determine the prevalence of insomnia and insomnia symptoms and its association with metabolic parameters and glycemic control in people with type 2 diabetes (T2D) in a systematic review and meta-analysis.

DATA SOURCES

A systematic literature search was conducted in PubMed/Embase until March 2018.

STUDY SELECTION

Included studies described prevalence of insomnia or insomnia symptoms and/or its association with metabolic parameters or glycemic control in adults with T2D.

DATA EXTRACTION

Data extraction was performed independently by 2 reviewers, on a standardized, prepiloted form. An adaptation of Quality Assessment Tool for Quantitative Studies was used to assess the methodological quality of the included studies.

DATA SYNTHESIS

When possible, results were meta-analyzed using random-effects analysis and rated using Grading of Recommendations Assessment, Development and Evaluation (GRADE).

RESULTS

A total of 11 329 titles/abstracts were screened and 224 were read full text in duplicate, of which 78 studies were included. The pooled prevalence of insomnia (symptoms) in people with T2D was 39% (95% confidence interval, 34-44) with I2 statistic of 100% (P < 0.00001), with a very low GRADE of evidence. Sensitivity analyses identified no clear sources of heterogeneity. Meta-analyses showed that in people with T2D, insomnia (symptoms) were associated with higher hemoglobin A1c levels (mean difference, 0.23% [0.1-0.4]) and higher fasting glucose levels (mean difference, 0.40 mmol/L [0.2-0.7]), with a low GRADE of evidence. The relative low methodological quality and high heterogeneity of the studies included in this meta-analysis complicate the interpretation of our results.

CONCLUSIONS

The prevalence of insomnia (symptoms) is 39% (95% confidence interval, 34-44) in the T2D population and may be associated with deleterious glycemic control.

Associations Between Dietary Patterns and Sleep-Related Impairment in a Cohort of Community Physicians: A Cross-sectional Study

There is increasing evidence that diet can mitigate fatigue. The objective of this study was to assess the associations between dietary habits and sleep-related impairment (SRI) in a cohort of community physicians. In this cross-sectional study, we analyzed data from 245 physicians who had completed a wellness survey in March 2016 (98% response rate). Three dietary patterns were derived using principal component analysis: plant based, high protein, and high saturated fat and sugar. In the adjusted analysis, every SD increase in the plant-based dietary pattern score was associated with a 0.71-point decrease (β = -0.72; SE = 0.32; P = .027; 95% CI = -1.35 to -0.08) in the SRI score, and every SD increase in the high saturated fat and sugar dietary pattern score was associated with a 0.77-point increase (β = 0.77; SE = 0.32; P = .015; 95% CI = 0.15 to 1.39) in the SRI score. There were no associations between high protein diets and SRI scores. Physicians adhering to diets that are high in plant-based foods and low in saturated fat and added sugars had less SRI. Physicians currently face significant barriers to maintaining a healthy diet. This study highlights the potential role of workplace nutrition on SRI and work performance of physicians.