Prevalence, symptomatic features, and factors associated with sleep disturbance/insomnia in Japanese patients with type-2 diabetes

Insomnia and its risk factors in patients with type 2 diabetes: A cross-sectional study

AIMS

Insomnia is notably prevalent among individuals with type 2 diabetes and adversely affects both glycemic control and overall quality-of-life. The objective of this study was to evaluate the possible risk factors for insomnia in patients diagnosed with type 2 diabetes and co-morbid insomnia.

METHODS

This is a baseline study analyzing cross-sectional data at baseline timepoint collected in a randomized controlled trial study. A total of 227 participants with type 2 diabetes and insomnia were recruited. The diagnosis of insomnia was based on Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition and the total score of Insomnia Severity Index. Multiple linear regression model was used to analyze the possible biomedical and mental health risk factors for insomnia severity, total sleep time, sleep efficiency and sleep onset latency.

RESULTS

Factors significantly associated with insomnia severity included fasting blood glucose and depression. Blood magnesium level was related to total sleep time. Sleep efficiency was associated with blood phosphorus. Factors related to sleep onset latency were depression and fatigue.

CONCLUSION

Factors related to high insomnia severity and poor sleep quality in type 2 diabetes patients with insomnia included fasting blood glucose, blood magnesium, blood phosphorus, depression and fatigue.

Association between persistent nocturnal sleep duration patterns and carotid intima-media thickness in Chinese patients with type 2 diabetes

The aim of this study was to investigate the association between persistent nocturnal sleep duration patterns and carotid intima-media thickness (CIMT) in Chinese patients with type 2 diabetes mellitus (T2DM). From March 1, 2018 to August 31, 2023, a cross-sectional study was carried out at the National Metabolic Management Center of the First Affiliated Hospital of Ningbo University. Each patient completed a minimum of three sleep questionnaire assessments during the study period. Group-based trajectory modeling was employed to identify distinct groups of patients exhibiting different trajectories of nocturnal sleep duration. CIMT ≥ 1 mm was used to assess early atherosclerotic changes in arterial structure. Multiple logistic regression was used to assess the association between trajectories of nocturnal sleep duration and CIMT. Three trajectories of nocturnal sleep duration were identified: persistent short (6.44 h: n = 114, 13.5% of all subjects), persistent moderate (7.59 h: n = 500, 59.0%), and persistent long (8.69 h: n = 233, 27.5%). After adjusting for age, sex, education, body mass index, physical activity, current smoking, current alcohol drinking, hypertension, hyperlipidemia, and HbA1c, the odds of CIMT ≥ 1 mm were found to be higher in patients with persistent short nocturnal sleep duration (OR 3.03, 95%CI 1.15, 7.98). However, no significant association was found between persistent long sleep duration at night and CIMT ≥ 1 mm. Persistent short nocturnal sleep duration was associated with increased CIMT in Chinese patients with T2DM. Further longitudinal studies are warranted to fully elucidate this topic.

Prevalence and correlates of insomnia and fatigue in patients with type 2 diabetes in Jordan

OBJECTIVE

The present study examined the prevalence and correlates of insomnia and fatigue in patients with type-2 diabetes in Jordan.

METHODS

This was a cross-sectional online study involving a convenience sample of 390 patients with type-2 diabetes. Insomnia was assessed by the Insomnia-Severity Index (ISI-A) and fatigue by the Brief Fatigue Inventory (BFI-A).

RESULTS

Severe insomnia was present in 132 patients (33.8%), and was correlated with length of diabetes (diagnosis >5 years) (OR = 2.13, 95% CI = 1.19-3.81, P = 0.01), presence of uncontrolled diabetes (OR = 1.97, 95% CI = 1.45-2.69, P < 0.001), taking gabapentin (OR = 2.07, 95% CI = 1.07-4.01, P = 0.003), and age (<40 years) (OR = 0.30, 95% CI = 0.13-0.69, P = 0.005). Significant fatigue was also prevalent and correlated with gender (female) (B = 9.25, t = 4.48, P < 0.001), age (<40 years) (B = 7.56, t = 2.56, P = 0.01), a diagnosis of hypertension (B = 4.74, t = 2.03, P = 0.04), uncontrolled diabetes (B = 7.21, t = 4.82, P < 0.001), and taking a sulfonylurea (B = 8.03, t = 3.37, P < 0.001), carbamazepine (B = 10.93, t = 2.65, P = 0.008), or gabapentin (B = 12.60, t = 3.83, P < 0.001).

CONCLUSION

Given the high prevalence of insomnia and fatigue in this population, increased attention by primary healthcare providers to these symptoms in diabetic patients is warranted, particularly in developing countries such as Jordan.

The association between insomnia (related symptoms) and glycaemic control: a systematic review and meta-analysis

Background

Insomnia characterised by difficulties in falling asleep and maintaining sleep, and early awaking, is a prevalent worldwide sleep disorder. While previous studies have suggested an association between insomnia and adverse glycaemic control, the evidence remains inconclusive. Therefore, this meta-analysis aims to explore this association.

Methods

Insomnia was assessed based on defined criteria, including related symptoms such as poor sleep quality and low sleep efficiency. Glycaemic control was evaluated using indicators such as fasting plasma glucose, haemoglobin A1c, and the presence of diabetes. A literature search was performed in PubMed, Web of Science, and Scopus. The quality of the included studied was assessed using The Newcastle-Ottawa Scale. Effect sizes, including odds ratio, relative risk, mean difference, and standard mean difference, were chosen based on data type. Forest plots visually displayed pooled effect sizes and corresponding 95% confidence intervals, while the I2 test calculated heterogeneity. Meta-regression and subgroup analysis explored potential sources of heterogeneity. Leave-one-out sensitivity analysis assessed result robustness, and Begg's and Egger's tests evaluated publication bias.

Results

Ninety-one articles, comprising 84 are cross-sectional studies, (five are case-control studies, and two are cohort studies) with 2 217 521 participants, were included. Ten separate meta-analyses were conducted based on variable type (binary/continuous), study design (cross-sectional, case-control, or cohort), and measurement of exposures/outcomes. All meta-analyses indicated a positive association between insomnia (related symptoms) and adverse glycaemic control. However, three meta-analyses showed significant heterogeneity, and three lacked robustness. No publication bias was detected across any of the analyses.

Conclusions

Insomnia is likely associated with adverse glycaemic control. As the included studies are observational, future research should prioritise diverse methodologies and robust study designs to further explore this complex relationship.

Keywords

insomnia, insomnia related symptoms, glycaemic control, systematic review, meta-analysis.

Registration

PROSPERO CRD42024491688.

Quality of Sleep and Its Determinants Among People with Diabetes Mellitus in Sub-Saharan Africa: A Systematic Review and Meta-Analysis

BACKGROUND

Poor sleep quality is a serious concern among diabetes mellitus patients, adversely affecting glycemic management and the prognosis of diabetic patients. Therefore, the main aim of this study was to estimate the overall pooled prevalence of poor sleep quality and its associated factors among diabetic patients in Sub-Saharan Africa.

METHODS

Several search databases were employed to retrieve the eligible studies. A standardized data extraction format was used to extract the data, and the analysis was conducted using STATA version 14. To determine heterogeneity, the I2 test was conducted, and both the funnel plot and Egger's regression test were used to assess the publication bias. A random effects model meta-analysis was performed to estimate the overall prevalence and associated factors of poor sleep quality.

RESULTS

In the current meta-analysis, a total of 11 studies with 3,766 study participants were included. The overall pooled prevalence of poor sleep quality among diabetic patients was 53.22% (95% CI: 36.26, 70.19). Poor sleep quality was significantly associated with longer duration of diabetes (OR = 2.94, 95% CI: 1.85, 4.67), poor glycemic control (OR = 2.24, 95% CI: 1.51, 3.32), depression (OR = 4.09, 95% CI: 2.07, 8.05) and comorbidity (OR = 1.94, 95% CI: 1.31, 2.88).

CONCLUSION

In this study, more than half of diabetic patients in Sub-Saharan Africa had poor sleep quality. Therefore, healthcare providers should give more attention to sleep disorders when screening diabetic patients to improve their poor sleep quality.

Relationship between sleep quality and depression in people with type 2 diabetes

Background

sleep quality disorder is both a risk factor for diabetics and a symptom of depression. This study aimed to determine the relationship between sleep quality and depression in people with type 2 diabetes in Delijan city in 2022.

Methods

The present study was a descriptive-analytical study conducted on 245 people with Type 2 Diabetes Mellitus(T2DM). The data were collected from health centers and homes, diabetes clinics in the city of Delijan. The sampling method in this study was Convenienc. Inclusion criteria include people over 30 years old, people with a history of diabetes for more than six months and and people with no known mental disorders. Data collection tools included the Pittsburgh Sleep Quality Index (PSQI), the Beck questionnaire, clinical information about diabetes(FBS, %HbA1c level and duration of diabetes), and a checklist of demographic information. SPSS 23 software was used for data analysis. Data were analyzed using independent t-tests, Chi-square, ANOVA and logistic regression. A significance level of P < 0.05 was considered significant.

Results

The mean (SD) age of the participants was 57.58 (10.58) years. Regarding gender, 162 subjects (66.1%) were female. A statistically significant relationship was observed between the quality of sleep in people with type 2 diabetes with gender, education, Family history T2DM, age, and between depression with gender and FBG. a statistically significant relationship was observed between sleep quality and depression. Also, according to the logistic regression, sleep quality (dependent variable) showed a significant relationship with depression, age, sex, and education.

Conclusion

According to the results, there is a significant relationship between sleep quality and depression In people with T2DM, so it can be used in periodic care of diabetic people to screen for depression, which could improve their sleep quality to some extent.

Sleep quality in relation to perceived psychological stress in patients with type 2 diabetes and in age- and sex-matched control individuals

AIM

To assess sleep quality in relation to perceived stress in patients with type 2 diabetes (T2DM) and age- and sex-matched controls.

METHODS

Perceived stress level and sleep quality assessed in 154 patients with T2DM (58 men, 96 women, age 58.3 ± 11.9 years), 154 matched controls (58 men, 96 women, age 56.8 ± 12.2 years) using Perceived Stress Scale and Pittsburgh Sleep Quality Index.

RESULTS

Patients with T2DM had worse subjective sleep quality (p < 0.001), sleep latency (p = 0.047) than controls. Patients with high stress level had worse subjective sleep quality (p = 0.027), higher use of sleeping medication (p = 0.023), daytime dysfunction (p < 0.001) than those with low stress level. No significant differences in sleep quality between controls with high and low perceived stress level. Perceived stress level in patients with T2DM correlated with subjective sleep quality (r = 0.260, p = 0.002), sleep duration (r = 0.228, p = 0.005), use of sleep medication (r = 0.245, p = 0.004), daytime dysfunction (r = 0.326, p < 0.001), in age- and sex-matched controls-to daytime dysfunction (r = 0.191, p = 0.037).

CONCLUSION

Sleep quality (subjective sleep quality, sleep latency) is worse in patients with type 2 diabetes than in age- and sex-matched controls. Patients with high perceived stress level have worse subjective sleep quality, higher use of sleeping medication, daytime dysfunction than patients with low perceived stress level; no significant differences in sleep quality between controls with high and low stress level. Perceived stress level in patients with type 2 diabetes is related to subjective sleep quality, sleep duration, use of sleep medication, daytime dysfunction, in age- and sex-matched controls-to daytime dysfunction.

The Prevalence of Sleep Disorders in People with Type 2 Diabetes and Obesity in Saudi Arabia: A Cross-Sectional Study

Purpose

Difficulty falling or staying asleep are considered sleep disorders, and these are common among people with type 2 diabetes mellitus (T2DM) and obesity. The presence of sleep disorders may cause poor glycemic control among this population. We therefore designed this study to assess sleep disorders among patients with T2DM and obesity.

Patients and Methods

This cross-sectional study examined the prevalence of sleep disorders in 148 patients with T2DM and obesity at a hospital in Taif, Saudi Arabia using a validated questionnaire.

Results

Among those patients who have been involved in this study, we found a moderate level of sleep disorders and disturbances. The average sleep disorder assessment score for the patients with T2DM and obesity was 2.8 ± 1.4. Additionally, the average score for the sleep pattern assessment was 2.7 ± 1.3 and 2.9 ± 1.5 for symptoms of lack of sleep. Our study also revealed that those patients also had suboptimal weight and glycemic control.

Conclusion

These findings demonstrate that patients with T2DM and obesity are at a higher risk of developing sleep disorders. Therefore, these patients need to be screened for sleep disorders to avoid further diabetes-related complications and to have an early lifestyle intervention.

Sleep quality and its associated factors among patients with type 2 diabetes mellitus in Hunan, China: a cross-sectional study

OBJECTIVES

Type 2 diabetes mellitus (T2DM) is a serious public health issue. Compared with the general population, patients with T2DM have a higher risk of poor sleep quality, which could ultimately result in poor prognosis. Therefore, this study aimed to evaluate sleep quality and its associated factors among patients with T2DM in Hunan, China.

DESIGN

This was a cross-sectional study.

SETTING

A tertiary hospital in Hunan, China.

PARTICIPANTS

Patients with T2DM hospitalised at the Endocrinology Department were consecutively enrolled between March 2021 and December 2022. Sociodemographic characteristics, lifestyle factors and T2DM-related information were collected retrospectively.

PRIMARY AND SECONDARY OUTCOME MEASURES

Sleep quality was evaluated using the Pittsburgh Sleep Quality Index, with a cut-off value of >7 suggesting poor sleep quality. Multivariate logistic regression analysis was used to determine factors associated with poor sleep quality.

RESULTS

Of the 1039 participants included, 1001 provided complete data. The mean age of the study sample was 60.24±10.09 years, and 40.5% (95% CI 37.5% to 43.5%) of patients had poor sleep quality. Multivariate logistic regression analysis showed that female sex (adjusted OR (aOR) 1.70, 95% CI 1.25 to 2.29), unmarried status (aOR 1.72, 95% CI 1.05 to 2.83), diabetic retinopathy (aOR 1.38, 95% CI 1.04 to 1.83), diabetic foot (aOR 1.80, 95% CI 1.11 to 2.93) and a per capita monthly household income of >5000 RMB (aOR 0.66, 95% CI 0.47 to 0.93) were associated with poor sleep quality.

CONCLUSIONS

Nearly two-fifths of patients with T2DM reported poor sleep quality in Hunan, China. Sex, marital status, diabetic retinopathy, diabetic foot and household income were independently associated with sleep quality among patients with T2DM in Hunan, China.

Effects of light therapy on sleep and circadian rhythm in older type 2 diabetics living in long-term care facilities: a randomized controlled trial

Background

Light influences the secretion of melatonin in the body and regulates circadian rhythms, which play an important role in sleep and mood. The light level of rooms in long-term care facilities is usually far below the threshold required to regulate the body's circadian rhythm, and insufficient light can easily lead to sleep and mood disturbances among older residents in nursing homes. Therefore, the objective of this study was to investigate the effects of light therapy on sleep and circadian rhythm in older adults with type 2 diabetes residing in long-term care facilities.

Methods

This study was a prospective, single-blind, randomized controlled trial. Participants were randomly assigned to either the light therapy (LT) group or the control group and received the intervention for four weeks. Primary outcomes included the Pittsburgh Sleep Quality Index (PSQI) and objective sleep parameters recorded by a sleep monitoring bracelet, Morningness-Eveningness Questionnaire (MEQ). The secondary outcome included glycated serum protein (GSP). Data was collected at three time points: at baseline (T0), immediate post-treatment (T1), and 4-week follow-up (T2). A linear mixed model analysis was used to analyzed the data.

Results

We enrolled 45 long-term care residents. Compared with the control group, significant reductions in PSQI scores were observed at T1 and T2. At T2, the sleep score of objective sleep parameters was significantly higher in the LT group compared to the control group. Additionally, compared to the baseline T0, MEQ scores were significantly lower in the LT group at T1 and T2, with no significant difference in the control group. There was no significant difference between groups in glycated serum protein values at T1 and T2. However, compared to T0, glycated serum protein values decreased in the LT group while increased in the control group at T2.

Conclusion

Light therapy had a positive effect on subjective sleep quality and circadian rhythm time type in long-term care residents with type 2 diabetes, and had a possible delayed effect on objective sleep. However, no discernible alterations in blood glucose levels were detected in this study.

Latent Profile Analysis of Fear of Hypoglycemia in Middle-Aged and Elderly Hospitalized Patients with Type 2 Diabetes and Its Relationship with Sleep Quality

Introduction

Hypoglycemia is an acute complication that can appear in people with type 2 diabetes treated with drugs which are associated with a risk of hypoglycemia, and it may lead to individual's fear of hypoglycemia (FoH). FoH adversely affects diabetic self-management, psychological well-being, and quality of life, and it is associated with sleep quality. Nevertheless, this problem is often underestimated. The purpose of this study was to explore the heterogeneous characteristics of FoH in middle-aged and elderly hospitalized patients with type 2 diabetes and assess its relationship with the sleeping quality.

Patients and Methods

A cross-sectional study was performed on 263 middle-aged and elderly patients with type 2 diabetes hospitalized at the Zhejiang Veteran Hospital in Jiaxing, China, from May to August 2022, selected by a convenient sampling method. A questionnaire containing general information, fear of hypoglycemia scale-15 (FH-15) and the Pittsburgh sleep quality index (PSQI) was provided to the participants. Latent profile analysis was performed to examine the potential latent groups in the distribution of answers on the individual FoH items.

Results

The results identified three latent classes: Class 1 - Low FoH group (33%); Class 2 - No FoH group (61%); Class 3 - High FoH group (6%). The latent FoH class was the influencing factor of sleep quality, which was better in the No FoH group than in the Low FoH group, while the sleep quality of the Low FoH group was better than that in the High FoH group.

Conclusion

A heterogeneity was found in the FoH of middle-aged and elderly hospitalized patients with type 2 diabetes. Health-care providers should pay more attention to these patients with high FoH and develop intervention strategies to mitigate it and improve their sleep quality.

Association between the Pittsburgh sleep quality index and white matter integrity in healthy adults: a whole-brain magnetic resonance imaging study

To disclose possible associations between poorer sleep quality and structural brain alterations in a non-psychiatric healthy population, this study investigated the association between the Pittsburgh sleep quality index (PSQI) and brain correlates, using a whole-brain approach. This study included 371 right-handed healthy adults (138 males, mean age: 46.4 ± 14.0 years [range: 18-75]) who were right-handed. Subjective sleep quality was assessed using the Japanese version of the PSQI (PSQI-J), and the cutoff score for poor subjective sleep quality was set at ≥ 6. Voxel-based morphometry (VBM) and diffusion tensor imaging (DTI) were performed to examine whether a higher score of the PSQI-J indicates, poorer sleep quality is associated with gray matter volume and white matter microstructure alternations, respectively. Among the participants, 38.8% had a PSQI-J cutoff score of ≥ 6. VBM did not reveal any correlation between PSQI-J scores and gray matter volume. However, DTI revealed that PSQI-J global scores were significantly and negatively correlated with diffuse white matter fractional anisotropy (FA) values (p < 0.05, corrected). Moreover, the PSQI-J sleep disturbance and use of sleep medication component scores were significantly and negatively correlated with right anterior thalamic radiation and diffuse white matter FA values, respectively (p < 0.05, corrected). There were no significant differences in gray matter volume and white matter metrics (FA, axial, radial, and mean diffusivities) between the groups with PSQI-J scores above or below the cutoff. Our findings suggest that lower sleep quality, especially the use of sleep medication, is associated with impaired white matter integrity in healthy adults. Limitations of this study are relatively small number of participants and cross-sectional design. Fine sleep quality, possibly preventing the use of sleep medication, may contribute to preserve white matter integrity in the brain of healthy adults.

Supplementary Information

The online version contains supplementary material available at 10.1007/s41105-022-00442-0.

Consequences of Sleep Deprivation in Adult Diabetes Mellitus Type 2 Patients: An Integrative Review

BACKGROUND: Sleep deprivation in individuals with diabetes mellitus type 2 is more prevalent than in ordinary people. At present, the adverse effects of diabetes type 2 people with sleep disorders and sleep deprivation on blood sugar control are irrefutable. Thorough assessments covering the whole structure should be of concern in health-care treatment. It is precipitated and delivered to the physical, mental health, and social environment, but no systematic review or minimal data were published. Furthermore, it may significantly affect the system more than existing research. AIM: An integrative review aims to clarify the results or consequences of sleep disturbance/deprivation or insomnia symptoms among diabetes mellitus type 2 patients. METHODS: The writers implemented a literature search in PubMed, CINAHL, and Medline using the terms DM type 2, insomnia, adult, effect, DM, sleep disturbance, sleep disorder, and a consequence between 2012 and 2022. Inclusion criteria selected through considering the entire article, and providing an abstract, were 20 articles. RESULTS: Integrative data extraction and information were analyzed thematically. Identified were nine ideas: Association with blood sugar control, blood pressure control, risk of CVD, diabetes self-care behavior, weight gained and Obstructive Sleep Apnea (OSA), lifestyle and physical activity, mood/depression and anxiety symptoms, daily calories distribution, cholesterol/triglyceride, and liver enzyme levels. CONCLUSION: The adverse effects of sleep deprivation in type 2 diabetes significantly affect all pathophysiologically, mentally, and lifestyle modifications, including diabetes self-care. Therefore, to highlight the importance of promoting optimum sleep in diabetes type2 patients, a health-care system is inevitably as necessary as diet and exercise management.

Association between daily sleep duration and the risk of incident dementia according to the presence or absence of diseases among older Japanese individuals in the New Integrated Suburban Seniority Investigation (NISSIN) project

OBJECTIVE

This study aimed to investigate the association between daily sleep duration and incident dementia among physically and socially independent older people with/without diseases (hypertension, diabetes mellitus, cardiovascular diseases) in a Japanese age-specific cohort.

METHODS

We carried out a prospective cohort study including 1954 (1006 men and 948 women) Japanese individuals aged 64/65 years. Information on daily sleep duration, medical status, demographics, and lifestyle characteristics was collected by a baseline questionnaire survey and health checkup (2000-2005). Dates of incident dementia were confirmed using the nationally standardized dementia scale proposed by the Ministry of Health, Labor, and Welfare. A competing risk model was used to calculate the hazard ratios (HRs) and 95% confidence intervals (CIs) for incident dementia. We treated censored cases due to death as competing events.

RESULTS

During a median of 15.6 years of follow-up, 260 participants reported incident dementia. Compared with participants without diseases and who slept 6-7.9 h/day, those with a shorter daily sleep duration of <6 h/day, presence of disease and shorter, moderate, or longer daily sleep duration ≥8 h/day had an increased risk of incident dementia (HR 1.73; 95% CI 1.04-2.88, HR 1.98; 95% CI 1.14-3.44, HR 1.44; 95% CI 1.03-2.00, and HR 2.09; 95% CI 1.41-3.09, respectively) with a significant interaction between the presence of diseases and sleep duration (p < 0.001).

CONCLUSIONS

The present findings suggest that habitual sleep duration predicts future risk of dementia.

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.

Sleep quality in people with type 2 diabetes controlled at the primary level and its association with sociodemographic and clinical characteristics

Type 2 diabetes (DM2) is one of the diseases that cause the highest premature mortality and disability worldwide. Sleep disturbances have been associated with the onset of metabolic disorders and increased levels of glycated haemoglobin in diabetics.

OBJECTIVE

To evaluate the quality of sleep of people with type 2 diabetes and its association with sociodemographic, clinical, and metabolic characteristics.

METHODS

Observational, cross-sectional, analytical study of 223 patients with DM2 between 20 and 64 years old, controlled in a primary health care centre in Chile.

RESULTS

Most were women (66.4%), average age 54.7 years. Only 33% slept the required number of hours (7-9 h) to maintain health. Fifty-seven point seven percent were metabolically unbalanced (Hb1Ac > 7%). Seventy-five point two percent presented sleep problems of varying severity, which were associated with being a woman, night pain, nocturia, time of diagnosis of diabetes, and depressive symptoms. Persons with poor sleep quality were 73% more likely to be metabolically decompensated, however, this result was not statistically significant: OR = 1.73 (CI: 78-3.87).

CONCLUSIONS

The high frequency of poor sleep quality and metabolic decompensation in the sample stands out, which could complicate DM2. The association between poor sleep quality and DM2 decompensation is inconclusive. Future research will contribute to elucidating the role of sleep in metabolic compensation and in the prevention of metabolic disorders.

Association of sleep disturbance with diabetic retinopathy

PURPOSE

Diabetes mellitus (DM) patients are more likely to experience sleep disturbances than normal. Sleep disturbances may contribute to the development of diabetic retinopathy (DR) by higher inflammatory markers in circulation. We investigated the association between sleep quality and DR.

METHODS

Institutional case control study with type 2 DM patients of <10 years duration and HbA1c ⩽8%; 70 cases with DR and 70 controls without DR (NODR) (power 0.8). Sleep quality was assessed by Pittsburg sleep quality index (PSQI) questionnaire and compared.

RESULTS

Cronbach's alpha was 0.777 with high internal homogeneity. Global PSQI score in DR (7.44 ± 3.99; 95%CI 6.88, 9.42) was more than in NODR (4.30 ± 3.26; 95%CI 3.87, 6.45) (p < 0.001). All sleep disturbance scores were more in DR except sleep duration. Poor sleep (PSQI score>5) was more prevalent in DR (p = 0.000) and associated with increasing DR severity (p = 0.026). Normal sleep latency was recorded in 78.57% and 42.85% patients in NODR and DR respectively (p < 0.001). Severe difficulty in subjective sleep quality (p = 0.024), sleep latency (p = 0.002) and daytime dysfunction (p < 0.001) was seen more in DR. Elevated daytime dysfunction was observed with increasing DR severity (p = 0.008). The optimal cut-off for global PSQI score and sleep latency for DR was 5.5 (OR: 5.97; 95%CI 2.86, 12.47) and 25 min(OR: 4.89; 95%CI 2.32, 10.26) respectively.

CONCLUSION

Sleep disturbance is positively associated with DR. Our study identifies cut off value for DR of a modifiable parameter like sleep latency. It emphasizes the need of sleep quality assessment for risk assessment of DR.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

Slow-wave sleep and obstructive sleep apnea in patients with type 2 diabetes mellitus

PURPOSE

This study aimed to analyze sleep architecture and obstructive sleep apnea (OSA) in patients with type 2 diabetes and clarify the association between sleep characteristics and glycemic control.

METHODS

All participants underwent metabolism-related laboratory testing and a cross-sectional analysis of nocturnal polysomnography for sleep parameter analysis. Data were analyzed using the chi-squared test, a one-way analysis of variance, and Kruskal-Wallis test to compare the differences among three groups (type 2 diabetes, prediabetes, and control groups). The prevalence of OSA was evaluated using descriptive statistics and comparing the group divided into HbA1c quartiles. Univariate and multivariate linear regression analyses were used to determine factors associated with glycemic control.

RESULTS

Of 75 study participants (age 57.3 ± 4.1 years, 32 men), there were 25 participants each in the type 2 diabetes, prediabetes, and control groups. Participants with type 2 diabetes had significantly decreased slow-wave sleep duration (77.9 ± 30.0 min, p = 0.026) and shortened rapid eye movement sleep latency (median 75 min, p = 0.018) compared with those in the prediabetes and control groups. Forty-five participants (60%) had OSA (apnea-hypopnea index ≥ 5/h), 18 of whom were in the type 2 diabetes group. The prevalence of OSA in this group was 72%. The prevalence of moderate-to-severe OSA was significantly higher in the type 2 diabetes group than in the control group (p = 0.025) and in groups with HbA1c levels of > 6.7% than in groups with HbA1c levels of < 5.3% (p = 0.007). Multiple regression analysis showed that dyslipidemia (β = 0.179, p = 0.000) and slow-wave sleep duration (β =  - 0.113, p = 0.008) were independently associated with the HbA1c level.

CONCLUSION

Our results suggest that increasing slow-wave sleep is positively associated with glycemic control.

Is There an Association between Sleep Disorders and Diabetic Foot? A Scoping Review

Diabetic foot is associated with a low quality of life since physical disabilities, mood disturbances and psychological disorders are frequent. One of the most important biological processes to ensure quality of life is sleep. Sleep disorders can impair glycemic control in patients with diabetes mellitus or even cause long-term type 2 diabetes mellitus. The aim of this study is to carry out a scoping review about the association between sleep cycle disorders and diabetic foot. PubMed, Scopus, CINAHL, PEDro, Cochrane Library, SCIELO and EMBASE databases were chosen for the search and the following terms were used: "diabetic foot","sleep*","rest-activity","mood" and"behavior". All the studies should include outcome variables about sleep and diabetic foot. Finally, 12 articles were selected, all of whichwere observational. The most frequent variables were those regarding diabetic foot ulcer aspects and diabetic neuropathy on one side, and obstructive sleep apnea, sleep duration and sleep quality on the other side. The results suggest that there is a possible association between obstructive sleep apnea and the presence or history of diabetic foot ulcers. No direct associations between sleep quality or sleep duration and diabetic foot or diabetic foot ulcer variables have been found.

Association between Sleep Quality and Painless Diabetic Peripheral Neuropathy Assessed by Current Perception Threshold in Type 2 Diabetes Mellitus

BACKGROUND

It is known that the painful sensation of diabetic peripheral neuropathy (DPN) results in sleep problems in type 2 diabetes mellitus (T2DM). However, it is not known that the painless DPN also is associated with poor sleep quality in T2DM. The purpose of the current study was to investigate the association between painless DPN and poor sleep quality in T2DM.

METHODS

A total of 146 patients of T2DM who do not have any painful symptoms of DPN were recruited into the study. Among the patients, painless DPN was diagnosed by using the current perception threshold test. Sleep quality was assessed using the Pittsburgh Sleep Quality Index questionnaire.

RESULTS

The percentage of painless DPN was significantly higher in the poor sleep quality group than the good sleep quality group (70.0% vs. 35.5%, P<0.001). In the subscale results, stimulus values at 2,000 Hz, hypoesthesia and hyperesthesia were more common in the poor sleep quality group than in the good sleep quality group (45.7% vs. 25.0%, P=0.009; 34.3% vs. 18.4%, P=0.029; 40.0% vs. 19.7%, P=0.007, respectively). The association of painless DPN and poor sleep quality remained significant after adjustment for significant covariates (odds ratio, 3.825; 95% confidence interval, 1.674 to 8.742; P<0.001).

CONCLUSION

The current study showed that painless DPN was associated with poor sleep quality. Future studies are required to clarify the pathophysiologic causal relationship between painless DPN and sleep quality.

The Evolutionarily Mismatched Impact of Urbanization on Insomnia Symptoms: a Short Review of the Recent Literature

PURPOSE OF REVIEW

For the most part of human existence, individuals have been living a rural lifestyle in a rural setting. However, such sleep-conducive conditions have largely been transformed dramatically by urbanization within a relatively short span of time in recent history, and the resulting evolved mechanisms-environment mismatch is theorized to bring about an increased risk for insomnia symptoms. This brief review of the recent literature is designed to evaluate the veracity of this proposition.

RECENT FINDINGS

The majority of recent findings have suggested that most proposed evolutionarily mismatched urban factors are indeed related to the presence of insomnia symptoms. However, there is a general paucity of longitudinal evidence (and for some other factors, a lack of enough evidence of any kind). Although there is a preponderance of recent findings indicating a link between evolutionarily mismatched urban phenomena and insomnia symptoms, more longitudinal data are needed before any causative conclusion can be drawn.

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 Quality and Associated Factors Among Diabetes Mellitus Patients in a Follow-Up Clinic at the University of Gondar Comprehensive Specialized Hospital in Gondar, Northwest Ethiopia: A Cross-Sectional Study

INTRODUCTION

Diabetic mellitus has a negative impact on the quality of sleep. It is one of the leading public health conditions which can result in poor sleep quality. Poor sleep quality is an unreported and unrecognized problem which can affect the prognosis of diabetes patients.

OBJECTIVE

The aim of this study is to assess the prevalence of poor sleep quality and its associated factors among patients with diabetes mellitus attending follow-up clinics at the University of Gondar Comprehensive Specialized Hospital, Northwest Ethiopia, 2019.

METHODS

An institution-based cross-sectional study was conducted among 430 diabetes mellitus patients at the University of Gondar Comprehensive Specialized Hospital from February 1, 2020 to March 28, 2020. A systematic random sampling method was used to reach the study subjects. An interviewer-administered questionnaire was used for data collection. Pittsburgh sleep quality index was used for assessing sleep quality. To explain study variables, frequency tables and percentages were used. A binary logistic regression was conducted to see the relation between dependent and independent variables.

RESULTS

A total of 430 diabetes mellitus patients participated in the study with a response rate of 100%. The overall prevalence of poor sleep quality was 47.2%. Drinking alcohol (AOR = 2.45, 95% CI: 1.28-4.69), smokers (AOR = 6.26, 95% CI: 2.04-19.21), comorbidity (AOR = 1.80, 95% CI: 1.10-2.96), BMI ≥ 30 (AOR = 4.87, 95% CI: 1.07-22.09), having type 2 diabetes mellitus (AOR = 2.16, 95% CI: 1.04-4.50), poor glycemic control (AOR = 2.61, 95% CI: 1.81-4.81) and having depression (AOR = 9.95, 95% CI: 4.85-20.38) were associated with poor sleep quality.

CONCLUSION

In this study, nearly half of the patients had poor sleep quality. Drinking alcohol, smoking, comorbidities, higher BMI, type 2 diabetes mellitus, poor glycemic control and having depression were factors in poor sleep quality. Creating awareness of the need for weight reduction, minimizing alcohol intake, cessation of smoking, and improving sleep hygiene for DM patients would be effective management for improving poor sleep quality.

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).

Sleeping disturbances and predictor risk factors among type 2 diabetic mellitus patients

Background

Sleep disturbance is a major health issue among people with type 2 diabetes mellitus (T2DM). The Pittsburgh Sleep Quality Index (PSQI) has been the most widely used instrument to measure subjective sleep disturbance.

Aim

The aim of this study was to determine the impact of sleeping factor structure of the PSQI as potential predictor for glycosylated hemoglobin A1c (HbA1C) among people living with T2DM in the Turkish community to facilitate its use in the clinical practice and research.

Subjects and Methods

This is a cross-sectional study and participants were between the age group of 25 and 65 years old who visited the diabetes and endocrinology department of Mega Medipol University Teaching Hospital, Istanbul. The PSQI was conducted on 871 patients with T2DM. Good sleep quality was defined as PSQI score <5. Multivariate logistic regression analysis was used to estimate the associated risk factors for the T2DM.

Results

The current study showed significant differences between male and female patients with respect to their age in years, body mass index (BMI) (kg/m2), physical activity, smoking habit, sheesha smoking, income, family history of metabolic syndrome, coronary heart disease (CHD), and PSQI. The results revealed significant differences between HbA1c ≤7 and females and HbA1c >7 T2DM patients with respect to gender, BMI (kg/m2), CHD, and PSQI. The study demonstrated significant differences between sleeping categories PSQI as good, average, and poor sleeping among T2DM patients with respect to age and gender. Meanwhile, significant differences were reported between sleeping categories among T2DM patients with respect to their: number of sleeping hours, wake-up time, sleeping time, HbA1c, fasting blood glucose, uric acid, and systolic and diastolic blood pressure. This study showed very strong statistically significant correlations between low HbA1c and poor sleep quality in patients with T2DM patients, including subjective sleep quality r = 0.763, sleep latency r = 0.327, sleep duration r = 0.472, habitual sleep efficiency r = 0.575, sleep disturbances r = 0.564, use of sleep medication r = 0.728, and daytime dysfunction r = 0.734. Multivariate stepwise logistic regression analysis revealed that Vitamin D (mmol/L) (P < 0.001), HbA1c (P < 0.001), duration of DM (P < 0.001), uric acid (mmol/L) (P < 0.001), systolic blood pressure mmHg (P = 0.006), diastolic blood pressure mmHg (P = 0.015), and BMI (P = 0.024) were considered at higher risk as the predictors for sleeping quality among T2DM patients.

Conclusion

The results suggest a strong positive correlation between PSQI with HbA1c levels, systolic and diastolic blood pressure, age, BMI, among type 2 diabetic patients. This study ascertains that poor sleep quality may be due to elevated level of HbA1c, metabolic syndrome, diabetes, obesity, and/or hypertension.

Health-related quality of life and sleep quality among North Indian type 2 diabetes mellitus patients: evidence from a cross-sectional study

OBJECTIVE

The objective of this study is to measure the relationship between sleep quality and health-related quality of life (HRQOL), in Indian population with type 2 diabetes mellitus (T2DM).

METHODS

A cross-sectional study, included a total of 300 patients with T2DM. All participants were responding to the Pittsburgh Sleep Quality Index (PSQI) and European Quality of Life-5 Dimensions Questionnaire (EQ-5D). A PSQI global score ≥5 was defined as poor sleep quality. EQ-5D visual analogue scale (VAS), determining the overall health status. Logistic regression analysis was used to examine the association between PSQI and EQ-5D. All the study data were analysed using the SPSS software version 20.0. Values of p < 0.05 were considered statistically significant.

RESULTS

The mean age of included participants were 55.29. Majority of the participants (55.3%) were identified as "poor sleepers" and female (31.3%) contributing higher proportion. Poor sleepers had significantly lower the HRQoL (p < 0.001). After adjustment, poor sleep quality was significantly associated with a lower HRQoL; EQ-5D index (OR = 1.080, 95%, CI: 1.015-1.148, p < 0.05), and EQ-5D VAS (OR = 1.092, 95%, CI: 1.021-1.176, p < 0.01). Overall, the EQ-5D index and EQ-5D VAS were found to be an independent predictors of sleep quality.

CONCLUSIONS

Poor sleep quality is prevalent in Indian T2DM population, and it imparts negative impact on several dimensions of EQ-5D that characterising the daily activities performance. Therefore, further real-world studies are needed to determine the causal relationship between T2DM patients and measure of objective sleep and their impact on health.

Depressive symptoms mediate the relationship between sleep disturbances and type 2 diabetes mellitus

BACKGROUND

The current study aimed at examining whether individuals diagnosed with type 2 diabetes mellitus (T2DM) have more severe sleep disturbances compared to individuals who are healthy or have prediabetes and whether depressive symptoms mediate the relationship between sleep disturbances and having T2DM.

METHODS

T2DM patients (n = 107) were compared to individuals with prediabetes (n = 48) and healthy individuals (n = 154) regarding the severity of depressive symptoms, measured via the Beck Depression Inventory-II (BDI-II), and sleep disturbances, measured via the Mini Sleep Questionnaire (MSQ). Mediation analysis examined whether depressive symptoms mediated the relationship between sleep disturbances and T2DM.

RESULTS

Compared to healthy individuals and individuals with prediabetes, T2DM patients had more depressive symptoms and higher levels of insomnia, hypersomnia, and overall more sleep disturbances. The prediabetes group did not differ from the healthy control group on these measures, and these groups were thus combined for further analysis. Sleep disturbances were correlated with severity of depressive symptoms (r =0.43). After controlling for age, gender, and ethnic background, both severity of sleep disturbances (odds ratio [OR]: 1.04; 95% CI: 1.01-1.07, P <.001) and severity of depressive symptoms (OR: 8.54, 95% CI: 3.37-21.69, P <.001) predicted T2DM. Depression symptoms mediated the relationship between sleep disturbances and T2DM, whereas the direct relationship between sleep disturbances and T2DM was nonsignificant.

CONCLUSIONS

The findings imply that sleep disturbances may contribute to the development and progression of T2DM by promoting depressive symptoms. Thus, treatments for the emotional distress associated with sleep disturbances may help reduce the risk for T2DM and the progression of the disease.

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.

Risk and protective factors of co-morbid depression in patients with type 2 diabetes mellitus: a meta analysis

The aim from this paper is to identify the main influencing factors of co-morbid depression among T2DM (Type 2 Diabetes Mellitus) patients and to provide reliable evidence for relative researches. A systematic review and meta-analysis of risk factors for co-morbid depression in T2DM was performed on all retrieved studies through an observational research of network database. Data were analyzed by Review Manager 5.3 from the extracted results, the heterogeneity index of the studies was determined using Chi-squared I² tests and on the basis of heterogeneity, a fixed or random effect model was used to estimates the pooled effect of each influencing factor. Fourteen observational studies containing total of 82,239,298 cases that have been identified. Diabetic complications (OR = 2.91; 95%CI, 1.76-4.82, p < 0.0001), insulin use (OR = 1.71; 95%CI, 1.18-2.48, p = 0.005), education status (OR = 1.91; 95%CI, 1.30-2.81, p = 0.001) were confirmed as risk factors, while regular exercising (OR = 0.51; 95%CI, 0.27-0.96, p = 0.04), gender (OR = 0.56; 95%CI, 0.47-0.65, p < 0.0001), marital status (OR = 0.53; 95%CI, 0.34-0.83, p = 0.005), current social status (OR = 0.64; 95%CI, 0.47-0.88, p = 0.006) were confirmed as protective factors of co-morbid depression in the patients with T2DM. Subgroup analysis claimed age (≥60 years) was a risk factor and smoking was protective factor for co-morbid depression in the patients with T2DM. Being female, have diabetic complications, insulin use, education level less than secondary are risk factors. However, doing regular exercise, being married and on work are protective factors of co-morbid depression in patients with T2DM. As to the other influencing factors should be further studied.

Geriatric syndromes and quality of life in older adults with diabetes

AIM

To describe geriatric syndromes and their relationships with quality of life in older adults with diabetes.

METHODS

Community-dwelling older adults (aged >60 years) with diabetes (n = 316) participated in the present study. Eight geriatric syndromes, including polypharmacy (number of medications), pain (Brief Pain Inventory), urinary incontinence (International Consultation on Incontinence Questionnaire), sleep disturbance (hours of sleep), lower cognitive level (Mini-Mental State Examination), falls, depressive symptoms (Geriatric Depression Scale short form) and functional limitation (Barthel Index and Instrumental Activity of Daily Living), were assessed. The WHOQOL-BREF Taiwan version was used to measure physical, psychological, social and environmental domains of quality of life.

RESULTS

Polypharmacy was the most common geriatric syndrome (46.6%), followed by pain (41.5%). Participants with any of the geriatric syndromes, except for polypharmacy and sleep disturbance, had significantly poorer quality of life than those without. The Geriatric Depression Scale score was the only common and significant contributor to all four domains of quality of life, explaining 16~29% of the variance. Number of medications, pain level and cognitive level were also significant contributors, although they explained a small amount (<5%) of the variance. The number of geriatric syndromes (mode = 2) was significantly correlated with all four domains of quality of life (partial correlation r = -0.278~0.460, all P < 0.001).

CONCLUSIONS

Geriatric syndromes, especially polypharmacy and pain, were common among older adults with diabetes. A greater number of geriatric syndromes or a higher Geriatric Depression Scale score were associated with poorer quality of life. Further studies focusing on combinations of different geriatric syndromes or comorbidities are required. Geriatr Gerontol Int 2019; 19: 518-524.

Gender differences in the associations between insomnia and glycemic control in patients with type 2 diabetes: a cross-sectional study

STUDY OBJECTIVES

Insomnia is associated with insulin resistance and type 2 diabetes (T2D) in the general population. However, the associations between insomnia and glycemic control in T2D population are not consistently reported. In this study, we aimed to examine the associations between insomnia and glycemic control, and gender differences in these associations among Hong Kong Chinese patients with T2D.

METHODS

This was a cross-sectional study involving T2D patients recruited from the Hong Kong Diabetes Registry between July 2010 and June 2015. Glycemic control was estimated by fasting plasma glucose (FPG) and glycated hemoglobin (HbA1c). Participants with the Insomnia Severity Index score > 14 were considered as having insomnia.

RESULTS

A total of 3753 patients were recruited. Compared with patients without insomnia, patients with insomnia had higher levels of FPG and HbA1c. After adjustment for potential confounding factors, insomnia was associated with higher FPG and HbA1c in the entire cohort. There were significant interactions between insomnia and gender for FPG (p = 0.001) and HbA1c (p = 0.025) in the full model. Subgroup analyses found that men with insomnia had higher FPG [8.23 (7.85-8.61) mmol/L versus 7.50 (7.39-7.61) mmol/L, p < 0.001] and HbA1c [7.79 (7.57-8.02)% versus 7.45 (7.39-7.52)%, p = 0.005] than men without insomnia after adjusted for confounding factors, whereas such difference was not observed in women.

CONCLUSIONS

T2D patients with insomnia had worse glycemic control than the patients without insomnia. The associations were particularly pronounced in men.

Association between insomnia and personality traits among Japanese patients with type 2 diabetes mellitus

AIMS/INTRODUCTION

Insomnia is associated with type 2 diabetes mellitus, and results in a low quality of life. There are several known relationships between insomnia and personality. Thus, we clarified the association between some personality traits and insomnia among Japanese type 2 diabetes mellitus patients.

MATERIALS AND METHODS

The participants were 504 type 2 diabetes mellitus patients (mean age 63.9 ± 12.5 years). Sleep disturbance and personality traits were evaluated using the Pittsburgh Sleep Quality Index-Japanese version and the Ten-Item Personality Inventory Japanese version, respectively. Lifestyle factors, glycated hemoglobin levels and depressive status of the patients were also included in the analyses.

RESULTS

Among the 504 participants with type 2 diabetes mellitus, 154 (30.6%) showed probable insomnia. After adjustment for confounders, being female, living alone, high body mass index and "high neuroticism" were found to be significantly correlated with current insomnia. No other relationships between insomnia and glycated hemoglobin or lifestyle factors, such as smoking, drinking alcohol or exercise frequency, were found.

CONCLUSIONS

The prevalence of insomnia in individuals with type 2 diabetes mellitus was high, and the risk factors included some personality factors. Future prospective studies are required to confirm the therapeutic effects of behavioral interventions for insomnia in patients with type 2 diabetes mellitus.

Association between sarcopenia and sleep disorder in older patients with diabetes

AIM

In the present study, we aimed to examine the association between sarcopenia and sleep disorder in older patients with diabetes using the Japanese version of SARC-F (SARC-F-J).

METHODS

Outpatients with diabetes (aged ≥65 years) at the Ise Red Cross Hospital were included in the present study. We used the Japanese version of the Pittsburgh Sleep Quality Index, which is a self-administered questionnaire, to measure sleep disorder. To evaluate sarcopenia, we used SARC-F-J, a self-administered questionnaire, comprising five items. For multiple logistic regression analysis, the dependent variable was sleep disorder and the explanatory variable was sarcopenia, and these were used for calculating the odds ratios of sarcopenia with regard to sleep disorder.

RESULTS

In total, 318 patients were included in this study (189 men and 129 women). The prevalence of sarcopenia was 22.5% and that of sleep disorder was 44.8%. Adjusted odds ratios of sarcopenia and sleep disorder were 6.04 in men (95% CI 1.71-21.36, P = 0.005) and 6.33 in women (95% CI 1.91-20.97, P = 0.003).

CONCLUSIONS

We found a statistically significant association between sarcopenia and sleep disorder in older patients with diabetes using SARC-F-J. Therefore, older patients with diabetes should be cautioned regarding sleep disorder if they are diagnosed with sarcopenia. Geriatr Gerontol Int 2019; 19: 399-403.

Association between insomnia and type 2 diabetes mellitus in Han Chinese individuals in Shandong Province, China

PURPOSE

Diabetes and sleep disorders are public health threats worldwide, but the potential association between them is still unclear.

METHODS

We conducted a community-based cross-sectional study including 5078 participants (2665, 52.5% male) to determine the association between insomnia and diabetes mellitus prevalence.

RESULTS

In patients with type 2 diabetes mellitus (T2DM) and nondiabetic controls, the prevalence of insomnia was 20.2% (68/377) and 12.2% (578/4741), respectively. The results showed that insomnia was associated with T2DM after adjusting for age, sex, BMI, smoking, alcohol consumption, presence of disease history (hypertension, dyslipidemia, stroke, cardiovascular diseases, cancers), and depression (odds ratio [OR] = 1.31, 95% confidence interval [CI] 1.03-1.66). After stratifying by age and sex, insomnia was significantly associated with diabetes mellitus only in the subgroup of middle-aged participants (40-59 years) (OR = 1.61, 95% CI 1.16-2.23) and males (OR = 1.48, 95% CI 1.08-2.03) after controlling for the above covariates.

CONCLUSIONS

This study suggests that insomnia is independently and significantly associated with diabetes mellitus in the northern Chinese population, especially in the 40-59-year-old age group and in males.

Prevalence and risk factors of type 2 diabetes in insomnia sufferers: a study on 1311 individuals referred for sleep examinations

BACKGROUND

Several studies have investigated the particular relationship between insomnia and type 2 diabetes. However, few studies have investigated the prevalence and risk factors for type 2 diabetes in insomnia sufferers. The aim of this study was to examine the prevalence and risk factors of type 2 diabetes in a large sample of insomnia sufferers.

METHODS

Data from 1311 insomnia sufferers recruited from the research database of the Erasme Hospital sleep laboratory were analyzed. Only individuals with a diagnosis of type 2 diabetes according to the diagnostic criteria of the American Diabetes Association at admission were included in the diabetes group. Logistic regression analyses were conducted to examine clinical and demographic risk factors of type 2 diabetes in insomnia sufferers.

RESULTS

The prevalence of type 2 diabetes in insomnia sufferers is 21.13%. Multivariate logistic regression analysis revealed that significant risk factors of type 2 diabetes in insomnia sufferers were as follows: being male, Z-drugs use, high blood pressure, hypertriglyceridemia, alcohol consumption of ≥4 units/day, BMI ≥25 & <30 kg/m², BMI ≥30 kg/m², age ≥50 years, C-reactive protein ≥4.5 mg/L, a sleep duration of <6.5 h, apnea-hypopnea index ≥15/hour, periodic limb movements index ≥26/hour, and severe complaints of early morning awakening.

CONCLUSION

Type 2 diabetes is a common pathology in insomnia sufferers. In this subpopulation, most of the risk factors for type 2 diabetes are reversible, which justifies better prevention and management of this pathology in order to avoid its negative consequences.

Association of usual sleep quality and glycemic control in type 2 diabetes in Japanese: A cross sectional study. Sleep and Food Registry in Kanagawa (SOREKA)

Objectives

Excessively short and long sleep durations are associated with type 2 diabetes, but there is limited information about the association between sleep quality and diabetes. Accordingly, the present study was performed to investigate this relationship.

Materials and methods

The subjects were 3249 patients with type 2 diabetes aged 20 years or older. Sleep quality was assessed by using the Pittsburgh Sleep Quality Index (PSQI). A higher global PSQI score indicates worse sleep quality, and a global PSQI score >5 differentiates poor sleepers from good sleepers.

Results

The mean global PSQI score was 5.94 ± 3.33, and 47.6% of the patients had a score of 6 or higher. Regarding the components of the PSQI, the score was highest for sleep duration, followed by subjective sleep quality and then sleep latency in decreasing order. When the patients were assigned to HbA1c quartiles (≤ 6.5%, 6.6–7.0%, 7.1–7.8%, and ≥ 7.9%), the top quartile had a significantly higher global PSQI score than the other quartiles. The top HbA1c quartile had a sleep duration of only 6.23 ± 1.42 hours, which was significantly shorter than in the other quartiles. Also, sleep latency was 25.3 ± 31.8 minutes in the top quartile, which was significantly longer (by approximately 20 minutes) than in the other quartiles. When analysis was performed with adjustment for age, gender, BMI, smoking, and other confounders, the global PSQI score was still significantly higher and sleep duration was shorter in the top HbA1c quartile (HbA1c ≥ 7.9%).

Conclusions

Japanese patients with type 2 diabetes were found to have poor subjective sleep quality independently of potential confounders, especially those with inadequate glycemic control. Impairment of sleep quality was associated with both increased sleep latency and a shorter duration of sleep.