Association of sleep disturbance with risk of cardiovascular disease and all-cause mortality in patients with new-onset type 2 diabetes: data from the Korean NHIS-HEALS

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 experiences of parents of children 18 years or younger with sickle cell disease during the COVID-19 pandemic: a qualitative study

STUDY OBJECTIVES

The coronavirus disease pandemic has highlighted disparities in health care. Parents assist in sickle cell disease management in children. Understanding sleep in parents of children who are diagnosed with sickle cell disease is an important facet of disease management. Our objectives were to identify sleep characteristics of parents of children with sickle cell disease age 18 years or younger during the coronavirus disease pandemic, to investigate measures used by parents to achieve restful sleep, and to discuss how sleep may be improved in parents of children diagnosed with sickle cell disease.

METHODS

This study conducted 14 face-to-face semistructured interviews with parents of children diagnosed with sickle cell disease. A majority of the interviews (93%) were conducted at a hematology clinic. Qualitative thematic analysis was used to analyze data.

RESULTS

All parents reported that their child experienced pain because of sickle cell disease. Most parents (86.7%) reported that their child was diagnosed with sickle cell anemia. Four themes were identified: difficulty obtaining restful sleep during their child's sickle cell crisis, sleep during the coronavirus disease pandemic, factors affecting sleep, and effects of sleep disturbance and deprivation on parental performance.

CONCLUSIONS

This research has highlighted some of the difficulties experienced by parents of children who are diagnosed with sickle cell disease and allows for additional insight into the sleep experiences of parents as they attempt to manage their child's disease.

CITATION

Osborne JC, Odlum M, Sedrak A. Sleep experiences of parents of children 18 years or younger with sickle cell disease during the COVID-19 pandemic: a qualitative study. J Clin Sleep Med. 2024;20(5):777-782.

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

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

The impact of sleep disturbances on suicide risk among people living HIV: An eleven-year national cohort

OBJECTIVES

The suicide rate among individuals who experience sleep disturbances is five times higher than in the general population. Up to 70 % of people living with HIV (PLHIV) experience sleep disturbances. This study's purpose was to determine whether this population has higher rates of suicide compared to those without sleep disorders. Possible risk factors were also explored.

METHODS

A secondary analysis of nationwide data on all males and females over 15 years old with HIV living in Taiwan was conducted from January 1, 2005, to December 31, 2016. Sleep disturbances were identified through recorded diagnoses and medical treatments. Cox proportional hazard models and hazard ratios (HRs) and mediation analysis were employed to estimate the association between sleep disturbances and suicide risk during the follow-up period.

RESULTS

Of the 5680 PLHIV, 72 suicide events were reported. The suicide incidence rate among PLHIV suffering from sleep disturbances was 769 per 100,000 person-years. Sleep disturbances were associated with a significantly increased risk of suicide (AHR = 1.75, 95 % CI 1.02-3.02, p = 0.0429). A premium-based monthly salary of <24,000 (NT $) was also associated with an increased hazard of suicide (AHR = 4.14, 95 % CI 1.60-10.75, p = 0.0035). The pathway effect analysis using potential outcomes showed that depression did not mediate the effect of sleep disturbance on suicide.

CONCLUSIONS

Sleep disturbances were associated with higher suicide rates, even after adjusting for pre-existing depression. These findings suggest that paying attention to suicidal ideation among PLHIV suffering from sleep disturbances is necessary.

Interplay of sleep patterns and oxidative balance score on total cardiovascular disease risk: Insights from the National Health and Nutrition Examination Survey 2005-2018

Background

Unhealthy lifestyle and diet may contribute to the development of cardiovascular disease (CVD), but limited evidence exists regarding the association between sleep patterns, oxidative stress-related exposures to diet and lifestyle, and CVD risk.

Methods

We analysed data from 10 212 adults in the National Health and Nutrition Examination Survey (NHANES) database (2005-2018). Self-report questionnaires were used to collect data on sleep duration, sleepiness, and trouble sleeping, classified into three categories: healthy, intermediate, and poor sleep patterns. Healthy sleep was defined as sleeping seven to nine hours per night with no self-reported sleepiness or trouble sleeping, while intermediate and poor sleep patterns indicated one and two to three sleep problems, respectively. The oxidative balance score (OBS) was calculated based on twenty oxidative stress-related exposures to dietary and lifestyle factors, with a higher score indicating greater antioxidant exposure. Survey-based multivariable-adjusted regression analysis was conducted to examine the association of sleep patterns or OBS alone and combined with the total and specific CVD risk.

Results

Participants with poor sleep patterns had a higher likelihood of developing CVD (odds ratio (OR) = 1.76; 95% confidence interval (CI) = 1.26-2.45, P < 0.05), while an inverse association was found between OBS and CVD risk (quartile (Q) 4 vs Q1: OR = 0.67; 95% CI = 0.47-0.94, P = 0.02, P for trend <0.05). There was an interaction between sleep patterns and OBS (P for interaction = 0.03). Participants with unhealthy (intermediate and poor) sleep patterns and pro-oxidant OBS (Q1 and Q2) were significantly associated with increased risk of total CVD (OR = 2.31; 95% CI = 1.42-3.74, P < 0.05), as well as angina and congestive heart failure, but not coronary heart disease (CHD). Stratified analysis showed that among individuals without hyperlipidaemia, participants with both unhealthy sleep patterns and pro-oxidant OBS exhibited a higher risk of CHD compared to those with healthy sleep patterns and antioxidative OBS.

Conclusions

Unhealthy sleep patterns and reduced oxidative balance are positively associated with an increased risk of overall and specific CVD. Interventions that target healthy sleep habits and antioxidant-rich diets and lifestyles may be important for reducing the risk of CVD.

The relationship between social isolation, social support, and loneliness with cardiovascular disease and shared risk factors: A narrative review

BACKGROUND

Cardiovascular disease (CVD) is the greatest contributor to global morbidity and mortality. Poor social health plays a critical role in CVD incidence. Additionally, the relationship between social health and CVD may be mediated through CVD risk factors. However, the underlying mechanisms between social health and CVD are poorly understood. Certain social health constructs (social isolation, low social support and loneliness) have complicated the characterisation of a causal relationship between social health and CVD.

AIM

To provide an overview of the relationship between social health and CVD (and its shared risk factors).

METHOD

In this narrative review, we examined published literature on the relationship between three social health constructs (social isolation, social support, and loneliness) and CVD. Evidence was synthesised in a narrative format, focusing on the potential ways in which social health affects CVD, including shared risk factors.

RESULTS

The current literature highlights an established relationship between social health and CVD with a likelihood for bi-directionality. However, there is speculation and varied evidence regarding how these relationships may be mediated through CVD risk factors.

CONCLUSIONS

Social health can be considered an established risk factor for CVD. However, the potential bi-directional pathways of social health with CVD risk factors are less established. Further research is needed to understand whether targeting certain constructs of social health may directly improve the management of CVD risk factors. Given the health and economic burdens of poor social health and CVD, improvements to addressing or preventing these interrelated health conditions would have societal benefits.

Comparison of Operational Definition of Type 2 Diabetes Mellitus Based on Data from Korean National Health Insurance Service and Korea National Health and Nutrition Examination Survey

BACKGROUND

We evaluated the validity and reliability of the operational definition of type 2 diabetes mellitus (T2DM) based on the Korean National Health Insurance Service (NHIS) database.

METHODS

Adult subjects (≥40 years old) included in the Korea National Health and Nutrition Examination Survey (KNHANES) from 2008 to 2017 were merged with those from the NHIS health check-up database, producing a cross-sectional dataset. We evaluated the sensitivity, specificity, accuracy, and agreement of the NHIS criteria for defining T2DM by comparing them with the KNHANES criteria as a standard reference.

RESULTS

In the study population (n=13,006), two algorithms were devised to determine from the NHIS dataset whether the diagnostic claim codes for T2DM were accompanied by prescription codes for anti-diabetic drugs (algorithm 1) or not (algorithm 2). Using these algorithms, the prevalence of T2DM was 14.9% (n=1,942; algorithm 1) and 20.8% (n=2,707; algorithm 2). Good reliability in defining T2DM was observed for both algorithms (Kappa index, 0.73 [algorithm 1], 0.63 [algorithm 2]). However, the accuracy (0.93 vs. 0.89) and specificity (0.96 vs. 0.90) tended to be higher for algorithm 1 than for algorithm 2. The validity (accuracy, ranging from 0.91 to 0.95) and reliability (Kappa index, ranging from 0.68 to 0.78) of defining T2DM by NHIS criteria were independent of age, sex, socioeconomic status, and accompanied hypertension or dyslipidemia.

CONCLUSION

The operational definition of T2DM based on population-based NHIS claims data, including diagnostic codes and prescription codes, could be a valid tool to identify individuals with T2DM in the Korean population.

A nationwide study on pain manifestations and sleep problems in community-dwelling older adults: findings from ELSI-Brazil

PURPOSE

Sleep problems are common and affect approximately 36-70% of older adults worldwide and can be associated with negative outcomes such as pain. There is believed to be a bidirectional relationship between sleep problems and pain, modulated by inflammation and stress. The objective was to investigate the association between self-reported sleep problems and pain manifestations.

METHODS

A cross-sectional study using data from the second wave of the Brazilian Longitudinal Study of Aging (2019-2021) was conducted. The exposure variables were self-reported sleep problems: poor sleep quality, insomnia (initial, intermediate, and final), and daytime sleepiness. The outcomes were self-reported pain manifestations: frequent pain, moderate/intense/strong pain, and pain-related disability. Logistic regressions were performed to verify the association between exposures and outcomes.

RESULTS

A total of 6875 community-dwelling older adults participated in this study (71.1 ± 8.3 years; 54.4% female). Older adults with self-reported poor sleep quality, initial, intermediate and final insomnia, and daytime sleepiness had, respectively, 1.99 (95% CI 1.57-2.53), 1.47 (95% CI 1.11-1.97), 1.65 (95% CI 1.27-2.14), 1.69 (95% CI 1.29-2.22), and 1.76 (95% CI 1.35-2.29) greater odds of reporting frequent pain. The odds of moderate/intense/strong pain were higher in older adults that reported poor sleep quality (OR: 2.21; 95% CI 1.08-4.51). Older adults with self-reported poor sleep quality, initial, intermediate and final insomnia, and daytime sleepiness had, respectively, 1.84 (95% CI 1.11-3.02), 1.73 (95% CI 1.14-2.62), 1.80 (95% CI 1.19-2.73), 1.58 (95% CI 1.07-2.34), and 1.63 (95% CI 1.11-2.39) greater odds of reporting pain-related disability.

CONCLUSION

Self-reported sleep problems are associated with pain manifestations in older adults. The results may help in the proposition of programs and public health policies.

Causal association between sleep traits and the risk of coronary artery disease in patients with diabetes

Background and aims

The association between sleep traits and coronary artery disease (CAD) in patients with diabetes has been reported in previous observational studies. However, whether these potential relationships are causal remains unclear. We aim to assess the causal relationship between sleep traits and CAD in diabetic.

Methods

Genetic instrumental variables associated with five sleep-related traits (insomnia, sleep duration, ease of getting up, morningness and snoring) were extracted from corresponding genome-wide association studies (GWAS). The associations of genetic variants with CAD were based on 15,666 individuals with diabetes (3,968 CAD cases and 11,696 controls). The primary analysis was derived using the inverse variance weighting method. Further sensitivity analysis was conducted to confirm the robustness and consistency of the main results.

Results

Genetic liability to insomnia was significantly related to the increased risk of CAD in individuals with diabetes [odds ratio (OR): 1.163; 95% CI: 1.072-1.254; p = 0.001]. Suggestive evidence was found for the borderline associations between both sleep duration (OR: 0.629; 95% CI: 0.380-1.042, p = 0.072) and snoring (OR: 1.010, 95% CI: 1.000-1.020, p = 0.050) with CAD risk. However, no consistent evidence was found for the association between ease of getting up and morningness with the risk of CAD in diabetic. Similar results can be verified in most sensitivity analyses.

Conclusions

We provide consistent evidence for the causal effect of insomnia on the increased risk of CAD in individuals with diabetes. The management of sleep health should be emphasized to prevent CAD in diabetic patients.

Association between abdominal obesity indices and risk of cardiovascular events in Chinese populations with type 2 diabetes: a prospective cohort study

BACKGROUND

Waist circumference (WC), visceral adiposity index (VAI), lipid accumulation product (LAP), and Chinese visceral adiposity index (CVAI) are considered surrogate indicators of abdominal fat deposition, but the longitudinal association of these indices with cardiovascular (CV) events in adults with type 2 diabetes (T2D) remains unclear. Our study aimed to examine the associations between abdominal obesity indices and incident CV events among people with T2D and to compare their predictive performance in risk assessment.

METHODS

The present study included 2328 individuals with T2D from the Xinjiang Multi-Ethnic Cohort. Multivariable Cox regression analyses were applied to assess the associations between abdominal obesity indices and CV events. Harrell's concordance statistic (C-statistic), net reclassification improvement (NRI) index, and integrated discrimination improvement (IDI) index were utilized to evaluate the predictive performance of each abdominal obesity index.

RESULTS

At a median follow-up period of 59 months, 289 participants experienced CV events. After multivariable adjustment, each 1-SD increase in WC, VAI, LAP, and CVAI was associated with a higher risk of CV events in people with T2D, with adjusted hazard ratios (HRs) being 1.57 [95% CI (confidence interval): 1.39-1.78], 1.11 (95% CI 1.06-1.16), 1.46 (95% CI 1.36-1.57), and 1.78 (95% CI 1.57-2.01), respectively. In subgroup analyses, these positive associations appeared to be stronger among participants with body mass index (BMI) < 25 kg/m² compared to overweight/obese participants. As for the predictive performance, CVAI had the largest C-statistic (0.700, 95% CI 0.672-0.728) compared to VAI, LAP, WC, and BMI (C-statistic: 0.535 to 0.670, all P for comparison < 0.05). When the abdominal obesity index was added to the basic risk model, the CVAI index also showed the greatest incremental risk stratification (C-statistic: 0.751 vs. 0.701, P < 0.001; IDI: 4.3%, P < 0.001; NRI: 26.6%, P < 0.001).

CONCLUSIONS

This study provided additional evidence that all abdominal obesity indices were associated with the risk of CV events and highlighted that CVAI might be a valuable abdominal obesity indicator for identifying the high risk of CV events in Chinese populations with T2D. These results suggest that proactive assessment of abdominal obesity could be helpful for the effective clinical management of the diabetic population.

Effects of sleep deprivation on coronary heart disease

The presence of artificial light enables humans to be active 24 h a day. Many people across the globe live in a social culture that encourages staying up late to meet the demands of various activities, such as work and school. Sleep deprivation (SD) is a severe health problem in modern society. Meanwhile, as with cardiometabolic disease, there was an obvious tendency that coronary heart disease (CHD) to become a global epidemic chronic disease. Specifically, SD can significantly increase the morbidity and mortality of CHD. However, the underlying mechanisms responsible for the effects of SD on CHD are multilayered and complex. Inflammatory response, lipid metabolism, oxidative stress, and endothelial function all contribute to cardiovascular lesions. In this review, the effects of SD on CHD development are summarized, and SD-related pathogenesis of coronary artery lesions is discussed. In general, early assessment of SD played a vital role in preventing the harmful consequences of CHD.

Association of the Coexistence of Somnipathy and Diabetes With the Risks of Cardiovascular Disease Events, Stroke, and All‐Cause Mortality: A Systematic Review and Meta‐analysis

Background

Somnipathy and diabetes are independently associated with an increased risk of cardiovascular disease (CVD). However, whether a combination of both conditions is associated with a higher risk of CVD events remains uncertain. Therefore, the aim of this meta‐analysis was to clarify this association.

Methods and Results

We searched MEDLINE, Web of Science, EMBASE, ClinicalTrials.gov , and the Cochrane Central Register for Controlled Trials. We included randomized controlled trials, nonrandomized trials, and prospective observational cohort studies that assessed the combined effect of diabetes and comorbid somnipathy on CVD risk and mortality for at least 1 year. Outcomes included CVD, coronary heart disease, stroke, and all‐cause mortality. Twelve studies involving 582 267 participants were included in the meta‐analysis. Patients with somnipathy and comorbid diabetes exhibited increased risks of CVD, coronary heart disease, stroke, and all‐cause mortality (risk ratio [RR], 1.27 [95% CI, 1.12–1.45], P <0.0001; RR, 1.40 [95% CI, 1.21–1.62], P <0.0001; RR, 1.28 [95% CI, 1.08–1.52], P =0.004, and RR, 1.56 [95% CI, 1.26–1.94], P <0.0001, respectively).

Conclusions

The coexistence of somnipathy and diabetes is associated with higher risks of CVD, coronary heart disease, stroke, and mortality than somnipathy or diabetes alone. Resolving sleep problems in patients with diabetes may reduce the risks of CVD, stroke, and mortality.

Registration Information

https://www.crd.york.ac.uk/prospero/ . Identifier: PROSPERO CRD42021274566.

Sleep duration predicts subsequent long-term mortality in patients with type 2 diabetes: a large single-center cohort study

Background

Sleep duration is associated with mortality. However, prior studies exploring whether sleep duration predicts subsequent long-term mortality in patients with diabetes are limited. This study aims to examine whether metabolic factors affect the associations between baseline sleep duration and subsequent risks of all-cause, expanded, and non-expanded cardiovascular disease (CVD) mortalities among patients with type 2 diabetes (T2D).

Methods

A total of 12,526 T2D patients aged 30 years and older, with a follow-up period ≥ 3 years, were identified from the Diabetes Case Management Program of a medical center in Taiwan. Sleep duration was measured using computerized questionnaires by case managers, and the time frame for this question was 1 month prior to the interview date. Sleep duration in relation to subsequent mortality from all causes, expanded CVD, and non-expanded CVD was examined using Cox proportional hazard models.

Results

Within 10 years of follow-up, 2918 deaths (1328 CVD deaths and 1590 non-CVD deaths) were recorded. A J-shaped association was observed for all-cause, expanded CVD, and non-expanded CVD mortalities, and the lowest risks were observed for patients with 5–7 h of sleep. The significant joint effects included sleep duration of more or less than 7 h with age ≥ 65 years [adjusted HRs: 4.00 (3.49–4.60)], diabetes duration ≥ 5 years [1.60 (1.40–1.84)], age at diabetes diagnosis ≤ 45 years [1.69 (1.38–2.07)], insulin use [1.76 (1.54–2.03)], systolic blood pressure/diastolic blood pressure > 130/85 mmHg [1.24 (1.07–1.43)], triglyceride ≥ 150 mg/dL [1.38 (1.22–1.56)], HbA1c ≥ 7% [1.31 (1.13–1.52)], and body mass index < 27 kg/m² [1.31 (1.17–1.45)] for all-cause mortality.

Conclusion

A J-shaped association was observed between sleep duration and all-cause and expanded CVD mortality, and a sleep duration of 5–7 h had the lowest mortality risk. Sleep duration also showed significant synergistic interactions with diabetes duration but shared an antagonistic interaction with age and obesity.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12933-022-01500-0.

Comparison of the Quality of Sleep in Patients With Chronic Kidney Disease and End-Stage Renal Disease

Objective

In this study, we aimed to compare the quality of sleep between patients with (CKD) and those with end-stage renal disease (ESRD).

Methodology

We performed a cross-sectional study between August 2020 and January 2021. We included 240 patients, among which 178 (74.2%) were CKD patients and 62 (25.8%) were ESRD patients on maintenance hemodialysis (MHD). Demographic data were collected on a pre-designed proforma. The quality of sleep was evaluated using the Pittsburgh Sleep Quality Index (PSQI). PSQI assesses subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, use of sleeping medication, and daytime dysfunction. A PSQI score >5 indicates poor sleep quality.

Results

Out of the 240 patients, 159 (66%) had poor sleep quality. We found a significant difference in mean PSQI scores between CKD and ESRD patients (9.6 ± 12.4 vs. 11.4 ± 3.9 respectively), indicating poorer sleep quality in ESRD patients as compared to those with CKD (p<0.001). In our study, among all comorbidities, poor sleep was significantly associated with ischemic heart disease (IHD) (p = 0.025), after adjusting for confounding factors.

Conclusions

Our study showed that two-thirds of the study population had poor sleep quality. ESRD patients suffered from more disturbed sleep as compared to CKD patients.

Association of healthy sleep pattern with the risk of cardiovascular disease and all-cause mortality among people with diabetes: A prospective cohort study

AIMS

This study aimed to assess the association of healthy sleep pattern with the risk of cardiovascular disease and all-cause mortality among people with diabetes.

METHODS

Our study included 12,770 individuals from the UK Biobank at baseline. Sleep patterns were defined by a combination of five sleep behaviors (chronotype, sleep duration, snoring, insomnia, and excessive daytime sleepiness). The competing risk models were used to estimate the relationship between sleep patterns and CVD (including coronary heart disease [CHD] and stroke) in individuals with diabetes. To examine the association between sleep patterns and all-cause mortality risk, we utilized the flexible parametric Royston-Parmar proportion-hazard models.

RESULTS

We recorded 2627 CVD events, which includes 1999 CHD and 903 S events, and 1576 all-cause mortality events. Compared to those with poor sleep pattern, individuals having healthy sleep pattern have a 24% lower CVD risk (p < 0.001), a 26% lower CHD risk (p = 0.001), a 25% lower stroke risk (p = 0.036), and a 21% lower all-cause mortality risk (p = 0.020).

CONCLUSIONS

Adherence to healthy sleep pattern has been significantly related to cardiovascular disease and all-cause mortality risk reduction among people with diabetes.

The Association of Cardiometabolic Disease with Psychological Factors in Colombian People during the COVID-19 Pandemic: A Cross-Sectional Study

During the COVID-19 pandemic, psychological disorders have been documented in the population, and their exacerbation in vulnerable populations such as those with Cardiometabolic Diseases (CD) might challenge health systems. This study determined psychological factors associated with CD in Colombian adults during the COVID-19 pandemic. For this purpose, 284 persons were evaluated, 142 without CD and 142 with CD. Sociodemographic data were collected, and the International Physical Activity Questionnaire (IPAQ), the SF-12v2, the Pittsburgh Sleep Quality Index (PSQI) and the Zung Self-Rating Depression Scale (ZSDS), which were integrated into an online form, were used. Through a simple and multiple logistic regression model, it was shown that CD was associated with low sleeping quality (LSQ) (OR = 3.51) and with depressive symptoms (DS) (OR = 1.98). In addition, in the group with CD, the presence of DS was related to BMI (OR = 2.45), and LSQ was related to living with persons at risk for COVID-19 (OR = 3.64) and BMI (OR = 5.88). In conclusion, this study showed that people with CD have a higher chance of presenting DS and LSQ. Furthermore, living with people at risk for COVID-19 was related to the presence of LSQ.

Sleep Disorders in Individuals With High Risk for Diabetes in Indian Population

Background:

Sleep restores physiology and neurochemical components of our body and is essential for physical and mental health. Sleep disorders (SDs) are associated with insulin resistance and metabolic disorders. The association between SDs and diabetes needs to be understood in the Indian population.

Purpose:

The purpose was to investigate the association between SD and diabetes in the Indian population.

Methods:

As a part of nationwide Niyantrita Madhumeha Bharata Abhiyaan-2017 (NMB-2017), a cross-sectional study was conducted and data was collected from seven zones of India, after screening through the Indian Diabetes Risk Score (IDRS). The sleep quality was assessed on a scale of 1 to 4 (very good = 1, very bad = 4). The time taken to fall asleep (sleep latency) was assessed on a scale of 0 to 5 (“0” = nil and “5” = >1.5 h). Stress was assessed by the perceived stress scale.

Results:

Bad sleep quality was positively (odds ratio 1.055, CI [1.001, 1.113], and P < .01) associated with self-reported known diabetes. Increased time taken to fall in sleep (sleep latency) was associated significantly with IDRS high risk (odds ratio 1.085, CI [1.008, 1.168], and P = .01), with an average sleep latency /time takes to fall in sleep (maximum range 5 [>1.5 h], mode 2 [10 to 30 min]) minutes. Moderate stress was significantly associated with bad sleep quality (odds ratio 1.659).

Conclusion:

A positive association of bad sleep quality and stress with diabetes, and an increased sleep latency in the IDRS high-risk population point to the role of modifiable risk factors. Behavioral modification and stress reduction by using yoga may be beneficial in the better management of diabetes.