Short Sleep, Insomnia, and Cardiovascular Disease

Ethnic Disparities in the Risk Factors, Morbidity, and Mortality of Cardiovascular Disease in People With Diabetes

Cardiovascular disease (CVD) is the leading cause of death in people with diabetes. Compared with European Americans, African Americans have more favorable lipid profiles, as indicated by higher high-density lipoprotein cholesterol, lower triglycerides, and less dense low-density lipoprotein particles. The less atherogenic lipid profile translates to lower incidence and prevalence of CVD in African Americans with diabetes, despite higher rates of hypertension and obesity. However, African Americans with CVD experience worse clinical outcomes, including higher mortality, compared with European Americans. This mini-review summarizes the epidemiology, pathophysiology, mechanisms, and management of CVD in people with diabetes, focusing on possible factors underlying the "African American CVD paradox" (lower CVD incidence/prevalence but worse outcomes). Although the reasons for the disparities in CVD outcomes remain to be fully elucidated, we present a critical appraisal of the roles of suboptimal control of risk factors, inequities in care delivery, several biological factors, and psychosocial stress. We identify gaps in current knowledge and propose areas for future investigation.

Neighborhood determinants of sleep and the moderating role of cultural factors among native adolescents

OBJECTIVE

This study examined the association between neighborhood social environment and sleep among urban American Indian and Alaska Native (AI/AN) adolescents as well as the moderating role of cultural factors in this association.

METHOD

The analytic sample included 133 urban AI/AN adolescents (age 12-16, 57.1% female, Mage = 14.03, SDage = 1.35). Perceived neighborhood social environment included safety and cohesion. Cultural factors included AI/AN cultural identification and historical loss. Sleep duration, efficiency, and wake after sleep onset (WASO) were measured via actigraphy. Sleep disturbance was measured via a questionnaire.

RESULTS

Greater neighborhood safety was significantly associated with lower sleep disturbance (b = -2.17, SE = 0.8, p = .008), higher sleep efficiency (b = 1.75, SE = 0.64, p = .006), and lower WASO (b = -8.60, SE = 3.34, p = .01). Neighborhood cohesion was not associated with any sleep outcomes. Cultural factors moderated the association between neighborhood social environment and sleep outcomes (p < .05). Specifically, both neighborhood safety and cohesion were associated with lower sleep disturbance, only among individuals reporting higher levels of AI/AN cultural identification. Further, neighborhood safety was associated with greater sleep efficiency and lower WASO (i.e., better sleep) only among adolescents with higher contemplation of historical loss.

CONCLUSIONS

Findings highlight the importance of considering cultural factors in addressing sleep and health disparities. AI/AN cultural identification and a sense of historical loss may be important targets for identifying adolescents who might benefit the most from policies and interventions focused on improving the social environment in order to improve sleep and other health outcomes. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Insomnia and Early Incident Atrial Fibrillation: A 16-Year Cohort Study of Younger Men and Women Veterans

Background There is growing consideration of sleep disturbances and disorders in early cardiovascular risk, including atrial fibrillation (AF). Obstructive sleep apnea confers risk for AF but is highly comorbid with insomnia, another common sleep disorder. We sought to first determine the association of insomnia and early incident AF risk, and second, to determine if AF onset is earlier among those with insomnia. Methods and Results This retrospective analysis used electronic health records from a cohort study of US veterans who were discharged from military service since October 1, 2001 (ie, post-9/11) and received Veterans Health Administration care, 2001 to 2017. Time-varying, multivariate Cox proportional hazard models were used to examine the independent contribution of insomnia diagnosis to AF incidence while serially adjusting for demographics, lifestyle factors, clinical comorbidities including obstructive sleep apnea and psychiatric disorders, and health care utilization. Overall, 1 063 723 post-9/11 veterans (Mean age=28.2 years, 14% women) were followed for 10 years on average. There were 4168 cases of AF (0.42/1000 person-years). Insomnia was associated with a 32% greater adjusted risk of AF (95% CI, 1.21-1.43), and veterans with insomnia showed AF onset up to 2 years earlier. Insomnia-AF associations were similar after accounting for health care utilization (adjusted hazard ratio [aHR], 1.27 [95% CI, 1.17-1.39]), excluding veterans with obstructive sleep apnea (aHR, 1.38 [95% CI, 1.24-1.53]), and among those with a sleep study (aHR, 1.26 [95% CI, 1.07-1.50]). Conclusions In younger adults, insomnia was independently associated with incident AF. Additional studies should determine if this association differs by sex and if behavioral or pharmacological treatment for insomnia attenuates AF risk.

Investigating the causal interplay between sleep traits and risk of acute myocardial infarction: a Mendelian randomization study

BACKGROUND

Few studies have investigated the joint effects of sleep traits on the risk of acute myocardial infarction (AMI). No previous study has used factorial Mendelian randomization (MR) which may reduce confounding, reverse causation, and measurement error. Thus, it is prudent to study joint effects using robust methods to propose sleep-targeted interventions which lower the risk of AMI.

METHODS

The causal interplay between combinations of two sleep traits (including insomnia symptoms, sleep duration, or chronotype) on the risk of AMI was investigated using factorial MR. Genetic risk scores for each sleep trait were dichotomized at their median in UK Biobank (UKBB) and the second survey of the Trøndelag Health Study (HUNT2). A combination of two sleep traits constituting 4 groups were analyzed to estimate the risk of AMI in each group using a 2×2 factorial MR design.

RESULTS

In UKBB, participants with high genetic risk for both insomnia symptoms and short sleep had the highest risk of AMI (hazard ratio (HR) 1.10; 95% confidence interval (CI) 1.03, 1.18), although there was no evidence of interaction (relative excess risk due to interaction (RERI) 0.03; 95% CI -0.07, 0.12). These estimates were less precise in HUNT2 (HR 1.02; 95% CI 0.93, 1.13), possibly due to weak instruments and/or small sample size. Participants with high genetic risk for both a morning chronotype and insomnia symptoms (HR 1.09; 95% CI 1.03, 1.17) and a morning chronotype and short sleep (HR 1.11; 95% CI 1.04, 1.19) had the highest risk of AMI in UKBB, although there was no evidence of interaction (RERI 0.03; 95% CI -0.06, 0.12; and RERI 0.05; 95% CI -0.05, 0.14, respectively). Chronotype was not available in HUNT2.

CONCLUSIONS

This study reveals no interaction effects between sleep traits on the risk of AMI, but all combinations of sleep traits increased the risk of AMI except those with long sleep. This indicates that the main effects of sleep traits on AMI are likely to be independent of each other.

Contribution of Comorbid Conditions to the Diagnosis of Insomnia: A Database Study in a Commercially Insured Population

ABSTRACT

Insomnia is a common sleep disorder characterized as dissatisfaction with sleep quantity or quality resulting in distress or impairment of social, occupational, or other daily functioning. It is unknown if there are medical conditions that have strong associations with insomnia but are unrecognized in previous literature. In this cross-sectional study based on IBM Marketscan Research Databases, we measured insomnia and 78 medical conditions in patients with 2-year continuous enrollment during 2018-2019. We selected important comorbidities associated with insomnia for eight age-sex groups and built logistic regression models to measure the associations. The prevalence of diagnosed insomnia increased with age, from <0.4% in the age group 0-17 to 4%-5% in the age group ≥65. Females had a higher prevalence of insomnia than males. Anxiety and depression were two important comorbidities across all age-sex subgroups. Most odds ratios of comorbidities remained significant after adjusting for other comorbidities in regression models. We did not find any new medical conditions that had strong associations with insomnia but were unrecognized in previous literature. The findings can help physicians use comorbidities to identify patients with high risk of insomnia.

Assessment of lifestyle "vital signs" in healthcare settings

Unhealthy lifestyles, such as maintenance of poor diets and physical inactivity, are a powerful driver of disease-producing risk factors and chronic illnesses. This has led to an increasing call to assess adverse lifestyle factors in healthcare settings. This approach could be aided by designating health-related lifestyle factors as "vital signs" that can be recorded during patient visits. Just such an approach has been used for assessing patients' smoking habits since the 1990s. In this review, we assess the rationale for addressing six other health-related lifestyle factors, beyond smoking, in patient care settings: physical activity (PA), sedentary behavior (SB), participation in muscle strengthening exercises, mobility limitations, diet, and sleep quality. For each domain, we evaluate the evidence that supports currently proposed ultra-short screening tools. Our analysis indicates strong medical evidence to support the use of one to two-item screening questions for assessing patients' PA, SB, muscle strengthening activities, and presence of "pre-clinical" mobility limitations. We also present a theoretical basis for measuring patients' diet quality through use of an ultrashort dietary screen, based on evaluation of healthy food intake (fruits/vegetables) and unhealthy food intake (high consumption of highly processed meats and/or consumption of sugary foods and beverages) and a proposed evaluation of sleep quality using a single-item screener. The result is a 10-item lifestyle questionnaire that is based on patient self-report. As such, this questionnaire has the potential to be employed as a practical tool for assessing health behaviors in clinical care settings without impairing the normal workflow of healthcare providers.

Cardiac events and economic burden among patients with hypertension and treated insomnia in the USA

Background: Cardiovascular (CV) event risk, healthcare resource utilization (HCRU) and costs have not been elucidated among hypertension patients with treated insomnia (H + TI). Materials & methods: Adult patients with H + TI were identified in IBM MarketScan databases. H + TI patients were matched 1:1 on age and sex to controls with hypertension but without sleep disorders. Multivariable models were used to estimate associations between treated insomnia and CV event risk, HCRU and costs. Results: In total, 81,502 H + TI patients (mean age = 62 years, 53% female) were matched. Relative to controls, H + TI patients were 2.4 times as likely to have CV events. H + TI patients incurred higher costs per patient per month (US$2343 vs US$1013). Conclusion: Treated insomnia was associated with higher costs and HRCU in hypertension patients.

Short Sleep Duration and Erectile Dysfunction: A Review of the Literature

The meaning of sleep has puzzled people for millennia. In modern society, short sleep duration is becoming a global problem. It has been established that short sleep duration can increase the risk of several diseases, such as cardiovascular and metabolic diseases. Currently, a growing body of research has revealed a possible link between sleep disorders and erectile dysfunction (ED). However, the mechanisms linking short sleep duration and ED are largely unknown. Thus, we provide a review of clinical trials and animal studies. In this review, we propose putative pathways connecting short sleep duration and ED, including neuroendocrine pathways and molecular mechanisms, aiming to pave the way for future research. Meanwhile, the assessment and improvement of sleep quality should be recommended in the diagnosis and treatment of ED patients.

Understanding insomnia as systemic disease

Sleep plays a critical role in homeostasis of the body and mind. Insomnia is a disease that causes disturbances in the initiation and maintenance of sleep. Insomnia is known to affect not only the sleep process itself but also an individual’s cognitive function and emotional regulation during the daytime. It increases the risk of various neuropsychiatric diseases such as depression, anxiety disorder, and dementia. Although it might appear that insomnia only affects the nervous system, it is also a systemic disease that affects several aspects of the body, such as the cardiovascular, endocrine, and immune systems; therefore, it increases the risk of various diseases such as hypertension, diabetes mellitus, and infection. Insomnia has a wide range of effects on our bodies because sleep is a complex and active process. However, a high proportion of patients with insomnia do not seek treatment, which results in high direct and indirect costs. This is attributed to the disregard of many of the negative effects of insomnia. Therefore, we expect that understanding insomnia as a systemic disease will provide an opportunity to understand the condition better and help prevent secondary impairment due to insomnia.

A Feasibility Study on Smart Mattresses to Improve Sleep Quality

Good sleep quality is essential, especially for clinical users. Sleep disorders not only impair the success rate of treatment but also delay recovery. They can seriously interfere with treatment outcomes and even endanger a user's life. In this study, we created a smart mattress containing 10 × 18 air packs and control units. Each air pack contains a set of pressure and height sensors and two air valves. Each row control unit can detect and adjust the pressure and height of each air bag in the row. When the bed body is turned on, it automatically initializes, adjusts the state of each air bag to the same height and pressure, and enters a slow scanning state. When perceived objects or people are lying on the bed, the bed automatically perceives the human body structure and body pressure matrix, increases the scanning speed for more timely and accurate measurements of the digital matrix and forming pressure by matrix-normalized processing, and then uses local pressure variance detection to automatically adjust to the sleeping position of the human body and thus achieve a uniform force distribution and a comfortable state. Finally, pressure matrix binarization was used to match sleeping position templates to identify the best template for automatic recognition of the sleeping position. The experimental results show that the sleeping position recognition method has high accuracy, recall, and precision. Our mattress is designed with interfaces for external devices. In future research, the smart mattress can connect to an auxiliary part of a smart ecosystem consisting of a smart pill box, a smart lighting system, and a microclimate system, which is expected to yield a more comprehensive intelligent ward to explore the possibility of improving sleep quality.

Automatic identification of insomnia using optimal antisymmetric biorthogonal wavelet filter bank with ECG signals

Sleep is a fundamental human physiological activity required for adequate working of the human body. Sleep disorders such as sleep movement disorders, nocturnal front lobe epilepsy, insomnia, and narcolepsy are caused due to low sleep quality. Insomnia is one such sleep disorder where a person has difficulty in getting quality sleep. There is no definitive test to identify insomnia; hence it is essential to develop an automated system to identify it accurately. A few automated methods have been proposed to identify insomnia using either polysomnogram (PSG) or electroencephalogram (EEG) signals. To the best of our knowledge, we are the first to automatically detect insomnia using only electrocardiogram (ECG) signals without combining them with any other physiological signals. In the proposed study, an optimal antisymmetric biorthogonal wavelet filter bank (ABWFB) has been used, which is designed to minimize the joint duration-bandwidth localization (JDBL) of the underlying filters. The L₁-norm feature is computed from the various wavelet sub-bands coefficients of ECG signals. The L₁ norm features are fed to various supervised machine learning classifiers for the automated detection of insomnia. In this work, ECG recordings of seven insomnia patients and six normal subjects are used from the publicly available cyclic alternating pattern (CAP) sleep database. We created ten different subsets of ECG signals based on annotations of sleep-stages, namely wake (W), S1, S2, S3, S4, rapid eye moment (REM), light sleep stage (LSS), slow-wave sleep (SWS), non-rapid eye movement (NREM) and W + S1+S2+S3+S4+REM for the automated identification of insomnia. Our proposed ECG-based system obtained the highest classification accuracy of 97.87%, F1-score of 97.39%, and Cohen's kappa value of 0.9559 for K-nearest neighbour (KNN) with the ten-fold cross-validation strategy using ECG signals corresponding to the REM sleep stage. The support vector machine (SVM) yielded the highest value of 0.99 for area under the curve with the ten fold cross-validation corresponding to REM sleep stage.

Relationships Between a Range of Inflammatory Biomarkers and Subjective Sleep Quality in Chronic Insomnia Patients: A Clinical Study

PURPOSE

To examine whether associations exist between chronic insomnia disorder (CID) and overlooked inflammatory factors (Serum amyloid protein A [SAA]), tumor necrosis factor [TNF]-α, granulocyte-macrophage colony-stimulating factor [GM-CSF], and regulated on activation and normal T cell expressed and presumably secreted [RANTES]).

PATIENTS AND METHODS

A total of 65 CID patients and 39 sex- and age-matched good sleeper (GS) controls participated in this study. They completed a baseline survey to collect data on demographics, and were elevated sleep and mood by Pittsburgh Sleep Quality Index (PSQI), Athens Insomnia Scale (AIS), 17-item Hamilton Depression Rating Scale (HAMD-17) and 14-item Hamilton Anxiety Rating Scale (HAMA-14), respectively. The blood samples were collected and tested the serum levels of SAA, TNF-α, GM-CSF and RANTES.

RESULTS

The CID group had higher serum levels of SAA, TNF-α, and GM-CSF and a lower level of RANTES than the GS group. In the Spearman correlation analysis, SAA and GM-CSF positively correlated with the PSQI and AIS scores. After controlling for sex, HAMD-17 score, and HAMA-14 score, the partial correlation analysis showed that GM-CSF was positively correlated with PSQI score. Further stepwise linear regression analyses showed that GM-CSF was positively associated with the PSQI and AIS scores, while RANTES was negatively associated with them, and SAA was positively associated with just the AIS score.

CONCLUSION

The serum levels of inflammatory mediators (SAA, TNF-α, and GM-CSF) were significantly elevated and the level of RANTES was significantly decreased in CID patients and, to some extent, the changes are related to the severity of insomnia. These findings may help us to improve interventions to prevent the biological consequences of CID by inhibiting inflammation, thereby promoting health.