Multiple lines of evidence support a complex relationship between obstructive sleep apnea (OSA) and diabetes. However, no population-based study has evaluated the potential bidirectional association ...between these two highly prevalent disorders.
We followed 146,519 participants from the Nurses' Health Study (NHS; 2002-2012), Nurses' Health Study II (NHSII; 1995-2013), and Health Professionals Follow-up Study (HPFS; 1996-2012) who were free of diabetes, cardiovascular disease, and cancer at baseline. Cox proportional hazards models were used to estimate hazard ratios (HRs) for developing diabetes according to OSA status. In parallel, we used similar approaches to estimate risk of developing OSA according to diabetes status among 151,194 participants free of OSA, cardiovascular disease, and cancer at baseline. In all three cohorts, diagnoses of diabetes and OSA were identified by validated self-reports.
Similar results were observed across the three cohorts. In the pooled analysis, 9,029 incident diabetes cases were identified during follow-up. After accounting for potential confounders, the HR (95% CI) for diabetes was 2.06 (1.86, 2.28) comparing those with versus without OSA. The association was attenuated but remained statistically significant after further adjusting for waist circumference and BMI (HR 1.37 95% CI 1.24, 1.53), with the highest diabetes risk observed for OSA concomitant with sleepiness (1.78 1.13, 2.82). In the second analysis, we documented 9,364 incident OSA cases during follow-up. Compared with those without diabetes, the multivariable HR (95% CI) for OSA was 1.53 (1.32, 1.77) in individuals with diabetes. Adjustment for BMI and waist circumference attenuated the association (1.08 1.00, 1.16); however, an increased risk was observed among those with diabetes who used insulin compared with those without diabetes (1.43 1.11, 1.83), particularly among women (1.60 1.34, 1.89).
OSA is independently associated with an increased risk of diabetes, whereas insulin-treated diabetes is independently associated with a higher risk of OSA, particularly in women. Clinical awareness of this bidirectional association may improve prevention and treatment of both diseases. Future research aimed at elucidating the mechanisms that underlie each association may identify novel intervention targets.
Sleep-disordered breathing (SDB), characterized by specific underlying physiological mechanisms, comprises obstructive and central pathophysiology, affects nearly 1 billion individuals worldwide, and ...is associated with excessive cardiopulmonary morbidity. Strong evidence implicates SDB in cardiac arrhythmogenesis. Immediate consequences of SDB include autonomic nervous system fluctuations, recurrent hypoxia, alterations in carbon dioxide/acid-base status, disrupted sleep architecture, and accompanying increases in negative intrathoracic pressures directly affecting cardiac function. Day-night patterning and circadian biology of SDB-induced pathophysiological sequelae collectively influence the structural and electrophysiological cardiac substrate, thereby creating an ideal milieu for arrhythmogenic propensity. Cohort studies support strong associations of SDB and cardiac arrhythmia, with evidence that discrete respiratory events trigger atrial and ventricular arrhythmic events. Observational studies suggest that SDB treatment reduces atrial fibrillation recurrence after rhythm control interventions. However, high-level evidence from clinical trials that supports a role for SDB intervention on rhythm control is not available. The goals of this scientific statement are to increase knowledge and awareness of the existing science relating SDB to cardiac arrhythmias (atrial fibrillation, ventricular tachyarrhythmias, sudden cardiac death, and bradyarrhythmias), synthesizing data relevant for clinical practice and identifying current knowledge gaps, presenting best practice consensus statements, and prioritizing future scientific directions. Key opportunities identified that are specific to cardiac arrhythmia include optimizing SDB screening, characterizing SDB predictive metrics and underlying pathophysiology, elucidating sex-specific and background-related influences in SDB, assessing the role of mobile health innovations, and prioritizing the conduct of rigorous and adequately powered clinical trials.
Extremes of sleep duration have been associated with adverse health outcomes. The mechanism is unclear but may be related to increased inflammation. We sought to assess the association between sleep ...duration and inflammatory biomarkers.
A total of 614 individuals from the Cleveland Family Study completed questionnaires about sleep habits and underwent polysomnography. A morning fasting blood sample was assayed for 5 inflammatory cytokines.
In this cohort, mean (SD) habitual sleep duration based on self-report was 7.6 (1.6) h and mean sleep duration by polysomnography (PSG) on the night prior to blood sampling was 6.2 (1.3) h. After adjusting for obesity and apnea severity, each additional hour of habitual sleep duration was associated with an 8% increase in C-reactive protein (CRP) levels (P=0.004) and 7% increase in interleukin-6 (IL-6) levels (P=0.0003). These associations were independent of self-reported sleepiness. In contrast, PSG sleep duration was inversely associated with tumor necrosis factor alpha (TNFa) levels. For each hour reduction in sleep, TNFalpha levels increased by 8% on average (P=0.02). Sleep duration was not associated with IL-1 or IL-10.
Increases in habitual sleep durations are associated with elevations in CRP and IL-6 while reduced PSG sleep duration is associated with elevated TNFa levels. Activation of pro-inflammatory pathways may represent a mechanism by which extreme sleep habits affect health.
Short sleep duration, which is associated with increased morbidity and mortality, has been shown to vary by occupation and industry, but few studies have investigated differences between black and ...white populations. By using data from a nationally representative sample of US adult short sleepers (n = 41,088) in the National Health Interview Survey in 2004-2011, we estimated prevalence ratios for short sleep duration in blacks compared with whites for each of 8 industry categories by using adjusted Poisson regression models with robust variance. Participants' mean age was 47 years; 50% were women and 13% were black. Blacks were more likely to report short sleep duration than whites (37% vs. 28%), and the black-white disparity was widest among those who held professional occupations. Adjusted short sleep duration was more prevalent in blacks than whites in the following industry categories: finance/information/real estate (prevalence ratio (PR) = 1.44, 95% confidence interval (CI): 1.30, 1.59); professional/administrative/management (PR = 1.30, 95% CI: 1.18, 1.44); educational services (PR = 1.39, 95% CI: 1.25, 1.54); public administration/arts/other services (PR = 1.30, 95% CI: 1.21, 1.41); health care/social assistance (PR = 1.23, 95% CI: 1.14, 1.32); and manufacturing/construction (PR = 1.14, 95% CI: 1.07, 1.20). Short sleep generally increased with increasing professional responsibility within a given industry among blacks but decreased with increasing professional roles among whites. Our results suggest the need for further investigation of racial/ethnic differences in the work-sleep relationship.
Linear mixed models (LMMs) are widely used in genome-wide association studies (GWASs) to account for population structure and relatedness, for both continuous and binary traits. Motivated by the ...failure of LMMs to control type I errors in a GWAS of asthma, a binary trait, we show that LMMs are generally inappropriate for analyzing binary traits when population stratification leads to violation of the LMM’s constant-residual variance assumption. To overcome this problem, we develop a computationally efficient logistic mixed model approach for genome-wide analysis of binary traits, the generalized linear mixed model association test (GMMAT). This approach fits a logistic mixed model once per GWAS and performs score tests under the null hypothesis of no association between a binary trait and individual genetic variants. We show in simulation studies and real data analysis that GMMAT effectively controls for population structure and relatedness when analyzing binary traits in a wide variety of study designs.
Hispanic/Latino populations have a high prevalence of cardiovascular risk factors and may be at risk for sleep-disordered breathing (SDB). An understanding of SDB among these populations is needed ...given evidence that SDB increases cardiovascular risk.
To quantify SDB prevalence in the U.S. Hispanic/Latino population and its association with symptoms, risk factors, diabetes, and hypertension; and to explore variation by sex and Hispanic/Latino background.
Cross-sectional analysis from the baseline examination of the Hispanic Community Health Study/Study of Latinos.
The apnea-hypopnea index (AHI) was derived from standardized sleep tests; diabetes and hypertension were based on measurement and history. The sample of 14,440 individuals had an age-adjusted prevalence of minimal SDB (AHI ≥ 5), moderate SDB (AHI ≥ 15), and severe SDB (AHI ≥ 30) of 25.8, 9.8, and 3.9%, respectively. Only 1.3% of participants reported a sleep apnea diagnosis. Moderate SDB was associated with being male (adjusted odds ratio, 2.7; 95% confidence interval, 2.3-3.1), obese (16.8; 11.6-24.4), and older. SDB was associated with an increased adjusted odds of impaired glucose tolerance (1.7; 1.3-2.1), diabetes (2.3; 1.8-2.9), and hypertension. The association with hypertension varied across background groups with the strongest associations among individuals of Puerto Rican and Central American background.
SDB is prevalent in U.S. Latinos but rarely associated with a clinical diagnosis. Associations with diabetes and hypertension suggest a large burden of disease may be attributed to untreated SDB, supporting the development and evaluation of culturally relevant detection and treatment approaches.
Abstract
Study Objectives:
Short sleep duration and poor sleep quality are associated with adverse cardiovascular outcomes. Potential pathophysiological mechanisms include sleep-associated ...alterations in the autonomic nervous system. The objective of this study was to examine the associations of shorter sleep duration and poorer sleep quality with markers of autonomic tone: heart rate (HR), high-frequency HR variability (HF-HRV) and salivary amylase.
Methods:
Cross-sectional analysis of data from actigraphy-based measures of sleep duration and efficiency and responses to a challenge protocol obtained from 527 adult participants in the Multi-Ethnic Study of Atherosclerosis.
Results:
Participants who slept fewer than 6 h per night (compared to those who slept 7 h or more per night) had higher baseline HR (fully adjusted model 0.05 log beats/min, 95% confidence interval CI 0.01, 0.09) and greater HR orthostatic reactivity (fully adjusted model 0.02 log beats/min, 95% CI 0.002, 0.023). Participants who slept 6 to less than 7 h/night (compared to those who slept 7 h or more per night) had lower baseline HF-HRV (fully adjusted model −0.31 log msec2, 95% CI −0.60, −0.14). Participants with low sleep efficiency had lower baseline HF-HRV than those with higher sleep efficiency (fully adjusted model −0.59 log msec2, 95% CI −1.03, −0.15). Participants with low sleep efficiency had higher baseline levels of amylase than those with higher sleep efficiency (fully adjusted model 0.45 log U/mL, 95% CI 0.04, 0.86).
Conclusions:
Short sleep duration, low sleep efficiency, and insomnia combined with short sleep duration were associated with markers of autonomic tone that indicate lower levels of cardiac parasympathetic (vagal) tone and/or higher levels of sympathetic tone.
Most existing automated sleep staging methods rely on multimodal data, and scoring a specific epoch requires not only the current epoch but also a sequence of consecutive epochs that precede and ...follow the epoch.
We proposed and tested a convolutional neural network called SleepInceptionNet, which allows sleep classification of a single epoch using a single-channel electroencephalogram (EEG).
SleepInceptionNet is based on our systematic evaluation of the effects of different EEG preprocessing methods, EEG channels, and convolutional neural networks on automatic sleep staging performance. The evaluation was performed using polysomnography data of 883 participants (937,975 thirty-second epochs). Raw data of individual EEG channels (ie, frontal, central, and occipital) and 3 specific transformations of the data, including power spectral density, continuous wavelet transform, and short-time Fourier transform, were used separately as the inputs of the convolutional neural network models. To classify sleep stages, 7 sequential deep neural networks were tested for the 1D data (ie, raw EEG and power spectral density), and 16 image classifier convolutional neural networks were tested for the 2D data (ie, continuous wavelet transform and short-time Fourier transform time-frequency images).
The best model, SleepInceptionNet, which uses time-frequency images developed by the continuous wavelet transform method from central single-channel EEG data as input to the InceptionV3 image classifier algorithm, achieved a Cohen κ agreement of 0.705 (SD 0.077) in reference to the gold standard polysomnography.
SleepInceptionNet may allow real-time automated sleep staging in free-living conditions using a single-channel EEG, which may be useful for on-demand intervention or treatment during specific sleep stages.
Sleep duration and sleep quality are important predictors of risk for cardiovascular disease (CVD). One potential link between sleep health and CVD is through lifestyle factors such as diet. To ...clarify the association between diet and sleep, we assessed the associations of sleep duration and insomnia symptoms with current Mediterranean-style diet (aMed) and with historical changes in aMed score. Actigraphy-measured sleep duration and self-reported insomnia symptoms categorized as insomnia with short sleep (<6 hr/night), insomnia without short sleep, no insomnia with short sleep, and no insomnia or short sleep were obtained from 2068 individuals who also had dietary intake data. A 10-point aMed score, derived from a self-report food frequency questionnaire, was collected concurrently with the sleep assessment and 10 years before. Compared with individuals who currently reported a low aMed score, those with a moderate-high aMed score were more likely to sleep 6-7 vs. <6 hr/night (p < 0.01) and less likely to report insomnia symptoms occurring with short sleep (vs. no insomnia or short sleep alone; p < 0.05). An increase in aMed score over the preceding 10 years was not associated with sleep duration or insomnia symptoms. However, compared with those with decreasing aMed score, individuals with an unchanging score reported fewer insomnia symptoms (p ≤ 0.01). These results suggest that a Mediterranean-style diet is associated with adequate sleep duration, less insomnia symptoms, and less likely to have insomnia accompanied by short sleep. Further research should identify possible mediators through which diet may promote adequate sleep duration and reduce the risk of insomnia.
Research indicates that sleep duration and quality are inter-related factors that contribute to obesity, but few studies have focused on sleep chronotype, representing an individual's circadian ...proclivity, nor assessed these factors in racially diverse middle-aged samples. We examined the associations between chronotype and obesity among black and white men and women participating in the Bogalusa Heart Study (BHS).Body mass index (BMI) and sleep data were available for 1,197 middle-aged men and women (mean age 48.2 ± 5.3 years) who participated in the BHS 2013-2016. Based on the reduced Morningness-Eveningness Questionnaire's cutoff values for chronotypes, we combined 'definitely morning' and 'moderately morning' types into 'morning' type, 'definitely evening' and 'moderately evening' types into 'evening' type and kept those who were "neither" type in a separate group. We used 'morning' type as the referent group. Obesity was defined as a BMI ≥ 30. Multivariable logistic regression models were used to examine associations adjusting for sex, age, education, smoking, alcohol use and drug use, depression, shift work, physical activity and sleep duration.Evening chronotype, reported by 11.1% of participants, was associated with obesity after multi-variable adjustment, including shift work, physical activity and sleep duration (OR 1.67, 95% CI: 1.08-2.56). However, once stratified by race (black/white), this association was found only among white participants (OR = 1.91, 95% CI = 1.12-3.25) after full adjustment.In our biracial, community-based population, evening chronotype was independently associated with obesity, specifically among white participants. Further research is needed to identify behavioral, endocrine, nutritional and genetic pathways which underlie these associations.
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