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Study Objectives: Stroke can result in or exacerbate various sleep disorders. The presence of behaviors such as daytime sleepiness poststroke can indicate underlying sleep disorders which can significantly impact functional recovery and thus require prompt detection and monitoring for improved care. Actigraphy, a quantitative measurement technology, has been primarily validated for nighttime sleep in healthy adults; however, its validity for daytime sleep monitoring is currently unknown. Therefore this study aims to identify the best-performing actigraphy sensor and algorithm for detecting daytime sleep in poststroke individuals., Methods: Participants wore Actiwatch Spectrum and ActiGraph wGT3X-BT on their less-affected wrist, while trained observers recorded daytime sleep occurrences and activity levels (active, sedentary, and asleep) during non-therapy times. Algorithms, Actiwatch (Autoscore AMRI) and ActiGraph (Cole-Kripke, Sadeh), were compared with on-site observations and assessed using F2 scores, emphasizing sensitivity to detect daytime sleep., Results: Twenty-seven participants from an inpatient stroke rehabilitation unit contributed 173.5 hours of data. The ActiGraph Cole-Kripke algorithm (minute sleep time = 15 minutes, bedtime = 10 minutes, and wake time = 10 minutes) achieved the highest F2 score (0.59). Notably, when participants were in bed, the ActiGraph Cole-Kripke algorithm continued to outperform Sadeh and Actiwatch AMRI, with an F2 score of 0.69., Conclusions: The study demonstrates both Actiwatch and ActiGraph's ability to detect daytime sleep, particularly during bed rest. ActiGraph (Cole-Kripke) algorithm exhibited a more balanced sleep detection profile and higher F2 scores compared to Actiwatch, offering valuable insights for optimizing daytime sleep monitoring with actigraphy in stroke patients., (© The Author(s) 2024. Published by Oxford University Press on behalf of Sleep Research Society.)

We aim to examine the association of sleep duration, sleep quality, late chronotype, and circadian misalignment with glycemic control and risk of complications in young adults with youth-onset type 2 diabetes followed in the Treatment Options for Type 2 Diabetes in Adolescents and Youth (TODAY) study. Self-reported sleep duration, quality, timing, and circadian misalignment were assessed via a modified Pittsburgh Sleep Quality Index (PSQI) questionnaire, and chronotype was assessed via the Morningness-Eveningness Questionnaire (MEQ). We examined diabetes complications including loss of glycemic control (defined as hemoglobin A1c ≥8%), hypertension, dyslipidemia, albuminuria, and diabetic peripheral neuropathy. Multivariable logistic regression models were constructed to assess associations between sleep and circadian measures with outcomes of interest, such as loss of glycemic control and diabetes complications. A total of 421 participants (34.2% male), mean age 23.6 ± 2.5 yr, mean body mass index (BMI) of 36.1 ± 8.3 kg/m 2 , and mean diabetes duration of 10.0 ± 1.5 yr were evaluated. Self-reported short sleep duration, daytime sleepiness, and sleep quality were not associated with loss of glycemic control or diabetes complications. Late self-reported bedtime (after midnight) on work/school nights, rather than self-expressed chronotype or circadian misalignment, was independently associated with loss of glycemic control. An association was seen between late bedtimes and albuminuria but was attenuated after adjusting for depression. In conclusion, late bedtime on work/school days, rather than short sleep duration, daytime sleepiness, or poor sleep quality, was independently associated with loss of glycemic control in this longitudinal cohort of young adults with youth-onset type 2 diabetes. NEW & NOTEWORTHY The prevalence of type 2 diabetes in youth is increasing at an alarming rate. Identifying potentially modifiable factors modulating glycemic control is critically important to reduce micro and macrovascular complications. In a large cohort of youth-onset type 2 diabetes, self-reported late bedtime on work/school days was independently associated with loss of glycemic control in this longitudinal cohort of young adults with youth-onset type 2 diabetes.

Study Objectives: To evaluate wearable devices and machine learning for detecting sleep apnea in patients with stroke at an acute inpatient rehabilitation facility (IRF)., Methods: A total of 76 individuals with stroke wore a standard home sleep apnea test (ApneaLink Air), a multimodal, wireless wearable sensor system (ANNE), and a research-grade actigraphy device (ActiWatch) for at least one night during their first week after IRF admission as part of a larger clinical trial. Logistic regression algorithms were trained to detect sleep apnea using biometric features obtained from the ANNE sensors and ground truth apnea rating from the ApneaLink Air. Multiple algorithms were evaluated using different sensor combinations and different apnea detection criteria based on the Apnea-Hypopnea Index (AHI≥5, AHI≥15)., Results: Seventy-one (96%) participants wore the ANNE sensors for multiple nights. In contrast, only forty-eight participants (63%) could be successfully assessed for OSA by ApneaLink; 28 (37%) refused testing. The best-performing model utilized photoplethysmography (PPG) and finger temperature features to detect moderate-severe sleep apnea (AHI≥15), with 88% sensitivity and a positive likelihood ratio (LR+) of 44.00. This model was tested on additional nights of ANNE data achieving 71% sensitivity (10.14 LR+) when considering each night independently and 86% accuracy when averaging multi-night predictions., Conclusions: This research demonstrates the feasibility of accurately detecting moderate-severe sleep apnea early in the stroke recovery process using wearable sensors and machine learning techniques. These findings can inform future efforts to improve early detection for post-stroke sleep disorders, thereby enhancing patient recovery and long-term outcomes., (© The Author(s) 2024. Published by Oxford University Press on behalf of Sleep Research Society. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Gender and age are well-established determinants of health and sleep health that influence overall health, which also often varies by gender and age. Sleep architecture is an important component of sleep health. The goal of this analysis was to examine whether associations between age and sleep stages differ by gender in the absence of moderate-severe obstructive sleep apnea (OSA) in a rural setting in Brazil. This study conducted polysomnography recordings in the Baependi Heart Study, a cohort of Brazilian adults. Our sample included 584 women and 309 men whose apnea-hypopnea index was ≤15 events/h. We used splines to distinguish non-linear associations between age, total sleep time, wake after sleep onset (WASO), N2, N3, and rapid-eye-movement sleep. The mean (standard deviation; range) age was 47 (14; 18-89) years. All sleep outcomes were associated with age. Compared to men, women had more N3 sleep and less WASO after adjusting for age. Model-based comparisons between genders at specific ages showed statistically higher mean WASO for men at ages 60 (+13.6 min) and 70 years (+19.5 min) and less N3 for men at ages 50 (-13.2 min), 60 (-19.0 min), and 70 years (-19.5 min) but no differences at 20, 30, 40 or 80 years. The other sleep measures did not differ by gender at any age. Thus, even in the absence of moderate-severe OSA, sleep architecture was associated with age across adulthood, and there were gender differences in WASO and N3 at older ages in this rural community., (© 2024 The Authors. Journal of Sleep Research published by John Wiley & Sons Ltd on behalf of European Sleep Research Society.)

Study Objective: The objective of this study was to examine the association between the timing of dietary macronutrients and sodium intake and sleep quantity and quality., Methods: This was a cross-sectional study that included 34 adults between 21 and 50 years of age. The main outcome measures were objective sleep measures assessed from three nights of wrist actigraphy including sleep duration, fragmentation, and wake after sleep onset (WASO), and one night of polysomnography (PSG), including rapid eye movement (REM) sleep, non-REM stage 2 (N2), stage 3 (N3), and WASO. Multiple linear regression models and linear mixed models were used to estimate the associations between sleep measures and dietary measures (carbohydrates, fats, saturated fats, proteins, and sodium). Dietary timing was examined in two ways: (1) the average amount of each nutrient consumed within 3 hours of sleep start, and (2) the interval between the final intake of each nutrient and sleep., Results: Average fat intake within 3 hours of sleep was associated with greater WASO from PSG ( β  = 4.48, p  = 0.01). No other associations were found between the macronutrients or sodium intake ( p  > 0.05) within 3 hours of sleep and the sleep parameters from PSG or actigraphy. Similarly, no associations were found between any of the PSG or actigraphy sleep measures and the interval between final nutrient intakes and sleep with sleep duration., Conclusions: The study suggests that greater fat but not carbohydrate, protein, saturated fat, or sodium intake close to sleep may be associated with greater sleep disruption; however, no other associations were observed., (© The Author(s) 2024. Published by Oxford University Press on behalf of Sleep Research Society.)

Introduction: Fatigue, brain fog, and sleep disturbance are among the most common symptoms of postacute sequelae of SARS-CoV-2 infection (PASC). We sought to determine the impact of sleep disruption on cognition and quality of life in patients with neurologic manifestations of PASC (Neuro-PASC)., Methods: Thirty-nine patients were recruited from Neuro-COVID-19 clinic. Mean age was 48.1 years, 71.8% were female, and 82% were never hospitalized for COVID-19. Patients were evaluated via clinical assessment, quality-of-life measures in domains of cognitive function, fatigue, sleep disturbance, anxiety, and depression, NIH Toolbox cognitive tests, and 7 days of wrist actigraphy., Results: The median number of neurologic symptoms attributed to PASC was 6, with brain fog being the most common in 89.7%. Regarding non-neurologic symptoms, 94.9% complained of fatigue and 74.4% of insomnia. Patients reported significant impairment in all quality-of-life domains and performed worse in a task of attention compared to a normative US population. Actigraphy showed Neuro-PASC patients had lower sleep efficiency, longer sleep latency (both p  < 0.001), and later sleep midpoint ( p  = 0.039) compared to 71 age-matched healthy controls with no PASC history. Self-reported cognitive symptoms correlated with the severity of fatigue ( p  < 0.001), anxiety ( p  = 0.05), and depression ( p  < 0.01). Objective evidence of sleep disruption measured by wakefulness after sleep onset, sleep efficiency, and latency were associated with decreased performance in attention and processing speed., Conclusion: Prospective studies including larger populations of patients are needed to fully determine the interplay of sleep disruption on the cognitive function and quality of life of patients with PASC., (© The Author(s) 2024. Published by Oxford University Press on behalf of Sleep Research Society.)

Study Objectives: People with diabetes and prediabetes are more likely to have sleep-disordered breathing (SDB), but few studies examined sleep architecture in people with diabetes or prediabetes in the absence of moderate-severe SDB, which was the aim of our cross-sectional study., Methods: This cross-sectional sample is from the Baependi Heart Study, a family-based cohort of adults in Brazil. About 1074 participants underwent at-home polysomnography (PSG). Diabetes was defined as fasting glucose >125 mg/dL or HbA1c > 6.4 mmol/mol or taking diabetic medication, and prediabetes was defined as HbA1c ≥ 5.7 & <6.5 mmol/mol or fasting glucose ≥ 100 & ≤125 mg/dl. We excluded participants with an apnea-hypopnea index (AHI) ≥ 30 in primary analyses and ≥ 15 in secondary analysis. We compared sleep stages among the 3 diabetes groups (prediabetes, diabetes, neither)., Results: Compared to those without diabetes, we found shorter REM duration for participants with diabetes (-6.7 min, 95%CI -13.2, -0.1) and prediabetes (-5.9 min, 95%CI -10.5, -1.3), even after adjusting for age, gender, BMI, and AHI. Diabetes was also associated with lower total sleep time (-13.7 min, 95%CI -26.8, -0.6), longer slow-wave sleep (N3) duration (+7.6 min, 95%CI 0.6, 14.6) and higher N3 percentage (+2.4%, 95%CI 0.6, 4.2), compared to those without diabetes. Results were similar when restricting to AHI < 15., Conclusions: People with diabetes and prediabetes had less REM sleep than people without either condition. People with diabetes also had more N3 sleep. These results suggest that diabetes and prediabetes are associated with differences in sleep architecture, even in the absence of moderate-severe sleep apnea., (© The Author(s) 2023. Published by Oxford University Press on behalf of Sleep Research Society. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Stress and diabetes coexist in a vicious cycle. Different types of stress lead to diabetes, while diabetes itself is a major life stressor. This was the focus of the Chicago Biomedical Consortium's 19 th annual symposium, "Stress and Human Health: Diabetes," in November 2022. There, researchers primarily from the Chicago area met to explore how different sources of stress - from the cells to the community - impact diabetes outcomes. Presenters discussed the consequences of stress arising from mutant proteins, obesity, sleep disturbances, environmental pollutants, COVID-19, and racial and socioeconomic disparities. This symposium showcased the latest diabetes research and highlighted promising new treatment approaches for mitigating stress in diabetes., Competing Interests: RMS declares that he has received honoraria from CVS/Health and the American Medical Forum; neither of which relate this manuscript. SAO is a co-founder, equity holder, and consultant for OptiKIRA, LLC. All other authors have no competing interests to declare., (© The Author(s) 2023.)

Introduction: Cognitive dysfunction, a leading cause of mortality and morbidity in the USA and globally, has been shown to disproportionately affect the socioeconomically disadvantaged and those who identify as black or Hispanic/Latinx. Poor sleep is strongly associated with the development of vascular and metabolic diseases, which correlate with cognitive dysfunction. Therefore, sleep may contribute to observed disparities in cognitive disorders. The Epidemiologic Study of Disparities in Sleep and Cognition in Older Adults (DISCO) is a longitudinal, observational cohort study that focuses on gathering data to better understand racial/ethnic sleep disparities and illuminate the relationship among sleep, race and ethnicity and changes in cognitive function. This investigation may help inform targeted interventions to minimise disparities in cognitive health among ageing adults., Methods and Analysis: The DISCO study will examine up to 495 individuals aged 55 and older at two time points over 24 months. An equal number of black, white and Hispanic/Latinx individuals will be recruited using methods aimed for adults traditionally under-represented in research. Study procedures at each time point will include cognitive tests, gait speed measurement, wrist actigraphy, a type 2 home polysomnography and a clinical examination. Participants will also complete self-identified assessments and questionnaires on cognitive ability, sleep, medication use, quality of life, sociodemographic characteristics, diet, substance use, and psychological and social health., Ethics and Dissemination: This study was approved by the Northwestern University Feinberg School of Medicine Institutional Review Board. Deidentified datasets will be shared via the BioLINCC repository following the completion of the project. Biospecimen samples from the study that are not being analysed can be made available to qualified investigators on review and approval by study investigators. Requests that do not lead to participant burden or that conflict with the primary aims of the study will be reviewed by the study investigators., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Study Objectives: The US Preventive Services Task Force recently released guidelines suggesting little evidence of benefit to screening asymptomatic adults for obstructive sleep apnea (OSA). Our goal was to provide important context to this statement. Specifically, we examined associations between common OSA symptoms, excessive daytime sleepiness and snoring, and OSA severity for different racial/ethnic and sex groups., Methods: Analyses were performed on 2 samples. One combined 2 observational studies that included full polysomnography, the Epworth Sleepiness Scale (ESS), and questions about snoring (mean [standard deviation] age 39 [15.2] years). The second sample was the Multi-Ethnic Study of Atherosclerosis study of older adults (mean [standard deviation] age 69 [9.1] years), which also included polysomnography, ESS and a question about snoring. Apnea-hypopnea index represented OSA severity. For each racial/ethnic-sex group we estimated correlations between apnea-hypopnea index and ESS and the sensitivity and specificity of excessive daytime sleepiness (ESS >10) or frequent snoring to predict moderate-to-severe OSA (apnea-hypopnea index >15 events/h)., Results: A weak significant correlation between OSA severity and ESS was found only in White men in the first sample and Black men in the second sample. Screening tool characteristics for ESS and snoring were poor except for moderate specificity in some racial/ethnic-sex groups., Conclusions: Excessive daytime sleepiness and snoring are commonly used to identify symptomatic patients. Our results suggest that the accuracy of these symptoms to identify OSA varies by race/ethnicity and sex. Therefore, focus on common symptoms as an OSA screen could systematically leave out certain patient populations who would benefit from treatment., Citation: Stepney D, Attarian HP, Knutson KL. Association between severity of obstructive sleep apnea and its common symptoms varies by race, ethnicity, and sex. J Clin Sleep Med . 2023;19(10):1727-1733., (© 2023 American Academy of Sleep Medicine.)

Previous research has demonstrated that experiences of discrimination contribute to racial disparities in sleep, and that psychological distress mediates these relationships. However, previous research has not included race as part of the mediation pathway and has had limited dimensions of sleep health and psychological mediators. In the current study, we examine serial mediation pathways by which race and sleep health are mediated through discrimination and subsequently through psychological distress (i.e., depressive symptoms, chronic stress, and loneliness). Data were from the 2010 wave of the Health Retirement Study (HRS). The analytic sample (n = 7,749) included Black and White participants who were included in the enhanced face-to-face interview in 2010 and who completed the psychosocial questionnaire. Race was reported as either Black or White. Sleep health was assessed with a 4-item questionnaire. Depressive symptoms were assessed with the shortened CES-D, chronic stress via the ongoing chronic stressor scale, and loneliness via the UCLA loneliness scale. Covariates were included in all serial mediation models. Relative to White participants, Black participants reported increased experiences of discrimination, which was associated with increased psychological distress, and poorer sleep health. Findings demonstrate the significant adverse impact that discrimination has on both psychological well-being and sleep health., (© 2022. W. Montague Cobb-NMA Health Institute.)

Previous research has demonstrated that exposure to light preceding and during sleep is associated with poor sleep, but most research to date has utilized either experimental or cross-sectional designs. The current study expands upon prior studies by using a microlongitudinal design that examines the night-to-night associations between light and sleep health in a diverse sample of adults (pre-registered at osf.io/k5zgv). US adults aged 18-87 years from two parent studies (N = 124) wore an actiwatch for up to 10 nights. Light variables estimated from actigraphy include both average exposure and time above light threshold of 10 (TALT 10 ) and 40 (TALT 40 ) lux both during sleep and for the 1-hr preceding sleep. Actigraphy-based sleep variables included sleep offset, duration, percentage and fragmentation index. Higher average light exposure during sleep was associated with a later sleep-offset time, lower sleep percentage and higher fragmentation index (all p < 0.01). More minutes of TALT 10 during sleep was associated with later sleep timing, lower sleep percentage and higher fragmentation index (all p < 0.01), and greater TALT 40 during sleep was associated with lower sleep percentage. Light exposure was not related to sleep duration. In summary, greater light exposure during sleep was related to poorer sleep continuity and later wake time. The lack of association between light and sleep duration may be the result of compensating for sleep disruption by delaying wake time. Multi-level interventions to consistently reduce light levels during sleep should be considered., (© 2022 The Authors. Journal of Sleep Research published by John Wiley & Sons Ltd on behalf of European Sleep Research Society.)

The human circadian system plays a vital role in many physiological processes, and circadian rhythms are found in virtually all tissues and organs. The disruption of circadian rhythms may lead to adverse health outcomes. Evidence from recent population-based studies was reviewed because they represent real-world behavior and can be useful in developing future studies to reduce the risk of adverse health conditions, including cardiovascular diseases, obesity, and diabetes mellitus, which may occur because of circadian disruption. An electronic search in PubMed and Web of Science (2012-2022) was performed. Selected articles were based on specific inclusion and exclusion criteria. Five factors that may disrupt circadian rhythm alignment are discussed: shift work, late chronotype, late sleep timing, sleep irregularity, and late meal timing. Evidence from observational studies of these circadian disruptors suggests potential detrimental effects on cardiometabolic health, including higher BMI/obesity, higher blood pressure, greater dyslipidemia, greater inflammation, and diabetes. Future research should identify the specific underlying pathways in order to mitigate the health consequences of shift work. Furthermore, optimal sleep and mealtimes for metabolic health can be explored in intervention studies. Lastly, it is important that the timing of external environmental cues (such as light) and behaviors that influence circadian rhythms are managed., (© 2023 The Authors. Obesity published by Wiley Periodicals LLC on behalf of The Obesity Society.)

Diabetes is highly prevalent and is associated with dietary behaviors. Time-restricted eating, which consolidates caloric intake to a shortened eating duration, has demonstrated improvement in metabolic health. Timing of eating could also impact metabolism. Our objective was to examine whether the timing of eating was associated with metabolic health independently of eating duration. Data (n = 7619) are from four cycles (2005-2012) of the National Health and Nutrition Examination Survey (NHANES), a nationally representative U.S. survey that included surveys, physical examinations, and dietary recalls. The primary exposures are eating duration and eating start time estimated from two non-consecutive dietary recalls. Primary outcomes were fasting glucose and estimated insulin resistance using the homeostatic model assessment method (HOMA-IR). The mean (95% CI) eating duration was 12.0 h (11.9-12.0) and the mean (95% CI) start time was 8:21 (8:15-8:26). Earlier eating start time was significantly associated with lower fasting glucose and estimated insulin resistance but eating interval duration was not. Every hour later that eating commenced was associated with approximately 0.6% higher glucose level and 3% higher HOMA-IR (both p < 0.001). In this cross-sectional study, earlier eating start time was associated with more favorable metabolic measures, indicating that meal timing is another important characteristic of dietary patterns that may influence metabolism.

Objective: To generate the Chinese Sleep Health Index (SHI-C) in Mandarin with cross-cultural adaptations and test its psychometric properties., Methods: This study used a cross-sectional design. Health science students were included (N = 271) and a sub-set (n = 74) was invited for the re-test. Cross-cultural adaptation of the SHI-C was performed prior to formal validation. The SHI-C, Pittsburgh Sleep Quality Index (PSQI), Insomnia Severity Index (ISI), Bedtime Procrastination Scale, and Sleep Hygiene Index were used to measure variables of interest. Exploratory factor analysis was used to evaluate the structure validity. Bivariate analyses were used to evaluate the construct validity., Results: Exploratory factor analysis identified 3 factors (ie, sleep quality, sleep duration, and disordered sleep) accounting for 55.6% of the total variance. The SHI-C total and sleep quality sub-index scores were significantly associated with both PSQI global score (r = -0.132, p < .05; r = -0.182, p < .01, respectively) and ISI score (r = -0.655, p < .05; r = -0.820, p < .05, respectively). SHI-C total, sleep quality sub-index, and sleep duration sub-index scores were significantly associated with Bedtime Procrastination Scale and Sleep Hygiene Index scores (r = -0.238 to -0.368, p < .05). Students with insomnia (ISI > 9) or poor sleep quality (PSQI > 5) had significantly lower SHI-C scores than those without (73.5 vs. 89.0, p < .01; 84.1 vs. 86.7, p < .05, respectively). SHI-C showed good internal consistency (Cronbach's alpha = 0.73) and test-retest reliability (intraclass correlation coefficient = 0.82)., Conclusions: The SHI-C demonstrated good validity and adequate reliability in a Chinese sample of health science students. It could be used to measure sleep health in future research and practice. Psychometric properties of the SHI-C among other Chinese populations remain to be confirmed., (Copyright © 2022 National Sleep Foundation. Published by Elsevier Inc. All rights reserved.)

Background: In addition to quantity and quality, meal timing and eating duration are additional dietary characteristics that impact cardiometabolic health. Given that cardiometabolic health disparities exist among racial and ethnic groups, we examined whether meal timing and eating duration are additional diet-related differences among racial and ethnic groups. Methods: Participants (n = 13,084) were adults (≥20 years) from the National Health and Nutrition Examination (NHANES, 2011−2018) Survey. Times of first and last meal and the interval between them (eating duration) were derived from two 24-h dietary recalls. Multiple linear regression analyses compared these variables among race and ethnicity after adjusting for potential confounders. Results: Compared to non-Hispanic White adults, the first mealtime was significantly later for Mexican American (23 min), Non-Hispanic Asian (15 min), Non-Hispanic Black (46 min), and Other Hispanic (20 min) and Other Racial (14 min) adults (all p < 0.05). Mexican American and Non-Hispanic Asian adults had a significantly different last mealtime by 13 min earlier and 25 min later, respectively, compared to Non-Hispanic White adults. Compared to Non-Hispanic White adults, the mean eating duration was shorter for other Hispanic (20 min), Mexican American (36 min), and Non-Hispanic Black (49 min) adults. Conclusions: Meal timing and eating duration are additional dietary characteristics that vary significantly among racial and ethnic groups.

Study Objectives: As an antagonist of calcium (Ca), magnesium (Mg) has been implicated in the regulation of sleep. We aimed to examine the longitudinal associations of Mg intake and Ca-to-Mg intake ratio (Ca:Mg) with sleep quality and duration., Methods: The study sample consisted of 3,964 participants from the Coronary Artery Risk Development in Young Adults (CARDIA) study. Dietary and supplementary intake of Mg were obtained using the CARDIA Dietary History at baseline (1985-1986), exam years 7 and 20. Self-reported sleep outcomes were measured at years 15 and 20. Sleep quality was rating from 1 (very good) to 5 (very bad). We categorized sleep duration to <7, 7-9, and >9 h. Generalized estimating equation was used to examine the associations of interest as repeated measures at the two time points., Results: After adjustment for potential confounders, Mg intake was borderline associated with better sleep quality [highest quartile (Q4) vs. intake quartile (Q1): odds ratio (OR) = 1.23; 95% CI = 0.999, 1.50, ptrend = 0.051]. Participants in Q4 were also less likely to have short sleep (<7 h) compared to those in Q1 (OR = 0.64; 95% CI = 0.51, 0.81, ptrend = 0.012). The observed association with short sleep persisted among participants without depressive disorders (Q4 vs. Q1: OR = 0.64; 95% CI = 0.49, 0.82, ptrend < 0.001), but not among individuals with depressive disorder. Ca:Mg was not associated with either outcomes, regardless of depression status., Conclusions: Mg intake was associated with both sleep outcomes in this longitudinal analysis. Randomized controlled trials with objective measures of sleep are warranted to establish the potential causal inference., (© Sleep Research Society 2021. Published by Oxford University Press on behalf of the Sleep Research Society. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Objectives: Prior studies have examined sleep during the coronavirus disease 2019 (COVID-19) pandemic, but have few compared sleep measured both during and prior to COVID. We examined the impact of the COVID-19 pandemic on subjective sleep quality in general and separately by gender and age (<50 vs. ≥50 years). Further, we compared sleep quality between those who did and did not follow quarantine orders., Methods: This sample is from the Baependi Heart Study, a family-based cohort of adults in South-eastern Brazil. Longitudinal data were from 417 individuals who completed the Pittsburgh Sleep Quality Index (PSQI) twice: between January 2010 and September 2014 (pre-COVID) and during the COVID-19 stay-at-home order March-June, 2020. Cross-sectional analysis included 800 participants., Results: Mean (±SD) PSQI scores were significantly higher during than before COVID-19 (5.7 ± 3.8 vs. 5.0 ± 3.3, p < .01). This increase was significant among women and among adults ≥50 years but not in men or younger adults. The significant increase in PSQI was only observed in those who quarantined during COVID-19 (5.9 ±3.7 vs. 5.2 ±3.4, p < .01) and not those who did not quarantine (5.0 ± 3.7 vs. 4.5 ± 3, p = .12). In cross-sectional analyses, individuals who quarantined had higher PSQI scores than nonquarantined individuals (6.1 ± 3.9 vs. 5.0 ± 3.5, p < .01). The quarantine status-dependent differences were significant for women (6.4 ± 4 vs. 5.2 ± 3.7, p < .01) and older adults (6.6 ± 0.1 vs. 5.5 ± 3.3, p = .04). Differences by quarantine status were attenuated after adjusting for age and gender., Conclusions: Subjective sleep quality declined during the COVID-19 pandemic, particularly among women, older adults, and those compliant to quarantine orders., (Copyright © 2021 National Sleep Foundation. Published by Elsevier Inc. All rights reserved.)

Background: The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs)., Methods: The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update. The 2022 Statistical Update is the product of a full year's worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. This year's edition includes data on the monitoring and benefits of cardiovascular health in the population and an enhanced focus on social determinants of health, adverse pregnancy outcomes, vascular contributions to brain health, and the global burden of cardiovascular disease and healthy life expectancy., Results: Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics., Conclusions: The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Non-communicable diseases, including diabetes, are partly responsible for the deceleration of improvements of life expectancy in many countries. Diabetes is also associated with sleep disturbances. Our aim was to determine whether sleep disturbances, particularly in people with diabetes, were associated with increased mortality risk. Data from the UK Biobank were analysed (n = 487,728, mean follow-up time = 8.9 years). The primary exposure was sleep disturbances, assessed through the question: Do you have trouble falling asleep at night or do you wake up in the middle of the night? The primary outcome was mortality. We also dichotomized sleep disturbances into "never/sometimes" versus "usually" (frequently), and combined with the presence/absence of diabetes: 24.2% of participants reported "never/rarely" experiencing sleep disturbances, 47.8% "sometimes" and 28.0% "usually". In age- and sex-adjusted models, frequent sleep disturbances were associated with an increased risk of all-cause mortality (hazard ratio [HR], 1.31; 95% confidence interval [CI], 1.26-1.37), which remained significant in the fully adjusted model (HR 1.13, 95% CI 1.09-1.18). The presence of both diabetes and frequent sleep disturbances was associated with greater risk of all-cause mortality than either condition alone. In the fully adjusted model, the hazard ratio for all-cause mortality was 1.11 (95% CI, 1.07-1.15) for frequent sleep disturbances alone, 1.67 (95% CI, 1.57-1.76) for diabetes alone and 1.87 for both (95% CI, 1.75-2.01). Frequent sleep disturbances (experienced by more than one quarter of the sample) were associated with increased risk of all-cause mortality. Mortality risk was highest in those with both diabetes and frequent sleep disturbances. Complaints of difficulty falling or staying asleep merit attention by physicians., (© 2021 The Authors. Journal of Sleep Research published by John Wiley & Sons Ltd on behalf of European Sleep Research Society.)

Sleep disorders are linked to development of type 2 diabetes and increase the risk of developing diabetes complications. Treating sleep disorders might therefore play an important role in the prevention of diabetes progression. However, the detection and treatment of sleep disorders are not part of standardised care for people with type 2 diabetes. To highlight the importance of sleep disorders in people with type 2 diabetes, we provide a review of the literature on the prevalence of sleep disorders in type 2 diabetes and the association between sleep disorders and health outcomes, such as glycaemic control, microvascular and macrovascular complications, depression, mortality and quality of life. Additionally, we examine the extent to which treating sleep disorders in people with type 2 diabetes improves these health outcomes. We performed a literature search in PubMed from inception until January 2021, using search terms for sleep disorders, type 2 diabetes, prevalence, treatment and health outcomes. Both observational and experimental studies were included in the review. We found that insomnia (39% [95% CI 34, 44]), obstructive sleep apnoea (55-86%) and restless legs syndrome (8-45%) were more prevalent in people with type 2 diabetes, compared with the general population. No studies reported prevalence rates for circadian rhythm sleep-wake disorders, central disorders of hypersomnolence or parasomnias. Additionally, several cross-sectional and prospective studies showed that sleep disorders negatively affect health outcomes in at least one diabetes domain, especially glycaemic control. For example, insomnia is associated with increased HbA 1c levels (2.51 mmol/mol [95% CI 1.1, 4.4]; 0.23% [95% CI 0.1, 0.4]). Finally, randomised controlled trials that investigate the effect of treating sleep disorders in people with type 2 diabetes are scarce, based on a small number of participants and sometimes inconclusive. Conventional therapies such as weight loss, sleep education and cognitive behavioural therapy seem to be effective in improving sleep and health outcomes in people with type 2 diabetes. We conclude that sleep disorders are highly prevalent in people with type 2 diabetes, negatively affecting health outcomes. Since treatment of the sleep disorder could prevent diabetes progression, efforts should be made to diagnose and treat sleep disorders in type 2 diabetes in order to ultimately improve health and therefore quality of life., (© 2021. The Author(s).)

This study aimed to determine which dietary factors were associated with habitual sleep duration in pre/peri- and post-menopausal women. Data from the 2007-2008 National Health and Nutrition Examination Survey were used ( N = 1,783). Habitual sleep duration was categorized as very short (<5 h), short (5-6 h), normal (7-8 h), and long (≥9 h). Diet assessment was performed following validated procedures. In pre/peri-menopausal women ( n = 1,116), controlling for the confounders, fewer number of foods, less intake of protein, carbohydrates, thiamin (B1), food folate, total choline, phosphorus, sodium, potassium, and selenium were significantly associated with a higher risk for very short sleep. Being on a low-salt diet was related to a lower risk for long sleep. In comparison, in post-menopausal women ( n = 667), controlling for the confounders, more sugar intake, less intake of phosphorus and zinc were related to a higher risk for short sleep. There were novel associations between diet and sleep duration, particularly among pre/peri-menopausal women. Future research is needed to confirm those causal relationships.

Circadian disruption is pervasive and can occur at multiple organizational levels, contributing to poor health outcomes at individual and population levels. Evidence points to a bidirectional relationship, in that circadian disruption increases disease severity and many diseases can disrupt circadian rhythms. Importantly, circadian disruption can increase the risk for the expression and development of neurologic, psychiatric, cardiometabolic, and immune disorders. Thus, harnessing the rich findings from preclinical and translational research in circadian biology to enhance health via circadian-based approaches represents a unique opportunity for personalized/precision medicine and overall societal well-being. In this Review, we discuss the implications of circadian disruption for human health using a bench-to-bedside approach. Evidence from preclinical and translational science is applied to a clinical and population-based approach. Given the broad implications of circadian regulation for human health, this Review focuses its discussion on selected examples in neurologic, psychiatric, metabolic, cardiovascular, allergic, and immunologic disorders that highlight the interrelatedness between circadian disruption and human disease and the potential of circadian-based interventions, such as bright light therapy and exogenous melatonin, as well as chronotherapy to improve and/or modify disease outcomes.

Sleep hygiene recommendations discourage eating before bedtime; however, the impact of mealtime on sleep has been inconsistent. We examined gender-stratified associations between eating or drinking <1, <2 and <3 h before bedtime, sleep duration and wake after sleep onset (WASO >30 min). This study utilised 2003-2018 data from the American Time Use Survey, a nationally representative sample of USA residents aged ≥15 years. Participants recorded weekday/weekend activities during a 24-h period. Age-specific sleep duration and WASO were estimated categorically and continuously. Eating or drinking were identified from all activities recorded <1, <2 and <3 h before bedtime. Mean ± se sleep duration was 8·0 ± 0·006 h, and 6% of participants ate or drank <1 h prior to weekdays bedtime. Overall, eating or drinking <1 h prior to bedtime was associated with longer weekdays sleep duration. Women and men who ate or drank <1 h before bedtime, v. those who did not, had 35 min (95% CI (30,39)) and 25 min (95 % CI (21,29)) longer sleep duration, respectively, as well as increased odds of WASO; women (OR=2·03, 95% CI (1·66,2·49)) and men (OR=2·64, 95% CI (2·08,3·36)). As the interval of eating or drinking prior to bedtime expanded, odds of short and long sleep durations and WASO decreased. This population-based data linked eating or drinking <1 h before bedtime to longer sleep duration, but increased WASO. Eating or drinking further from bedtime lowers the odds of short and long sleep duration and WASO. Causal pathways are difficult to discern, though inefficient sleep after late-night eating could increase WASO and trigger compensatory increases in sleep duration.

Study Objectives: The association between obstructive sleep apnea (OSA) and increased cardiometabolic risk (CMR) has been well documented in higher-income countries. However, OSA and its association with CMR have not yet been investigated, based on objective measures, in southern Africa. We measured polysomnography-derived sleep characteristics, OSA prevalence, and its association with cardiometabolic diseases in a rural, low-income, African-ancestry sample of older adult participants in South Africa., Methods: Seventy-five participants completed the study. Body mass index, hypertension, diabetes, dyslipidemia, and HIV status were determined. A continuous CMR score was calculated using waist circumference, random glucose, high-density-lipoprotein cholesterol, triglycerides, and mean arterial blood pressure. Sleep architecture, arousal index, and apnea-hypopnea index for detection of the OSA (apnea-hypopnea index ≥ 15 events/h) were assessed by home-based polysomnography. Associations between CMR score and age, sex, socioeconomic status, apnea-hypopnea index, and total sleep time were investigated by multivariable analysis., Results: In our sample (53 women, age 66.1 ± 10.7 years, 12 HIV+), 60.7% of participants were overweight/obese, 61.3% were hypertensive, and 29.3% had undiagnosed OSA. Being older (P = .02) and having a higher body mass index (P = .02) and higher waist circumference (P < .01) were associated with OSA. Apnea-hypopnea index severity (β = 0.011; P = .01) and being a woman (β = 0.369; P = .01) were independently associated with a higher CMR score in socioeconomic status- and age-adjusted analyses., Conclusions: In this South African community with older adults with obesity and hypertension, OSA prevalence is alarming and associated with CMR. We show the feasibility of detecting OSA in a rural setting using polysomnography. Our results highlight the necessity for actively promoting health education and systematic screening and treatment of OSA in this population to prevent future cardiovascular morbidity, especially among women., (© 2021 American Academy of Sleep Medicine.)

Background: The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs)., Methods: The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update. The 2021 Statistical Update is the product of a full year's worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. This year's edition includes data on the monitoring and benefits of cardiovascular health in the population, an enhanced focus on social determinants of health, adverse pregnancy outcomes, vascular contributions to brain health, the global burden of cardiovascular disease, and further evidence-based approaches to changing behaviors related to cardiovascular disease., Results: Each of the 27 chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics., Conclusions: The Statistical Update represents a critical resource for the lay public, policy makers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Studying communities at different stages of urbanisation and industrialisation can teach us how timing and intensity of light affect the circadian clock under real-life conditions. We have previously described a strong tendency towards morningness in the Baependi Heart Study, located in a small rural town in Brazil. Here, we tested the hypothesis that this morningness tendency is associated with early circadian phase based on objective measurements (as determined by dim light melatonin onset, DLMO, and activity) and light exposure. We also analysed how well the previously collected chronotype questionnaire data were able to predict these DLMO values. The average DLMO observed in 73 participants (40 female) was 20:03 ± 01:21, SD, with an earlier average onset in men (19:38 ± 01:16) than in women (20:24 ± 01:21; P ≤ .01). However, men presented larger phase angle between DLMO and sleep onset time as measured by actigraphy (4.11 hours vs 3.16 hours; P ≤ .01). Correlational analysis indicated associations between light exposure, activity rhythms and DLMO, such that early DLMO was observed in participants with higher exposure to light, higher activity and earlier light exposure. The strongest significant predictor of DLMO was morningness-eveningness questionnaire (MEQ) (beta=-0.35, P ≤ .05), followed by age (beta = -0.47, P ≤ .01). Sex, light exposure and variables derived from the Munich chronotype questionnaire were not significant predictors. Our observations demonstrate that both early sleep patterns and earlier circadian phase have been retained in this small rural town in spite of availability of electrification, in contrast to metropolitan postindustrial areas., (© 2020 The Authors. Journal of Pineal Research published by John Wiley & Sons Ltd.)

Optimism is associated with better health outcomes with hypothesized effects due in part to optimism's association with restorative health processes. Limited work has examined whether optimism is associated with better quality sleep, a major restorative process. We test the hypothesis that greater optimism is associated with more favorable sleep quality and duration. Main analyses included adults aged 32-51 who participated in the Coronary Artery Risk Development in Young Adults ( CARDIA ) study (n = 3,548) during the fifth (Year 15: 2000-2001) and sixth (Year 20: 2005-2006) follow-up visits. Optimism was assessed using the revised Life-Orientation Test. Self-report measures of sleep quality and duration were obtained twice 5 years apart. A subset of CARDIA participants (2003-2005) additionally provided actigraphic data and completed the Pittsburgh Sleep Quality Index ( PSQI ) and Epworth Sleepiness Scale ( ESS ). Multivariate regression analyses were used to examine associations of optimism and sleep indicators. In cross-sectional analyses of 3548 participants, each standard deviation (SD) higher optimism score resulted in 78% higher odds of self-reporting very good sleep quality. Prospectively, a 1-SD higher optimism score was related to higher odds of reporting persistently good sleep quality across 5-years relative to those with persistently poor sleep [OR = 1.31; 95%CI:1.10,1.56]. In participant with supplementary data, each SD higher optimism score was marginally associated with 22% greater odds of favorable sleep quality [OR = 1.22; 95%CI:1.00,1.49] as measured by the PSQI, with possible mediation by depressive symptoms. Optimism was unrelated to objective actigraphic sleep data. Findings support a positive cross-sectional and prospective association between optimism and self-reported sleep behavior.

Background: The American Heart Association, in conjunction with the National Institutes of Health, annually reports on the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs)., Methods: The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update. The 2020 Statistical Update is the product of a full year's worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. This year's edition includes data on the monitoring and benefits of cardiovascular health in the population, metrics to assess and monitor healthy diets, an enhanced focus on social determinants of health, a focus on the global burden of cardiovascular disease, and further evidence-based approaches to changing behaviors, implementation strategies, and implications of the American Heart Association's 2020 Impact Goals., Results: Each of the 26 chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics., Conclusions: The Statistical Update represents a critical resource for the lay public, policy makers, media professionals, clinicians, healthcare administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

In addition to the caloric and macronutrient composition of meals, timing of energy consumption may be important for optimal glucose metabolism. Our goal was to examine whether the habitual timing of energy intake was associated with insulin sensitivity in healthy volunteers. Volunteers without diabetes aged 21-50 years completed a 3-day food diary and underwent an oral glucose tolerance test to estimate insulin sensitivity ( n = 44). From the food diary, we calculated the proportions of the total energy and macronutrients consumed in the morning and evening, and the clock time at which 25%, 50% and 75% of total energy was consumed. A greater proportion of energy intake in the morning was significantly associated with higher insulin sensitivity estimated by Matsuda Index (B = 2.8 per 10%; 95%CI: 0.3, 5.2). The time at which 25% of energy was consumed was associated with insulin sensitivity estimated by Matsuda Index (B = -1.6 per hour; 95%CI: -3.0, -0.3) and QUICKI (B = -1.4 per hour, 95%CI: -2.8, -0.1). The timing of carbohydrate consumption demonstrated similar associations. Greater energy intake earlier in the day was associated with higher insulin sensitivity in individuals without diabetes.

Study Objectives: Although sleep disturbance is common in acutely ill patients during and after a hospitalization, how hospitalization affects sleep in general medicine patients has not been well characterized. We describe how sleep and activity patterns vary during and after hospitalization in a small population of older, predominately African American general medicine patients., Methods: Patients wore a wrist accelerometer during hospitalization and post-discharge to provide objective measurements of sleep duration, efficiency, and physical activity. Random effects linear regression models clustered by subject were used to test associations between sleep and activity parameters across study days from hospitalization through post-discharge., Results: We recorded 404 nights and 384 days from 54 patients. Neither nighttime sleep duration nor sleep efficiency increased from hospitalization through post-discharge (320.2 vs. 320.2 min, p = 0.99; 74.0% vs. 71.7%, p = 0.24). Daytime sleep duration also showed no significant change (26.3 vs. 25.8 min/day, p = 0.5). Daytime physical activity was significantly less in-hospital compared to post-discharge (128.6 vs. 173.2 counts/min, p < 0.01) and increased 23.3 counts/min (95% CI = 16.5 to 30.6, p < 0.01) per hospital day. A study day and post-discharge period interaction was observed demonstrating slowed recovery of activity post-discharge (β 3 = -20.8, 95% CI = -28.8 to -12.8, p < 0.01)., Conclusions: Nighttime sleep duration and efficiency and daytime sleep duration were similar in-hospital and post-discharge. Daytime physical activity, however, was greater post-discharge and increased more rapidly during hospitalization than post-discharge. Interventions, both in hospital and at home, to restore patient sleep and sustain activity improvements may improve patient recovery from illness., (© Sleep Research Society 2019. Published by Oxford University Press on behalf of the Sleep Research Society. All rights reserved. For permissions, please e-mail journals.permissions@oup.com.)

Background: Little is known about the contribution of genetic variation to food timing, and breakfast has been determined to exhibit the most heritable meal timing. As breakfast timing and skipping are not routinely measured in large cohort studies, alternative approaches include analyses of correlated traits., Objectives: The aim of this study was to elucidate breakfast skipping genetic variants through a proxy-phenotype genome-wide association study (GWAS) for breakfast cereal skipping, a commonly assessed correlated trait., Methods: We leveraged the statistical power of the UK Biobank (n = 193,860) to identify genetic variants related to breakfast cereal skipping as a proxy-phenotype for breakfast skipping and applied several in silico approaches to investigate mechanistic functions and links to traits/diseases. Next, we attempted validation of our approach in smaller breakfast skipping GWAS from the TwinUK (n = 2,006) and the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium (n = 11,963)., Results: In the UK Biobank, we identified 6 independent GWAS variants, including those implicated for caffeine (ARID3B/CYP1A1), carbohydrate metabolism (FGF21), schizophrenia (ZNF804A), and encoding enzymes important for N6-methyladenosine RNA transmethylation (METTL4, YWHAB, and YTHDF3), which regulates the pace of the circadian clock. Expression of identified genes was enriched in the cerebellum. Genome-wide correlation analyses indicated positive correlations with anthropometric traits. Through Mendelian randomization (MR), we observed causal links between genetically determined breakfast skipping and higher body mass index, more depressive symptoms, and smoking. In bidirectional MR, we demonstrated a causal link between being an evening person and skipping breakfast, but not vice versa. We observed association of our signals in an independent breakfast skipping GWAS in another British cohort (P = 0.032), TwinUK, but not in a meta-analysis of non-British cohorts from the CHARGE consortium (P = 0.095)., Conclusions: Our proxy-phenotype GWAS identified 6 genetic variants for breakfast skipping, linking clock regulation with food timing and suggesting a possible beneficial role of regular breakfast intake as part of a healthy lifestyle., (Copyright © American Society for Nutrition 2019.)

Introduction: False beliefs about sleep can persist despite contradicting scientific evidence, potentially impairing population health. Identifying commonly held false beliefs lacking an evidence base ("myths") can inform efforts to promote population sleep health., Method: We compiled a list of potential myths using Internet searches of popular press and scientific literature. We used a Delphi process with sleep experts (n = 10) from the fields of sleep medicine and research. Selection and refinement of myths by sleep experts proceeded in 3 phases, including focus groups (Phase 1); email-based feedback to edit, add, or remove myths (Phase 2); and closed-ended questionnaires (Phase 3) where experts rated myths on 2 dimensions, falseness and public health significance, using 5-point Likert scale from 1 ("not at all") to 5 ("extremely false")., Results: The current study identified 20 sleep myths. Mean expert ratings of falseness ranged from 5.00 (SD = 0.00) for the statement "during sleep the brain is not active" to 2.50 (SD = 1.07) for the statement "sleeping in during the weekends is a good way to ensure you get adequate sleep." Mean responses to public health significance ranged from 4.63 (SD = 0.74) for debunking the statement that "many adults need only 5 or less hours of sleep for general health" to 1.71 (SD = 0.49) for the statement that "remembering your dreams is a sign of a good night's sleep.", Conclusion: The current study identified commonly held sleep myths that have a limited or questionable evidence base. Ratings provided by experts suggest areas that may benefit from public health education to correct myths and promote healthy sleep., (Copyright © 2019 National Sleep Foundation. Published by Elsevier Inc. All rights reserved.)

Aim: To test the association between cardiometabolic risk factors and subjective sleep quality assessed by the Pittsburgh sleep quality index (PSQI), independent of obstructive sleep apnea (OSA) and sleep duration., Methods: A total of 573 participants from the Baependi Heart Study, a rural cohort from Brazil, completed sleep questionnaires and underwent polygraphy for OSA evaluation. Multivariable linear regression analysis tested the association between cardiovascular risk factors (outcome variables) and sleep quality measured by PSQI, adjusting for OSA and other potential confounders (age, sex, race, salary/wage, education, marital status, alcohol intake, obesity, smoking, hypertension, and sleep duration)., Results: The sample mean age was 43 ± 16 years, 66% were female, and mean body mass index (BMI) was 26 ± 5 kg/m 2 . Only 20% were classified as obese (BMI ≥30). Overall, 50% of participants reported poor sleep quality as defined by a PSQI score ≥5. A high PSQI score was significantly associated with higher very-low-density lipoprotein (VLDL) cholesterol levels (beta = 0.392, p = 0.012) and higher triglyceride levels (beta = 0.017, p = 0.006), even after adjustments, including the apnea-hypopnea index. Further adjustments accounting for marital status, alcohol intake, and medication use did not change these findings. No significant association was observed between PSQI scores and glucose or blood pressure. According to PSQI components, sleep disturbances (beta = 1.976, p = 0.027), sleep medication use (beta = 1.121, p = 0.019), and daytime dysfunction (beta = 1.290, p = 0.024) were significantly associated with higher VLDL serum levels. Only the daytime dysfunction domain of the PSQI components was significantly associated with higher triglyceride levels (beta = 0.066, p = 0.004)., Conclusion: Poorer lipid profile was independently associated with poor sleep quality, assessed by the PSQI questionnaire, regardless of a normal sleep duration and accounting for OSA and socio-economic status., (Copyright © 2019 Elsevier B.V. All rights reserved.)

We created Sleep for Inpatients: Empowering Staff to Act (SIESTA), which combines electronic "nudges" to forgo nocturnal vitals and medications with interprofessional education on improving patient sleep. In one "SIESTAenhanced unit," nurses received coaching and integrated SIESTA into daily huddles; a standard unit did not. Six months pre- and post-SIESTA, sleep-friendly orders rose in both units (foregoing vital signs: SIESTA unit, 4% to 34%; standard, 3% to 22%, P < .001 both; sleeppromoting VTE prophylaxis: SIESTA, 15% to 42%; standard, 12% to 28%, P < .001 both). In the SIESTAenhanced unit, nighttime room entries dropped by 44% (-6.3 disruptions/room, P < .001), and patients were more likely to report no disruptions for nighttime vital signs (70% vs 41%, P = .05) or medications (84% vs 57%, P = .031) than those in the standard unit. The standard unit was not changed. Although sleep-friendly orders were adopted in both units, a unit-based nursing empowerment approach was associated with fewer nighttime room entries and improved patient experience., (© 2019 Society of Hospital Medicine.)

Later chronotype (i.e. evening preference) and later timing of sleep have been associated with greater morbidity, including higher rates of metabolic dysfunction and cardiovascular disease (CVD). However, no one has examined whether chronotype is associated with mortality risk to date. Our objective was to test the hypothesis that being an evening type is associated with increased mortality in a large cohort study, the UK Biobank. Our analysis included 433 268 adults aged 38-73 at the time of enrolment and an average 6.5-year follow-up. The primary exposure was chronotype, as assessed through a single self-reported question-defining participants as definite morning types, moderate morning types, moderate evening types or definite evening types. The primary outcomes were all-cause mortality and mortality due to CVD. Prevalent disease was also compared among the chronotype groups. Analyses were adjusted for age, sex, ethnicity, smoking, body mass index, sleep duration, socioeconomic status and comorbidities. Greater eveningness, particularly being a definite evening type, was significantly associated with a higher prevalence of all comorbidities. Comparing definite evening type to definite morning type, the associations were strongest for psychological disorders (OR 1.94, 95% CI 1.86-2.02, p = < 0.001), followed by diabetes (OR 1.30, 95% CI 1.24-1.36, p = < 0.001), neurological disorders (OR 1.25, 95% CI 1.20-1.30, p = < 0.001), gastrointestinal/abdominal disorders (OR 1.23, 95% CI 1.19-1.27, p = < 0.001) and respiratory disorders (OR 1.22, 95% CI 1.18-1.26, p = < 0.001). The total number of deaths was 10 534, out of which 2127 were due to CVD. Greater eveningness, based on chronotype as an ordinal variable, was associated with a small increased risk of all-cause mortality (HR 1.02, 95% CI 1.004-1.05, p = 0.017) and CVD mortality (HR 1.04, 95% CI 1.00-1.09, p = 0.06). Compared to definite morning types, definite evening types had significantly increased risk of all-cause mortality (HR 1.10, 95% CI 1.02-1.18, p = 0.012). This first report of increased mortality in evening types is consistent with previous reports of increased levels of cardiometabolic risk factors in this group. Mortality risk in evening types may be due to behavioural, psychological and physiological risk factors, many of which may be attributable to chronic misalignment between internal physiological timing and externally imposed timing of work and social activities. These findings suggest the need for researching possible interventions aimed at either modifying circadian rhythms in individuals or at allowing evening types greater working hour flexibility.

Physiological evidence suggests that sleep modulates kidney function. Our objective was to examine the cross-sectional association between kidney function and objectively-estimated habitual sleep duration, quality and timing in a cohort of patients with mild to moderate chronic kidney disease. This study involved two US clinical centers of the Chronic Renal Insufficiency Cohort (CRIC) study, including 432 participants in a CRIC ancillary sleep study. Habitual sleep duration, quality and timing were measured using wrist actigraphy for 5-7 days. Validated sleep questionnaires assessed subjective sleep quality, daytime sleepiness and risk of sleep apnea. Kidney function was assessed with the estimated glomerular filtration rate using the Chronic Kidney Disease Epidemiology Collaboration equation, and the urinary protein to creatinine ratio. Lower estimated glomerular filtration rate was associated with shorter sleep duration (-1.1 mL min -1  1.73 m -2 per hour less sleep, P = 0.03), greater sleep fragmentation (-2.6 mL min -1  1.73 m -2 per 10% higher fragmentation, P < 0.001) and later timing of sleep (-0.9 mL min -1  1.73 m -2 per hour later, P = 0.05). Higher protein to creatinine ratio was also associated with greater sleep fragmentation (approximately 28% higher per 10% higher fragmentation, P < 0.001). Subjective sleep quality, sleepiness and persistent snoring were not associated with estimated glomerular filtration rate or protein to creatinine ratio. Thus, worse objective sleep quality was associated with lower estimated glomerular filtration rate and higher protein to creatinine ratio. Shorter sleep duration and later sleep timing were also associated with lower estimated glomerular filtration rate. Physicians treating patients with chronic kidney disease should consider inquiring about sleep and possibly sending for clinical sleep assessment. Longitudinal and interventional trials are needed to understand causal direction., (© 2017 European Sleep Research Society.)

Objectives: A validated survey instrument to assess general sleep health would be a useful research tool, particularly when objective measures of sleep are not feasible. Thus, the National Sleep Foundation spearheaded the development of the Sleep Health Index (SHI)., Design: The development of the SHI began with a task force of experts who identified key sleep domains and questions. An initial draft of the survey was created and questions were refined using cognitive testing and pretesting. The resulting 28-question survey was administered via random-sample telephone interviews to nationally representative samples of adults in 2014 (n=1253) and 2015 (n=1250). These data were combined to create the index. A factor analysis linked 14 questions to 3 discrete domains: sleep quality, sleep duration, and disordered sleep. These were assembled as sub-indices, then combined to form the overall SHI, with scores ranging from 0 to 100 (higher score reflects better sleep health)., Results: Americans earned an overall SHI score of 76/100, with sub-index scores of 81/100 in disordered sleep, 79/100 in sleep duration, and 68/100 in sleep quality. In regression analyses, the strongest independent predictors of sleep health were self-reported stress (β=-0.26) and overall health (β=0.26), which were also the strongest predictors of sleep quality (β=-0.32 and β=0.27 respectively)., Conclusions: The current 12-item SHI is a valid, reliable research tool that robustly measures 3 separate but related elements of sleep health-duration, quality, and disorders-and assesses the sleep health status of adults in the United States., (Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.)

The well-established negative health outcomes of sleep deprivation, and the suggestion that availability of electricity may enable later bed times without compensating sleep extension in the morning, have stimulated interest in studying communities whose sleep pattern may resemble a pre-industrial state. Here, we describe sleep and activity in two neighbouring communities, one urban (Milange) and one rural (Tengua), in a region of Mozambique where urbanisation is an ongoing process. The two communities differ in the amount and timing of daily activity and of light exposure, with later bedtimes (≈1 h) associated with more evening and less daytime light exposure seen in the town of Milange. In contrast to previous reports comparing communities with and without electricity, sleep duration did not differ between Milange (7.28 h) and Tengua (7.23 h). Notably, calculated sleep quality was significantly poorer in rural Tengua than in Milange, and poor sleep quality was associated with a number of attributes more characteristic of rural areas, including more intense physical labour and less comfortable sleeping arrangements. Thus, whilst our data support the hypothesis that access to electricity delays sleep timing, the higher sleep quality in the urban population also suggests that some aspects of industrialisation are beneficial to sleep.

In recent years, strong evidence has emerged suggesting that insufficient duration, quality, and/or timing of sleep are associated with cardiovascular disease (CVD), and various mechanisms for this association have been proposed. Such associations may be related to endophenotypic features of the sleep homeostat and the circadian oscillator, or may be state-like effects of the environment. Here, we review recent literature on sleep, circadian rhythms and CVD with a specific emphasis on differences between racial/ethnic groups. We discuss the reported differences, mainly between individuals of European and African descent, in parameters related to sleep (architecture, duration, quality) and circadian rhythms (period length and phase shifting). We further review racial/ethnic differences in cardiovascular disease and its risk factors, and develop the hypothesis that racial/ethnic health disparities may, to a greater or smaller degree, relate to differences in parameters related to sleep and circadian rhythms. When humans left Africa some 100,000 years ago, some genetic differences between different races/ethnicities were acquired. These genetic differences have been proposed as a possible predictor of CVD disparities, but concomitant differences in culture and lifestyle between different groups may equally explain CVD disparities. We discuss the evidence for genetic and environmental causes of these differences in sleep and circadian rhythms, and their usefulness as health intervention targets., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

Objectives: To investigate the association of sleep characteristics with prevalent hypertension, diabetes, and obesity in a multiethnic cohort., Design: This study used a population-based cross-sectional study design., Setting: Participants were recruited between 2009 and 2011 from Chicago, Illinois, and the surrounding suburbs., Participants: Participants were 492 adults aged 35 to 64years who self-reported as white, black, Hispanic, or Asian and who had a low likelihood of sleep apnea based on the apnea screening questionnaires and 1 night of apnea screening using an in-home device (apnea hypopnea index <15 or oxygen desaturation index <10)., Measurements: Participants wore a wrist actigraphy monitor (Actiwatch™) for 7days. During a clinical examination, participants completed questionnaires about sleep, other health behaviors, and medical history and had their blood pressure, anthropometric measures, and fasting blood glucose measured; metabolic risk factors were determined based on standard clinical guidelines., Results: The prevalence of hypertension, obesity, and diabetes was 17.1%, 5.5%, and 35.4%, respectively. Sleep duration was not associated with any cardiovascular risk factor. There was a significantly increased odds for hypertension (odds ratio [OR], 1.05; 95% confidence interval [CI], 1.01-1.08) and obesity (OR, 1.03; 95% CI, 1.00-1.05) associated with higher sleep fragmentation (per 1%). There was also a significantly increased odds for hypertension associated with poorer self-reported sleep quality (OR, 1.14 [95% CI, 1.05-1.24] per 1-unit higher Pittsburgh Sleep Quality Index global score)., Conclusion: Objective and self-reported sleep quality may be more important than duration in relation to prevalent hypertension., (Copyright © 2017 National Sleep Foundation. Published by Elsevier Inc. All rights reserved.)

Study Objectives: Recent studies implicate inadequate sleep duration and quality in metabolic disease. Fewer studies have examined the timing of sleep, which may be important because of its potential impact on circadian rhythms of metabolic function. We examined the association between sleep timing and metabolic risk among Hispanic/Latino adults., Methods: Cross-sectional data from community-based study of 13429 participants aged 18-74 years. People taking diabetic medications were excluded. Sleep timing was determined from self-reported bedtimes and wake times. Chronotype was defined as the midpoint of sleep on weekends adjusted for sleep duration on weekdays. Other measurements included body mass index (BMI), fasting glucose levels, estimated insulin resistance (HOMA-IR), glucose levels 2 hours post oral glucose ingestion, and hemoglobin A1c. Survey linear regression models tested associations between sleep timing and metabolic measures. Analyses were stratified by diabetes status and age-group when significant interactions were observed., Results: Among participants with diabetes, fasting glucose levels were positively associated with bedtime (approximately +3%/hour later, p < .01) and midpoint of sleep (approximately +2%/hour later, p < .05). In participants with and without diabetes combined, HOMA-IR was positively associated with midpoint of sleep (+1.5%/hr later, p < .05), and chronotype (+1.2%/hour later, p < .05). Associations differed by age-group. Among those < 36 years, later sleep timing was associated with lower BMI, lower fasting glucose, and lower HbA1c, but the opposite association was observed among older participants., Conclusions: Later sleep timing was associated with higher estimated insulin resistance across all groups. Some associations between sleep timing and metabolic measures may be age-dependent., (© Sleep Research Society 2017. Published by Oxford University Press on behalf of the Sleep Research Society. All rights reserved. For permissions, please e-mail journals.permissions@oup.com.)

Purpose: Limited data from former National Football League (NFL) players suggest that obstructive sleep apnea (OSA) may be highly prevalent after retirement. It remains unclear whether the high prevalence of OSA in retired players is comparable to nonathletes. This retrospective analysis compared sleep apnea (SA) risk in retired NFL players to a community cohort (CARDIA Sleep study), and examined associations between SA risk and cardiovascular risk factors, including subclinical atherosclerosis., Materials and Methods: Retired NFL players (n=122) were matched to CARDIA Sleep participants by age ±2 years (range 37-55 years), body mass index ±2 kg/m 2 , race, and male sex. Participants underwent electron-beam computed tomography to measure coronary artery calcium (CAC) and completed the Berlin Questionnaire to determine SA risk. The presence of CAC was defined as an Agatston score >0., Results: Retired NFL players had a greater prevalence of high SA risk than the matched CARDIA Sleep participants (27% vs 11.5%, P =0.002). Compared to the CARDIA Sleep participants, retired players were less likely to smoke, and had higher blood pressure, lower fasting glucose levels, and higher cholesterol levels. However, there was no difference in the prevalence of detectable CAC (30% vs 30%, P =1). In both players and the community cohort, SA risk was not significantly associated with CAC after controlling for age, race, and body mass index., Conclusion: Retired NFL players have a greater prevalence of high SA risk but similar prevalence of CAC compared with a well-matched community cohort., Competing Interests: Disclosure The authors report no conflicts of interest in this work.

Objective: To determine whether inpatient sleep duration and efficiency are associated with a greater risk of hyperglycemia in hospitalized patients with and without diabetes., Research Design and Methods: In this retrospective analysis of a prospective cohort study, medical inpatients ≥50 years of age were interviewed, and their charts were reviewed to obtain demographic data and diagnosis. Using World Health Organization criteria, patients were categorized as having normal blood glucose, impaired fasting blood glucose, or hyperglycemia based on morning glucose from the electronic health record. Wrist actigraphy measured sleep. Multivariable ordinal logistic regression models, controlling for subject random effects, tested the association between inpatient sleep duration and proportional odds of hyperglycemia versus impaired fasting blood glucose or impaired fasting blood glucose versus normal blood glucose in hospitalized adults., Results: A total of 212 patients (60% female and 74% African American) were enrolled. Roughly one-third (73, 34%) had diabetes. Objective inpatient sleep measures did not differ between patients with or without diabetes. In ordinal logistic regression models, each additional hour of in-hospital sleep was associated with an 11% (odds ratio 0.89 [95% CI 0.80, 0.99]; P = 0.043) lower proportional odds of a higher glucose category the next morning (hyperglycemia vs. elevated and elevated vs. normal). Every 10% increase in sleep efficiency was associated with an 18% lower proportional odds of a higher glucose category (odds ratio 0.82 [95% CI 0.74, 0.89]; P < 0.001)., Conclusions: Among medical inpatients, both shorter sleep duration and worse sleep efficiency were independently associated with greater proportional odds of hyperglycemia and impaired fasting glucose., (© 2017 by the American Diabetes Association.)