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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.)

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.)

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.)

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.)

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.)

Background: Racial disparities in hypertension prevalence in the United States are established. Given our understanding of racial and ethnic disparities in sleep characteristics and demonstrated associations between sleep characteristics and hypertension, we tested whether sleep characteristics mediated racial disparities in hypertension., Methods: Analyses were performed in the Chicago Area Sleep Study, a population-based cohort study of 154 Blacks, 128 Whites, 103 Hispanics, and 109 Asians without obstructive sleep apnea. Participants underwent 7 days of wrist actigraphy monitoring. Algorithms were used to determine sleep duration and sleep maintenance (the percent of sleep in the sleep period). Hypertension was determined as systolic blood pressure >140mm Hg or diastolic blood pressure >90mm Hg or the use of antihypertensive medications. We estimated sample prevalence ratios for hypertension before and after adjustment for sleep characteristics and also conducted mediation analysis., Results: The sample prevalence of hypertension was highest in Blacks (36%), followed by Hispanics (14%), Asians (8%), and Whites (5%). The sample prevalence ratio for hypertension for Blacks vs. Whites was 5.52 (95% confidence interval (CI): 2.36, 13.23) after adjusting for age, sex, and education. Adjustment for sleep duration had no influence on the effect estimate, but adjustment for sleep maintenance attenuated the sample prevalence ratio to 4.55 (95% CI: 1.91, 11.14). Sleep maintenance mediated 11.4% of the difference in hypertension prevalence between Blacks and Whites in this sample., Conclusions: Sleep maintenance mediated a small but significant portion of the disparity in hypertension between Blacks and Whites. Future research should investigate the mechanisms underlying these findings., (© American Journal of Hypertension, Ltd 2016. All rights reserved. For Permissions, please email: journals.permissions@oup.com)

Study Objectives: Sleep duration has been associated with risk of dementia and stroke, but few studies have investigated the relationship between sleep duration and brain MRI measures, particularly in middle age., Methods: In a prospective cohort of 613 black and white adults (mean age = 45.4 years) enrolled in the Coronary Artery Risk Development in Young Adults (CARDIA) study, participants reported typical sleep duration, dichotomized into moderate sleep duration (> 6 to ≤ 8 h) and short sleep duration (≤ 6 h) at baseline (2005-2006). Five years later, we obtained brain MRI markers of white matter including fractional anisotropy, mean diffusivity, and white matter hyperintensities., Results: Compared to moderate sleepers, short sleepers had an elevated ratio of white matter hyperintensities to normal tissue in the parietal region (OR = 2.31, 95% CI: 1.47, 3.61) adjusted for age, race/sex, education, hypertension, stroke/TIA, depression, smoking status, and physical activity. White matter diffusivity was also higher, approximately a 0.2 standard deviation difference, in frontal, parietal, and temporal white matter regions, among those reporting shorter sleep duration in (P < 0.05 for all)., Conclusions: Short sleep duration was associated with worse markers of white matter integrity in midlife. These mid-life differences in white matter may underlie the link between poor sleep and risk of dementia and stroke., (© 2016 Associated Professional Sleep Societies, LLC.)

The popularity of energy drinks has increased rapidly in the past decade. One of the main reasons people use energy drinks is to counteract effects of insufficient sleep or sleepiness. Risks associated with energy drink use, including those related to sleep loss, may be disproportionately borne by racial minorities and those of lower socioeconomic status. In this review, a brief introduction to the issue of health disparities is provided, population-level disparities and inequalities in sleep are described, and the social-ecological model of sleep and health is presented. Social and demographic patterns of energy drink use are then presented, followed by discussion of the potential ways in which energy drink use may contribute to health disparities, including the following: 1) effects of excessive caffeine in energy drinks, 2) effects of energy drinks as sugar-sweetened beverages, 3) association between energy drinks and risk-taking behaviors when mixed with alcohol, 4) association between energy drink use and short sleep duration, and 5) role of energy drinks in cardiometabolic disease. The review concludes with a research agenda of critical unanswered questions., (© 2014 International Life Sciences Institute.)

Study Objective: Loneliness has been shown to predict poor health. One hypothesized mechanism is that lonely individuals do not sleep as well as individuals who feel more connected to others. Our goal was to test whether loneliness is associated with sleep fragmentation or sleep duration., Design: Cross-sectional study., Setting: Members of a traditional, communal, agrarian society living in South Dakota., Participants: Ninety-five participants (mean age 39.8 years, 55% female) who were ≥ 19 years of age at the study's inception., Interventions: Not applicable., Measurements and Results: We conducted interviews querying loneliness, depression, anxiety, and stress, as well as subjective sleep quality and daytime sleepiness. Study participants wore a wrist actigraph for one week to measure objective sleep properties; the two studied here were sleep fragmentation and sleep duration. Higher loneliness scores were associated with significantly higher levels of sleep fragmentation (β = 0.073, t = 2.55, P = 0.01), controlling for age, sex, body mass index, risk of sleep apnea, and negative affect (a factor comprising symptoms of depression and anxiety, and perceived stress). Loneliness was not associated with sleep duration or with either subjective sleep measure., Conclusions: Loneliness was a significant predictor of sleep fragmentation. Humans' social nature may partly be manifest through our dependence on feeling secure in our social environment to sleep well.

Study Objectives: To determine (1) whether short sleep has increased over 31 years; (2) whether trends in short sleep differed by employment status; (3) which sociodemographic factors predict short sleep; and (4) how short sleepers spend their time., Design: Time diaries from eight national studies conducted between 1975 and 2006., Patients or Participants: U.S. adults > or = 18 years., Measurements and Results: Short sleepers were defined as those reporting < 6 hours of sleep in their time diary. Unadjusted percentages of short sleepers ranged from 7.6% in 1975 to 9.3% in 2006. The 1998-99 study had the highest odds of short sleep. The odds ratio for the 31-year period predicting short sleep was 1.14 (95% CI: 0.92, 1.50, P = 0.22), adjusting for age, sex, education, employment, race, marital status, income, and day of week. When stratified by employment, there was a significant increase for full-time workers (P = 0.05), who represented over 50% of participants in all studies, and a significant decrease for students (P = 0.01), who represented < 5% of participants. The odds of short sleep were lower for women, those > or = 65 years, Asians, Hispanics, and married people. The odds were higher for full-time workers, those with some college education, and African Americans. Short sleepers in all employment categories spent more time on personal activities. Short sleepers who were full- and part-time workers spent much more time working., Conclusions: Based on time diaries, the increase in the odds of short sleep over the past 31 years was significant among full-time workers only. Work hours are much longer for full-time workers sleeping < 6 hours.

Numerous studies have found an association between shorter sleep duration and higher body mass index (BMI) in adults. Most previous studies have been cross-sectional and relied on self-reported sleep duration, which may not be very accurate. In the Coronary Artery Risk Development in Young Adults (CARDIA) Sleep Study (2000-2006), the authors examine whether objectively measured sleep is associated with BMI and change in BMI. They use several nights of wrist actigraphy to measure sleep among participants in an ongoing cohort of middle-aged adults. By use of linear regression, the authors examine whether average sleep duration or fragmentation is associated with BMI and 5-year change in BMI, adjusting for confounders. Among 612 participants, sleep duration averaged 6.1 hours and was grouped into 4 categories. Both shorter sleep and greater fragmentation were strongly associated with higher BMI in unadjusted cross-sectional analysis. After adjustment, BMI decreased by 0.78 kg/m(2) (95% confidence interval: -1.6, -0.002) for each increasing sleep category. The association was very strong in persons who reported snoring and weak in those who did not. There were no longitudinal associations between sleep measurements and change in BMI. The authors confirmed a cross-sectional association between sleep duration and BMI using objective sleep measures, but they did not find that sleep predicted change in BMI. The mechanism underlying the cross-sectional association is not clear.

Sleep is an important modulator of neuroendocrine function and glucose metabolism in children as well as in adults. In recent years, sleep curtailment has become a hallmark of modern society with both children and adults having shorter bedtimes than a few decades ago. This trend for shorter sleep duration has developed over the same time period as the dramatic increase in the prevalence of obesity. There is rapidly accumulating evidence from both laboratory and epidemiological studies to indicate that chronic partial sleep loss may increase the risk of obesity and weight gain. The present article reviews laboratory evidence indicating that sleep curtailment in young adults results in a constellation of metabolic and endocrine alterations, including decreased glucose tolerance, decreased insulin sensitivity, elevated sympathovagal balance, increased evening concentrations of cortisol, increased levels of ghrelin, decreased levels of leptin, and increased hunger and appetite. We also review cross-sectional epidemiological studies associating short sleep with increased body mass index and prospective epidemiological studies that have shown an increased risk of weight gain and obesity in children and young adults who are short sleepers. Altogether, the evidence points to a possible role of decreased sleep duration in the current epidemic of obesity.

Study Objectives: To describe the day-to-day and year-to-year variation in sleep characteristics among early middle-aged adults., Design: Participants wore an Actiwatch (Mini Mitter, Inc) for 3 days on two occasions approximately 1 year apart., Participants: N = 669 participants aged 38-50 years from the Chicago site of the Coronary Artery Risk Development in Young Adults (CARDIA) cohort study., Measurements and Results: Sleep measures included sleep duration, sleep latency, sleep efficiency, and time in bed. For each sleep parameter, total variance was decomposed into between-subject variance, within-subject variance from day to day, and within-subject variance from year to year. The standard deviation was calculated from the variance. Analysis yielded a within-subject daily standard deviation (SD) of 1.26 hours and a within-subject yearly SD of 0.39 hours for sleep duration. Daily SD was 30.7 minutes and yearly SD was 6.3 minutes for within-subject variability of sleep latency. Daily SD was 8.4% and yearly SD was 2.7% for within-subject variability of sleep efficiency. Finally, daily SD was 1.31 hours and yearly SD was 0.52 hours for within-subject variability of time in bed., Conclusions: For each of the 4 sleep characteristics, nightly variability was much greater than yearly variability, meaning sleep behavior changes little in one year in this cohort of early middle-aged adults, despite large daily fluctuations. These results have important methodological implications, including that single-day measures of sleep may not accurately reflect habitual behavior.

Study Objectives: To describe the stability of the Pittsburgh Sleep Quality Index (PSQI) and the Epworth Sleepiness Scale (ESS) scores over 1 year among a population-based sample of black and white early middle-aged adults., Participants: More than 600 participants, aged 38 to 50 years, from the Chicago site of the Coronary Artery Risk Development in Young Adults (CARDIA) Study., Methods: The PSQI and ESS were completed twice, approximately 1 year apart, between 2003 and 2005. Seven PSQI 4-level component scores, a global PSQI score, and the ESS scores were calculated. A PSQI global score greater than 5 was classified as poor quality sleep, and an ESS score greater than 10 was classified as high daytime sleepiness., Results: The mean+/-SD PSQI score was 5.7+/-3.1 in Year 1 and 5.9+/-3.1 in Year 2. The mean ESS score was 7.4+/-4.3 in Year 1 and 7.2+/-4.2 in Year 2. The Pearson correlation coefficient for the PSQI score in both years in the full sample was .68 and ranged from .54 among black men to .72 among black women. The Pearson correlation coefficient for the ESS score in both years in the full sample was .76 and ranged from .70 among black men to .80 among white men. In the full sample, 76% had the same PSQI dichotomous classification, and 85% had the same ESS dichotomous classification in both years., Conclusions: These results suggest that the PSQI and ESS are stable measures of sleep quality and sleepiness over the past year in early middle-aged adults.

Despite mounting evidence that sleep duration is a risk factor across diverse health and functional domains, little is known about the distribution and determinants of sleep. In 2003-2004, the authors used wrist activity monitoring and sleep logs to measure time in bed, sleep latency (time required to fall asleep), sleep duration, and sleep efficiency (percentage of time in bed spent sleeping) over 3 days for 669 participants at one of the four sites of the Coronary Artery Risk Development in Young Adults (CARDIA) study (Chicago, Illinois). Participants were aged 38-50 years, 58% were women, and 44% were Black. For the entire sample, mean time in bed was 7.5 (standard deviation (SD), 1.2) hours, mean sleep latency was 21.9 (SD, 29.0) minutes, mean sleep duration was 6.1 (SD, 1.2) hours, and mean sleep efficiency was 80.9 (SD, 11.3)%. All four parameters varied by race-sex group. Average sleep duration was 6.7 hours for White women, 6.1 hours for White men, 5.9 hours for Black women, and 5.1 hours for Black men. Race-sex differences (p < 0.001) remained after adjustment for socioeconomic, employment, household, and lifestyle factors and for apnea risk. Income was independently associated with sleep latency and efficiency. Sleep duration and quality, which have consequences for health, are strongly associated with race, sex, and socioeconomic status.