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Objectives: Many sleep-wake behaviors have been associated with cognition. We examined a panel of sleep-wake/activity characteristics to determine which are most robustly related to having low cognitive performance in midlife. Secondarily, we evaluate the predictive utility of sleep-wake measures to screen for low cognitive performance., Methods: The outcome was low cognitive performance defined as being >1 standard deviation below average age/sex/education internally normalized composite cognitive performance levels assessed in the Hispanic Community Health Study/Study of Latinos. Analyses included 1006 individuals who had sufficient sleep-wake measurements about 2years later (mean age=54.9, standard deviation= 5.1; 68.82% female). We evaluated associations of 31 sleep-wake variables with low cognitive performance using separate logistic regressions., Results: In individual models, the strongest sleep-wake correlates of low cognitive performance were measures of weaker and unstable 24-hour rhythms; greater 24-hour fragmentation; longer time-in-bed; and lower rhythm amplitude. One standard deviation worse on these sleep-wake factors was associated with ∼20%-30% greater odds of having low cognitive performance. In an internally cross-validated prediction model, the independent correlates of low cognitive performance were: lower Sleep Regularity Index scores; lower pseudo-F statistics (modellability of 24-hour rhythms); lower activity rhythm amplitude; and greater time in bed. Area under the curve was low/moderate (64%) indicating poor predictive utility., Conclusion: The strongest sleep-wake behavioral correlates of low cognitive performance were measures of longer time-in-bed and irregular/weak rhythms. These sleep-wake assessments were not useful to identify previous low cognitive performance. Given their potential modifiability, experimental trials could test if targeting midlife time-in-bed and/or irregular rhythms influences cognition., (Copyright © 2024 National Sleep Foundation. Published by Elsevier Inc. All rights reserved.)

The time-varying frequency characteristics of many biomedical time series contain important scientific information. However, the high-dimensional nature of the time-varying power spectrum as a surface in time and frequency limits its direct use by applied researchers and clinicians for elucidating complex mechanisms. In this article, we introduce a new approach to time-frequency analysis that decomposes the time-varying power spectrum in to orthogonal rank-one layers in time and frequency to provide a parsimonious representation that illustrates relationships between power at different times and frequencies. The approach can be used in fully nonparametric analyses or in semiparametric analyses that account for exogenous information and time-varying covariates. An estimation procedure is formulated within a penalized reduced-rank regression framework that provides estimates of layers that are interpretable as power localized within time blocks and frequency bands. Empirical properties of the procedure are illustrated in simulation studies and its practical use is demonstrated through an analysis of heart rate variability during sleep., (© 2021 The International Biometric Society.)

Background: Depressive symptoms and sleep disturbances disproportionately affect midlife women. While there may be a bidirectional association, few studies have examined whether depressive symptoms are longitudinally associated with subsequent sleep. Sleep is typically considered unidimensional, despite emerging evidence that multidimensional sleep health provides novel information on the sleep-health link., Purpose: The current study examined whether higher depressive symptoms were longitudinally associated with poorer multidimensional sleep health., Method: Depressive symptoms were assessed with the Center for Epidemiologic Studies Depression Scale across six to nine annual assessments in 302 midlife women from the Study of Women's Health Across the Nation. Six months after their last assessment, actigraphy (mean ± standard deviation = 29.3 ± 6.9 days) and self-report were used to assess sleep health components: efficiency, duration, mid-sleep timing, regularity, alertness, and satisfaction, which were dichotomized and summed to create a composite multidimensional sleep health score. Mixed-effects models were used to evaluate the longitudinal associations between depressive symptoms and multidimensional sleep health, as well as individual sleep health components, adjusting for covariates. Exploratory analyses stratified models by race/ethnicity., Results: Higher depressive symptoms were associated with subsequent poorer multidimensional sleep health (p < .0.001) and lower alertness (p < .0001) and satisfaction with sleep (p < .0001)., Conclusions: Our finding that higher average depressive symptoms were associated longitudinally with actigraphy-measured poorer sleep health in midlife women is novel and converges with the larger body of evidence that these two common symptoms are strongly associated. The bidirectional relationship between these two prevalent symptoms needs to be studied in prospective longitudinal studies., (© Society of Behavioral Medicine 2021. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Objectives: The association between sleep and adiposity (indexed by body mass index or waist-to-hip ratio) has typically been evaluated using a single dimension of self-reported sleep. However, other dimensions and behavioral measures of sleep may also be associated with adiposity. This study evaluated whether multidimensional sleep health calculated from actigraphy and self-report was longitudinally associated with adiposity in a sample of midlife women who have a high prevalence of sleep disturbances and adiposity., Design: Longitudinal study with 11-14 years of follow-up time between the sleep health assessment and body mass index / waist-to-hip ratio measurements., Participants: Two hundred and twenty-one midlife women enrolled in the Study of Women's Health Across the Nation Sleep Study., Measurements: Multidimensional sleep health was quantified using actigraphy (M[SD] = 29.1[7.2] nights) measures of sleep efficiency, midpoint, duration, regularity, and self-report measures of alertness and satisfaction. Each component was dichotomized and summed; higher values indicated better sleep health. Height, body weight, and waist and hip circumference were measured at the sleep study and at follow-up. Linear regression models were used to assess associations between sleep health and adiposity, adjusting for demographic and menopausal covariates., Results: There was no substantial within-person change in adiposity over time. Better sleep health was cross-sectionally and longitudinally associated with lower adiposity in unadjusted, but not in adjusted, models. Individual sleep health components were not associated with adiposity after adjustment., Conclusion: We did not observe cross-sectional or longitudinal associations between multidimensional sleep health and adiposity. The sleep-adiposity link may be weaker in midlife adults than in other age groups., (Copyright © 2020 National Sleep Foundation. Published by Elsevier Inc. All rights reserved.)

Purpose: Physical activity has been associated with several individual dimensions of sleep. However, the association between physical activity and sleep health, a construct that emphasizes the multidimensional nature of sleep, has not been explored. This analysis examined the relationship between physical activity and a composite measure of sleep health., Methods: A total of 114 adults (66% female, 60.3 ± 9.2 years) were included in the analyses. Participants reported daily light-intensity physical activity (LPA) and moderate- and vigorous-intensity physical activity (MVPA) via diary, while wearing a pedometer (Omron HJ-720ITC) to measure daily steps. Sleep health was measured using the RU&#95;SATED questionnaire, which addresses regularity of sleep patterns, satisfaction with sleep, daytime alertness, and sleep timing, efficiency, and duration. Multiple linear regression, binary logistic regression, and analysis of covariance (ANCOVA) were utilized for analyses., Results: Mean sleep health score was 9.6 ± 2.4 (0 [poor]-12 [good]). Participants reported 62.9 ± 66.0 and 51.2 ± 51.2 min/day of LPA and MVPA, respectively, and took 5585.5 ± 2806.7 steps/day. Greater MVPA was associated with better sleep health (β = 0.27, P = 0.005) and sleep health scores differed between those reporting < 30 min/day and ≥ 60 min/day of MVPA (P = 0.004). Greater MVPA was associated with higher odds of having good sleep satisfaction (OR = 1.58 [1.14-2.20], P < 0.01), timing (OR = 2.07 [1.24-3.46], P < 0.01), and duration (OR = 1.48 [1.02-2.18], P = 0.04). Pedometer-based physical activity and LPA were not related to sleep health or its individual dimensions., Conclusions: In middle- to older-aged adults, higher-intensity activity, but not lower-intensity or volume of activity, was associated with greater sleep health. These data suggest that physical activity intensity may be important for sleep health.

Objective: Subjective sleep disturbances have been associated with greater risk for concurrent and incident metabolic syndrome (MetS). Previous studies have not examined prospective associations among polysomnography-assessed sleep and the MetS, despite knowledge that self-reported sleep is subject to reporting bias, and that subjectively and objectively assessed sleep are weakly correlated., Method: In the current study, objectively-assessed (polysomnography) and subjectively-assessed (Pittsburgh Sleep Quality Index, PSQI) sleep was measured in 145 adults at two timepoints, separated by 12-30 years. A continuous measure of the MetS was assessed at the second time point. Statistical analyses were adjusted for age, sex, lifetime history of major depressive disorder, follow-up time, and apnea-hypopnea index., Results: Polysomnography-assessed sleep duration, latency, efficiency, and slow wave sleep were not significantly prospectively associated with the MetS (ps ≥ 0.16). Self-reported longer sleep latency was prospectively associated with higher MetS scores in unadjusted (β = 0.29, p = 0.002) and adjusted models (β = 0.25, p = 0.009). Longer sleep latency was associated with higher fasting glucose levels (β = 0.47, p < 0.001)., Conclusion: Our study provides evidence that subjective and objective measures of sleep may differ in their ability to prospectively predict MetS., (Copyright © 2019. Published by Elsevier B.V.)

Depression is associated with disturbances to sleep and the 24-h sleep-wake pattern (known as the rest-activity rhythm: RAR). However, there remains a need to identify the specific sleep/RAR correlates of depression symptom severity in population subgroups, such as strained dementia caregivers, who are at elevated risk for major depressive disorder. We assessed the cross-sectional associations of sleep/RARs with non-sleep depression symptom severity among 57 (mean age: 74 years, standard deviation: 7.4) strained dementia caregivers who were currently without clinical depression. We derived sleep measures from polysomnography and actigraphy, modelled RARs using a sigmoidally transformed cosine curve and measured non-sleep depression symptom severity using the Hamilton Depression Rating Scale (HRDS) with sleep items removed. The following sleep-wake measures were associated with greater depression symptom severity (absolute Spearman's correlations ranged from 0.23 to 0.32): more time awake after sleep onset (WASO), higher RAR middle level (mesor), relatively shorter active periods (alpha), earlier evening settling time (down-mesor) and less steep RARs (beta). In multivariable analysis, high WASO and low RAR beta were associated independently with depression symptom severity. Predicted non-sleep HDRS means (95% confidence intervals) in caregivers with and without these characteristics were: normal WASO/beta = 3.7 (2.3-5.0), high WASO/normal beta = 5.5 (3.5-7.6), normal WASO/low beta = 6.3 (3.6-8.9) and high WASO/low beta = 8.1 (5.3-10.9). Thus, in our sample of strained caregivers, greater sleep fragmentation (WASO) and less sustained/sharply segregated resting and active periods (low RAR beta) correlate uniquely with depression symptom severity. Longitudinal studies are needed to establish whether these independent sleep-wake correlates of depression symptoms explain heightened depression risk in dementia caregivers., (© 2017 European Sleep Research Society.)

Study Objectives: The mechanisms linking short sleep duration to cardiovascular disease (CVD) are poorly understood. Emerging evidence suggests that endothelial dysregulation may lie along the causal pathway linking sleep duration to cardiovascular risk, although current evidence in humans is based on cross-sectional studies. Our objective was to evaluate the prospective association between objectively assessed sleep duration and clinical indices of endothelial health., Methods: A total of 141 medically healthy adults underwent an overnight laboratory sleep study when they were between the ages of 21 and 60 years. Total sleep time was objectively assessed by polysomnography at study entry. Endothelial health, including brachial artery diameter (BAD) and flow-mediated dilation (FMD), was measured 18.9 ± 4.6 years later. Medical health and psychiatric status were assessed at both time points. Approximately half of the sample had a lifetime history of major depressive disorder., Results: In univariate analyses, shorter sleep duration was associated with increased BAD (β = -0.24, p = .004) and decreased FMD (β = 0.17, p = .042). BAD, but not FMD, remained significantly associated with sleep duration after adjusting for sex, age, body mass index (BMI), smoking, diabetes, hypertension, and lifetime history of major depressive disorder (MDD) at T2. The association between sleep duration and BAD was stronger than the association between BAD and an aggregate measure of CVD risk including three or more of the following risk factors: male sex, age ≥ 65 years, smoker, BMI ≥ 30, diabetes, hypertension, and MDD., Conclusions: Objectively assessed short sleep duration was prospectively associated with increased BAD over a 12- to 30-year period., (© 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.)

Study Objectives: Evaluate whether levels of upsetting life events measured over a 9-y period prospectively predict subjective and objective sleep outcomes in midlife women., Design: Prospective cohort study., Setting: Four sites across the United States., Participants: 330 women (46-57 y of age) enrolled in the Study of Women's Health Across the Nation (SWAN) Sleep Study., Interventions: N/A., Measurements and Results: Upsetting life events were assessed annually for up to 9 y. Trajectory analysis applied to life events data quantitatively identified three distinct chronic stress groups: low stress, moderate stress, and high stress. Sleep was assessed by self-report and in-home polysomnography (PSG) during the ninth year of the study. Multivariate analyses tested the prospective association between chronic stress group and sleep, adjusting for race, baseline sleep complaints, marital status, body mass index, symptoms of depression, and acute life events at the time of the Sleep Study. Women characterized by high chronic stress had lower subjective sleep quality, were more likely to report insomnia, and exhibited increased PSG-assessed wake after sleep onset (WASO) relative to women with low to moderate chronic stress profiles. The effect of chronic stress group on WASO persisted in the subsample of participants without baseline sleep complaints., Conclusions: Chronic stress is prospectively associated with sleep disturbance in midlife women, even after adjusting for acute stressors at the time of the sleep study and other factors known to disrupt sleep. These results are consistent with current models of stress that emphasize the cumulative effect of stressors on health over time., (© 2015 Associated Professional Sleep Societies, LLC.)

No studies have evaluated the dynamic, time-varying relationship between delta electroencephalographic (EEG) sleep and high frequency heart rate variability (HF-HRV) in women. Delta EEG and HF-HRV were measured during sleep in 197 midlife women (M(age)  = 52.1, SD = 2.2). Delta EEG-HF-HRV correlations in nonrapid eye movement (NREM) sleep were modeled as whole-night averages and as continuous functions of time. The whole-night delta EEG-HF-HRV correlation was positive. The strongest correlations were observed during the first NREM sleep period preceding and following peak delta power. Time-varying correlations between delta EEG-HF-HRV were stronger in participants with sleep-disordered breathing and self-reported insomnia compared to healthy controls. The dynamic interplay between sleep and autonomic activity can be modeled across the night to examine within- and between-participant differences including individuals with and without sleep disorders., (Copyright © 2014 Society for Psychophysiological Research.)

Background: Although sleep is often associated with waking health behaviors (WHB) such as alcohol consumption, caffeine use, smoking, and exercise, the causal direction of these relationships is unclear., Purpose: The present study used time series data to examine the temporal dynamics of WHB and sleep characteristics in participants of the Study of Women's Health Across the Nation Sleep Study., Methods: Three hundred three women completed daily assessments of WHB and wore wrist actigraphs to measure sleep characteristics for the duration of the study (mean = 29.42 days, SD = 6.71)., Results: Vector autoregressive modeling revealed that weekly patterns of sleep and WHB best predicted subsequent sleep and WHB suggesting that the associations between WHB and sleep persist beyond their immediate influence. Some WHB predicted some subsequent sleep characteristics, but sleep did not predict subsequent WHB., Conclusions: These novel findings provide insight into the temporal dynamics of 24-h behaviors and encourage consideration of both sleep and WHB in health promotion and behavior change efforts.

Study Objectives: To examine relationships between different physical activity (PA) domains and sleep, and the influence of consistent PA on sleep, in midlife women., Design: Cross-sectional., Setting: Community-based., Participants: 339 women in the Study of Women's Health Across the Nation Sleep Study (52.1 ± 2.1 y)., Interventions: None., Measurements and Results: Sleep was examined using questionnaires, diaries and in-home polysomnography (PSG). PA was assessed in three domains (Active Living, Household/Caregiving, Sports/Exercise) using the Kaiser Physical Activity Survey (KPAS) up to 4 times over 6 years preceding the sleep assessments. The association between recent PA and sleep was evaluated using KPAS scores immediately preceding the sleep assessments. The association between the historical PA pattern and sleep was examined by categorizing PA in each KPAS domain according to its pattern over the 6 years preceding sleep assessments (consistently low, inconsistent/consistently moderate, or consistently high). Greater recent Sports/Exercise activity was associated with better sleep quality (diary "restedness" [P < 0.01]), greater sleep continuity (diary sleep efficiency [SE; P = 0.02]) and depth (higher NREM delta electroencephalographic [EEG] power [P = 0.04], lower NREM beta EEG power [P < 0.05]), and lower odds of insomnia diagnosis (P < 0.05). Consistently high Sports/Exercise activity was also associated with better Pittsburgh Sleep Quality Index scores (P = 0.02) and higher PSG-assessed SE (P < 0.01). Few associations between sleep and Active Living or Household/Caregiving activity (either recent or historical pattern) were noted., Conclusion: Consistently high levels of recreational physical activity, but not lifestyle- or household-related activity, are associated with better sleep in midlife women. Increasing recreational physical activity early in midlife may protect against sleep disturbance in this population.

Study Objectives: Quantify the short-term stability of multiple indices of sleep and nocturnal physiology in good sleeper controls and primary insomnia patients., Design: Intra-class correlation coefficients (ICC) were used to quantify the short-term stability of study outcomes., Setting: Sleep laboratory., Participants: Fifty-four adults with primary insomnia (PI) and 22 good sleeper controls (GSC)., Measurements: Visually scored sleep outcomes included indices of sleep duration, continuity, and architecture. Quantitative EEG outcomes included power in the delta, theta, alpha, sigma, and beta bands during NREM sleep. Power spectral analysis was used to estimate high-frequency heart rate variability (HRV) and the ratio of low- to high-frequency HRV power during NREM and REM sleep., Results: With the exception of percent stage 3+4 sleep; visually scored sleep outcomes did not exhibit short-term stability across study nights. Most QEEG outcomes demonstrated short-term stability in both groups. Although power in the beta band was stable in the PI group (ICC = 0.75), it tended to be less stable in GSCs (ICC = 0.55). Both measures of cardiac autonomic tone exhibited short-term stability in GSCs and PIs during NREM and REM sleep., Conclusions: Most QEEG bandwidths and HRV during sleep show high short-term stability in good sleepers and patients with insomnia alike. One night of data is, thus, sufficient to derive reliable estimates of these outcomes in studies focused on group differences or correlates of QEEG and/or HRV. In contrast, one night of data is unlikely to generate reliable estimates of PSG-assessed sleep duration, continuity or architecture, with the exception of slow wave sleep.