Trajectories of Sleep Over Midlife and Incident Cardiovascular Disease Events in the Study of Women's Health Across the Nation.

BACKGROUND: Up to 50% of women report sleep problems in midlife, and cardiovascular disease (CVD) is the leading cause of death in women. How chronic poor sleep exposure over decades of midlife is related to CVD risk in women is poorly understood. We tested whether trajectories of insomnia symptoms or sleep duration over midlife were related to subsequent CVD events among SWAN (Study of Women's Health Across the Nation) participants, whose sleep was assessed up to 16 times over 22 years. METHODS: At baseline, SWAN participants (n=2964) were 42 to 52 years of age, premenopausal or early perimenopausal, not using hormone therapy, and free of CVD. They completed up to 16 visits, including questionnaires assessing insomnia symptoms (trouble falling asleep, waking up several times a night, or waking earlier than planned ≥3 times/week classified as insomnia), typical daily sleep duration, vasomotor symptoms, and depressive symptoms; anthropometric measurements; phlebotomy; and CVD event ascertainment (ie, fatal or nonfatal myocardial infarction, stroke, heart failure, revascularization). Sleep trajectories (ie, insomnia, sleep duration) were determined by means of group-based trajectory modeling. Sleep trajectories were tested in relation to CVD in Cox proportional hazards models (multivariable models: site, age, race and ethnicity, education, CVD risk factors averaged over visits; additional covariates: vasomotor symptoms, snoring, depression). RESULTS: Four trajectories of insomnia symptoms emerged: low insomnia symptoms (n=1142 [39% of women]), moderate insomnia symptoms decreasing over time (n=564 [19%]), low insomnia symptoms increasing over time (n=590 [20%]), and high insomnia symptoms that persisted (n=668 [23%]). Women with persistently high insomnia symptoms had higher CVD risk (hazard ratio, 1.71 [95% CI, 1.19, 2.46], P=0.004, versus low insomnia; multivariable). Three trajectories of sleep duration emerged: persistently short (~5 hours: n=363 [14%]), moderate (~6 hours: n=1394 [55%]), and moderate to long (~8 hours: n=760 [30%]). Women with persistent short sleep had marginally higher CVD risk (hazard ratio, 1.51 [95% CI, 0.98, 2.33], P=0.06, versus moderate; multivariable). Women who had both persistent high insomnia and short sleep had significantly elevated CVD risk (hazard ratio, 1.75 [95% CI, 1.03, 2.98], P=0.04, versus low insomnia and moderate or moderate to long sleep duration; multivariable). Relations of insomnia to CVD persisted when adjusting for vasomotor symptoms, snoring, or depression. CONCLUSIONS: Insomnia symptoms, when persistent over midlife or occurring with short sleep, are associated with higher CVD risk among women.

Study Design and Protocol of the Multisite Pregnancy 24/7 Cohort Study.

Hypertensive disorders of pregnancy and other adverse pregnancy outcomes (APOs) are associated with an increased risk of future maternal cardiovascular disease. Physical activity during pregnancy reduces the risk of these APOs, yet few meet physical activity guidelines during pregnancy. Little is known about the role of sedentary behavior or sleep in APOs, a critical gap in knowledge given these behaviors comprise the majority of a 24-hour day. To address this knowledge gap, the Pregnancy 24/7 cohort study (2020-2025) uses 2 devices for 24-hour activity assessment in each trimester of pregnancy to examine associations of sedentary behavior, sleep, and the 24-hour activity cycle (composition of sedentary behavior, physical activity, and sleep) with hypertensive disorders and other APOs. Participants (n = 500) are recruited from the University of Iowa, University of Pittsburgh, and West Virginia University in early pregnancy and followed through delivery. The activPAL3 micro and Actiwatch Spectrum Plus are worn in each trimester for 7 days of 24-hour wear to assess the 24-hour activity cycle. APOs are abstracted from medical charts. This study will provide critical data to fuel future research examining how modifying the 24-hour activity cycle in pregnancy can improve maternal health.

Isotemporal Associations of Device-Measured Sedentary Time and Physical Activity with Cardiac-Autonomic Regulation in Previously Pregnant Women.

BACKGROUND: High sedentary time (ST) and low physical activity may increase cardiovascular risk, potentially though cardiac-autonomic dysregulation. This study investigated associations of statistically exchanging device-measured ST and physical activity with measures of cardiac-autonomic regulation in previously pregnant women. METHOD: This cross-sectional, secondary analysis included 286 women (age = 32.6 ± 5.7 years; 68% white) measured 7-15 years after delivery. ST and light (LPA), moderate (MPA), vigorous (VPA), and moderate-to-vigorous (MVPA) intensity physical activity were measured by ActiGraph GT3X. ST was further partitioned into long (≥ 30 min) and short (< 30 min) bouts. MVPA was also partitioned into long (≥ 10 min) and short (< 10 min) bouts. Cardiac-autonomic regulation was assessed by heart rate variability (HRV) (resting heart rate, natural log transformed standard deviation of normal R-R intervals [lnSDNN], natural log-transformed root mean square of successive differences [lnRMSSD]) from a 5-min seated ECG. Progressive isotemporal substitution models adjusted for confounders. Sensitivity analyses removed women with related underlying medical conditions and who did not meet respiration rate criteria. RESULTS: Initial analyses found no significant associations with HRV when exchanging 30 min of ST and physical activity (p > 0.05). Yet, replacing long- and short-bout ST with 30 min of long-bout MVPA yielded significantly higher (healthier) lnRMSSD (B = 0.063 ± 0.030 and B = 0.056 ± 0.027, respectively; both p < 0.05). Sensitivity analyses strengthened these associations and yielded further associations of higher lnSDNN and lnRMSSD when replacing 30 min of short-bout MVPA with equivalent amounts of long-bout MVPA (B = 0.074 ± 0.037 and B = 0.091 ± 0.046, respectively). CONCLUSION: Replacing ST with long-bout MVPA is a potential strategy to improve cardiac-autonomic function in previously pregnant women.

Neighborhood Walkability Is Associated with Physical Activity and Prediabetes in a Behavioral Weight Loss Study: a Secondary Analysis.

BACKGROUND: Socio-environmental factors may affect uptake and utility of behavioral interventions targeting weight loss and cardiometabolic health. To evaluate the relation of neighborhood walkability to physical activity (PA) and glucose control in a sample of adults with overweight/obesity participating in a weight loss study. METHODS: Secondary analysis of a 12-month behavioral weight loss intervention (2011-2015) using one-group pretest-posttest design. Neighborhood walkability was assessed via residential Walk Score (0-100) at study entry. Fasting plasma glucose (FPG) via phlebotomy and PA via waist-worn ActiGraph GT3X were assessed at baseline and end of study. Study variables included neighborhood walkability (car-dependent: Walk Score < 50 vs. walkable: Walk Score ≥ 50), prediabetes (FPG 100-125 mg/dL), and recommended PA (moderate to vigorous PA [MVPA] > 22 min/day). Generalized linear model with logit link results were reported as adjusted odds ratios (AOR) with 95% confidence intervals (CI). RESULTS: The sample (N = 114) was mostly female (88.6%), white (83.3%), college educated (73.7%), and on average 51.4 ± 1.0 years of age. At baseline, persons residing in car-dependent neighborhoods tended to have higher income than those in walkable neighborhoods. Neighborhood walkability interacted with household income at study entry to predict participants' ability to meet the MVPA goal at 12 months (AOR = 13.52, 95% CI: 1.86-119.20). Those from walkable neighborhoods had 67% lower odds of having prediabetes compared to those from car-dependent neighborhoods (AOR = 0.33, 95% CI: 0.10-0.87) at 12 months. CONCLUSION: Our findings corroborate previous research characterizing the relationship between neighborhood walkability, PA, and prediabetes status. Key drivers of this impact warrant further investigation in a study with a larger, more diverse sample.

Examining reactivity to intensive longitudinal ecological momentary assessment: 12-month prospective study.

PURPOSE: To examine the association between intensive, longitudinal ecological momentary assessment (EMA) and self-reported eating behaviors. METHODS: Secondary analysis of the EMPOWER study-a 12-month observational study that examined the microprocesses of relapse following intentional weight loss using smartphone-administered EMA-was conducted. Participants were asked to complete four types of EMA surveys using a mobile app. For this analysis, only the number of completed random EMA surveys was used. Using linear mixed-effects modeling, we analyzed whether the number of completed random EMA surveys was associated with changes in self-reported dietary restraint, dietary disinhibition, and susceptibility to hunger measured using the Three-Factor Eating Questionnaire (TFEQ). RESULTS: During the 12-month study, 132 participants completed a mean of 1062 random EMA surveys (range: 673-1362). The median time it took for participants to complete random EMA surveys was 20 s and 90% of random EMA surveys were completed within 46 s. The number of completed random EMA surveys was not significantly associated with the TFEQ scores. CONCLUSIONS: Intensive longitudinal EMA did not influence self-reported eating behaviors. The findings suggest that EMA can be used to frequently assess real-world eating behaviors with minimal concern about assessment reactivity. Nonetheless, care must be taken when designing EMA surveys-particularly when using self-reported outcome measures. LEVEL OF EVIDENCE: Level III, prospective observational study.

Cardiovascular responses to physical activity during work and leisure.

OBJECTIVES: Recent evidence suggests that occupational physical activity (OPA) is associated with adverse cardiovascular health, whereas leisure time physical activity is protective. This study explored explanatory physiological mechanisms. METHODS: Nineteen males (68% white, age=46.6±7.9 years, body mass index=27.9±5.1 kg/m2) with high self-reported OPA wore activity (ActiGraph and activPAL) and heart rate (HR) monitors for 7 days and an ambulatory blood pressure (BP) monitor on one workday and one non-workday. Mixed effects models compared cardiovascular variables (24-hour, nocturnal, waking and non-work time HR and BP) and nocturnal HR variability (HRV) on workdays versus non-workdays. Additional models examined associations of daily activity (steps, light physical activity (LPA) and moderate-to-vigorous physical activity (MVPA)) with cardiovascular variables. Workday by daily activity interactions were examined. RESULTS: 24-hour and waking HR and diastolic BP as well as non-work diastolic BP were significantly higher on workdays versus non-workdays (p<0.05 for all). However, no difference in systolic BP or nocturnal HR or BP was observed between work and non-workdays (p>0.05 for all). Low-frequency and high-frequency power indices of nocturnal HRV were lower on workdays (p<0.05 for both). Daily steps and LPA were positively associated with 24-hour and waking HR on work and non-workdays. Significant interactions suggested MVPA increases HR and lowers nocturnal HRV during workdays, with the opposite effect on non-workdays. CONCLUSIONS: Cardiovascular load was higher on workdays versus non-workdays with no compensatory hypotensive response following workdays. Daily MVPA may differentially affect ambulatory cardiovascular load and nocturnal HRV on workdays versus non-workdays, supporting the physical activity health paradox hypothesis.

Sleep health mediates the relationship between physical activity and depression symptoms.

PURPOSE: This study aimed to investigate cross-sectional associations between physical activity, sleep health, and depression symptoms using mediation models. METHODS: Participants (N = 1576, MAge = 39.3 years, 40% female) were recruited online from Amazon's Mechanical Turk crowd-sourcing service. Physical activity was measured using a single-item self-report measure and depression symptoms were reported using the Hospital Anxiety and Depression Scale. Sleep health was measured using the 6-question RUSATED Sleep Health survey V2.0. RESULTS: Good sleep health (direct effect: ß = - .273, t = - 13.87, p < .0001) and high levels of physical activity (direct effect: ß = - .092, t = - 4.73, p < .0001) were both individually associated with fewer depression symptoms. Sleep health significantly mediated 19% of the association between physical activity and depression symptoms (indirect effect: ß = - .022, 95% CI [- .036 to - .008]), while physical activity significantly mediated 3% of the relationship between sleep health and depression symptoms (indirect effect: ß = - .008, 95% CI [- .014 to - .003]). CONCLUSION: Physical activity and sleep health act as predictors and mediators of depression symptoms.

Nightly Variation in Sleep Influences Self-efficacy for Adhering to a Healthy Lifestyle: A Prospective Study.

BACKGROUND: Self-efficacy, or the perceived capability to engage in a behavior, has been shown to play an important role in adhering to weight loss treatment. Given that adherence is extremely important for successful weight loss outcomes and that sleep and self-efficacy are modifiable factors in this relationship, we examined the association between sleep and self-efficacy for adhering to the daily plan. Investigators examined whether various dimensions of sleep were associated with self-efficacy for adhering to the daily recommended lifestyle plan among participants (N = 150) in a 12-month weight loss study. METHOD: This study was a secondary analysis of data from a 12-month prospective observational study that included a standard behavioral weight loss intervention. Daily assessments at the beginning of day (BOD) of self-efficacy and the previous night's sleep were collected in real-time using ecological momentary assessment. RESULTS: The analysis included 44,613 BOD assessments. On average, participants reported sleeping for 6.93 ± 1.28 h, reported 1.56 ± 3.54 awakenings, and gave low ratings for trouble sleeping (3.11 ± 2.58; 0: no trouble; 10: a lot of trouble) and mid-high ratings for sleep quality (6.45 ± 2.09; 0: poor; 10: excellent). Participants woke up feeling tired 41.7% of the time. Using linear mixed effects modeling, a better rating in each sleep dimension was associated with higher self-efficacy the following day (all p values < .001). CONCLUSION: Our findings supported the hypothesis that better sleep would be associated with higher levels of reported self-efficacy for adhering to the healthy lifestyle plan.

The association between sleep health and weight change during a 12-month behavioral weight loss intervention.

BACKGROUND: Prior research on the relationship between sleep and attempted weight loss failed to recognize the multidimensional nature of sleep. We examined the relationship between a composite measure of sleep health and change in weight and body composition among adults in a weight loss intervention. METHODS: Adults (N = 125) with overweight or obesity (50.3 ± 10.6 years, 91% female, 81% white) participated in a 12-month behavioral weight loss intervention, with assessments of sleep, weight, fat mass, and fat-free mass at baseline, 6 months, and 12 months. Six sleep dimensions (regularity, satisfaction, alertness, timing, efficiency, and duration) were categorized as "good" or "poor" using questionnaires and actigraphy. A composite score was calculated by summing the number of "good" dimensions. Obstructive sleep apnea (OSA) was assessed in a subsample (n = 117), using the apnea-hypopnea index (AHI) to determine OSA severity. Linear mixed modeling was used to examine the relationships between sleep health and outcomes of percent weight, fat mass, or fat-free mass change during the subsequent 6-month interval, adjusting for age, sex, bed partner, and race; an additional model adjusted for AHI. RESULTS: Mean baseline and 6-month sleep health was 4.5 ± 1.1 and 4.5 ± 1.2, respectively. Mean weight, fat mass, and fat-free mass changes from 0 to 6 months were -9.3 ± 6.1%, -16.9 ± 13.5%, and -3.4 ± 3.4%, respectively, and 0.4 ± 4.8%, -0.3 ± 10.3%, and 0.7 ± 4.1% from 6 to 12 months. Better sleep health was associated with greater subsequent weight loss (P = 0.016) and fat loss (P = 0.006), but not fat-free mass loss (P = 0.232). Following AHI adjustment, the association between sleep health and weight loss was attenuated (P = 0.102) but remained significant with fat loss (P = 0.040). Regularity, satisfaction, timing, and efficiency were each associated with weight and/or fat loss (P ≤ 0.041). CONCLUSIONS: Better sleep health was associated with greater weight and fat loss, with associations attenuated after accounting for OSA severity. Future studies should explore whether improving sleep health, OSA, or the combination improves weight loss.

Longitudinal Association Between Depressive Symptoms and Multidimensional Sleep Health: The SWAN Sleep Study.

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.

Vicarious Experience in Multi-Ethnic Study of Atherosclerosis (MESA) Is Associated with Greater Odds of Attaining the Recommended Leisure-Time Physical Activity Levels.

BACKGROUND: Social cognitive theory posits that observing similar others succeed (i.e., vicarious experience) can improve self-efficacy. However, there are very limited data on the utility of vicarious experience in promoting physical activity (PA). This analysis examined the association between vicarious experience and leisure-time PA (LTPA) in the Multi-Ethnic Study of Atherosclerosis (MESA). METHODS: Cross-sectional analysis of MESA participants who completed exam 5. LTPA and neighborhood factors were self-reported. Neighborhood factors were converted into aesthetic, walking, and safety scores. Group comparative analyses evaluated differences in variables of interest. The relationship between vicarious experience and recommended LTPA (≥ 7.5 MET-h/week) was assessed via logistic regression. Adjusted odds ratios (ORs) with 95% confidence intervals (CIs) are reported. RESULTS: Participants (N = 4579) were older (69.7 ± 9.4 years), 53% female, 41% Caucasian, 26% Black, 21% Hispanic, and 12% Chinese. Those who reported vicarious experience had 45% (95% CI 1.16-1.81) greater odds of attaining recommended LTPA. Unfavorable walking score was associated with lower odds of attaining recommended LTPA (OR = 0.89, 95% CI 0.79-1.00). The aesthetic and safety scales were not associated with LTPA (OR = 1.00 [95% CI 0.89-1.13] and OR = 0.91 [95% CI 0.82-1.10], respectively). CONCLUSIONS: Programs exposing community-dwelling adults to peers engaging in PA could provide an effective public health approach to increase community-level PA participation.

The association between physical activity and a composite measure of sleep health.

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_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 (ß = 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.

Field-based Measurement of Sleep: Agreement between Six Commercial Activity Monitors and a Validated Accelerometer.

OBJECTIVE: To examine agreement between multiple commercial activity monitors (CAMs) and a validated actigraph to measure sleep. METHODS: Thirty adults without sleep disorders wore an Actiwatch Spectrum (AW) and alternated wearing 6 CAMs for one 24-h period each (Fitbit Alta, Jawbone Up3, Misfit Shine 2, Polar A360, Samsung Gear Fit2, Xiaomi Mi Band 2). Total sleep time (TST) and wake after sleep onset (WASO) were compared between edited AW and unedited CAM outputs. Comparisons between AW and CAM data were made via paired t-tests, mean absolute percent error (MAPE) calculations, and intra-class correlations (ICC). Intra-model reliability was performed in 10 participants who wore a pair of each AW and CAM model. RESULTS: Fitbit, Jawbone, Misfit, and Xiaomi overestimated TST relative to AW (53.7-80.4 min, P ≤ .001). WASO was underestimated by Fitbit, Misfit, Samsung and Xiaomi devices (15.0-27.9 min; P ≤ .004) and overestimated by Polar (27.7 min, P ≤ .001). MAPEs ranged from 5.1% (Samsung) to 25.4% (Misfit) for TST and from 36.6% (Fitbit) to 165.1% (Polar) for WASO. TST ICCs ranged from .00 (Polar) to .92 (Samsung), while WASO ICCs ranged from .38 (Misfit) to .69 (Samsung). Differences were similar between poor sleepers (Pittsburgh Sleep Quality Index global score >5; n = 10) and good sleepers. Intra-model reliability analyses revealed minimal between-pair differences and high ICCs. CONCLUSIONS: Agreement between CAMs and AW varied by device, with greater agreement observed for TST than WASO. While reliable, variability in agreement across CAMs with traditional actigraphy may complicate the interpretation of CAM data obtained for clinical or research purposes.

The effect of moderate-intensity exercise on nightly variability in objectively measured sleep parameters among older women.

Objective/Background: Exercise training has been demonstrated to beneficially influence mean-level measures of sleep; however, few studies have examined the impact of an exercise intervention on night-to-night variability in sleep. This study investigated whether four months of moderate-intensity exercise impacted night-to-night variability in sleep among older women. Methods: Participants (n = 49) were randomized to one of two moderate-intensity walking programs with different doses of energy expenditure: low-dose (n = 23: 8 kcal/kg of body weight per week) or high-dose (n = 26: 14 kcal/kg of body weight per week). Sleep parameters were assessed objectively via actigraphy at baseline, mid- (2 months), and postintervention (4 months). Nightly variability in each of the sleep parameters was calculated using the seven-day standard deviation (SD) and a coefficient of variation (SD/mean x 100%). Cardiorespiratory fitness (VO2peak) was measured at baseline and postintervention using a graded treadmill test. Results: Both measures of nightly variability demonstrated a borderline to significantly lower amount of night-to-night variability in wake time after sleep onset (WASO) and number of awakenings at postintervention in comparison to baseline (p ≤ 0.05). Higher VO2peak levels at baseline were associated with less time in bed and lower total sleep time variability throughout the exercise intervention (p < 0.05). Conclusion: Overall, participation in moderate-intensity exercise was observed to reduce the amount of nightly variability for WASO and number of awakenings over time in older women.

Wake up call for collegiate athlete sleep: narrative review and consensus recommendations from the NCAA Interassociation Task Force on Sleep and Wellness.

Sleep is an important determinant of collegiate athlete health, well-being and performance. However, collegiate athlete social and physical environments are often not conducive to obtaining restorative sleep. Traditionally, sleep has not been a primary focus of collegiate athletic training and is neglected due to competing academic, athletic and social demands. Collegiate athletics departments are well positioned to facilitate better sleep culture for their athletes. Recognising the lack of evidence-based or consensus-based guidelines for sleep management and restorative sleep for collegiate athletes, the National Collegiate Athletic Association hosted a sleep summit in 2017. Members of the Interassociation Task Force on Sleep and Wellness reviewed current data related to collegiate athlete sleep and aimed to develop consensus recommendations on sleep management and restorative sleep using the Delphi method. In this paper, we provide a narrative review of four topics central to collegiate athlete sleep: (1) sleep patterns and disorders among collegiate athletes; (2) sleep and optimal functioning among athletes; (3) screening, tracking and assessment of athlete sleep; and (4) interventions to improve sleep. We also present five consensus recommendations for colleges to improve their athletes' sleep.

The Effect of Structured Exercise on Sleep During the Corresponding Night Among Older Women in an Exercise Program.

This study investigated the acute effect of exercise on sleep outcomes among healthy older women by comparing days with structured exercise versus days without structured exercise during 4 months of exercise training. Participants (n = 51) in this study had wrist-worn actigraphic sleep data available following at least 3 days with structured exercise and 3 days without structured exercise at mid-intervention and at the end of intervention. The exercise intervention was treadmill walking. Multilevel models were used to examine whether structured exercise impacted sleep outcomes during the corresponding night. Overall, 1,362 nights of data were included in the analyses. In unadjusted and adjusted models, bedtimes were significantly earlier on evenings following an acute bout of structured exercise than on evenings without structured exercise. No other sleep parameters differed between exercise and nonexercise days. Understanding the effects of exercise on sleep in this understudied population may help to improve their overall sleep quality.

Cardiovascular Stress Reactivity and Carotid Intima-Media Thickness: The Buffering Role of Slow-Wave Sleep.

OBJECTIVE: Exaggerated cardiovascular reactivity to acute psychological stress has been associated with increased carotid intima-media thickness (IMT). However, interstudy variability in this relationship suggests the presence of moderating factors. The current study aimed to test the hypothesis that poor nocturnal sleep, defined as short total sleep time or low slow-wave sleep, would moderate the relationship between cardiovascular reactivity and IMT. METHODS: Participants (N = 99, 65.7% female, age = 59.3 ± 9.3 years) completed a two-night laboratory sleep study and cardiovascular examination where sleep and IMT were measured. The multisource interference task was used to induce acute psychological stress, while systolic and diastolic blood pressure and heart rate were monitored. Moderation was tested using the PROCESS framework in SPSS. RESULTS: Slow-wave sleep significantly moderated the relationship between all cardiovascular stress reactivity variables and IMT (all pinteraction ≤ .048, all ΔRinteraction ≥ .027). Greater stress reactivity was associated with higher IMT values in the low slow-wave sleep group and lower IMT values in the high slow-wave sleep group. No moderating effects of total sleep time were observed. CONCLUSIONS: The results provide evidence that nocturnal slow-wave sleep moderates the relationship between cardiovascular stress reactivity and IMT and may buffer the effect of daytime stress-related disease processes.

When does sedentary behavior become sleep? A proposed framework for classifying activity during sleep-wake transitions.

The Sedentary Behavior Research Network recently published a consensus definition for sedentary behavior as 'any waking behavior characterized by an energy expenditure ≤1.5 metabolic equivalents, while in a sitting, reclining, or lying posture.' While this is a great step toward theoretical and methodological unity, further clarity around issues of classifying sedentary behavior while in bed is needed, specifically during sleep-wake transitions. A thigh-worn inclinometer with a 24-h wear protocol is recommended for best practice assessment of sedentary behavior, but this method introduces challenges for activity classification and data reduction. The constant stream of data collection does not distinguish waking sedentary activities in bed, e.g., watching television or reading, from sleep. Moreover, correct classification during sleep-wake transitions is not well established. Sleep-related behaviors can include time spent trying to fall asleep (sleep onset latency), night awakenings while attempting to fall back asleep (wakefulness after sleep onset), and unsuccessful attempts to fall back asleep in the morning (wakefulness after sleep offset). While these behaviors technically fit into the current definition of sedentary behavior, sleep-related behaviors belong in the sleep domain, are a normal part of the sleep-wake cycle, and are not likely an intervention target for sedentary behavior reduction. For these reasons, we argue that sleep-related behaviors should not be classified as sedentary. The research implications of using this framework for classifying sedentary behavior via 24-h thigh inclinometers include that diaries must ask participants to report the time they got into bed, began attempting to fall asleep ('lights out'), woke up for the day, and got out of bed for the day. Using these diaries, researchers must manually extract the relevant period of wakefulness (and remove sleep-related and sleep time). The importance of this more burdensome protocol for researchers and participants, and across various subject populations, should be evaluated in future research.

Exercise during early pregnancy is associated with greater sleep continuity.

OBJECTIVES/BACKGROUND: Pregnant women report disturbed sleep beginning in early pregnancy. Among nonpregnant populations, exercise has been associated with improved sleep; however, research in pregnant samples has been equivocal. We examined whether varying degrees of exercise were associated with better nocturnal sleep among pregnant women during early gestation. PARTICIPANTS: 172 pregnant women. METHODS: Self-reported sleep and exercise and objective sleep were collected during early gestation: T1 (10-12 weeks), T2 (14-16 weeks), and T3 (18-20 weeks) from 172 pregnant women. Exercise was categorized into three time-varying groups: 0 metabolic equivalent minutes per week (MET-min/week), 1 to < 500 MET-min/week, or ≥ 500 MET-min/week. Linear mixed-effects models were employed to test hypotheses. RESULTS: A significant main effect for Time (F[2,254] = 9.77, p < 0.0001) and Time*Exercise group interaction were observed for actigraphic sleep efficiency (aSE) (F[4,569] = 2.73, p = 0.0285). At T2, women who reported ≥ 500 MET-min/week had higher aSE than those who reported 0 MET-min/week. Significant main effects for Exercise Group and Time were observed for actigraphic wake after sleep onset (aWASO; F[2,694] = 3.04, p = 0.0483 and F[2,260] = 3.21, p = 0.0419). aWASO was lowest for those reporting 1 to < 500 MET-min/week (t[701] = 2.35, adjusted p = .0489) and aWASO decreased from T1 to T3 (t[258] = 2.53, adjusted p value = 0.036). Lastly, there was a main effect for Time for the PSQI (F[2,689] = 52.11, p < 0.0001), indicating that sleep quality improved over time. CONCLUSIONS: Some level of exercise among pregnant women appears to be more advantageous than no exercise at all. Moderate exercise, while still unclearly defined, may be a worthwhile adjunct treatment to combat sleep disturbances during pregnancy.

Sleep quality moderates the association between physical activity frequency and feelings of energy and fatigue in adolescents.

Physical activity (PA) can improve sleep quality, low energy, and fatigue. Though poor sleep quality may induce feelings of low energy and fatigue, the potential moderating effect of sleep quality on associations between PA and feelings of energy and fatigue among adolescents is unknown. Thus, this study examined the moderating effect of sleep quality on associations between PA frequency and feelings of energy and fatigue among adolescents in Ireland. Adolescents (N = 481; 281 males, 200 females) aged 15.1 ± 1.7 years self-reported PA frequency, feelings of energy and fatigue, and sleep quality (September to December 2015). Two-way ANCOVAs examined variation in feelings of energy and fatigue according to the interaction of PA and sleep quality. Standardized mean difference (d) quantified the magnitude of differences. Poor sleepers with low PA reported greater feelings of fatigue compared to normal sleepers with low PA (d = 1.02; 95% CI 0.60, 1.44), and poor sleepers with moderate PA reported greater feelings of fatigue compared to normal sleepers with moderate PA (d = 0.50; 0.17, 0.82). Poor sleepers with low PA reported greater feelings of fatigue compared to both poor sleepers with moderate PA (d = 0.44; 0.05, 0.83) and poor sleepers with high PA (d = 0.87; 0.46, 1.28). Poor sleepers with moderate PA reported greater feelings of fatigue compared to poor sleepers with high PA (d = 0.52; 0.14, 0.91). Poor sleep did not moderate the association between PA and feelings of energy. Sleep quality moderates the association between PA frequency and feelings of fatigue. Fatigue symptoms improve as PA frequency increases among adolescents with poor sleep quality.