The effects of social jetlag and sleep variability on sleepiness in a population-based study: The mediating role of sleep debt.

Sleepiness is a multicausal condition, and previous research has highlighted associations between this symptom and the circadian timing system, specifically concerning social jetlag and sleep variability. Recent inquiries have shown that the effects of social jetlag on sleepiness can be confounded with the consequences of sleep debt. In light of the current evidence, we aimed to assess the effects of social jetlag and sleep variability on sleepiness and the potential mediating role of sleep debt. We used data from the EPISONO study, a cross-sectional population-based study with a sample size of 1042 participants, representative of the city of Sao Paulo, Brazil. Participants completed the UNIFESP Sleep Questionnaire (self-reported bedtime and get-up time) and the Epworth Sleepiness Scale (subjective daytime sleepiness). Subsequently, sleep-corrected mid-sleep time (chronotype), total sleep time, social jetlag (absolute difference between the mid-sleep time on workdays and mid-sleep time on free days), sleep variability (standard deviation of mid-sleep time), and sleep debt (difference between total sleep time on workdays and free days) were calculated. Generalised linear models were used to test whether social jetlag and sleep variability affected sleepiness. Mediation models were used to determine if any observed significant effects were mediated by sleep debt. The prevalence of social jetlag was 23% for >1 h and 12% for >2 h. The mean sleep variability was 41 ± 30 min. Social jetlag had a significant effect on the Epworth Sleepiness Scale scores. This association was no longer statistically significant after controlling for age, sex, body mass index, work schedule, and chronotype. A significant indirect effect of social jetlag on sleep debt and subsequently on the Epworth Sleepiness Scale scores was found. No effect of sleep variability on sleepiness could be identified. In conclusion, the association between social jetlag and sleepiness was mediated by sleep debt but was not independent of demographic, work, and chronotype variables. This study provides new evidence on the importance of circadian misalignment and sleep debt for sleep health on a population level.

The Ecology of Human Sleep (EcoSleep) Cohort Study: Protocol for a longitudinal repeated measurement burst design study to assess the relationship between sleep determinants and outcomes under real-world conditions across time of year.

The interplay of daily life factors, including mood, physical activity, or light exposure, influences sleep architecture and quality. Laboratory-based studies often isolate these determinants to establish causality, thereby sacrificing ecological validity. Furthermore, little is known about time-of-year changes in sleep and circadian-related variables at high resolution, including the magnitude of individual change across time of year under real-world conditions. The Ecology of Human Sleep (EcoSleep) cohort study will investigate the combined impact of sleep determinants on individuals' daily sleep episodes to elucidate which waking events modify sleep patterns. A second goal is to describe high-resolution individual sleep and circadian-related changes across the year to understand intra- and inter-individual variability. This study is a prospective cohort study with a measurement-burst design. Healthy adults aged 18-35 years (N = 12) will be enrolled for 12 months. Participants will continuously wear actimeters and pendant-attached light loggers. A subgroup will also measure interstitial fluid glucose levels (six paticipants). Every 4 weeks, all participants will undergo three consecutive measurement days of four ecological momentary assessments each day ('bursts') to sample sleep determinants during wake. Participants will also continuously wear temperature loggers (iButtons) during the bursts. Body weight will be captured before and after the bursts in the laboratory. The bursts will be separated by two at-home electroencephalogram recordings each night. Circadian phase and amplitude will be estimated during the bursts from hair follicles, and habitual melatonin onset will be derived through saliva sampling. Environmental parameters (bedroom temperature, humidity, and air pressure) will be recorded continuously.

Associations Between Multiple Dimensions of Sleep and Mood During Early Adolescence: A Longitudinal Daily Diary Study.

Prior research has observed reciprocal associations between sleep and mood. However, these findings are primarily based on the examination of one or two aspects of sleep behaviors (e.g., duration, quality), neglecting how multiple dimensions of sleep (particularly indicators pertinent to adolescence, e.g., sleep variability) are linked to adolescent mood both daily and longitudinally. Drawing on a multidimensional framework for sleep, this study addressed the knowledge gap by examining the directionality of and differential effects for associations between multiple dimensions of sleep and mood during early adolescence. Participants were 273 Chinese early adolescents (34.39% girls; Mage = 11.57, SD = 1.31), who filled out a pre-survey on demographics (T1) and 7-day diaries on sleep (i.e., duration, quality, disturbance, and latency) and mood (i.e., positive and negative mood). Adolescents completed another wave of diary reports 1 year later (T2). Findings revealed both bidirectional and unidirectional, within-person effects depending on specific sleep parameters, suggesting differential associations between multiple dimensions of sleep and mood. Specifically, on days when adolescents had longer sleep latency and greater disturbance than usual, they reported higher negative mood the next day, whereas higher negative mood was linked to poorer sleep quality the next day. The longitudinal investigation found that greater variability in sleep quality at T1 was associated with higher negative mood at T2. These findings underscore the importance of understanding the complex interplay between sleep and mood by examining the directionality of and differential effects for the daily and longer-term associations between multiple dimensions of sleep and mood among early adolescents.

Variability in Sleep Duration and Biomarkers of Cardiovascular Disease Across the Menstrual Cycle.

Variability in sleep duration and cardiovascular health have been infrequently investigated, particularly among reproductive-age women. We examined these associations across the menstrual cycle among a cohort of 250 healthy premenopausal women, aged 18-44 years. The BioCycle study (New York, 2005-2007) collected cardiovascular biomarkers (serum high- and low-density lipoprotein (HDL, LDL), total cholesterol, triglycerides, and C-reactive protein (CRP)) at key time points along the menstrual cycle (follicular, ovulatory, and luteal phases). Women also recorded sleep duration in daily diaries. From these data, we computed L-moments, robust versions of location, dispersion, skewness, and kurtosis. We fitted linear mixed models with random intercepts and inverse probability weighting to estimate associations between sleep variability and cardiovascular biomarkers, accounting for demographic, lifestyle, health, and reproductive factors. Sleep dispersion (any deviation from mean duration) was associated with lower mean LDL for nonshift workers and non-White women. Skewed sleep duration was associated with higher mean CRP and lower mean total cholesterol. Sleep durations with extreme short and long bouts (kurtosis) were associated with a lower mean HDL, but not mean CRP, LDL, or triglycerides. Sleep duration modified associations between sleep dispersion and LDL, HDL, and total cholesterol. Even in young and healthy women, sleep duration variability could influence cardiovascular health.

Short-term and intermediate-term fine particulate air pollution are synergistically associated with habitual sleep variability in adolescents - A cross-sectional study.

BACKGROUND: Both air pollution and poor sleep have been associated with increased risk of cardiovascular diseases. However, the association between air pollution and sleep health, especially among adolescents, is rarely investigated. METHODS: To investigate the association between fine particulate (PM2.5) air pollution and habitual sleep patterns, we analyzed data obtained from 246 adolescents who participated in the Penn State Child Cohort follow-up examination. We collected their individual-level 24-h (short-term) PM2.5 concentration by using a portable monitor. We estimated their residential-level PM2.5 concentration during the 60-day period prior to the examination (intermediate-term) using a kriging approach. Actigraphy was used to measure participants' sleep durations for seven consecutive nights. Habitual sleep duration (HSD) and sleep variability (HSV) were calculated as the mean and SD of the seven-night sleep duration. Multivariable-adjusted linear regression models were used to assess the association between PM2.5 exposures and HSD/HSV. An interaction between short-term and intermediate-term PM2.5 was created to explore their synergistic associations with HSD/HSV. RESULTS: Elevated short-term and intermediate-term PM2.5 exposure were significantly (p < 0.05) associated with higher HSV, but not HSD. Specifically, the mean (95% CI) increase in HSV associated with 1 SD higher 24-h (26.3 µg/m3) and 60-day average (2.2 µg/m3) PM2.5 were 14.6 (9.4, 14.8) and 4.9 (0.5, 9.2) minutes, respectively. In addition, there was a synergistic interaction (p = 0.08) between short-term and intermediate-term PM2.5 exposure on HSV, indicative that the association between intermediate-term PM2.5 and HSV became stronger as short-term PM2.5 increases, and vice versa. CONCLUSION: Short-term individual-level and intermediate-term residential-level PM2.5 exposures are adversely and synergistically associated with increased sleep variability, an indicator of instability of sleep quantity, in adolescents. Through such an association with sleep pattern, PM2.5 air pollution may increase long-term cardiometabolic risks.

Sleep, Affect, and Emotion Reactivity in First-Year College Students: A Daily Diary Study.

BACKGROUND: Sleep is an important factor in well-being, especially during the transition to college when academic and social commitments increase. Identifying factors that contribute to poor sleep (including short duration and increased variability in duration) can support development of interventions. Affect and emotion reactivity are factors that could contribute to sleep, and have not been studied in relation to sleep variables among first-year college students during their adjustment to the college environment. This adjustment might be difficult for some students, and therefore elicit affect fluctuations that contribute to poor sleep. Alternatively, sleep could contribute to daily affect. The present daily diary study examined bidirectional relations between daily sleep and affect, as well as between emotion reactivity and sleep (duration and variability) and affect (daily and overall variability) in first-year college students. METHOD: First-year college students (n = 244; 86.1% female) completed a baseline survey including measures of emotion reactivity and anxiety and depressive symptoms, followed by 7 days of a once-per-day diary, reporting on their affect and sleep duration. RESULTS: On days when individuals reported increased sleep duration, they also tended to experience greater positive affect the following day (p = .01). Those who experienced high levels of emotion reactivity also experienced more negative affect (p < .001) and negative affect variability (p < .001). CONCLUSION: Emotion reactivity might identify college students who experience more negative affect and are possibly at risk to develop mental health disorders. The importance of sleep health should continue to be emphasized to students as they transition to college.

Interrupted lullabies: the association between menopausal symptoms and sleep variability in peri- and post-menopausal women.

Poor sleep is a reality for many midlife women experiencing menopause. Although much empirical attention has been allocated toward ameliorating vasomotor symptoms and related consequences, less focus has been given toward sleep, specifically sleep variability, in menopausal women. The present study aimed to determine the association between menopausal symptoms and night-to-night sleep variability among peri- and post-menopausal women. Participants were 220 menopausal women (42.3 percent peri-menopausal, 57.7 percent post-menopausal) aged 40 to 64 from the United States recruited via Prolific, and online platform. The current study conducted secondary analyses on data collected as part of a larger investigation on midlife women from the United States. A structural equation model assessed associations between a latent menopausal symptom construct, composed of several Women's Health Questionnaire domains, and a latent sleep variability construct, composed of sleep diary indices. Menopausal symptoms were associated with latent sleep variability (ß = 0.49, p < .05); greater experience of menopausal symptoms was associated with more night-to-night sleep variability (medium effect size). Waking after sleep onset (WASO) was the sole significant indicator of the latent sleep factor. The findings highlight the importance of menopausal symptoms for sleep variability, specifically wakefulness. As such, wakefulness may be an important target for sleep interventions for menopausal women. The findings further suggest a need for more research and interventions targeted toward understanding and ameliorating the impact of menopausal symptoms on night-to-night wakefulness overall.

Association of job strain with accelerometer-based sleep duration and timing of sleep among older employees.

Job strain has been associated with poor sleep quality and could lead to changes in duration and timing of sleep as well. This study examined the association of job strain with sleep duration, bedtimes and awakening times among public sector employees close to their retirement age. Differences in these sleep parameters between workdays and free days across job strain groups were examined. Duration and timing of sleep were measured repeatedly with accelerometers among 466 public sector employees in Finland (mean age 63 years, 86% women), who contributed to 759 measurements in total. Job demands (low/high) and control (low/high) measured by self-reports and job exposure matrix were used to identify low strain (low demand, high control), passive (low, low), active (high, high) and high strain (high, low) jobs. No differences in sleep duration were observed on workdays, whereas on free days those in the high strain group had longer sleep duration than those in the low strain and passive job groups. The high strain group also extended their sleep from workdays to free days more, the extension being on average 59 min (95% CI 42 min-75 min) when adjusted for several sociodemographic, work and health factors. This extension of sleep duration resulted mostly from a greater delay of awakening times from workdays to free days. Psychosocial work factors, such as job strain, need to be considered when promoting sufficient sleep duration among older employees, as those with job strain may have a greater need for recovery and sleep.

The impact of self-selected short sleep on monetary risk taking.

Risky choice has been widely studied in experimental settings, but there is a paucity of research examining the effects of self-selected sleep schedules on risky choices. The current study examined incentivised risky choices of 100 young, healthy adults whose self-selected (at-home) sleep schedules were tracked via actigraphy for 1 week prior to decision making. Average nightly sleep was 6.43 h/night. On each trial of the decision task, individuals chose between two monetary gambles, with separate blocks of trials presenting amounts to gain versus amounts to lose for each paired gamble choice. In general, participants were risk-averse when trying to maximise gains (GAINS) and risk-seeking when trying to minimise losses (LOSSES). These tendencies were amplified in trials where gambles differed more (vs less) in their riskiness. Response times were longer for real choices (vs. dummy trials of random choice), LOSS versus GAINS trials, and when gambles were more similar versus different in risk. Gamble choices were not impacted by actigraphy measured average sleep levels, which suggests self-selected moderate sleep deprivation does not affect risky monetary choices, as has been found in studies of experimentally induced sleep deprivation. However, our data showed that sleep variability increased risk-taking behaviour in the LOSS condition. Thus, risky decision-making may relate more to variability in sleep efficiency than to overall sleep duration or quality in naturalistic settings. The current study gives insight into how decision making in experimental sleep settings may or may not translate to more ecologically valid settings of self-directed sleep.

Worse sleep health predicts less frequent breakfast consumption among adolescents in a micro-longitudinal analysis.

BACKGROUND: Poor self-reported sleep health has been linked to not consuming breakfast in adolescents, but it is unknown whether poor sleep measured objectively predicts next-day breakfast consumption within adolescents. We investigated within- and between-person associations of objectively measured sleep dimensions and subjective sleep quality with adolescent breakfast consumption. METHODS: Data were collected from a micro-longitudinal substudy of the Year 15 wave of the Fragile Families and Child Wellbeing Study (n = 590). Adolescents wore an actigraphy device and completed daily diaries for ~ 1 week (M ± SD = 5.6 ± 1.4 nights per adolescent, range: 3-9), where they rated their sleep quality and reported whether they had eaten breakfast that day, with no specific definition of breakfast provided (M ± SD = 5.5 ± 1.4 days per adolescent, range: 3-9). Separate mixed models assessed whether actigraphy-measured sleep duration (linear and quadratic, sleep duration x sleep duration), timing, maintenance efficiency, and subjective quality predicted odds of breakfast consumption both within and between adolescents. Variability of sleep duration and timing (standard deviation per person), sleep regularity index (SRI), and social jetlag were tested as additional between-person predictors. Analyses with predictors other than sleep duration were adjusted for sleep duration. RESULTS: Following nights when adolescents had shorter or longer sleep duration (p = .005; curvilinear association), later sleep onset, or later sleep midpoint (both p = .025) than their own usual, they had lower odds of consuming breakfast the next day (within-person associations). Adolescents who on average had later sleep onset (p = .013) or midpoint (p = .013) or who reported lower sleep quality (p = .011) had lower average odds of consuming breakfast (between-person associations). Adolescents with greater variability of sleep duration (p = .005), midpoint (p = .004), or offset (p < .001) had lower average odds of consuming breakfast (between-person associations). Sleep maintenance efficiency (within or between adolescents), SRI, and social jetlag were not associated with breakfast consumption (all p > .10). CONCLUSIONS: Multiple dimensions of sleep health are associated with breakfast consumption, both within and between adolescents. Poor sleep and dietary behaviors in adolescence may negatively impact future metabolic health.

Neighborhood Disadvantage Is Associated with Lower Quality Sleep and More Variability in Sleep Duration among Urban Adolescents.

Differential social and contextual environments may contribute to adolescent sleep disparities, yet most prior studies are limited to self-reported sleep data and have not been conducted at a national level, limiting the variation in neighborhood contexts. This study examined the association between neighborhood disadvantage and objective measures of adolescent sleep. A racially and geographically diverse sample of American adolescents (N = 682) wore wrist-worn accelerometers, "actigraphs," for ≥ 5 nights. Neighborhood disadvantage was calculated using a standardized index of neighborhood characteristics (proportion of female-headed households, public assistance recipients, households in poverty, adults without high school degrees, and unemployed). Adolescents in more disadvantaged neighborhoods spent more time awake after falling asleep (4.0 min/night, p < .05), a greater percentage of nighttime sleep intervals awake (1%, p < .01), and had less consistent sleep duration (11.6% higher standard deviation, p < .05). Sleep duration and timing did not differ across neighborhood groups. These findings demonstrate that adolescents who live in more disadvantaged neighborhoods have lower quality, less consistent sleep.

Sleep quantity and variability during the first semester at university: implications for well-being and academic performance.

Research has demonstrated the importance of sleep quality for university students, although work is limited with respect to how sleep during the first semester of school impacts well-being and academic outcomes. The current study sought to examine the role of sleep quantity and variability over the first semester of university on GPA and happiness. Students (n = 97) from a first-semester psychology course completed weekly assessments of sleep and well-being (happiness and anxiety) for 15 weeks, and they gave permission for researchers to collect their GPA and SAT data from the registrar. Average weekly sleep quantity was associated with greater weekly happiness and less anxiety. Weekly sleep variability was associated with lower happiness and more anxiety. Even when accounting for sleep quantity and initial start-of-semester measures, sleep variability predicted worse GPA and happiness for students at the end-of-semester. In summary, sleep consistency may be an important target for health professionals working within the university setting. This study contributes to the literature on the importance not only of sleep but also of sleep consistency, during a major life transition.

Neurobehavioural functions during variable and stable short sleep schedules.

We investigated whether variable sleep schedules might mitigate the neurobehavioural deficits induced by multiple nights of sleep restriction. In this 4-night experiment, 78 young adults (age: 18-28 years) were randomly assigned to four groups: 8888, 8666, 8846 and 8486, where each digit corresponded to time-in-bed in hours for each study night. After one baseline night of 8-hr time-in-bed, time-in-bed remained unchanged for the 8888 group, while the other groups had short sleep schedules (total time-in-bed = 18 hr) that differed in the number of time-in-bed changes. Sleep was monitored using actigraphy at home. Daytime neurobehavioural functions were assessed in the laboratory at single time points, after the baseline night, and again after 3 nights of the sleep manipulation period. For sustained attention, the 8888 group responded faster in the Psychomotor Vigilance Task after the manipulation period (p = .01), while responses became slower for the less variable sleep schedules (8666 and 8846; p < .01), but not the most variable sleep schedule (8486; p = .14). Processing speed also improved in the 8888 group and the variable 8846 and 8486 groups (p < .01), but not in the stable 8666 group (p = .09). Furthermore, subjective sleepiness was preserved in the 8888 and, importantly, 8486 groups (p > .05), but was elevated in the 8666 and 8846 groups (p < .05). These findings suggest that when sleep opportunities are limited across multiple nights, a variable sleep schedule that allows for prophylactic and/or recovery sleep on some nights may mitigate some daytime neurobehavioural deficits as compared with a schedule with no opportunity for recovery.

Sleep variability, 6-sulfatoxymelatonin, and diabetic retinopathy.

PURPOSE: Recent evidence suggests that diabetic retinopathy (DR) is associated with abnormal melatonin regulation, possibly related to dysfunction of the melanopsin-expressing intrinsically photosensitive retinal ganglion cells. This study explored melatonin regulation in type 2 diabetes (T2D) patients with DR and its relation to sleep and circadian functioning. METHODS: Thirty-five participants (10 non-diabetic controls, 10 T2D without DR, and 15 T2D with DR) were recruited. Overnight urine 6-sulfatoxymelatonin (aMT6s) and objective sleep and wrist activity (7-day actigraphy) were obtained. RESULTS: After adjusting for covariates, having T2D with DR was significantly associated with lower urinary aMT6s (ß = - 1.369, p = 0.004) compared with controls, while having T2D without DR was not (p = 0.418). T2D patients with DR reported poorer sleep quality (p = 0.014) and had greater variability of sleep duration (p = 0.017) than others, while no differences were found in sleep duration, efficiency, and rest-activity rhythm. After adjusting for covariates, lower nocturnal aMT6s was significantly associated with greater sleep variability. CONCLUSION: T2D patients with DR exhibited low overnight production of aMT6s which likely contributed to sleep irregularities possibly due to weak circadian signaling. Whether or not melatonin supplementation could improve health in T2D patients with DR remains to be explored.

Variability of Sleep and Relations to Body Weight Among First-Year College Students.

BACKGROUND: Existing research suggests that greater sleep variability may increase risk for weight gain. College often marks a transition to a less consistent daily schedule, which may adversely impact sleep routines and further increase risk for weight gain. The current study is among the first to explore relations between nighttime sleep variability and daytime sleep (napping) and body weight among first-year college students. METHODS: Using daily diary methods, first-year college students (N = 307; 84.7% female) self-reported their sleep for seven days. Several indices were created to capture sleep variability for reported bedtime, wake time, and sleep duration, including weekday versus weekend differences (WvW), day to day differences (D2D), and overall standard deviation (SD). Napping was also assessed. Based on body mass index (BMI), individuals were categorized as underweight, healthy weight, overweight, and obese. RESULTS: Across indices, students' sleep varied over an hour on average across the week. Hierarchical regressions revealed that greater differences in wake time D2D, wake time SD, and sleep duration WvW were all associated with higher BMI, after accounting for gender, depressive symptoms, and sleep duration. Longer napping was also associated with higher BMI, using the same covariates. Finally, greater sleep variability was reported by overweight and obese than healthy weight individuals. CONCLUSION: These findings suggest that sleep variability, particularly wake times and napping may be important modifiable sleep behaviors to investigate in future studies. More longitudinal research is needed to explore relations between multiple facets of sleep variability and weight gain, including possible mechanisms.

Longitudinal associations between adolescents' sleep and adjustment: Respiratory sinus arrhythmia as a moderator.

Sleep and autonomic nervous system functioning are important bioregulatory systems. Poor sleep and low baseline respiratory sinus arrhythmia (RSA), a measure of parasympathetic nervous system activity, are associated with externalizing behaviors and depressive symptoms in youth. Rarely, however, have measures of these systems been examined conjointly. The present study examined baseline RSA (RSA-B) as a moderator of longitudinal relations between adolescent sleep and adjustment. Participants were 256 adolescents (52% girls, 66% White/European American, 34% Black/African American) from small towns and surrounding rural communities in the southeastern United States. Sleep (minutes, efficiency, variability in minutes and efficiency) was assessed at age 15 via actigraphs across seven nights. RSA-B was derived from electrocardiogram data collected at rest. Adolescents self-reported externalizing problems and depressive symptoms at ages 15 and 17. Controlling for age 15 adjustment, findings generally demonstrated that sleep predicted age 17 adjustment particularly at higher (rather than lower) levels of RSA-B, such that adolescents with good sleep (more minutes and lower variability) and high RSA-B were at lowest risk for maladjustment. The results highlight the value of examining multiple bioregulatory processes conjointly and suggest that promoting good sleep habits and regulation of physiological arousal should support adolescent adjustment.

Sleep Regularity and Cardiometabolic Heath: Is Variability in Sleep Patterns a Risk Factor for Excess Adiposity and Glycemic Dysregulation?

PURPOSE OF REVIEW: Night-to-night variability in sleep patterns leads to circadian disruption and, consequently, could increase cardiometabolic risk. The purpose of this review is to summarize findings from studies published between 2015 and 2020 examining various measures of night-to-night variability in sleep in relation to metabolic syndrome (MetS), type 2 diabetes (T2D), and their risk factors. We illustrate a potential causal pathway between irregular sleep patterns and T2D, highlighting knowledge gaps along the way. RECENT FINDINGS: Across different measures of sleep variability, irregular sleep patterns were associated with poorer cardiometabolic outcomes. Higher standard deviations (SD) across nights of sleep duration and onset or midpoint of sleep were associated with increased odds of having MetS and clusters of metabolic abnormalities as well as greater adiposity and poorer glycemic control. Conversely, greater regularity of rest-activity patterns related to lower risk for T2D. Social jetlag was associated with glycemic dysregulation, adiposity, T2D, and MetS. These associations are often observed in both metabolically healthy and unhealthy individuals; both higher SD of sleep duration and social jetlag relate to poorer glucose regulation in individuals with diabetes. There is consistent evidence of associations of sleep variability with increased risk for adiposity, glucose dysregulation, T2D, and MetS. Although experimental evidence is needed to determine causation, there is support to recommend stabilizing sleep patterns for cardiometabolic risk prevention.

Adolescent sleep patterns are associated with the selection of positive and negative emotional situations.

Poor sleep in youth is a risk factor for experiencing increased negative emotions and decreased positive emotions, which can contribute to the development of later emotional disorders. Understanding of specific processes that produce sleep-related alterations in emotion is limited, although preliminary studies suggest changes in the ability to appropriately regulate or control emotions as one mechanism. The current study builds on this research by examining the relationship between adolescent sleep patterns and a previously unexplored emotion regulation strategy: situation selection. Situation selection strategies are implemented prior to the onset of an emotional experience via decisions to approach rewarding/positive situations or avoid unwanted/negative situations. Fifty-four healthy adolescents (ages 13-17 years) completed 1 week of actigraphy and assessments of situation selection using: (a) trait-based questionnaires; (b) daily reports; and (c) an experimental lab task where participants were given the option to watch various emotional video clips of their choice. Greater variability in sleep timing was associated with less avoidance of negative emotional situations, and a longer sleep-onset latency was associated with more avoidance of negative emotional situations. Greater variability in nightly sleep patterns was also associated with decreased tendencies to select positive emotional situations as assessed by trait questionnaires, daily reports, and the lab-based task, but only for boys. These findings add to a growing body of research on sleep and emotional experience, and provide further support for the importance of intra-individual variability of sleep patterns in youth.

Variability in Sleep Patterns: an Emerging Risk Factor for Hypertension.

PURPOSE OF REVIEW: In this review, we summarize recent epidemiological data (2014-2019) that examine the association of sleep variability with blood pressure (BP), discuss potential underlying mechanisms, and highlight future research directions. RECENT FINDINGS: Higher standard deviations of sleep duration and sleep-onset timing were not related to BP. However, a higher Sleep Regularity Index score was associated with lower odds of hypertension. Studies on social jetlag, a prevalent form of sleep variability, reported null associations. In contrast, lower interdaily stability in circadian rest-activity rhythms, a measure of invariability in sleep-wake cycles between days and synchronization to light and dark cycles, was associated with higher BP and greater hypertension odds, particularly among non-shift workers. Sleep variability is consistently associated with risk factors for hypertension. Evidence on sleep variability and BP is limited and varies depending on the measure used to characterize day-to-day variability in sleep. Studies that identify and utilize a standard definition of sleep variability, incorporate a 24-h ambulatory BP monitoring, and ensure coinciding timing of sleep and BP measurements are necessary to disentangle these relationships.

Sleep, self-management, neurocognitive function, and glycemia in emerging adults with Type 1 diabetes mellitus: A research protocol.

Type 1 Diabetes (T1D) affects 1.6 million Americans, and only 14% of emerging adults ages 18-25 years achieve targets for glycemic control (A1C < 7.0%). Sleep deficiency, including habitual short sleep duration (<6.5 hr total sleep time and high within-person variability in total sleep time), is associated with poorer glycemic control. Emerging adults with T1D have a more pronounced sleep extension on weekends compared with matched controls, consistent with sleep deficiency; however, associations among sleep variability and glycemic control have not been explored in this population. Sleep deficiency may affect the complex higher-order neurocognitive functioning needed for successful diabetes self-management (DSM). We report the protocol for an ongoing study designed to characterize sleep and the associations among sleep deficiency, neurocognitive function, DSM, diabetes quality of life, and glycemia among a sample of 40 emerging adults with T1D. We monitor sleep via wrist-worn actigraphy and glucose via continuous glucose monitoring concurrently over 14 days. We are collecting data on self-report and objective sleep, a 10-min psychomotor vigilance test on a PVT-192 device, a 3-min Trail Making Test on paper, and questionnaires, including twice-daily Pittsburgh sleep diaries using Research Electronic Data Capture (REDCap)TM . Results from this study will be used to support the development and testing of the efficacy of a tailored sleep self-management intervention that may improve total sleep time, sleep variability, neurocognitive function, DSM, glycemic control, and glucose variability among emerging adults with T1D.