Sleep Duration Variability Research Articles

Interconnection between adolescents' and family members' sleep.

Deficient sleep has been linked to a broad range of physical, cognitive and mental health impacts, in particular during adolescence. It is thus essential to understand its underlying mechanisms, including family factors. The goal of our study was to assess through combined subjective and objective assessments, how family members' daily variations in sleep are interconnected, between parents and siblings of adolescents. A total of 111 participants within 30 families were included, of whom 30 adolescents (14.5 years +/- 2.1 years, 46.7% boys), 30 siblings (12.8 years + /- 3.8, 40% boys), 30 mothers (43.5 years +/- 5.5) and 21 fathers (47.5 years +/- 7.6). Sleep was objectively assessed using parallel actigraphy recordings during a single week for all family members. Adolescents' daily variation in sleep duration and timing displayed many concordances with their siblings' and their mothers' sleep, but not with their fathers' sleep. Adolescents whose parents did not set limits on sleep time or screen use went to bed over an hour later (p < 0.001) and slept over 30 min less on school nights. Our study demonstrates the important role of family sleep on adolescent sleep, through rule-setting and congruence between each family members sleep, in particular regarding sleep duration and timing.

Associations Between Sleep Health and Child Behavior at Age 6 Years in the INSIGHT Study.

Suboptimal sleep is associated with disruptive behaviors in childhood. We evaluate associations of mean and variability (SD) of sleep duration, quality, and timing with emotion regulation, impulsivity, and prosocial and antisocial behavior in children. Intervention Nurses Start Infants Growing on Healthy Trajectories, a randomized controlled trial designed for obesity prevention, compared a responsive parenting intervention delivered in the first 2.5 years after birth with a home safety control group. At age 6 years, children wore an actigraphy device for 7 days and participated in behavioral tasks evaluating behavioral control, emotion regulation, and prosocial and antisocial behaviors. Separate linear regression models examined associations between sleep and behavioral variables, adjusting for study group, child sex, and household income. Moderation analysis investigated whether the study group moderated relationships between sleep and positive age-appropriate behavior. Children (N = 143, age 6.7 ± 0.3 years) were predominantly non-Hispanic White (95%). Mean actigraphic sleep duration, quality, and timing were not associated with behavioral variables. By contrast, greater variability in sleep onset timing was associated with greater impulsivity (B = 0.85, p = 0.004) and poorer emotion regulation (B = -0.65, p = 0.01). Greater variability in sleep midpoint timing was associated with greater impulsivity (B = 0.80, p = 0.03). The study group moderated the effect of sleep onset variability on behavior; only the home safety control group exhibited a significant negative relationship between variability in sleep onset timing and emotion regulation (B = -1.28, p = 0.0002). Findings support the importance of consistency in sleep timing and how this may play a greater role in children's behavioral and emotional outcomes than mean actigraphic sleep duration and quality.

Prospective associations between Sleep, Sensation-Seeking and Mature Screen Usage in Early Adolescents: Findings from the Adolescent Brain Cognitive Development (ABCD) Study.

Early exposure to mature content is linked to high-risk behaviors. This study aims to prospectively investigate how sleep and sensation-seeking behaviors influence the consumption of mature video games and R-rated movies in early adolescents. A secondary analysis examines the bidirectional relationships between sleep patterns and mature screen usage. Data were obtained from a subsample of 3,687 early adolescents (49.2% female; mean age: 11.96 years) participating in the Adolescent Brain and Cognitive Development study. At Year 2 follow-up, participants wore Fitbit wearables for up to 21 nights to assess objective sleep measures and completed a scale about sensation-seeking traits. At Year 3 follow-up, they answered questions about mature screen usage. Of the sample, 41.8% of the sample reported playing mature-rated video games and 49% reported watching R-rated movies. Sensation-seeking traits were associated with R-rated movie watching one year later. Shorter sleep duration, later bedtime, more bedtime variability, and more social jetlag (discrepancy between the mid-sleep on weekdays and weekends) were associated with mature-rated video gaming and R-rated movie watching one year later. Sleep duration variability was associated with mature-rated video gaming. There was also an interaction effect: those with higher sensation-seeking scores and shorter sleep duration reported more frequent R-rated movie usage than those with longer sleep duration. Secondary analyses showed bidirectional associations between later bedtimes, more variability in bedtimes, and more social jetlag with mature screen usage. Early adolescents with sensation-seeking traits and poorer sleep health were more likely to engage in mature screen usage.

Sleep, Sleep Apnea, and Fatigue in People Living With HIV.

People living with HIV (PLWH) often report fatigue even when viral load is suppressed. Obstructive sleep apnea (OSA), which is often associated with fatigue, is common in PLWH, but whether OSA explains fatigue in this population is unknown. Academic university-affiliated HIV and Sleep Medicine Clinics. PLWH, aged 18-65 years, with a body mass index of 20-35 kg/m2 and viral suppression (RNA <200 copies per mL), were recruited to undergo daytime questionnaires, including the Functional Assessment of Chronic Illness Therapy Fatigue Scale and Epworth Sleepiness Scale, 7 days of actigraphy (to determine daily sleep duration and activity amplitude and rhythms), and an in-laboratory polysomnography to assess for the presence and severity of OSA. Of 120 subjects with evaluable data, 90 (75%) had OSA using the American Academy of Sleep Medicine 3% desaturation or arousal criteria, with an apnea-hypopnea index >5/h. There was no difference in Functional Assessment of Chronic Illness Therapy scores between those with and without OSA, although those with OSA did report more daytime sleepiness as measured using the Epworth Sleepiness Scale. In a multivariable model, predictors of fatigue included more variable daily sleep durations and decreased mean activity counts. Sleepiness was predicted by the presence of OSA. OSA was very common in our cohort of PLWH, with those with OSA reporting more sleepiness but not more fatigue. Variability in sleep duration was associated with increased fatigue. Further study is needed to determine if treatment of OSA, or an emphasis on sleep consistency and timing, improves symptoms of fatigue in PLWH.

Letter to the editor in response to "Variability in Sleep Duration and Biomarkers of Cardiovascular Disease Across the Menstrual Cycle".

Letter to the editor in response to "Variability in Sleep Duration and Biomarkers of Cardiovascular Disease Across the Menstrual Cycle".

Actigraphy-assessed sleep duration and quality and executive function in a sample of typically developing preschoolers.

Sleep is essential for cognitive development and brain maturation during early childhood. Studies focused on preschool populations using objective measures of sleep are still scarce. The objective of this study was to examine the associations between objective measures of sleep duration and quality with executive functioning in a 133 non-clinical sample of Spanish participants (Mage = 60.33 months, SD = 9.04; ages 41-77 months; 51.1% girls). Sleep was assessed for five weeknights using actigraphy; Shape School task was applied to assess inhibition and cognitive flexibility; and Word Span task was used to assess working memory. The results revealed that relation between sleep and executive functioning was significant for inhibition and working memory. Preschoolers with higher sleep efficiency showed better results in executive functioning tasks after controlling for the effect of age. Additionally, age and sleep duration and quality variables were predictive of inhibition, working memory, and cognitive flexibility. These results suggest that the different dimensions of sleep could play an important role in the development of executive functions during preschool age. Therefore, improving sleep could lead to an improvement in children's executive functioning in both clinical and educational contexts.

Sleep disturbances across two weeks predict future mental healthcare utilization.

Insufficient sleep costs the U.S. economy over $411 billion per year. However, most studies investigating economic costs of sleep rely on one-time measures of sleep, which may be prone to recall bias and cannot capture variability in sleep. To address these gaps, we examined how sleep metrics captured from daily sleep diaries predicted medical expenditures. Participants were 391 World Trade Center responders enrolled in the World Trade Center Health Program (mean age = 54.97 years, 89% men). At baseline, participants completed 14 days of self-reported sleep and stress measures. Mean sleep, variability in sleep, and a novel measure of sleep reactivity (i.e., how much people's sleep changes in response to daily stress) were used to predict the subsequent year's medical expenditures, covarying for age, race/ethnicity, sex, medical diagnoses, and body mass index. Mean sleep efficiency did not predict mental healthcare utilization. However, greater sleep efficiency reactivity to stress (b=$191.75, p=.027), sleep duration reactivity to stress (b=$206.33, p=.040), variability in sleep efficiency (b=$339.33, p=.002), variability in sleep duration (b=$260.87, p=.004), and quadratic mean sleep duration (b=$182.37, p=.001) all predicted greater mental healthcare expenditures. Together, these sleep variables explained 12% of the unique variance in mental healthcare expenditures. No sleep variables were significantly associated with physical healthcare expenditures. People with more irregular sleep, more sleep reactivity, and either short or long sleep engage in more mental healthcare utilization. It may be important to address these individuals' sleep problems to improve mental health and reduce healthcare costs.

Discrepancy Between Desired Time in Bed and Desired Total Sleep Time, Insomnia, Depression, and Dysfunctional Beliefs About Sleep Among a Clinical Sample of Patients With Insomnia.

This study investigated whether the discrepancy between desired time in bed and desired total sleep time (DBST) index could be a meaningful indicator for assessing insomnia severity in a clinical sample of patients with insomnia. Furthermore, we sought to identify the mediators of the association between DBST and insomnia severity in individuals with insomnia. We collected the medical records of 127 patients with insomnia. Each participant's DBST index was calculated using sleep indices, including time and duration variables. Psychological symptoms were investigated using the Insomnia Severity Index (ISI), Patients Health Questionnaire-9 items (PHQ-9), Generalized Anxiety Disorder-7, Dysfunctional Beliefs and Attitudes about Sleep-16 items (DBAS-16), and Epworth Sleepiness Scale. The DBST index was significantly correlated with the ISI (r=0.20, p<0.05), desired total sleep time (r=-0.52, p<0.001), and desired time in bed (r=0.32, p<0.01). Linear regression analysis revealed that insomnia severity was associated with age (β=-0.18, p=0.018), DBST (β=0.23, p=0.003), PHQ-9 (β=0.23, p=0.031), and DBAS-16 (β=0.42, p<0.001). The DBST directly influenced insomnia severity, although indirect effects of mediators were not significant. The DBST index directly influenced insomnia severity regardless of the mediating effects of psychological factors among a clinical sample of patients with insomnia. This finding implies that the DBST index can be a simple measure of insomnia severity, even among patients with insomnia.

Sleep duration irregularity and risk for incident cardiovascular disease in the UK Biobank.

Emerging evidence supports a link between circadian disruption as measured by higher night-to-night variation in sleep duration and increased risk of cardiovascular disease (CVD). It remains unclear whether this association varies by CVD types or may be modified by average sleep duration and genetic risk for CVD. Our prospective analysis included 86,219 UK Biobank participants who were free from CVD when completing 7 days of accelerometer measurement in 2013-2016. Sleep irregularity was evaluated by the standard deviation (SD) of accelerometer-measured sleep duration over 7 days. Incident major CVD events, defined as fatal or nonfatal myocardial infarction (MI) and stroke, were identified through linkage to Hospital Episode Statistics data until May 31, 2022. Multivariable-adjusted Cox proportional hazard models were used to estimate hazard ratios (HRs) and 95% CIs for associations of sleep duration SD with risk for major CVD events overall and for MI and stroke separately. We documented 2,310 incident cases of major CVD events (MI: 1,183, stroke: 1,175) over 636,258 person-years of follow-up. After adjusting for sociodemographic factors and family history of CVD, the HR (95% CI) associated with a 1-hour increase in sleep duration SD was 1.19 (1.10, 1.27) for CVD (p-trend<0.0001), 1.23 (1.11, 1.35) for MI (p-trend<0.0001), and 1.17 (1.05, 1.29) for stroke (p-trend=0.003). Additional adjustment for lifestyle factors, co-morbidities and sleep-related factors modestly attenuated these associations. Higher sleep irregularity was associated with higher CVD risk irrespective of genetic risk (p-interaction=0.43), but this association was stronger among individuals with longer average sleep duration >8 hours (p-interaction=0.006). Higher night-to-night variation in accelerometer-measured sleep duration was associated with consistently higher risks for major CVD events. The association did not seem to be modified by genetic risk for CVD and was more pronounced in long sleepers.

The relationship between wearable-derived sleep features and relapse in Major Depressive Disorder

BackgroundChanges in sleep and circadian function are leading candidate markers for the detection of relapse in Major Depressive Disorder (MDD). Consumer-grade wearable devices may enable remote and real-time examination of dynamic changes in sleep. Fitbit data from individuals with recurrent MDD were used to describe the longitudinal effects of sleep duration, quality, and regularity on subsequent depression relapse and severity. MethodsData were collected as part of a longitudinal observational mobile Health (mHealth) cohort study in people with recurrent MDD. Participants wore a Fitbit device and completed regular outcome assessments via email for a median follow-up of 541 days. We used multivariable regression models to test the effects of sleep features on depression outcomes. We considered respondents with at least one assessment of relapse (n = 218) or at least one assessment of depression severity (n = 393). ResultsIncreased intra-individual variability in total sleep time, greater sleep fragmentation, lower sleep efficiency, and more variable sleep midpoints were associated with worse depression outcomes. Adjusted Population Attributable Fractions suggested that an intervention to increase sleep consistency in adults with MDD could reduce the population risk for depression relapse by up to 22 %. LimitationsLimitations include a potentially underpowered primary outcome due to the smaller number of relapses identified than expected. ConclusionOur study demonstrates a role for consumer-grade activity trackers in estimating relapse risk and depression severity in people with recurrent MDD. Variability in sleep duration and midpoint may be useful targets for stratified interventions.

Association Between Accelerometer-Measured Irregular Sleep Duration and Type 2 Diabetes Risk: A Prospective Cohort Study in the UK Biobank.

To evaluate the association between irregular sleep duration and incident diabetes in a U.K. population over 7 years of follow-up. Among 84,421 UK Biobank participants (mean age 62 years) who were free of diabetes at the time of providing accelerometer data in 2013-2015 and prospectively followed until May 2022, sleep duration variability was quantified by the within-person SD of 7-night accelerometer-measured sleep duration. We used Cox proportional hazard models to estimate hazard ratios (HRs) for incident diabetes (identified from medical records, death register, and/or self-reported diagnosis) according to categories of sleep duration SD. There were 2,058 incident diabetes cases over 622,080 person-years of follow-up. Compared with sleep duration SD ≤ 30 min, the HR (95% CI) was 1.15 (0.99, 1.33) for 31-45 min, 1.28 (1.10, 1.48) for 46-60 min, 1.54 (1.32, 1.80) for 61-90 min, and 1.59 (1.33, 1.90) for ≥91 min, after adjusting for age, sex, and race. We found a nonlinear relationship (P nonlinearity 0.0002), with individuals with a sleep duration SD of >60 vs. ≤60 min having 34% higher diabetes risk (95% CI 1.22, 1.47). Further adjustment for lifestyle, comorbidities, environmental factors, and adiposity attenuated the association (HR comparing sleep duration SD of >60 vs. ≤60 min: 1.11; 95% CI 1.01, 1.22). The association was stronger among individuals with lower diabetes polygenic risk score (PRS; P interaction ≤ 0.0264) and longer sleep duration (P interaction ≤ 0.0009). Irregular sleep duration was associated with higher diabetes risk, particularly in individuals with a lower diabetes PRS and longer sleep duration.

Association of total sleep duration variability with risk of new stroke in the middle-aged and elderly Chinese population

ObjectiveTo investigate the association between total sleep duration variability and stroke in the middle-aged and elderly population in China.MethodsData were collected from the 2011, 2013, 2015, and 2018 surveys of the China Health and Retirement Longitudinal Study (CHARLS). A total of 3485 participants, who had not experienced a stroke until 2015 and completed the follow-up in 2018, were enrolled to analyze the relationship between total sleep duration variability and new stroke. Total sleep duration was calculated by summing self-reported nocturnal sleep duration and daytime napping. The variability was determined by calculating the standard deviation (SD) of total sleep duration across the first three waves. A binary logistic regression model was utilized to analyze this association.ResultsOf the 3485 participants, 183 (5.25%) sustained a stroke event. A dose-response relationship was observed, indicating an increased stroke risk of 0.2 per unit (hours) increase in total sleep duration variability [OR (95% CI): 1.20 (1.01–1.42)]. Upon stratification by sex groups, this increased risk was significant only in men [OR (95% CI): 1.44 (1.12–1.83)].ConclusionIncreased total sleep duration variability was associated with an increased risk of stroke in the middle-aged and elderly, independent of factors such as age, nocturnal sleep duration, napping habits, region of residence, hypertension, diabetes mellitus, dyslipidemia, BMI, smoking, drinking habits, and marital status. However, a more notable correlation was observed in males.

Assessment of Stress and Well-Being of Japanese Employees Using Wearable Devices for Sleep Monitoring Combined With Ecological Momentary Assessment: Pilot Observational Study.

Poor sleep quality can elevate stress levels and diminish overall well-being. Japanese individuals often experience sleep deprivation, and workers have high levels of stress. Nevertheless, research examining the connection between objective sleep assessments and stress levels, as well as overall well-being, among Japanese workers is lacking. This study aims to investigate the correlation between physiological data, including sleep duration and heart rate variability (HRV), objectively measured through wearable devices, and 3 states (sleepiness, mood, and energy) assessed through ecological momentary assessment (EMA) and use of rating scales for stress and well-being. A total of 40 office workers (female, 20/40, 50%; mean age 40.4 years, SD 11.8 years) participated in the study. Participants were asked to wear a wearable wristband device for 8 consecutive weeks. EMA regarding sleepiness, mood, and energy levels was conducted via email messages sent by participants 4 times daily, with each session spaced 3 hours apart. This assessment occurred on 8 designated days within the 8-week timeframe. Participants' stress levels and perception of well-being were assessed using respective self-rating questionnaires. Subsequently, participants were categorized into quartiles based on their stress and well-being scores, and the sleep patterns and HRV indices recorded by the Fitbit Inspire 2 were compared among these groups. The Mann-Whitney U test was used to assess differences between the quartiles, with adjustments made for multiple comparisons using the Bonferroni correction. Furthermore, EMA results and the sleep and HRV indices were subjected to multilevel analysis for a comprehensive evaluation. The EMA achieved a total response rate of 87.3%, while the Fitbit Inspire 2 wear rate reached 88.0%. When participants were grouped based on quartiles of well-being and stress-related scores, significant differences emerged. Specifically, individuals in the lowest stress quartile or highest subjective satisfaction quartile retired to bed earlier (P<.001 and P=.01, respectively), whereas those in the highest stress quartile exhibited greater variation in the midpoint of sleep (P<.001). A multilevel analysis unveiled notable relationships: intraindividual variability analysis indicated that higher energy levels were associated with lower deviation of heart rate during sleep on the preceding day (β=-.12, P<.001), and decreased sleepiness was observed on days following longer sleep durations (β=-.10, P<.001). Furthermore, interindividual variability analysis revealed that individuals with earlier midpoints of sleep tended to exhibit higher energy levels (β=-.26, P=.04). Increased sleep variabilities, characterized by unstable bedtime or midpoint of sleep, were correlated with elevated stress levels and diminished well-being. Conversely, improved sleep indices (eg, lower heart rate during sleep and earlier average bedtime) were associated with heightened daytime energy levels. Further research with a larger sample size using these methodologies, particularly focusing on specific phenomena such as social jet lag, has the potential to yield valuable insights. UMIN-CTR UMIN000046858; https://center6.umin.ac.jp/cgi-open-bin/ctr/ctr_view.cgi?recptno=R000053392.

Circadian misalignment proxies, BMI, and chronic conditions: the role for weekday to weekend sleep differences.

To evaluate whether social jet lag (SJL) and weekend catch-up sleep (CUS), proxies of circadian misalignment, were associated with BMI and chronic conditions. Participants (n = 2,050,18-65y) were part of a virtual cross-sectional and population-based research. We examined CUS and SJL as continuous and categorical (< 1h,1-2h, > 2h). Linear regression analyses were performed to assess the differences in BMI (outcome) associated with CUS and SJL. Restricted cubic splines were performed to explore the shape of the relationship between weekday-to-weekend variability in sleep duration, midpoint, wake time, and bedtime. Logistic regression models were used to estimate ORs(95%CIs) for chronic conditions and overweight related to CUS and SJL. Analyses were adjusted for sleep duration, biological and behavior-related variables. We found a positive association of SJL and CUS with BMI. The effects remained even after adjustment for weekly sleep duration and demonstrated a proportional increase with the magnitude of sleep variability. Among participants with SJL > 2h, BMI increased by 2.29kg/m2 (95%CI:0.84;3.74,p:0.002). They also had 129% higher odds of chronic conditions (95%CI:1.16;4.52, p:0.01) and 119% higher odds of overweight (95%CI: 1.20;3.98,p:0.01). Individuals with CUS > 2h presented 78% higher odds of overweight (95%CI:1.27;2.50,p:0.001) and an increase of 1.61kg/m2 in BMI (95%CI: 0.81; 2.40,p < 0.001). Our findings, which demonstrate that even a slight weekend sleep extension and variability of just 1h is associated with higher values of BMI, suggest incorporating measures for sleep consistency and regularity into clinical protocols and public health guidelines to prevent and treat obesity and related diseases.

Patterns of Sleep Duration and Metabolic Biomarkers Across the Menstrual Cycle.

Along the menstrual cycle, associations between inconsistent sleep duration and levels of metabolic biomarkers are uncertain and could involve fluctuations in estrogen concentrations. To examine associations between patterns of sleep duration and metabolic biomarkers across two menstrual cycles within a cohort of premenopausal women. The BioCycle Study was conducted in New York between 2005-2007, enrolling 259 premenopausal women over two menstrual cycles. This micro-longitudinal cohort study involved intensive data collection including daily sleep diaries and biomarker assessments of leptin, insulin, and glucose at 16 key points timed to menstrual cycle phases. We considered dynamic sleep duration, as hours slept one night or as mean hours slept during the two nights prior to each biomarker assessment. Variability in habitual sleep duration, i.e., reported daily sleep duration, summarized across both menstrual cycles. Variation in habitual sleep duration was computed using L-moments, a robust version of dispersion, skewness, and kurtosis. To examine associations between patterns of sleep duration and metabolic biomarkers, we fitted a series of linear mixed models with random intercepts and inverse probability weighting. These models were adjusted for potential demographic, lifestyle, health confounders, and menstrual cycle phase. Sleep duration one night or two nights prior to clinic visits were not associated with metabolic biomarker measures we assessed. However, overall variability (dispersion) in habitual sleep duration was associated with lower mean insulin HOMA-IR levels, but not glucose. Moreover, extreme short or long bouts of sleep duration was associated with higher mean levels of leptin, insulin, and HOMA-IR. These data suggest that variation in habitual sleep duration along the menstrual cycle may be associated with metabolic function.

Do Sleep Problems Exacerbate the Mental Health Consequences of Discrimination Among Adults?

An emerging literature suggests that sleep may play an important role in moderating the association between discrimination and mental health problems among adolescents. However, few if any studies have considered this topic among adults. Addressing this knowledge gap, the current study examined multiple sleep parameters as moderating variables in the association between discrimination and mental health problems among adults. Participants were 874 adults residing in small towns and semirural contexts within the Southeastern region of the United States ( Mage = 41 years, SD = 7; 57% female; 31% Black, 69% White; 52% income-to-needs < 2). Sleep duration and night-to-night variability in duration were assessed using wrist actigraphy. Established self-report measures were used to assess global sleep problems, experiences of discrimination, and mental health problems (anxiety, depression, and externalizing symptoms). Experiences of discrimination were associated with more depression, anxiety, and externalizing problems. Two out of three sleep parameters were found to moderate the effects of discrimination on mental health. The association between discrimination and externalizing problems (but not anxiety or depression) was attenuated among those with less night-to-night variability in sleep duration. The associations between discrimination and anxiety and externalizing problems (but not depression) were attenuated among those with fewer global sleep problems. Less variability in sleep duration and fewer global sleep problems were also directly associated with lower levels of depression, anxiety, and externalizing problems. Greater consistency in sleep duration from night-to-night, and fewer overall sleep problems appear to mitigate risk of mental health problems among adults, particularly in contexts where discrimination is prevalent.

Unraveling the interplay between chronobiology, circadian rhythm, and gut microbiome dynamics in human health

Background: This study investigates the intricate interplay between disrupted circadian rhythms, sleep variations, and gut microbiota dynamics, recognizing their bidirectional influences on human health. The relationships are explored through the brain-gut-microbiota axis, emphasizing the importance of maintaining a harmonious balance for overall well-being. Methods: A selection criteria was determined after a thorough literature review across search engines and databases. SANRA guidelines were followed to draft the manuscript. Objectives: To elicit the interplay between sleep patterns, chronobiology, and circadian rhythm influence the composition and functionality of the gut microbiome in human participants. Results: Disruptions in circadian rhythms impact gut microbiota composition, leading to dysbiosis and pathological mechanisms. Reciprocally, variations in sleep duration and quality influence the diversity and function of the gut microbiome. Identified microbial patterns associated with different circadian phases reveal nuanced connections, highlighting the broader implications of circadian rhythm disruption on human health.

Abstract 23: Multidimensional Association of Sleep With Health Behaviors and Cardiometabolic Risk in Adolescents

Introduction: Insufficient sleep has been recognized by AHA as part of Life’s Essential 8 in the prevention of cardiovascular disease (CVD). While sleep is a multidimensional phenomenon comprised of duration, efficiency, quality, timing, and regularity, prior epidemiological research in youth has predominantly focused on sleep duration. It is important to disentangle which sleep dimensions most associate with other health behaviors and biomarkers for CVD risk in adolescents. Hypothesis: We hypothesize that specific dimensions of insufficient, disturbed, and misaligned sleep will be differentially associated with nutrition, physical activity, and inflammation. Methods: We analyzed data from 421 population-based randomly-selected adolescents from the Penn State Child Cohort (median 16 years; 47% female; 21% racial/ethnic minority) who had at least 5-night at-home actigraphy (ACT), 1-night in-lab 9-h polysomnography (PSG), self-reported insomnia symptoms, daytimes sleepiness, sleep schedule, circadian preference, and dietary assessment, as well as fasting blood draw assayed for C-reactive protein (CRP), interleukin-6 (IL-6), and tumor necrosis factor alpha (TNFα). Linear regression models tested the independent association of each sleep dimension with caloric intake, ACT-derived sedentary behavior, and blood-based inflammatory biomarkers, while accounting for sex, age, race/ethnicity, and body mass index. Results: Higher ACT-measured night-to-night variability in sleep duration was most strongly associated with increased caloric intake, particularly carbohydrates (B=0.203, p&lt;0.001), while shorter PSG-measured sleep duration was also associated with carbohydrates but to a lesser extent (B=-0.150, p=0.002). Later bedtime on weekdays was most strongly associated with higher bouts of sedentary behavior (B=0.216, p&lt;0.001), while shorter ACT-measured sleep duration was most strongly associated with time spent sedentary (B=-0.226, p&lt;0.001). PSG-measured sleep apnea was most strongly associated with higher CRP (B=0.287, p&lt;0.001) and IL-6 levels (B=0.260, p&lt;0.001), while later bedtime on weekdays (B=0.136, p=0.025) and evening circadian preference (B=-0.124, p=0.017) were also associated with inflammation but to a lesser extent. Conclusions: The association of inadequate sleep with health behaviors and cardiometabolic risk in adolescents is in itself multidimensional. These data support that AHA guidelines should be updated to include insufficient, disturbed, and misaligned sleep as contributors to CVD risk.

Preventive noninvasive vagal nerve stimulation reduces insufficient sleep-induced depression by improving the autonomic nervous system

BackgroundDepression is closely linked to an imbalance in the autonomic nervous system (ANS). However, the role of this imbalance in mediating the effects of sleep deprivation (SD) and vagus nerve stimulation (VNS) on emotional well-being is not fully understood. MethodsA population-based analysis was conducted to explore the relationship between sleep duration, depression scores, and heart rate variability (HRV). Additionally, the chronic SD mouse model was established to assess the impact of preventive transcutaneous auricular VNS (taVNS) on pathological and behavioral changes. ResultsOur study found a significant link between sleep duration, depression severity, and HRV. Shorter sleep duration was associated with higher depression scores and lower RMSSD (a measure of HRV). In our rat model, insufficient sleep consistently impaired HRV. This effect was mitigated by taVNS, accompanied by corresponding changes in levels of IL-1β and IL-6, astrocyte and microglia activation, and tail suspension times. ConclusionsUsing VNS as a preventive treatment for depression-risk individuals with insufficient sleep shows promise. It not only broadens the potential applications of VNS but also sheds light on its mechanism—particularly its role in enhancing vagal nerve function and balancing the ANS, as evidenced by HRV measurements.

Cross-sectional associations of actigraphy-assessed sleep with dietary outcomes in emerging adults.

Emerging adults (~18-28 years of age) have a high prevalence of poor sleeping habits and poor diet quality; however, little is known on whether these poor sleeping habits are associated with dietary outcomes in this age group. This study assessed associations between actigraphy-based sleep with energy intake (EI), overall diet quality, and measures of meal timing in emerging adults. Data on 135 emerging adults (age = 19.4 ± 1.3 years; body mass index (BMI) = 26.5 ± 6.9 kg/m2; 58% female; 65% White) from the RIGHT Track Health project were used. Measures included actigraphy-assessed sleep duration, sleep efficiency, sleep timing midpoint, day-to-day sleep duration and sleep timing midpoint variability and combined sleep duration and sleep timing behaviors (early-bed/late-rise, early-bed/early-rise, late-bed/late-rise, late-bed/early-rise); EI (three 24-h dietary recalls), diet quality (Healthy Eating Index 2015 total score) and meal timing outcomes (timing of first and last meal intake, total duration, and midpoint of the eating window). Shorter sleep duration, later sleep timing midpoint and greater sleep efficiency, as well as combined late-bed/late-rise and late-bed/early-rise groups, were associated with lower diet quality. Greater sleep timing midpoint variability was associated with higher EI, and the late-bed/early-rise group had significantly delayed first meal timing. In emerging adults, shorter sleep duration and later sleep timing are associated with lower overall diet quality, and greater sleep timing variability is associated with higher EI. Future research is needed to examine the role of sleep on diet quality and eating habits to identify potential targets for nutritional interventions in this age group.