Midpoint Of Sleep Research Articles

Chronotype predicts working memory-dependent regional cerebral oxygenation under conditions of normal sleep and following a single night of sleep extension

The aim of this study was to test the hypothesis that the association between sleep duration and brain activation as assessed by regional cerebral oxygenation using near-infrared spectroscopy (NIRS) is dependent on chronotype. Sleep was tracked across two weeks by actigraphy in 22 adults instructed to keep their normal sleep behavior. Chronotype was assessed by the midpoint of sleep on free days corrected for sleep debt on workdays (MSFsc). Prefrontal cerebral oxygenation (ΔHbDiff) during a visuospatial working memory task was measured in the morning after a night of normal sleep and after one night of extended sleep. Sleep extension was included to experimentally test the robustness of the association between sleep duration and ΔHbDiff. Habitual sleep duration (r = 0.43, p = 0.04) and MSFsc (r = − 0.66, p < 0.001) were significantly correlated with ΔHbDiff. After adjusting for MSFsc the relationship between sleep duration and ΔHbDiff was reduced to nonsignificant levels (r = 0.34, p = 0.11), while adjusting for sleep duration did not change the significant relationship between MSFsc and ΔHbDiff (r = − 0.62, p = 0.001). One night of sleep extension increased sleep duration by 140 min, on average, but no change in ΔHbDiff was observed. Dividing participants into earlier and later chronotypes revealed greater ΔHbDiff responses in earlier chronotypes that persisted after the night of sleep extension (mean ΔHbDiff difference = 1.35 μM, t = 2.87, p = 0.006, Hedges’ g = 0.89). These results find chronotype to predict regional cerebral oxygenation responses during working memory processing under conditions of normal sleep and following a single night of sleep extension.

Associations between social jetlag trajectories and body mass index among young adults.

This study employed longitudinal data collected repeatedly from individuals over the course of several years to examine the trajectories of social jetlag from ages 11 to 22 years and their associations with subsequent body mass index (BMI). Potential sex differences were also investigated. Data were obtained from two longitudinal studies conducted in Taiwan (N = 4287). Social jetlag was defined as ≥ 2 hours of absolute difference in sleep midpoint between weekdays and weekends. BMI was calculated using weight (kg)/height(m)2 and categorized as underweight (<18 kg/m2), normal weight (18 kg/m2 ≤ BMI < 24 kg/m2), overweight (24 kg/m2 ≤ BMI < 27 kg/m2), and obese (≥27 kg/m2). Group-based trajectory modeling and multinomial logistic regression were applied to investigate study objectives. Four distinct trajectories of social jetlag throughout the adolescent years were identified, with corresponding proportions as follows: low-stable (42%), moderate-decreasing (19%), low-increasing (22%), and chronic (17%) trajectories. Among males, the risk of being underweight (aOR, 1.96; 95% CI: 1.35 to 2.84) or obese (aOR, 1.40; 95% CI: 1.02 to 1.92) was higher in individuals with a low-increasing trajectory than in those with a low-stable trajectory. Among females, those with a low-increasing (aOR, 1.61; 95% CI: 1.02 to 2.54) or chronic (aOR, 2.04; 95% CI: 1.27 to 3.25) trajectory were at a higher risk of being obese relative to those with a low-stable trajectory. Addressing the development of increasing or chronic social jetlag during adolescence can help prevent abnormal BMI in young adulthood. Practitioners should consider sex differences in treatment or consultation.

Sleep Variability, Sleep Irregularity, and Nighttime Blood Pressure Dipping.

Circadian rhythm regulates many important biological functions in humans. The goal of this study is to explore the impact of day-to-day deviations in the sleep-wake cycle on nighttime blood pressure (BP) dipping and further examine whether the ethnic difference in day-to-day deviations in sleep patterns can explain the ethnic difference in nighttime BP dipping. Twenty-four-hour ambulatory BP monitoring and 7-day accelerometer data were obtained from 365 adult participants (age range, 18.7-50.1 years; 52.6% Black participants and 47.3% European Americans; 64.1% females). Systolic BP dipping level was used to represent nighttime BP dipping. The SD of sleep duration was calculated as the index of sleep variability, and the SD of sleep midpoint was calculated as the index of sleep irregularity. A 1-hour increase in the SD of sleep midpoint was associated with a 1.16% decrease in nighttime BP dipping (P<0.001). A 1-hour increase in the SD of sleep duration was associated with a 1.39% decrease in nighttime BP dipping (P=0.017). The ethnic difference in the SD of sleep midpoint can explain 29.2% of the ethnicity difference in BP dipping (P=0.008). Sleep variability and sleep irregularity are associated with blunted BP dipping in the general population. In addition, data from the present investigation also demonstrate that the ethnic difference in sleep irregularity could partly explain the ethnic difference in BP dipping, an important finding that may help reduce the health disparity between Black participants and European Americans.

Circadian misalignment impacts the association of visceral adiposity with metabolic syndrome in adolescents.

Although insufficient sleep is a risk factor for metabolic syndrome (MetS), the circadian timing of sleep (CTS) is also involved in cardiac and metabolic regulation. We examined whether delays and deviations in the sleep midpoint (SM), a measure of CTS, modify the association between visceral adipose tissue (VAT) and MetS in adolescents. We evaluated 277 adolescents (median 16 years) who had at least 5 nights of at-home actigraphy (ACT), in-lab polysomnography (PSG), dual-energy X-ray absorptiometry (DXA) scan, and MetS score data. Sleep midpoint (SM), sleep irregularity (SI), and social jetlag (SJL) were examined as effect modifiers of the association between VAT and MetS, including waist circumference, blood pressure, insulin resistance, triglycerides, and cholesterol. Linear regression models adjusted for demographics, ACT-sleep duration, ACT-sleep variability, and PSG-apnea-hypopnea index. The association between VAT and MetS was significantly stronger (p-values for interactions < 0.001) among adolescents with a schooldays SM later than 4:00 (2.66 [0.30] points increase in MetS score), a SI higher than 1 hour (2.49 [0.30]) or a SJL greater than 1.5 hours (2.15 [0.36]), than in those with an earlier SM (<3:00; 1.76 [0.28]), lower SI (<30 minutes; 0.98 [0.70]), or optimal SJL (<30 minutes; 1.08 [0.45]). A delayed sleep phase, an irregular sleep-wake cycle, and greater social jetlag on schooldays identified adolescents in whom VAT had a stronger association with MetS. Circadian misalignment is a risk factor that enhances the impact of visceral obesity on cardiometabolic morbidity and should be a target of preventative strategies in adolescents.

Social and built neighborhood environments and sleep health: The Hispanic Community Health Study/Study of Latinos Community and Surrounding Areas and Sueño Ancillary Studies.

To test associations between neighborhood social, built, and ambient environment characteristics and multidimensional sleep health in Hispanic/Latino adults. Data were from San Diego-based Hispanic/Latino adults mostly of Mexican heritage enrolled in the Hispanic Community Health Study/Study of Latinos (N = 342). Home addresses were geocoded to ascertain neighborhood characteristics of greenness, walkability (density of intersections, retail spaces, and residences), socioeconomic deprivation (e.g. lower income, lower education), social disorder (e.g. vacant buildings, crime), traffic density, and air pollution (PM 2.5) in the Study of Latinos Communities and Surrounding Areas Study. Sleep dimensions of regularity, satisfaction, alertness, timing, efficiency, and duration were measured by self-report or actigraphy approximately 2 years later. Multivariable regression models accounting for study design (stratification and clustering) were used to examine associations of neighborhood variables with individual sleep dimensions and a multidimensional sleep health composite score. Neighborhood characteristics were not significantly associated with the multidimensional sleep health composite, and there were few significant associations with individual sleep dimensions. Greater levels of air pollution (B = 9.03, 95% CI: 1.16, 16.91) were associated with later sleep midpoint, while greater social disorder (B = -6.90, 95% CI: -13.12, -0.67) was associated with earlier sleep midpoint. Lower walkability was associated with more wake after sleep onset (B = -3.58, 95% CI: -7.07, -0.09). Living in neighborhoods with lower walkability and greater air pollution was associated with worse sleep health, but otherwise findings were largely null. Future research should test these hypotheses in settings with greater variability and investigate mechanisms of these associations.

Clinical Phenotypes Supporting the Relationship Between Sleep Disturbance and Impairment of Placebo Effects

Lack of good sleep or insomnia can lead to many health issues, including an elevated risk of cardiovascular disease, obesity, fatigue, low mood, and pain. While chronic pain negatively impacts sleep quality, the relationship between descending pain modulatory systems like placebo effects and sleep quality is not thoroughly known. We addressed this aspect in a cross-sectional study in participants with chronic pain. Placebo effects were elicited in a laboratory setting using thermal heat stimulations delivered with visual cues using classical conditioning and verbal suggestions. We estimated the levels of insomnia severity with the Insomnia Severity Index and the sleep quality with the Pittsburg Sleep Quality Index. The previous night’s sleep continuity was assessed as total sleep time, sleep efficiency, and sleep midpoint the night before the experiment. 277 people with chronic pain and 189 pain-free control individuals participated. Participants with chronic pain and insomnia showed smaller placebo effects than those with chronic pain without insomnia. Similarly, poor sleep quality was associated with reduced placebo effects among participants with chronic pain. Clinical anxiety measured by Depression Anxiety Stress Scales partially mediated these effects. In contrast, placebo effects were not influenced by the presence of insomnia or poor sleep quality in pain-free participants. Sleep continuity the night before the experiment did not influence the placebo effects. Our results indicate that participants who experience insomnia and/or poor sleep quality and chronic pain have smaller placebo effects, and that the previous night sleep continuity does not influence the magnitude of placebo effects. PerspectiveThis study examined the relationship between sleep disturbances and experimentally induced placebo effects. We found that individuals with chronic pain who experience insomnia and poor sleep quality demonstrated reduced placebo effects compared to their counterparts with good sleep quality and no insomnia.

Association between Sleep Timing, Being Overweight and Meal and Snack Consumption in Children and Adolescents in Southern Brazil.

Sleep timing is one of the dimensions of sleep that refers to the time of day when sleep occurs. It has been included in sleep-related research because of the potential associations between being overweight and the consumption of meals and snacks. This cross-sectional study aimed to investigate associations between sleep timing, meal and snack consumption and weight status in 1333 schoolchildren aged 7-14 years. The midpoint of sleep was used as a sleep timing measure obtained by the midpoint between bedtime and wake-up time, classified as Early, Intermediate, and Late. Schoolchildren in the Early group were less likely to be overweight (OR: 0.83, 95% CI 0.69; 0.99), and had higher odds of mid-morning snack consumption (OR: 1.95, 95% CI 1.56; 2.44) and lower probability to consume an evening snack (OR: 0.75, 95% CI 0.59; 0.94) compared with the Intermediate group. The Late group had lower odds of mid-morning snack consumption (OR: 0.67, 95% CI 0.55, 0.80) than the Intermediate group. The consumption of mid-morning and evening snacks was associated with the Early and Late midpoints of sleep. These results suggest that bedtime and wake-up time are relevant to consuming meals and snacks and may also be related to a greater probability of being overweight in children and adolescents.

Concordance in parent-child and sibling actigraphy-measured sleep: Evidence among early adolescent twins and primary caregivers

Study objectivesGrowing evidence suggests concordance between parent and youth sleep. However, no known study has simultaneously examined concordance among siblings’ sleep patterns. This study investigated daily and average concordance in (1) parent-youth and (2) sibling actigraphy-measured sleep, as well as the degree to which sibling concordance varied by sleeping arrangements. Methods516 twin siblings (Mage = 10.74, 51% female; 30% monozygotic (MZ) twin pairs, 37% same-sex dizygotic pairs (DZ-ss), 33% opposite-sex DZ pairs (DZ-os)) and their primary caregivers (Mage = 40.59, 95% female) wore wrist-based accelerometers for 7 consecutive nights to measure sleep duration, efficiency, midpoint time, and latency. Primary caregivers also reported on demographics, youth pubertal status, and room-sharing. Two-level multilevel models were estimated to examine daily and average concordance in parent-youth and sibling sleep. ResultsDaily concordance was observed between parent and youth sleep duration and midpoint; average concordance was found for sleep duration, midpoint, and latency. Within sibling dyads, daily and average concordance was evident across all sleep parameters (duration, efficiency, midpoint, latency), with generally stronger concordance patterns for MZ than DZ twin pairs, and for twins who shared a room with their co-twin. ConclusionsThis is the first known study to document concordance among parent-youth and siblings’ actigraphy-measured sleep within the same study (i.e., triad). Our findings can help inform the development of family-level interventions targeting daily and overall sleep hygiene.

Nonlinear relationship between sleep midpoint and depression symptoms: a cross-sectional study of US adults

BackgroundDespite the close relationship between sleep–wake cycles and depression symptoms, the relationship between sleep midpoint and depression symptoms in adults remains understudied.MethodsIn this cross-sectional study, 18280 adults aged ≥ 18 years from the National Health and Nutrition Examination Survey (NHANES) 2015–2020 were analyzed. Covariates included age, sex, race/ethnicity, education level, marital status, family income, body mass index, smoking status, drinking status, physical activity, comorbid condition, sleep duration, and sleep disturbance were adjusted in multivariate regression models.ResultsWeighted restricted cubic spline based on the complex sampling design of NHANES showed that in participants with a sleep midpoint from 2:18 AM to 6:30 AM, the prevalence of depression symptoms increased by 0.2 times (adjusted odds ratio [OR] = 1.20, 95% confidence interval [CI]: 1.08–1.33) per 1-h increment in sleep midpoint compared to the reference point of 2:18 AM. For participants with a sleep midpoint after 6:30 AM and before 2:18 AM the next day, the relationship between sleep midpoint and depression symptoms was not significant after adjusting for all covariates (adjusted OR = 1.01, 95% CI: 0.99–1.03).ConclusionsThe findings indicate a significant nonlinear association between sleep midpoint and depression symptoms in a nationally representative sample of adults.

Association of Gut Microbiota With Objective Sleep Measures in Women With and Without Human Immunodeficiency Virus Infection: The IDOze Study.

Poor sleep health is an underrecognized health challenge, especially for people with human immunodeficiency virus (HIV). Gut microbiota related to sleep are underinvestigated. The IDOze microbiota substudy included 190 women (114 with HIV and 76 without HIV). Wrist actigraphy measured total sleep duration, sleep efficiency, number of wake bouts, wake after sleep onset, fragmentation index, and sleep timing. 16S rRNA gene sequencing identified gut microbial genera. Analysis of compositions of microbiomes with bias correction was used to investigate cross-sectional associations between gut microbiota and sleep. Abundances of sleep-related gut microbial genera were compared between women with and without HIV. Enrichment of 7 short-chain fatty acid-producing genera (eg, Butyricimonas, Roseburia, and Blautia) was associated with lower fragmentation index. Enrichment of 9 genera (eg, Dorea) was associated with lower sleep efficiency and/or more wake after sleep onset. Enrichment of proinflammatory Acidaminococcus was associated with late sleep midpoint and offset time. These associations were largely consistent regardless of HIV status. The abundance of Butyricimonas was lower among women with HIV compared to those without HIV. Seventeen genera were identified to be associated with sleep continuity or timing. Butyricimonas, a potentially beneficial genus associated with sleep continuity, was less abundant among women with HIV.

Day-to-day deviations in sleep parameters and biological aging: Findings from the NHANES 2011-2014

ObjectivesThe majority of the previous research has focused on the impact of average sleep parameters on longevity. In this study, we aimed to investigate the associations of day-to-day deviations in sleep parameters with biological ages among 6052 adults participating in the 2011-2014 waves of the US National Health and Nutrition Examination Survey. MethodsSleep parameters, including sleep duration, efficiency, midpoint, and day-to-day deviations in sleep parameters, including standard deviation of sleep duration (sleep variability), standard deviation of sleep midpoint (sleep irregularity), catch-up sleep, and social jetlag, were obtained from 4 to 7 days of 24-h accelerometer recording. We used physiological data to compute measurements of biological aging according to 3 published algorithms: PhenoAge, Klemera-Doubal method Biological Age, and homeostatic dysregulation. ResultsAfter adjustment of multiple covariates, we observed that all parameters of day-to-day deviations in sleep were significantly associated with biological aging with larger sleep variability, larger sleep irregularity, more catch-up sleep, and more social jetlag linked with more advanced biological aging. The significant associations of sleep irregularity, catch-up sleep, and social jetlag with biological aging indices remained even after adjustment for sleep duration, efficiency, and midpoint. ConclusionIn this study, we found that day-to-day deviations in sleep parameters are independently associated with biological aging in US general population. Since day-to-day deviation in sleep is a modifiable behavioral factor, our finding suggests that intervention aiming at increasing regularity in sleep patterns may be a novel approach for extending a healthy life span.

Associations of the timing of sleep and meals with the presence of gastroesophageal reflux disease in community-dwelling women in Japan.

It has been suspected that circadian rhythms may play a part in the pathogenesis of gastrointestinal diseases including gastroesophageal reflux disease (GERD). The present study aimed to examine the cross-sectional association of the timing of sleep and meals with the presence of GERD in community-dwelling women in Japan. In total, 605 women responded to a self-administered questionnaire asking for information on GERD symptoms, sleep habits, sleep disturbances and the timing of meals. GERD symptoms were evaluated using the Frequency Scale for the Symptoms of GERD, and participants with a score of more than seven points were classified as having GERD. In total, 104 (17.2%) women were found to have GERD. Later bedtime on both weekdays and weekends and later midpoint of sleep were significantly associated with the odds ratios (OR) of GERD after controlling for covariates: ORs for each 1 h delay were 1.31 (95% confidence interval [CI] = 1.03-1.68), 1.38 (95% CI = 1.08-1.75) and 1.43 (95% CI = 1.06-1.95). Having lunch at irregular times was significantly associated with the increased OR of GERD (1.99; 95% CI = 1.02-3.91). Longer overnight fasting duration and longer time intervals from the midpoint of sleep to breakfast and lunch were significantly associated with decreased OR of GERD (ORs for each 1 h increase were 0.73 [95% CI = 0.56-0.95], 0.64 [95% CI = 0.46-0.88] and 0.70 [95% CI = 0.51-0.96]). These data suggest that the timing of sleep and timing of meals relative to the sleep/wake cycle are associated with the presence of GERD.

Prolonged Use of an Automated Insulin Delivery System Improves Sleep in Long-Standing Type 1 Diabetes Complicated by Impaired Awareness of Hypoglycemia.

This study assessed changes in actigraphy-estimated sleep and glycemic outcomes after initiating automated insulin delivery (AID). Ten adults with long-standing type 1 diabetes and impaired awareness of hypoglycemia (IAH) participated in an 18-month clinical trial assessing an AID intervention on hypoglycemia and counter-regulatory mechanisms. Data from eight participants (median age = 58 years) with concurrent wrist actigraph and continuous glucose monitoring (CGM) data were used in the present analyses. Actigraphs and CGM measured sleep and glycemic control at baseline (one week) and months 3, 6, 9, 12, 15, and 18 (three weeks) following AID initiation. HypoCount software integrated actigraphy with CGM data to separate wake and sleep-associated glycemic measures. Paired sample t-tests and Cohen's d effect sizes modeled changes and their magnitude in sleep, glycemic control, IAH (Clarke score), hypoglycemia severity (HYPO score), hypoglycemia exposure (CGM), and glycemic variability (lability index [LI]; CGM coefficient-of-variation [CV]) from baseline to 18 months. Sleep improved from baseline to 18 months (shorter sleep latency [P < .05, d = 1.74], later sleep offset [P < .05, d = 0.90], less wake after sleep onset [P < .01, d = 1.43]). Later sleep onset (d = 0.74) and sleep midpoint (d = 0.77) showed medium effect sizes. Sleep improvements were evident from 12 to 15 months after AID initiation and were preceded by improved hypoglycemia awareness (Clarke score [d = 1.18]), reduced hypoglycemia severity (HYPO score [d = 2.13]), reduced sleep-associated hypoglycemia (percent time glucose was < 54 mg/dL, < 60 mg/dL,< 70 mg/dL; d = 0.66-0.81), and reduced glucose variability (LI, d = 0.86; CV, d = 0.62). AID improved sleep initiation and maintenance. Improved awareness of hypoglycemia, reduced hypoglycemia severity, hypoglycemia exposure, and glucose variability preceded sleep improvements.This trial is registered with ClinicalTrials.gov NCT03215914 https://clinicaltrials.gov/ct2/show/NCT03215914.

Greater sleep variability is associated with higher systemic inflammation in type 2 diabetes.

Sleep irregularity and variability have been shown to be detrimental to cardiometabolic health. The present pilot study explored if higher day-to-day sleep irregularity and variability were associated with systemic inflammation, as assessed by high-sensitivity C-reactive protein, in type 2 diabetes. Thirty-five patients with type 2 diabetes (mean age 54.3 years, 54.3% female) who were not shift-workers participated. The presence of diabetic retinopathy was determined. The standard deviation of sleep duration and sleep midpoint across all recorded nights were used to quantify sleep variability and regularity, respectively, assessed by 14-day actigraphy. The presence and severity of sleep apnea were assessed using an overnight home monitor. Low-density lipoprotein, haemoglobin A1C and high-sensitivity C-reactive protein were collected. Multiple regression analysis using natural-log-transformed values was performed to establish an independent association between sleep variability and high-sensitivity C-reactive protein. Twenty-two (62.9%) patients had diabetic retinopathy. The median (interquartile range) of high-sensitivity C-reactive protein was 2.4 (1.4, 4.6) mg L-1. Higher sleep variability was significantly associated with higher high-sensitivity C-reactive protein (r = 0.342, p = 0.044), as was haemoglobin A1C (r = 0.431, p = 0.010) and low-density lipoprotein (r = 0.379, p = 0.025), but not sleep regularity, sleep apnea severity or diabetic retinopathy. Multiple regression analysis showed that higher sleep variability (B = 0.907, p = 0.038) and higher HbA1c (B = 1.519, p = 0.035), but not low-density lipoprotein, contributed to higher high-sensitivity C-reactive protein. In conclusion, higher sleep variability in patients with type 2 diabetes who were not shift-workers was independently associated with higher systemic inflammation, conferring increased cardiovascular risk. Whether sleep interventions to reduce sleep variability can reduce systemic inflammation and improve cardiometabolic health should be investigated.

Consistency of chronotype measurements is affected by sleep quality, gender, longitude, and latitude

ABSTRACT Chronotype has received increasing research attention. However, there remains some confusion about the influence of gender, age, sleep quality, insomnia severity, longitude, and latitude on the consistency of the chronotype measured by the different tools. Chronotype measurement indicators were collected from 421 participants. The midpoint of sleep for actigraphy (MSF_A), sleep diary (MSF_D), and Munich Chronotype Questionnaire (MCTQ) (MSFsc) on free days and the Morningness-Eveningness Questionnaire (rMEQ) scores were used to measure the chronotype. In addition, demographic information, Pittsburgh Sleep Quality Index (PSQI), and Insomnia Severity Index (ISI) were also collected. A significant correlation was identified between the questionnaires (MSF_D, MSFsc, rMEQ) and actigraphy (MSF_A) as measures of chronotype. MSF_A was associated with sleep latency and sleep disturbance in the PSQI subdimensions. The correlation between MS_D and sleep disturbance was significant. Both rMEQ and MSFsc were significantly correlated with PSQI (total scores and daytime dysfunction) and ISI. The consistency of all chronotype measurements for the questionnaires and actigraphy was influenced by gender. Among them, MSF_D is also affected by age, while only the latitude and sleep disturbance effect was found in the MSFsc. The influence of age, gender, sleep quality, and latitude should be emphasized when measuring the chronotype using self-reported methods.

Comparison of actigraphy-measured and parent-reported sleep in association with weight status among preschool children.

This study compared weekday and weekend actigraphy-measured and parent-reported sleep in relation to weight status among preschool-aged children. Participants were 3-6 years old preschoolers from the cross-sectional DAGIS-study with sleep data for ≥2 weekday and ≥2 weekend nights. Parents-reported sleep onset and wake-up times were gathered alongside 24 h hip-worn actigraphy. An unsupervised Hidden-Markov Model algorithm provided actigraphy-measured night time sleep without the guidance of reported sleep times. Waist-to-height ratio and age-and-sex-specific body mass index characterised weight status. Comparison of methods were assessed with consistency in quintile divisions and Spearman correlations. Associations between sleep and weight status were assessed with adjusted regression models. Participants included 638 children (49% girls) with a mean ± SD age of 4.76 ± 0.89. On weekdays, 98%-99% of actigraphy-measured and parent-reported sleep estimates were classified in the same or adjacent quintile and were strongly correlated (rs = 0.79-0.85, p < 0.001). On weekends, 84%-98% of actigraphy-measured and parent-reported sleep estimates were respectively classified and correlations were moderate to strong (rs = 0.62-0.86, p < 0.001). Compared with actigraphy-measured sleep, parent-reported sleep had consistently earlier onset, later wake-up, and greater duration. Earlier actigraphy-measured weekday sleep onset and midpoint were associated with a higher body mass index (respective β-estimates: -0.63, p < 0.01 and -0.75, p < 0.01) and waist-to-height ratio (-0.004, p = 0.03 and -0.01, p = 0.02). Though the sleep estimation methods were consistent and correlated, actigraphy measures should be favoured as they are more objective and sensitive to identifying associations between sleep timing and weight status compared with parent reports.

Onsite versus home-office: differences in sleep patterns according to workplace.

This study aimed to evaluate the sleep patterns of students and employees working onsite versus those working from home during the COVID-19 pandemic using actigraphy. A total of 75students/employees (onsite: N = 40, home-office: N = 35; age range:19-56years; 32% male; 42.7% students, 49.3% employees) were studied between December2020 and January2022 using actigraphy, asleep diary, and an online questionnaire assessing sociodemographics and morningness-eveningness. Independent-sample t-tests, paired-sample tests, and amultivariate general linear model adjusting for age (fixed factors: sex and work environment) were applied. Overall, onsite workers had significantly earlier rise times (7:05 [SD: 1:11] versus 7:44 [1:08] hours) and midpoints of sleep (2:57 [0:58] versus 3:33 [0:58] hours) on weekdays compared to home-office workers. Sleep efficiency, sleep duration, variability of sleep timing, and social jetlag did not differ between the groups. Home-office workers showed adelay in sleep timing that did not affect any other sleep parameters such as sleep efficiency or nighttime sleep duration. The work environment had only marginal impact on sleep patterns and thus sleep health in this sample. Sleep timing variability did not differ between groups. The online version of this article (10.1007/s11818-023-00408-5) contains supplementary material1 and2, which is available to authorized users.

0764 End of daylight saving and sleep children 4-24 months

Abstract Introduction Daylight saving time (DST) imposes a twice yearly 1h change in local clock time. Although it may seem a small adjustment, there is increasing awareness of the potential acute and long term effects at the individual and population level. Several studies have shown detrimental effects on sleep patterns, but mostly focusing on adults. Only one study has looked at the effect in infants’ sleep of change from standard time (ST) to DST, reporting negative effects. One study limitation was the reliance on parental reports of infant sleep. In addition, effects of the change from DST to ST are unknown. We hypothesize that the change from DST to ST would lead to earlier rise times, leading to sleep loss in the week following the change. Methods Caregivers of 510 children ages 3-24 mos (M=9.8 mos) tracked their child’s sleep using Nanit baby-monitor. Sleep metrics analyzed were: Nighttime sleep duration (NSD) and midpoint, number of night-wakings and sleep efficiency. Wilcoxon rank sum tests compared the average of each sleep metric for the week preceding the time change (Oct 31st-Nov 4th 2022, Baseline) with sleep metrics for each night of the following week (Nov 7-11 2022, post-DST week). Analyses were repeated stratifying by age group (4-6,7-12 and 13-24 months). Results After the time change, there was no change in NSD or sleep efficiency. There was a significant decrease in the number of night-wakings for infants 3-6 months, with an average of 0.5 fewer wakings per night compared to Baseline (Baseline mean=5 wakings). Midpoint was significantly earlier for all ages by an average of 10min, every day of the post-DST week. Conclusion The return to ST affected infants’ sleep midpoint. Observed effects were minor compared to those reported in previous literature for the ST to DST change, in line with other fields like cardiovascular health. This easier adjustment could be attributed to the fact that during DST there is an increased mismatch between body clock and social clock time, thus infants more readily adjust to a return to ST which minimizes this mismatch. Support (if any) This research was supported by Nanit

0114 Interplay of School and Free Days on the Association of Circadian Misalignment with Heart Rate Variability in Adolescents

Abstract Introduction The circadian timing system, which governs the sleep-wake cycle, is involved in cardiometabolic and autonomic regulation. Heart rate variability (HRV), a marker of cardiac autonomic modulation (CAM), is known to predict cardiovascular morbidity. Therefore, circadian misalignment of the sleep-wake cycle, which is highly prevalent in adolescents and may express differently if youth are in school or free-days, is likely to impact CAM. We examined whether deviations in the circadian timing of sleep are associated with blunted HRV in adolescents as a function of being entrained to school or not. Methods We studied 337 population-based randomly-selected adolescents from the Penn State Child Cohort (median 16 years; 47% female; 21% racial/ethnic minority) who had at least 3-night at-home actigraphy (ACT), in-lab 9-h polysomnography (PSG) and 24-h Holter-monitoring heart rate variability (HRV) data. ACT-measured sleep midpoint (SM) was calculated as the midpoint of the sleep period for weekdays (5-nights) and weekends (2-nights), whereas ACT-measured sleep regularity (SR) was calculated as the intra-individual standard deviation of the SM across 5- and 7-nights. Frequency and time-domain HRV indices were primary outcomes. Linear regression models were stratified by “in school” and “on break” to test SM and SR as predictors of HRV indices while accounting for sex, race/ethnicity, age, BMI percentile, ACT-sleep duration, ACT-sleep variability, and PSG-apnea/hypopnea index. Results Lower SR on schooldays was associated with lower nighttime Log-HF, Log-LF and SDNN, yet higher HR (all p&amp;lt; 0.01); e.g., each standard deviation increase in SR on schooldays (i.e., 45m higher) was associated with -7.15ms (2.57) in nighttime SDNN (p=0.006). A later SM on free weekends was associated with lower nighttime Log-HF, Log-LF, SDNN and RMSSD, yet higher HR and LF-HF ratio (all p&amp;lt; 0.03); e.g., each standard deviation increase in SM on free weekends (i.e., 1.5h later) was associated with -7.33ms (2.85) in nighttime RMSSD (p=0.011). Conclusion A delayed and an irregular sleep midpoint during breaks and during schooldays, respectively, were associated with impaired CAM in adolescents. These data suggest that not only circadian misalignment contributes to adverse cardiovascular outcomes but its distinct metrics require measurement under different entrainment conditions in adolescents. Support (if any) NIH (R01HL136587,R01MH118308,UL1TR000127), American Heart Association (23PRE1011962).

0124 The influence of the family environment on children’s sleep during the school year and summer

Abstract Introduction More than a third of US children do not receive adequate sleep. Earlier bedtimes, consistent bedtime routines, and good sleep hygiene help to support more adequate sleep. Our previous work has shown that during summer, 5-8-year-old children go to bed later and obtain less sleep compared to the school year. We hypothesized that school year-summer differences in the family environment would explain differences in children’s sleep timing during these periods. Methods During the school year and summer, 119 parents of 5–8-year-olds completed measures of child temperament, sleep hygiene, parenting practices, and parent stress and social support. Child sleep was measured for 8 days using wrist actigraphs. Sleep onset and offset were determined using the Sadeh algorithm and sleep diaries to determine sleep midpoint. Paired samples t-tests examined school year-summer differences in family environment variables and stepwise linear regression analyses were used to examine the effect of the family environment on sleep midpoint, controlling for age, gender, chronotype, and sleep duration. Results Compared to the school year, during summer parents reported less parent-child conflict before bed (t(117)=3.913, p&amp;lt;.001), less consistent bedtime routines (t(117)=4.808, p&amp;lt;.001), and average daily screen use (t(117)=-2.756, p=.007) and greater child surgency or impulsivity (t(108)=-2.960, p=.004. Overall, our model explained 48% of the variance in children’s sleep timing during the school year (p=&amp;lt;.001) and 45% during the summer (p=&amp;lt;.001). In the final model, greater caffeine intake (β=2.1, p=.033), later chronotype (β=0.4, p=&amp;lt;.001) and greater effortful control or self-regulatory skills (β=0.2, p=.047) predicted having a later sleep midpoint during the school year. During the summer, less consistent bedtime routines and later chronotype (β=0.3, p=.002) predicted having a later sleep midpoint (β=-0.2, p=.022). Conclusion The relaxed nature of the summer family environment likely contributes to decreased conflict over bedtime, increased child media use, and decreased bedtime routine consistency. However, only decreases in bedtime routine consistency contributed to later bedtimes during summer. Worryingly, 5-8-year-olds appear to be using caffeine during the school year contributing to later sleep timing. Addressing summer bedtime routines and children’s school-year caffeine intake are important targets for intervention to improve children’s sleep. Support (if any) Texas Children's Pediatric Pilot Award