Sleep Onset Time Research Articles

Prenatal exposure to per- and polyfluoroalkyl substances and infant sleep disturbance: A prospective cohort study

BackgroundPrenatal exposure to per- and polyfluoroalkyl substances (PFAS) may adversely affect fetal brain development, yet no study has investigated the potential association between prenatal PFAS exposure and infant sleep. ObjectivesTo explore the associations of prenatal PFAS exposure with infant sleep disturbances during the first year of life in a prospective cohort study. MethodsWe recruited 4127 pregnant women from the Shanghai Birth Cohort (SBC) and followed their children from birth to 12 months old. A total of 2366 infants were included in the 6-month analyses, and 2466 infants in the 12-month analyses. Ten PFAS were quantified in blood serum collected in the first trimester. Sleep quality was measured using the Brief Infant Sleep Questionnaire. We used multiple linear regression and multinomial logistic regression to estimate the individual effects of PFAS on sleep outcomes. We utilized a quantile-based g-computation model to determine the joint effects of the PFAS mixture on infant sleep outcomes. Additionally, generalized estimating equation (GEE) models were performed to examine the longitudinal effects of PFAS exposure during pregnancy. ResultsIn infants aged 6 months, perfluorooctane sulfonate and perfluoroheptanoic acid were associated with a more than 2-fold risk of parent-reported sleep problems as severe. Perfluorodecanoic acid was associated with an increased risk of often or almost always snoring in one-year-old infants (relative risk ratios, 1.79; 95% CI, 1.12–2.86). PFAS mixtures were positively associated with nighttime awakenings both among infants aged 6 months (β, 0.11; 95% CI, 0.04–0.19) and 12 months (β, 0.11; 95% CI, 0.05–0.18). Prenatal exposure to PFAS were associated with longer sleep latency, increased nighttime awakenings, longer nocturnal wakefulness hours, snoring, and earlier sleep-onset time in infants aged 6–12 months, according to GEE models. ConclusionsOur study suggests that prenatal exposure to PFAS may increase the risk of sleep disturbance in infants.

Social dimensions impact individual sleep quantity and quality

While sleep positively impacts well-being, health, and productivity, the effects of societal factors on sleep remain underexplored. Here we analyze the sleep of 30,082 individuals across 11 countries using 52 million activity records from wearable devices. Our data are consistent with past studies of gender and age-associated sleep characteristics. However, our analysis of wearable device data uncovers differences in recorded vs. self-reported bedtime and sleep duration. The dataset allowed us to study how country-specific metrics such as GDP and cultural indices relate to sleep in groups and individuals. Our analysis indicates that diverse sleep metrics can be represented by two dimensions: sleep quantity and quality. We find that 55% of the variation in sleep quality, and 63% in sleep quantity, are explained by societal factors. Within a societal boundary, individual sleep experience was modified by factors like exercise. Increased exercise or daily steps were associated with better sleep quality (for example, faster sleep onset and less time awake in bed), especially in countries like the U.S. and Finland. Understanding how social norms relate to sleep will help create strategies and policies that enhance the positive impacts of sleep on health, such as productivity and well-being.

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.

Automatic-Scoring Actigraph Compares Favourably to a Manually-Scored Actigraph for Sleep Measurement in Healthy Adults.

Introduction Actigraphy has been used widely in sleep research due to its non-invasive, cost-effective ability to monitor sleep. Traditionally, manually-scored actigraphy has been deemed the most appropriate in the research setting; however, technological advances have seen the emergence of automatic-scoring wearable devices and software. Methods A total of 60-nights of sleep data from 20-healthy adult participants (10 male, 10 female, age: 26 ± 10 years) were collected while wearing two devices concomitantly. The objective was to compare an automatic-scoring device (Fatigue Science Readiband™ [AUTO]) and a manually-scored device (Micro Motionlogger® [MAN]) based on the Cole-Kripke method. Manual-scoring involved trained technicians scoring all 60-nights of sleep data. Sleep indices including total sleep time (TST), total time in bed (TIB), sleep onset latency (SOL), sleep efficiency (SE), wake after sleep onset (WASO), wake episodes per night (WE), sleep onset time (SOT) and wake time (WT) were assessed between the two devices using mean differences, 95% levels of agreement, Pearson-correlation coefficients ( r ), and typical error of measurement (TEM) analysis. Results There were no significant differences between devices for any of the measured sleep variables ( p ≥0.05). All sleep indices resulted in very-strong correlations ( all r ≥0.84) between devices. A mean difference between devices of <1 minutes for TST was associated with a TEM of 15.5 minute (95% CI =12.3 to 17.7 minutes). Conclusion Given there were no significant differences between devices in the current study, automatic-scoring actigraphy devices may provide a more practical and cost-effective alternative to manually-scored actigraphy in healthy populations.

0097 Sleep and Eating Rhythms are Associated with Metabolic Risk in Postmenopausal Women

Abstract Introduction Postmenopausal women are particularly vulnerable to metabolic dysfunction. Compelling evidence suggests that this is due to their lacking the protective effect of estrogens. We have shown that circulating estrogens regulate daily eating and sleep-activity rhythms in female mice and protect them from obesity and diabetes. However, few studies have investigated whether postmenopausal women have disrupted eating and sleep-activity rhythms that could contribute to their metabolic dysfunction. The purpose of this study was to investigate the relationship between eating rhythms, sleep, and metabolic risk in postmenopausal women. Methods During 7 days, we studied sedentary, postmenopausal women who were not taking hormones (estrogens ± progestin) and were metabolically unhealthy, defined as prediabetic or normal glucose tolerance with at least 1 feature of the metabolic syndrome. Women taking medications affecting sleep or eating were excluded. Sleep timing and quality were assessed by actigraphy and sleep logs. Times of first and last meals were collected from participants with a texting system. Body composition (DXA), body mass index (BMI), and waist circumference were collected as markers of obesity. Lipid metabolism and glycemic control were assessed by fasting lipid panel and HbA1c as well as oral glucose tolerance test. Results Eighteen postmenopausal women (mean ± SEM; 57.2 ± 1.1 years) participated in the study. Both sleep timing and quality were associated with metabolic risk in postmenopausal women. Specifically, later timing of sleep onset was associated with later meal timing and greater BMI and body fat percentage. Increased sleep fragmentation was associated with reduced HDL. In addition, both the timing and duration of eating were associated with worse metabolic measures. Longer eating duration was associated with larger waist circumference. Later eating time was associated with greater waist circumference and BMI. Conclusion We found that late timing and poor quality of sleep, as well as long eating duration, are associated with markers of metabolic risk in postmenopausal women. These data suggest that interventions that reduce eating duration and advance the timing of last meal and sleep onset may improve metabolic risk in postmenopausal women. Support (if any) This study is supported by NIH awards R01DK124774, T32 AG078110, and UL1TR001998.

0601 An Atypical Cause of Hallucinations in Type 1 Narcolepsy

Abstract Introduction Narcolepsy is a disorder of hypersomnolence affecting between 1:5000-1:10,000 individuals. Type 1 Narcolepsy can be differentiated from Type 2 Narcolepsy by the presence of cataplexy. Visual hallucinations are reported in 50-80% of T1 Narcoleptics and ~25% of T2 Narcoleptics. This is thought to be a REM-related phenomenon occurring at transitions of sleep and wakefulness. Auditory hallucinations or paranoid delusions are more rare. We report a case of a 17 year old patient who experienced psychotic symptoms after trialing more than one class of stimulants. Methods This was primarily a retrospective case review. A subsequent literature search was performed reviewing similar reports of psychosis secondary to medications used to treat Narcolepsy. Results The patient is a 17 year old female who was 10 years old at the time of her diagnosis of Narcolepsy T1. At onset, the patient had reported cataplexy and visual hallucinations occurring at the time of sleep onset and wakening. After finding minimal help with stimulants, by age 15 she was maintained on sodium oxybate 6 grams per night for her cataplexy and started modafinil 200mg BID for wakefulness. She then reported new auditory hallucinations and hyperreligiosity and was admitted to inpatient psychiatry where both medications were discontinued. She was subsequently started on extended release methylphenidate and within 2 months had a recurrence of auditory hallucinations and hyperreligiosity resulting in two consecutive inpatient hospitalizations for psychosis. Conclusion Psychosis induced by medications for Narcolepsy has been reported in the literature where sodium oxybate and stimulants are the most common offending agents. Symptoms primarily related to modafinil or armodafinil are less frequently described. Most medications used to treat Narcolepsy may directly or indirectly act on dopamine pathways, which in theory have the propensity to lead to psychotic symptoms. Small studies of patients with Narcolepsy have reported psychosis in less than 1-2% of Modafinil users. Larger meta-analyses of patients with both Narcolepsy and Schizophrenia, have not found an increased likelihood for uncontrolled psychotic symptoms while on modafinil. Further case studies are needed to elucidate the relationship between stimulants and risk of psychosis in Narcolepsy patients. Support (if any)

0007 Later circadian phase and increased sleep variability are associated with overnight blood pressure dipping in chronic shiftworkers

Abstract Introduction Nighttime shift work is associated with adverse cardiovascular outcomes, including hypertension. Increased sleep variability and circadian disruption may increase sympathetic activity and waking blood pressure (BP), potentially constraining typical BP reductions during overnight sleep. However, the relationships between circadian phase, sleep variability, and overnight BP reduction (dipping) among day vs. chronic nightshift workers is unknown. Methods Ambulatory BP was monitored for up to 48-hours among 10 dayshift (mean□SD; age 33.1□7.0y; BMI 26.3□5.4 kg/m2) and 10 chronic (9.3□6.8y of shiftwork) nightshift workers (age 32.7□9.1y; BMI 27.9□7.6 kg/m2). Overnight BP dipping was calculated from the sleeping/waking systolic BP ratio. Variability in sleep timing was defined as the SD of self-reported daily-diary sleep onset across 1-week. Circadian phase was determined by salivary dim-light melatonin onset (DLMO; 3pg/ml threshold). Differences between groups were assessed using independent t-tests and linear mixed-effects models with group and time-from-sleep-onset or circadian phase as fixed-effects, and participant as a random effect. Relationships between overnight BP dipping and DLMO, sleep onset timing variability, and phase angle of entrainment (DLMO to sleep onset during ambulatory BP) were assessed using Pearson correlation analyses. Results Chronic nightshift workers had reduced overnight BP dipping (-9.3□1.5 % vs -13.4□4.4 %; p=0.04), later DLMO timing (21:08□0:53 vs 19:21□1:02; p=0.001), smaller phase angle of entrainment (3.7□1.0 h vs 5.0□0.90 h; p=0.02), and greater variability in sleep onset timing (3.2□1.5 h vs 0.87□0.34 h; p&amp;lt; 0.001). Significant group effects for higher systolic BP across circadian phase and time from sleep onset in the nightshift group were observed compared to dayshift (both p&amp;lt; 0.05). DLMO (r=0.49; p=0.04) and phase angle of entrainment (r=0.53; p=0.02) were associated with overnight BP dip magnitude (later circadian phase correlated with less dipping). Sleep onset timing variability was negatively correlated with magnitude of overnight BP dipping in nightshift (r= -0.76; p=0.04) but not dayshift workers (r=0.26; p=0.61). Conclusion Attenuated overnight BP dipping among chronic nightshift workers may be indicative of increased cardiovascular risk. Chronic circadian disruptions (i.e., smaller phase angle of entrainment) as a function of higher sleep variability among nightshift workers may mechanistically contribute to poorer health outcomes compared to dayshift workers. Support (if any) R01HL105495, K01HL146992

0101 Greater Variability in Sleep Health is Associated with Obesogenic Appetitive Traits in 6-Year-Olds in the INSIGHT Study

Abstract Introduction Poor sleep health is associated with increased risk for childhood obesity, but the underlying mechanisms are unclear. Eating behaviors may play a role. We examined the association between appetitive traits and objectively-measured sleep variables in 6-year-old children. We hypothesized that poorer or more variable sleep health measures would be associated with higher levels of food approach traits (food responsiveness, enjoyment of food, emotional overeating, and desire to drink), and lower levels of satiety responsiveness. Methods Participants were from an observational long-term follow-up of INSIGHT, an RCT of a responsive parenting intervention for first-time mothers compared to a safety control intervention. At age 6 years, children wore wrist actigraphy (Spectrum Plus) for 7 days to assess sleep. Children with ≥3 valid days were included in analyses (n=167). Mothers completed the Children’s Eating Behavior Questionnaire to assess appetitive traits. Separate regression models examined the association between appetitive traits and sleep variables (M/SD of nighttime total sleep time (TST), onset, offset, and midpoint of sleep timing, and sleep maintenance efficiency), controlling for intervention group, child age, sex, and overweight status. Results Mean TST was unrelated to appetitive traits; greater variability (SD) in TST was associated with higher food responsiveness (B=0.008, p=0.03) and desire to drink (B=0.010, p=0.04). Mean sleep onset time was unrelated to appetitive traits, but greater variability in sleep onset time was associated with higher desire to drink (B=0.686, p=0.004). Higher mean sleep maintenance efficiency was associated with higher satiety responsiveness (B=0.035, p=0.04) and lower enjoyment of food (B=-0.053, p=0.008). Greater variability in sleep maintenance efficiency was associated with higher enjoyment of food (B=0.092, p=0.03) and lower satiety responsiveness (B=-0.089, p=0.01). Emotional overeating was unrelated to sleep variables, and sleep offset and midpoint were unrelated to appetitive traits. Conclusion Other than sleep efficiency, mean levels of sleep health appear unrelated to appetitive traits, but greater variability in sleep health measures were associated with higher levels of potentially obesogenic traits and lower levels of protective traits. Future studies should examine whether promotion of sleep regularity can improve regulation of eating behavior and reduce childhood obesity risk. Support (if any) R01DK088244, KL2TR002015

0922 Interference of racial and socioeconomic factors in the sleep of a large Brazilian city: lessons for comparisons between countries

Abstract Introduction Investigation on the effects of racial and socioeconomic parameters on sleep has markedly increased along the years. The vast majority of these studies take place on countries in North America or Europe, thus making it necessary that new initiatives are conducted in developing nations. The objective of this study was to evaluate how race and socioeconomic factors influence sleep in the city of São Paulo, Brazil. Methods Health and sleep parameters of participants of the EPISONO (2007) study were assessed with validated questionnaires and a night of polysomnographic examination. Data regarding their self-identified race was collected during this protocol. Among the applied questionnaires, scores in the Critério de Classificação Econômica Brasil (CCEB) questionnaire were adopted in this analysis. General Linear Models were used to investigate the relationship between objective sleep parameters and the racial and socioeconomic classification according to the CCEB questionnaire. Results 1,008 participants of the EPISONO were included (mean age=42.3 years; 574 women). Class C Blacks had greater total sleep time (TST) than Class A Whites, while Class C Asians presented less TST. Indigenous participants had reduced wake after sleep onset (WASO) time when sided to Whites and, similarly, Class D Blacks presented lower WASO compared to Class A Whites. Arousal index was lower in Class B and C individuals when comparing to Class A individuals and higher in Class C Blacks when compared to Class A Whites. Conclusion The variety of results when comparing socioeconomic and racial factors highlights the richness of the interplay between these parameters. While some findings are similar to those of North American and European studies, there are differences underlining the necessity of evaluating the socioeconomic and racial background of each population cautiously. Future research on sleep patterns of the Brazilian population concerning the effect of race and socioeconomic status is essential and a promising frontier of investigation to be explored. Support (if any) Our studies are supported by Associação Fundo de Incentivo à Pesquisa (AFIP), Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES Finance Code 001 to GLF) and Conselho Nacional de Desenvolvimento Científico Tecnológico (CNPq – Grant #141445/2021-1 to GLF); S.T. and M.L.A. received CNPq fellowships.

0767 INSIGHT Responsive Infant Parenting Intervention and Child Sleep at Age 6 Years

Abstract Introduction The Intervention Nurses Start Infants Growing on Healthy Trajectories (INSIGHT) responsive parenting (RP) intervention for first-time mothers resulted in more responsive bedtime parenting and longer infant sleep duration in the first year after birth. The current analysis evaluates intervention effects on parent-reported sleep behaviors and objectively-measured sleep at child age 6 years. Methods Mothers (n=279) were randomized to the RP or control intervention, delivered by nurses at home and clinic visits through child age 2.5 years. Sleep content focused on establishing bedtime routines, age-appropriate bedtimes, and promoting self-soothing at bedtime and after night wakings. At 6 years, children completed wrist actigraphy (Spectrum Plus) for 7 days during the school year. Children with ≥3 valid days were included in analyses (n=162). Mothers (n=173) completed the Children’s Sleep Wake Scale and Children’s Sleep Hygiene Scale. Study group differences for 10 sleep actigraphy variables (M/SD of onset, offset, and midpoint of sleep timing, sleep maintenance efficiency, and total sleep time), as well as survey scores, were examined. Results Children (mean age 6.7 years, 96% non-Hispanic White) slept on average 8.8 hours ± 33 minutes per night, with 40% meeting the minimum recommendation of 9 hours. The mean sleep onset time was 9:14 pm ± 50 minutes. There were no significant study group differences in any actigraphy variables. RP mothers reported higher scores for Total Sleep Quality (4.6 ± 0.5 vs. 4.4 ± 0.6, p=0.03), ‘Going to Bed’ subscale (4.3 ± 0.8 vs. 4.0 ± 0.9, p=0.03), which captures child compliance with bedtime, and ‘Reinitiating Sleep’ subscale (4.6 ± 0.9 vs. 4.2 ± 1.1, p=0.005), which captures the child’s ability to go back to sleep on their own after waking. Total Sleep Hygiene score did not differ between groups. Conclusion The INSIGHT intervention targeting sleep in infancy was associated with improved parental perception of bedtime stalling and self-soothing behaviors at age 6 years. However, this did not translate into differences in sleep duration, timing, or quality measured by actigraphy. Future research should examine strategies to maintain the impacts of the RP intervention on infant sleep into middle childhood. Support (if any) R01DK088244, KL2TR002015

Six multidimensional sleep health facets in older adults identified with factor analysis of actigraphy: Results from the Einstein Aging Study

ObjectivesThe concept of multi-dimensional sleep health, originally based on self-report, was recently extended to actigraphy in older adults, yielding five components, but without a hypothesized rhythmicity factor. The current study extends prior work using a sample of older adults with a longer period of actigraphy follow-up, which may facilitate observation of the rhythmicity factor. MethodsWrist actigraphy measures of participants (N = 289, Mage = 77.2 years, 67% females; 47% White, 40% Black, 13% Hispanic/Others) over 2 weeks were used in exploratory factor analysis to determine factor structures, followed by confirmatory factor analysis on a different subsample. The utility of this approach was demonstrated by associations with global cognitive performance (Montreal Cognitive Assessment). ResultsExploratory factor analysis identified six factors: Regularity: standard deviations of four sleep measures: midpoint, sleep onset time, night total sleep time (TST), and 24-hour TST; Alertness/Sleepiness (daytime): amplitude, napping (mins and #/day); Timing: sleep onset, midpoint, wake-time (of nighttime sleep); up-mesor, acrophase, down-mesor; Efficiency: sleep maintenance efficiency, wake after sleep onset; Duration: night rest interval(s), night TST, 24-hour rest interval(s), 24-hour TST; Rhythmicity (pattern across days): mesor, alpha, and minimum. Greater sleep efficiency was associated with better Montreal Cognitive Assessment performance (β [95% confidence interval] = 0.63 [0.19, 1.08]). ConclusionsActigraphic records over 2 weeks revealed that Rhythmicity may be an independent factor in sleep health. Facets of sleep health can facilitate dimension reduction, be considered predictors of health outcomes, and be potential targets for sleep interventions.

Differences in sleep patterns between patients with anorexia nervosa and healthy controls: a cross-sectional study

BackgroundSleep difficulties are common in patients with anorexia nervosa (AN), but objective assessments have mostly been performed in hospital and laboratory settings. We aimed to identify differences in sleep patterns between patients with AN and healthy controls (HC) in their free-living environments, and potential associations between sleep patterns and clinical symptoms in patients with AN.MethodsThis cross-sectional study analyzed 20 patients with AN prior to them starting outpatient treatment and 23 HC. Sleep patterns were measured objectively using an accelerometer (Philips Actiwatch 2) for 7 consecutive days. Average sleep onset, sleep offset, total sleep time, sleep efficiency, wake after sleep onset (WASO) and mid-sleep awakenings lasting ≥ 5 min were compared between patients with AN and HC using nonparametric statistical analyses. Associations of sleep patterns with body mass index, eating-disorder symptoms, eating-disorder-associated impairment, and symptoms of depression were assessed in the patient group.ResultsCompared with HC, patients with AN had shorter WASO [median (interquartile range(IQR)): 33 vs. 42 min], but a longer average duration of mid-sleep awakenings lasting ≥ 5 min [median (IQR): 9 vs. 6 min, p = 0.006] and had more nights with no sleep (six nights in four patients with AN vs. zero nights in HC). There were no differences between patients with AN and HC regarding other sleep parameters and no significant correlations between sleep patterns and clinical parameters in patients with AN. However, HC presented a Intraindividual variability pattern that was closer to a normal distribution, whereas patients with AN tended to either have very regular or large variability in sleep onset time (AN; n = 7 < 25th percentile and n = 8 > 75th percentile vs. HC; n = 4 < 25 percentile and n = 3 > 75th percentile) during the week of sleep recordings.ConclusionPatients with AN seem to spend more time awake during the night and have more nights without sleep than do HC, even though their average weekly sleep duration did not differ from that in HC. The intraindividual variability in sleep pattern seems to be an important parameter that should be assessed when studying sleep in patients with AN.Trial registration ClinicalTroals.gov. Identifier: NCT02745067. Registered: April 20, 2016.

Activities and social contact as antecedents to sleep onset time in U.S. adolescents.

This study evaluated adolescents' evening patterns in activities, social contact, and location to better understand antecedents to adolescents' sleep onset time (SOT). The SOT is important for sleep duration and related health outcomes. Using a nationally representative sample of 15- to 18-year-old adolescents from the American Time Use Survey (N = 10,341; 47% female; 57% white), structural equation modeling demonstrated that late SOTs mediated links between evening activities, social contact, locations, and shorter sleep durations. Passive leisure, time in public locations, and time with friends late in the evenings were associated with later SOTs, whereas homework and active leisure did not. Parents and practitioners can use this information to carefully evaluate evening activities, social contact, and location to support healthy SOTs for adolescents across time.

0105 INSIGHT Study associations between sleep health and child behavior at age 6 years

Abstract Introduction Sub-optimal sleep duration, quality and timing are associated with the presence of disruptive behaviors in childhood. Previous studies have largely utilized parent-/teacher-report of children’s behaviors and focused on mean sleep duration and quality measures, ignoring sleep variability. This analysis uses actigraphy and standardized laboratory behavioral tasks to examine the associations of average levels and variability (SD) of sleep duration, timing, and quality with child behavior. Methods The Intervention Nurses Start Infants Growing on Healthy Trajectories (INSIGHT) Study randomized families with firstborn newborns to a responsive parenting intervention or a safety control shortly after delivery. At age 6 years, children wore a wrist actigraphy device (Spectrum Plus) for 7 days to measure sleep and completed frustration (Transparent Box) and parent-child interaction (Picture Frame) tasks. Tasks were recorded and coded using global behavioral coding schemes; inter-rater reliability was sufficient (Transparent Box ICCs=.83-.97; Picture Frame=.83-1). Children with data on sleep (≥3 valid days) and both behavioral tasks were included in this secondary data analysis (n=143). Separate linear regression models examined associations between 10 sleep variables (M/SD of onset, offset, and midpoint of sleep timing, sleep maintenance efficiency, and total sleep time) and 4 behavioral variables (Transparent Box: emotion regulation, impulsivity; Picture Frame: prosocial and antisocial behavior). Models controlled for child sex and age, household income, and study group. Results Children were aged 6.7 ± 0.3 years and predominantly White, non-Hispanic (95%). Sleep onset (timing) variability was positively associated with impulsivity (B=.85, p=.004) and negatively associated with emotion regulation (B=-.65, p=.01). Sleep midpoint (timing) variability was positively associated with impulsivity (B=.80, p=.03). Mean sleep timing, sleep duration, and sleep maintenance efficiency were not associated with any of the behavioral variables. Conclusion The regularity of sleep timing (onset and midpoint) at age 6 had a greater role in behavioral and emotional regulation than duration and quality of sleep. These findings support existing literature that highlight the importance of parents implementing consistent routines (e.g., consistent bedtime) and how such routines play a key role in socioemotional outcomes among children. Support (if any) R01DK088244

0183 Bedtime Routine Stability in the Context of Developmental Risk

Abstract Introduction Consistent bedtime routines are an important promoter of child sleep health. This is particularly true for children developing at elevated risk for sleep and developmental challenges. Consistent and calming bedtime routines are associated with fewer parent-reported night wakings, shorter sleep onset times, and (for some) longer nighttime sleep bouts. However, few studies systematically address bedtime consistency within the context of developmental risk. To inform future sleep promotion in children with developmental concerns, this study assessed bedtime routine consistency. Methods Across two video-recorded bedtimes, this study assessed the consistency of routines for children (n = 40) with social communication concerns from ages 8-61 months, M(SD)= 28.14(11.76). Each child was enrolled in an eight-session Family Routines Intervention (FRI). The goals of this intervention were to improve family social communication scaffolding within family routines. Bedtime routines were coded for caregiver involvement, sleep onset location, and dyad actions. Results Mothers were the most common bedtime caregiver (93-95%) and her involvement was consistent for most children (96%). Father involvement was less common (present for 25-38% of recordings) and was less consistent at 56%. Other caregivers were present for roughly 18% of dyads, but their involvement was not as consistent (13%). Sleep onset location varied widely with only 33-38% sleeping in a crib, yet crib placement was moderately consistent (64%). Roughly 20% of children slept in an adult bed, with similar consistency (63%). Book reading was the most common (40-43%) and consistent (73%) bedtime action. Bedtime media use was uncommon (8-15%) but surprisingly consistent (44%). Conclusion For children at elevated risk for sleep and developmental concerns, bedtime routines were notably diverse and inconsistent. Although bedtime routines were not the focus of the FRI study, it afforded a unique opportunity to objectively assess how families prepare their child for bed on distinct nights across a relatively short time (8-12 weeks). Not surprisingly, mothers were the primary caregiver, highlighting her potential role in future interventions. The variability in sleep onset location and bedtime actions were notable. These areas reflect clear targets for future interventions designed to promote relatively short, calming, and consistent bedtime routines. Support (if any) Purdue Research Foundation and the Gadomski Foundation

Temporal associations between nightly sleep with daytime eating and activity levels in free-living young adults.

This study aimed to quantify the temporal associations between nightly sleep quantity and timing with daytime eating behavior and activity levels in free-living (i.e. non-experimental) settings. Generally healthy young adults (N = 63; 28.9 ± 7.1 years) completed concurrent sleep (wrist actigraphy), eating (photo-assisted diet records), and activity (waist actigraphy) assessments over 14 days. Multilevel models quantified the associations between nightly sleep (total sleep time, timing of sleep and wake onset) with next-day eating behavior (diet quality, caloric intake, timing of eating onset/offset, eating window duration) and activity levels (total physical activity, sedentary time). Associations in the reverse direction (i.e. eating and activity predicting sleep) were explored. Models adjusted for demographic and behavioral confounders and accounted for multiple testing. At within- and between-subject levels, nights with greater-than-average total sleep time predicted a shorter eating window the next day (all p ≤ 0.002). Later-than-average sleep and wake timing predicted within- and between-subject delays in next-day eating onset and offset, and between-subject reductions in diet quality and caloric intake (all p ≤ 0.008). At within- and between-subject levels, total sleep time was bidirectionally, inversely associated with sedentary time (all p < 0.001), while later-than-average sleep and wake timing predicted lower next-day physical activity (all p ≤ 0.008). These data underscore the complex interrelatedness between sleep, eating behavior, and activity levels in free-living settings. Findings also suggest that sleep exerts a greater influence on next-day behavior, rather than vice versa. While testing in more diverse samples is needed, these data have potential to enhance health behavior interventions and maximize health outcomes.

Examining daily stimulant medication use and sleep in adolescents with ADHD.

Research has been inconclusive as to whether stimulant treatment causes or exacerbates sleep problems in adolescents with ADHD. This study examined sleep differences in adolescents with ADHD as a function of stimulant use. Participants were adolescents with ADHD (N = 159, ages 12-14). Parents reported on receipt of stimulant treatment (n = 92, 57.86%; n = 47 amphetamines, n = 45 methylphenidate). Adolescents wore actigraphs and completed daily diaries assessing sleep and daily use of stimulants for 2 weeks. Sleep parameters included daily-reported bedtime, sleep onset latency (SOL), sleep duration, daytime sleepiness, and difficulty waking the following morning; and actigraphy-measured sleep onset time, total time in bed, and sleep efficiency. We estimated between- and within-individual associations between stimulant medication use and sleep indices with all stimulants, after removing adolescents using sleep aids and weekend days, and as a function of stimulant type. Adolescent sleep did not differ between those receiving and not receiving stimulant treatment. Within individuals using stimulants, we largely observed no significant differences between medicated and unmedicated days, though findings were most often significant for school days only. Small effects were found indicating longer SOL, later sleep onset time, and more daytime sleepiness related to medication use. In contrast, there were slight improvements to sleep duration and sleep efficiency related to methylphenidate use, though methylphenidate was also associated with later sleep onset time and more daytime sleepiness. Given the inconsistent and small effects, findings suggest that stimulant medication may impact sleep, but does not appear to be a primary contributor to sleep problems in adolescents with ADHD.

Clinical presentation, diagnosis, and treatment of sleep disorders in adolescents

Background: Sleep is vital for adolescents’ physical and emotional development; however, sleep disturbances and disorders frequently occur in this age group and affect their health and well-being. In this review, we investigated the prevalence, etiology, diagnosis, clinical characteristics, and treatment of sleep disorders observed among adolescents.Current Concepts: The diagnostic criteria for insomnia disorder among adolescents include difficulties in falling asleep, maintaining sleep, or waking up too early and feeling unrefreshed, which are observed at least 3 days per week over 3 or more months. Cognitive-behavioral therapy for insomnia typically includes identifying and addressing negative thoughts and behaviors associated with sleep and establishing a consistent sleep-wake schedule. Delayed sleep phase syndrome is diagnosed in individuals in whom sleep onset and wake times are persistently delayed by 2 or more hours beyond the desired or existing sleep schedule, which leads to excessive daytime sleepiness or impaired functioning. Behavioral interventions comprise sleep hygiene education, relaxation techniques, and phototherapy. Symptoms such as pronounced snoring, apnea observed by others, and gasping or pauses in breathing during sleep may indicate sleep apnea. Continuous positive airway pressure therapy is an effective treatment strategy for sleep apnea. A history of excessive daytime sleepiness and cataplexy suggests narcolepsy, and treatment options include pharmacotherapy, behavior modification, and lifestyle adjustments. Restless leg syndrome treatments include behavioral therapy, as well as anticonvulsant and dopamine receptor agonist administration.Discussion and Conclusion: Addressing sleep disorders is important to promote optimal health and well-being of adolescents and requires a multidisciplinary approach. Early detection, accurate diagnosis, and individualized treatment improve sleep and overall health outcomes and promote academic and social success.

Sleep Irregularity Is Associated With Hypertension: Findings From Over 2 Million Nights With a Large Global Population Sample.

Irregularities in sleep duration and sleep timing have emerged as potential risk factors for hypertension. This study examined associations between irregularity in sleep duration and timing with hypertension in a large, global sample over multiple months. Data from 12 287 adults, who used an under-mattress device to monitor sleep duration and timing and also provided blood pressure recordings on ≥5 separate occasions, were analyzed. Sleep duration irregularity was assessed as the SD in total sleep time across the ≈9-month recording period. Sleep timing irregularity was assessed as SDs in sleep onset time, sleep midpoint, and sleep offset time. Logistic regressions were conducted to investigate associations between sleep irregularity and hypertension, defined as median systolic blood pressure ≥140 mm Hg or median diastolic blood pressure ≥90 mm Hg. Participants were middle-aged (mean±SD, 50±12 years), mostly men (88%) and overweight (body mass index, 28±6 kg/m-2). Sleep duration irregularity was consistently associated with an ≈9% to 17% increase in hypertension independently of the total sleep time. A ≈34-minute increase in sleep onset time irregularity was associated with a 32% increase in hypertension (1.32 [1.20-1.45]). A 32-minute increase in sleep midpoint irregularity was associated with an 18% increase in hypertension (1.18 [1.09-1.29]), while a 43-minute increase in sleep offset time irregularity was associated with an 8.9% increase in hypertension (1.09 [1.001-1.18]). These findings support that sleep irregularity, both in duration and timing, is a risk marker for poor cardiovascular health. Further mechanistic investigations of temporal relationships between day-to-day fluctuations in sleep duration and timing, next-day blood pressure, and other cardiovascular outcomes are warranted.

COVID-19 stay-at-home restrictions increase the alignment in sleep and light exposure between school days and weekends in university students.

Younger adults have a biological disposition to sleep and wake at later times that conflict with early morning obligations like work and school; this conflict leads to inadequate sleep duration and a difference in sleep timing between school days and weekends. The COVID-19 pandemic forced universities and workplaces to shut down in person attendance and implement remote learning and meetings that decreased/removed commute times and gave students more flexibility with their sleep timing. To determine the impact of remote learning on the daily sleep-wake cycle we conducted a natural experiment using wrist actimetry monitors to compare activity patterns and light exposure in three cohorts of students: pre-shutdown in-person learning (2019), during-shutdown remote learning (2020), and post-shutdown in-person learning (2021). Our results show that during-shutdown the difference between school day and weekend sleep onset, duration, and midsleep timing was diminished. For instance, midsleep during school days pre-shutdown occurred 50 min later on weekends (5:14 ± 12 min) than school days (4:24 ± 14 min) but it did not differ under COVID restrictions. Additionally, we found that while the interindividual variance in sleep parameters increased under COVID restrictions the intraindividual variance did not change, indicating that the schedule flexibility did not cause more irregular sleep patterns. In line with our sleep timing results, school day vs. weekend differences in the timing of light exposure present pre- and post-shutdown were absent under COVID restrictions. Our results provide further evidence that increased freedom in class scheduling allows university students to better and consistently align sleep behavior between school days and weekends.