Weekend Nights Research Articles

630 Longer Sleep Duration Reduces the Odds of Hypertension in Children Referred to Nephrology for Elevated Blood Pressure

Abstract Introduction Lifestyle modification is often prescribed as first line-therapy for hypertension in childhood. We aimed to determine if there was an association between sleep duration and hypertension in children referred for evaluation to Nephrology for elevated blood pressure (BP). We hypothesized that, longer sleep duration would be associated with a reduced likelihood of a hypertension diagnosis. Methods Medical record data were retrospectively extracted from patients referred to the Children’s Hospital of Philadelphia’s pediatric nephrology clinic for the evaluation of elevated BP, without a prior hypertension diagnosis. Ambulatory blood pressure monitoring (ABPM) data collected between December 2015 to December 2018 were extracted. Hypertension was defined by ABPM according to American Heart Association recommendations for pediatric ABPM and we evaluated BP indexed to sex and height. Sleep duration was calculated as the difference between self-reported time of sleep onset and offset. Regression models were adjusted for age, sex, race, body mass index, and weeknight status. Results Our sample included 249 patients, with a mean age of 14.5 (SD: 3.1) years. Of these, 29% were obese and 42% met criteria for hypertension. Mean sleep duration was 9.3 (SD: 1.6) hours per night and duration was shorter with increasing age in years (β=-0.11, 95% CI: -0.18, -0.05) and on week vs. weekend nights (β=-0.62, 95% CI: -1.05, -0.24). Each additional hour of sleep was associated with lower daytime systolic BP Index Z-score (β=-0.12, 95% CI: -0.20, -0.05), lower daytime diastolic BP Index Z-score (β=-0.11, 95% CI: -0.19, -0.03) and 19% reduced odds of daytime hypertension (OR=0.81, 95% CI: 0.67, 0.98). Each additional hour of earlier timing of sleep onset was associated with lower daytime systolic BP Index Z-score (β=-0.10, 95% CI: -0.19, -0.01), lower daytime diastolic BP Index Z-score (β=-0.16, 95% CI -0.25, -0.06) and 16% reduced odds of daytime hypertension (OR=0.84, 95% CI: 0.68, 1.05). Conclusion In children referred for the evaluation of elevated BP, longer sleep duration and earlier sleep onset were associated with a reduced likelihood of being diagnosed with hypertension. Targeting improvements in sleep should be further investigated as part of first line therapy to treat pediatric hypertension. Support (if any) NIH/NHLBI K01HL123612

Sleep duration and its relationship with school performance in Iranian adolescents.

SummaryBackgroundInadequate or poor sleep quality is common problems in adolescent that affect on their learning, memory and school performance. The present study aimed to determine the association between sleep hours and academic performance in young adults.MethodsThis cross-sectional study was designed as a descriptive-analytic study. Samples of adolescents of 14-18 years old in Qazvin city were enrolled. The Pediatric sleep questionnaire and BEARS questionnaire used for all students to screen comprehensively major sleeps problems in them. Chi-square test, t-test, analysis of variance (ANOVA), and correlation were performed to determine the relationship between the data (P < 0.001).ResultsBetween 653 adolescents, 40% were male and 60% were female. Sleep duration, sleep onset delay, sleep insufficient, rate of oversleeping and academic performance had a direct relationship with gender (P < 0.001). The sleep duration, rate of oversleeping and academic performance were significantly higher in boys, sleep onset delay and sleep insufficient was significantly higher in girls. Time of falling sleep at weekend nights and weekday nights have positively correlation with age (P < 0.001). Also, a significant relationship between students’ sleep hours with academic performance was shown (P < 0.001).ConclusionsThe overall result was that sleep duration, sleep onset delay, sleep insufficient and rate of oversleeping of students in this study had a significant influence on academic performance. Students without difficulty in falling asleep had good academic performance in compared to students with difficulty in falling asleep.

Ten seconds of my nights: Exploring methods to measure brightness, loudness and attendance and their associations with alcohol use from video clips.

IntroductionMost evidence on associations between alcohol use behaviors and the characteristics of its social and physical context is based on self-reports from study participants and, thus, only account for their subjective impressions of the situation. This study explores the feasibility of obtaining alternative measures of loudness, brightness, and attendance (number of people) using 10-second video clips of real-life drinking occasions rated by human annotators and computer algorithms, and explores the associations of these measures with participants’ choice to drink alcohol or not.MethodsUsing a custom-built smartphone application, 215 16-25-year-olds documented characteristics of 2,380 weekend night drinking events using questionnaires and videos. Ratings of loudness, brightness, and attendance were obtained from three sources, namely in-situ participants’ ratings, video-based annotator ratings, and video-based computer algorithm ratings. Bivariate statistics explored differences in ratings across sources. Multilevel logistic regressions assessed the associations of contextual characteristics with alcohol use. Finally, model fit indices and cross-validation were used to assess the ability of each set of contextual measures to predict participants’ alcohol use.ResultsRaw ratings of brightness, loudness and attendance differed slightly across sources, but were all correlated (r = .21 to .82, all p < .001). Participants rated bars/pubs as being louder (Cohen’s d = 0.50 [95%-CI: 0.07–0.92]), and annotators rated private places as darker (d = 1.21 [95%-CI: 0.99–1.43]) when alcohol was consumed than when alcohol was not consumed. Multilevel logistic regressions showed that drinking in private places was more likely in louder (ORparticipants = 1.74 [CI: 1.31–2.32]; ORannotators = 3.22 [CI: 2.06–5.03]; ORalgorithm = 2.62 [CI: 1.83–3.76]), more attended (ORparticipants = 1.10 [CI: 1.03–1.18]; ORalgorithm = 1.19 [CI: 1.07–1.32]) and darker (OR = 0.64 [CI: 0.44–0.94]) situations. In commercial venues, drinking was more likely in darker (ORparticipants = 0.67 [CI: 0.47–0.94]; ORannotators = 0.53 [CI: 0.33–0.85]; ORalgorithm = 0.58 [CI: 0.37–0.88]) and louder (ORparticipants = 1.40 [CI: 1.02–1.92]; ORalgorithm = 2.45 [CI: 1.25–4.80]) places. Higher inference accuracies were found for the models based on the annotators’ ratings (80% to 84%) and the algorithms’ ratings (76% to 86%) than on the participants’ ratings (69% to 71%).ConclusionsSeveral contextual characteristics are associated with increased odds of drinking in private and commercial settings, and might serve as a basis for the development of prevention measures. Regarding assessment of contextual characteristics, annotators and algorithms might serve as appropriate substitutes of participants’ in-situ impressions for correlational and regression analyses despite differences in raw ratings. Collecting contextual data by means of sensors or media files is recommended for future research.

Other Shoes

Another weekend night shift…In that place we call “The Pit”…The inner city E.R.…Where the tumult doesn't quit.Tonight the “Knife and Gun Club” meets…So named as you might tell.…It's when the locals hit the streets…And alleys turn to hell.I was still evaluating…If a head blow caused much harm…When the cops brought in another…With a bullet in his arm.“Here's another you can practice on…” I heard some old cop say.…“We're catchin’ ‘em like stripers…This one didn't get away.”His “fish” was only in his teens…They chained him to a cot.

Who ‘Tweets’ Where and When, and How Does it Help Understand Crime Rates at Places? Measuring the Presence of Tourists and Commuters in Ambient Populations

Test the reliability of geotagged Twitter data for estimating block-level population metrics across place types. Evaluate whether the proportion of Twitter users on a block at a given time who are local residents, inter-metro commuters, or tourists is correlated with incidences of public violence and private conflict for four different time periods: weekday days, weekday nights, weekend days, and weekend nights. DBSCAN* machine learning technique is used to estimate the home clusters of 54,249 Twitter users who sent at least one geotagged tweet in Boston. Public violence and private conflict are measured using geocoded 911 dispatches. ANOVA models are used to evaluate how the presence of our three groups of interests varies across three types of block-level land usage. Hierarchical linear regression models are used to evaluate whether the proportion of commuters and tourists at census tract- and block-levels are predictive of crime events across the four time periods of interest. We find evidence that Twitter data has limited reliability across residential blocks due to data sparseness. For non-residential blocks, we find that commuter and tourist presence at the block-level are positively associated with both public violence and private conflict, but that these effects are not stable across time periods. Commuters and tourists only effect violence during weekday days, and the effects of commuters and tourists on private conflict are only statistically significant during weekday days and weekend days. Consistent with routine activities and crime pattern theories, the influx of outsiders in a given location impacts the likelihood of crime occurring there. While we find that data from Twitter users can be valuable for measuring block-level ambient populations, it appears this is not true for residential blocks. Future research may further consider how the characteristics of Twitter users may inform spatial patterns in crime.

Patterns of injury among assault victims presenting at the accident service Colombo South Teaching Hospital (CSTH)

Introduction: Injury patterns and the interpretation of injuries in assault victims are important bits of data that needs to be collected in an emergency department with a view of achieving two main goals. This includes, data for treatment purpose and a medico-legal workup. The objectives of this study are to describe the demographic data of the victims, the mechanism responsible for the injury, the regions of the body involved and the usage of intoxicants. Method: The study was a retrospective cross-sectional study conducted at the accident service CSTH where 170 assault-injured respondents participated. Results: The total sample of 170 assault-injured respondents, 128 (75.3%) were males. 49 (28.9%) of them belonged to the age group of 20-29 years. As per the legal classification; grievous hurt was identified among 55 (32.4%) victims. Blunt trauma occurred in 80 (47.06%). 76 (45.2%) were assaults involving the head, neck or face region. Most of these were superficial injuries. Majority of admissions following assaults occurred among young males, who were mostly victimized at night during weekends (Saturdays and Sundays). The assailants were friends or young acquaintances while they were under the influence of alcohol. Conclusion: Implementing counselling programs, targeting vulnerable groups which includes the intoxicated young male population who are responsible for conflicts, especially during weekend nights. Encouraging gender equality to prevent home violence against women, these steps could be recommended to reduce the number of assault victims.

Fun/intoxication pre-drinking motives lead indirectly to more alcohol-related consequences via increased alcohol consumption on a given night

IntroductionPre-drinking increases alcohol use on drinking nights, which is associated with various adverse alcohol-related consequences but what motivates people to do so, i.e. the role of pre-drinking motives (PDM) in this link, is unclear. The current study examined a) the association of three PDM factors (fun/intoxication, facilitation, and conviviality) with average night-level alcohol use, b) whether PDM are associated with adverse alcohol-related consequences (hangover, drunk driving, blackout, risky sex, injury, and fights) and c) whether PDM mediates the link between night-level alcohol use and negative consequences. MethodsA sample of 204 young adult nightlife goers (48.8% males, Mage = 19 SD = 2.4) from Switzerland reported PDM at baseline, and subsequently participated in a 2-month event-level study. Regressions models assessed direct and mediated associations. ResultsFun/intoxication PDM predicted alcohol use in subsequent drinking nights (11.3 nights per participant on average), but not the two other PDM. No direct link between PDM and consequences was found. However, fun/intoxication PDM lead indirectly to more adverse consequences through higher alcohol use. ConclusionThis study shows that predominantly ‘fun/intoxication’ predrinkers are at increased risk for alcohol consumption and consequences, but not those who predrink for conviviality or facilitation motives. The outcomes thus suggest the importance of specific PDM in preventing alcohol use for instance by tailoring interventions based on individuals’ PDM in order to curb drinking and its associated consequences among young adults on weekend nights out.

Shooting shots: Estimating alcoholic drink sizes in real life using event-level reports and annotations of close-up pictures.

Drinks consumed in real life are diverse, in terms of beverage type, container size and alcohol by volume. To date, most ecological momentary assessment studies have assessed drinking amounts with 'standard' drinks, although their event-level design allows for more advanced assessment schemes. The purpose of this empirical study is to compare participants' estimates of alcoholic drink characteristics, assessed using drink-specific questions, with estimates generated by annotators based on pictures of the same drinks. On weekend nights, 186 young adults took 1484 close-up pictures of their drinks using a custom-built smartphone application. Participants reported the beverage type, drink size and alcohol by volume. Annotators described the beverage type, container size and filling level. Correspondence between participants' and annotators' estimates was explored using descriptive statistics, difference tests and correlations. Annotators were unable to precisely identify the beverage types in most pictures of liqueurs, spirits and mixed drinks. Participants' drink size estimates converged with annotators' estimates of the container size for beer (41 cl corresponding to 16 g of pure alcohol) and mixed drinks (28 cl/35 g), and of the content size for wine (10 cl/9 g). However, annotators estimated larger sizes for liqueur/fortified wine (12 cl/14 g vs. 7 cl/9 g) and spirits (8 cl/26 g vs. 4 cl/10 g) than participants. Annotations of pictures should be considered as a complement to participants' reports rather than a substitute. Except for wine, real-life drinks vary largely and often exceed 10 g 'standard' drinks.

The relationship between sleep habits, lifestyle factors, and achieving guideline-recommended physical activity levels in ten-to-fourteen-year-old Japanese children: A cross-sectional study.

The current focus of meeting the physical activity guidelines for children and young people include preventing conditions such as high blood cholesterol, high blood pressure, metabolic syndrome, obesity, low bone density, depression, and injuries. However, the relationship between sleep habits and meeting physical activity guidelines is still unclear. This study aimed to assess this relationship among fifth- to eighth-grade (ages 10–14) Japanese children. This cross-sectional study included 3,123 children (boys: 1,558, girls: 1,565, mean age: 12.5 ± 1.2 years). Questionnaires were used to assess parameters such as moderate-to-vigorous physical activity per day, school and weekend night sleep durations, social jetlag, daytime sleepiness, napping, screen time, and breakfast intake. Participants were divided into an achievement and a non-achievement group depending on their physical activity guideline achievement status (i.e., whether they met the children’s physical activity guideline of 60 min or more of moderate-to-vigorous physical activity per day). Then, to determine the sleep habits in relation to the children’s achievement of guideline-recommended physical activity levels, multivariate logistic regression analyses were conducted. In fifth- and sixth-grade (ages 10–12) boys, an inverse association was observed between physical activity guideline achievement and daytime sleepiness. In seventh- and eighth-grade (ages 12–14) boys, physical activity guideline achievement was inversely associated with social jetlag and skipping breakfast. Additionally, in seventh- and eighth-grade girls, physical activity guideline achievement was inversely associated with inappropriate sleep duration on weekends and screen time. These results suggest that meeting the physical activity guideline is related to favorable sleep habits in Japanese children. However, their relevance may differ by school type and gender.

Measuring Empiric Antibiotic Spectrum Patterns Across Space and Time

Background: Quantitative evaluation of antibiotic spectrum is an important, underutilized metric in measuring antibiotic use (AU) and may assist antimicrobial stewards in identifying targets and strategy for intervention. We evaluated the spectrum of initial antibiotic choices by hospital location, day of the week, and time of day to determine whether these factors may be associated with broad-spectrum antibiotic choices. Methods: We identified all admissions with antibiotic exposure in medical and surgical wards and critical care units in a tertiary academic medical center between July 1, 2014, and July 1, 2019. The antibiotic spectrum index (ASI), proposed by Gerber et al, is a numeric score based on the number of pathogens covered by a particular agent. We defined ASI for initial antibiotic choice as follows: ASI for each unique antibiotic administered within 24 hours of the first antibiotic administration was summed and assigned to the administration time of the first dose. We categorized time into 4 distinct categories: weekday days (Monday–Friday, 7 a.m.–7 p.m.), weekday nights, weekend days, and weekend nights. Weekend time began 7 p.m. Friday and ended 7 a.m. Monday. We constructed heatmaps stratified by hospital location. Mann-Whitney U tests were applied to evaluate differences in the distributions of ASI using weekday days as a reference. Results: Data included 90,455 unique antibiotic admissions with initial antibiotic starts in medical and surgical wards and critical care units. Patterns of ASI for initial antibiotic choice varied between unit locations and time (Figs. 1 and 2). Mean and median ASIs for initial antibiotic choices were higher for medical ward and medical ICUs than for surgical wards and surgical ICUs. Initial antibiotic choices had higher ASIs during overnight hours for all units except the surgical ICU. Notable differences in ASIs were identified between weekday and weekend prescribing for surgical units, whereas medical units demonstrated less extreme differences. Conclusion: We observed a “weekend effect” across hospital units; the most extreme occurred in surgical wards. This observation may be due to differences in patient volume and rounding patterns. For example, hospitalist and critical care units have 7-day schedules, whereas surgical wards are highly influenced by operating room schedules. Antimicrobial stewardship teams may use these data to identify strategies targeting the most opportune time and place to intervene on the spectrum of initial antibiotic choice.Funding: NoneDisclosures: None

Outcome of Hypotensive Trauma Patients by Time and Day of Arrival

BackgroundAlthough most studies of trauma patients have not demonstrated a “weekend” or “night” effect on mortality, outcomes of hypotensive (systolic blood pressure <90 mm Hg) patients have not been studied. We sought to evaluate whether outcomes of hypotensive patients were associated with admission time and day. MethodsWe retrospectively analyzed patients from Pennsylvania Level 1 and Level 2 trauma centers with systolic blood pressure of <90 mm Hg over 5 y. Patients were stratified into four groups by arrival day and time: Group 1, weekday days; Group 2, weekday nights; Group 3, weekend days; and Group 4, weekend nights. Patient characteristics and outcomes were compared for the four groups. Adjusted mortality risks for Groups 2, 3, and 4 with Group 1 as the reference were determined using a generalized linear mixed effects model. ResultsAfter exclusions, 27 trauma centers with a total of 4937 patients were analyzed. Overall mortality was 44%. Compared with patients arriving during the day (Groups 1 and 3), those arriving at night (Groups 2 and 4) were more likely to be younger, to be male, to have lower Glasgow Coma Scale scores and blood pressures, to have penetrating injuries, and to die in the emergency room. Controlled for admission variables, odds ratios (95% confidence intervals) for Groups 2, 3, and 4 were 0.92 (0.72-1.17), 0.89 (0.65-1.23), and 0.76 (0.56-1.02), respectively, for mortality with Group 1 as reference. ConclusionsPatients arriving in shock to Pennsylvania Level 1 and Level 2 trauma centers at night or weekends had no increased mortality risk compared with weekday daytime arrivals.

Beyond sleep duration: Sleep timing as a risk factor for childhood obesity.

SummaryBackground:Ample evidence attests to the relationship between short sleep duration, sleep problems and childhood obesity. However, few studies have examined the association between sleep timing and obesity in children.Objectives:To investigate how sleep duration, problems and timing relate to obesity and obesogenic behaviours in children.Methods:Eighty-five children (58.8% girls) with severe obesity and mean (SD) age of 12.1 (2.9) years, were matched by age and sex with peers with normal weight (n = 85,12.0 [2.8] years). Sleep and moderate-to-vigorous physical activity (MVPA) were measured via accelerometer for seven consecutive days. Children self-reported emotional eating on the Dutch eating behavior questionnaire. Parents reported children’s screen time and sleep problems.Results:Children with severe obesity had significantly later mean mid-sleep time, overall (36 minutes later, P < .001), on school nights (36 minutes later, P < .001) and weekend nights (39 minutes later, P = .002) compared to children with normal weight. Children with obesity had more sleep problems (P = .030), but no differences emerged in sleep duration or social jetlag. After adjusting for demographic factors, mid-sleep time was positively related to screen time (P = .030). Mid-sleep time and sleep duration were inversely related to time in MVPA (Ps ≤ .041). There were no other significant associations between the sleep variables and the obesogenic behaviours.Conclusions:Later sleep timing was related to obesogenic behaviours in children and may represent an obesity risk factor.

What's Important: Empathy in Patient Care: Lessons from My Own Knee Story.

What's Important: Empathy in Patient Care: Lessons from My Own Knee Story.

Association Between Free-living Weekday 24-hour Urinary Hydration Markers And Weekend Sleep Measures

PURPOSE: Inadequate sleep and underhydration have been independently associated with adverse health outcomes. However, the relation between hydration status and sleep has yet to be investigated over the course of several days in young adults. Thus, the purpose of this study was to assess the association between 24h urinary hydration markers and both perceived and objective sleep quality. METHODS: Eighteen participants (female, n=7; age, 23±3; height, 174.6±15.3cm; body mass, 73.5±15.9kg; body fat, 19.4± 9.4%) provided a 24h urine sample on seven consecutive days for measures of urine volume (UVOL), urine osmolality (UOSMO), urine specific gravity (USG) and urine color (UCOL). Objective sleep metrics (wrist-worn actigraphy) and subjective sleep assessments (Karolinska Sleep Diary) were recorded each day. Actigraph measures included periods of wakefulness after defined sleep onset (WASO), sleep time, wake time, and sleep efficiency. The Karolinska Sleep Diary included nine questions used to assess perceived sleep quality from the previous night. Mean values were calculated for each participant for all variables on weekdays (Monday-Friday) and weekend days (Saturday/Sunday). RESULTS: Higher weekday USG and darker UCOL were both associated with greater weekend time spent sleeping (USG, adj R2 = 0.203, p = 0.024; UCOL, adj R2 = 0.274, p = 0.015). Decreased weekday UVOL was associated with increased weekend time spent sleeping (adj R2 = 0.220, p = 0.028). Higher weekday UOSMO was associated with greater weekend WASO actigraph measures (adj R2 = 0.205, p = 0.045). CONCLUSIONS: Mean 24-hour urinary hydration markers depicting a state of underhydration (elevated USG and reduced UVOL) across weekdays were associated with an increased number of awakenings during the weekend nights, albeit, having a longer sleep time. Determining how day-to-day variations in hydration status and other general health behaviors influence sleep has yet to be explained.

Sleep Quality Is Associated With Nighttime Heart Rate Variability In Young Adults

Heart rate variability (HRV) reflects autonomic nervous system function, and low nighttime HRV is linked to reduced parasympathetic control. Optimal parasympathetic function is important for the induction and maintenance of sleep, overall wellbeing, and is inversely associated with chronic disease. In young adults, 60% of whom report poor sleep quality, disrupted parasympathetic function may reflect suboptimal health and lifestyle behaviors. While there is an established relationship between physical activity (PA), stress, and nighttime HRV, the associations between HRV and other lifestyle-related factors such as sleep quality and social jet lag (SJL) in young adult populations are yet to be determined. PURPOSE: The purpose of this study was to determine the relationship between nighttime HRV and sleep characteristics in young adults. METHODS: Healthy young adults (n=33, 18.6 ± 0.7 years, 69.6% female) wore a chest-strap heart rate monitor for 24 hours and a triaxial accelerometer on the non-dominant wrist for 7 days during free-living PA and sleep. Average sleep duration and SJL were determined from objective sleep data, with SJL calculated as the difference in hours between the midpoint of sleep on weeknights (school) and weekend (free) nights. The Pittsburgh Sleep Quality Index (PSQI) and Perceived Stress Scale were used as subjective measures of sleep quality and stress. Nighttime HRV outcomes were calculated using R-R intervals between the hours of 1:00 AM - 5:00 AM. Linear regression assessed multivariate relationships among sleep duration, quality, SJL, and HRV while controlling for moderate-to-vigorous PA and perceived stress. RESULTS: Independent of average sleep duration and SJL, perceived sleep quality was associated with the HRV outcomes low frequency (LF; B= -10.62 ± 4.85, 95% CI: -20.56, -.67) and high frequency power (HF; B= 10.55 ± 4.84, 95% CI: .61, 20.49). Following control for PA and stress, these relationships remained significant and the association between SJL and LF/HF ratio approached significance (B= -.33 ± .18, 95% CI: -.69, .04). CONCLUSIONS: Our findings suggest that both LF and HF HRV components are related to sleep quality in young adults, highlighting a potential relationship between sleep quality and nighttime autonomic nervous system function.

Sleep in New Zealand children aged 7-9: associations with ethnicity, socioeconomic status, and achievement in reading and mathematics.

The aims were (1) to investigate differences by ethnicity and socioeconomic status (SES) in objective measures of sleep in children aged 7-9 years and (2) determine whether measures of sleep predict child achievement in reading or mathematics after controlling for ethnicity and SES. Four groups of parent-child dyads were recruited: Māori, low-SES schools (n = 18); Māori, high-SES schools (n = 17); New Zealand European, low-SES schools (n = 18); New Zealand European, high-SES schools (n = 17). Child sleep was measured by actigraphy. Parents and teachers reported child daytime sleepiness and behavior, and children completed a self-report of anxiety symptoms. Teachers also reported on child achievement in reading and mathematics. Children from low-SES schools went to bed later on school nights (F[1,68] = 12.150, P = .001) and woke later (F[1,68] = 15.978, P < .001) than children from high-SES schools but had similar sleep duration. There were no differences related to ethnicity. Children from low-SES schools were almost 3 times more likely to be below national standards for mathematics. Children not meeting academic standards in mathematics had a later sleep start time, lower sleep period efficiency, and a decreased total sleep time. However, when SES and sleep period efficiency were modeled together neither were found to significantly influence achievement in mathematics. In this study, SES influenced sleep timing but not the quality and quantity of sleep in 7- to 9-year-old children, and a significant independent effect of sleep efficiency on learning could not be demonstrated.

Assessment of Craniomaxillofacial Injuries After Electric Scooter Accidents in Turku, Finland, in 2019

Since the introduction of rental electric scooters (ESs), clinicians have increasingly encountered facial trauma patients whose injuries were caused by ES use. Despite this fact, few studies have analyzed these patients, particularly in Nordic countries, where the climate may cause additional challenges. We hypothesized that ESs have caused several facial trauma cases in Turku, Finland, that might be related to the timing of ES use, that is, month, day, and hour. The medical records of all patients in whom craniofacial fractures or dental injuries caused by ES use were diagnosed at Turku University Hospital, Turku, Finland, in 2019 were reviewed. The occurrence and characteristics of injuries, with special reference to time of the accident, intoxication, hospital stay, and additional injuries sustained were analyzed. A total of 23 patients were identified for this analysis. The mean age was 30years, and most patients (n=16) were men. Four patients had not used helmets, whereas for 19, there was no mention whatsoever about helmet use. Of the patients, 21 were intoxicated and 18 had a blood alcohol content greater than 0.1%.A great majority of the accidents occurred in the nighttime (n=17) and during weekends (n=19). Most injuries (n=15) occurred between September and November. We observed craniofacial fractures in 15 patients and dental injuries in 14; brain injuries occurred in 5 patients, and multiple chest injuries occurred in 1. All patients with dental injuries and 9 of the 15 patients with craniofacial fractures required interventions. An average of 3days of hospitalization was required for 14 patients. Injuries associated with ESs result from driving under the heavy influence of alcohol and occur mostly during weekend nights without helmet use.

0964 Out Like a Light: Preliminary Results of Parent-Child Dyad Use of an Audio-Based Mobile Application Aiding Bedtime Routine and Sleep Health

Abstract Introduction Adequate sleep is essential for a child’s growth and development. However, a growing number of children are experiencing trouble falling asleep. Smartphone audio-based mobile applications with soothing melodies and calming nighttime stories may improve sleep onset. Our study examined the efficacy of Moshi Twilight, an app designed to improve sleep onset, among children ages 3-8 years old using a parent-child dyadic approach. Methods Our within-subjects pre-post study design focused on healthy children studied over 10 days, spanning 3 weeknights and 2 weekend nights. During the baseline (Days 1-5) and exposure (Days 6-10) conditions the Child Sleep Health Questionnaire was used to measure children’s sleep behavior. The PROMIS and Pittsburgh Sleep Quality Index were used to assess parents’ sleep quality. Parents exposed their child to 1 story per night (15-20 minutes) during the exposured condition. Statistical analysis was based on paired t-tests, independent t-tests, and correlations. Results On average, participating parents were 37 (SD +9.6) year-old mothers. The sample was: 60% Black; 20% White, 20% other race/ethnicity. On average, children were 4 (SD + 0.78) years old and 50% male. Paired t-tests showed significant differences in children’s sleep onset within 20 minutes (t=2.582, 95% CI 0.116, 2.634, p= 0.036). Significant correlations were noted for children’s bedtime consistency (r = -0.755, p = 0.030), falling asleep in own bed (r = 0.735, p=0.015) and sleep duration (r = -0.715, p=0.046,) Significant correlations and paired t-test in parents’ sleep onset were also found (r = 0.744, p = 0.014); (mean= -1.2, t= -3.674, 95% CI -1.939, -0.461, p=0.005) Conclusion Our results showed that the audio-based sleep app, Moshi Twilight, might be useful in improving sleep health among both children and parents. This could be included in enhance bedtime routine among preschool-aged children. Support Bezos Grant and Community Service Plan grant.

0954 Sleep of Gifted Children Using Actigraphy

Abstract Introduction Intellectual giftedness is characterized by an intellectual development superior to peers (QI &amp;gt; 120) while emotional and relational development corresponds to the age norms. Anecdotal reports from parents suggest that they sleep poorly compared to typically developing (TD) peers. We measured sleep of gifted children using actigraphy. Methods Thirteen gifted children (10 boys, mean age = 10.58, SD = 2.11) were studied. Giftedness was identified using Renzulli’s three-factor definition of giftedness conceptualise in terms of above-average ability and high levels of task commitment (refined or focused form of motivation), and creativity. Sleep was measured with actigraphy for two weeks and compared to normative data from TD children using T-tests. Results Compared to normative data from TD children, gifted children had a significantly shorter sleep latency (p &amp;lt; 0.001), longer sleep periods (p = 0.001), shorter total sleep time and more wake time after sleep onset (p = 0.03). These differences were present both on week nights and weekend nights except that total sleep time was shorter in gifted children only during weekends (p &amp;lt; 0.001). Conclusion These data suggest that gifted children sleep poorly, and more so upon weekends. Whether this correlates with daytime functioning remains to be determined. Support N/A

0443 Intra Week Sleep Patterns Analyzed Using Consumer Sleep Tracker Data

Abstract Introduction Big data collected using consumer sleep technology can provide objectively measured insights on sleep behavior in the real-life environment. It has the advantage over self-report data of being less prone to bias. Here we used a non-contact bio-motion sensor to remotely capture objective sleep data. We analyzed 168432 nights of sleep data to test if differences between weekday versus weekend sleep behavior, known from self-report, would still hold using objective data in a large population. Methods Sleep data was acquired using the SleepScore Max remote sleep sensor and included 168432 nights (2730 users, mean age: 46.6 +/- 11.8 years, 33% female, all resident in the USA). Analysis was restricted to those of working age; adults between 20-65. Any sleep which ended from Monday to Friday was considered weekday sleep, and any ending on Saturday or Sunday as weekend sleep. Data records were inspected and cleaned before analyzing. Descriptive statistics and independent t-tests were used to analyze the data. Results Total Sleep Time, Time In Bed and Sleep Onset Latencies were longer during weekend (TST: + 20.6 mins, TIB: +22.9 mins, SOL: +1.1 min, all p &amp;lt;0.001), resulting in a slightly poorer Sleep Efficiency (-.016%, p&amp;lt;0.01) for weekend nights. Time to bed and final awakening were both delayed in weekends as compared to weekdays (Time to bed +30.0 mins, and final awakening +53.4 mins, both p&amp;lt;0.001). Conclusion This big data analysis confirms the earlier observed difference in sleep and sleep behavior between weekdays and weekends. This should be considered for optimizing (automated) sleep interventions, that may not normally take the weekend effect into consideration. Support