Typical Weekend Research Articles

Prevalence of social jetlag and associated factors in Brazilian adolescents: Results from a country-wide cross-sectional study

ObjectivesSocial jetlag is a disturbance in the circadian rhythm caused by a desynchronization between an individual's biological rhythm and social commitments and responsibilities. It leads to sleep debt during the week and compensation on weekends. Social jetlag is associated with an increased risk of chronic diseases and cognitive dysfunction in adolescents. This study aims to assess the prevalence of social jetlag and associated factors in Brazilian adolescents. MethodsAdolescents of both sexes, aged between 12 and 17years, participating in the Study of Cardiovascular Risks in Adolescents (ERICA), were included. The sleep duration on a typical weekday and weekend day was collected through a self-reported questionnaire. The occurrence of social jetlag was defined as the difference between the midpoint of sleep on weekends and weekdays, with differences equal to or higher than 1hour considered as an indicator of positive social jetlag. Factors associated with the prevalence of social jetlag were investigated using Poisson regression models. ResultsThe sample included a total of 64,029 adolescents. Social jetlag affects more than 80% of Brazilian adolescents, with higher prevalence among girls in the age group of 16-17years, with white skin color, attending private schools, and those having morning classes. Additionally, unhealthy risk behaviors such as skipping breakfast, alcohol consumption, and increased screen time are associated with a higher prevalence of social jetlag. ConclusionThe prevalence of social jetlag was high in Brazilian adolescents, and, among its associated factors, studying in the morning shift and engaging in unhealthy risk behaviors stand out.

Impact of usage of electronic devices on sleep quality among healthcare professions students in Ajman, UAE

Due to the advancement in technology, people are using various electronic devices. People using electronics and the internet at inappropriate times may have a harder time falling asleep and have less sleep duration, and the sharp rise in electronic device use has numerous adverse effects. This study aimed to assess the impact of the usage of electronic devices on sleep and also to determine the factors influencing sleep among healthcare professions students. A cross-sectional study was conducted using a self-administered questionnaire. The association was assessed using the Chi-square test and simple binary logistic regression to identify the factors. Of the total 446, 36.4% reported not having problems during the past month in getting to sleep within 30 minutes. Internet use at school during a typical weekday, 22.2% use 2-4 hours a day; outside of school during a typical weekday, 24.7% use >6 hours. 34.3% use the internet >6 hours outside of school on weekends. The crude OR observed was 4.1, 3.7, 3.6 and 3.9 for 1-2, 2-4, 4-6, >6 hours respectively which is statistically significant. Factors that showed statistical significance for sleep duration were nationality and internet use outside the school during a typical weekend day. For how long it takes to fall asleep, the age group was the factor that showed statistical significance.

Performance investigation and operation optimization of an innovative hybrid renewable energy integration system for commercial building complex and hydrogen vehicles

With the increasing in energy demands and carbon emissions of building and transport sectors, improving the penetration of renewable resources in these areas are inevitable trends. To further develop the theoretical method of energy integrated system in building/transportation area, load forecasting of commercial building complex and hydrogen vehicles are determined, a novel hybrid renewable energy integration system is presented and studied. Thermal, economic and environmental performances for poly-generation system are performed and optimized, optimal performance and configuration are obtained by NSGA-II algorithm and TOPSIS-Shannon entropy weight method. In addition, operating performance characteristics of integration system during typical weekday and weekend in different seasons are analyzed, the influences of critical parameters on comprehensive performances of integrated system are also conducted. The results showed that optimal exergetic efficiency, levelized cost of product (LCOP) and levelized CO2 emissions of product (LCEP) are 12.61 %, 0.0711 $/kWh and 0.0185 kg/kWh. Furthermore, thermodynamic performances of proposed system decreases while LCOP and LCEP rise with the increasing in HVs stock. Biomass and purchased electricity prices have different impacts on system comprehensive performances. In general, this study provides a new alternative for multiple renewable energy integrated system optimization in building and transportation sectors.

Abstract 2196: Susceptibility to tobacco use among rural adolescents: Examining the role of tobacco marketing exposure and media use intensity

Abstract Background: Rural youth have higher rates of electronic nicotine delivery systems (ENDS) and tobacco product use compared to their urban counterparts. Prior literature confirms that marketing exposure increases pro-tobacco attitudes and susceptibilities, yet the extent to which tobacco product marketing and advertising messages relate to tobacco use susceptibility among rural adolescents is understudied. Objectives: To examine the association between tobacco marketing exposure and susceptibility to tobacco use and ever tobacco use among a population of rural youth. Methods: Youth (aged 14-18 years), enrolled in grades 9-11, able to speak and write in English, and residing in rural counties in Virginia (n = 697) were recruited to participate in the Southern Virginia - Adolescents, Place, and Behavior study. At baseline, eligible participants were asked to answer survey questions, including demographics (e.g., age, race/ethnicity, and gender), tobacco product (e.g., e-cigarettes/vapes, cigarettes, and cigars), tobacco use susceptibility (e.g., “do you think you will try any type of tobacco product in the next year?”), digital media use (e.g., “how many hours do you spend visiting social networking sites on both a typical weekday and a typical weekend day?"), and interaction and exposure to tobacco advertisements. Results: The majority of participants were female (51.9%), White (62.4%) and non-Hispanic (86.6%), with an average age of 15.1 years old (SD = .96). Less than a quarter (20.7%) of participants reported ever using any tobacco products. Heavy social media users and text users were more likely to be tobacco ever-users than those who were light social media users, X2(1) = 12.00, p < .001. Multivariate logistic regression models report that exposure to online ads promoting tobacco products (OR: 2.03, 95% CI [1.37 - 3.03]) and higher grade level (OR: 1.77, 95% CI [1.29 - 2.43]) were significantly associated with the likelihood of ever using tobacco products, while controlling for mother’s education, gender, and ethnicity. Among adolescents who never used tobacco products, higher grade levels (OR: 1.40, 95% CI [1.05 - 1.86]) were associated with greater susceptibility to initiating tobacco product use while controlling for the covariates. Conclusions: Greater social media use and exposure to ads promoting tobacco products were significantly associated with tobacco ever use. For never tobacco users, social media use or tobacco ad exposure was not associated with greater susceptibility to tobacco use. Higher grade levels were associated with both tobacco ever use and greater susceptibility to tobacco product use. Identification of these risk factors may help inform potential targets for future tobacco prevention campaigns. Citation Format: Sunny Jung Kim, Kendall Fugate-Laus, Jeremy Barsell, Elizabeth K. Do, Rashelle Hayes, David Wheeler, Bernard Fuemmeler. Susceptibility to tobacco use among rural adolescents: Examining the role of tobacco marketing exposure and media use intensity [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2196.

Abstract P406: Screen Time and Behavioral Cardiovascular Health in Youth by Age: The Young Hearts Study

Background: Research suggests that screen time is associated with negative health outcomes, including cardiovascular health (CVH) factors (BP, lipids, glucose, BMI) but seldom include CVH behaviors (diet, physical activity, nicotine exposure, and sleep). Methods: Young Hearts is an observational study of CVH trajectories in youth aged 0-20. This analysis includes 1749 participants aged 6-18 with complete baseline surveys. Parents (for 6-17 year olds) and adolescents aged 12+ (for themselves) completed surveys on CVH behaviors, medical history, and social context. Participants (stratified by age groups: 6-9, 10-14, and 15-18) reported hours spent on screens during a typical weekday and weekend day, excluding schoolwork and video calls. For 12-17-year-olds, we calculated the average reported screen time. We calculated CVH using the 4 health behaviors in the AHA’s Life’s Essential 8. Each behavior was assigned a score of 0 to 100 and averaged to create the behavioral CVH score. Linear regression assessed the association between screen time (continuous) and CVH score, adjusting for age, sex, race, ethnicity, income, parental education, chronic disease, insurance type, and depressive symptoms. Results: The mean age of 1749 participants was 12, 47% were female, 46% non-Hispanic White, 26% Hispanic, 20% non-Hispanic Black, and 9% identified as other. For participants aged 10-14, a 1-hour screen time increase was associated with a -0.9 CVH score (95% CI -1.4, -0.4). Inverse associations between screen time and sleep score were observed among youth aged 10-14 and 15-18 (-1.4; 95% CI -2.6, -0.2). Screen time was inversely related to diet across age groups. Among children aged 6-9, screen time was positively associated with physical activity (1.2; 95% CI 0.2 - 2.1). The findings were consistent by race/ethnicity. Conclusion: Higher screen time was associated with less favorable CVH scores due to sleep and diet scores. Future research is needed to better understand the relationship between screen time and physical activity among youth.

Bi-level optimal dispatching of distribution network considering friendly interaction with electric vehicle aggregators

The widespread application of electric vehicles (EVs) is a positive force driving green development. However, their widespread penetration also poses significant challenges and threats to the security and stable operation of the power grid. To address this urgent issue, this article constructs a bi-level optimal dispatching model fostering collaboration between electric vehicle aggregators and the distribution network. The upper-level optimization targets the minimization of peak-valley differences in the distribution network via considerably arranging power outputs of gas turbines, while the lower-level one focuses on reducing the charging expense of EV aggregators via efficient charging transfer. Note that the charging expense is not only composed of electric cost but also a dynamic carbon emission factor-based cost, which contributes to the electricity economy and carbon reduction concurrently. A geometric mean optimizer (GMO) is introduced to solve the mode. Its efficiency is evaluated against three typical algorithms, i.e., genetic algorithm, great-wall construction algorithm, and optimization algorithm based on an extended IEEE 33-bus system with different charging behaviors of EVs on both a typical weekday and weekend. Simulation results demonstrate that the GMO outperforms other competitive algorithms in accuracy and stability. The peak-valley difference between the distribution network and the total cost of EV aggregators can be decreased by over 98% and 76%, respectively.

Why do people take e-scooter trips? Insights on temporal and spatial usage patterns of detailed trip data

Electric scooters (e-scooters) are becoming one of the most popular micromobility options in the United States. Although there is some evidence of increased mobility, reduced carbon emissions, replaced car trips, and associated public health benefits, there is little known about the patterns of e-scooter use. This study proposes a framework for high-resolution analysis of micromobility data based on temporal, spatial, and weather attributes. As a case study, we scrutinized more than one million e-scooter trips of Nashville, Tennessee, from September 1, 2018, to August 31, 2019. Weather data and land use data from the Nashville Travel Demand Model and scraping of Google Maps Point of Interest (POI) data complemented the trip data. The combination of Principal Component Analysis (PCA) and a K-means unsupervised machine learning algorithm identified five distinct e-scooter usage patterns, namely morning work/school, daytime short errand, social, nighttime entertainment district, and utilitarian trips. Among other findings, the most common use of e-scooters in Nashville was daytime short errand trips, contributing to 29% of all e-scooter trips. We found that 7% of all e-scooter trips resembled morning commuting to work or school. Only 16% of trips were classified as Nighttime Entertainment District trips. The average daily number of trips on a typical weekend was 81% higher than a typical weekday. We also found variation in e-scooter usage patterns over a year with high summer ridership patterns. The findings of this study can help city administrations, planners, and micromobility operators to understand when and where people are using e-scooters. Such knowledge can guide them in making data-driven decisions regarding safety, sustainability, and mode substitution of emerging micromobility.

Analysis of Charging Load Acceptance Capacity of Electric Vehicles in the Residential Distribution Network

After large-scale electric vehicles (EVs) are connected to the residential distribution network, community charging has become one of the main bottlenecks at present, especially in old residential areas. Therefore, the current residential distribution network’s ability to accept charging load and when and how the distribution network needs to be transformed have become meaningful research points. Based on the characteristics of the EVs’ charging load of residential areas on a typical day and the size of the target annual charging load, this paper analyzes the acceptance capacity of the charging load of the distribution network on typical weekdays and weekends. By taking the charging load characteristics, the charging time of EVs, the voltage of each node of the distribution network, the line capacity, the transformation capacity of the distribution station as constraints, and the maximum capacity of the residential distribution network to accept the charging load as the objective function, the charging load capacity of the residential distribution network is analyzed. The particle swarm optimization algorithm is employed to solve the optimized mathematical model. The simulation uses an actual residential distribution network as an analysis example, and the partition optimization results prove the correctness and feasibility of this proposed method.

Modeling the risk of wrong-way driving at the exit ramp terminals of partial cloverleaf interchanges

Introduction: Partial cloverleaf (parclo) interchanges with closely spaced parallel entrance and exit ramps are more prone to wrong-way driving (WWD) compared to other interchange types. In this study, a logistic regression model was developed to predict the risk of WWD at the exit ramp terminals of parclo interchanges. Method: The logistic regression model was developed using Firth’s penalized likelihood techniques based on the predictor variables such as exit ramp geometric design features, wrong-way related traffic control devices, area type, and traffic volume. Results: According to the model, the significant predictors of WWD at parclo exit ramp terminals include corner radius from crossroad to entrance ramp, type of median on crossroad, width of median on two-way ramp, channelizing island, distance to the nearest access point, “Keep Right” sign, wrong-way arrow, intersection signalization, and traffic volume at the exit and entrance ramps. This model was used to conduct network screening for all the exit ramp terminals of parclo interchanges in Alabama and Georgia to identify high-risk locations in these two states. Seven high-risk locations were monitored by video cameras for 48-hours to observe the occurrences of WWD incidents. Results suggest that two locations in Alabama and two locations in Georgia experienced multiple WWD incidents within 48-hours of a typical weekend. Conclusion: The observation of WWD incidents at high-risk locations demonstrates strong evidence that the model could identify the exit ramp terminals with high risk of WWD. Practical Applications: Transportation agencies can use this model to assess the risk of WWD at the exit ramp terminals within their jurisdictions and identify the high-risk locations for countermeasures implementation.

Physical environmental opportunities for active play and physical activity level in preschoolers: a multicriteria analysis

BackgroundActive play opportunities seems to influence the level of physical activity during childhood. However, a gap remains about which environmental opportunities including the daycare physical environment could have a positive impact on the level of physical activity in preschoolers.Objectives(1) To develop an index to measure the environmental opportunities of free active play for preschoolers of middle-income countries; (2) to check the relationship and contribution of the index to explain objectively the level of physical activity.MethodsA quantitative, cross-sectional, exploratory study with 51 preschool children. The established criteria for the index according to the literature were: (1) Outdoor time on typical days of the week. (2) Outdoor time on a typical weekend day. (3) The presence of internal space and external environment in the child’s home that allows playing. (4) Presence of patio with space for games at the school. (5) Presence of a playground with a toy at the school. We applied multi-attribute utility theory for the determination of the multicriteria index of physical environmental opportunities. Pearson’s correlation analysis and simple linear regression were used to verify the association between the index and the physical activity level.ResultsThe index showed a positive correlation with the level of physical activity, e.g., the average time of MVPA (r = 0.408, p = 0.003). The univariate linear regression demonstrated that the quality of physical environmental opportunities for physical activity explained 20% of the preschooler’s classification as active and 16% of the time in moderate to vigorous physical activity (p < 0.001).ConclusionPhysical environmental opportunities for active play have a positive effect on physical activity in preschoolers and should be encouraged in different social segments.

When are alcohol-related blackout Tweets written in the United States?

BackgroundAlcohol use varies throughout the year and often peaks on weekends or during celebrations (e.g., New Year’s). There is not a perfect correlation between alcohol use and negative consequences, and the extent to which one particularly risky consequence—an alcohol-related blackout—is more common during certain times of the year is unknown. Identifying when blackouts occur may help identify which periods are associated with more risk and be critical in designing public health campaigns. Thus, we examined Twitter data to ascertain whether alcohol-related blackouts occur more during certain holidays/celebrations than typical weekends and whether they differed in timing from general alcohol-related Tweets. MethodsWe used a Twitter-sponsored platform to access unique Tweets written in the United States referencing blackouts (e.g., “blackout”) and alcohol generally (e.g., “drunk”). ResultsThe final dataset included 3.5 million blackout Tweets and 591 million alcohol Tweets (written between 2009 and 2020). Both blackout and alcohol Tweets were written in the late evening, on weekends, and during certain holidays (New Years, St. Patrick’s). However, relative to typical weekends, only blackout Tweets were more common during Thanksgiving and only general alcohol-related Tweets were more common during Cinco de Mayo. ConclusionWhile blackout and alcohol-related Tweets were similar in time of day (peaking in the evening) and day of week (peaking on weekends), they differed during certain celebrations/holidays, suggesting that while alcohol use may be more common during some celebrations, others are more associated with serious harms.

A Simplified Approach to Quantifying a Child's Bilingual Language Experience

Purpose Bilingual children's linguistic experience can vary markedly from child to child. For appropriate audiological assessment and intervention, audiologists need accurate and efficient ways to describe and understand a bilingual child's dynamic linguistic experience. This report documents an approach for quantitatively capturing a child's language exposure and usage in a time-efficient manner. Method A well-known pediatric bilingual language survey was administered to 83 parents of bilingual children, obtaining information about the child's exposure to (input) and usage of (output) Spanish and English for seventeen 1-hr intervals during a typical weekday and weekend day. Results A factor analysis indicated that capturing linguistic exposure and usage over three grouped-time intervals during a typical weekday and weekend day accounted for ≥ 74% of the total variance of the linguistic information captured with the full-length survey. Conclusions Although further confirmation is required, these results suggest that collecting language exposure and usage data from parents of bilingual children for three grouped-time intervals provides similar information as a comprehensive hour-by-hour approach. A time-efficient method of capturing the dynamic bilingual linguistic experience of a child would benefit pediatric audiologists and speech-language pathologists alike.

Exploring the relationship between adults’ perceptions of sedentary behaviours and psychological stress: Is your mindset stressing you out?

ABSTRACT Mindsets that people hold regarding activity adequacy play an integral part in various health outcomes. Yet, little is known about the relationship between the mindset one has about their sedentary behaviour levels and psychological stress. As such, the present study sought to understand if adults’ perceptions of themselves as compared to others of the same age, specifically perceptions about their level of sedentary behaviours, is a significant predictor of psychological stress. Three-hundred and seventy-four adults (n female = 279, n male = 95; M age = 60.4% aged between 18 and 24) completed an online survey package that included two multi-scale instruments to assess perceived stress symptoms and actual time spent sitting during a typical week, and two single-items to measure perceptions of their level of sedentary behaviours during a typical week (i.e., typical weekday, weekend day). Cross-sectional results indicated that perceived sedentary behaviour relative to others on a typical weekend day explained significant albeit modest unique variance in perceived stress scores, even after controlling for covariates including actual sitting time on a typical weekend day (t(363) = 2.35, p = 0.019, R2 increment = 0.010). Weekday perceptions failed to be an influential factor (t(363) = −0.28, p = 0.780, R2 inc = .000). These findings suggest that a sedentary behaviour mindset, yoked within a social comparison framework, may be important for understanding psychological stress.

The impact of the UK’s COVID-19 lockdowns on energy demand and emissions

Around the world, efforts to contain the COVID-19 pandemic have profoundly changed human activity, which may have improved air quality and reduced greenhouse gas emissions. We investigated the impact of the pandemic on energy demand and subsequent emissions from electricity and gas throughout 2020 in the UK. The daily pattern of electricity demand changed in both lockdowns, with weekday demand shifting to that of a typical pre-pandemic weekend. Energy demand in 2020 was modelled to reveal the impact of the weather and the pandemic. The first lockdown reduced demand by 15.6% for electricity and 12.0% for commercial gas, whereas the second lockdown produced reductions less than half. Domestic gas demand did not change during the first lockdown, but increased by 6.1% in the second, likely due to increased domestic heat demand. The changes in demand for gas resulted in little change to overall gas consumption emissions during the pandemic. For electricity, large emission reductions occurred during the two lockdowns: up to 22% for CO2, 47% for NO x , and 29% for PM2.5. Yet, the largest CO2 emission reduction for electricity in 2020 (25%) occurred before the pandemic, which happened during a warm and stormy spell with exceptional wind generation. These observations suggest that future similar changes in activity may result in little change for gas demand and emissions. For electricity, emission reductions through changes in energy demand are made possible by the generation mix. To enable further emission reductions in the future, the generation mix should continue to decarbonise. This will yield emission reductions in both times of lowered energy demand, but more importantly, during times of high renewable output.

Screen time use impacts low-income preschool children's sleep quality, tiredness, and ability to fall asleep.

Sleep is increasingly recognized as a vital part of health. Screen time has been linked to sleep quality in children. The purpose of this study was to analyze associations between screen time and sleep characteristics among low-income preschoolers. A total of 1,700 preschool-aged children participated in this study at 50 federally and state-funded preschool centers in Michigan. Baseline measurement for an ongoing longitudinal intervention trial was obtained for cross-sectional use. At baseline, parents reported the number of hours their child spent engaging in screen time on a typical week day and weekend. An aggregate measure of total screen time was created. Parents reported on the quality of their child's sleep, how often they were tired during the day, and whether they had difficulty falling asleep. A mixed model linear regression was created to analyze data. Controlling for child's age, race, and parental income, children who engaged in more screen time were significantly more likely to have more trouble falling or staying asleep, be tired during the day, and had worse quality of sleep (P values = .004, .006 and .001, respectively). Spearman correlations of screen time, sleep variables and demographics show parents of Black children reported significantly higher weekly screen time than parents of non-Black children (r = 0.23, P < .001) and that tiredness was associated with Black race (r = 0.15, P < .001), Hispanic/Latino ethnicity (r= -0.14, P < .001), and parental education (r = 0.06, P = .016). This report confirms prior associations between screen time and sleep reported in other pediatric populations. Further research is needed to confirm these results in other populations using more rigorous measures of screen time, sleep, and physical activity, as well as longitudinal assessments. Despite these limitations, findings suggest that interventions to help parents limit children's screen time and impact their sleep health merit investigation.

Mix of destinations and sedentary behavior among Brazilian adults: a cross-sectional study

BackgroundSedentary behavior is influenced by contextual, social, and individual factors, including the built environment. However, associations between the built environment and sitting time have not been extensively investigated in countries with economies in transition such as Brazil. The objective of this study is to examine the relationship between sitting-time and access to a mix of destinations for adults from Sao Paulo city, Brazil.MethodsThis study uses data from the Health Survey of Sao Paulo. Sedentary behavior was assessed by a questionnaire using two questions: total sitting time in minutes on a usual weekday; and on a usual weekend day. The mix of destinations was measured by summing the number of facilities (comprising bus stops, train/subway stations, parks, squares, public recreation centres, bike paths, primary health care units, supermarkets, food stores, bakeries, and coffee-shops) within 500 m of each participant’s residence. Minutes of sitting time in a typical weekday and weekend day were the outcomes and the mix of destinations score in 500 m buffers was the exposure variable. Associations between the mix of destinations and sitting time were examined using multilevel linear regression: these models accounted for clustering within census tracts and households and adjusted for environmental, sociodemographic, and health-related factors.ResultsAfter adjustment for covariates, the mix of destinations was inversely associated with minutes of sitting time on a weekday (β=− 8.8, p=0.001) and weekend day (β=− 6.1, p=0.022). People who lived in areas with a greater mix of destinations had shorter average sitting times.ConclusionGreater mix of destinations within 500 m of peoples’ residences was inversely associated with sitting time on a typical weekday and weekend day. In Latin American cities like Sao Paulo built environments more favorable for walking may contribute to reducing sedentary behavior and prevent associated chronic disease.

Estimating hourly PM2.5 concentrations at the neighborhood scale using a low-cost air sensor network: A Los Angeles case study

Predicting PM2.5 concentrations at a fine spatial and temporal resolution (i.e., neighborhood, hourly) is challenging. Recent growth in low cost sensor networks is providing increased spatial coverage of air quality data that can be used to supplement data provided by monitors of regulatory agencies. We developed an hourly, 500 × 500 m gridded PM2.5 model that integrates PurpleAir low-cost air sensor network data for Los Angeles County. We developed a quality control scheme for PurpleAir data. We included spatially and temporally varying predictors in a random forest model with random oversampling of high concentrations to predict PM2.5. The model achieved high prediction accuracy (10-fold cross-validation (CV) R2 = 0.93, root mean squared error (RMSE) = 3.23 μg/m3; spatial CV R2 = 0.88, spatial RMSE = 4.33 μg/m3; temporal CV R2 = 0.90, temporal RMSE = 3.85 μg/m3). Our model was able to predict spatial and diurnal patterns in PM2.5 on typical weekdays and weekends, as well as non-typical days, such as holidays and wildfire days. The model allows for far more precise estimates of PM2.5 than existing methods based on few sensors. Taking advantage of low-cost PM2.5 sensors, our hourly random forest model predictions can be combined with time-activity diaries in future studies, enabling geographically and temporally fine exposure estimation for specific population groups in studies of acute air pollution health effects and studies of environmental justice issues.

Screen media use and sleep disturbance symptom severity in children

ObjectivesFew studies have sought to evaluate how screen media use relates to symptoms of sleep-wake disturbances. To extend these prior studies in a large sample of children, this study examined associations of different types of screen media with symptom severity of different classes of sleep-wake disturbances. This study was preregistered here. DesignThis study utilized the baseline cross-sectional survey administered within the Adolescent Brain Cognitive Development Study (ABCD; Release 2.0). ParticipantsABCD recruited over 11,000 U.S. children age 9–10 across 21 study sites using an epidemiologically-informed school-based recruitment strategy. MeasurementsChildren reported typical weekend and weekday use of TV, video, video game, social media, texting, and video chat, and parents completed reports of the child's symptom severity of sleep-wake disturbances via the Sleep Disturbance Scale for Children. ResultsGreater screen media use, TV, video, and video game use, was associated with decreased sleep duration, increased sleep onset latency as well as greater excessive sleepiness, insomnia, and overall sleep disturbance symptom severity. Use of these screen medias were also associated with clinically relevant sleep problems. Ethnoracial differences emerged in screen use and sleep, but did not moderate the association between screen use and sleep. ConclusionsGreater use of screen medias was not just associated with longer sleep onset latency and shorter sleep duration, but also increased severity of multiple types of sleep-wake disturbances. Future research should use longitudinal designs to determine the direction of these associations in adolescent populations.

Natural Language Input: Maternal Education, Socioeconomic Deprivation, and Language Outcomes in Typically Developing Children.

Purpose The current study was designed to investigate the differences in language input related to family factors (maternal level of education [MLE] and socioeconomic level of deprivation [SLD]) and their association with language outcomes in preschoolers. Method This study used New Zealand SLD and MLE classification systems to examine differences in language input related to these factors among 20 typically developing preschool children aged 2-5 years. The quantity of children's language input (adult words [AWs], conversational turns [CTs]) was calculated using the Language ENvironment Analysis audiotaping technology for two typical weekend days. Four 5-min Language ENvironment Analysis recording segments were transcribed and coded, and parental language strategies were classified as optimal language strategy, moderate language strategy, or sub-optimal language strategy (S-OLS) for child language outcomes. The receptive and expressive language of each child was assessed using the Preschool Language Scales-Fifth Edition. Results Mann-Whitney U tests showed significant differences between the quantity of language input (AWs/hr, CTs/hr) for high and low MLE and high and low SLD groups. Consistent with the literature, the use of S-OLSs was significantly lower for families with high MLE (Mdn = .25, IQR = .14) and low SLD (Mdn = .22, IQR = .13) than for families with low MLE (Mdn = .41, IQR = .24) and high SLD (Mdn = .41, IQR = .26). Spearman correlation coefficients indicated significant associations between language input (AWs/hr, CTs/hr, S-OLSs) and language outcomes. Conclusions Reduced language input and the frequent use of S-OLSs associated with low maternal education and high deprivation and low language outcomes for these children highlight the importance for all parents/families to learn optimal language strategies to support the development of strong language skills in their children in young age.

Home Use of Remote Microphone Systems by Children with Hearing Loss

Home Use of Remote Microphone Systems by Children with Hearing Loss