Average Weekday Research Articles

Cross-Lagged Associations Among Sleep, Headache, and Pain in Pediatric Mild Traumatic Brain Injury: An A-CAP Study.

To test cross-lagged associations among sleep, headache, and pain in pediatric mild traumatic brain injury (mTBI). Children and adolescents aged 8.0 to 16.9years who sustained a mTBI and presented to 1 of 5 pediatric emergency departments across Canada completed assessments at 1-week, 3 months, and 6 months post-injury as part of a larger prospective cohort study. Sleep disturbance was measured using 7 sleep items from the Child Behaviour Checklist. Sleep duration was measured using average weekday and weekend sleep from the Healthy Lifestyle Behaviours Questionnaire. Pain intensity was measured using an 11-point numerical rating scale. Headache severity and associated functional impairment were measured using the Headache Impact Test and 1 item from the Health and Behaviour Inventory. Analyses included trivariate-indicator random-intercept cross-lagged panel models. Of 633 recruited children, 563 were included in the current study. Headache showed significant within-person, bidirectional, cross-lagged associations with sleep disturbance and duration, as well as with pain intensity. More specifically, worse headache predicted greater sleep disturbance (1-week to 3 months and 3 months to 6 months: Bs = .47, Ps ≤ .013) and shorter sleep duration (1-week to 3 months: B = -.21, P = .006), while greater sleep disturbance predicted worse headache (1-week to 3 months: B = .08, P = .001). Worse headache also predicted higher pain intensity (1-week to 3 months & 3 months to 6 months: Bs ≥ 1.27, P s < .001), while higher pain intensity predicted worse headache (3 months to 6 months: Bs ≥ .03, Ps ≤ .042). No cross-lagged associations involving sleep disturbance or duration with pain intensity were significant. Significant bi-directional, cross-lagged associations exist between headache and both sleep and pain. The findings suggest that early intervention for headaches may help prevent later sleep disturbance and pain after pediatric mTBI.

Evaluation of the Impacts of On-Demand Bus Services Using Traffic Simulation

This paper uses smart card data from Melbourne’s public transport network to model and evaluate the impacts of a flexible on-demand transport system. On-demand transport is an emerging mode of urban passenger transport that relies on meeting passenger demand for travel using dynamic and flexible scheduling using shared vehicles. Initially, a simulation model was developed to replicate existing fixed-schedule bus performance and was then extended to incorporate on-demand transport services within the same network. The simulation results were used to undertake a comparative analysis which included reliability, service quality, operational efficiency, network-wide effectiveness, and environmental impacts. The results showed that on-demand buses reduced average passenger trip time by 30%, increased vehicle occupancy rates from 8% to over 50%, and reduced emissions per passenger by over 70% on an average weekday compared to fixed-schedule buses. This study also offers insights for successful on-demand transport implementation, promoting urban sustainability. It also outlines future research directions, particularly the need for accurate short-term passenger demand prediction to improve service provision and passenger experience.

Potential of e-bikes to replace passenger car trips and reduce greenhouse gas emissions

In Sweden, the transport sector accounts for 32% of greenhouse gas emissions, with passenger cars contributing to 62% of these. In this context, electric bikes, commonly known as e-bikes, have emerged as a promising solution for reducing carbon emissions in the transport sector. This paper explores the potential of e-bikes in substituting passenger car trips and reducing transportation-related emissions. To achieve this objective, we use a synthetic population in the Västra Götaland (VG) region, Sweden, with daily activity schedules and simulate an average weekday of travelling with e-bikes instead of their private cars. For assessing the potential for e-bike substitution, the current literature often relies on trip-level analysis, which does not adequately consider people’s daily travel-activity plans, resulting in an unrealistic estimation of replaceable trips and their carbon emissions reduction. Combining an e-bike speed model by agents’ characteristics and an open-source routing engine, our simulation identifies potential car trips that can be replaced with e-bikes, considering all activities and the travel between them for an average weekday. The simulation results suggest that e-bikes could replace 57.6% of car trips. Building on this, we explore the potential reduction in greenhouse gas emissions from car trips taken by residents in the study area. If the top 70% of feasible car users, ranked by shortest to longest daily travel distances, switch to e-bikes, emissions could be reduced by 10.1% compared to 2018 levels. If all feasible car users adopt e-bikes, a reduction of up to 22.8% in emissions could be achieved, representing the upper limit presented by our study. The findings also reveal that males under 40 years old provide the highest e-bike substitution rates in their daily activity schedules, and in areas with a high population density, replaceable car trips are more common than in rural areas. This research provides valuable insights into e-bike substitution and its impact on emission reduction. It contributes to the existing literature through its modelling approach that realistically considers individuals’ socio-demographic characteristics and daily activity schedules when assessing the substitution potential.

A Case Study of Ridership and Equity Implications of All-Day Massachusetts Bay Transportation Authority Commuter Rail Service

As the COVID-19 pandemic emerged from the acute phase and vaccines became widely available in 2021, transit agencies like the Massachusetts Bay Transportation Authority (MBTA) faced a daunting challenge of drawing riders back into their systems. Despite systemwide staffing shortages, service disruptions, and ridership patterns that have yet to return to 2019 levels, ridership on MBTA’s Commuter Rail has consistently outperformed the agency’s other services in the current COVID recovery era. In April 2021, as part of a multiyear vision to overhaul the system, MBTA switched from a schedule focused on serving traditional peak-period commuters to providing steady, all-day service modeled on more legible “clockface” departures. This study used regression analysis to show this change was consistent with the Commuter Rail outperforming other modes in ridership recovery, generating over 7,000 average daily weekday boardings and over 9,000 average weekend boardings. Latent class analysis demonstrated that this schedule shift primarily benefited riders traveling for a variety of purposes, rather than just traditional office work. This group, which we referred to as general riders, was more likely to be low-income (household income below $75,000), young (25 or younger), and Hispanic. This research demonstrated the ability of all-day service on Commuter Rail to serve MBTA’s key aims of increasing ridership and providing more equitable, accessible service.

지역문화정책 대상범위에 관한 연구

The purpose of this study is to investigate the scope of local cultural policies through an empirical study on the cultural enjoyment gap. For this purpose, the cultural enjoyment status of culturally marginalized groups derived from the review of previous studies was compared and analyzed within the same basic local government. In addition, the experience level of each cultural genre was investigated and analyzed by dividing cultural enjoyment into viewing, participation, and education stages. The results of the analysis showed that, first, when it comes to leisure time for cultural enjoyment, those in their 60s and older, those with lower income levels, and those living in towns and villages have more leisure time on an average weekday. Second, 25% of all respondents have experienced veiwing cultural events. Movies and museums were found to be universal cultural enjoyment genres, and in most genres, the underrepresented groups were found to be real. Third, direct participation in cultural events was lower among those under the age of 50, those with lower median income, and those living in the urban. Fourth, the experience of cultural education was also low, with significant mean differences by class.

Correspondence distribution over a network in designing public urban passenger transportation tasks

Introduction. The process of planning public transport is divided into a few number of tasks in strategic, tactical and operational levels, which include the development route system, the establishment of traffic intensity along routes, the design of the structure of road transport vehicles, the distribution of the current road transport vehicles along the routes, determining the required amount of the subsidies, etc. Materials and methods. The article presents a multi-criteria mathematical model of transportation design, according to which the tasks have been solved by distributing (limited or unlimited) transport resources between the permissible routes of the transport network in accordance with a variety of efficiency criteria, which can be the subject to appropriate restrictions. The formation acceptable routes on the transport network can be carried out by means of the algorithms developed, for example, in the framework of solving TNDP and TNDFSP tasks. The routes can also be adjusted by experts. Transport demand is set by a matrix of passenger correspondence generated for the entire period of traffic on a weekday, to ensure that all passenger flows along the route network are taken into account, and not only the periods of the greatest traffic intensity. The calculation of the parameters of the transport offer in the process of solving the problems of transportation design is carried out based on the results of the passenger correspondence distribution on the route network (PAP), which is a complex problem unsolved today. The article describes the developed PAP methodology based on a flexible passenger strategy that takes into account the waiting time for transport, the proximity of the route through an empirical model of dividing demand by the length of trips, the preferences of transport modes, the possible redistribution of passenger flows between the stopping points of the network located within a walking distance. Results. The tasks of designing public transport transportation have been formulated, a multi-criteria mathematical model of their solution has been developed. The method of distribution of passenger flows on the route network based on a flexible passenger strategy has been described. The effectiveness of the developed PAP methodology is shown on test calculations, which were carried out using passenger correspondence, an average weekday in October 2019, obtained by processing validations of e-tickets of urban passenger transport in Krasnoyarsk. Discussion and conclusion. The practical implementation of the described methodology for the distribution of passenger flows on the route network using relational database management systems (DBMS) MS SQL Server has been carried out.

Association between screen time and suspected developmental coordination disorder in preschoolers: A national population-based study in China.

Excessive screen exposure (ESE) is a growing global public health concern. This study aims to investigate the potential association between ESE and suspected developmental coordination disorder (DCD) in Chinese pre-schoolers, with or without siblings. A retrospective cohort study was conducted, involving 126,433 children from 551 cities in China. The Little Developmental Coordination Disorder Questionnaire (LDCDQ) was employed to evaluate motor impairment in children, while parents provided information on their children's screen time in the past year. A mixed and multi-level logistic regression model was used to analyze the associations of all screen exposure measurements from the past year with LDCDQ scores and the risk of suspected DCD. The prevalence of excessive screen exposure was 67.6% (>1 h per day) and 28.9% (>2 h per day) in Chinese pre-schoolers. One hour's increase in weekday daily screen time, weekend daily screen time, and screen time before sleep in the past year was associated with a decreased total score of the LDCDQ (β were -0.690, -0.398, and -1.587, p < 0.001) and an increased risk of suspected DCD by 15.3%, 9.1%, and 46.8% when adjusting for the child, family and maternal health characteristics. Excessive screen exposure decreased the total LDCDQ scores by 1.335 (>1 vs. ≤1 h) and 1.162 (>2 vs. ≤2 h) and increased risks of suspected DCD by 44.0% (>1 vs. ≤1 h) and 31.1% (>2 vs. ≤2 h) with statistical significance (each p < 0.05). The stratified analysis showed that the association between screen time and LDCDQ score was stronger in children without siblings than in those with siblings. The risk of suspected DCD was highest for screen time exposure before bed compared with average weekday and weekend exposures. Parents should be advised to prevent their children from using electronic screens unsupervised, especially in one-child families.

The future of unpaid work: Estimating the effects of automation on time spent on housework and care work in Japan and the UK

Unpaid domestic work is vital for human reproduction and enables all other forms of work. In this article, we present first estimates of the impacts of “smart” and “AI” technologies on unpaid work. We ask what the likelihood is of various types of unpaid work being automated, and how this would change the time spent on domestic work and on the gendered division of labour. We adapt three automation likelihood estimates for paid work occupations to estimate the automation likelihood of 19 domestic work tasks. Applying these estimates to Japanese and UK national time use data, we find that 50–60 % of the total time spent on unpaid work could be saved through automation. The savings are unevenly distributed: a Japanese woman aged 20–59 could save up to 3.5 h, a UK woman of the same age could save up to 3 h on an average weekday. A man in the UK could save 1.5 h and a Japanese man only 1 h on an average weekday. Domestic automation could free up to 9.3 % of women in Japan and 5.8 % of women in the UK to take up full- or part-time employment, pointing to substantial potential economic and social gains.

Freeway Crash Prediction Models with Variable Speed Limit/Variable Advisory Speed

Variable speed limit (VSL) and variable advisory speed (VAS) signs are efficient, cost-effective and among the state-of-the-art active traffic management (ATM) strategies. They adopt the idea of dynamically changing posted speed limits to improve highway safety performance and operation by harmonizing traffic speed. VSL/VAS system involves changing speed limits according to real-time traffic events and weather conditions. Hence, traditional average annual daily traffic (AADT) based crash prediction models may not capture the temporal effect of traffic characteristics due to the high level of aggregation. To address this issue, short-term safety performance functions (SPFs) with aggregation levels of average annual weekday hourly traffic (AAWDHT) and average annual weekday peak traffic (AAWDPT) along with AADT-based SPFs were developed using high-resolution traffic detector and VSL/VAS operational data. In this study, the Poisson log-normal model performed well at each level of aggregation and thus is recommended for developing short-term SPFs. In line with previous studies, traffic volume and standard deviation of speed were found to be positively associated with crash frequency in all the estimated models. In addition, it was found that implementation of VSL/VAS significantly reduced crash frequency by 15.97% and 26.14% for the AAWDHT and AAWDPT models, respectively. The safety improvement was captured in the short-term models in a more distinguished way than in the highly aggregated AADT-based model. The findings of this study pave the way for practitioners and policymakers to evaluate and select important parameters for VSL/VAS strategy implementation on freeways.

A case study of digital eye strain in a university student population during the 2020 COVID-19 lockdown in South Africa: evidence of an emerging public health issue

BackgroundThe COVID-19 pandemic resulted in a nationwide lockdown in South Africa, initiating a shift in society’s interaction to the online space. Students therefore became reliant on electronic devices for learning.ObjectiveThe study aimed to investigate the prevalence of digital eye strain (DES) in a university student population during the nationwide COVID-19 lockdown in South Africa.MethodsRandomly sampled 290 university students were surveyed online about their screen time and DES during lockdown. The survey included a validated screen time questionnaire to measure screen time in hours per day and a validated computer vision syndrome questionnaire (CVS-Q) to measure the frequency and intensity of symptoms during edevice use (s). Descriptive statistics were used to analyze CVS-Q scores and screen time.ResultsThe mean (SD) age of the sample was 21.04 _ 2.32 years. Of these, 82.41% used smartphone devices and 55.52% of the participants did not use any optical correction. The prevalence of DES during COVID-19 lockdown in 2020 was 64.24%. Screen time on an average weekday and over the weekend, as a primary activity, had a median of 13 hours per day during lockdown.ConclusionThe high prevalence of digital eye strain may be a harbinger of a decrease in student performance. Creating awareness of proper visual hygiene amongst students is paramount in decreasing the high prevalence of DES.

The association between sleeping behavior, obesity, psychological depression, and eating habits among adolescents in the emirate of Abu Dhabi-United Arab Emirates.

ObjectiveThe study aimed to investigate the association between sleeping behavior (specifically sleep duration), body mass index (BMI), eating habits, and psychological mood depression among adolescents in the Emirate of Abu Dhabi- UAE.Methods and materialsA subsample of three hundred and ninety-five participants (209 females and 186 males) from middle and high schools (aged 12–18 years) in the emirate of Abu Dhabi completed the surveys in the presence of their parents and two research assistants. Measures of daytime sleepiness and other sleep parameters (sleep duration on weekdays and weekends), eating habits, and mood depression questionnaires were reported.ResultsDifferences in BMI between males and females were statistically significant (26.12 ± 4.5 vs. 24.4 ± 4.3; p < 0.01). There was a negative linear association (p < 0.01) between the students’ BMI and the weekday/ weekend sleep duration. The average weekday and weekend sleep duration ranged from 5.7 hours (weekdays) to 9.3 hours(weekend). The study showed that an increase in BMI was correlated to mood depression (r = 0.396, p<0.01). In terms of eating habits, there was a significant association between eating unhealthy food and sleep duration; 72.6% of students who slept less than 6 hours reported unhealthy eating habits (p <0.05).ConclusionThe study showed a clear association between short sleep duration and obesity among adolescents in the UAE. This relationship between sleep duration and obesity is less studied and less understandable. Future research about exploring how sleeping behaviors can affect obesity during adolescence can support understanding this association and create an effective intervention.

Short-Term Safety Performance Functions for Freeways Including High Occupancy Vehicle Lanes

Short-term safety performance functions (SPFs) were proposed to achieve accurate and dynamic crash frequency predictions and bridge the gap between annual crash frequency prediction and real-time crash likelihood prediction. The proposed short-term SPFs consider the temporal variation in crashes and traffic characteristics. This study contributes to the literature by developing short-term SPFs at hourly aggregation levels for freeways that include high-occupancy vehicle (HOV) lanes using loop detector data from Arizona State, U.S. Variables that capture the short-term traffic turbulence were prepared and considered in the developed SPFs. Further, this study investigated the factors contributing to crash frequency using three different ways to represent the hourly traffic: annual average hourly traffic, annual average weekday hourly traffic (AAWDHT), and annual average weekday peak hour traffic (AAWDPT). The results indicated that the traffic volume variable was found to be significant in all the developed models. Further, the variables that represent the speed and occupancy differences between HOV lanes and general-purpose lanes were positively associated with crash frequency. This study proposed a series of variables that reflect the short-term traffic turbulence. The models comparison results showed an improvement in [Formula: see text] from 2.4% to 12.8% when including the proposed variables. Further, the results indicated that the Poisson-lognormal approach outperformed the basic negative binomial model in both AAWDHT, and AAWDPT models. Further, the AAWDPT model was found to have the best performance in relation to Akaike information criterion and [Formula: see text].

Traffic noise reduction attributed to roadside vegetation: ohio case study

This paper reports the findings of a research study which examined the noise reduction associated with roadside vegetation. A case study location along a major freeway in Columbus, Ohio, was utilized. Noise measurements were obtained at two locations in a neighborhood adjacent to the freeway. The neighborhood was partially shielded from the freeway by a stand of bushes and trees typical of roadside vegetation in Ohio. One location with high-density vegetation was completely shielded from the freeway while the second had lower-density vegetation with some direct line-of-sight downstream of the position. Noise measurements at the site were conducted in September 2019 on an average weekday under typical meteorological conditions for the region. Measurements were obtained simultaneously at each position to permit direct comparison of the noise reduction. Analysis indicated that the noise reduction attributed to the vegetation was approximately 3.0 dBA with an additional 1.0 dBA of reduction at the high-density position. Models of the site using FHWA TNM indicated that the modeled noise reduction was lower than what was measured in the field. The results of this case study add the body of knowledge on the topic of traffic noise reduction attributed to the presence of roadside vegetation.

Dog walk frequency and duration: Analysis of a cohort of dogs up to 15 months of age

Regular exercise for dogs has health and welfare benefits. This study sought to address a gap in existing research regarding what constitutes ‘common’ age-specific walking practices by owners of young dogs, and how these practices change as the dogs reach adulthood. Dog owners living in the United Kingdom and the Republic of Ireland participating in a longitudinal study reported the frequency and duration of their average weekday and average weekend walks when their dogs were aged 16 weeks (n = 2225), 9 months (n = 1200) and 15 months (n = 808). Owners also reported the amount of time their dogs spent on lead during these walks. For the statistical analysis, a subpopulation of dogs with data regarding walking practices at all three timepoints were used (n = 609). At all three timepoints dogs were most commonly walked twice a day. Commonly, 16-week-old puppies were walked for a total of 30 min on weekdays and weekend days, whereas dogs aged 9 and 15 months were walked for a total of 1 h on weekdays and 2 h on weekend days. Commonly, 16-week-old puppies spent ≥75% of total walk time on lead, whereas the older dogs mostly spent < 25% of total walk time on lead on weekdays and weekend days. Most owners reported using a short lead rather than a long lead (for example, a flexi-lead, training line, long line). For the subpopulation of dogs for which data were available at all three timepoints, the total duration of walks on both an average weekday and average weekend day increased significantly as the dogs aged. The proportion of total walk time spent on lead on both an average weekday and average weekend day significantly decreased as the dogs aged. This study can provide veterinarians and dog behaviourists with an insight into the common walking practices of owners with puppies and young dogs, which potentially could help them advise their clients on appropriate practices for the health and wellbeing of their dogs. Additionally, this study can potentially be used as a baseline for comparison for other populations of dogs at these age points, as the practices described by owners within this large sample offer an indication of the walking practices by owners of young dogs. Future research within this longitudinal study will explore how walk frequency and duration are associated with dog behaviour, welfare indicators and health outcomes, and what factors are associated with walk frequency and duration.

Sleep pattern regularity and measures of infant weight and length during the first 6 months

PurposeTo examine the association between sleep pattern regularity and measures of weight and length in infants. Design and methodsThis was a prospective observational study conducted in a university-affiliated children's hospital in northern Taiwan. A total of 316 healthy infants recruited during their 6-month well-child checkups had their weight and recumbent length measured, and wore an actigraph on the ankle for a week. Based on average weekday, weekend, and all-week sleep durations, infants were categorized into 3 groups: regular sleep, weekend catch-up sleep, and weekend sleep curtailment. General linear model analyses were performed with the 3 sleep regularity groups as the primary predictor variable of interest and infant anthropometry as the dependent variable. ResultsAt risk of overweight, overweight, and obese was present in a total of 62 (19.6%) infants. In both unadjusted and adjusted models, infants in the weekend catch-up sleep group (30.4%) and those in the weekend sleep curtailment group (34.5%) had significantly higher weight-to-length ratios, body mass index, weight-for-age z-scores, and weight velocity of 6-month increments z-scores when compared with infants in the regular sleep group (35.1%, all p < 0.05). ConclusionsDifferences in weekday-weekend sleep exist as early as in the first 6 months of life, and both catch-up sleep and sleep curtailment over the weekend is associated with higher measures of weight and length in infants. Practice implicationsSleep assessments in well-child checkups should include not only global assessments of average sleep duration but also address sleep patterns and their regularity.

Habitual Sleep, Sleep Duration Differential, and Weight Change Among Adults

We assessed longitudinal associations between diary-measured sleep duration and clinically assessed body mass index (BMI) among 784 men and women enrolled in the Wisconsin Sleep Cohort Study (mean [SD] age = 51.1 [8.0] years at baseline). The outcome was BMI (kg/m2). Key predictors were habitual sleep duration (defined as average weekday nighttime sleep duration) and sleep duration differential (defined as the difference between average weekday and average weekend nighttime sleep duration) at each data collection wave. Men with shorter habitual sleep duration on weekdays had higher BMI than men with longer habitual sleep duration on weekdays. Participants with larger differentials between weekday and weekend sleep duration experienced more rapid BMI gain over time for both men and women. Inadequate sleep, characterized as shorter habitual sleep during weekdays and larger weekday-weekend sleep differential, is positively associated with BMI levels and trajectories among men and women in mid-to-late life.

Audiobook routines: identifying everyday reading by listening practices amongst young adults

PurposeThis article explores, identifies and conceptualises everyday audiobook reading practices amongst young adults.Design/methodology/approachSemi-structured interviews were conducted with ten Swedish audiobook users aged 18–19. The material was analysed using qualitative content analysis and focused on their audiobook use during an average weekday, as this was the time that they listened the most. The theoretical framework consists of theories on practice, time and everyday routine.FindingsFive timespaces emerged when audiobook practices were most prevalent: morning routines, commuting routines, school routines, after school routines and bedtime routines. Within these timespaces, several practices could be identified and conceptualised. Three mobile practices were commute listening, exercise listening and chore listening while more stationary practices were homework listening, schoolwork listening and leisure listening. An unexpected finding was how audiobooks routinely were used to aid respondents’ wellbeing. This wellbeing listening was used to alleviate stress, loneliness and help listeners relax or fall asleep. Furthermore, respondents switch between Music, Audiobooks and Podcasts, which is conceptualised as MAP-switching.Originality/valueThere is a scarcity of research on audiobook use, and this paper contributes with new knowledge on audiobook reading practices, how audiobooks fit into everyday routine and provides concepts to aid further research on audiobook practices.

Digital Media Exposure and Predictors for Screen Time in 12-Month-Old Children: A Cross-Sectional Analysis of Data From a German Birth Cohort.

Background: Early exposure to digital media may affect the physical and cognitive development in young children. The American Academy of Pediatrics and national guidelines recommend no digital media use at all under the age of 18 months. The aim of our study was to determine the actual exposure to digital media in 12-month-old infants and to reveal potential risk factors for screen time.Methods: In this prospective cross-sectional survey, data was collected from the KUNO Kids birth cohort study using parent-report questionnaires regarding the media exposure of the study child. We determined age at first contact with different digital media, mean screen time on an average weekday, and the influence of major demographic and socioeconomic factors.Results: Data for screen time analysis was available for 630 children. In summary, 45% of children had already been exposed to digital media by their first birthday. The most frequent first digital media exposure was the TV (33.0%) followed by smartphones (16.9%), both most commonly exposed to around the age of 8 months. On a regular weekday, 20% of the children spent 0.5–1 h in front of a TV and 9% were exposed to a smartphone for the same time frame, compared to 31% of joint parent-child media use. Predictors for screen time were having one sibling, less living space per person, and excessive TV use in the household, the latter of which doubled the chance of the child being exposed to digital media.Conclusion: A proportion of 10% of 1-year-old children were already regularly exposed to digital media. The TV remains the most predominant device but new media, particularly smartphones, might be catching up. Our study provides further support that family TV time is a major predictor of infant screen time. Pediatric recommendations should be re-evaluated in the light of the actual exposure to digital media already in infancy and parents should be proactively counseled regarding possible effects on child development.

Habitual sleep, sleep duration differential, and weight change among adults: Findings from the Wisconsin Sleep Cohort Study

ObjectivesAssess longitudinal associations between diary-measured sleep duration and clinically assessed body mass index (BMI). DesignMultilevel growth curve analyses examined how within-person changes and between-person differences in habitual sleep duration were associated with BMI trajectories. SettingSleep diaries across 2-6 consecutive weekday and weekend nights at each data collection point, repeatedly collected at approximate 4-year intervals, for an average of 9.2 (standard deviation [SD] = 3.6) years between 1989 and 2011. ParticipantsAbout 784 participants (47% women) enrolled in the Wisconsin Sleep Cohort Study (mean [SD] age = 51.1 [8.0] years at baseline). MeasurementsThe outcome variable was BMI (kg/m2). Key predictors were habitual sleep duration (defined as average weekday nighttime sleep duration) and sleep duration differential (defined as the difference between average weekday and average weekend nighttime sleep duration) at each data collection wave. ResultsMen with shorter habitual sleep duration on weekdays had higher BMI than men with longer habitual sleep duration on weekdays (β = −0.90 kg/m2/hour, se = 0.34, p = .008). Participants with larger differentials between weekday and weekend sleep duration experienced more rapid BMI gain over time for both men (β = 0.033 kg/m2/year per hour differential, se = 0.017, p = .044) and women (β = 0.057 kg/m2/year per hour differential, se = 0.027, p = .036). ConclusionThis study suggests that habitual short sleep is associated with higher BMI levels in men and that a larger weekday-weekend sleep differential is associated with increasing BMI trajectories among both men and women in mid-to-late life.

Association between sleep characteristics, ideal cardiovascular health, and systemic inflammation, NHANES 2017-2018.

There is conflicting evidence regarding the associations between sleep deprivation and inflammatory biomarkers indicative of cardiovascular disease risk, such as high-sensitivity C-reactive protein (hsCRP). The association between sleep habits and hsCRP was quantified in a nationally representative sample of adults in the United States and mediation by ideal cardiovascular health metrics was explored. A cross-sectional analysis of cardiovascular disease-free participants aged 20-79years from the 2017-2018National Health and Nutrition Examination Survey was conducted. The primary exposures were self-reported sleep duration, sleep debt (difference between the average weekday and weekend sleep duration), and ideal cardiovascular health (11-14 points). The primary outcome was hsCRP (high-risk≥3.0mg/L). Multivariable robust Poisson models were used to estimate prevalence ratios after multiple imputation. A subgroup analysis of shift workers was also conducted. Of 4027 participants included (mean age 46years; 52% female; 41% shift workers), the prevalence of sleeping <6h on weekdays was 9%, with 40% sleeping ≥9h on weekends. One-quarter had a high (≥2h) sleep debt, 82% had poor cardiovascular health, and 34% had high-risk hsCRP. There were no significant associations between weekday sleep duration or sleep debt with high-risk hsCRP, even among shift workers. Mediation analysis was not conducted. Ideal cardiovascular health was associated with a lower prevalence of high-risk hsCRP (prevalence ratios, 0.60, 95% CI, 0.48-0.75). The lack of significant associations suggests a complex interrelationship of hsCRP with factors beyond sleep duration. Examination of populations at highest risk of chronic sleep deprivation could help to elucidate the association with systemic inflammation-related outcomes.