Abstract Compositional data analysis (CoDA) is widely used to examine the associations between one’s balance of movement behaviors (sedentary behavior, physical activity, and sleep) and health outcomes. Existing reviews have primarily focused on reporting standards for physical activity and sedentary behavior, but have not considered the contribution of sleep reporting to our understanding of CoDA. Purpose To characterize device-based sleep data measurement, processing, and reporting in studies using CoDA to examine associations between movement behaviors and health indicators. Methods A systematic search was conducted in seven databases, along with supplemental strategies (forward and backward citation searches and expert review). Observational studies published since 2015 that employed CoDA approaches using isometric log-ratio transformations to examine the associations between movement behavior compositions utilizing device-based measures of sleep and health outcomes were included. Data extraction included items based on sleep actigraphy measurement, processing, and reporting practices recommended by the American Academy of Sleep Medicine. The National Institutes of Health Quality Assessment Tool for Observational Cohort and Cross-sectional Studies was used to assess study quality. Results Among the 70 included studies (n = 60 cross-sectional, n = 10 longitudinal), few articles reported key sleep measurement and processing information. Most articles (n = 67) included only one sleep component in the time-use composition, and less than half of the articles (n = 29) acknowledged sleep-related limitations. Reports were classified as having good (n = 60) or poor (n = 10) study quality. Conclusions This review identified inconsistencies in the measurement, processing, and reporting of device-measured sleep in studies using CoDA. Varying protocols and reporting on sleep data processing highlight the need for adoption of current standardized approaches and reporting practices. Future research should prioritize transparency and consistency to improve the validity and comparability of findings on sleep’s role as a key component of the integrative 24-h approach to health.

Objective: To examine rural-urban differences in perceived social and built environment characteristics and assess associations with the frequency of meeting physical activity guidelines among United States youth. Methods: We used data from the 2022-2023 National Survey of Children’s Health, a nationally representative sample of United States children and adolescents. Weighted cumulative logit models were used to determine associations between parental perceptions of social/built environments and number of days youth met physical activity guidelines, stratified by rural-urban status. Results: The total sample included 55,551 (Representative N=41,792,444, 11.9 ± 3.5 years, 48% female) youth. Positive perceptions of neighborhood support were associated with higher odds of meeting physical activity guidelines (OR:1.43; 95% CI:1.32,1.54) as were perceptions of school safety (OR:1.29; 95% CI:1.08,1.54). Access to neighborhood amenities was associated with higher odds of meeting guidelines (OR:1.18; 95% CI:1.05,1.34). For rural youth, neighborhood support (OR:1.62; 95% CI: 1.34,1.95) and neighborhood amenities (OR:1.26; 95% CI:1.05,1.52) were positively associated with odds of meeting guidelines. For urban youth, neighborhood support (OR:1.40; 95% CI:1.29,1.53) and school safety (OR:1.31; 95% CI:1.07,1.59) were positively associated with odds of meeting guidelines. Conclusions: Perceived social/built environmental factors are associated with youth physical activity, although associations differ by urbanicity.

Barriers to physical activity (PA) participation affect United States (US) youth’s ability to meet PA guidelines. There is evidence showing lower PA among rural versus urban youth due to fewer PA opportunities and resources. Out-of-school programs can help reduce geographic disparities in PA, but there is a dearth of literature on participation factors among rural youth. This study aimed to identify, describe, and synthesize peer-review literature on barriers and facilitators to participation in structured, out-of-school PA at multiple ecological levels for rural-dwelling, US youth. A systematic review was conducted November 2024 using Medline, PubMed, SPORTDISC, Web of Science, APA Psychinfo, and CINAHL for articles published 2000–2024. Articles needed to be (1) peer-reviewed; (2) English-language; (3) conducted among US rural populations; (4) examining barriers and/or facilitators to out-of-school, structured PA; and (5) conducted among youth ages 6–17. Articles focusing on participants with additional needs were excluded. A search of 3,070 articles was refined to a final sample of 39 articles. Participant factors were identified at multiple ecological levels, including environmental and program (programs and facilities, transportation and accessibility, resources and infrastructure, safety, cost/fees); social (family support and role models, peer support, lack of social support); and individual (interest, motivation, and enjoyment; skill development; time constraints and prioritization) levels. Rural youth participation in structured, out-of-school PA is informed by multi-level factors, including facilities and programs, transportation, resources and infrastructure, social support, and interest/motivation. Additional research is needed to examine participation factors among this population. Findings can be used to design and adapt out-of-school programs that meet the unique needs of youth in rural settings.

Background: Although several studies have reported associations between screentime and shortened sleep duration among adolescents, contextual relationships between different forms of screentime are not well understood. The purpose of this study was to examine how television (TV) watching (passive media use) and video/computer gaming (interactive media use) are associated with short sleep duration among 8th and 11th grade adolescents. Methods: We used data from adolescents (8th and 11th grade students) who participated in the Texas School Physical Activity and Nutrition (Texas SPAN) survey in 2015–2016. Sleep duration was the outcome variable, which was dichotomized into short sleep duration (less than 8 h) and meeting sleep recommendations (more than 8 h). Independent variables included daily TV screentime and video/computer game screentime. We used weighted logistic regression models to understand associations between sleep duration and both TV screentime and video/computer game screentime. Results: Among both 8th grade boys and Hispanic 8th grade girls, spending more than 2 h/day playing video/computer games was associated with greater odds of shorter sleep duration. Among 11th graders, TV screentime was associated with lower odds of shorter sleep duration. Conclusions: Watching TV and playing video/computer games have differential associations with sleep duration among adolescents, and these associations differ by grade, gender, and ethnicity. Researchers and public health agencies interested in associations between meeting sleep recommendations and screentime in adolescents should consider these contextual differences when designing and conducting studies related to electronic media use and sleep.

Later meal timing, increased variability in timing, and meal skipping are associated with negative health outcomes among children. Few studies examine whether these behaviors are different between the school year and summer. This study analyzed changes in meal timing (i.e., absolute timing, variability in timing, and meal skipping) from the school year to summer in elementary-aged children, and whether changes differed by child age, child sex, and/or household income. Parents (n = 1,004) of 1,004 children (ages 5–14 years, 50

INTRODUCTION:The purpose of this study was to assess the associations between perceived socioenvironmental neighborhood attributes and objectively assessed habitual physical activity among US adults as well as whether associations vary by sociodemographic characteristics. METHODS:We used data from the All of Us research program, a longitudinal cohort study of a diverse sample of Americans. Perceived neighborhood social cohesion, physical and social disorder, walkability, and sociodemographic characteristics were self-reported. Habitual physical activity was ascertained using Fitbit-derived step counts over ≥24 weeks. Generalized additive mixed-effects models were used to test the associations between perceived socioenvironmental neighborhood attributes and daily step counts. RESULTS:Among participants (n = 6716), average daily step count was 7274.1 (SD = 3353.6). Social cohesion (B = 117.15, SE = 30.12, P < .001) and walkability (B = 72.74, SE = 31.43, P = .021) were positively associated with step count. The association of social cohesion with step count was moderated by age, being strongest among younger adults (B for interaction term = -5.43, SE = 2.00, P = .001), whereas the association between walkability and step count was moderated by income, being strongest for the lowest income group (B = -211.57, SE = 90.92, P = .020). Despite not finding main effects on step count for perceived physical disorder, age- and income-moderated effects were observed, with opposite-direction associations found for low (inverse) versus mid-upper income (direct) (B = 229.66, SE = 94.48, P = .015) and for younger (inverse) versus older (direct) adults (B for interaction term = 4.48, SE = 2.01, P = .030). CONCLUSIONS:Perceived neighborhood social cohesion, walkability, and physical disorder are associated with habitual physical activity among US adults. Age and income moderated the associations between neighborhood attributes and physical activity.

Objective:Examine school-level associations between school characteristics, health-related fitness, and academics. Methods:This observational study included schools in the NFL PLAY60 FitnessGram® project. We used 2022-2023 school year school-level data from three sources: 1) school characteristics data from the National Center for Education Statistics website; 2) cardiorespiratory fitness (CRF) and body mass index (BMI) data; and 3) academic data (students at or above grade-level for math and English Language Arts (ELA)) from state department of education websites. We used mixed effects linear regression models to examine aims. Results:One-hundred-sixty-six schools had CRF data and 67 had BMI data. Economic disadvantage was inversely associated with students meeting Healthy Fitness Zone (HFZ) BMI standards (β = -0.10, p < 0.001, R2 = 0.60), and academic performance (math, β = -0.38, p < 0.001, R2 = 0.52; ELA, β = -0.42, p < 0.001, R2 = 0.59). There were differences in the percentage of students meeting HFZ standards and academic performance across schools with different racial/ethnic compositions. School-level CRF was directly associated with academic performance (math, β = 0.10, p = 0.04, R2 = 0.52; ELA, β = 0.13, p = 0.006, R2 = 0.59), and there were no significant relations between BMI and academic performance (math, β = 0.26, p = 0.25, R2 = 0.54; ELA, β = 0.18, p = 0.47, R2 = 0.71). Conclusions:Findings highlight fitness and academic disparities related to economic disadvantage and race/ethnicity, and relations between fitness and academics.

Scale-up penalty, a common phenomenon in which the promising effects found in early preliminary studies are substantially reduced when evaluated in a subsequent larger trial, can stall the advancement of health behavior interventions. In obesity-related behavioral interventions, changes to key features between a preliminary study and subsequent larger trials inflate scale-up penalty. The purpose of this study is to examine whether changes in intervention features occur in other behavioral disciplines that utilize a similar developmental continuum wherein smaller-scale preliminary studies inform larger-scale trials, and whether changes in key features inflate scale-up penalty. We conducted a systematic review identifying preliminary studies followed by a larger trial conducted by the same author(s) (i.e., a study pair) in four areas—tobacco/smoking cessation, alcohol use, interpersonal violence, and sexually transmitted diseases. We coded intervention features in the preliminary study and larger trial to capture changes in key study features (e.g., who delivered the intervention). Multi-level meta-regressions estimated the association between the changes to key study features and change in standardized mean difference for health outcomes and calculated scale-up penalty. We identified 222 effects across 69 study pairs of preliminary studies with subsequent larger trials. Fifty-eight study pairs (84

PURPOSE:Healthy sleep habits are important when children transition from variable preschool environments to a more structured elementary school setting. However, few studies have harnessed the unique partnership between teachers and parents in preventing suboptimal child sleep. This study aimed to engage key community partners (i.e., 4K & 5K teachers and parents) in developing a combined school- and home-based sleep promotion program for young children (4-6 years old). METHODS:Teachers (n=34, 100% female, 12.4±9.0 years' experience) from 2 school districts participated in semistructured focus groups or phone interviews (n=26 teachers in 3 focus groups; n=8 interviews), while parents (n=61, 97% female, age=33.1 ± 5.1 years) completed an online semistructured survey to inform the development of a sleep promotion program. Transcripts were independently coded using an inductive approach and consensus coding. Themes were generated using constant-comparison methods. Survey results were summarized using descriptive statistics. RESULTS:Four key themes emerged from teachers' perspectives: 1) suboptimal sleep impacts children during the school day across multiple domains, (2) several barriers to adequate sleep exist, 3) parent-teacher interactions about sleep are complex and require unique approaches, and 4) a sleep program must fit within parent and teacher needs. Teachers noted leveraging the parent-teacher relationship may increase parent buy-in. Parents reported challenges with their child's sleep and conveyed interest in a tailored sleep promotion program during 4K. CONCLUSIONS:Teachers are concerned about suboptimal child sleep and are invested in working with parents to support healthy sleep habits. A sleep promotion program that encompasses collaboration between the school and home environment would be well-received by families of young children. Findings will inform future content, engagement strategies, and delivery mode.

The purpose of this study was to (1) examine differences in child screen time from school to summer, and (2) assess how attending structured programming relates to child screen time during the summer in a diverse cohort of children. Parents completed daily time use diaries for their children (n = 1,032 children; 9.7 ± 1.8 years old; 33

This study investigated associations between device-independent physical activity (PA) metrics and adiposity-related indicators among U.S. children and adolescents. Nationally representative cross-sectional data from three NHANES cycles (2011-2014) were analyzed, including 5,274 participants (weighted n = 43,156,858; 49.3% female; ages 6-17 years) who wore accelerometers on their non-dominant wrist for 7 days and had five adiposity-related indicators assessed: BMI z-score, total body and trunk fat percent (DXA), overweight/obesity (BMI), and abdominal obesity (waist-to-height ratio). Raw accelerometry data were used to calculate PA volume (Daily Monitor Independent Movement Summary [MIMS]) and intensity (Peak-60 MIMS). Survey-weighted regression models, adjusted for covariates, showed inverse associations between PA volume (B = -0.230, 95% CI: -0.334,-0.125) and intensity (B = -0.211, 95% CI: -0.250,-0.172) with total body fat percent, trunk fat percent (volume B = -0.192, 95% CI: -0.312,-0.071; intensity B = -0.227, 95% CI: -0.273,-0.181), overweight/obesity (volume OR = 0.967, 95% CI: 0.944,0.991; intensity OR = 0.953, 95% CI: 0.943,0.963) and abdominal obesity (volume OR = 0.963, 95% CI: 0.939,0.988; intensity OR = 0.951, 95% CI: 0.940,0.962). PA intensity was inversely associated with BMI z-score (B = -0.022, 95% CI: -0.028,-0.016). Stronger associations were observed during childhood and among girls. These findings highlight the importance of promoting PA, particularly higher-intensity activities, to mitigate excess adiposity and demonstrate the value of device-independent metrics for PA research.

BACKGROUND:Summer vacation is a time when youth gain excessive weight. A key driver of unhealthy weight gain is poor dietary quality. The absence of consistent structure (e.g., school), is hypothesized to be one of the reasons for lower diet quality during summer. This study examined differences in school and summer dietary quality among a diverse cohort of children across three years. We also examined the impact of attending structured programs on children's diets. METHODS:Parents of 1,032 children (age 5-14 years, 48% girls) completed a time use diary each day for 14-days during school (April/May) and again in summer (July) from 2021 to 2023, for a total of 6 timepoints. The daily diary collected information on the child's location and dietary intake for that day. Mixed-effects models examined the odds (OR) of consuming a food/beverage (e.g., fruit, vegetable, soda, salty snacks) on a given day during school vs. summer, overall and by income. Models also examined the impact of attending structured programming during summer (e.g., summer day camp) on the likelihood of consumption. RESULTS:A total of 39,983 time use diaries were completed. Overall, children were less likely to consume fruit, vegetables, milk, 100% juice, and salty snacks (OR range 0.63 to 0.87), and they were more likely to consume non-carbonated sweetened beverages, soda, frozen desserts, and fast food (OR range 1.17 to 1.63) during the summer compared to school. On summer days with structured programming, children were more likely to consume fruits, vegetables, milk, salty snacks, sweetened beverages (OR range 1.13 to 1.45), and they were less likely to consume frozen desserts, fast food, and soda (OR range 0.63 to 0.90). Few differences were observed between income groups. CONCLUSIONS:Children were less likely to report consumption of healthier foods/beverages and more likely to report consumption of unhealthier foods/beverages during summer compared to school. Attending structured programming during summer is associated with improved diet- suggesting such settings have potential to modify dietary intake.

Schools are recommended to use a whole-of-school (WOS) approach to promote physical activity opportunities before, during, and after school. Yet, the barriers and facilitators to implementing a WOS approach successfully are not well understood. The R = MC2 heuristic, which defines readiness for implementation as a combination of an organization’s motivation and capacity to implement, can enhance our understanding of implementation in the school setting. This study examines associations between constructs from the R = MC2 heuristic and schools’ implementation of a WOS approach. We conducted a secondary analysis of cross-sectional data from U.S. elementary schools participating in the NFL PLAY60 FitnessGram Project during the 2022–23 school year. From surveys administered to school staff, we created a WOS index (range = 0–12) comprising six physical activity practices: physical education, recess, before and after-school programs, classroom-based approaches, and active transport. We also assessed how six constructs from the R = MC2 heuristic (i.e., culture, implementation climate, leadership, priority, resources utilization, resource availability) impact physical activity implementation using a series of questions measured on a 5-point Likert scale. We used linear regression models to determine associations between R = MC2 constructs (independent variables) and WOS index scores (dependent variable), controlling for school-level characteristics (student enrollment, percentage of race/ethnicity and economically disadvantaged students served) and state-level clustering. The analytic sample consisted of 132 schools across 18 states. On average, school staff rated leadership (mean = 4.1, range = 1.5–5) and organizational culture (mean = 4.0, range = 2.25–5) the highest. The mean WOS index score was 6.1. Partially adjusted models indicated significant positive associations between each R = MC2 construct and WOS index scores. Fully adjusted regression models revealed priority (b = 0.88; p = 0.010; 95

Engaging in no moderate-to-vigorous physical activity (MVPA) has been recognized as an important indicator in physical activity (PA) surveillance, as any engagement in MVPA confers health benefits compared to none. Studying the prevalence of no MVPA can provide valuable insights into physical inactivity patterns and inform public health intervention efforts. While some cross-sectional studies have examined this issue, no research has analysed year-to-year trends. Therefore, the aim of this study was to assess trends of no MVPA among adolescents and key subgroups using a nationally representative US sample. Data from 2005 to 2021 cycles of the Youth Risk Behavior Surveillance System were used, with 115,926 US adolescents aged 14–17 years included (female: unweighted sample size = 58,582, 50.5

Although moderate-to-vigorous physical activity (MVPA) is a widely used construct in physical activity (PA) research, the lack of standardized assessment methods – particularly with the growing use of consumer-grade wearable activity trackers – poses challenges for comparability. Consumer-grade devices tend to rely on heart rate (HR)-based estimation methods to classify PA intensity, which contrasts with traditional research-grade accelerometers that use count- or raw-acceleration metrics. Comparability issues are particularly salient across individuals with varying weight status. In this commentary, we discuss systematic discrepancies between HR-based (relative intensity) and acceleration-based (absolute intensity) classifications of MVPA among individuals with greater adiposity. Using Fitbit data from the Adolescent Brain Cognitive Development Study, we illustrate how HR-based PA intensity classification may indicate higher MVPA in youth with greater adiposity despite lower step counts and light PA levels. We highlight implications for research design, public health surveillance, messaging, policy, and interventions. We also call for greater transparency, standardized methodologies, and integrative measurement approaches to ensure more accurate assessment of PA behavior.

Background: Sleep irregularity are associated with health outcomes, particularly during adolescence. Early adversity may exacerbate sleep irregularity, but longitudinal evidence remains limited. Objective: To investigate the relationship between early adversity, social jetlag, and weekly sleep loss in youth from the Adolescent Brain Cognitive Development (ABCD) Study. Participants and setting: The sample included 11,002 adolescents (mean age at 2-year follow-up = 12.03 years, SD = 0.67) from the ABCD Study (53 % boys and 47 % girls). Racial/ethnic composition was 53 % White, 14 % Black, 20 % Hispanic, and 13 % other/multi-racial. Methods: Social jetlag and weekly sleep loss were assessed using the Munich Chronotype Questionnaire at 2-year and 3-year follow-ups. Concurrently, lifetime adversity was measured using 16 of 17 items from the Pediatric Early Adversity and Related Life Events Screener (PEARLS). Mixed-effects linear and logistic regression models examined associations between lifetime adversities and sleep, adjusting for key covariates. Results: Adolescents experienced an average of 2.13 ( ± 1.9) hours of weekly sleep loss, and 33.32 % reported four or more PEARLS. Adolescents with four or more PEARLS experienced greater weekly sleep loss (coef. = 0.38, 95 % CI: 0.26, 0.51), translating to 23 min of additional sleep loss per week. Adolescents with four or more PEARLS were also more likely to experience more than 1 h of social jetlag (aOR = 2.79, 95 % CI: 2.19, 3.55). Conclusions: Early adversity is associated with social jetlag and sleep loss in adolescence, suggesting that targeted prevention approaches may improve sleep regularity and quantity.

The purpose of this study was to investigate the five-year trends in 24-hour movement behavior (24hrMB) guideline adherence among children and adolescents in the United States (U.S.) using the 2018–2022 waves of the National Survey of Children’s Health (NSCH), giving particular attention to disparities in guideline adherence with respect to sex, age, and overweight/obesity status. This secondary data analysis study utilized a successive independent samples design involving data from five waves (2018–2022) of the U.S. NSCH. Robust Poisson regression models were used to examine adherence to 24hrMB guidelines (physical activity [PA], screentime [ST], sleep [SL]), with survey year included as a categorical independent variable. Post-hoc marginal prevalences were calculated for each survey year and Cochrane-Armitage tests for trend were used to examine trends in 24hrMB guideline adherence across 2018–2022. Models were adjusted for age, sex, race/ethnicity, household income level relative to the Federal Poverty Level, metropolitan statistical area status, and overweight/obesity status, in addition to adherence to the guidelines not included as the outcome variable. Separate models were also employed to analyze interactions between sex, age, and overweight/obesity status and 24hrMB guideline adherence across survey years. A total of 135,309 (Weighted N = 48,419,077) children and adolescents (mean age = 11.9 ± 3.5 years, 48.9

OBJECTIVE:Cognitive-behavioral (CBT) interventions combined with either a physical activity (CBT+PA) or exercise intervention (CBT+Ex) are becoming more common in pediatric populations. Considering the independent effects of PA and exercise on health and psychological outcomes, it is unclear whether CBT alone differs from CBT+PA or CBT+Ex in efficacy. The main objective of this systematic review and meta-analysis of randomized clinical trials (RCTs) was to assess the efficacy of CBT+PA and CBT+Ex interventions in pediatric chronic disease. METHOD:This review included RCTs in children (≤18 years) with a chronic condition, a CBT+Ex or CBT+PA intervention, and an objective measure of PA&Ex. Seven databases were searched using MeSH terms and key terms and included studies published before July 1, 2023. Abstracts were reviewed for inclusion by two independent reviewers, data was extracted by three independent reviewers. Risk of bias (RoB 2) and study quality were coded. Random effect meta-analyses of differences in between-group change in PA&Ex were conducted. RESULTS:Eligible studies (k = 5) reported outcomes for a combined 446 children. A small, nonsignificant overall effect was found (d = 0.10, 95% CI -0.16, 0.35) indicating intervention groups (CBT+PA or CBT+Ex) increased engagement in PA&Ex more than comparator groups (CBT). Additional analyses were inconclusive due to the small number of eligible studies. DISCUSSION:Additional RCTs are needed with integrated PA&Ex interventions targeting pediatric chronic disease. Future trials should report more detailed PA&Ex data. The full protocol for this analysis was prospectively registered in Open Science Framework (project ID: osf.io/m4wtc).

INTRODUCTION:Summer day camps can mitigate summer weight gain by providing a structured daily environment that promotes healthy behaviors, but summer day camps are often cost prohibitive to families with low income. This study evaluated the cost effectiveness of providing free summer day camps to disadvantaged children to prevent summer weight gain. METHODS:A total of 422 children from a low-income school district in South Carolina were recruited and randomly assigned to receive 8-10 weeks of free summer day camps or to experience summer as usual in 2021-2023. The incremental cost-effectiveness ratio was calculated by dividing summer day camp cost by the difference between the intervention and control groups in changes in BMI z-scores from the start to end of summer. Incremental cost-effectiveness ratios at varied doses of summer day camp participation were also calculated. Sensitivity analyses were conducted using nonparametric bootstrapping of trial-based BMI z-score outcomes, matched with summer day camp costs from across the country. The probability of cost effectiveness was assessed over a range of potential costs at which policymakers may be willing to support. RESULTS:The summer day camp voucher program averted 0.0917 BMI z-score gain relative to the controls at a cost of $1,307, yielding an incremental cost-effectiveness ratio of $1,463 per 0.1 BMI z-score averted per child. Attending summer day camp 5 days per week, representing the highest dose, yielded the highest cost effectiveness. Sensitivity analyses showed that the bootstrapped incremental cost-effectiveness ratios averaged $2,187 per 0.1 BMI z-score averted, with 80% being <$3,500 per 0.1 BMI z-score averted. CONCLUSIONS:The voucher program is likely cost effective, with 80% probability of cost effectiveness if policymakers are willing to pay $3,500 per 0.1 BMI z-score averted.