Five-year trends in U.S. child and adolescent 24-hour movement behavior guideline adherence, 2018-2022

Five-year trends in U.S. child and adolescent 24-hour movement behavior guideline adherence, 2018-2022 | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Five-year trends in U.S. child and adolescent 24-hour movement behavior guideline adherence, 2018-2022 Christopher D. Pfledderer, Emma J. Mullane, Denver M.Y. Brown, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7215360/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract Background 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. Methods 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 sociodemographic, geographic, and health status variables, 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. Results A total of 135,309 (Weighted N = 48,419,077) children and adolescents (mean age = 11.9 ± 3.5 years, 48.9% female, 71.3% White) were included in the analytical sample. From pooled data across 2018–2022, 20.8% met PA guidelines, 49.6% met ST guidelines, 64.7% met SL guidelines, and 9.7% met all three guidelines concurrently. Except for sleep, which remained stable, the predictive prevalence of adherence to every combination of 24hrMB guideline was significantly lower in 2022 compared to 2018, with variations in trends between individual guidelines and years. The largest predicted prevalence difference from 2018 to 2022 was adherence to ST guidelines, which was 0.52 (95%CI: 0.50–0.54) in 2018 and 0.47 (95%CI: 0.46–0.48) in 2022 ( p < 0.001). The largest year-to-year predictive prevalence difference was also adherence to ST guidelines from 2019–2020, which was 0.52 (95%CI: 0.50–0.53) in 2019 and 0.40 (95%CI: 0.39–0.42) in 2020 ( p < 0.001). Cochran-Armitage tests for trend revealed a significant downward trend in guideline adherence for all 24hrMB across 2018–2022 ( X 2 range = 45.9-826.2, p < 0.01). Conclusions The predictive prevalence of adherence to every combination of 24hrMB guideline was significantly lower in 2022 compared to 2018, except for individual SL guideline adherence, which remained stable. These findings are concerning from a public health perspective, as meeting 24hrMB guidelines is linked to numerous indicators of healthy development for children and youth, underscoring the need for effective multi-level behavioral interventions to address the continued decline in meeting 24hrMB guidelines among youth. 24-Hour Movement Behaviors Physical Activity Sleep Screentime Youth Figures Figure 1 Figure 2 1. INTRODUCTION In the past decade there has been a proliferation of research taking an integrative approach to studying physical activity (PA), sedentary behaviors and screentime (ST), and sleep (SL), as opposed to in isolation. 1 This novel approach combines these behaviors together in a 24-hour activity cycle, commonly referred to as 24-hour movement behaviors (24hrMB) ), explicitly recognizing the co-dependence of these behaviors as time spent in one cannot be spent in another. To adhere to 24hrMB guidelines, children and adolescents in the US should accrue ≥ 60 minutes of moderate-to-vigorous physical activity (MVPA) each day, 2 ≤ 2 hours of recreational ST, 3 and 9–11 hours or 8–10 hours of sleep per night for children (6–12 years) and adolescents (13–17 years), 4 respectively. Adherence to individual 24hrMB guidelines is beneficially associated with several health indicators in children and adolescents including cardiometabolic risk factors and aspects of mental health. 5 – 11 There is a large body of evidence that has demonstrated associations between PA and a range of outcomes including cognition, 12 academic achievement, 13 motor skills, 12 , overweight/obesity, 14 , and a host of other non-communicable diseases. 15 Falling short of ST recommendations has been deleteriously linked to outcomes such as depression, anxiety, and other mental health outcomes, 16 – 18 and an increased odds of having overweight/obesity. 19 Insufficient sleep duration among youth has been shown to be associated with cognitive and emotional difficulties including learning and self-regulation, 20 increased risk taking behaviors, school performance, and psychosocial health, 21 and increased risk of developing a number of non-communicable diseases including overweight/obesity and diabetes. 22 Finally, evidence has demonstrated that concurrent adherence to multiple guidelines, especially concurrent adherence to all three guidelines, is associated with the most favorable benefits regarding developmental and health outcomes. 23 – 28 Despite these developmental and health benefits, relatively few children and adolescents in the US meet 24hrMB guidelines and even fewer concurrently adhere to multiple guidelines. 23 , 26 , 27 , 29 – 31 Recent studies indicate that the proportion of children and adolescents who meet individual PA guidelines is as low as 22.3%, the proportion meeting ST guidelines is between 10–28%, and the proportion meeting SL guidelines is as low as 57%. 32,33 Further, less than 5% of children and adolescents meet all three guidelines concurrently. 32 Evidence has also revealed disparities between sex, age, and overweight/obesity status in adherence to 24hrMB guidelines among children and adolescents with recent findings showing a higher proportion of males compared to females, children compared to adolescents, and those without overweight/obesity compared to those with overweight/obesity adhering to guidelines. 29 , 30 , 34 – 38 Child and adolescent adherence to 24hrMB has been declining in the past few years as well. 29 , 35 , 37 , 39 , 40 An eight-year study in the US (2011–2019) found that the prevalence of meeting 24hrMB guidelines in children and adolescents decreased each year. 35 A similar study found that children and adolescents with overweight and obesity had a continuous increase in ST from 2018 to 2022. 37 Diminished adherence to 24-hour movement behaviors in youth may have significant implications for future generations, including a higher prevalence of non-communicable, obesity-related diseases, a higher prevalence of mental health-related complications, and an increased burden to an already strained healthcare system given the non-communicable disease crisis in the U.S. 8 – 11 , 23 – 28 , 33 , 41 – 43 There is a critical need to understand recent trends in 24hrMB guideline adherence among children and adolescents in the US. Given a) already known sex-based movement behavior disparities, b) the youth obesity epidemic that the US has been experiencing for the past two decades, c) seemingly ubiquitous access to technology-based leisure/entertainment among children, and d) social norms favoring sedentary travel and restricting independent mobility among younger children, there is also a critical need to identify current disparities with respect to sex, age, and overweight/obesity status. It is important to not just diagnose the extent to which children and adolescents adhere to 24hr MB guidelines, but if and how adherence has changed over time, and in particular, see if these changes are affecting certain age-groups, males and females, and children with overweight/obesity vs. those without overweight/obesity differently. By using these factors as effect modifiers, there is also the potential to guide more tailored public health interventions and inform whether existing guidelines need to be adapted for high-risk subgroups, including children, females, and those with overweight/obesity. To date, few studies have explored children’s and adolescent’s individual guideline adherence and concurrent adherence to multiple guidelines across recent years and even fewer have done so on a national level. Given concerning downward trends of guideline adherence pre- COVID-19 pandemic and evidence that suggests a sharper decrease in guideline adherence during the height of the pandemic, 44 understanding how guideline adherence has shifted in the years that followed is important as we work to design targeted interventions and provide public health evidence for policy makers. Monitoring trends in 24hrMB guideline adherence may provide insights into whether public health messaging, policy changes, and environmental shifts are leading to an improvement or a worsening of these behaviors among youth. Additionally, it is important to identify emerging disparities across certain subgroups (males vs. females, children vs. adolescents, those with overweight/obesity vs. those without) in an effort for health systems and public health initiatives to be proactive as opposed to reactive in addressing declines in PA, ST, and SL guideline adherence. Ultimately, this research is essential for guiding evidence-based interventions, policies, and national health promotion strategies. Therefore, the purpose of this study was to investigate the five-year trends in 24hrMB guideline adherence among children and adolescents using the 2018–2022 National Survey of Children’s Health (NSCH) and explore differences in adherence with respect to age, sex, and overweight/obesity status. 2. METHODS 2.1. Data Source and Participants This secondary data analysis study utilized a successive independent samples design involving data from five waves (2018-2022) of the NSCH. The NSCH is a parent-reported, nationally representative survey of non-institutionalized children and adolescents living in the U.S., administered by the United States Census Bureau and the Maternal and Child Health Bureau of Health Resources and Services administration. 45 Because this study used de-identified, publicly available data, it did not qualify as human subjects research and did not require Institutional Review Board review, as per the federal policy for the protection of human subjects. 46 The NSCH includes children and adolescents between the ages of 0-17 years. For this study, we excluded children who were less than six years old and those who were missing 24hrMB data. Although 24hrMB guidelines apply to children as young as 5 years old, the NSCH does not collect PA data for children under 6 years, necessitating their exclusion from this study. Sample sizes for pooled data, for each survey year, and for those excluded from the final analytical sample are communicated in Figure 1 . Briefly, the 2018-2022 waves of NSCH included responses from 207,735 (Weighted N = 73,057,474) participants, of which our analytical sample included responses from 135,309 (Weighted N = 48,419,077) children and adolescents ages 6-17 years. Across 2018-2022 survey years, response rates ranged from 39.1% to 43.1%, and no strong/consistent evidence of nonresponse bias was detected during any survey year. 47 2.2. Measures The following section details measures for primary outcomes (adherence to 24hrMB guidelines) and relevant covariates. The Maternal and Child Health Bureau, the US Census Bureau, and a national technical expert panel, comprised of representatives from other federal agencies, family organizations, child health leaders, and others, led the development of indicators, and validated survey questions are used on the NSCH when available. Cognitive testing was performed on all survey items, although the NSCH does not make this data publicly available. 48 2.2.1. Physical activity (PA). Physical activity guideline adherence was determined from a single question which asked parent/caregivers, “During the past week, on how many days did this child exercise, play a sport, or participate in physical activity for at least 60 minutes?” Responses were dichotomized into whether participants met the guideline of engaging in 60 minutes of physical activity every day or not (6 days or less). 2.2.2. Screen time (ST). Screen time guideline adherence was determined from a single question which asked parents/caregivers, “On most weekdays, about how much time did this child spend in front of a TV, computer, cellphone, or other electronic device watching programs, playing games, accessing the internet or using social media? Do not include time spent doing schoolwork.” Responses were dichotomized into whether participants engaged in ≤ 2h of screen time per day (met the guideline) or engaged in >2h of screen time per day (did not meet the guideline). 2.2.3. Sleep duration (SL). Sleep guideline adherence was determined from a single question which asked parents/caregivers, “During the past week, how many hours of sleep did this child get on most weeknights?” Guideline adherence for children (6-12 years) was operationalized as sleeping 9-11 hours per night and, for adolescents (13-17 years), guideline adherence was operationalized as sleeping 8-10 hours per night. 2.2.4. Adherence to combinations of guidelines. Adherence to combinations of 24hrMB guidelines (PA+ST, PA+SL, SL+ST, and all three) was created by combining dichotomized individual guideline adherence variables and recoding them as an additional dichotomized variable (0= did not concurrently meet combined guidelines, 1 = concurrently met combined guidelines). 2.2.5. Covariates. Demographic covariatesincluded age (dichotomized into children [6-12 years] and adolescents [13-17 years]), race/ethnicity (Hispanic, Black, White, Other/Multi-racial), sex (male/female), household income level relative to the federal poverty line (FPL; <100%, 100-199% FPL, 200-399% FPL, ≥400% FPL), metropolitan statistical area status (Metro/non-Metro), and overweight/obesity status (yes [≥85th BMI percentile], no [<85th BMI percentile]). 2.3. Statistical Analysis Weighted prevalence and unweighted counts were calculated for all variables for the pooled sample and compared across survey years (2018-2022) using chi-square tests. Weighted logistic regression models were used to examine adherence to 24hrMB guidelines, with survey year included as a categorical independent variable. These models were adjusted for age, sex, race/ethnicity, household income level relative to the FPL, metropolitan statistical area status, and overweight/obesity status, in addition to adherence to the guidelines not included as the outcome variable. Follow-up analyses were computed to examine adherence to each component of the 24hrMB guidelines and meeting different combinations of the individual components of the guidelines (i.e., PA + ST, PA + SL, ST + SL). Separate models were also employed to analyze interactions between sex, age, and overweight/obesity status and 24hrMB guideline adherence across survey years. Post-hoc marginal probabilities were calculated for each survey year and Cochran-Armitage tests for trend were used to examine trends in 24hrMB guideline adherence across 2018-2022. Statistical analyses were carried out using Stata v18.0 (StataCorp LP, College Station, Texas, USA) and a type I error level of 0.05 was used to establish statistical significance. The sampling design of the NSCH datasets was accounted for and weighting was applied using the Taylor Series Linearization variance estimation before all statistical testing was conducted. All code used for the analysis is available in the Appendix . 3. RESULTS 3.1. Total sample A total of 135,309 (Weighted N = 48,419,077) children and adolescents (mean age = 11.9 ± 3.5 years, 48.9% female, 71.3% White) were included in the analytical sample (Fig. 1 ). Complete demographic and 24hrMB guideline adherence statistics for the total sample are communicated in Table 1 . From pooled data across 2018–2022, 20.8% met PA guidelines, 49.6% met ST guidelines, 64.7% met SL guidelines, and 9.7% met all three guidelines concurrently. Table 1 Demographic and behavioral characteristics of children and adolescents from pooled data of the 2018–2022 National Survey of Children’s Health (N = 135,309, Representative N = 48,419,077). Demographic Characteristics Unweighted Count (Weighted Percent) Age, years (Mean ± SD) 11.9 ± 3.5 Age Category Children (6–12 years) 70,165 (57.9%) Adolescents (13–17 years) 65,144 (42.1%) Sex (Female) 66,435 (48.9%) Race American Indian or Alaska Native 1,357 (1.5%) Asian 7,729 (5.3%) Black or African American 9,970 (14.6%) Native Hawaiian or Other Pacific Islander 747 (0.7%) Two or More Races 10,534 (6.6%) White 104,972 (71.3%) Hispanic or Latino Origin 18,169 (26.5%) Overweight/Obesity (≥ 85th BMI percentile) 38,814 (33.2%) Non-Metropolitan Statistical Area Status 19,357 (12.4%) Federal Poverty Level Ratio (Mean ± SD) 286 ± 183 24-Hour Movement Guideline Adherence Physical Activity 28,163 (20.8%) Screentime 65,781 (49.6%) Sleep 92,129 (64.7%) Physical Activity + Screentime 18,334 (13.3%) Physical Activity + Sleep 20,270 (14.4%) Screentime + Sleep 47,623 (34.2%) All Three 13,809 (9.7%) 3.2. Five-year trends in 24-hour movement behavior guideline adherence Except for SL, which remained stable, the prevalence of adherence to every 24hrMB guideline decreased from 2018 to 2022, with variation between individual guidelines and years (Fig. 2 , Table 2 ). The largest decrease from 2018 to 2022 was in adherence to ST guidelines, with 52% meeting the guideline in 2018 and 47% meeting the guideline in 2022 (5% decrease). Comparatively, PA guideline adherence decreased by 4% between 2018 and 2022. Prevalence of concurrently meeting all three guidelines decreased from 9% in 2018 to 7% in 2022 (2% decrease). The largest year to year decrease occurred with ST guideline adherence between 2019 and 2020 (12% decrease), with incremental increases each year after. Cochran-Armitage tests for trend revealed a significant downward trend in guideline adherence for all 24hrMB across 2018–2022 ( X 2 range = 45.9-826.2, p < 0.01), with SL adherence increasing between 2018–2020 and then declining between 2021–2022 ( Appendix ). Table 2 Marginal predicted prevalences of children and adolescents in the National Survey of Children’s Health adhering to 24-hour movement behavior between 2018–2022 (N = 135,309, Representative N = 48,419,077). 24-hour guideline Year 2018 2019 2020 2021 2022 Margin 95% CI Margin 95% CI Margin 95%CI Margin 95% CI Margin 95% CI Physical Activity 0.21 0.19–0.22 0.19 0.18–0.20 0.19 0.18–0.20 0.19 0.18–0.20 0.17 0.16–0.18 Screentime 0.52 0.50–0.54 0.52 0.50–0.53 0.40 0.39–0.42 0.44 0.43–0.45 0.47 0.46–0.48 Sleep 0.62 0.61–0.64 0.64 0.62–0.65 0.65 0.64–0.67 0.65 0.64–0.67 0.63 0.62–0.64 Physical Activity + Screentime 0.13 0.12–0.14 0.12 0.11–0.13 0.10 0.09–0.11 0.11 0.10–0.12 0.10 0.10–0.11 Physical Activity + Sleep 0.14 0.12–0.15 0.13 0.12–0.14 0.13 0.12–0.14 0.13 0.13–0.14 0.11 0.11–0.12 Screentime + Sleep 0.35 0.33–0.36 0.35 0.34–0.37 0.28 0.27–0.29 0.30 0.29–0.31 0.32 0.31–0.33 All Three 0.10 0.09–0.10 0.09 0.08–0.97 0.07 0.07–0.08 0.08 0.08–0.09 0.07 0.07–0.08 3.3. Variations in 24-hour movement behavior guideline adherence trends by sex, age, and overweight/obesity status Post-hoc marginal predicted prevalences for interactions with sex, age, and overweight/obesity status are communicated in the Appendix . Compared to males, females had significantly lower predicted prevalence of meeting PA, PA + ST, PA + SL, and concurrent adherence to all three guidelines, and significantly higher predicted prevalence of meeting ST and ST + SL, with the predicted prevalence of meeting individual SL guidelines roughly the same between males and females. Trends in marginal predicted prevalences across 2018–2022 for both males and females were similar to that of the total sample. Compared to adolescents, children had significantly higher predicted prevalence of meeting all combinations of 24hrMB guidelines, except for SL. Trends across 2018–2022 for children and adolescents were similar to that of the total sample, although the predicted prevalence of meeting ST, ST + PA, and all three guidelines decreased more for children than adolescents in 2020. Children with overweight/obesity had significantly lower predicted prevalence of meeting all guidelines when compared to children without overweight/obesity and trends across 2018–2022 were similar for both groups and mirrored that of the total sample. 4. DISCUSSION We investigated the five-year trends in 24hrMB guideline adherence among U.S. children and adolescents using the 2018–2022 waves of the NSCH. We found that the prevalence of adherence to every 24hrMB guideline, except for sleep, decreased from 2018 to 2022, with largest decreases observed for adherence to individual ST and PA guidelines. Children, males, and those without overweight/obesity had higher adherence to most guidelines, although year-to-year trends for these subgroups mirrored trends of the total sample. These findings offer an updated perspective on trends in 24hrMB guideline adherence, highlighting subgroups that may benefit most from targeted interventions. Approximately 20% of the total sample in our study met PA guidelines, less than 50% met the ST guidelines, and almost two-thirds (64.7%) met the SL guidelines. These findings tend to align with adherence rates observed in previous studies. 29 , 31 , 35 , 37 – 39 For example, a similar cross-sectional study analyzing NSCH data from 2016–2017 found that the proportion of U.S. children and adolescents meeting PA guidelines was approximately 23%, ST guidelines were 33%, and SL guidelines were about 86%. 29 Separately, a global meta-analysis utilizing school-based surveys determined that over 80% of adolescents (aged 11 to 17 years) did not adhere to PA recommendations/guidelines. 49 Slight differences in the frequency of adherence to individual 24hrMB guidelines between this study and past findings may be due to increased technology use among youth 29 , 37 , 50 , 51 and the COVID-19 pandemic, which had considerable influence over child and adolescent 24hrMB guideline adherence due to quarantine policies, remote learning, and other disruptions to routine and structure. 37 , 40 , 44 , 52 Finally, our overall findings are comparable to a recent meta-analysis including 22 other countries outside of the US, which suggests 24hrMB guideline adherence is a growing concern on a global scale. 30 The main finding of our study is the decrease in guideline adherence between 2018–2022. During these five years, we observed a 5% decrease in ST guideline adherence and a 4% decrease in PA guideline adherence. It was found that adherence to the SL guidelines was stable during this five-year period and even slightly increased between 2018–2021, before decreasing again in 2022. In addition, concurrent guideline adherence decreased by 3%. The trends in marginal predicted prevalences according to sex, age, and overweight/obesity status were similar to the total sample from 2018 to 2022. However, the prevalence of adhering to ST, PA + ST, and all three guidelines decreased for children more than adolescents in 2020, the year of the onset of the COVID-19 pandemic and when stricter movement restriction and space closure policies took place across the U.S. This alarming rise in individual and concurrent guideline non-adherence has been seen in multiple research findings 35 , 37 , 39 , 51 , 53 – 55 and globally, these trends are similar to findings from other countries where trend analyses have been conducted, including Australia, 39 South Korea, 56 and New Zealand. 57 Collectively, the observed declines in ST and PA guideline adherence underscore the urgent need for targeted interventions to address growing disparities in wake-time movement behaviors, particularly during childhood. Such efforts could help establish healthy habits that support sustained guideline adherence through adolescence. While the prevalence of ST guideline adherence did decrease from 2018 to 2022, and sharply decreased from 2019 to 2020, we did observe incremental increases in ST adherence after 2020, although it did not recover to the prevalence observed in 2018. This pattern of ST adherence has several public health implications. First, the sharp reduction in adherence from 2019 to 2020 suggest that the COVID-19 pandemic had a major influence on ST behaviors among youth. This point will be highlighted at length later in the Discussion. Second, the recovery of ST guideline adherence post-2020 may suggest that ST behaviors are largely modifiable and responsive to environmental changes, like schools reopening and the resumption of structured routines. 58 , 59 This finding offers of a window of opportunity for public health interventions, as it suggests that promoting healthy ST habits can be effective post-pandemic and beyond. However, public health researchers should focus on identifying and supporting those who have not yet recovered health ST habits, including males, adolescents, and those with overweight/obesity, as our study also demonstrated lower adherence across time among these subgroups. Interestingly, SL guideline adherence remained relatively stable from 2018 to 2022. This finding may have a number of public health implications. First, sleep duration (which is what the SL guidelines specify) may be less sensitive to large-scale external disruptions, like the COVID-19 pandemic or longer-term shifts in daily routines. This resilience could reflect the biological regulation of sleep, 60 stronger parental control, particularly in children, and/or the influence of consistent bedtime routines. 61 – 63 Second, stable adherence to SL guidelines may provide a reference point for large-scale population health studies for understanding how more variable behaviors, like ST and PA, may interact with more stable movement behaviors, like SL. However, it is important to remember that SL guidelines only establish parameters for sleep duration, not for other factors such as sleep quality, consistency, or timing, all of which can impact health outcomes. 64 – 66 Future trend or longitudinal studies should explore dimensions of sleep beyond duration to better understand overall sleep health among youth across time. Recent publications 40 , 44 , 67 – 69 reveal that the COVID-19 pandemic had a considerable effect on 24hrMB among youth and the decreases that were found in our study and others may be partly due to remote learning, social restrictions, and stressors brought on during this time. 70 , 71 Indeed, the transfer to remote learning gave rise to major changes in the routine and structure of the 24-hour day for school-aged children. As seen in a study 59 examining the impact of virtual and in-person school during COVID-19, days in which children were attending in-person school were associated with a greater likelihood of children meeting the 24hrMB guidelines compared to days students were attending virtual school. Another adjustment for youth throughout the pandemic was an absence of recreational sports and local community programs that typically prompt greater adherence to the movement behavior guidelines. 32 , 70 To further support the notion that closures brought on by the COVID-19 pandemic were detrimental to 24hrMB guideline adherence, our study found that adherence to ST and ST + SL increased slightly between 2020–2022, but never recovered back to similar proportions as 2018. This could be because youth returned to in-person school and were able to participate in recreational sports and other structured activities after 2020. Still, the fact that adherence has yet to recover to pre-pandemic levels is concerning, suggesting a broader shift toward increasingly sedentary lifestyles. Increased use of technology in children and adolescents could also explain the trend of diminished guideline adherence reported in our study, but the trend of increased ST appears to precede the COVID-19 pandemic. For example, an Australian study 39 examining trends in adolescent guideline adherence discovered that adherence to ST guidelines fell from 19% in 2009 to 10% in 2018. Future research should incorporate data that spans a longer timeframe to determine if trends in guideline adherence have been consistently declining or if the decline has accelerated in recent years. We found significant differences in concurrent guideline adherence between sex, age, and overweight/obesity status, which held constant between 2018–2022 and mirrored downward trajectories found in the total sample. Females had a significantly lower predicted prevalence of meeting PA, PA + ST, PA + SL, and concurrent adherence to all three guidelines, and had a significantly higher predicted prevalence of meeting ST and ST + SL than males. Previous studies support the result of higher PA adherence in boys 30 , 35 , 37 , 49 , 72 , 73 and higher ST adherence in girls. 37 , 38 , 72 These differences could be a result of greater participation in light physical activity (LPA) and non-screen-based activities found among females in previous studies. In a study 72 evaluating differences between first-grade males and females, it was determined that males favored sports, team games, and endurance activities compared to females who favored activities involving flexibility, roller skating, and dance. Several other investigations have discovered that males are more likely to participate in more moderate to vigorous physical activities than females. 74 – 77 Additionally, it has been noted that females may engage in more non-screen-based activities than males. 78 – 80 In a longitudinal study 81 from 2011 to 2017 surveying leisure activities in children and adolescents, it was established that females were more likely to be involved in theater, choir, orchestra, and dance. Future research should explore how context, activity type, and preferences may drive disparities between males and females with respect to 24hrMB guideline adherence. Children had a higher prevalence of adherence to all 24hrMB guideline combinations (except SL) compared to adolescents across 2018–2022, although both subgroups mirrored the total sample with downward trajectories across the five-year period. This finding of greater concurrent guideline adherence in children compared to adolescents is commonly reported. 30 , 35 , 36 , 38 , 73 The transition from primary to secondary schools for youth may justify why children are meeting the guidelines more than adolescents. This transition period for children typically occurs at the age of 11 to 12 years old (preadolescence) and is marked by increased academic demands and shorter breaks throughout the day. 82 , 83 For example, Chong et al., 84 found that during the primary to secondary school transition, there was an increase in sedentary behavior (SB) and a decrease in SL and PA. The study indicated that these shifts in 24hrMB were partially due to added homework and extended ST before bed. Expanding on this idea, diminished adherence to 24hrMB guidelines by adolescents could be caused by independence gained in adolescence. As children grow into adolescence, they frequently acquire more responsibility and autonomy. This is accompanied by less parental control, greater use of the internet and mobile devices, and increased extracurriculars (social activities, employment, etc.). 30 , 39 , 53 , 84 Time spent managing other tasks in adolescence may result in decreases in PA and increases in ST. Furthermore, less parental control could presume that adolescents can sleep longer during the weekend. In a cross-sectional study 85 analyzing adolescent sleep patterns on weekday versus weekend nights, it was found that on weekend nights students averaged 1.5 hours more sleep than on weekday nights. However, less parental control among adolescents could also indicate an unstructured bedtime compared to children who commonly have a mandatory bedtime. 30 Another explanation for the difference in child versus adolescent guideline adherence, including the SL discrepancy, could be in measurement methodology. Notably, our results derive from parent-reported surveys. Parents might be unaware of when their children are going to bed, particularly if adolescents have access to their smartphone at nighttime. Moreover, the varied SL recommendation 4 for children (9–12 hours of sleep per night) and adolescents (8–10 hours of sleep per night), may also explain differences in guideline adherence prevalence. 53 Another explanation for this age-related discrepancy could be tied to chronotype shifts in adolescence. Studies have shown that adolescents have a greater preference for going to bed later compared to children, which can lead to an inability to meet SL guidelines, particularly on weeknights when youth sleep schedules are governed by school start times. 86 – 88 Our findings also indicated that children with overweight/obesity status had a lower prevalence of meeting all the 24hrMB guidelines than children without overweight/obesity status, which also aligns with prior literature. 37 , 73 , 89 For example, Chen et al., 36 found that Chinese children and adolescents who met the 24hrMB guidelines had a lower risk of being overweight or obese. Furthermore, a separate study 90 noted that children and adolescents with increased PA and SL and decreased sedentary behavior had favorable levels of adiposity and health. It has also been proposed that reduced PA may occur because of greater adiposity. 73 , 91 While our findings are not causal, the relationship between overweight/obesity and 24hrMB guideline adherence cannot be overlooked. Future longitudinal studies should examine the bi-directional associations between overweight/obesity and 24hrMB among children and adolescents. Ultimately, our study garners further support for interventions that are designed to promote concurrent adherence to 24hrMB guidelines and indicates a strong need to slow and reverse the downward trend in guideline adherence among children and adolescents. Additionally, although the US has individual guidelines for PA, ST, and SL, it has not established 24hrMB guidelines, like many other countries have already done. 92 – 94 In not doing so, this fails to recognize the co-dependence of PA, ST, and SL as a collective 24-hour behavioral cycle. Public health officials and policy makers in the US should be aware of the co-dependency of these behaviors and work to establish 24hrMB guidelines, which could set the stage for widespread adoption, education, and promotion of 24hrMB as a collective health outcome. Differences in guideline adherence between sex, age, and overweight/obesity status further strengthen the notion that behavioral interventions should be tailored to meet the needs of demographic subgroups. Researchers should strive to understand what factors are driving these differences and work to develop programs/interventions that prioritize minimizing the 24hrMB guideline adherence gaps between youth of different sex, age, and overweight/obesity status. 4.1. Strengths and Limitations Our study utilized data from five waves (2018–2022) of the NSCH, a large, nationally representative sample of children and adolescents in the US. Data from 135,309 participants were included in our analytical sample, with very low percentages of missing data for each variable. Not only did we use multiple waves of data to understand yearly variations in PA, ST, and SL guideline adherence, but we also present findings for concurrent adherence to every combination of 24hrMB guidelines, accounting for the co-dependent nature of the behaviors. Finally, we compare yearly trends between several key demographic variables including sex, age, and overweight/obesity status. This is the first study to thoroughly report recent trends in 24hrMB adherence for a nationally representative sample of children and adolescents from the US. Despite these strengths, our study has several weaknesses to note, including the cross-sectional, successive, independent samples design, which prevents causal interpretations of the findings. Additionally, repeated cross-sectional studies have several other limitations including 1) these studies survey different individuals at each timepoint making it impossible to assess within-person changes or individual trajectories, 2) differences observed over time may reflect cohort effects rather than true trends, and 3) without longitudinal tracking, it is more difficult to adjust for time-varying confounders and/or establish temporal ordering between exposure (year) and 24hrMB guideline adherence. Larger-scale longitudinal designs utilizing the same sample of children and adolescents are warranted to thoroughly investigate trends in 24hrMB guideline adherence. Additionally, all data were parent-reported with single-item questions, although survey questions used to measure PA, SL, and ST in NSCH have been validated. Also, the NSCH includes responses for youth aged 0–17 years. We chose to exclude those aged 0–5 years because NSCH does not collect the same type of PA data on this age range and the recommendations are operationalized differently for infants, toddlers, and preschoolers. 95 On the topic of PA guidelines, this study did not account for muscle/bone strengthening activities (which are part of the guidelines for youth in the US), although the NSCH does not ask about these types of activities on their survey. Other possible disparities beyond those based on sex, age group, and overweight obesity status, known to help explain many health inequities in the U.S. (race/ethnicity, socioeconomic status, urban/rural status) were not explored in this analysis. These factors should be considered in future trend studies focusing on 24hrMB guideline adherence. As previously noted, the US does not currently have 24hrMB guidelines, but instead has individual guidelines for PA, ST, and SL. Because of this we relied on several sources for quantifying guideline adherence and these sources/organizations may differ from others in the US with respect to recommendations. Finally, we must acknowledge that this study focused on years 2018–2022, which is a relatively short timeframe, capturing movement behaviors before, during, and immediately after the height of the COVID-19 pandemic. Future studies should continue to investigate the longer-term trends in 24hrMB, incorporating data from future waves of NSCH or from other nationally representative data sources. 5. Conclusions The prevalence of adherence to every 24hrMB guideline decreased from 2018 to 2022, with largest decreases observed for adherence to individual ST and PA guidelines, and lower adherence observed for females, adolescents, and individuals with overweight/obesity. These trends are concerning from a public health perspective, as meeting these guidelines is linked to numerous indicators of healthy development for children and youth. This highlights the urgent need for multi-level intervention strategies that target multiple movement behaviors to address the issue. The pandemic had a seemingly lasting effect on children during the movement restriction/space closure years. This is a lesson for future major times of crises (other infectious disease emergencies, natural disasters, etc.) to prioritize opportunities for staying active and limiting ST while balancing other threats. While sex-based, age-based, and weight-status-based gaps in 24hrMB guideline adherence are not widening over time, closing the gap in guideline adherence between sex, age, and overweight/obesity status should be a priority among those implementing behavioral interventions for youth and may be accomplished by designing context-specific interventions for demographic subgroups. Overall, researchers, public health practitioners, and policy-makers should strive to take an integrative approach when promoting PA, ST, and SL in an effort to slow and reverse the downward trend in 24hrMB guideline adherence among children and adolescents in the US. Abbreviations 24-Hour Movement Behaviors (24hrMB); National Survey of Children’s Health (NSCH); Physical Activity (PA), Screentime (ST); Sleep (SL) Declarations ACKNOWLEDGMENTS The authors would like to thank the participants who took part in the 2018-2022 waves of the National Survey of Children’s Health. Ethics approval and consent to participate The United States Census Bureau conducts the NSCH on behalf of HHS under Title 13, United States Code, Section (b), which allows the Census Bureau to conduct surveys on behalf of other agencies. Title 42 U.S.C. Section 701(a)(2) allows HHS to collect information for the purpose of understanding the health and well-being of children in the U.S. Availability of data and materials Full datasets may be requested at: https://www.childhealthdata.org/dataset. The data collected under this agreement are confidential under 13 U.S.C. Section 9. All access to Title 13 data from this survey is restricted to Census Bureau employees and those holding Census Bureau Special Sworn Status pursuant to 13 U.S.C. Section 23(c). Any effort to determine the identity of any reported case is prohibited. The Census Bureau and HRSA MCHB take extraordinary measures to assure that the identity of survey subjects cannot be disclosed. All direct identifiers, as well as characteristics that might lead to identification, have been omitted from the data files. Any intentional identification or disclosure of a person or establishment violates the assurances of confidentiality given to the providers of the information. Therefore, users must: • Use the data in these data files for statistical reporting and analysis only; • Make no use of the identity of any person discovered, inadvertently or otherwise; • Not link these data files with individually identifiable data from any other Census Bureau or non-Census Bureau data sets. Use of the data files signifies users’ agreement to comply with the above-stated statutory-based requirements. Before releasing any statistics to the public, the Census Bureau reviews them to make sure none of the information or characteristics could identify someone. For more information about the Census Bureau’s privacy and confidentiality protections, contact the Policy Coordination Office toll-free at 1-800-923-8282. All code used as part of this study is available in the Appendix . Funding Data Resource Center for Child and Adolescent Health supported by Cooperative Agreement U59MC27866 from the U.S. Department of Health and Human Services, Health Resources and Services Administration (HRSA), Maternal and Child Health Bureau (MCHB). Author’s contributions CDP conceived the study, carried out formal analyses and data management, prepared visualizations, and drafted and finalized the manuscript; EJM carried out formal analyses and data management, prepared tables and figures, and drafted and edited the manuscript; DMYB drafted and edited the manuscript and provided analyses support; SB drafted, edited/reviewed, and finalized the manuscript; ETH drafted and edited the manuscript; AJ drafted and edited the manuscript; HP drafted, edited, and finalized the manuscript; DS provided conceptualization support and supervision, and drafted, edited, and finalized the manuscript. 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Int J Behav Nutr Phys Act. 2022;19(1):2. 10.1186/s12966-021-01236-2 . Centers for Disease Control. Physical Activity Basics. Accessed March 5. 2025. https://www.cdc.gov/physical-activity-basics/guidelines/children.html Additional Declarations No competing interests reported. Supplementary Files Pfledderer5YearTrendsJASSBAppendix.docx Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 10 Sep, 2025 Reviews received at journal 02 Sep, 2025 Reviews received at journal 17 Aug, 2025 Reviewers agreed at journal 11 Aug, 2025 Reviewers agreed at journal 11 Aug, 2025 Reviewers agreed at journal 06 Aug, 2025 Reviewers invited by journal 05 Aug, 2025 Editor assigned by journal 30 Jul, 2025 Submission checks completed at journal 29 Jul, 2025 First submitted to journal 25 Jul, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Pfledderer","email":"data:image/png;base64,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","orcid":"","institution":"University of Texas Health Science Center Houston (UTHealth Houston)","correspondingAuthor":true,"prefix":"","firstName":"Christopher","middleName":"D.","lastName":"Pfledderer","suffix":""},{"id":497111737,"identity":"a45e2377-cce2-4ac8-993e-b4dad96098a4","order_by":1,"name":"Emma J. Mullane","email":"","orcid":"","institution":"University of Texas Health Science Center (UTHealth Houston) School of Public Health","correspondingAuthor":false,"prefix":"","firstName":"Emma","middleName":"J.","lastName":"Mullane","suffix":""},{"id":497111738,"identity":"df702031-f735-4aa4-ab24-56bd3b394a05","order_by":2,"name":"Denver M.Y. Brown","email":"","orcid":"","institution":"Kansas State University","correspondingAuthor":false,"prefix":"","firstName":"Denver","middleName":"M.Y.","lastName":"Brown","suffix":""},{"id":497111739,"identity":"01e68e24-184d-435f-a966-29ef24aa6dd3","order_by":3,"name":"Sarah Burkart","email":"","orcid":"","institution":"University of South Carolina","correspondingAuthor":false,"prefix":"","firstName":"Sarah","middleName":"","lastName":"Burkart","suffix":""},{"id":497111741,"identity":"3df6ba38-8722-428e-bd7a-b7fa0e56a4b7","order_by":4,"name":"Ethan T. Hunt","email":"","orcid":"","institution":"University of Texas Health Science Center Houston (UTHealth Houston)","correspondingAuthor":false,"prefix":"","firstName":"Ethan","middleName":"T.","lastName":"Hunt","suffix":""},{"id":497111742,"identity":"3fd3a5f2-0494-4dac-86cd-58a5a7596de8","order_by":5,"name":"Ashleigh Johnson","email":"","orcid":"","institution":"San Diego State University","correspondingAuthor":false,"prefix":"","firstName":"Ashleigh","middleName":"","lastName":"Johnson","suffix":""},{"id":497111743,"identity":"e809f73d-5498-4776-a7c6-4566f358c2dc","order_by":6,"name":"Hannah Parker","email":"","orcid":"","institution":"University of South Carolina","correspondingAuthor":false,"prefix":"","firstName":"Hannah","middleName":"","lastName":"Parker","suffix":""},{"id":497111744,"identity":"7089b21e-08a2-4860-b72a-9300fd377641","order_by":7,"name":"Deborah Salvo","email":"","orcid":"","institution":"The University of Texas at Austin","correspondingAuthor":false,"prefix":"","firstName":"Deborah","middleName":"","lastName":"Salvo","suffix":""}],"badges":[],"createdAt":"2025-07-25 14:53:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7215360/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7215360/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":88775567,"identity":"1934b40e-a6d9-4415-a3df-90d12fc35ae9","added_by":"auto","created_at":"2025-08-11 10:06:04","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":88789,"visible":true,"origin":"","legend":"\u003cp\u003eCONSORT diagram.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7215360/v1/002faade04060815b6bfc040.png"},{"id":88775568,"identity":"8b88d11e-0914-417c-b925-34cda3fc4f40","added_by":"auto","created_at":"2025-08-11 10:06:04","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":49604,"visible":true,"origin":"","legend":"\u003cp\u003eFive-year trends in 24-hour movement behavior guideline adherence among children and adolescents from pooled data of the 2018-2022 National Survey of Children’s Health (N=135,309, Representative N=48,419,077).\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7215360/v1/2595e532056173dfd317b16d.png"},{"id":88779128,"identity":"60a4e66e-7b79-4273-8e93-7c031e47bdca","added_by":"auto","created_at":"2025-08-11 10:30:04","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1132925,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7215360/v1/9c967bcb-c323-4e67-822c-e02b7cf423e3.pdf"},{"id":88775574,"identity":"ee338be9-2830-46b2-8f3b-b77bc3ec10b3","added_by":"auto","created_at":"2025-08-11 10:06:04","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":40412,"visible":true,"origin":"","legend":"","description":"","filename":"Pfledderer5YearTrendsJASSBAppendix.docx","url":"https://assets-eu.researchsquare.com/files/rs-7215360/v1/c10f2e859bd482a3f2d06444.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Five-year trends in U.S. child and adolescent 24-hour movement behavior guideline adherence, 2018-2022","fulltext":[{"header":"1. INTRODUCTION","content":"\u003cp\u003eIn the past decade there has been a proliferation of research taking an integrative approach to studying physical activity (PA), sedentary behaviors and screentime (ST), and sleep (SL), as opposed to in isolation.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e This novel approach combines these behaviors together in a 24-hour activity cycle, commonly referred to as 24-hour movement behaviors (24hrMB) ), explicitly recognizing the co-dependence of these behaviors as time spent in one cannot be spent in another. To adhere to 24hrMB guidelines, children and adolescents in the US should accrue\u0026thinsp;\u0026ge;\u0026thinsp;60 minutes of moderate-to-vigorous physical activity (MVPA) each day,\u003csup\u003e2\u003c/sup\u003e \u0026le; 2 hours of recreational ST,\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e and 9\u0026ndash;11 hours or 8\u0026ndash;10 hours of sleep per night for children (6\u0026ndash;12 years) and adolescents (13\u0026ndash;17 years),\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e respectively.\u003c/p\u003e\u003cp\u003eAdherence to individual 24hrMB guidelines is beneficially associated with several health indicators in children and adolescents including cardiometabolic risk factors and aspects of mental health.\u003csup\u003e\u003cspan additionalcitationids=\"CR6 CR7 CR8 CR9 CR10\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e There is a large body of evidence that has demonstrated associations between PA and a range of outcomes including cognition,\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e academic achievement,\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e motor skills,\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e, overweight/obesity,\u003csup\u003e14\u003c/sup\u003e, and a host of other non-communicable diseases.\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e Falling short of ST recommendations has been deleteriously linked to outcomes such as depression, anxiety, and other mental health outcomes,\u003csup\u003e\u003cspan additionalcitationids=\"CR17\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e and an increased odds of having overweight/obesity.\u003csup\u003e19\u003c/sup\u003e Insufficient sleep duration among youth has been shown to be associated with cognitive and emotional difficulties including learning and self-regulation,\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e increased risk taking behaviors, school performance, and psychosocial health,\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e and increased risk of developing a number of non-communicable diseases including overweight/obesity and diabetes.\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e Finally, evidence has demonstrated that concurrent adherence to multiple guidelines, especially concurrent adherence to all three guidelines, is associated with the most favorable benefits regarding developmental and health outcomes.\u003csup\u003e\u003cspan additionalcitationids=\"CR24 CR25 CR26 CR27\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eDespite these developmental and health benefits, relatively few children and adolescents in the US meet 24hrMB guidelines and even fewer concurrently adhere to multiple guidelines.\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e,\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e,\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e,\u003cspan additionalcitationids=\"CR30\" citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e Recent studies indicate that the proportion of children and adolescents who meet individual PA guidelines is as low as 22.3%, the proportion meeting ST guidelines is between 10\u0026ndash;28%, and the proportion meeting SL guidelines is as low as 57%.\u003csup\u003e32,33\u003c/sup\u003e Further, less than 5% of children and adolescents meet all three guidelines concurrently.\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e Evidence has also revealed disparities between sex, age, and overweight/obesity status in adherence to 24hrMB guidelines among children and adolescents with recent findings showing a higher proportion of males compared to females, children compared to adolescents, and those without overweight/obesity compared to those with overweight/obesity adhering to guidelines.\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e,\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e,\u003cspan additionalcitationids=\"CR35 CR36 CR37\" citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eChild and adolescent adherence to 24hrMB has been declining in the past few years as well.\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e,\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e,\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e,\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e,\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e An eight-year study in the US (2011\u0026ndash;2019) found that the prevalence of meeting 24hrMB guidelines in children and adolescents decreased each year.\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e A similar study found that children and adolescents with overweight and obesity had a continuous increase in ST from 2018 to 2022.\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e Diminished adherence to 24-hour movement behaviors in youth may have significant implications for future generations, including a higher prevalence of non-communicable, obesity-related diseases, a higher prevalence of mental health-related complications, and an increased burden to an already strained healthcare system given the non-communicable disease crisis in the U.S.\u003csup\u003e\u003cspan additionalcitationids=\"CR9 CR10\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan additionalcitationids=\"CR24 CR25 CR26 CR27\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e,\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e,\u003cspan additionalcitationids=\"CR42\" citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003e There is a critical need to understand recent trends in 24hrMB guideline adherence among children and adolescents in the US. Given a) already known sex-based movement behavior disparities, b) the youth obesity epidemic that the US has been experiencing for the past two decades, c) seemingly ubiquitous access to technology-based leisure/entertainment among children, and d) social norms favoring sedentary travel and restricting independent mobility among younger children, there is also a critical need to identify current disparities with respect to sex, age, and overweight/obesity status. It is important to not just diagnose the extent to which children and adolescents adhere to 24hr MB guidelines, but if and how adherence has changed over time, and in particular, see if these changes are affecting certain age-groups, males and females, and children with overweight/obesity vs. those without overweight/obesity differently. By using these factors as effect modifiers, there is also the potential to guide more tailored public health interventions and inform whether existing guidelines need to be adapted for high-risk subgroups, including children, females, and those with overweight/obesity.\u003c/p\u003e\u003cp\u003e To date, few studies have explored children\u0026rsquo;s and adolescent\u0026rsquo;s individual guideline adherence and concurrent adherence to multiple guidelines across recent years and even fewer have done so on a national level. Given concerning downward trends of guideline adherence pre- COVID-19 pandemic and evidence that suggests a sharper decrease in guideline adherence during the height of the pandemic,\u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e understanding how guideline adherence has shifted in the years that followed is important as we work to design targeted interventions and provide public health evidence for policy makers. Monitoring trends in 24hrMB guideline adherence may provide insights into whether public health messaging, policy changes, and environmental shifts are leading to an improvement or a worsening of these behaviors among youth. Additionally, it is important to identify emerging disparities across certain subgroups (males vs. females, children vs. adolescents, those with overweight/obesity vs. those without) in an effort for health systems and public health initiatives to be proactive as opposed to reactive in addressing declines in PA, ST, and SL guideline adherence. Ultimately, this research is essential for guiding evidence-based interventions, policies, and national health promotion strategies. Therefore, the purpose of this study was to investigate the five-year trends in 24hrMB guideline adherence among children and adolescents using the 2018\u0026ndash;2022 National Survey of Children\u0026rsquo;s Health (NSCH) and explore differences in adherence with respect to age, sex, and overweight/obesity status.\u003c/p\u003e"},{"header":"2. METHODS","content":"\u003cp\u003e\u003cstrong\u003e2.1. Data Source and Participants\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis secondary data analysis study utilized a successive independent samples design involving data from five waves (2018-2022) of the NSCH. The NSCH is a parent-reported, nationally representative survey of non-institutionalized children and adolescents living in the U.S., administered by the United States Census Bureau and the Maternal and Child Health Bureau of Health Resources and Services administration.\u003csup\u003e45\u003c/sup\u003e Because this study used de-identified, publicly available data, it did not qualify as human subjects research and did not require Institutional Review Board review, as per the federal policy for the protection of human subjects.\u003csup\u003e46\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003eThe NSCH includes children and adolescents between the ages of 0-17 years. For this study, we excluded children who were less than six years old and those who were missing 24hrMB data. Although 24hrMB guidelines apply to children as young as 5 years old, the NSCH does not collect PA data for children under 6 years, necessitating their exclusion from this study. Sample sizes for pooled data, for each survey year, and for those excluded from the final analytical sample are communicated in \u003cstrong\u003eFigure 1\u003c/strong\u003e. Briefly, the 2018-2022 waves of NSCH included responses from 207,735 (Weighted N = 73,057,474) participants, of which our analytical sample included responses from 135,309 (Weighted N = 48,419,077) children and adolescents ages 6-17 years. Across 2018-2022 survey years, response rates ranged from 39.1% to 43.1%, and no strong/consistent evidence of nonresponse bias was detected during any survey year.\u003csup\u003e47\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2. Measures\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe following section details measures for primary outcomes (adherence to 24hrMB guidelines) and relevant covariates. The Maternal and Child Health Bureau, the US Census Bureau, and a national technical expert panel, comprised of representatives from other federal agencies, family organizations, child health leaders, and others, led the development of indicators, and validated survey questions are used on the NSCH when available. Cognitive testing was performed on all survey items, although the NSCH does not make this data publicly available.\u003csup\u003e48\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2.1. Physical activity (PA).\u0026nbsp;\u003c/strong\u003ePhysical activity guideline adherence was determined from a single question which asked parent/caregivers, \u0026ldquo;During the past week, on how many days did this child exercise, play a sport, or participate in physical activity for at least 60 minutes?\u0026rdquo; Responses were dichotomized into whether participants met the guideline of engaging in 60 minutes of physical activity every day or not (6 days or less).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2.2. Screen time (ST).\u0026nbsp;\u003c/strong\u003eScreen time guideline adherence was determined from a single question which asked parents/caregivers, \u0026ldquo;On most weekdays, about how much time did this child spend in front of a TV, computer, cellphone, or other electronic device watching programs, playing games, accessing the internet or using social media? Do not include time spent doing schoolwork.\u0026rdquo; Responses were dichotomized into whether participants engaged in \u0026le; 2h of screen time per day (met the guideline) or engaged in \u0026gt;2h of screen time per day (did not meet the guideline).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2.3. Sleep duration (SL).\u0026nbsp;\u003c/strong\u003eSleep guideline adherence was determined from a single question which asked parents/caregivers, \u0026ldquo;During the past week, how many hours of sleep did this child get on most weeknights?\u0026rdquo; Guideline adherence for children (6-12 years) was operationalized as sleeping 9-11 hours per night and, for adolescents (13-17 years), guideline adherence was operationalized as sleeping 8-10 hours per night.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2.4. Adherence to combinations of guidelines.\u0026nbsp;\u003c/strong\u003eAdherence to combinations of 24hrMB guidelines (PA+ST, PA+SL, SL+ST, and all three) was created by combining dichotomized individual guideline adherence variables and recoding them as an additional dichotomized variable (0= did not concurrently meet combined guidelines, 1 = concurrently met combined guidelines).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2.5. Covariates.\u0026nbsp;\u003c/strong\u003eDemographic covariatesincluded age (dichotomized into children [6-12 years] and adolescents [13-17 years]), race/ethnicity (Hispanic, Black, White, Other/Multi-racial), sex (male/female), household income level relative to the federal poverty line (FPL; \u0026lt;100%, 100-199% FPL, 200-399% FPL, \u0026ge;400% FPL), metropolitan statistical area status (Metro/non-Metro), and overweight/obesity status (yes [\u0026ge;85th BMI percentile], no [\u0026lt;85th BMI percentile]).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.3. Statistical Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWeighted prevalence and unweighted counts were calculated for all variables for the pooled sample and compared across survey years (2018-2022) using chi-square tests. Weighted logistic regression models were used to examine adherence to 24hrMB guidelines, with survey year included as a categorical independent variable. These models were adjusted for age, sex, race/ethnicity, household income level relative to the FPL, metropolitan statistical area status, and overweight/obesity status, in addition to adherence to the guidelines not included as the outcome variable. Follow-up analyses were computed to examine adherence to each component of the 24hrMB guidelines and meeting different combinations of the individual components of the guidelines (i.e., PA + ST, PA + SL, ST + SL). Separate models were also employed to analyze interactions between sex, age, and overweight/obesity status and 24hrMB guideline adherence across survey years. \u0026nbsp;Post-hoc marginal probabilities were calculated for each survey year and Cochran-Armitage tests for trend were used to examine trends in 24hrMB guideline adherence across 2018-2022. Statistical analyses were carried out using\u0026nbsp;Stata v18.0 (StataCorp LP, College Station, Texas, USA) and a type I error level of 0.05 was used to establish statistical significance. The sampling design of the NSCH datasets was accounted for and weighting was applied using the Taylor Series Linearization variance estimation before all statistical testing was conducted. All code used for the analysis is available in the \u003cstrong\u003eAppendix\u003c/strong\u003e.\u003c/p\u003e"},{"header":"3. RESULTS","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e3.1. Total sample\u003c/h2\u003e\u003cp\u003eA total of 135,309 (Weighted N\u0026thinsp;=\u0026thinsp;48,419,077) children and adolescents (mean age\u0026thinsp;=\u0026thinsp;11.9\u0026thinsp;\u0026plusmn;\u0026thinsp;3.5 years, 48.9% female, 71.3% White) were included in the analytical sample (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Complete demographic and 24hrMB guideline adherence statistics for the total sample are communicated in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. From pooled data across 2018\u0026ndash;2022, 20.8% met PA guidelines, 49.6% met ST guidelines, 64.7% met SL guidelines, and 9.7% met all three guidelines concurrently.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eDemographic and behavioral characteristics of children and adolescents from pooled data of the 2018\u0026ndash;2022 National Survey of Children\u0026rsquo;s Health (N\u0026thinsp;=\u0026thinsp;135,309, Representative N\u0026thinsp;=\u0026thinsp;48,419,077).\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDemographic Characteristics\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUnweighted Count\u003c/p\u003e\u003cp\u003e(Weighted Percent)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge, years (Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e11.9\u0026thinsp;\u0026plusmn;\u0026thinsp;3.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge Category\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChildren (6\u0026ndash;12 years)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e70,165 (57.9%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAdolescents (13\u0026ndash;17 years)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e65,144 (42.1%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSex (Female)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e66,435 (48.9%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRace\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAmerican Indian or Alaska Native\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1,357 (1.5%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAsian\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7,729 (5.3%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBlack or African American\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e9,970 (14.6%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNative Hawaiian or Other Pacific Islander\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e747 (0.7%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTwo or More Races\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e10,534 (6.6%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWhite\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e104,972 (71.3%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHispanic or Latino Origin\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e18,169 (26.5%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOverweight/Obesity (\u0026ge;\u0026thinsp;85th BMI percentile)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e38,814 (33.2%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNon-Metropolitan Statistical Area Status\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e19,357 (12.4%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFederal Poverty Level Ratio (Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e286\u0026thinsp;\u0026plusmn;\u0026thinsp;183\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e24-Hour Movement Guideline Adherence\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePhysical Activity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e28,163 (20.8%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eScreentime\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e65,781 (49.6%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSleep\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e92,129 (64.7%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePhysical Activity\u0026thinsp;+\u0026thinsp;Screentime\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e18,334 (13.3%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePhysical Activity\u0026thinsp;+\u0026thinsp;Sleep\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e20,270 (14.4%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eScreentime\u0026thinsp;+\u0026thinsp;Sleep\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e47,623 (34.2%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAll Three\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e13,809 (9.7%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e3.2. Five-year trends in 24-hour movement behavior guideline adherence\u003c/h2\u003e\u003cp\u003e Except for SL, which remained stable, the prevalence of adherence to every 24hrMB guideline decreased from 2018 to 2022, with variation between individual guidelines and years (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The largest decrease from 2018 to 2022 was in adherence to ST guidelines, with 52% meeting the guideline in 2018 and 47% meeting the guideline in 2022 (5% decrease). Comparatively, PA guideline adherence decreased by 4% between 2018 and 2022. Prevalence of concurrently meeting all three guidelines decreased from 9% in 2018 to 7% in 2022 (2% decrease). The largest year to year decrease occurred with ST guideline adherence between 2019 and 2020 (12% decrease), with incremental increases each year after. Cochran-Armitage tests for trend revealed a significant downward trend in guideline adherence for all 24hrMB across 2018\u0026ndash;2022 (\u003cem\u003eX\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u003csub\u003erange\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;45.9-826.2, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), with SL adherence increasing between 2018\u0026ndash;2020 and then declining between 2021\u0026ndash;2022 (\u003cb\u003eAppendix\u003c/b\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eMarginal predicted prevalences of children and adolescents in the National Survey of Children\u0026rsquo;s Health adhering to 24-hour movement behavior between 2018\u0026ndash;2022 (N\u0026thinsp;=\u0026thinsp;135,309, Representative N\u0026thinsp;=\u0026thinsp;48,419,077).\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"11\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e24-hour guideline\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"10\" nameend=\"c11\" namest=\"c2\"\u003e\u003cp\u003eYear\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e2018\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e2019\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003e2020\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003e2021\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u003cp\u003e2022\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMargin\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e95% CI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMargin\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e95% CI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eMargin\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003e95%CI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eMargin\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003e95% CI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e\u003cp\u003eMargin\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c11\"\u003e\u003cp\u003e95% CI\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePhysical Activity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.19\u0026ndash;0.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.18\u0026ndash;0.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.18\u0026ndash;0.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.18\u0026ndash;0.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e0.16\u0026ndash;0.18\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eScreentime\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.50\u0026ndash;0.54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.50\u0026ndash;0.53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.39\u0026ndash;0.42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.43\u0026ndash;0.45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e0.46\u0026ndash;0.48\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSleep\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.62\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.61\u0026ndash;0.64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.62\u0026ndash;0.65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.64\u0026ndash;0.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.64\u0026ndash;0.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e0.62\u0026ndash;0.64\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePhysical Activity\u0026thinsp;+\u0026thinsp;Screentime\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.12\u0026ndash;0.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.11\u0026ndash;0.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.09\u0026ndash;0.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.10\u0026ndash;0.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e0.10\u0026ndash;0.11\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePhysical Activity\u0026thinsp;+\u0026thinsp;Sleep\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.12\u0026ndash;0.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.12\u0026ndash;0.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.12\u0026ndash;0.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.13\u0026ndash;0.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e0.11\u0026ndash;0.12\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eScreentime\u0026thinsp;+\u0026thinsp;Sleep\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.33\u0026ndash;0.36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.34\u0026ndash;0.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.27\u0026ndash;0.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.29\u0026ndash;0.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e0.31\u0026ndash;0.33\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAll Three\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.09\u0026ndash;0.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.08\u0026ndash;0.97\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.07\u0026ndash;0.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.08\u0026ndash;0.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e0.07\u0026ndash;0.08\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e3.3. Variations in 24-hour movement behavior guideline adherence trends by sex, age, and overweight/obesity status\u003c/h2\u003e\u003cp\u003ePost-hoc marginal predicted prevalences for interactions with sex, age, and overweight/obesity status are communicated in the \u003cb\u003eAppendix\u003c/b\u003e. Compared to males, females had significantly lower predicted prevalence of meeting PA, PA\u0026thinsp;+\u0026thinsp;ST, PA\u0026thinsp;+\u0026thinsp;SL, and concurrent adherence to all three guidelines, and significantly higher predicted prevalence of meeting ST and ST\u0026thinsp;+\u0026thinsp;SL, with the predicted prevalence of meeting individual SL guidelines roughly the same between males and females. Trends in marginal predicted prevalences across 2018\u0026ndash;2022 for both males and females were similar to that of the total sample. Compared to adolescents, children had significantly higher predicted prevalence of meeting all combinations of 24hrMB guidelines, except for SL. Trends across 2018\u0026ndash;2022 for children and adolescents were similar to that of the total sample, although the predicted prevalence of meeting ST, ST\u0026thinsp;+\u0026thinsp;PA, and all three guidelines decreased more for children than adolescents in 2020. Children with overweight/obesity had significantly lower predicted prevalence of meeting all guidelines when compared to children without overweight/obesity and trends across 2018\u0026ndash;2022 were similar for both groups and mirrored that of the total sample.\u003c/p\u003e\u003c/div\u003e"},{"header":"4. DISCUSSION","content":"\u003cp\u003e We investigated the five-year trends in 24hrMB guideline adherence among U.S. children and adolescents using the 2018\u0026ndash;2022 waves of the NSCH. We found that the prevalence of adherence to every 24hrMB guideline, except for sleep, decreased from 2018 to 2022, with largest decreases observed for adherence to individual ST and PA guidelines. Children, males, and those without overweight/obesity had higher adherence to most guidelines, although year-to-year trends for these subgroups mirrored trends of the total sample. These findings offer an updated perspective on trends in 24hrMB guideline adherence, highlighting subgroups that may benefit most from targeted interventions.\u003c/p\u003e\u003cp\u003e Approximately 20% of the total sample in our study met PA guidelines, less than 50% met the ST guidelines, and almost two-thirds (64.7%) met the SL guidelines. These findings tend to align with adherence rates observed in previous studies.\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e,\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e,\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e,\u003cspan additionalcitationids=\"CR38\" citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e For example, a similar cross-sectional study analyzing NSCH data from 2016\u0026ndash;2017 found that the proportion of U.S. children and adolescents meeting PA guidelines was approximately 23%, ST guidelines were 33%, and SL guidelines were about 86%.\u003csup\u003e29\u003c/sup\u003e Separately, a global meta-analysis utilizing school-based surveys determined that over 80% of adolescents (aged 11 to 17 years) did not adhere to PA recommendations/guidelines.\u003csup\u003e49\u003c/sup\u003e Slight differences in the frequency of adherence to individual 24hrMB guidelines between this study and past findings may be due to increased technology use among youth\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e,\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e,\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e,\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e and the COVID-19 pandemic, which had considerable influence over child and adolescent 24hrMB guideline adherence due to quarantine policies, remote learning, and other disruptions to routine and structure.\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e,\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e,\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e,\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e Finally, our overall findings are comparable to a recent meta-analysis including 22 other countries outside of the US, which suggests 24hrMB guideline adherence is a growing concern on a global scale.\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003e The main finding of our study is the decrease in guideline adherence between 2018\u0026ndash;2022. During these five years, we observed a 5% decrease in ST guideline adherence and a 4% decrease in PA guideline adherence. It was found that adherence to the SL guidelines was stable during this five-year period and even slightly increased between 2018\u0026ndash;2021, before decreasing again in 2022. In addition, concurrent guideline adherence decreased by 3%. The trends in marginal predicted prevalences according to sex, age, and overweight/obesity status were similar to the total sample from 2018 to 2022. However, the prevalence of adhering to ST, PA\u0026thinsp;+\u0026thinsp;ST, and all three guidelines decreased for children more than adolescents in 2020, the year of the onset of the COVID-19 pandemic and when stricter movement restriction and space closure policies took place across the U.S. This alarming rise in individual and concurrent guideline non-adherence has been seen in multiple research findings\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e,\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e,\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e,\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e,\u003cspan additionalcitationids=\"CR54\" citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u003c/sup\u003e and globally, these trends are similar to findings from other countries where trend analyses have been conducted, including Australia,\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e South Korea,\u003csup\u003e\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u003c/sup\u003e and New Zealand.\u003csup\u003e\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u003c/sup\u003e Collectively, the observed declines in ST and PA guideline adherence underscore the urgent need for targeted interventions to address growing disparities in wake-time movement behaviors, particularly during childhood. Such efforts could help establish healthy habits that support sustained guideline adherence through adolescence.\u003c/p\u003e\u003cp\u003e While the prevalence of ST guideline adherence did decrease from 2018 to 2022, and sharply decreased from 2019 to 2020, we did observe incremental increases in ST adherence after 2020, although it did not recover to the prevalence observed in 2018. This pattern of ST adherence has several public health implications. First, the sharp reduction in adherence from 2019 to 2020 suggest that the COVID-19 pandemic had a major influence on ST behaviors among youth. This point will be highlighted at length later in the Discussion. Second, the recovery of ST guideline adherence post-2020 may suggest that ST behaviors are largely modifiable and responsive to environmental changes, like schools reopening and the resumption of structured routines.\u003csup\u003e\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e,\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e\u003c/sup\u003e This finding offers of a window of opportunity for public health interventions, as it suggests that promoting healthy ST habits can be effective post-pandemic and beyond. However, public health researchers should focus on identifying and supporting those who have not yet recovered health ST habits, including males, adolescents, and those with overweight/obesity, as our study also demonstrated lower adherence across time among these subgroups.\u003c/p\u003e\u003cp\u003e Interestingly, SL guideline adherence remained relatively stable from 2018 to 2022. This finding may have a number of public health implications. First, sleep duration (which is what the SL guidelines specify) may be less sensitive to large-scale external disruptions, like the COVID-19 pandemic or longer-term shifts in daily routines. This resilience could reflect the biological regulation of sleep,\u003csup\u003e\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e\u003c/sup\u003e stronger parental control, particularly in children, and/or the influence of consistent bedtime routines.\u003csup\u003e\u003cspan additionalcitationids=\"CR62\" citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e\u003c/sup\u003e Second, stable adherence to SL guidelines may provide a reference point for large-scale population health studies for understanding how more variable behaviors, like ST and PA, may interact with more stable movement behaviors, like SL. However, it is important to remember that SL guidelines only establish parameters for sleep duration, not for other factors such as sleep quality, consistency, or timing, all of which can impact health outcomes.\u003csup\u003e\u003cspan additionalcitationids=\"CR65\" citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e\u003c/sup\u003e Future trend or longitudinal studies should explore dimensions of sleep beyond duration to better understand overall sleep health among youth across time.\u003c/p\u003e\u003cp\u003eRecent publications\u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e,\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e,\u003cspan additionalcitationids=\"CR68\" citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e\u003c/sup\u003e reveal that the COVID-19 pandemic had a considerable effect on 24hrMB among youth and the decreases that were found in our study and others may be partly due to remote learning, social restrictions, and stressors brought on during this time.\u003csup\u003e\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e,\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e\u003c/sup\u003e Indeed, the transfer to remote learning gave rise to major changes in the routine and structure of the 24-hour day for school-aged children. As seen in a study\u003csup\u003e\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e\u003c/sup\u003e examining the impact of virtual and in-person school during COVID-19, days in which children were attending in-person school were associated with a greater likelihood of children meeting the 24hrMB guidelines compared to days students were attending virtual school. Another adjustment for youth throughout the pandemic was an absence of recreational sports and local community programs that typically prompt greater adherence to the movement behavior guidelines.\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e,\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e\u003c/sup\u003e To further support the notion that closures brought on by the COVID-19 pandemic were detrimental to 24hrMB guideline adherence, our study found that adherence to ST and ST\u0026thinsp;+\u0026thinsp;SL increased slightly between 2020\u0026ndash;2022, but never recovered back to similar proportions as 2018. This could be because youth returned to in-person school and were able to participate in recreational sports and other structured activities after 2020. Still, the fact that adherence has yet to recover to pre-pandemic levels is concerning, suggesting a broader shift toward increasingly sedentary lifestyles. Increased use of technology in children and adolescents could also explain the trend of diminished guideline adherence reported in our study, but the trend of increased ST appears to precede the COVID-19 pandemic. For example, an Australian study\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e examining trends in adolescent guideline adherence discovered that adherence to ST guidelines fell from 19% in 2009 to 10% in 2018. Future research should incorporate data that spans a longer timeframe to determine if trends in guideline adherence have been consistently declining or if the decline has accelerated in recent years.\u003c/p\u003e\u003cp\u003e We found significant differences in concurrent guideline adherence between sex, age, and overweight/obesity status, which held constant between 2018\u0026ndash;2022 and mirrored downward trajectories found in the total sample. Females had a significantly lower predicted prevalence of meeting PA, PA\u0026thinsp;+\u0026thinsp;ST, PA\u0026thinsp;+\u0026thinsp;SL, and concurrent adherence to all three guidelines, and had a significantly higher predicted prevalence of meeting ST and ST\u0026thinsp;+\u0026thinsp;SL than males. Previous studies support the result of higher PA adherence in boys\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e,\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e,\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e,\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e,\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e,\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e\u003c/sup\u003e and higher ST adherence in girls.\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e,\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e,\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e\u003c/sup\u003e These differences could be a result of greater participation in light physical activity (LPA) and non-screen-based activities found among females in previous studies. In a study\u003csup\u003e\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e\u003c/sup\u003e evaluating differences between first-grade males and females, it was determined that males favored sports, team games, and endurance activities compared to females who favored activities involving flexibility, roller skating, and dance. Several other investigations have discovered that males are more likely to participate in more moderate to vigorous physical activities than females.\u003csup\u003e\u003cspan additionalcitationids=\"CR75 CR76\" citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e\u003c/sup\u003e Additionally, it has been noted that females may engage in more non-screen-based activities than males.\u003csup\u003e\u003cspan additionalcitationids=\"CR79\" citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e\u003c/sup\u003e In a longitudinal study\u003csup\u003e\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e\u003c/sup\u003e from 2011 to 2017 surveying leisure activities in children and adolescents, it was established that females were more likely to be involved in theater, choir, orchestra, and dance. Future research should explore how context, activity type, and preferences may drive disparities between males and females with respect to 24hrMB guideline adherence.\u003c/p\u003e\u003cp\u003e Children had a higher prevalence of adherence to all 24hrMB guideline combinations (except SL) compared to adolescents across 2018\u0026ndash;2022, although both subgroups mirrored the total sample with downward trajectories across the five-year period. This finding of greater concurrent guideline adherence in children compared to adolescents is commonly reported.\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e,\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e,\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e,\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e,\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e\u003c/sup\u003e The transition from primary to secondary schools for youth may justify why children are meeting the guidelines more than adolescents. This transition period for children typically occurs at the age of 11 to 12 years old (preadolescence) and is marked by increased academic demands and shorter breaks throughout the day.\u003csup\u003e\u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e,\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e\u003c/sup\u003e For example, Chong et al.,\u003csup\u003e\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e\u003c/sup\u003e found that during the primary to secondary school transition, there was an increase in sedentary behavior (SB) and a decrease in SL and PA. The study indicated that these shifts in 24hrMB were partially due to added homework and extended ST before bed. Expanding on this idea, diminished adherence to 24hrMB guidelines by adolescents could be caused by independence gained in adolescence. As children grow into adolescence, they frequently acquire more responsibility and autonomy. This is accompanied by less parental control, greater use of the internet and mobile devices, and increased extracurriculars (social activities, employment, etc.).\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e,\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e,\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e,\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e\u003c/sup\u003e Time spent managing other tasks in adolescence may result in decreases in PA and increases in ST. Furthermore, less parental control could presume that adolescents can sleep longer during the weekend. In a cross-sectional study\u003csup\u003e\u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e85\u003c/span\u003e\u003c/sup\u003e analyzing adolescent sleep patterns on weekday versus weekend nights, it was found that on weekend nights students averaged 1.5 hours more sleep than on weekday nights. However, less parental control among adolescents could also indicate an unstructured bedtime compared to children who commonly have a mandatory bedtime.\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e Another explanation for the difference in child versus adolescent guideline adherence, including the SL discrepancy, could be in measurement methodology. Notably, our results derive from parent-reported surveys. Parents might be unaware of when their children are going to bed, particularly if adolescents have access to their smartphone at nighttime. Moreover, the varied SL recommendation\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e for children (9\u0026ndash;12 hours of sleep per night) and adolescents (8\u0026ndash;10 hours of sleep per night), may also explain differences in guideline adherence prevalence.\u003csup\u003e\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e Another explanation for this age-related discrepancy could be tied to chronotype shifts in adolescence. Studies have shown that adolescents have a greater preference for going to bed later compared to children, which can lead to an inability to meet SL guidelines, particularly on weeknights when youth sleep schedules are governed by school start times.\u003csup\u003e\u003cspan additionalcitationids=\"CR87\" citationid=\"CR86\" class=\"CitationRef\"\u003e86\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e88\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eOur findings also indicated that children with overweight/obesity status had a lower prevalence of meeting all the 24hrMB guidelines than children without overweight/obesity status, which also aligns with prior literature.\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e,\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e,\u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e89\u003c/span\u003e\u003c/sup\u003e For example, Chen et al.,\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e found that Chinese children and adolescents who met the 24hrMB guidelines had a lower risk of being overweight or obese. Furthermore, a separate study\u003csup\u003e\u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e90\u003c/span\u003e\u003c/sup\u003e noted that children and adolescents with increased PA and SL and decreased sedentary behavior had favorable levels of adiposity and health. It has also been proposed that reduced PA may occur because of greater adiposity.\u003csup\u003e\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e,\u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e91\u003c/span\u003e\u003c/sup\u003e While our findings are not causal, the relationship between overweight/obesity and 24hrMB guideline adherence cannot be overlooked. Future longitudinal studies should examine the bi-directional associations between overweight/obesity and 24hrMB among children and adolescents.\u003c/p\u003e\u003cp\u003e Ultimately, our study garners further support for interventions that are designed to promote concurrent adherence to 24hrMB guidelines and indicates a strong need to slow and reverse the downward trend in guideline adherence among children and adolescents. Additionally, although the US has individual guidelines for PA, ST, and SL, it has not established 24hrMB guidelines, like many other countries have already done.\u003csup\u003e\u003cspan additionalcitationids=\"CR93\" citationid=\"CR92\" class=\"CitationRef\"\u003e92\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e94\u003c/span\u003e\u003c/sup\u003e In not doing so, this fails to recognize the co-dependence of PA, ST, and SL as a collective 24-hour behavioral cycle. Public health officials and policy makers in the US should be aware of the co-dependency of these behaviors and work to establish 24hrMB guidelines, which could set the stage for widespread adoption, education, and promotion of 24hrMB as a collective health outcome. Differences in guideline adherence between sex, age, and overweight/obesity status further strengthen the notion that behavioral interventions should be tailored to meet the needs of demographic subgroups. Researchers should strive to understand what factors are driving these differences and work to develop programs/interventions that prioritize minimizing the 24hrMB guideline adherence gaps between youth of different sex, age, and overweight/obesity status.\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e4.1. Strengths and Limitations\u003c/h2\u003e\u003cp\u003eOur study utilized data from five waves (2018\u0026ndash;2022) of the NSCH, a large, nationally representative sample of children and adolescents in the US. Data from 135,309 participants were included in our analytical sample, with very low percentages of missing data for each variable. Not only did we use multiple waves of data to understand yearly variations in PA, ST, and SL guideline adherence, but we also present findings for concurrent adherence to every combination of 24hrMB guidelines, accounting for the co-dependent nature of the behaviors. Finally, we compare yearly trends between several key demographic variables including sex, age, and overweight/obesity status. This is the first study to thoroughly report recent trends in 24hrMB adherence for a nationally representative sample of children and adolescents from the US.\u003c/p\u003e\u003cp\u003eDespite these strengths, our study has several weaknesses to note, including the cross-sectional, successive, independent samples design, which prevents causal interpretations of the findings. Additionally, repeated cross-sectional studies have several other limitations including 1) these studies survey different individuals at each timepoint making it impossible to assess within-person changes or individual trajectories, 2) differences observed over time may reflect cohort effects rather than true trends, and 3) without longitudinal tracking, it is more difficult to adjust for time-varying confounders and/or establish temporal ordering between exposure (year) and 24hrMB guideline adherence. Larger-scale longitudinal designs utilizing the same sample of children and adolescents are warranted to thoroughly investigate trends in 24hrMB guideline adherence. Additionally, all data were parent-reported with single-item questions, although survey questions used to measure PA, SL, and ST in NSCH have been validated. Also, the NSCH includes responses for youth aged 0\u0026ndash;17 years. We chose to exclude those aged 0\u0026ndash;5 years because NSCH does not collect the same type of PA data on this age range and the recommendations are operationalized differently for infants, toddlers, and preschoolers.\u003csup\u003e\u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e95\u003c/span\u003e\u003c/sup\u003e On the topic of PA guidelines, this study did not account for muscle/bone strengthening activities (which are part of the guidelines for youth in the US), although the NSCH does not ask about these types of activities on their survey. Other possible disparities beyond those based on sex, age group, and overweight obesity status, known to help explain many health inequities in the U.S. (race/ethnicity, socioeconomic status, urban/rural status) were not explored in this analysis. These factors should be considered in future trend studies focusing on 24hrMB guideline adherence. As previously noted, the US does not currently have 24hrMB guidelines, but instead has individual guidelines for PA, ST, and SL. Because of this we relied on several sources for quantifying guideline adherence and these sources/organizations may differ from others in the US with respect to recommendations. Finally, we must acknowledge that this study focused on years 2018\u0026ndash;2022, which is a relatively short timeframe, capturing movement behaviors before, during, and immediately after the height of the COVID-19 pandemic. Future studies should continue to investigate the longer-term trends in 24hrMB, incorporating data from future waves of NSCH or from other nationally representative data sources.\u003c/p\u003e\u003c/div\u003e"},{"header":"5. Conclusions","content":"\u003cp\u003e The prevalence of adherence to every 24hrMB guideline decreased from 2018 to 2022, with largest decreases observed for adherence to individual ST and PA guidelines, and lower adherence observed for females, adolescents, and individuals with overweight/obesity. These trends are concerning from a public health perspective, as meeting these guidelines is linked to numerous indicators of healthy development for children and youth. This highlights the urgent need for multi-level intervention strategies that target multiple movement behaviors to address the issue. The pandemic had a seemingly lasting effect on children during the movement restriction/space closure years. This is a lesson for future major times of crises (other infectious disease emergencies, natural disasters, etc.) to prioritize opportunities for staying active and limiting ST while balancing other threats. While sex-based, age-based, and weight-status-based gaps in 24hrMB guideline adherence are not widening over time, closing the gap in guideline adherence between sex, age, and overweight/obesity status should be a priority among those implementing behavioral interventions for youth and may be accomplished by designing context-specific interventions for demographic subgroups. Overall, researchers, public health practitioners, and policy-makers should strive to take an integrative approach when promoting PA, ST, and SL in an effort to slow and reverse the downward trend in 24hrMB guideline adherence among children and adolescents in the US.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003e24-Hour Movement Behaviors (24hrMB); National Survey of Children\u0026rsquo;s Health (NSCH); Physical Activity (PA), Screentime (ST); Sleep (SL)\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eACKNOWLEDGMENTS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to thank the participants who took part in the 2018-2022 waves of the National Survey of Children\u0026rsquo;s Health.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe United States Census Bureau conducts the NSCH on behalf of HHS under Title 13, United States Code, Section (b), which allows the Census Bureau to conduct surveys on behalf of other agencies. Title 42 U.S.C. Section 701(a)(2) allows HHS to collect information for the purpose of understanding the health and well-being of children in the U.S.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFull datasets may be requested at: https://www.childhealthdata.org/dataset. The data collected under this agreement are confidential under 13 U.S.C. Section 9. All access to Title 13 data from this survey is restricted to Census Bureau employees and those holding Census Bureau Special Sworn Status pursuant to 13 U.S.C. Section 23(c). Any effort to determine the identity of any reported case is prohibited. The Census Bureau and HRSA MCHB take extraordinary measures to assure that the identity of survey subjects cannot be disclosed. All direct identifiers, as well as characteristics that might lead to identification, have been omitted from the data files. Any intentional identification or disclosure of a person or establishment violates the assurances of confidentiality given to the providers of the information. Therefore, users must:\u003c/p\u003e\n\u003cp\u003e\u0026bull; Use the data in these data files for statistical reporting and analysis only;\u003c/p\u003e\n\u003cp\u003e\u0026bull; Make no use of the identity of any person discovered, inadvertently or otherwise;\u003c/p\u003e\n\u003cp\u003e\u0026bull; Not link these data files with individually identifiable data from any other Census Bureau or non-Census Bureau data sets.\u003c/p\u003e\n\u003cp\u003eUse of the data files signifies users\u0026rsquo; agreement to comply with the above-stated statutory-based requirements. Before releasing any statistics to the public, the Census Bureau reviews them to make sure none of the information or characteristics could identify someone. For more information about the Census Bureau\u0026rsquo;s privacy and confidentiality protections, contact the Policy Coordination Office toll-free at 1-800-923-8282.\u003c/p\u003e\n\u003cp\u003eAll code used as part of this study is available in the \u003cstrong\u003eAppendix\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData Resource Center for Child and Adolescent Health supported by Cooperative Agreement U59MC27866 from the U.S. Department of Health and Human Services, Health Resources and Services Administration (HRSA), Maternal and Child Health Bureau (MCHB).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor\u0026rsquo;s contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCDP conceived the study, carried out formal analyses and data management, prepared visualizations, and drafted and finalized the manuscript; EJM carried out formal analyses and data management, prepared tables and figures, and drafted and edited the manuscript; DMYB drafted and edited the manuscript and provided analyses support; SB drafted, edited/reviewed, and finalized the manuscript; ETH drafted and edited the manuscript; AJ drafted and edited the manuscript; HP drafted, edited, and finalized the manuscript; DS provided conceptualization support and supervision, and drafted, edited, and finalized the manuscript. All authors have read and approved the final version of the manuscript and agree with the order of presentation of the authors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests \u003cstrong\u003e\u003cbr\u003e\u003c/strong\u003e\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003ePedišić Z, Dumuid D, Olds TS. Integrating sleep, sedentary behaviour, and physical activity research in the emerging field of time-use epidemiology: definitions, concepts, statistical methods, theoretical framework, and future directions. Kinesiology 49(2):252\u0026ndash;69.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePiercy KL, Troiano RP, Ballard RM, et al. The Physical Activity Guidelines for Americans. 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Int J Behav Nutr Phys Act. 2022;19(1):2. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12966-021-01236-2\u003c/span\u003e\u003cspan address=\"10.1186/s12966-021-01236-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCenters for Disease Control. Physical Activity Basics. Accessed March 5. 2025. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.cdc.gov/physical-activity-basics/guidelines/children.html\u003c/span\u003e\u003cspan address=\"https://www.cdc.gov/physical-activity-basics/guidelines/children.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"journal-of-activity-sedentary-and-sleep-behaviors","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jassb","sideBox":"Learn more about [Journal of Activity, Sedentary and Sleep Behaviors](https://jassb.biomedcentral.com/)","snPcode":"44167","submissionUrl":"https://submission.nature.com/new-submission/44167/3","title":"Journal of Activity, Sedentary and Sleep Behaviors","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"24-Hour Movement Behaviors, Physical Activity, Sleep, Screentime, Youth","lastPublishedDoi":"10.21203/rs.3.rs-7215360/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7215360/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003e 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\u0026ndash;2022 waves of the National Survey of Children\u0026rsquo;s Health (NSCH), giving particular attention to disparities in guideline adherence with respect to sex, age, and overweight/obesity status.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eThis secondary data analysis study utilized a successive independent samples design involving data from five waves (2018\u0026ndash;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\u0026ndash;2022. Models were adjusted for sociodemographic, geographic, and health status variables, 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.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eA total of 135,309 (Weighted N\u0026thinsp;=\u0026thinsp;48,419,077) children and adolescents (mean age\u0026thinsp;=\u0026thinsp;11.9\u0026thinsp;\u0026plusmn;\u0026thinsp;3.5 years, 48.9% female, 71.3% White) were included in the analytical sample. From pooled data across 2018\u0026ndash;2022, 20.8% met PA guidelines, 49.6% met ST guidelines, 64.7% met SL guidelines, and 9.7% met all three guidelines concurrently. Except for sleep, which remained stable, the predictive prevalence of adherence to every combination of 24hrMB guideline was significantly lower in 2022 compared to 2018, with variations in trends between individual guidelines and years. The largest predicted prevalence difference from 2018 to 2022 was adherence to ST guidelines, which was 0.52 (95%CI: 0.50\u0026ndash;0.54) in 2018 and 0.47 (95%CI: 0.46\u0026ndash;0.48) in 2022 (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The largest year-to-year predictive prevalence difference was also adherence to ST guidelines from 2019\u0026ndash;2020, which was 0.52 (95%CI: 0.50\u0026ndash;0.53) in 2019 and 0.40 (95%CI: 0.39\u0026ndash;0.42) in 2020 (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Cochran-Armitage tests for trend revealed a significant downward trend in guideline adherence for all 24hrMB across 2018\u0026ndash;2022 (\u003cem\u003eX\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u003csub\u003erange\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;45.9-826.2, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003e The predictive prevalence of adherence to every combination of 24hrMB guideline was significantly lower in 2022 compared to 2018, except for individual SL guideline adherence, which remained stable. These findings are concerning from a public health perspective, as meeting 24hrMB guidelines is linked to numerous indicators of healthy development for children and youth, underscoring the need for effective multi-level behavioral interventions to address the continued decline in meeting 24hrMB guidelines among youth.\u003c/p\u003e","manuscriptTitle":"Five-year trends in U.S. child and adolescent 24-hour movement behavior guideline adherence, 2018-2022","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-11 10:05:59","doi":"10.21203/rs.3.rs-7215360/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-09-10T07:35:23+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-02T21:22:56+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-17T14:31:23+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"187931432909042719419263918635191101672","date":"2025-08-11T17:29:01+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"251041161185312435359503300166654442846","date":"2025-08-11T14:18:42+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"282141383436394668233297139989690724268","date":"2025-08-06T12:48:55+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-08-06T02:45:18+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-07-30T04:50:35+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-07-29T10:23:36+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Activity, Sedentary and Sleep Behaviors","date":"2025-07-25T14:38:41+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-activity-sedentary-and-sleep-behaviors","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jassb","sideBox":"Learn more about [Journal of Activity, Sedentary and Sleep Behaviors](https://jassb.biomedcentral.com/)","snPcode":"44167","submissionUrl":"https://submission.nature.com/new-submission/44167/3","title":"Journal of Activity, Sedentary and Sleep Behaviors","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"1a33d555-5666-4069-b416-5f3dada6871b","owner":[],"postedDate":"August 11th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-09-24T04:23:48+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-11 10:05:59","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7215360","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7215360","identity":"rs-7215360","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}