Despite adverse neighborhood effects on sleep, the underlying behavioral factors linking this association remain uncertain. This study aimed to (1) evaluate whether physical activity (PA) and sedentary behavior (SB) mediate associations between neighborhood socioeconomic status (nSES) and sleep, and (2) explore whether PA- and SB-mediated associations vary by racial and/or ethnic groups. Data came from the NIH-AARP Diet and Health Study (n=233,335). Self-reported sleep outcomes included: short sleep (< 7 h [h] versus 7–8 h), long sleep (≥ 9 h versus 7–8 h), and long napping (≥ 1 h versus <1 h). A standardized nSES was derived from census variables. Primary cross-sectional mediation analyses for self-reported moderate-to-vigorous PA (MVPA) and SB (television [TV] viewing) were conducted using linear regression with bootstrap-generated 95
Engaging in high volumes of sedentary behaviour increases the risk of adverse health outcomes, especially for individuals with Type 2 diabetes mellitus (T2DM). Understanding likely influences on behaviour and effective strategies for reducing sedentary time, as explored in this study, can inform future intervention development and implementation. A randomised controlled feasibility trial was undertaken to evaluate a remotely delivered sedentary behaviour intervention in adults with T2DM. As part of the process evaluation, intervention participants (n = 35) were asked to report the barriers they experienced, and strategies adopted, in their efforts to reduce sitting time. Using template analysis, 44 statements of barriers (from n = 18) and 99 statements of attempted behaviour change strategies (from n = 17) from two time periods were analysed. Themes were similar across 3- and 6-month data for barriers [fatigue/sleep (e.g., feeling drowsy), disability/health, work-related (e.g., work tasks and facilities), and context (social or environmental contextual barriers)]. The themes for strategies reflected behaviours associated with ways to break up sitting, increasing incidental physical activity, and adding in purposeful physical activity. Barriers reflected various individual and contextual factors, while change strategies centred on breaking up sitting through substitution of other behaviours and the use of different types of physical activity. Such information may prove useful in future interventions to reduce sedentary behaviour.
Surveillance of children’s sleep, physical activity (PA), and sedentary behaviour is a cornerstone of movement behaviour and health research, providing key information for guiding future health promotion policies, programs, and services. Systematic monitoring of these behaviours in preschool-aged children is lacking, particularly for certain sub-groups (males/females, urban/rural areas). This cross-sectional study aimed to assess the prevalence of 3- to 4-year-old children across five Canadian provinces meeting the 24-Hour Movement Guidelines for the Early Years, while examining associations with sex, age, and urban/rural location. Sleep and PA data were collected for 7 continuous days using waist-worn ActiGraph wGT3X+ accelerometers. Sleep duration was also gathered from parent reports, as were sedentary behaviour measures (screen and restrained time). Children were classified as meeting guidelines if they accumulated 10–13 h/day of sleep, ≥ 180 min/day of total PA (TPA), including ≥ 60 min/day of moderate-to-vigorous-intensity PA (MVPA), ≤ 1 h/day of screen time, and ≤ 1 h of restrained sedentary bouts. Within the final sample (n = 631), 29.0
Prior research examining sedentary time and cognitive function has produced mixed findings with limited attention to specific types of sedentary behavior. This cross-sectional study tested the hypothesis that more cognitively active sedentary behaviors (playing video games, internet use, and reading) are positively associated with cognitive performance, in contrast to cognitively passive sedentary behavior (watching television). Data from 3,943 participants (aged 46–48; 53.3
Understanding how 24-h movement behaviors (i.e., physical activity, sedentary behavior, sleep) differ among children with developmental disabilities (e.g., delays, disorders, disabilities) is crucial, with evidence indicating that variations seen in older children may begin to emerge in early childhood. However, reviews have not acknowledged such developmental considerations in young participants. Therefore, a scoping review of the growing body of research focused on preschool-aged children is essential for gaining deeper insights into how these behaviors evolve and differ during this critical period. This scoping review aimed to (1) identify 24-h movement behavior levels in preschool-aged children with developmental disabilities, (2) determine whether 24-h movement behaviors differed between children with and without developmental disabilities, and (3) determine if 24-h movement behaviors varied by the domain of developmental difference. We conducted a systematic search in nine databases. Inclusion criteria were: (1) children between 33 and 72 months, (2) inclusion of children with developmental disabilities in the sample, (3) measures of at least two movement behaviors, (4) written in English, and (5) empirical, original research designs. The date of publication was unrestrained. Title/abstract and full text screening were completed by two independent reviewers. The date of publication was unrestrained. Twenty predominantly cross-sectional articles published between 2004 and 2024 were included. Studies examined movement behaviors across various developmental domains such as autism spectrum disorder, cerebral palsy, and developmental coordination disorder. Findings on sleep, sedentary behavior, and physical activity were mixed, with some studies reporting significant group differences while others found no or inconsistent group differences. This review highlights the variability and gaps in current research on movement behaviors among children with developmental disabilities, underscoring the need for more comprehensive and consistent measurements that consider all 24-h movement behaviors to better inform targeted interventions.
Public health research and practice are shifting towards integrative consideration of physical activity (PA), sedentary behaviour (SB), and sleep, as interdependent components of daily time use. However, no previous reviews have synthesised evidence on economic costs associated with these movement behaviours. The aim of this systematic review was to synthesise evidence on economic costs of insufficient PA, excessive SB, and inadequate sleep duration. Literature searches were conducted in Open Dissertations, PsycINFO, PubMed/MEDLINE, Scopus, SPORTDiscus, and Web of Science. Publications that provided estimates of total, direct, or indirect monetary cost of any of the three behaviours in the general adult population were included. Out of 21,418 screened references, 40 papers met the inclusion criteria (77.5
As flexible work arrangements (FWAs) become more common among office workers, the challenge of maintaining a healthy balance between work and recovery increases. However, studies addressing workplace interventions to promote recovery in FWAs are sparse. This study examined the effects of a co-created workplace intervention on the 24-hour composition of physical behaviors and recovery during sleep among office workers with FWAs. A controlled intervention study was performed in a large governmental organization offering FWAs. Office workers from one unit (n = 27) participated in, (1) an individual-level course on work strategies and (2) a workgroup-level workshop to develop common rules and routines for FWAs. These activities were expected to reduce work demands, facilitate detachment after work, and promote healthier 24-hour physical behavior patterns and improve recovery during sleep. Employees from a comparable unit were included as a control group working as usual (n = 21). Physical behaviors at baseline and at a 12-month follow-up were assessed in both groups using 24-hour accelerometry for three days, together with heart rate variability indicators of recovery during sleep. We calculated time used in physical activity, inactivity and sleep in a Compositional data analysis framework, and analyzed intervention effects on these behaviors and heart rate variability indicators using repeated-measures MANOVA. The intervention led to, on average, 36 min more sleep per night, compared to 23 min less sleep in the control group, and the effect size was large (F = 10.87, p < 0.01, ηₚ² = 0.28). The intervention had limited effects on physical activity relative to inactivity, and on heart rate variability during sleep (interaction between time and group: p > 0.05). An intervention combining intervention activities at the individual and workgroup levels led to longer sleep time, indicating a behavioral effect that may promote recovery and health. The intervention did not, however, affect physical activity behaviors while awake, or heart rate variability indicators of recovery during sleep. These findings suggest that interventions targeting individual and collective work practices may influence physical behaviors and recovery. Further studies are needed to examine long-term effects in other groups of workers with flexible work.
Sleep, sedentary behaviors (SB) and physical activity are independently associated with cognitive function in older adults, yet the joint relationship of these 24-hour movement behaviors with cognitive function is less well studied. Additionally, the association between SB and cognitive function may differ depending on whether SB is mentally active or inactive. This study aimed to examine the associations between 24-hour movement behavior compositions and cognitive function in older adults, explore the differential associations of different sedentary behavior (SB) types with cognitive function, and assess the predicted cognitive differences associated with time reallocation among these behaviors. Data were drawn from 2516 US adults aged ≥ 60 years in the 2011–2014 National Health and Nutrition Examination Survey. Sleep, total SB, light physical activity (LPA), and moderate-to-vigorous physical activity (MVPA) were all assessed via wrist-worn accelerometry. Total SB was disaggregated into TV watching (inactive SB), computer use (active SB), and other SB using individual proportional weights derived from the Global Physical Activity Questionnaire (GPAQ). Cognitive function was evaluated using the Consortium to Establish a Registry for Alzheimer’s Disease Word Learning (memory), Animal Fluency (language), and Digit Symbol Substitution (executive function) tests. Standardized scores were combined into a global cognition score. Weighted compositional linear regression and isotemporal substitution models were applied. In the 4-component model, greater relative time in MVPA and total SB were positively associated with global cognition (β = 0.191 and β = 0.260, respectively; both P ≤ 0.001), whereas relative sleep and LPA were negatively associated with global cognition. In the 6-component model, disaggregating total SB revealed divergent associations: computer use was positively associated with all cognitive domains (global: β = 0.045, P < 0.001), while TV watching was negatively associated with global cognition (β=−0.050, P = 0.047) and language. Notably, neither “other SB” nor sleep remained significantly associated with cognition in this expanded model. Isotemporal substitution analyses indicated that reallocating time to MVPA or computer use was associated with predicted higher global cognition scores, revealing a pronounced asymmetric trajectory where reducing these behaviors predicted steep cognitive declines. Engaging in MVPA or mentally active SB may help preserve cognitive function in older adults, whereas mentally inactive SB is associated with poorer cognition. Optimizing 24-hour time use by replacing passive sedentary behaviors with MVPA or cognitively engaging activities represents a promising strategy.
Early childhood is a period of rapid development; research shows that the formation of healthy habits during this period can result in higher physical fitness levels and better sleep, but also long-term improved mental health and wellbeing. Despite structures supporting physical activity (PA) and related behaviours, many German children under 6 years do not achieve the recommended levels of PA, sedentary behaviour (SED), and sleep; this in turn can hinder the formation healthy lifestyle habits in the early years, and also lead to long-term poor mental health, later in life. Thus, this study aimed to explore the associations between device-based measured PA with nighttime sleep, SED, and mental health in German children under six years of age. PA, sleep, and SED were assessed at baseline and 1-year follow-up using wrist-worn GENEActiv accelerometers sampled at 100 Hz. The R-package GGIR (version 3.1.1) was used to derive light-intensity PA (LPA), moderate-to-vigorous-intensity PA (MVPA), total PA (TPA), inactivity (proxy for SED), total night sleep time (TST), and sleep efficiency (SE). Parents answered on children’s mental health using the Strengths and Difficulties Questionnaire (SDQ). Linear mixed models, were used to estimate cross-sectional associations from repeated measures of PA intensities with sleep, SED, and mental health, adjusting for age and sex of the child, parental education, migration background, urbanity, and household income. We investigated 212 children aged 2–6 years (51
Most children in the United States do not meet the recommended daily physical activity (PA) and sleep guidelines. This study described the contribution of after-school programs to children’s daily moderate-to-vigorous PA (MVPA), the prevalence of meeting the U.S. MVPA guidelines (60 min daily), sleep duration (9–12 h daily), and sleep efficiency (≥ 85
While physical activity (PA), sedentary time (ST), and sleep each show individual associations with learning outcomes, their combined associations remain largely unexplored. This cross-sectional study examined the association between the 24-h movement behavior composition and arithmetic and reading fluency in children and adolescents, gender differences in these associations, and theoretical 30‑minute behavior‑change scenarios. Volunteered children (N = 253, mean age: 9.5 ± 0.4 years, 53
Age-related cognitive decline poses challenges to healthy ageing. Physical activity (PA), sedentary behaviour (SB) and sleep have been linked to cognition, yet much evidence is cross-sectional and fails to account for the interdependent nature of these 24-h movement behaviours. This observational study applied a compositional approach to investigate longitudinal associations between 24-h movement behaviours and cognition in cognitively healthy adults. Community-dwelling adults aged ≥ 55 years were assessed at three time points, each one year apart (baseline n = 233; 51.1
Many breast cancer survivors experience persistent symptoms after treatment, impairing quality of life (QoL). At the same time, maintaining healthy levels of 24-hour movement behaviors (24h-MBs) i.e. engaging in 150 min of moderate-to-vigorous physical activity (PA) a week, several hours of light PA a day, limiting sedentary behavior during the day, and achieving restorative sleep, remains challenging. While these behaviors influence QoL individually, little is known about the combined impact of 24h-MBs in breast cancer survivorship. Therefore, this study aimed to 1) examine longitudinal changes in 24h-MBs across 1 week, 4 months, and 12 months post-surgery, 2) compare 24h-MBs of breast cancer survivors at 12-month post-surgery with healthy controls and 3) investigate associations between 24h-MBs and QoL in breast cancer survivors. The 24h-MBs were measured by a hip-worn Actigraph GT3X-BT + , and QoL by the McGill QoL questionnaire at 1 week, 4 months, and 12 months post-surgery. Compositional data analysis was used to account for the time-use interdependence of 24h-MBs. Multivariate linear mixed models assessed longitudinal changes in 24h-MBs, a MANOVA explored the group differences and regressions models examined associations between 24h-MBs and QoL at each timepoint. Results from 184 breast cancer survivors (54 ± 15 y/o) showed that sedentary behavior decreased while light and moderate-to-vigorous PA increased over 12 months (p < 0.001). Compared to 135 healthy women (44 ± 10 y/o), breast cancer survivors at 12 months post-surgery showed 24h-MBs with more sleep (> 9h/night) and less low and moderate-to-vigorous PA (p < 0.001). At 4 months post-surgery, light PA (relatively against the other behaviors) was associated with a better overall QoL, whereas longer sleep duration (relatively against the other behaviors) was associated with a worse overall QoL and less perceived support. No significant associations were found at 1 week and 12 months post-surgery. However, at all three timepoints, the most commonly self-reported impairing symptoms related to their QoL were fatigue, insomnia and pain. Breast cancer survivors gradually improved their 24h-MBs in the first year after surgery, but their 24h-MB profiles remained less favorable than those of healthy controls. More optimal post-surgery 24h-MBs were associated with a better QoL, emphasizing their relevance for recovery.
Due to academic pressures and irregular schedules, university students often face challenges in maintaining healthy movement behaviours (including sleep, physical activity, and screen time), which are interrelated and influence both physical and mental health. Smartwatch- and smartphone-based ecological momentary assessments (EMAs) and ecological momentary interventions (EMIs) offer real-time, context-aware strategies to promote movement behaviours. This pilot study aims to assess the feasibility and preliminary effectiveness of a hybrid approach that combines continuous digital monitoring of movement behaviours with sequentially embedded randomised controlled trials (RCTs) evaluating EMIs. MOVE@NUS pilot study employed a five-month hybrid design that combines continuous passive monitoring (primarily via Apple Watches, supplemented by iPhones) with three embedded RCTs targeting sleep (RCT-1), physical activity (RCT-2), and screen time (RCT-3). For each RCT, participants are randomised on a 1:1:1 schedule (control, intervention 1, intervention 2). Eligible participants are first-year undergraduates at the National University of Singapore, aged 18–25 years, who own or regularly use an iPhone and an Apple Watch. EMIs, delivered via the study app, comprise standard health messages or personalised reminders based on HealthKit data or participants’ self-reported behaviours and preferences. Self-reported measures include eight EMA bursts (three-day periods every two weeks) and online questionnaires at baseline, midway (2.5 months), and endpoint (5 months). All EMIs and EMAs are text-based and can be completed in under two minutes. Feasibility outcomes include recruitment, engagement, and user experience assessed through quantitative surveys and semi-structured interviews. Preliminary effectiveness will be explored separately for each RCT, comparing movement behaviours between intervention and control groups. Findings from this study will inform the development of scalable and longer-term digital intervention cohorts for promoting healthier lifestyles among university students. Furthermore, as university students soon transition to the workforce, insights gained will inform scalable digital health interventions for broader populations. ClinicalTrials.gov ID NCT06597890 First Posted: 19 September 2024.
Although interest in objective screen time measurement is growing, questions remain regarding data processing. The aim of this study was to investigate how different image capture intervals and processing assumptions influence screen time estimates from wearable camera images. Screen time was measured using chest-worn Brinno TLC130 cameras which took static images every two seconds over four days in children participating in a crossover trial manipulating sleep. Images were coded for screen usage and only children with data from the same time block (before school, after school, weekends) during both intervention conditions were included. Analyses compared estimates of screen time using different intervals of image capture (2, 4, 6, 8, 10, 20, 30, 60 s) and processing rules (images with screens only, Rules 1 and 2 which allowed for blocked [device being used not visible in photos] images as long as the surrounding images were coded as screen time). 51 children (51
Establishing early physical activity (PA) habits is vital for long-term health, with parents considered as key influencers on children’s PA. Yet, most previous parent–offspring dyads examining PA associations were cross-sectional, rarely used device-based measures, and often overlooked movement composition. The aim of this study was to determine whether mother’s and father’s waking movement composition is cross-sectionally or longitudinally associated with those of their children. The SOPHYA cohort recruited families from a nation-wide population-based random sample stratified by child’s sex, birth year, and language. All youth aged 6–16 years and their parents officially residing in Switzerland, were eligible. Baseline and follow-up assessment occurred in 2013–2015 and 2019–2020, respectively. Questionnaire information and accelerometer measurements were collected remotely. The main predictor was parental movement composition at baseline. The associations between parental and child movement compositions were examined using Dirichlet regression models, adjusting for child’s age and sex, parental education, and language region. The endpoints were children's movement composition at baseline (cross-sectional) and follow-up (longitudinal), respectively. Baseline assessment provided accelerometer and self-reported covariate data for the same measurement week in 686 mother–child and 373 father-child pairs. Follow-up assessment provided accelerometer data for 263 children with maternal and 149 with paternal baseline data. Cross-sectionally, replacing parental sedentary behaviour (SB) with moderate-to-vigorous activity (MVPA) (mothers: 0.10, p < 0.001; fathers: 0.09, p = 0.002) or replacing SB with light physical activity (LPA) (mothers: 0.13; < 0.001; fathers: 0.09; p < 0.005) was associated with similar, but smaller shifts in children. Longitudinally, replacing parental SB with LPA was associated with similar, but smaller shifts in children five years later (mothers: coefficient: 0.12, p = 0.021; fathers: coefficient: 0.10, p = 0.108). The cross-sectional change in children’s LPA/SB ratio predicted from a parent’s 20
Recreational sedentary screen time (rSST) is the most prevalent form of discretionary sedentary behavior and is strongly linked to poor health outcomes. However, the relationship between time spent in rSST and other 24-h behaviors is not well understood. The purpose of this study was to examine between- and within-day associations between rSST and other 24-h behaviors that include non-rSST or other sedentary time (other-SED), standing (STAND), light physical activity (LPA), moderate-to-vigorous physical activity (MVPA), and total sleep (SLEEP). Baseline data from participants randomized to the StandUPTV study, an intervention aimed to reduce rSST in adults, were included. All 24-h behaviors were assessed continuously for 7-days. The activPAL device was used to assess rSST, other-SED, STAND, LPA, and MPVA; SLEEP was assessed using a GENEactiv accelerometer. rSST was collected using Wi-Fi plugs to capture TV time and tablet app usage. A multilevel modelling approach was used to assess bidirectional associations between rSST (total, daytime, evening) and 24-h behaviors at the between-person (across persons) and within-person (across days) levels, adjusting for age, sex, chronotype, education level, and week versus weekend day. The results were scaled hourly for interpretation. On average, 8.0 ± 1.6 days of continuous daily 24-h behavior data were included from 94 participants (age [M ± SD: 42.3 ± 11.5] years; 82
Adolescent psychological wellbeing is a critical determinant of lifelong health. Global data suggest a concerning decline in adolescent wellbeing. While the 24-hour movement behaviours, moderate to vigorous physical activity (MVPA), light physical activity (LPA), sedentary time, and sleep, have been linked to mental health outcomes; their associations with specific domains of adolescent psychological wellbeing remain underexplored. This study used compositional data analysis (CoDA) to examine how time-use relate to domain-specific wellbeing in Australian secondary school adolescents. Data were drawn from 124 adolescents (aged 13–17 years) participating in the TransformUs Secondary effectiveness trial. Wrist worn Actigraph GT9X accelerometer captured 24-hour movement behaviour over at least three valid days (≥ 16 h/day). Wellbeing was assessed using the EPOCH Measure of Adolescent Wellbeing, which includes five domains: engagement, perseverance, optimism, connectedness, and happiness. CoDA was used to examine associations between the composition of daily movement behaviours and EPOCH domains using isometric log-ratio (ILR) transformations. A compositional time reallocation analysis (30-minutes) was also performed to explore hypothetical associations with wellbeing outcomes. The average daily time-use composition was 680.9 min (47.3
Average acceleration (AvAcc) and intensity gradient (IG) are accelerometer metrics which when combined describe the volume and intensity distribution of physical activity, sedentary behaviour, and sleep across the 24-h cycle. Little is known about trajectories of children’s AvAcc and IG over time on weekdays and weekends. This study describes school year trajectories of children’s weekday and weekend AvAcc and IG. During 2023–24 249 children (8–9 years old; 51.4
There is increasing interest in the importance of patterns of accumulation and overall daily time-use composition of physical activity (PA) and sedentary time (SED) for children’s cardiometabolic health. This study examined cross-sectional associations between the time-use composition of PA and SED patterns with cardiometabolic risk factors in 4-year-olds. Data were drawn from the Barwon Infant Study 4-year review (n = 467). Accelerometer data were classified into short (≤ 1-minute) and long (> 1-min) SED, light-, moderate-, and vigorous-intensity PA (LPA, MPA, VPA) bouts. A waking time-use composition of eight distinct components (total volumes plus short and long bouts of SED, LPA MPA, VPA) was constructed using compositional data analysis. Linear mixed models examined associations between composition patterns and body mass index (BMI), percent body fat, triceps and subscapular skinfold thickness, blood pressure, heart rate, carotid-femoral pulse wave velocity, and aortic and carotid intima-media thickness. Adjusted models indicated a higher ratio of long versus short LPA bouts was associated with higher z-BMI (β = 1.69, SE = 0.83, p = 0.04), percent body fat (β = 10.72, SE = 3.71, p = 0.004), and z-triceps (β = 1.90, SE = 0.93, p = 0.04). A higher ratio of long versus short MPA bouts was associated with lower z-BMI (β = − 0.99, SE = 0.46, p = 0.03) and percent body fat (β = − 4.63, SE = 1.93, p = 0.02). A higher total volume of MPA versus VPA was associated with higher percent body fat (β = 4.07, SE = 1.63, p = 0.01) and z-triceps (β = 1.05, SE = 0.43, p = 0.01). Other outcomes showed no associations (p ≥ 0.05). In preschoolers, accumulating LPA in shorter bursts, MPA in longer bursts, and maintaining a higher proportion of VPA may support healthier adiposity profiles. These findings underscore the importance of minimizing prolonged sedentary time and encouraging sustained, high-intensity PA from early childhood.
