The early childhood education and care (ECEC) environment is an important setting for providing children with daily opportunities for movement and music, supporting holistic child development in the early years. To date, there are no studies evaluating the implementation of a holistic programme in the ECEC context in the areas of movement behaviour and motor and musical skills. The main aim is to examine the effectiveness of a holistic movement and music programme on physical activity (PA), sedentary behaviour and sleep, motor skills and musical skills in young children (1-3 years). The secondary aims are to examine the impact of the movement and music programme on the perceptions of the educational community, as well as the barriers and facilitators they perceive in the process of baseline assessment, construction, and implementation of the movement and music programme in their own ECEC community. This cluster-randomised controlled trial (intervention and control groups) with public ECEC centres will be performed over a 24-month period. Baseline measurements will be taken in the first year of the project, and assessments to examine the effectiveness of the programme will take place 12 months after the baseline assessment. For young children the main outcome variables will be: (a) PA, sedentary time, and sleep time; (b) gross and fine motor skills; and (c) musical skills. The secondary outcomes will be: (a) PA and sedentary time during outdoor play and structured PA sessions; (b) play patterns during outdoor free play; and (c) movement and music behaviours after ECEC hours. For families, secondary outcomes will be: (a) perceived barriers and facilitators to PA in young children; (b) perceived barriers and facilitators to the inclusion of music at home; and (c) the means of transport to ECEC settings and barriers to active commuting. For ECEC educators, the secondary will be: (a) perceived barriers and facilitators for the inclusion of movement and music as curricular practices in the ECEC institution; (b) perceived impact of the implementation of the movement and music programme. This research project aims to fill a knowledge gap during a period of childhood that has rarely been explored, either nationally or internationally (1-3 years), and to position movement and music teaching practices as key contexts in the curriculum development of infant and toddler education.
Rheumatoid Arthritis (RA), an autoimmune systemic inflammatory disease, affects more than 17 million people globally. People with RA have higher risk of premature mortality; often experience chronic fatigue, pain and disrupted sleep; and are less physically active and more sedentary than healthy counterparts. It remains unclear how people with RA may balance sleep and awake movement activities over 24-hours, or how differences in 24-hour behaviours may be associated with determinants of health, or alignment with published activity guidelines. Cross-sectional exploration of objective measures of 24-hour sleep-wake activities in 203 people with RA. Latent Class Analysis (LCA) derived classes from time, by tertile, in six sleep-awake activities over 24 h. Comparisons of model fit statistics, class separation and interpretability defined best fit for number of classes. Variations in sleep-awake behaviour across classes and association of profile allocation with determinants of health, quality metrics for sleep, sitting and walking and alignment with published guidelines were explored. Multinomial logistic regression identified factors associated with likelihood of profile allocation. LCA identified 2 to 6 classes and a 4-class model was determined as best fit for 24-hour sleep-awake behaviour profiles. One profile (26%) presented with more balanced 24-hour sleep, sitting and walking behaviours. The other three profiles demonstrated progressively less balanced 24-hour behaviours including: having low (< 7 h), high (> 8 h), or recommended (7-8 h) sleep duration in respective combination with high sitting (> 10 h), limited walking (< 3 h) or both when awake. Age, existing sitting and walking habit strength and fatigue were associated with likelihood of belonging to different profiles. More balanced 24-hour behaviour was aligned with better quality metrics for sleep, sitting and walking and published guidelines. For people living with RA it is important to understand the 'whole person' and their 'whole day' to define who may benefit from support to modify 24-hour sleep-awake behaviours and which behaviours to modify. Supports should be informed by an understanding of personal or health-related factors that could act as barriers or facilitators for behavioural change, including exploring existing habitual sitting and walking behaviours. ClinicalTrials.gov ID: NCT02554474 (2015-09-16) and ClinicalTrials.gov ID: NCT03404245 (2018-01-11).
People living with severe mental illness (SMI) face significant health inequalities, including reduced quality of life and life expectancy. Evidence has shown that people living with SMI are highly sedentary, face challenges when seeking to engage in physical activity (PA), and experience sleep difficulties. Motivation, mood and energy have been identified as critical determinants of these behaviours. PA and sleep are traditionally measured in isolation using quantitative approaches, limiting our understanding of the contexts and interactive ways in which these occur, especially for this population. Here, we adopted a flexible and holistic approach, using audio diaries to explore the usability and acceptability of capturing movement behaviours in people living with SMI. This study employed a qualitative design. Data were collected with 10 participants self-identifying as living with SMI, who completed 7-days of audio diaries, pre and post diary use interviews. Reflexive thematic analysis was used to analyse participants' movement behaviours and their experiences of using the audio diaries. Audio diaries were perceived as acceptable to participants and their use for data capture was feasible, with participants experiencing their use as a flexible and empowering method of data capture. Within the exploratory data generated we identified four themes relating to participants' movement behaviours: finding themselves in a "vicious circle" with physical and mental issues impacting movement behaviours; a daily internal fight and dialogue concerning fear of feeling guilty and wasting time; a determination to "not let fatigue win" by pushing through the day; and the mixed effects of understanding the importance of movement behaviours yet finding it challenging to engage. Audio diaries offered an easy to use and relatively inclusive means of exploring movement behaviours for people living with SMI, especially their context and interrelated nature. Our findings reinforced the well-established link between mental and physical health, and their influence on 24 h movement behaviours, identifying population-specific challenges derived from medication side effects, rigid engagement opportunities, and illness symptoms. Given this, co-production involving individuals with lived experience is crucial for developing tailored recommendations and support to promote sleep and movement among those living with SMI. We emphasized the need for holistic measurement approaches and opportunities that consider the interconnected impact of disrupted sleep and movement.
Children aged 6 to 17 spend long periods of sitting at school. Reducing these behaviors and increasing physical activity has been linked to improvements in cognitive functions and decreased musculoskeletal issues. The purpose of this scoping review was to describe interventions implementing flexible learning spaces, active breaks, and active lessons and their effects on sedentary behaviors as well as on physical activity, learning, and musculoskeletal health. A search on databases (EDUCATION SOURCE, ERIC, SPORTDISCUS, MEDLINE, EMBASE, and WEB OF SCIENCE) was carried out in April 2021 and updated in June 2022 according to the guidelines of the "PRISMA-ScR". Studies on flexible learning spaces and physical activity in elementary and secondary school classes were retained. These also had to measure the effects of the interventions on sedentary behaviors, physical activity, learning (e.g., academic achievement), and musculoskeletal health outcomes. Ninety-two articles were identified; twenty-four from the initial screening, thirty-two from the update, and thirty-six were manually included. Among these 92 articles, twenty-one studies used only flexible learning spaces, twenty-three used only active breaks, thirty-six used only active lessons, four used both flexible learning spaces and active breaks separately in different classes, five combined active breaks and active lessons, and three combined flexible learning spaces and active breaks. Analyses show positive changes in sedentary behaviors (32 articles/40) and physical activity (52 articles/74) including sitting time, sit-to-stand transitions, number of steps, and moderate-to-vigorous physical activity. Positive effects were also observed on learning (13 articles/26) or musculoskeletal health outcomes (3 articles/8). Although many studies found no effect of these interventions, no studies report harmful interventions on these variables. The most effective strategy to reduce sedentary behaviors seems to be flexible learning spaces with adapted teaching approaches. Results indicate that flexible learning spaces, active breaks, and active lessons effectively reduce sedentary behaviors and increase physical activity without negatively influencing academic achievement. Further studies are needed to understand better the effects of combining these interventions and their effects on children's learning and musculoskeletal health outcomes.
Despite the established evidence that physical activity, sedentary behavior, and sleep affect cognitive function individually, less is known about the combined effects of these movement behaviors. The study aimed to identify movement patterns of physical activity, sitting time, and sleep and to examine the association of movement patterns with cognitive function. This cross-sectional study included 1,240 participants aged ≥ 55 years participating in the Cooper Center Longitudinal Study who visited the Cooper Clinic, Dallas (2016-2019) for preventive health care. Four movement behaviors were self-reported, including leisure-time aerobic activity, muscle-strengthening activity, sitting time, sleep, and other characteristics. Cognitive function was assessed by the Montreal Cognitive Assessment (MoCA). Four categorical indicators were created for each movement behavior and used to identify latent classes. Information criterion, scaled relative entropy and model interpretability were used to determine the optimal number of classes. Participants were assigned to the predicted classes based on their highest posterior probabilities. Multinomial regressions examined the association between movement patterns and each covariate. Linear and logistic regression models examined the association of movement patterns and cognitive function. A sensitivity analysis accounted for misclassification errors. Participants were predominantly White (95%), male (71%), with an average age of 62 years. A 3-class model was selected, comprising class 1: active long sleepers, class 2: very active short sleepers, and class 3: moderately active short sleepers, representing 11%, 62%, and 27% of the sample. Compared to class 2, class 1 was more likely to be older and female, while class 3 was more likely to be female, have less education, be overweight and obese, and have chronic conditions. Compared to class 2, class 3 was associated with a lower MoCA total score, adjusting for sociodemographic factors. There were no differences in MoCA total score between class 2 and class 3 when further controlling for health behaviors and indicators. Sensitivity analysis accounting for misclassification suggested that class 3 had a significantly lower average MoCA total score than class 2. The current study identified three distinct movement classes that exhibited different sociodemographic, health characteristics and cognitive functions. Findings highlight that less active, more sedentary, and shorter sleep individuals had worse cognitive function.
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.
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 other non-rSST 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% female; 78% White; BMI [M ± SD: 29.8 ± 7.8] kg/m2). Greater total rSST was significantly associated with less other-SED (between-person b =  - 45.0, SE = 4.4, p < 0.01; within-person b =  - 44.5, SE = 2.0, p < 0.01). Similar results were observed when examining both daytime and evening rSST with other-SED. Negative associations were also observed between other-SED, STAND, LPA, and MVPA with rSST variables. No significant associations were observed between rSST variables and SLEEP. This is the first known analysis of the bidirectional relationship between rSST and 24-h behaviors. The negative association between rSST and other-SED suggests that rSST may displace rather than contribute to more cumulative sedentary time. These findings advocate that contexts of sedentary behavior should be considered as distinct behavioral targets in intervention development. Future interventions targeting rSST reduction should also include strategies to reduce total sedentary time. NCT04464993.
Researchers have adopted a variety of analytical techniques to examine the collective influence of 24-h movement behaviors (i.e., physical activity, sedentary behaviors, sleep) on mental health, but efforts to synthesize this growing body of literature have been limited to studies of children and youth. This systematic review investigated how combinations of 24-h movement behaviors relate to indicators of mental ill-being and well-being across the lifespan. A systematic search of MEDLINE, PsycINFO, Embase, and SPORTDiscus was conducted. Studies were included if they reported all three movement behaviors; an indicator of mental ill-being or well-being; and were published in English after January 2009. Samples of both clinical and non-clinical populations were included. A total of 73 studies (n = 58 cross-sectional; n = 15 longitudinal) met our inclusion criteria, of which 47 investigated children/youth and 26 investigated adults. Seven analytical approaches were used: guideline adherence (total and specific combinations), movement compositions, isotemporal substitution, profile/cluster analyses, the Goldilocks method and rest-activity rhythmicity. More associations were reported for indicators of mental ill-being (n = 127 for children/youth; n = 53 for adults) than well-being (n = 54 for children/youth; n = 26 for adults). Across the lifespan, favorable benefits were most consistently observed for indicators of mental well-being and ill-being when all three components of the 24-h movement guidelines were met. Movement compositions were more often associated with indicators of mental health for children and youth than adults. Beneficial associations were consistently observed for indicators of mental health when sedentary behavior was replaced with sleep or physical activity. Other analytic approaches indicated that engaging in healthier and more consistent patterns of movement behaviors (emphasizing adequate sleep, maximizing physical activity, minimizing sedentary behaviors) were associated with better mental health. Favorable associations were reported less often in longitudinal studies. Collectively, these findings provide further support for adopting an integrative whole day approach to promote mental well-being and prevent and manage mental ill-being over the status quo of focusing on these behaviors in isolation. This literature, however, is still emerging-for adults in particular-and more longitudinal work is required to make stronger inferences.
BACKGROUND: Sleep, physical activity, and diet are key determinants of health, each independently associated with chronic disease risk and mortality. These behaviors also interact: insufficient sleep can impair physical activity and dietary choices, while regular exercise and healthy diet promote better sleep. Although lifestyle interventions commonly target physical activity and diet, few simultaneously address sleep. Emerging evidence suggests that even small improvements across all three behaviors can reduce all-cause mortality, highlighting the potential of multi-behavior approaches. However, the effects of a lifestyle intervention simultaneously targeting sleep, physical activity, and diet on quality of life and physical activity levels in inactive adults remain largely unexplored. METHODS: The SPIRAL+ study is a single-center, randomized controlled trial conducted in France, among non-exercising adults aged 18–80 years. Participants (n = 201) will be randomized to one of three groups: (1) lifestyle intervention (physical activity and diet) (2), lifestyle plus sleep intervention, or (3) control. Assessments will be conducted at baseline, 6 months (post-intervention), and 12 months. The primary outcomes are health-related quality of life (EQ-5D-5 L) and daily step count (measured by accelerometer) assessed immediately after the 6-month intervention. Secondary outcomes include whether intervention effects are sustained at 12 months, along with markers of physical fitness (cardiorespiratory fitness, body composition, handgrip strength), physical activity and sedentary behavior (accelerometry), and sleep (home-based sleep test, actigraphy, and validated questionnaires). Additional self-reported outcomes will cover diet, mental wellbeing, motivation, quality of life, and psychological constructs related to health behavior change. A qualitative component will explore barriers and facilitators to adherence through semi-structured interviews. DISCUSSION: This trial will evaluate whether adding a sleep component to a lifestyle intervention improves quality of life and physical activity levels in inactive adults. If effective, the findings will support the integration of sleep into multi-behavior interventions to enhance health outcomes and inform future public health strategies. TRIAL REGISTRATION: Clinical Trials NCT06424847.
Steatotic liver disease (SLD) is a prevalent metabolic disease. While single component movement behaviors have been related to its development, comprehensive assessments of their joint associations are scarce. To investigate the single-component and multi-component associations of moderate and vigorous physical activity (MVPA), light physical activity (LPA), sedentary behavior (SB), and sleep with prevalent SLD in Brazilian adults. A cross-sectional analysis using data from the third wave of the ELSA-Brasil cohort (2017-2019). Participants wore an ActiGraph wGT3X-BT in the waist for seven days and completed a sleep diary. SLD was defined by a Fatty Liver Index ≥ 60. To investigate single-component and multi-component associations, we used three exposure modeling approaches based on Poisson models: multivariable-adjusted regression, restricted cubic splines, and compositional data analysis. Among 8569 participants (55.7% women, mean age 59.2 ± 8.60), 43.9% had SLD. Total activity volume adjusted for covariates was inversely associated with prevalent SLD. Every 1 mg/day increase in total activity volume was associated with a PR of 0.95 in individuals sleeping < 7 h/day (95% CI 0.94-0.97) and 0.95 (95% CI 0.93-0.96) in those sleeping ≥ 7 h/day. Increasing 30 min/day of MVPA was associated with decreasing prevalence of SLD (sleep ≥ 7 h/day [PR 0.83; 95% CI 0.77-0.89]; sleep ≥ 7 h/day [PR 0.78; 95% CI 0.74-0.83]). Sleep, SB, and LPA were not associated with SLD. Associations of total activity volume and MVPA were more pronounced among females. Adjustment with adiposity markers attenuated the associations. In adults, total activity volume and MVPA were inversely associated with SLD in a dose-response fashion. Substituting lower-intensity behaviors with MVPA was associated with a lower prevalence of SLD independent of sleep duration, sex, and age.
Childhood is a critical period for the development of movement behaviours such as physical activity, sleep and sedentary behaviour. The PLAYCE Cohort was established to investigate how movement behaviours change over early to middle childhood, across key behaviour settings and relationships with health and development. An overview of the PLAYCE cohort, summary of key findings to date, and future research opportunities are presented. Children were recruited at 2-5 years of age (preschool; Wave 1) via early childhood education and care (ECEC) services and were followed up in junior primary school (5-7 years; Wave 2) at 8-10 years (Wave 3) and again at 11-13 years (Wave 4; in progress). Children's movement behaviours were measured via parent-report and accelerometry. Social-emotional development, motor development, weight status, diet, and child and family socio-demographics were parent-reported. Physical environmental features of children's key behaviour settings (home, neighbourhood, ECEC and school) were collected using geo-spatial and audit data. At wave 1 (2-5 years), only 8% of children met all three recommendations of the Australian 24-hour Movement Guidelines for the Early Years. Meeting all recommendations (8%) was positively associated with boys social-emotional development. Physical environment features of the home yard (size, play equipment, natural features) were positively associated with preschool children's physical activity. Tree canopy and more portable play equipment in ECEC outdoor areas was also positively associated with children's outdoor time and physical activity. Wave 4 (11-13 years) data collection will be completed in early 2026. Traditional longitudinal and compositional data analysis of the PLAYCE cohort will be undertaken. Four waves of data will provide detailed patterns of movement behaviours and their effect on child health and development as well as the environmental influences on children's movement behaviours across early to middle childhood. The findings can be used to inform national and international 24-Hour Movement Guidelines and behaviour setting-specific as well as population-level interventions to benefit child health and wellbeing across early to middle childhood.
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% female at baseline, 5.2% overweight or obese). At baseline, children spent on average 418.7 min/day inactive, 252.6 min/day in MVPA, and 480 min/day asleep, with a SE of 80%. The results indicated relevant associations of LPA, MVPA, or TPA with SED, SE, or TST, but no association of PA variables and SDQ. Given the rapid developmental changes in early childhood, it is essential to track 24-hour movement behaviors, and mental health over time using device-based measures to better inform strategies that promote lifelong physical and mental wellbeing. Future multi-component interventions should be explored to determine potential synergistic benefits for mental health.
To evaluate the association between sedentary behavior (SB), moderate to vigorous physical activity (MVPA), and sleep duration. Data from the 2017-2018 National Health and Nutrition Examination Survey (NHANES) was analyzed. SB was assessed based on the average daily sitting time, while MVPA was estimated by the frequency and duration of leisure and work-related activities. The ratio of time spent in MVPA to time in SB was analyzed, and a thresholds of ≥ 1.0, 2.5 and 10 min of MVPA per sedentary hour was used to determine sufficiency for mitigating the effects of a sedentary lifestyle. Sleep duration was measured by the average hours slept on weekdays and weekends, classified according to National Sleep Foundation guidelines. The measures of SB, MVPA, and sleep were self-reported. Descriptive statistics were used to characterize the sample, and multivariate logistic regression was applied to assess the associations between movement behaviors and sleep duration. The study included 5,533 participants, with 51.8% women, predominantly aged 26-64 years (66.1%). Insufficient physical activity was reported by 59.6% at work and 62.5% during leisure time. Recommended sleep duration was observed in 84.4% of the sample. Adjusted multivariate analysis revealed that individuals engaging in ≥ 2.5 min of MVPA during leisure-time for each sedentary hour were 38.9% less likely to experience short-term sleep (OR:0.72;95%CI:0.53-0.97). Conversely, those who performed the same amount of MVPA at work were 57.0% more likely to have short-term sleep (OR:1.57;95%CI:1.16-2.12). Meeting the MVPA threshold during leisure-time reduces the likelihood of short-term sleep, while higher MVPA levels at work increase the likelihood of short-term sleep.
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.
Comprehensive assessment of 24-hour movement profiles can reveal patterns of physical activity, sedentary behavior, and sleep across pregnancy. To fully capture sleep health, assessments should combine subjective measures (e.g. sleep diaries) with objective wearable data. However, collecting such data throughout pregnancy can be burdensome. This study evaluated the feasibility and acceptability of using a research-grade accelerometer and daily sleep diaries longitudinally. Ten pregnant individuals were recruited at 10 weeks' gestation and followed until 35 weeks. Participants wore the ActiGraph CentrePoint Insight accelerometer continuously and completed daily sleep diaries one week per month. Feasibility was based on adherence (≥ 4 valid accelerometer wear days ≥ 10 h/day and ≥ 4 completed diaries per week). Acceptability was evaluated via participant-reported ease of use and comfort with the accelerometer and sleep diaries in a feedback questionnaire at 35 weeks. Nine participants provided ≥ 4 valid accelerometer days per week for a mean of 15 weeks (range: 10-23; median: 15). Ten participants completed ≥ 4 days of text-based sleep diaries during assigned diary weeks for a mean of 5 months (range: 3-6, median: 6). Most (78%) found the sleep diaries easy to respond to and the watch comfortable, though several described the band as bulky. One-third (n = 3) experienced device issues, partially resolved through troubleshooting or replacement. Longitudinal 24-hour movement assessment using research-grade accelerometers paired with daily sleep diaries was feasible and acceptable for 90% of participants, though technical issues reduced wear time. Future studies should address comfort, anticipate device problems, and use reminders and text-based diaries to improve adherence.
The retirement transition provides a window of opportunity for the optimization of activity, sedentary and sleep behaviors. Identifying groups at risk for non-favorable changes is important in this matter. There are indications that lower socio-economic position (SEP) adults might be more prone to non-favorable changes. However, previous studies mainly used self-reported behaviors and only one indicator of SEP. The purpose of the present study was therefore to examine the association of SEP with changes in device-measured physical activity, SB and sleep during the retirement transition in adults in Flanders (Belgium) in a longitudinal study. The behaviors were measured pre-retirement and at three, six and twelve months post-retirement with a wrist-worn accelerometer (n = 96). The raw acceleration data were processed using the R package GGIR and analysed using compositional data analysis in linear mixed models including the SEP indicators education, occupation and income. Additionally, changes in intensity gradient and average acceleration were examined. The results showed that on average, physical activity was stable, sleep increased (+ 18 min) and SB decreased (- 15 min). The intensity gradient and average acceleration did not change significantly. The higher income group had significantly more favorable changes in movement behaviors compared to the lower income group. More specifically, they increased physical activity and shifted towards more intense physical activity, while the lower income group did not. The higher education and occupation groups showed a non-significant trend towards more favorable changes. The changes occurred mainly between pre-retirement and three months post-retirement and were relatively stable afterwards. The behaviors shifted towards more healthy behaviors in general, with stable physical activity, a decrease in SB and an increase in sleep. The changes in the behaviors were more favorable for retirees with higher SEP compared to retirees with lower lower socio-economic position. There seems to be a need for strategies to improve 24-h movement behaviors of lower SEP adults during the retirement transition. However, our results are based on a small sample and should be validated in larger studies.
The transition to college coincides with the peak age of onset for depression and is marked by substantial changes in 24-hour movement behaviors (sleep, sedentary behavior, physical activity). Although these behaviors are modifiable and increasingly implicated in depression risk, most studies rely on cross-sectional, self-reported data and aggregate symptom scores, limiting insight into temporal dynamics and symptom-level heterogeneity. Integrating compositional modeling of 24-hour time use data with network approaches to psychopathology may clarify when and how specific behavioral patterns relate to distinct depressive symptoms during this high-risk developmental window. The College Adjustment, Lifestyle and Mental health (CALM) Study is a 16-week prospective cohort study of 144 first-year undergraduate students (Mage = 18.2 ± 0.4 years; 54.9% female) during their first academic semester. A hybrid panel-burst design combined five monthly panel surveys assessing psychosocial and behavioral factors with five 7-day intensive daily diary assessment bursts distributed across a 108-day period. During each burst, participants completed daily diary adaptations of the PHQ-8 and GAD-7 to capture depressive and anxiety symptoms, along with other contextual variables. Sleep, sedentary behavior, light physical activity, and moderate-to-vigorous physical activity were assessed daily using Fitbit Charge 6 devices. Primary analyses will model daily 24-hour movement behaviors using compositional data analysis to account for the constrained nature of time-use data and integrate these compositions into multilevel vector autoregressive models to estimate within-person temporal, contemporaneous, and between-person associations with individual depressive and anxiety symptoms. Secondary analyses will examine symptom-behavior network differences across movement behavior profiles and assess stability of symptom-behavior networks across the first college term to identify periods of heightened risk for symptom onset and progression. By embedding wearable-derived 24-hour movement behavior compositions within dynamic symptom networks, this study advances precision behavioral psychiatry beyond aggregate depression scores by identifying which behaviors are most strongly linked to specific symptoms, for whom these associations differ, and when risk intensifies during the transition to college. The hybrid panel-burst design further provides a foundation for future predictive modeling of individual risk trajectories and the development of just-in-time adaptive interventions leveraging passive sensing to support early detection and prevention of depression in emerging adults.
Physical activity is an important component of metabolic health. However, little is known about the impact of specific types/intensities of physical activity on sleep health, especially among ethnically diverse populations. We examined the association of various sleep behaviors with moderate to vigorous work/recreational activity. Self-reported data from the National Health and Nutrition Examination Survey 2015-2020 were cross-sectionally analyzed for a sample of 11,039 participants in the United States (U.S.). Weighted univariate logistic regressions determined unadjusted associations, while weighted multivariable regression models adjusting for age, sex, ethnicity, BMI categories, and socio-economic status assessed the multivariable associations with moderate and vigorous work/recreational activity. Stratified analyses were performed to determine across-group differences by ethnicity and BMI categories. Of 11,039 adults (mean age 41 years), 50.7% were female, 59.8% were Non-Hispanic White, 17.8% Hispanic/Latino, 12% Non-Hispanic Black, 6.3% Non-Hispanic Asian, and 4.1% other/multiple ethnicities. Moderate work activity increased the odds of short sleep duration [aOR = 1.42; 95% CI: 1.22, 1.65], snoring [aOR = 1.45; 95% CI: 1.21, 1.73], breath cessation [aOR = 1.37; 95% CI: 1.18, 1.59], and daytime sleepiness [aOR = 1.63; 95% CI: 1.39, 1.91]. Vigorous recreational activity reduced the odds of short sleep duration [aOR = 0.81; 95% CI: 0.71, 0.94] and trouble sleeping [aOR = 0.83; 95% CI: 0.73, 0.96]. Stratified analyses indicated significant ethnicity-based differences in the odds of sleep behaviors across physical activity groups and increased odds of poor sleep behaviors among participants who were underweight, overweight or had obesity. Work-related activity was significantly associated with suboptimal sleep behaviors while recreational activity was associated with favorable sleep behaviors. These associations were more pronounced among certain ethnic groups. Further longitudinal investigation is needed to examine the mechanism driving the relationship between sleep behaviors and physical activity.
Brief measures of 24-hour movement behaviors are needed to easily evaluate their durations. The present study investigated the criterion validity and test-retest reliability of a brief self-report instrument to assess 24-hour movement behaviors. A paper-based self-administered questionnaire was used to assess sleep, sedentary behavior (SB), light-intensity physical activity (LPA), and moderate-to-vigorous physical activity (MVPA) with four items in 35 healthy adults. Participants wore a tri-axial accelerometer and answered the questionnaire on the final day of the accelerometry assessment and after 14 days. Spearman's correlations of self-reported measures with their accelerometer-derived counterparts were assessed and median values compared using Mann-Whitney U-tests. Bland-Altman plots were employed to characterize differences in self-reported and device-measured time in the behaviors and their limits of agreement. Test-retest reliability was assessed using Intra-class correlation coefficients (ICCs). Moderate correlations with device measures for sleep, SB, and LPA for a typical and the past week (rho = 0.46 to 0.60, respectively) and low correlations for MVPA (rho = 0.33 to 0.47, respectively) were observed. Less duration of sleep and MVPA were reported compared with accelerometer-derived durations for the three recall periods (z = -3.9 to -2.5 and -4.0 to -3.5, respectively). The test-retest reliability for a typical week was fair-to-good or excellent for all the four behaviors (ICCs = 0.72-0.90). Findings show acceptable validity and reliability of this questionnaire measure of 24-hour movement behaviors for typical week, past week, and previous day recall periods.
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.