BACKGROUND: The distribution of time across physical activity, sedentary behaviors, and sleep appears to be essential for the management of obesity. However, the impact of reallocating time among these behaviors, collectively known as 24-h movement behaviors, remains underexplored. OBJECTIVE: This study examines the theoretical effects of reallocating time between 24-h movement behaviors on obesity indicators across different age groups. METHODS: We performed a pooled data meta-analysis of 9818 participants from 11 observational and experimental studies. To estimate the time spent in movement behaviors, we reprocessed and harmonized individual-level raw accelerometer-derived data. Isotemporal substitution models estimated theoretical changes in body mass index (BMI) and waist circumference (WC) associated with time reallocation between movement behaviors. We performed the analysis separately for children, adolescents, adults, and older adults. RESULTS: Even minor reallocations of 10 min led to significant changes in obesity indicators, with pronounced effects observed when 30 min were reallocated. The most substantial adverse effects on BMI and WC occurred when moderate-to-vigorous physical activity (MVPA) was reallocated to other movement behaviors. For 30-min reallocations, the largest increase in BMI (or BMI z-score for children) occurred when MVPA was reallocated to light-intensity physical activity (LPA) in children (0.26 units, 95% confidence interval [CI] 0.15, 0.37) and to sedentary behavior (SB) in adults (0.72 kg/m2, 95% CI 0.47, 0.96) and older adults (0.73 kg/m2, 95% CI 0.59, 0.87). The largest increase in WC was observed when MVPA was substituted with LPA in adults (2.66 cm, 95% CI 1.42, 3.90) and with SB in older adults (2.43 cm, 95% CI 2.07, 2.79). Conversely, the highest magnitude of the decrease in obesity indicators was observed when SB was substituted with MVPA. Specifically, substituting 30 min of SB with MVPA was associated with a decrease in BMI z-score by - 0.15 units (95% CI - 0.21, - 0.10) in children and lower BMI by - 0.56 kg/m2 (95% CI - 0.74, - 0.39) in adults and by - 0.52 kg/m2 (95% CI - 0.61, - 0.43) in older adults. Reallocating time away from sleep and LPA showed several significant changes but lacked a consistent pattern. While the predicted changes in obesity indicators were generally consistent across age groups, inconsistent findings were observed in adolescents, particularly for reallocations between MVPA and other behaviors. CONCLUSIONS: This investigation emphasizes the crucial role of MVPA in mitigating obesity risk across the lifespan, and the benefit of substituting SB with low-intensity movement behaviors. The distinct patterns observed in adolescents suggest a need for age-specific lifestyle interventions to effectively address obesity. Emphasizing manageable shifts, such as 10-min reallocations, could have significant public health implications, promoting sustainable lifestyle changes that accommodate individuals with diverse needs, including those with severe obesity.

• MeSH
• Accelerometry MeSH
• Time Factors MeSH
• Exercise * MeSH
• Child MeSH
• Adult MeSH
• Body Mass Index MeSH
• Obesity Management * methods   MeSH
• Middle Aged MeSH
• Humans MeSH
• Adolescent MeSH
• Young Adult MeSH
• Obesity * MeSH
• Waist Circumference MeSH
• Sedentary Behavior * MeSH
• Aged MeSH
• Sleep MeSH
• Check Tag
• Child MeSH
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Adolescent MeSH
• Young Adult MeSH
• Male MeSH
• Aged MeSH
• Publication type
• Journal Article MeSH
• Meta-Analysis MeSH

INTRODUCTION: Obesity in older adults is linked to various chronic conditions and decreased quality of life. Traditional physical activity guidelines often overlook the specific postures and movements that older adults engage in daily. This study aims to explore the compositional associations between posture-specific behaviours and obesity risk in younger (M = 67.35 ± 2.03 years) and older (M = 75.73 ± 4.17 years) groups of older adults and investigate the differences in body mass index (BMI) associated with replacing time spent in lying, sitting and standing with moving or walking. METHODS: This cross-sectional study involved 309 older adults aged 65 and above from Czech Republic. Participants' movement behaviours, including lying, sitting, standing, moving, and walking, were measured using accelerometers. The data were analysed using compositional data analysis (CoDA) and isotemporal substitution models to assess the impact of reallocating time between different activities on self-reported (BMI). RESULTS: The younger group engaged in more overall movement (193.84 min/day vs. 172.41 min/day) and walking (92.15 min/day vs. 76.62 min/day) than the older group. Significant estimated increases in BMI were associated with reallocating 30 min from movement to lying, sitting, or standing (up to + 3.31 kg/m²), while reallocating the same amount of time from lying, sitting, or standing to movement was associated with estimated reductions in BMI (up to - 2.54 kg/m²). In the older group, reallocating time from slow walking to lying or sitting was associated with estimated increases in BMI (up to + 1.86 kg/m²), while increasing time spent slow walking at the expense of lying or sitting theoretically reduced BMI (up to - 0.95 kg/m²). CONCLUSIONS: The findings suggest that promoting movement and walking, including both slow and fast walking, may play a role in managing obesity risk in older adults. This study highlights the potential benefits of reducing sedentary time and encouraging low-intensity physical activity tailored to the capabilities of seniors, especially those aged 70+, as a possible strategy to mitigate obesity risk. However, further longitudinal studies are needed to confirm these associations and explore causal relationships.

• Keywords
• backwards pivot coordinates, body mass index, sitting, slow walking, standing,
• MeSH
• Accelerometry methods   MeSH
• Walking * physiology   MeSH
• Body Mass Index MeSH
• Humans MeSH
• Obesity * epidemiology   physiopathology   MeSH
• Posture physiology   MeSH
• Sitting Position * MeSH
• Cross-Sectional Studies MeSH
• Risk Factors MeSH
• Aged, 80 and over MeSH
• Aged MeSH
• Standing Position * MeSH
• Check Tag
• Humans MeSH
• Male MeSH
• Aged, 80 and over MeSH
• Aged MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Geographicals
• Czech Republic epidemiology   MeSH

The distribution of time that people spend in physical activity of various intensities has important health implications. Physical activity (commonly categorised by the intensity into light, moderate and vigorous physical activity), sedentary behaviour and sleep, should not be analysed separately, because they are parts of a time-use composition with a natural constraint of 24 h/day. To find out how are relative reallocations of time between physical activity of various intensities associated with health, herewith we describe compositional scalar-on-function regression and a newly developed compositional functional isotemporal substitution analysis. Physical activity intensity data can be considered as probability density functions, which better reflects the continuous character of their measurement using accelerometers. These probability density functions are characterised by specific properties, such as scale invariance and relative scale, and they are geometrically represented using Bayes spaces with the Hilbert space structure. This makes possible to process them using standard methods of functional data analysis in the L2 space, via centred logratio (clr) transformation. The scalar-on-function regression with clr transformation of the explanatory probability density functions and compositional functional isotemporal substitution analysis were applied to a dataset from a cross-sectional study on adiposity conducted among school-aged children in the Czech Republic. Theoretical reallocations of time to physical activity of higher intensities were found to be associated with larger and more progressive expected decreases in adiposity. We obtained a detailed insight into the dose-response relationship between physical activity intensity and adiposity, which was enabled by using the compositional functional approach.

• Keywords
• Compositional scalar-on-function regression, isotemporal substitution, physical activity, probability density functions, sedentary behaviour, sleep,
• MeSH
• Adiposity * MeSH
• Bayes Theorem MeSH
• Time Factors MeSH
• Exercise * physiology   MeSH
• Child MeSH
• Humans MeSH
• Obesity * MeSH
• Cross-Sectional Studies MeSH
• Check Tag
• Child MeSH
• Humans MeSH
• Publication type
• Journal Article MeSH

BACKGROUND: While there is evidence that physical activity, sedentary behaviour (SB) and sleep may all be associated with modified levels of inflammatory markers in adolescents and children, associations with one movement behaviour have not always been adjusted for other movement behaviours, and few studies have considered all movement behaviours in the 24-hour day as an exposure. PURPOSE: The aim of the study was to explore how longitudinal reallocations of time between moderate-to-vigorous physical activity (MVPA), light physical activity (LPA), SB and sleep are associated with changes in inflammatory markers in children and adolescents. METHODS: A total of 296 children/adolescents participated in a prospective cohort study with a 3-year follow-up. MVPA, LPA and SB were assessed by accelerometers. Sleep duration was assessed using the Health Behavior in School-aged Children questionnaire. Longitudinal compositional regression models were used to explore how reallocations of time between movement behaviours are associated with changes in inflammatory markers. RESULTS: Reallocations of time from SB to sleep were associated with increases in C3 levels (difference for 60 min/d reallocation [d60] = 5.29 mg/dl; 95% confidence interval [CI] = 0.28, 10.29) and TNF-α (d60 = 1.81 mg/dl; 95% CI = 0.79, 15.41) levels. Reallocations from LPA to sleep were also associated with increases in C3 levels (d60 = 8.10 mg/dl; 95% CI = 0.79, 15.41). Reallocations from LPA to any of the remaining time-use components were associated with increases in C4 levels (d60 ranging from 2.54 to 3.63 mg/dl; p < 0.05), while any reallocation of time away from MVPA was associated with unfavourable changes in leptin (d60 ranging from 3088.44 to 3448.07 pg/ml; p < 0.05). CONCLUSIONS: Reallocations of time between 24-h movement behaviours are prospectively associated with some inflammatory markers. Reallocating time away from LPA appears to be most consistently unfavourably associated with inflammatory markers. Given that higher levels of inflammation during childhood and adolescence are associated with an increased risk of chronic diseases in adulthood, children and adolescents should be encouraged to maintain or increase the level of LPA to preserve a healthy immune system.

• Keywords
• Compositional data analysis, Device-measured physical activity, Device-measured sedentary behaviour, Physical activity intensity levels,
• MeSH
• Accelerometry MeSH
• Exercise * MeSH
• Child MeSH
• Humans MeSH
• Adolescent MeSH
• Prospective Studies MeSH
• Sedentary Behavior MeSH
• Sleep * MeSH
• Inflammation MeSH
• Check Tag
• Child MeSH
• Humans MeSH
• Adolescent MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH

BACKGROUND: How we spend our time and what we eat have important implications for our health. Evidence suggests that health-equivalent behaviour change options which result in the same benefit are available within both time use (physical activities, sedentary behaviours and sleep) and diet (e.g., fruit and vegetables, snack foods). However, it is not yet known if health-equivalent choices exist across both time-use and diet behaviours. This study aimed to explore if a variety of different time-use and dietary profiles were associated with equivalent physical functioning score among adolescents. METHODS: This study used cross-sectional data from 2123 adolescent participants from the Longitudinal Study of Australian Children (LSAC) (mean age = 14.4 ± 0.5 years), including time-use diaries (min/day of sleep, self-care, screen time, quiet time, physical activity, school-related and domestic/social), diet questionnaires (serves/day of fruit and vegetables, discretionary (snack) foods and sugar-sweetened beverages) and a measure of physical functioning (PedsQL™ 4.0 physical functioning scale for teens). Multiple linear regression models were used to find the association of 24-h time-use composition (expressed as isometric log ratios) and dietary variables with physical functioning score. The models were used to estimate which time-use and diet profiles (within a feasible range from the sample average) were associated with equivalent physical functioning scores. Finally, an interactive app was developed to make the results accessible to end users. RESULTS: Within 30 min and 1.5 servings of the average adolescent's time-use and dietary behaviours, 45 equivalent options were associated with a ~ 0.2 SD improvement in physical functioning scale. All options associated with this improvement in physical function involved increasing physical activity and increasing fruit and vegetable intake, whilst also reducing discretionary food intake and sugar-sweetened beverages. Most behavioural options also increased sleep and reduced time spent in self-care, screen time and quiet time activities. CONCLUSIONS: There are a range of time-use and diet profiles that may result in equivalent benefits in physical functioning among adolescents. Communicating these options using decision tools such as interactive apps may allow for tailored interventions across both time use and diet which are based on an individual's needs, preferences and constraints.

• Keywords
• Adolescent, Diet, Health, Non-communicable diseases, Time use,
• Publication type
• Journal Article MeSH

Reallocations of time between daily activities such as sleep, sedentary behavior and physical activity are differentially associated with markers of physical, mental and social health. An individual's most desirable allocation of time may differ depending on which outcomes they value most, with these outcomes potentially competing with each other for reallocations. We aimed to develop an interactive app that translates how self-selected time reallocations are associated with multiple health measures. We used data from the Australian Child Health CheckPoint study (n = 1685, 48% female, 11-12 y), with time spent in daily activities derived from a validated 24-h recall instrument, %body fat from bioelectric impedance, psychosocial health from the Pediatric Quality of Life Inventory and academic performance (writing) from national standardized tests. We created a user-interface to the compositional isotemporal substitution model with interactive sliders that can be manipulated to self-select time reallocations between activities. The time-use composition was significantly associated with body fat percentage (F = 2.66, P < .001), psychosocial health (F = 4.02, P < .001), and academic performance (F = 2.76, P < .001). Dragging the sliders on the app shows how self-selected time reallocations are associated with the health measures. For example, reallocating 60 minutes from screen time to physical activity was associated with -0.8 [95% CI -1.0 to -0.5] %body fat, +1.9 [1.4 to 2.5] psychosocial score and +4.5 [1.8 to 7.2] academic performance. Our app allows the health associations of time reallocations to be compared against each other. Interactive interfaces provide flexibility in selecting which time reallocations to investigate, and may transform how research findings are disseminated.

• MeSH
• Exercise MeSH
• Child MeSH
• Quality of Life * MeSH
• Humans MeSH
• Mobile Applications * MeSH
• Sedentary Behavior MeSH
• Check Tag
• Child MeSH
• Humans MeSH
• Male MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Geographicals
• Australia MeSH

BACKGROUND: Most studies on day-to-day patterns of physical behaviours (i.e. physical activities and sedentary behaviour) are based on adults with high socioeconomic status (SES) and without differentiating between work and leisure time. Thus, we aimed to characterise the day-to-day leisure time physical behaviours patterns among low SES adults and investigate the influence of work physical behaviours. METHODS: This cross-sectional study included 963 adults from low SES occupations (e.g. manufacturing, cleaning and transportation). The participants wore accelerometers for 1-7 days to measure physical behaviours during work and leisure time, expressed as time-use compositions consisting of time spent sedentary, standing or being active (walking, running, stair climbing, or cycling). Compositional multivariate multilevel models were used to regress daily leisure time-use composition against work time-use compositions. Interaction between weekday and (1) type of day, (i.e., work/non-work) and (2) the work time-use composition were tested. Compositional isotemporal substitution was used to interpret the estimates from the models. RESULTS: Each weekday, workers consistently spent most leisure time being sedentary and most work time standing. Leisure time physical behaviours were associated with type of day (p < 0.005, more sedentary on workdays vs. non-workdays), weekday (p < 0.005, more sedentary on Friday, Saturday and Sunday), standing work (p < 0.005, more sedentary and less standing and active leisure time on Sunday), and active work (p < 0.005, less sedentary and more standing and active leisure time on Sunday). Sedentary leisure time increased by 18 min, while standing and active leisure time decreased by 11 and 7 min, respectively, when 30 min were reallocated to standing at work on Sunday. Conversely, sedentary leisure time decreased by 25 min, and standing and active leisure time increased by 15 and 10 min, respectively, when 30 min were reallocated to active time at work on Sunday. CONCLUSIONS: While low SES adults' leisure time was mostly sedentary, their work time was predominantly standing. Work physical behaviours differently influenced day-to-day leisure time behaviours. Thus, public health initiatives aiming to change leisure time behaviours among low SES adults should consider the influence of work physical behaviours.

• Keywords
• Accelerometer data, Compositional data analysis, Physical activity, Sedentary time, Socioeconomic inequality, Time-use,
• MeSH
• Accelerometry MeSH
• Adult MeSH
• Humans MeSH
• Cross-Sectional Studies MeSH
• Solanum tuberosum * MeSH
• Social Class MeSH
• Leisure Activities MeSH
• Check Tag
• Adult MeSH
• Humans MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH

BACKGROUND: Little is known on how context-specific sedentary behaviors (SB) affect adiposity. This study aimed to investigate compositional associations between context-specific SB and adiposity and estimate the differences in adiposity associated with replacing school and out-of-school SB with physical activity (PA). METHODS: This study included 336 children and adolescents. Time spent in SB and PA was estimated using multi-day 24-hour raw accelerometer data. SB and PA were specified for school and out-of-school times. Fat mass percentage (FM%) and fat mass index (FMI) were used as adiposity indicators. A compositional isotemporal substitution model was used to estimate differences in adiposity associated with one-to-one reallocations of time from context-specific SB to PA. RESULTS: Participants spent approximately two thirds of their school and out-of-school time being sedentary. Relative to the remaining 24-h movement behaviors, significant associations between out-of-school SB and adiposity were found in both boys (βilr1 = 0.63, 95% confidence interval [CI] = 0.03-1.22 for FM%; βilr1 = 0.76, 95% CI = 0.03-1.49 for FMI) and girls (βilr1 = 0.62, 95% CI = 0.25-0.98 for FM%; βilr1 = 0.80, 95% CI = 0.28-1.32 for FMI). Replacing 30 min/day of out-of-school SB with out-of-school light PA decreased FM% by 10.1% (95% CI = 3.3-17.9) and FMI by 14% (95% CI = 2.7-24) in girls. No significant associations were found for school SB. CONCLUSIONS: A reduction of out-of-school SB in favor of light PA should be advocated as an appropriate target for interventions and strategies to prevent childhood obesity.

• Keywords
• Accelerometry, Compositional data analysis, Schools, Time-use epidemiology,
• MeSH
• Adiposity * MeSH
• Accelerometry MeSH
• Exercise * MeSH
• Child MeSH
• Humans MeSH
• Adolescent MeSH
• Sedentary Behavior * MeSH
• Schools MeSH
• Check Tag
• Child MeSH
• Humans MeSH
• Adolescent MeSH
• Male MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Geographicals
• Czech Republic MeSH

BACKGROUND: Between-person differences in sedentary patterns should be considered to understand the role of sedentary behavior (SB) in the development of childhood obesity. This study took a novel approach based on compositional data analysis to examine associations between SB patterns and adiposity and investigate differences in adiposity associated with time reallocation between time spent in sedentary bouts of different duration and physical activity. METHODS: An analysis of cross-sectional data was performed in 425 children aged 7-12 years (58% girls). Waking behaviors were assessed using ActiGraph GT3X accelerometer for seven consecutive days. Multi-frequency bioimpedance measurement was used to determine adiposity. Compositional regression models with robust estimators were used to analyze associations between sedentary patterns and adiposity markers. To examine differences in adiposity associated with time reallocation, we used the compositional isotemporal substitution model. RESULTS: Significantly higher fat mass percentage (FM%; βilr1 = 0.18; 95% CI: 0.01, 0.34; p = 0.040) and visceral adipose tissue (VAT; βilr1 = 0.37; 95% CI: 0.03, 0.71; p = 0.034) were associated with time spent in middle sedentary bouts in duration of 10-29 min (relative to remaining behaviors). No significant associations were found for short (< 10 min) and long sedentary bouts (≥30 min). Substituting the time spent in total SB with moderate-to-vigorous physical activity (MVPA) was associated with a decrease in VAT. Substituting 1 h/week of the time spent in middle sedentary bouts with MVPA was associated with 2.9% (95% CI: 1.2, 4.6), 3.4% (95% CI: 1.2, 5.5), and 6.1% (95% CI: 2.9, 9.2) lower FM%, fat mass index, and VAT, respectively. Moreover, substituting 2 h/week of time spent in middle sedentary bouts with short sedentary bouts was associated with 3.5% (95% CI: 0.02, 6.9) lower FM%. CONCLUSIONS: Our findings suggest that adiposity status could be improved by increasing MVPA at the expense of time spent in middle sedentary bouts. Some benefits to adiposity may also be expected from replacing middle sedentary bouts with short sedentary bouts, that is, by taking standing or activity breaks more often. These findings may help design more effective interventions to prevent and control childhood obesity.

• Keywords
• Accelerometry, Body mass index, Child behavior, Pediatric obesity, Sedentary behavior,
• MeSH
• Adiposity * MeSH
• Accelerometry MeSH
• Data Analysis MeSH
• Child MeSH
• Body Mass Index MeSH
• Humans MeSH
• Cross-Sectional Studies MeSH
• Sedentary Behavior * MeSH
• Check Tag
• Child MeSH
• Humans MeSH
• Male MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH

BACKGROUND: This study aimed to use compositional data analysis to: (1) investigate the prospective associations between changes in daily movement behaviours and adiposity among elderly women; and (2) to examine how the reallocation of time between movement behaviours was associated with longitudinal changes in adiposity. SUBJECTS/METHODS: This is a 7-year longitudinal study in Central European older women (n = 158, baseline age 63.9 ± 4.4 years). At baseline and follow-up, light-intensity physical activity (LIPA), moderate-to-vigorous physical activity (MVPA) and sedentary behaviour were measured by accelerometer and body adiposity (body mass index [BMI], body fat percentage [%BF]) was assessed from measured height and weight and bioelectrical impedance analyser. Compositional regression with robust estimators and compositional longitudinal isotemporal substitution analysis explored if, and how, changes in movement behaviours were associated with adiposity. RESULTS: Over 7 years, the prevalence of obesity in the sample increased by 10.1% and 14.6% according to BMI and %BF, respectively, and time spent in sedentary behaviour increased by 14%, while time spent in LIPA and MVPA decreased by 14% and 21%, respectively. The increase in sedentary behaviour at the expense of LIPA and MVPA during the 7-year period was associated with higher BMI and %BF at follow-up (both p < 0.01). The increase in LIPA or MVPA at the expense of sedentary behaviour was associated with reduced BMI and %BF at follow-up. In our sample, the largest change in BMI (0.75 kg/m2; 95% confidence interval [CI]: 0.37-1.13) and %BF (1.28 U; 95% CI: 0.48-2.09) was associated with longitudinal reallocation of 30 min from MVPA to sedentary behaviour. CONCLUSIONS: We found an association between longitudinal changes in daily movement behaviours and adiposity among elderly women in Central Europe. Our findings support public health programmes to increase or maintain time spent in higher-intensity physical activity among elderly women.

• MeSH
• Adiposity physiology   MeSH
• Time Factors MeSH
• Exercise physiology   MeSH
• Body Mass Index MeSH
• Middle Aged MeSH
• Humans MeSH
• Longitudinal Studies MeSH
• Sedentary Behavior * MeSH
• Aged MeSH
• Body Composition MeSH
• Check Tag
• Middle Aged MeSH
• Humans MeSH
• Aged MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Geographicals
• Europe, Eastern MeSH