Compositional data analysis for physical activity, sedentary time and sleep research

Annual rhythms in adults' lifestyle and health (ARIA): protocol for a 12-month longitudinal study examining temporal patterns in weight, activity, diet, and wellbeing in Australian adults

BACKGROUND

Almost one in three Australian adults are now obese, and the rate continues to rise. The causes of obesity are multifaceted and include environmental, cultural and lifestyle factors. Emerging evidence suggests there may be temporal patterns in weight gain related, for example, to season and major festivals such as Christmas, potentially due to changes in diet, daily activity patterns or both. The aim of this study is to track the annual rhythm in body weight, 24 h activity patterns, dietary patterns, and wellbeing in a cohort of Australian adults. In addition, through data linkage with a concurrent children's cohort study, we aim to examine whether changes in children's body mass index, activity and diet are related to those of their parents.

METHODS

A community-based sample of 375 parents aged 18 to 65 years old, residing in or near Adelaide, Australia, and who have access to a Bluetooth-enabled mobile device or a computer and home internet, will be recruited. Across a full year, daily activities (minutes of moderate to vigorous physical activity, light physical activity, sedentary behaviour and sleep) will be measured using wrist-worn accelerometry (Fitbit Charge 3). Body weight will be measured daily using Fitbit wifi scales. Self-reported dietary intake (Dietary Questionnaire for Epidemiological Studies V3.2), and psychological wellbeing (WHOQOL-BREF and DASS-21) will be assessed eight times throughout the 12-month period. Annual patterns in weight will be examined using Lowess curves. Associations between changes in weight and changes in activity and diet compositions will be examined using repeated measures multi-level models. The associations between parent's and children's weight, activity and diet will be investigated using multi-level models.

DISCUSSION

Temporal factors, such as day type (weekday or weekend day), cultural celebrations and season, may play a key role in weight gain. The aim is to identify critical opportunities for intervention to assist the prevention of weight gain. Family-based interventions may be an important intervention strategy.

TRIAL REGISTRATION

Australia New Zealand Clinical Trials Registry, identifier ACTRN12619001430123 . Prospectively registered on 16 October 2019.

Associations of movement behaviors and body mass index: comparison between a report-based and monitor-based method using Compositional Data Analysis

BACKGROUND/OBJECTIVES

Evidence on the associations between lifestyle movement behaviors and obesity has been established without taking into account the time-constrained nature of categorized, time-based lifestyle behaviors. We examined the associations of sleep, sedentary behavior (SED), light-intensity physical activity (LPA), and moderate-to-vigorous PA (MVPA) with body mass index (BMI) using Compositional Data Analysis (CoDA), and compared the associations between a report-based method (24-h Physical Activity Recall; 24PAR) and a monitor-based method (SenseWear Armband; SWA).

SUBJECTS/METHODS

Replicate data from a representative sample of 1247 adults from the Physical Activity Measurement Survey (PAMS) were used in the study. Participants completed activity monitoring on two randomly selected days, each of which required wearing a SWA for a full day, and then completing a telephone-administered 24PAR the following day. Relationships among behavioral compositional parts and BMI were analyzed using CoDA via multiple linear regression models with both 24PAR and SWA data.

RESULTS

Using 24PAR, time spent in sleep (γ = -3.58, p = 0.011), SED (γ = 3.70, p = 0.002), and MVPA (γ = -0.53, p = 0.018) was associated with BMI. Using SWA, time spent in sleep (γ = -5.10, p < 0.001), SED (γ = 8.93, p < 0.001), LPA (γ = -3.12, p < 0.001), and MVPA (γ = -1.43, p < 0.001) was associated with BMI. The SWA models explained more variance in BMI (R2 = 0.28) compared with the 24PAR models (R2 = 0.07). The compositional isotemporal substitution models revealed reductions in BMI when replacing SED by MVPA, LPA (not with 24PAR) or sleep for both 24PAR and SWA, but the effect estimates were larger with SWA.

CONCLUSIONS

Favorable levels of relative time spent in lifestyle movement behaviors were, in general, associated with decreased BMI. The observed associations were stronger using the monitor-based SWA method compared with the report-based 24PAR method.

Cross-Sectional Associations Between Wake-Time Movement Compositions and Mental Health in Preschool Children With and Without Motor Coordination Problems

Movement behaviors have been found to be important correlates of health for children and may be particularly important for children with Developmental Coordination Disorder (DCD) who often experience greater mental health problems. To date, however, little research has investigated the daily movement composition of preschool children with Developmental Coordination Disorder (DCD) and/or its association with mental health. The purpose of the current study was to: (1) examine whether differences in movement compositions (i.e., sedentary time, light physical activity, moderate-to-vigorous physical activity) exist between typically developing (TD) preschool-age children and those at risk for DCD (rDCD); and (2) investigate associations between movement compositions and mental health indicators. This cross-sectional study used the baseline cohort data from the Coordination and Activity Tracking in CHildren (CATCH) study. A total of 589 preschool-age children (Mage = 4.94 ± 0.59 years; 57.4% boys) were included in this analysis, of which 288 scored at or below the 16th percentile on the Movement Assessment Battery for Children-2 and were thus classified as rDCD. Wake time movement behaviors were measured using accelerometers and parents completed the Child Behavior Checklist to assess their child's mental health (i.e., internalizing and externalizing problems). Compositional data analysis techniques were used. After adjusting for potential confounders, the results demonstrated similar movement compositions between TD and rDCD children. Among the full sample, findings revealed a significant association between sedentary time and externalizing problems, however, each of the other associations did not reach statistical significance. These results are consistent with emerging evidence demonstrating similar patterns of physical activity and sedentary time among TD children and those classified as rDCD during the preschool years. Although movement behaviors explained little variance in mental health during this period, future research should investigate when movement compositions diverge, and how these changes may impact the mental health of TD children and those classified as rDCD later in childhood.

The Impact of Pulmonary Rehabilitation on 24-Hour Movement Behavior in People With Chronic Obstructive Pulmonary Disease: New Insights From a Compositional Perspective

BACKGROUND

Physical activity levels are low in people with chronic obstructive pulmonary disease, and there is limited knowledge about how pulmonary rehabilitation transforms movement behaviors. This study analyzed data from a pulmonary rehabilitation trial and identified determinants of movement behaviors.

METHODS

Objectively assessed time in daily movement behaviors (sleep, sedentary, light-intensity physical activity, and moderate- to vigorous-intensity physical activity) from a randomized controlled trial (n = 73 participants) comparing home- and center-based pulmonary rehabilitation was analyzed using conventional and compositional analytical approaches. Regression analysis was used to assess relationships between movement behaviors, participant features, and response to the interventions.

RESULTS

Compositional analysis revealed no significant differences in movement profiles between the home- and center-based groups. At end rehabilitation, conventional analyses identified positive relationships between exercise capacity (6-min walk distance), light-intensity physical activity, and moderate- to vigorous-intensity physical activity time. Compositional analyses identified positive relationships between a 6-minute walk distance and moderate- to vigorous-intensity physical activity time, accompanied by negative relationships with sleep and sedentary time (relative to other time components) and novel relationships between body mass index and light-intensity physical activity/sedentary time.

CONCLUSION

Compositional analyses following pulmonary rehabilitation identified unique associations between movement behaviors that were not evident in conventional analyses.

Can a metric combining arm elevation and trapezius muscle activity predict neck/shoulder pain? A prospective cohort study in construction and healthcare

OBJECTIVE

To determine whether a composite metric of arm elevation and trapezius activity (i.e. neck/shoulder load) is more strongly associated with the 2-year course of neck and shoulder pain intensity (NSPi) among construction and healthcare workers than each exposure separately.

METHODS

Dominant arm elevation and upper trapezius muscle activity were estimated in construction and healthcare employees (n = 118) at baseline, using accelerometry and normalized surface electromyography (%MVE), respectively. At baseline and every 6 months for 2 years, workers reported NSPi (score 0-3). Compositions of working time were determined for arm elevation (< 30°; 30-60°;  > 60°), trapezius activity (< 0.5%; 0.5-7.0%; > 7.0%MVE), and a composite metric "neck/shoulder load" (restitution, low, medium, and high load). Associations between each of these three compositions and the 2-year course of NSPi were determined using linear mixed models.

RESULTS

Associations between exposure compositions and the course of NSPi were all weak and in general uncertain. Time spent in 0.5-7.0%MVE showed the largest and most certain association with changes in NSPi during follow-up (β = - 0.13; p = 0.037; corresponding to a -0.01 change in NPSi every 6 months). Among pain-free workers at baseline, medium (β = - 0.23; p = 0.039) and high (β = 0.15; p = 0.031) neck/shoulder load contributed the most to explaining changes in NSPi.

CONCLUSION

The composite metric of neck/shoulder load did not show a stronger association with the course of NSPi than arm elevation or trapezius activity alone in the entire population, while some indications of a stronger association were found among those who were pain-free at baseline.

The "Goldilocks Day" for Children's Skeletal Health: Compositional Data Analysis of 24-Hour Activity Behaviors

Optimization of children's activity behaviors for skeletal health is a key public health priority, yet it is unknown how many hours of moderate to vigorous physical activity (MVPA), light physical activity (LPA), sedentary behavior, or sleep constitute the best day-the "Goldilocks Day"-for children's bone structure and function. To describe the best day for children's skeletal health, we used data from the cross-sectional Child Health CheckPoint. Included participants (n = 804, aged 10.7 to 12.9 years, 50% male) underwent tibial peripheral quantitative CT to assesses cross-sectional area, trabecular and cortical density, periosteal and endosteal circumference, polar moment of inertia, and polar stress-strain index. Average daily time-use composition (MVPA, LPA, sedentary time, and sleep) was assessed through 8-day, 24-hour accelerometry. Skeletal outcomes were regressed against time-use compositions expressed as isometric log-ratios (with quadratic terms where indicated), adjusted for sex, age, pubertal status, and socioeconomic position. The models were used to estimate optimal time-use compositions (associated with best 5% of each skeletal outcome), which were plotted in three-dimensional quaternary figures. The center of the overlapping area was considered the Goldilocks Day for skeletal health. Children's time-use composition was associated with all skeletal measures (all p ≤ 0.001) except cross-sectional area (p = 0.72). Days with more sleep and MVPA, less sedentary time, and moderate LPA were beneficially associated with skeletal measures, except cortical density, which was adversely associated. The Goldilocks daily time-use composition for overall skeletal health was center (range): 10.9 (10.5 to 11.5) hours sleep; 8.2 (7.8 to 8.8) hours sedentary time; 3.4 (2.8 to 4.2) hours LPA, and 1.5 (1.3 to 1.5) hours MVPA. Estimated optimal sleep duration is consistent with current international guidelines (9 to 11 hours), while estimated optimal MVPA exceeds recommendations of at least 60 min/d. This first study to describe optimal durations of daily activities for children's skeletal health provides evidence to underpin guidelines. © 2020 American Society for Bone and Mineral Research (ASBMR).

New global guidelines on sedentary behaviour and health for adults: broadening the behavioural targets

BACKGROUND

In 2018, the World Health Organisation (WHO) commenced a program of work to update the 2010 Global Recommendations on Physical Activity for Health, for the first-time providing population-based guidelines on sedentary behaviour. This paper briefly summarizes and highlights the scientific evidence behind the new sedentary behaviour guidelines for all adults and discusses its strengths and limitations, including evidence gaps/research needs and potential implications for public health practice.

METHODS

An overview of the scope and methods used to update the evidence is provided, along with quality assessment and grading methods for the eligible new systematic reviews. The literature search update was conducted for WHO by an external team and reviewers used the AMSTAR 2 (Assessment of Multiple Systematic Reviews) tool for critical appraisal of the systematic reviews under consideration for inclusion. The Grading of Recommendations Assessment, Development and Evaluation (GRADE) method was used to rate the certainty (i.e. very low to high) of the evidence.

RESULTS

The updated systematic review identified 22 new reviews published from 2017 up to August 2019, 14 of which were incorporated into the final evidence profiles. Overall, there was moderate certainty evidence that higher amounts of sedentary behaviour increase the risk for all-cause, cardiovascular disease (CVD) and cancer mortality, as well as incidence of CVD, cancer, and type 2 diabetes. However, evidence was deemed insufficient at present to set quantified (time-based) recommendations for sedentary time. Moderate certainty evidence also showed that associations between sedentary behaviour and all-cause, CVD and cancer mortality vary by level of moderate-to-vigorous physical activity (MVPA), which underpinned additional guidance around MVPA in the context of high sedentary time. Finally, there was insufficient or low-certainty systematic review evidence on the type or domain of sedentary behaviour, or the frequency and/or duration of bouts or breaks in sedentary behaviour, to make specific recommendations for the health outcomes examined.

CONCLUSIONS

The WHO 2020 guidelines are based on the latest evidence on sedentary behaviour and health, along with interactions between sedentary behaviour and MVPA, and support implementing public health programmes and policies aimed at increasing MVPA and limiting sedentary behaviour. Important evidence gaps and research opportunities are identified.

Older Adults' Daily Step Counts and Time in Sedentary Behavior and Different Intensities of Physical Activity

Background

Daily step count is the simplest measure of physical activity. However, little is known about how daily step count related to time spent in different intensities of physical activity (PA) and sedentary behavior (SB).

Methods

These cross-sectional data were derived from 450 older Japanese adults (56.7% men; mean age, 74.3 years) who were randomly selected from three communities and responded a survey. Daily step count and time spent in moderate-to-vigorous PA (MVPA), light-intensity PA (LPA), and SB were measured using a validated wearable technology (HJA-350IT). Associations of daily step count with time spent in measured behaviors were examined using linear regression models with isometric log-ratio transformations of time-use composition, adjusting for gender, age, and residential area.

Results

Participants averaged 5,412 (standard deviation, 2,878) steps/d and accumulated MVPA, LPA, and SB corresponding to 4.0%, 34.8%, and 61.2% of daily waking time, respectively. Daily step count significantly increased with increase in time spent in MVPA relative to other behaviors (ie, LPA and SB) and in the ratio of LPA to SB after allowing for MVPA. After stratification, daily step count was significantly related to the ratio of LPA to SB in those taking <5,000 steps/d, but not in those taking 5,000–7,499 and ≥7,500 steps/d.

Conclusions

Higher daily step count can be an indicator of not only larger relative contribution of time spent in MVPA, but also higher ratio between LPA and SB, particularly among those who are the least physically active.

Racial Disparities in Financial Security, Work and Leisure Activities, and Quality of Life Among the Direct Care Workforce

Background and Objectives

Personal care, home health, and nursing aides provide the majority of care to chronically ill and disabled older adults. This workforce faces challenging working conditions, resulting in high turnover and workforce instability that affect the quality of care for older adults. We examine financial security, work–life balance, and quality of life of Black, Hispanic, and workers of other race/ethnicity compared to White workers.

Research Design and Methods

We hypothesize that Black and Hispanic workers experience greater financial insecurity, spend more time on work-related activities and have less time available for leisure activities, and have a lower quality of life compared to White workers. To test these hypotheses, we analyze the American Time Use Survey using descriptive analyses and multivariable and compositional regression.

Results

Black and Hispanic individuals were 2–3 times more likely to live in poverty than White individuals. The time use analysis indicated that Black and Hispanic workers spent more time on work-related activities and less time on nonwork-related activities, including longer work commutes and less time exercising. In analyses of aggregated paid/unpaid work and leisure, Black workers were the only group that spent significantly more time working and less time on leisure activities compared to White workers. This may explain the lower quality of life that we only observed in Black workers.

Discussion and Implications

Racial/ethnic disparities in well-being among direct care workers may affect the care older adults receive and contribute to widening inequities in this workforce and society. Policymakers should direct efforts toward securing funding for workers, incentivizing employer provisions, and implementing racial equity approaches.

Compositional data analysis of 24-hour movement behaviors and mental health in workers

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Time in sleep was favorably associated with mental distress and work engagement.

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Sedentary behavior (SB) was negatively correlated with distress and work engagement.

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Light-intensity physical activity (LPA) was negatively correlated with distress.

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Reallocating time in SB or LPA to sleep was associated with better mental health.

This cross-sectional study investigated the relationship between 24-hour movement behaviors and mental health among Japanese workers, accounting for the co-dependence of time spent in different behaviors during a single day. This research is part of a prospective cohort study called the Meiji Yasuda LifeStyle study. Participants were 1095 workers in Tokyo, Japan, who underwent annual health check-ups between 2017 and 2018. Time use during workdays and non-workdays was separately evaluated. Behaviors included sleep (self-reported duration), sedentary behavior (SB), light-intensity physical activity (LPA), and moderate- to vigorous-intensity physical activity (assessed with a tri-axial accelerometer). We used the six-item Kessler Psychological Distress scale to evaluate psychological distress and the Utrecht Work Engagement Scale to assess work engagement as indicators for negative and positive mental health, respectively. We performed compositional logistic regression and compositional isotemporal substitution to examine associations between 24-hour movement behaviors and mental health. After controlling for potential confounders, time spent in workdays was significantly associated with higher psychological distress and lower work engagement (p < 0.05), respectively. Time spent sleeping was positively correlated with both mental health indicators, whereas time spent in SB or LPA was negatively correlated (p < 0.05). During workdays, higher psychological distress and lower work engagement were predicted to be 11.4–26.6% lower when 60 min/day of time spent sleeping were reallocated to SB or LPA. Reallocating time spent on SB or LPA to sleep during workdays may minimize psychological distress and optimize work engagement. Thus, proper time management focused on encouraging sleep may help improve workers’ mental health.

Sweat, Sit, Sleep: A Compositional Analysis of 24-hr Movement Behaviors and Body Mass Index among Children with Autism Spectrum Disorder

This study (a) examined the daily composition of 24-hr movement behaviors in children with ASD using objective measures, and (b) applied compositional analysis to examine the associations of the time spent in moderate-vigorous physical activity (MVPA), light physical activity (LPA), sedentary behavior (SB), and sleep duration (SD) with body mass index (BMI), relative to the time spent in the other movement behaviors in a sample of children (aged 7-19 years) with ASD. Time spent in MVPA, LPA, SB, and SD were measured using accelerometers over a 7-day period. BMI was calculated from measured height and weight. Participants (n = 46) spent 40% of time in LPA (M = 9.6 hr), 30.6% (M = 7.34 hr) in SB, 24.9% (M = 5.98 hr) asleep, and 4.5% (M = 64.8 min) in MVPA. Reallocating 30 min from LPA to SD decreased BMI by 0.471 kg/m² (P = 0.003). Reallocating 30 min from MVPA to SD decreased BMI by 0.658 kg/m² (P = 0.051). Reallocation of 60 min in equal proportions from SB, MVPA, and SD to LPA increased BMI by 0.418 kg/m² (P = 0.021), and reallocation of 60 min in equal proportions from LPA, MVPA, and SD to SB increased BMI by 0.295 kg/m² (P = 0.052). Finally, reallocation of 60 min in equal proportions from SB, LPA, and MVPA to SD decreased BMI by -0.845 kg/m² (P = 0.001). LAY SUMMARY: Data was collected on time spent in light physical activity (LPA), moderate-vigorous physical activity (MVPA), sedentary behavior (SB), and sleep in 46 children with autism. The sample had insufficient sleep (a mean of 6 hr/night). We showed that replacing 30 min of LPA or MVPA with sleep decreased BMI. Also, moving 60 min to LPA or SB from the remaining movement behaviors (i.e., 20 min from each) increased BMI, and moving 60 min to sleep from the remaining behaviors decreased BMI.

The Relation between Domain-Specific Physical Behaviour and Cardiorespiratory Fitness: A Cross-Sectional Compositional Data Analysis on the Physical Activity Health Paradox Using Accelerometer-Assessed Data

In contrast to leisure time physical activity (LTPA), occupational physical activity (OPA) does not have similar beneficial health effects. These differential health effects might be explained by dissimilar effects of LTPA and OPA on cardiorespiratory fitness (CRF). This study investigated cross-sectional associations between different physical behaviours during both work and leisure time and CRF by using a Compositional Data Analysis approach. Physical behaviours were assessed by two accelerometers among 309 workers with various manual jobs. During work time, more sedentary behaviour (SB) was associated with higher CRF when compared relatively to time spent on other work behaviours, while more SB during leisure time was associated with lower CRF when compared to other leisure time behaviours. Reallocating more time to moderate-to-vigorous physical activity (MVPA) from the other behaviours within leisure time was positively associated with CRF, which was not the case for MVPA during work. The results of our study are in line with the physical activity health paradox and we call for further study on the interaction between LTPA and OPA by implementing device-worn measures in a longitudinal design. Our results highlight the need for recommendations to take into account the different effects of OPA and LTPA on CRF.

Cross-Sectional Associations of 24-Hour Sedentary Time, Physical Activity, and Sleep Duration Compositions with Sleep Quality and Habits in Preschoolers

Although some studies indicate physical activity and sleep quality are positively associated in children, most reports examined physical activity independent of other 24-h behaviors and focused on older children. The aim of this cross-sectional study was to examine the predicted changes in sleep efficiency and habits when reallocating time between movement behaviors using compositional isotemporal substitution in preschool-aged children. Accelerometers were worn by 288 participants (51.6 ± 9.5 months) for up to 16 days. Sleep outcomes included sleep efficiency, nap frequency, sleep disturbances, and bedtime resistance. Compositional isotemporal substitution analyses demonstrated that the combined effect of 24-h movement behaviors was associated with sleep efficiency (p < 0.001) and nap frequency (p < 0.003). When sleep increased by 30 min at the expense of stationary time or light physical activity, estimates of sleep efficiency and bedtime resistance decreased while nap frequency increased. When stationary time increased by 30 min from moderate to vigorous physical activity, estimated sleep efficiency increased and sleep disturbances decreased. Although this study presents preliminary evidence that 24-h movement behavior compositions in early childhood are associated with sleep quality and nap frequency, estimated effects from theoretical time reallocations across sleep outcomes were mixed.

Analysing body composition as compositional data: An exploration of the relationship between body composition, body mass and bone strength

Human body composition is made up of mutually exclusive and exhaustive parts (e.g. %truncal fat, %non-truncal fat and %fat-free mass) which are constrained to sum to the same total (100%). In statistical analyses, individual parts of body composition (e.g. %truncal fat or %fat-free mass) have traditionally been used as proxies for body composition, and have been linked with a range of health outcomes. But analysis of individual parts omits information about the other parts, which are intrinsically co-dependent because of the constant sum constraint of 100%. Further, body mass may be associated with health outcomes. We describe a statistical approach for body composition based on compositional data analysis. The body composition data are expressed as logratios to allow relative information about all the compositional parts to be explored simultaneously in relation to health outcomes. We describe a recent extension to the logratio approach to compositional data analysis which allows absolute information about the total of the compositional parts (body mass) to be considered alongside relative information about body composition. The statistical approach is illustrated by an example that explores the relationships between adults' body composition, body mass and bone strength.

Compliance of the 24-Hour Movement Guidelines in 9- to 11-Year-Old Children From a Low-Income Town in Chile

BACKGROUND

The purpose was to determine the proportion of 9- to 11-year-old children meeting the 24-hour movement guidelines (24-HMG) in a low-income town from Chile.

METHODS

Physical activity, sedentary behavior (recreational screen), and sleep times were measured with both questionnaire and accelerometer in 258 children from third to sixth grade. Meeting the 24-HMG was defined as having ≥60 minutes per day of moderate to vigorous physical activity, ≤2 hour day of screen time, and 9 to 11 hours of sleep per night. Compliance rates were calculated as self-reported 24-HMG, with all estimations based on questionnaires, and mixed 24-HMG, in which physical activity and sleep were determined with an accelerometer and sedentary behavior was determined with a questionnaire.

RESULTS

About 198 children (10.1 [0.8] y, range 9-11 y) provided valid data for estimating self-reported 24-HMG, and 141 for mixed 24-HMG. Only 3.2% and 0.7% met the 24-HMG when using the self-reported and mixed methods, respectively. When assessing individual recommendations, 13.1% and 3.7% of the sample were physically active based on the self-report and accelerometer, respectively. About a quarter met the sedentary behavior recommendations, while around 50% met the sleep recommendations with both self-reported and mixed methods.

CONCLUSIONS

An extremely low percentage of the participants met the 24-HMG. Multicomponent initiatives must be implemented to promote healthy movement behaviors in Chilean children.

Trends and correlates of meeting 24-hour movement guidelines: a 15-year study among 167,577 Thai adults

Background

Time spent in physical activity (PA), sedentary behaviour (SB), and sleep always takes up the whole day. New public health guidelines combining recommendations for PA, SB, and sleep have been issued in several countries. Thailand was the first country to release the 24-h guidelines for adults. Currently, there is no evidence on the population prevalence of meeting 24-h movement guidelines in Thailand. This study, therefore, aimed to determine 15-year trends and associations of meeting 24-h movement guidelines among Thai adults.

Method

We analysed cross-sectional data from 2001, 2004, 2009, and 2015 Thai Time-Use Surveys, coded using the International Classification of Activities for Time-Use Statistics (ICATUS). All ICATUS-based activities were categorised into moderate-to-vigorous PA (MVPA), light PA (LPA), SB, and sleep based on a previously developed classification system. A total of 167,577 adult participants were included. The participants were classified according to the Thai 24-h movement guidelines into meeting or not meeting the following criteria: 1) ≥150 min/week of MVPA; 2) interrupting SB every 2 h; 3) sleeping 7–9 h per day; and 4) adhering to all three guidelines.

Results

In 2015, the prevalence of adults who met the MVPA, SB, sleep, and overall recommendations was 81.7, 44.6, 56.4, and 21.3%, respectively. A significant linear increase was found for the prevalence of meeting the SB recommendation, while the prevalence meeting the MVPA, sleep, and overall recommendations was lowest in 2001, peaked in 2004 or 2009, and declined in 2015. The lowest odds for meeting the 24-h guidelines were found among males, those living in urban areas, inhabitants of Bangkok and South Thailand, unemployed, and those with low education level.

Conclusions

Despite promising trends in the prevalence of meeting PA, SB, and sleep recommendations, a majority of Thai adults still do not meet the overall 24-h movement guidelines. Further actions are needed to promote more MVPA, less SB, and adequate sleep in Thai adults, particularly among males, those living in urban areas, inhabitants of Bangkok and South Thailand, unemployed, and those with low education level.

Use of Compositional Data Analysis to Show Estimated Changes in Cardiometabolic Health by Reallocating Time to Light-Intensity Physical Activity in Older Adults

BACKGROUND

All physical activity (PA) behaviours undertaken over the day, including sleep, sedentary time, standing time, light-intensity PA (LIPA) and moderate-to-vigorous PA (MVPA) have the potential to influence cardiometabolic health. Since these behaviours are mutually exclusive, standard statistical approaches are unable to account for the impact on time spent in other behaviours.

OBJECTIVE

By employing a compositional data analysis (CoDA) approach, this study examined the associations of objectively measured time spent in sleep, sedentary time, standing time, LIPA and MVPA over a 24-h day on markers of cardiometabolic health in older adults.

METHODS

Participants (n =366; 64.6 years [5.3]; 46% female) from the Mitchelstown Cohort Rescreen Study provided measures of body composition, blood lipid and markers of glucose control. An activPAL3 Micro was used to obtain objective measures of sleep, sedentary time, standing time, LIPA and MVPA, using a 7-day continuous wear protocol. Regression analysis, using geometric means derived from CoDA (based on isometric log-ratio transformed data), was used to examine the relationship between the aforementioned behaviours and markers of cardiometabolic health.

RESULTS

Standing time and LIPA showed diverging associations with markers of body composition. Body mass index (BMI), body mass and fat mass were negatively associated with LIPA (all p <0.05) and positively associated with standing time (all p <0.05). Sedentary time was also associated with higher BMI (p <0.05). No associations between blood markers and any PA behaviours were observed, except for triglycerides, which were negatively associated with standing time (p < 0.05). Reallocating 30 min from sleep, sedentary time or standing time, to LIPA, was associated with significant decreases in BMI, body fat and fat mass.

CONCLUSION

This is the first study to employ CoDA in older adults that has accounted for sleep, sedentary time, standing time, LIPA and MVPA in a 24-h cycle. The findings support engagement in LIPA to improve body composition in older adults. Increased standing time was associated with higher levels of adiposity, with increased LIPA associated with reduced adiposity; therefore, these findings indicate that replacing standing time with LIPA is a strategy to lower adiposity.

Changes in rural older adults' sedentary and physically-active behaviors between a non-snowfall and a snowfall season: compositional analysis from the NEIGE study

BACKGROUND

Levels of physical activity change throughout the year. However, little is known to what extent activity levels can vary, based on accelerometer determined sedentary and physically-active time. The aim of this longitudinal study was to examine older adults' activity changes from a non-snowfall season to a subsequent snowfall season, with consideration of the co-dependence of domains of time use.

METHODS

Participants were 355 older Japanese adults (53.1% women, aged 65-84 years) living in a rural area of heavy snowfall who had valid accelerometer (Active style Pro HJA-750C) data during non-snowfall and snowfall seasons. Activity was classified as sedentary behavior (SB), light-intensity PA (LPA), and moderate-to-vigorous PA (MVPA). Compositional changes from the non-snowfall to the snowfall season were analyzed using Aitchison's perturbation method. The ratios of each component in the composition, such as [SBsnow/SBnon-snow, LPAsnow/LPAnon-snow, MVPAsnow/MVPAnon-snow] for seasonal changes, were calculated and were then divided by the sum of these ratios.

RESULTS

In men, the percentages of time spent in each activity during the non-snowfall/snowfall seasons were 53.9/64.6 for SB; 40.8/31.6 for LPA; and 5.3/3.8 for MVPA; these corresponded to mean seasonal compositional changes (∆SB, ∆LPA, ∆MVPA) of 0.445, 0.287, and 0.268 respectively. In women, the percentages of time spent in each activity during the non-snowfall/snowfall seasons were 47.9/55.5 for SB; 47.9/41.0 for LPA; and 4.2/3.5 for MVPA; these corresponded to mean seasonal compositional changes (∆SB, ∆LPA, ∆MVPA) of 0.409, 0.302, and 0.289 respectively. The degree of seasonal change was greatest in men.

CONCLUSIONS

In older adults, activity behaviors were changed unfavorably during snowfall season, particularly so for men. The degree of seasonal change was greatest for SB. Development of strategies to keep rural older adults active during the snowfall season may be needed for maintaining a consistently-active lifestyle for their health.

How do short sleepers use extra waking hours? A compositional analysis of 24-h time-use patterns among children and adolescents

BACKGROUND

To examine compositional associations between short sleep duration and sedentary behavior (SB), light physical activity (LPA) and moderate-to-vigorous physical activity (MVPA) among children and adolescents.

METHODS

Multi-day 24-h data on sleep, SB, LPA and MVPA were collected using accelerometers among 343 children (8-13 years old) and 316 adolescents (14-18 years old). Children and adolescents with sleep duration of < 9 and < 8 h, respectively, were classified as short sleepers. Robust compositional regression analysis was used to examine the associations between short sleep duration and the waking-time composition.

RESULTS

Seventy-one percent of children and 75.3% of adolescents were classified as short sleepers. In children, being a short sleeper was associated with higher SB by 95 min/day (p < 0.001) and lower MVPA by 16 min/day (p = 0.002). Specifically, it was associated with a higher amount of time spent in long sedentary bouts (β_ilr1 = 0.46, 95% confidence interval [CI] = 0.29 to 0.62) and lower amounts of time spent in sporadic SB (β_ilr1 = - 0.17, 95% CI = -0.24 to - 0.10), sporadic LPA (β_ilr1 = - 0.09, 95% CI = -0.14 to - 0.04) and sporadic MVPA (β_ilr1 = - 0.17, 95% CI = -0.25 to - 0.10, p < 0.001 for all), relative to the remaining behaviours. In adolescents, being a short sleeper was associated with a higher amount of time spent in SB by 67 min/day (p = 0.001) and lower LPA by 2 min/day (p = 0.035). Specifically, it was associated with more time spent in sedentary bouts of 1-9 min (β_ilr1 = 0.08, 95% CI = 0.02 to 0.14, p = 0.007) and 10-29 min (β_ilr1 = 0.10, 95% CI = 0.02 to 0.18, p = 0.015), relative to the remaining behaviours.

CONCLUSIONS

Among children and adolescents, short sleep duration seems to be highly prevalent and associated with less healthy waking time. Public health interventions and strategies to tackle the high prevalence of short sleep duration among children and adolescents are warranted.

How Does Time Use Differ between Individuals Who Do More versus Less Foodwork? A Compositional Data Analysis of Time Use in the United Kingdom Time Use Survey 2014-2015

BACKGROUND

Increased time spent on home food preparation is associated with higher diet quality, but a lack of time is often reported as a barrier to this practice. We compared time use in individuals who do more versus less foodwork (tasks required to feed ourselves and our households, including home food preparation).

METHODS

Cross-sectional analysis of the UK Time Use Survey 2014-15, participants aged 16+ (N = 6143). Time use over 24 h was attributed to seven compositional parts: personal care; sleep; eating; physical activity; leisure screen time; work (paid and unpaid); and socialising and hobbies. Participants were categorised as doing no, 'some' (<70 min), or 'more' foodwork (≥70 min). We used compositional data analysis to test whether time-use composition varied between these participant groups, determine which of the parts varied between groups, and test for differences across population subgroups.

RESULTS

Participants who spent more time on foodwork spent less time on sleep, eating, and personal care and more time on work. Women who did more foodwork spent less time on personal care, socialising, and hobbies, which was not the case for men.

CONCLUSION

Those who seek to encourage home food preparation should be aware of the associations between foodwork and other activities and design their interventions to guard against unintended consequences.

Transmissibility of COVID-19 in 11 major cities in China and its association with temperature and humidity in Beijing, Shanghai, Guangzhou, and Chengdu

BACKGROUND

The new coronavirus disease COVID-19 began in December 2019 and has spread rapidly by human-to-human transmission. This study evaluated the transmissibility of the infectious disease and analyzed its association with temperature and humidity to study the propagation pattern of COVID-19.

METHODS

In this study, we revised the reported data in Wuhan based on several assumptions to estimate the actual number of confirmed cases considering that perhaps not all cases could be detected and reported in the complex situation there. Then we used the equation derived from the Susceptible-Exposed-Infectious-Recovered (SEIR) model to calculate R0 from January 24, 2020 to February 13, 2020 in 11 major cities in China for comparison. With the calculation results, we conducted correlation analysis and regression analysis between R0 and temperature and humidity for four major cities in China to see the association between the transmissibility of COVID-19 and the weather variables.

RESULTS

It was estimated that the cumulative number of confirmed cases had exceeded 45 000 by February 13, 2020 in Wuhan. The average R0 in Wuhan was 2.7, significantly higher than those in other cities ranging from 1.8 to 2.4. The inflection points in the cities outside Hubei Province were between January 30, 2020 and February 3, 2020, while there had not been an obvious downward trend of R0 in Wuhan. R0 negatively correlated with both temperature and humidity, which was significant at the 0.01 level.

CONCLUSIONS

The transmissibility of COVID-19 was strong and importance should be attached to the intervention of its transmission especially in Wuhan. According to the correlation between R0 and weather, the spread of disease will be suppressed as the weather warms.

Transmissibility of COVID-19 in 11 major cities in China and its association with temperature and humidity in Beijing, Shanghai, Guangzhou, and Chengdu

BACKGROUND

The new coronavirus disease COVID-19 began in December 2019 and has spread rapidly by human-to-human transmission. This study evaluated the transmissibility of the infectious disease and analyzed its association with temperature and humidity to study the propagation pattern of COVID-19.

METHODS

In this study, we revised the reported data in Wuhan based on several assumptions to estimate the actual number of confirmed cases considering that perhaps not all cases could be detected and reported in the complex situation there. Then we used the equation derived from the Susceptible-Exposed-Infectious-Recovered (SEIR) model to calculate R₀ from January 24, 2020 to February 13, 2020 in 11 major cities in China for comparison. With the calculation results, we conducted correlation analysis and regression analysis between R₀ and temperature and humidity for four major cities in China to see the association between the transmissibility of COVID-19 and the weather variables.

RESULTS

It was estimated that the cumulative number of confirmed cases had exceeded 45 000 by February 13, 2020 in Wuhan. The average R₀ in Wuhan was 2.7, significantly higher than those in other cities ranging from 1.8 to 2.4. The inflection points in the cities outside Hubei Province were between January 30, 2020 and February 3, 2020, while there had not been an obvious downward trend of R₀ in Wuhan. R₀ negatively correlated with both temperature and humidity, which was significant at the 0.01 level.

CONCLUSIONS

The transmissibility of COVID-19 was strong and importance should be attached to the intervention of its transmission especially in Wuhan. According to the correlation between R₀ and weather, the spread of disease will be suppressed as the weather warms.

Can we walk away from cardiovascular disease risk or do we have to 'huff and puff'? A cross-sectional compositional accelerometer data analysis among adults and older adults in the Copenhagen City Heart Study

Background

It is unclear whether walking can decrease cardiovascular disease (CVD) risk or if high intensity physical activity (HIPA) is needed, and whether the association is modified by age. We investigated how sedentary behaviour, walking, and HIPA, were associated with systolic blood pressure (SBP), waist circumference (WC), and low-density lipoprotein cholesterol (LDL-C) among adults and older adults in a general population sample using compositional data analysis. Specifically, the measure of association was quantified by reallocating time between sedentary behaviour and 1) walking, and 2) HIPA.

Methods

Cross-sectional data from the fifth examination of the Copenhagen City Heart Study was used. Using the software Acti4, we estimated daily time spent in physical behaviours from accelerometer data worn 24 h/day for 7 days (i.e., right frontal thigh and iliac crest; median wear time: 6 days, 23.8 h/day). SBP, WC, and LDL-C were measured during a physical examination. Inclusion criteria were ≥ 5 days with ≥16 h of accelerometer recordings per day, and no use of antihypertensives, diuretics or cholesterol lowering medicine. The 24-h physical behaviour composition consisted of sedentary behaviour, standing, moving, walking, HIPA (i.e., sum of climbing stairs, running, cycling, and rowing), and time in bed. We used fitted values from linear regression models to predict the difference in outcome given the investigated time reallocations relative to the group-specific mean composition.

Results

Among 1053 eligible participants, we found an interaction between the physical behaviour composition and age. Age-stratified analyses (i.e., </≥65 years; 773 adults, 280 older adults) indicated that less sedentary behaviour and more walking was associated with lower SBP among older adults only. For less sedentary behaviour and more HIPA, the results i) indicated an association with a lower SBP irrespective of age, ii) showed an association with a smaller WC among adults, and iii) showed an association with a lower LDL-C in both age groups.

Conclusions

Less sedentary behaviour and more walking seems to be associated with lower CVD risk among older adults, while HIPA types are associated with lower risk among adults. Therefore, to reduce CVD risk, the modifying effect of age should be considered in future physical activity-promoting initiatives.

Light-intensity physical activity derived from count or activity types is differently associated with adiposity markers

Aim

The aim of this study was to compare the association between count‐ and activity type–based definitions of light‐intensity physical activity (LIPA) and adiposity markers.

Methods

A total of 516 Danish workers participated in 1‐4 days of hip‐ and thigh‐based accelerometer measurements. Three definitions of average daily time spent in LIPA were derived: LIPA (1) time spent between 100 and 2029 CPM, LIPA (2) time spent moving and slow walking, and LIPA (3) time spent moving, walking slow, and standing. Adiposity markers were body mass index (BMI), body fat percentage, and waist circumference. The cross‐sectional association between the three LIPA definitions and adiposity markers was analyzed and interpreted using compositional regression models followed by reallocation of time between LIPA, moderate‐to‐vigorous physical activity (MVPA), and sedentary behavior (SB), respectively.

Results

The geometric means of daily time (min/day) spent in LIPA 1, LIPA 2, and LIPA 3 were 326, 102, and 274, respectively. We found the direction and strength of the association between the relative importance of daily time spent in LIPA and the adiposity markers to depend on the LIPA definition. For example, reallocating 30 minutes from MVPA to LIPA 1, LIPA 2 and LIPA 3 were associated with a 2.97 (95% CI: 0.68; 5.27), −0.71 (95% CI: −1.43; 0.02), and −0.45 (95% CI: −1.01; 0.11) difference in BMI, respectively.

Conclusion

Our findings highlight the need for caution when comparing results from studies using different definitions of LIPA.

Prospective Changes in the Distribution of Movement Behaviors Are Associated With Bone Health in the Elderly According to Variations in their Frailty Levels

Frailty is associated with poor bone health and osteoporosis, and physical activity (PA) is one of the best treatments for both pathologies in older adults. Nonetheless, because daily time is limited, how the time is distributed during the waking hours is critical. The waking hours are spent according to different movement behaviors: sedentary behaviors (SB), light physical activity (LPA), and moderate-to-vigorous physical activity (MVPA). The aim of this study was to use compositional data analyses to examine the effects of the change in movement behaviors on bone health during aging in older people, related to the changes in their frailty levels. We analyzed 227 older people aged 65 to 94 (125 women and 102 men) over a 4-year period. Movement behaviors were assessed using accelerometry. Both bone mineral density (BMD) and bone mineral content (BMC) were determined using bone densitometry. The Frailty Trait Scale was used to divide the sample by frailty level evolution during aging. The R statistical system was used for the compositional data analysis and, in addition, all models were adjusted for several covariates. The changes in the distribution of all movement behaviors within a waking hour period were significantly associated with spine and femoral neck BMD changes in the subgroup with a positive change in frailty level and spine BMC in the subgroup with no change in frailty level (p ≤ .05). Likewise, MVPA relative to the change in other movement behaviors was also associated in both subgroups with higher BMD and BMC, respectively, in the same body areas (p ≤ .05). No significant associations were found in the negative change in frailty level subgroup. Older people who achieved a positive change in frailty level during a 4-year period showed higher BMD changes compared to those with no changes or increases in their frailty level. Therefore, increasing MVPA relative to the change in the other movement behaviors during a 4-year period could perhaps produce bone health improvements in the elderly that do not worsen their frailty level. © 2020 American Society for Bone and Mineral Research.

[Associations of distribution of time spent in physical activity and sedentary behavior with obesity]

OBJECTIVE

To explore associations of distribution of time spent in physical activity (PA) and sedentary behavior (SB) with obesity with taking account that time is finite during the day of adult residents in Wuhai City.

METHODS

A cross-sectional study was undertaken in Wuhai City, and we carried out a sampling of local residents aged 18-79 by using multiple stratified cluster sampling method. Data about social demographic characteristics, time spent in PA and SB, diet intake, controlling situation of chronic disease and other covariates were obtained by qualified investigators for face-to-face questionnaire survey. Data about height, weight, and waist circumstance, were obtained by doctors in a secondary hospital or above for body measurements. The statistical method used in our study was known as compositional data analysis, which had been used to process compositional data in many fields. Liner regression analysis with compositional data was used to synthetically analyze the associations of distribution of time spent in PA and SB with obesity,and to investigate the effect of re-allocating time from one behavior to another one whilst the remaining one was kept stable.

RESULTS

The investigation revealed the special advantage of compositional data analysis in processing time-use data. The result of liner regression analysis with the compositional data showed that after controlling the potential confounding factors, the associations of distribution of time spent in PA and SB was significantly associated with body mass index (BMI, P<0.001) and the negative natural logarithm of waist to height ratio (-lnWHtR, P<0.001). Among them, in professional population, the proportion of time spent in moderate-to-vigorous physical activity (MVPA) was negatively correlated with -lnWHtR (β=-0.008, P=0.022), while the proportion of time spent in SB was positively correlated with BMI and -lnWHtR (β=0.117, P=0.003; β=0.007, P=0.005). However, in nonprofessional population, the proportion of time spent in MVPA was only negatively correlated with BMI (β=-0.079, P=0.041). Nevertheless, the proportion of time spent in low-intensity physical activity (LIPA) was not significantly associated with BMI and -lnWHtR in both professional and nonprofessional population. In addition, the effects of MVPA replacing another behavior and of MVPA being displaced by another behavior were not symmetrical, and 10 minutes of MVPA replacing LIPA or SB had a greater influence on intervention and prevention of obesity than 10 minutes MVPA being replaced by LIPA or SB.

CONCLUSION

The research has resulted in a solution of the associations of the distribution of time spent in PA, SB with health risk. Our results suggest that public health messages should target the health effects of the distribution of time of PA and SB synergistically in developing PA guidelines and health management practice, rather than simply increasing or decreasing the absolute time of PA or SB, so that we can provide scientific suggestions to make people get a profounder healthy effect.

Sitting, standing and moving during work and leisure among male and female office workers of different age: a compositional data analysis

BACKGROUND

Gendered patterns of physical activity behaviours may help explaining health inequalities between men and women. However, evidence on such patterns in the working population is sparse. This study aimed at documenting and comparing compositions of sitting, standing and moving at work and during leisure among male and female office workers of different age.

METHODS

Sitting (including lying), standing and moving were measured using accelerometry for, on average, four working days in 55 male and 57 female Swedish office workers. Behaviours were described in terms of time spent in four exhaustive categories: sitting in short (< 30 min) and long (≥30 min) bouts, standing, and moving. In a compositional data analysis approach, isometric log-ratios (ilr) were calculated for time sitting relative to non-sitting, time in short relative to long sitting bouts, and time in standing relative to moving. Differences between genders (men vs. women), domains (work vs. leisure), and according to age were examined for each ilr using ANOVA.

RESULTS

At work, time spent sitting in short bouts, sitting in long bouts, standing, and moving was, on average, 29, 43, 21 and 7% among men, and 28, 38, 26 and 7% among women. Corresponding proportions during leisure were 34, 27, 27 and 13% among men and 28, 27, 32 and 13% among women. Men spent more time sitting relative to non-sitting ([Formula: see text] =0.04, p = 0.03) than women, and less time standing relative to moving ([Formula: see text] =0.07, p = 0.01). At work compared to during leisure, both genders spent more time sitting relative to non-sitting ([Formula: see text] =0.47, p < 0.01); within sitting more time was spent in long relative to short sitting bouts ([Formula: see text] =0.26, p < 0.01), and within non-sitting, more time was spent standing than moving ([Formula: see text] =0.12, p < 0.01). Older workers spent less of their non-sitting time moving than younger workers ([Formula: see text] =0.07, p = 0.01).

CONCLUSION

Male office workers spent more time sitting relative to non-sitting than female workers, and more time moving relative to standing. Both genders were sitting more at work than during leisure. Older workers moved less than younger. These workers could likely benefit from interventions to reduce or break up prolonged sitting time, preferably by moving more.

A Bayesian analysis for pseudo-compositional data with spatial structure

We proposed a Bayesian analysis of pseudo-compositional data in presence of a latent factor, assuming a spatial structure. This development was motivated by a dataset containing information on the number of newborns of primiparous mothers living in each of the microregions of the state of Sao Paulo, Brazil, in the year of 2015, stratified by the age of the mothers (15-18, 19-29 and 30 years or more). Considering that data on newborns are not stochastically distributed among the three age groups, but they are explained in relation to women's population structure, we adopted the expression "pseudo-compositional data" to refer to this data structure. The hypothesis of interest establishes that the age of the first pregnancy is associated with the economic conditions of the geographic area where the mother lives. The incidence of poverty was included as an independent variable. Additive log-ratio (alr) and isometric log-ratio (ilr) transformations were considered, as is usually done in the analysis of compositional data. The model included a random effect related to the spatial effect assumed to have a conditional autoregressive structure. A Bayesian Markov Chain Monte Carlo (MCMC) simulation procedure was used to get the posterior summaries of interest. The model based on the (ilr) transformation was well fitted to the data, showing that in the microregions with the highest incidence of poverty, there are higher proportions of women who have their first child in adolescence, while in the microregions with the lowest incidence of poverty, there are higher proportions of women who have their first child after the age of 30 years. From these results it is possible to conclude that this Bayesian approach was very useful in the estimation of the parameters of the proposed model. The proposed method should have a broad application to other problems involving pseudo-compositional data.

Cox regression survival analysis with compositional covariates: Application to modelling mortality risk from 24-h physical activity patterns

Survival analysis is commonly conducted in medical and public health research to assess the association of an exposure or intervention with a hard end outcome such as mortality. The Cox (proportional hazards) regression model is probably the most popular statistical tool used in this context. However, when the exposure includes compositional covariables (that is, variables representing a relative makeup such as a nutritional or physical activity behaviour composition), some basic assumptions of the Cox regression model and associated significance tests are violated. Compositional variables involve an intrinsic interplay between one another which precludes results and conclusions based on considering them in isolation as is ordinarily done. In this work, we introduce a formulation of the Cox regression model in terms of log-ratio coordinates which suitably deals with the constraints of compositional covariates, facilitates the use of common statistical inference methods, and allows for scientifically meaningful interpretations. We illustrate its practical application to a public health problem: the estimation of the mortality hazard associated with the composition of daily activity behaviour (physical activity, sitting time and sleep) using data from the U.S. National Health and Nutrition Examination Survey (NHANES).

Academic Schedule and Day-to-Day Variations in Sedentary Behavior and Physical Activity of University Students

Students starting at university tend to adopt unhealthy behaviors. With students expected to sit during classes, their academic schedule may be responsible for their activity patterns. The aim of the current study was to investigate the relationship between university students’ academic schedule and day-to-day variations in sedentary behavior (SB) and physical activity (PA). The activity of 317 first-year undergraduate students (mean age 19.6 ± 1.4 years, 69.4% female, 30.0% male, and 0.6% other) was measured with the activPAL3™ triaxial monitor for seven consecutive days. Each class hour was found to be associated with 9.0 additional minutes of SB (95% CI [4.9, 13.1]), 54 additional seconds of moderate-to-vigorous PA (MVPA; 95% CI [12, 96]), and 12.2 min less time in bed (95% CI [−16.6, −7.8]). Active SB ratio (total duration of SB bouts < 30 min divided by total SB duration) decreased by 0.011 per hour of class scheduled for the students (95% CI [−0.016, −0.006]). Light PA (LPA) was not significantly associated with class duration. Students tend to cycle more on days with classes. Seated transportation was not significantly related to whether the students had classes or not. Overall, the academic schedule is associated with SB and PA in students.

Associations of Objectively-Assessed Physical Activity and Sedentary Time with Hippocampal Gray Matter Volume in Children with Overweight/Obesity

This study investigated physical activity (PA) and sedentary time (SED) in relation to hippocampal gray matter volume (GMV) in pediatric overweight/obesity. Ninety-three children (10 ± 1 year) were classified as overweight, obesity type I, or type II–III. PA was assessed with non-dominant wrist accelerometers. GMV was acquired by magnetic resonance imaging (MRI). Neither PA nor SED associated with GMV in the hippocampus in the whole sample (p > 0.05). However, we found some evidence of moderation by weight status (p < 0.150). Moderate-to-vigorous PA (MVPA) positively associated with GMV in the right hippocampus in obesity type I (B = 5.62, p = 0.017), which remained when considering SED, light PA, and sleep using compositional data (γ = 375.3, p = 0.04). Compositional models also depicted a negative association of SED relative to the remaining behaviors with GMV in the right hippocampus in overweight (γ = −1838.4, p = 0.038). Reallocating 20 min/day of SED to MVPA was associated with 100 mm³ GMV in the right hippocampus in obesity type I. Multivariate pattern analysis showed a negative-to-positive association pattern between PA of increasing intensity and GMV in the right hippocampus in obesity type II–III. Our findings support that reducing SED and increasing MVPA are associated with greater GMV in the right hippocampus in pediatric overweight/obesity. Further studies should corroborate our findings.

Sedentary behavior patterns and adiposity in children: a study based on compositional data analysis

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%; β_ilr1 = 0.18; 95% CI: 0.01, 0.34; p = 0.040) and visceral adipose tissue (VAT; β_ilr1 = 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.

Association between objectively measured physical behaviour and neck- and/or low back pain: A systematic review

BACKGROUND AND OBJECTIVE

Clinical guidelines recommend physical activity to manage neck pain (NP) and low back pain (LBP). However, studies used to support these guidelines are based on self-reports of physical behaviour, which are prone to bias and misclassification. This systematic review aimed to investigate associations between objectively measured physical behaviour and the risk or prognosis of NP and/or LBP.

DATABASES AND DATA TREATMENT

Literature searches were performed in MEDLINE, Embase and Scopus from their inception until 18 January 2019. We considered prospective cohort studies for eligibility. Article selection, data extraction and critical appraisal were carried out by independent reviewers. Results were stratified on activity/sedentariness.

RESULTS

Ten articles out of 897 unique records identified met the inclusion criteria, of which eight studied working populations with mainly blue-collar workers. The overall results indicate that increased sitting time at work reduces the risk of NP and LBP while increased physical activity during work and/or leisure increases the risk of these conditions among blue-collar workers; however, associations were weak. Physical activity was not associated with prognosis of LBP (no studies investigated prognosis of NP). Most of the included articles have methodological shortcomings.

CONCLUSIONS

This review indicates that, among blue-collar workers, increased sitting at work may protect against NP and LBP while increased physical activity during work and/or leisure may increase this risk. There was no evidence supporting physical activity as a prognostic factor for LBP. Findings should be interpreted with caution due to the weak associations and few available studies with methodological shortcomings.

SIGNIFICANCE

Based on prospective cohort studies with objectively measured physical behaviour, this review questions the common notion that increased physical activity is associated with reduced risk or better prognosis of NP and/or LBP. We found that, among blue-collar workers, increased sitting time at work reduces the risk of NP and LBP, whereas physical activity somewhat increases the risk. Despite methodological shortcomings, there was consistency in the direction of the results, although high-quality articles reported the weakest associations. Systematic review registration: PROSPERO CRD42018100765.

Compositional Data Analysis in Time-Use Epidemiology: What, Why, How

In recent years, the focus of activity behavior research has shifted away from univariate paradigms (e.g., physical activity, sedentary behavior and sleep) to a 24-h time-use paradigm that integrates all daily activity behaviors. Behaviors are analyzed relative to each other, rather than as individual entities. Compositional data analysis (CoDA) is increasingly used for the analysis of time-use data because it is intended for data that convey relative information. While CoDA has brought new understanding of how time use is associated with health, it has also raised challenges in how this methodology is applied, and how the findings are interpreted. In this paper we provide a brief overview of CoDA for time-use data, summarize current CoDA research in time-use epidemiology and discuss challenges and future directions. We use 24-h time-use diary data from Wave 6 of the Longitudinal Study of Australian Children (birth cohort, n = 3228, aged 10.9 ± 0.3 years) to demonstrate descriptive analyses of time-use compositions and how to explore the relationship between daily time use (sleep, sedentary behavior and physical activity) and a health outcome (in this example, adiposity). We illustrate how to comprehensively interpret the CoDA findings in a meaningful way.

Compositional analysis of the associations between 24-h movement behaviours and cardio-metabolic risk factors in overweight and obese adults with pre-diabetes from the PREVIEW study: cross-sectional baseline analysis

BACKGROUND

Physical activity, sedentary time and sleep have been shown to be associated with cardio-metabolic health. However, these associations are typically studied in isolation or without accounting for the effect of all movement behaviours and the constrained nature of data that comprise a finite whole such as a 24 h day. The aim of this study was to examine the associations between the composition of daily movement behaviours (including sleep, sedentary time (ST), light intensity physical activity (LIPA) and moderate-to-vigorous activity (MVPA)) and cardio-metabolic health, in a cross-sectional analysis of adults with pre-diabetes. Further, we quantified the predicted differences following reallocation of time between behaviours.

METHODS

Accelerometers were used to quantify daily movement behaviours in 1462 adults from eight countries with a body mass index (BMI) ≥25 kg·m- 2, impaired fasting glucose (IFG; 5.6-6.9 mmol·l- 1) and/or impaired glucose tolerance (IGT; 7.8-11.0 mmol•l- 1 2 h following oral glucose tolerance test, OGTT). Compositional isotemporal substitution was used to estimate the association of reallocating time between behaviours.

RESULTS

Replacing MVPA with any other behaviour around the mean composition was associated with a poorer cardio-metabolic risk profile. Conversely, when MVPA was increased, the relationships with cardiometabolic risk markers was favourable but with smaller predicted changes than when MVPA was replaced. Further, substituting ST with LIPA predicted improvements in cardio-metabolic risk markers, most notably insulin and HOMA-IR.

CONCLUSIONS

This is the first study to use compositional analysis of the 24 h movement composition in adults with overweight/obesity and pre-diabetes. These findings build on previous literature that suggest replacing ST with LIPA may produce metabolic benefits that contribute to the prevention and management of type 2 diabetes. Furthermore, the asymmetry in the predicted change in risk markers following the reallocation of time to/from MVPA highlights the importance of maintaining existing levels of MVPA.

TRIAL REGISTRATION

ClinicalTrials.gov (NCT01777893).

Proportion of kindergarten children meeting the WHO guidelines on physical activity, sedentary behaviour and sleep and associations with adiposity in urban Beijing

Background

World Health Organisation (WHO) Guidelines on Physical Activity, Sedentary Behaviour and Sleep for Children under 5 Years of Age were released in 2019. The aim of this study was to examine the proportion of Chinese kindergarten children who met each individual guideline and each combination of the guidelines and the associations with adiposity.

Methods

Participants were 254 kindergarten children aged 4.1–6.3 years recruited from three kindergartens in urban area of Beijing. Physical activity, sedentary behaviour and sleep duration were assessed using 24-h accelerometry over three consecutive days. Screen time was reported by parents. Weight and height were measured; and children were categorised into normal weight and overweight/obese groups according to the WHO age- and sex- specific criteria. Frequency analyses were performed to examine the proportion of children meeting individual and combination of these guidelines. Logistics regression analyses were conducted to examine the associations between guideline compliance and adiposity.

Results

The proportion of children who met the physical activity (≥ 3 h daily physical activity, including ≥1 h daily moderate- to vigorous-intensity physical activity (MVPA)), sedentary screen time (< 1 h/day), and sleep guidelines (10-13 h/day) were 65.4, 88.2 and 29.5%, respectively; only 15.0% met all three guidelines and 2.7% did not meet any of the guidelines. Not meeting the physical activity guideline, sleep guideline, or combination of any two guidelines, or all three guidelines was not associated with overweight or obesity; however, children who did not meet the sedentary screen time guidelines were at higher risk for overweight and obesity (odds ratio = 3.76, 95% CI: 1.50–9.45).

Conclusions

In our study, only a small proportion of children met all three guidelines. Most Chinese kindergarten children met physical activity guidelines or screen time guidelines, whereas fewer children met sleep guideline. Not meeting sedentary screen time guidelines was associated with adiposity, which warrant further interventions for limiting screen time in young children.

The Association Between Time-Use Behaviors and Physical and Mental Well-Being in Adults: A Compositional Isotemporal Substitution Analysis

BACKGROUND

Substantial evidence links activity domains with health and well-being; however, research has typically examined time-use behaviors independently, rather than considering daily activity as a 24-hour time-use composition. This study used compositional data analysis to estimate the difference in physical and mental well-being associated with reallocating time between behaviors.

METHODS

Participants (n = 430; 74% female; 41 [12] y) wore an accelerometer for 7 days and reported their body mass index; health-related quality of life (QoL); and symptoms of depression, anxiety, and stress. Regression models determined whether time-use composition, comprising sleep, sedentary behavior, light physical activity (LPA), and moderate to vigorous physical activity (MVPA), was associated with well-being. Compositional isotemporal substitution models estimated the difference in well-being associated with reallocating time between behaviors.

RESULTS

Time-use composition was associated with body mass index and physical health-related QoL. Reallocating time to MVPA from sleep, sedentary behavior, and LPA showed favorable associations with body mass index and physical health-related QoL, whereas reallocations from MVPA to other behaviors showed unfavorable associations. Reallocations from LPA to sedentary behavior were associated with better physical health-related QoL and vice versa.

CONCLUSION

Results reinforce the importance of MVPA for physical health but do not suggest that replacing sedentary behavior with LPA is beneficial for health and well-being.

Associations between early-life screen viewing and 24 hour movement behaviours: findings from a longitudinal birth cohort study

BACKGROUND

Screen viewing is a sedentary behaviour reported to interfere with sleep and physical activity. However, few longitudinal studies have assessed such associations in children of preschool age (0-6 years) and none have accounted for the compositional nature of these behaviours. We aimed to investigate the associations between total and device-specific screen viewing time at age 2-3 years and accelerometer-measured 24 h movement behaviours, including sleep, sedentary behaviour, light physical activity, and moderate-to-vigorous physical activity (MVPA) at age 5·5 years.

METHODS

The Growing Up in Singapore Towards healthy Outcomes (GUSTO) study is an ongoing longitudinal birth cohort study in Singapore, which began in June 2009. We recruited pregnant women during their first ultrasound scan visit at two major public maternity units in Singapore. At clinic visits done at age 2-3 years, we collected parent-reported information about children's daily total and device-specific screen viewing time (television, handheld devices, and computers). At 5·5 years, children's movement behaviours for 7 consecutive days were measured using wrist-worn accelerometers. We assessed the associations between screen viewing time and movement behaviours (sedentary behaviour, light physical activity, MVPA, and sleep) using Dirichlet regression, which accounts for the compositional nature of such behaviours. This study is active but not recruiting and is registered with ClinicalTrials.gov, NCT01174875.

FINDINGS

Between June 1, 2009, and Oct 12, 2010, 1247 pregnant women enrolled and 1171 singleton births were enrolled. 987 children had parent-reported screen data at either 2 or 3 years, of whom 840 attended the clinic visit at age 5·5 years, and 577 wore an accelerometer. 552 children had at least 3 days of accelerometer data and were included in the analysis. Total screen viewing time at age 2-3 years had a significant negative association with sleep (p=0·008), light physical activity (p<0·0001), and MVPA (p<0·0001) in relation to sedentary behaviour at age 5·5 years. Compared with children who spent 1 h or less per day screen viewing at age 2-3 years, children who screen viewed for 3 h or more per day at 2-3 years engaged in more sedentary behaviour (439·8 mins per day [≤1 h screen viewing time] vs 480·0 mins per day [≥3 h screen viewing time]), and less light physical activity (384·6 vs 356·2 mins per day), and MVPA (76·2 vs 63·4 mins per day) at age 5·5 years. No significant differences in time spent sleeping were observed between the groups (539·5 vs 540·4 mins per day). Similar trends were observed for television viewing and handheld device viewing.

INTERPRETATION

Longer screen viewing time in children aged 2-3 years was associated with more time spent engaged in sedentary behaviour and shorter time engaged in light physical activity and MVPA in later childhood. Our findings indicate that screen viewing might displace physical activity during early childhood, and suggest that reducing screen viewing time in early childhood might promote healthier behaviours and associated outcomes later in life.

FUNDING

Singapore National Research Foundation, and Singapore Institute for Clinical Sciences, Agency for Science Technology and Research (A*STAR).

Are longitudinal reallocations of time between movement behaviours associated with adiposity among elderly women? A compositional isotemporal substitution analysis

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.

Introducing 24-Hour Movement Guidelines for the Early Years: A New Paradigm Gaining Momentum

Background: Emerging research shows that the composition of movement behaviors throughout the day (physical activities, sedentary behaviors, sleep) is related to indicators of health, suggesting previous research that isolated single movement behaviors maybe incomplete, misleading, and/or unnecessarily constrained. Methods: This brief report summarizes evidence to support a 24-hour movement behavior paradigm and efforts to date by a variety of jurisdictions to consult, develop, release, promote, and study 24-hour movement guidelines. It also introduces and summarizes the accompanying series of articles related specifically to 24-hour movement guidelines for the early years. Results: Using robust and transparent processes, Canada, Australia, New Zealand, South Africa, and the World Health Organization have developed and released 24-hour movement guidelines for the early years: an integration of physical activity, sedentary behavior, and sleep. Other countries are exploring a similar approach and related research is expanding rapidly. Articles related to guideline development in South Africa, the United Kingdom, Australia, and by the World Health Organization are a part of this special series. Conclusions: A new paradigm employing 24-hour movement guidelines for the early years that combines recommendations for movement behaviors across the whole day is gaining momentum across the globe.

Sedentary Behavior and Chronic Disease: Mechanisms and Future Directions

Background: Recent updates to physical activity guidelines highlight the importance of reducing sedentary time. However, at present, only general recommendations are possible (ie, “Sit less, move more”). There remains a need to investigate the strength, temporality, specificity, and dose–response nature of sedentary behavior associations with chronic disease, along with potential underlying mechanisms. Methods: Stemming from a recent research workshop organized by the Sedentary Behavior Council themed “Sedentary behaviour mechanisms—biological and behavioural pathways linking sitting to adverse health outcomes,” this paper (1) discusses existing challenges and scientific discussions within this advancing area of science, (2) highlights and discusses emerging areas of interest, and (3) points to potential future directions. Results: A brief knowledge update is provided, reflecting upon current and evolving thinking/discussions, and the rapid accumulation of new evidence linking sedentary behavior to chronic disease. Research “action points” are made at the end of each section—spanning from measurement systems and analytic methods, genetic epidemiology, causal mediation, and experimental studies to biological and behavioral determinants and mechanisms. Conclusion: A better understanding of whether and how sedentary behavior is causally related to chronic disease will allow for more meaningful conclusions in the future and assist in refining clinical and public health policies/recommendations.

The difference in sleep, sedentary behaviour, and physical activity between older adults with 'healthy' and 'unhealthy' cardiometabolic profiles: a cross-sectional compositional data analysis approach

Background

Studies have seldom used Compositional Data Analysis (CoDA) to map the effects of sleep, sedentary behaviour, and physical activity on older adults' cardio-metabolic profiles. This study therefore aimed to illustrate how sleep, sedentary behaviour, and physical activity profiles differ between older adult groups (60-89 years), with 'low' compared to those with 'high' concentrations of endocrine cardio-metabolic disease risk markers, using CoDA.

Method

Ninety-three participants (55% female) wore a thigh-mounted triaxial accelerometer for seven consecutive free-living days. Accelerometer estimates of daily average hours of engagement in sedentary behaviour (SB), standing, light-intensity physical activity (LIPA), sporadic moderate-vigorous physical activity (sMVPA, accumulated with bouts between 1 and 10 min), 10-min moderate-vigorous physical activity (₁₀MVPA, accumulated with bouts ≥10 min), in addition to self-reported sleeping hours were reported. Fasted whole blood concentrations of total cholesterol, triglyceride, glucose, and glycated haemoglobin, and serum lipoprotein lipase (LPL), interleukin-6 (IL-6), and procollagen III N-terminal propeptide were determined.

Results

Triglyceride concentration appeared to be highly dependent on ₁₀MVPA engagement as the 'low' and 'high' concentration groups engaged in 48% more and 32% less ₁₀MVPA, respectively, relative to the geometric mean of the entire study sample. Time-use composition of the 'low' LPL group's engagement in ₁₀MVPA was 26% less, while the 'high' LPL group was 7.9% more, than the entire study sample. Time-use composition of the 'high' glucose and glycated haemoglobin groups appeared to be similar as both engaged in more Sleep and SB, and less ₁₀MVPA compared to the study sample. Participants with a 'low' IL-6 concentration engaged in 4.8% more Sleep and 2.7% less ₁₀MVPA than the entire study sample. Time-use composition of the Total Cholesterol groups was mixed with the 'low' concentration group engaging in more Standing and ₁₀MVPA but less Sleep, SB, LIPA, and sMVPA than the entire study sample.

Conclusion

Older adults should aim to increase 10MVPA engagement to improve lipid profile and decrease SB engagement to improve glucose profile.

Standardised criteria for classifying the International Classification of Activities for Time-use Statistics (ICATUS) activity groups into sleep, sedentary behaviour, and physical activity

BACKGROUND

Globally, the International Classification of Activities for Time-Use Statistics (ICATUS) is one of the most widely used time-use classifications to identify time spent in various activities. Comprehensive 24-h activities that can be extracted from ICATUS provide possible implications for the use of time-use data in relation to activity-health associations; however, these activities are not classified in a way that makes such analysis feasible. This study, therefore, aimed to develop criteria for classifying ICATUS activities into sleep, sedentary behaviour (SB), light physical activity (LPA), and moderate-to-vigorous physical activity (MVPA), based on expert assessment.

METHOD

We classified activities from the Trial ICATUS 2005 and final ICATUS 2016. One author assigned METs and codes for wakefulness status and posture, to all subclass activities in the Trial ICATUS 2005. Once coded, one author matched the most detailed level of activities from the ICATUS 2016 with the corresponding activities in the Trial ICATUS 2005, where applicable. The assessment and harmonisation of each ICATUS activity were reviewed independently and anonymously by four experts, as part of a Delphi process. Given a large number of ICATUS activities, four separate Delphi panels were formed for this purpose. A series of Delphi survey rounds were repeated until a consensus among all experts was reached.

RESULTS

Consensus about harmonisation and classification of ICATUS activities was reached by the third round of the Delphi survey in all four panels. A total of 542 activities were classified into sleep, SB, LPA, and MVPA categories. Of these, 390 activities were from the Trial ICATUS 2005 and 152 activities were from the final ICATUS 2016. The majority of ICATUS 2016 activities were harmonised into the ICATUS activity groups (n = 143).

CONCLUSIONS

Based on expert consensus, we developed a classification system that enables ICATUS-based time-use data to be classified into sleep, SB, LPA, and MVPA categories. Adoption and consistent use of this classification system will facilitate standardisation of time-use data processing for the purpose of sleep, SB and physical activity research, and improve between-study comparability. Future studies should test the applicability of the classification system by applying it to empirical data.

Adiposity and changes in movement-related behaviors in older adult women in the context of the built environment: a protocol for a prospective cohort study

Background

In older adults, sedentary behaviors increase while physical activity decreases over time following the compositional nature of 24-h behaviors. These changes in movement-related behaviors (MRBs) might be associated with unhealthy weight gain and several health comorbidities. However, information is lacking on how obesity influences longitudinal changes in the composition of MRBs in older adults. Furthermore, the moderating effect of the built environment on prospective associations between obesity and MRBs in older adults is not fully understood. Therefore, using an integrated time-use approach, this study aims to identify prospective associations between obesity and MRBs together with an assessment of the moderating effect of the built environment in elderly women.

Methods

The study was designed as a prospective 7-year follow-up study. It is based on two previous cross-sectional studies that enable the use of participant data (women aged 60+ years, n = 409) as a baseline dataset in the current study. All methods designed for 7-year follow-up are based on previous studies. The data collection comprises device-based measurement of MRBs (ActiGraph GT1M accelerometer), objective assessment of body adiposity (multi-frequency bioelectrical impedance analysis), subjective assessment of the built environment (NEWS-A questionnaire), and other possible confounding factors. Time spent in sedentary behavior, light physical activity, and moderate-to-vigorous physical activity will be used as three components in a composition reflecting individual MRBs. In linear multiple compositional regression analysis assessing the prospective association between obesity and MRBs, the 7-year follow-up composition of the three mentioned components represents the dependent variable. The 7-year changes in the percentage of body fat (body adiposity), baseline composition of MRBs, and parameters of the built environment represent regressors.

Discussion

This study will use an integrated time-use approach to explore causality from obesity to device-measured behaviors in older women. The design and respective analysis consider the compositional nature of MRBs data and the potential moderating effects of various factors. A comprehensive assessment of causality may help to develop multilevel interventional models that enhance physical activity in older adults.