A systematic review of compositional data analysis studies examining associations between sleep, sedentary behaviour, and physical activity with health outcomes in adults

Associations of 24 h time-use compositions of sitting, standing, physical activity and sleeping with optimal cardiometabolic risk and glycaemic control: The Maastricht Study

AIMS/HYPOTHESIS

The associations of sitting, standing, physical activity and sleep with cardiometabolic health and glycaemic control markers are interrelated. We aimed to identify 24 h time-use compositions associated with optimal metabolic and glycaemic control and determine whether these varied by diabetes status.

METHODS

Thigh-worn activPAL data from 2388 participants aged 40-75 years (48.7% female; mean age 60.1 [SD = 8.1] years; n=684 with type 2 diabetes) in The Maastricht Study were examined. Compositional isometric log ratios were generated from mean 24 h time use (sitting, standing, light-intensity physical activity [LPA], moderate-to-vigorous physical activity [MVPA] and sleeping) and regressed with outcomes of waist circumference, fasting plasma glucose (FPG), 2 h plasma glucose, HbA1c, the Matsuda index expressed as z scores, and with a clustered cardiometabolic risk score. Overall analyses were adjusted for demographics, smoking, dietary intake and diabetes status, and interaction by diabetes status was examined separately. The estimated difference when substituting 30 min of one behaviour with another was determined with isotemporal substitution. To identify optimal time use, all combinations of 24 h compositions possible within the study footprint (1st-99th percentile of each behaviour) were investigated to determine those cross-sectionally associated with the most-optimal outcome (top 5%) for each outcome measure.

RESULTS

Compositions lower in sitting time and with greater standing time, physical activity and sleeping had the most beneficial associations with outcomes. Associations were stronger in participants with type 2 diabetes (p<0.05 for interactions), with larger estimated benefits for waist circumference, FPG and HbA1c when sitting was replaced by LPA or MVPA in those with type 2 diabetes vs the overall sample. The mean (range) optimal compositions of 24 h time use, considering all outcomes, were 6 h (range 5 h 40 min-7 h 10 min) for sitting, 5 h 10 min (4 h 10 min-6 h 10 min) for standing, 2 h 10 min (2 h-2 h 20 min) for LPA, 2 h 10 min (1 h 40 min-2 h 20 min) for MVPA and 8 h 20 min (7 h 30 min-9 h) for sleeping.

CONCLUSIONS/INTERPRETATION

Shorter sitting time and more time spent standing, undergoing physical activity and sleeping are associated with preferable cardiometabolic health. The substitutions of behavioural time use were significantly stronger in their associations with glycaemic control in those with type 2 diabetes compared with those with normoglycaemic metabolism, especially when sitting time was balanced with greater physical activity.

Time use and dimensions of healthy sleep: A cross-sectional study of Australian children and adults

BACKGROUND

Sleep is increasingly recognized as a multidimensional construct that occurs within the 24-hour day. Despite advances in our understanding, studies continue to consider the relationship between sleep, sedentary time and physical activity separately, and not as part of the 24-hour day.

AIMS

To determine the association between the 24-hour activity composition and dimensions of healthy sleep.

METHODS

This study examined data on 1168 children (mean age 12years; 49% female) and 1360 adults (mean age 44years; 87% female) collected as part of the Child Health CheckPoint study. Participants were asked to wear a GENEActiv monitor (Activinsights, Cambs, UK) on their nondominant wrist for eight consecutive days to measure 24-hour time-use. Compositional data analysis was used to examine the association between time use (actigraphy-derived sleep duration, sedentary time, light physical activity and moderate-vigorous physical activity) and dimensions of healthy sleep. Healthy sleep was conceptualized in terms of continuity/efficiency, timing, alertness/sleepiness, satisfaction/quality, and regularity. Time allocations were also examined.

RESULTS

The 24-hour activity composition was significantly associated with all objectively measured and self-report dimensions of healthy sleep in both children and adults. Allocating more time to sleep was associated with earlier sleep onsets, later sleep offsets, less efficient and more consistent sleep patterns for both children and adults.

CONCLUSION

This study highlights the integral relationship between daily activities and dimensions of sleep. Considering sleep within the 24-hour day activity composition framework may help inform lifestyle decisions to improve sleep health.

Maternal 24-h movement patterns across pregnancy and postpartum: The LIFE-Moms consortium

Objective

Time spent among the 24-h movement behaviors (physical activity [PA], sleep, sedentary behavior [SB]) in the perinatal period is important for maternal and child health. We described changes to 24-h movement behaviors and behavior guideline attainment during pregnancy and postpartum and identified correlates of behavior changes.

Methods

This secondary data analysis included the standard of care group (n = 439) from the U.S.-based Lifestyle Interventions For Expectant Moms (LIFE-Moms) consortium, including persons with overweight and obesity. Wrist-worn accelerometry was used to measure movement behaviors early (9-15 weeks) and late (35-36 weeks) pregnancy, and ∼ 1-year postpartum. Sleep and moderate-to-vigorous PA (MVPA) were compared to adult and pregnancy-specific guidelines, respectively. SB was classified into quartiles. PA and SB context were quantified using questionnaires. Mixed models were used to examine changes in behaviors and guidelines and identify correlates.

Results

Participants were 31.3 ± 3.5 years, 53.5 % were Black or Hispanic, and 45.1 % had overweight. Sleep duration decreased across time, but participants consistently met the guideline (range: 85.0-93.6 %). SB increased during pregnancy and decreased postpartum, while light PA and MVPA followed the inverse pattern. Participants met slightly fewer guidelines late pregnancy (1.2 ± 0.7 guidelines) but more postpartum (1.7 ± 0.8 guidelines) than early pregnancy (1.4 ± 0.8 guidelines). Black or Hispanic race/ethnicity, higher pregravid body mass index, and non-day work-shift (e.g., night-shift) were identified correlates of lower guideline adherence and varying PA and SB context.

Conclusion

Perinatal interventions should consider strategies to prevent SB increase and sustain MVPA to promote guideline adherence.

Changes in Accelerometer-Measured Physical Activity and Sedentary Time Across Retirement Transition as a Predictor of Self-Rated Health

BACKGROUND

Retirement transition has been shown to associate with changes in physical activity (PA) and self-rated health (SRH), but their interrelationship is less studied. The aim was to investigate changes in accelerometer-measured total PA, moderate to vigorous PA (MVPA), and sedentary time across retirement transition as a predictor of SRH.

METHODS

Data from the Swedish Retirement Study and the Finnish Retirement and Aging study were harmonized and pooled. Data from 3 waves (about 12 mo apart) were included: 1 preretirement (wave 1) and 2 postretirement follow-ups (wave 2-3). A totally of 245 participants (27% men) were included. Thigh-worn accelerometers were used to collect data for PA variables (wave 1-2), and SRH was obtained from the questionnaire (wave 1-3).

RESULTS

Between wave 1 and 2, total PA decreased with 11 (CI, -22 to -1) minutes per day, MVPA was stable (0 [CI, -3 to 3] min), and sedentary time decreased nonsignificantly with 9 (CI, -20 to 1) minutes. SRH changed between all 3 waves (all P < .001). At preretirement, 10 more minutes of MVPA was associated with greater odds of better SRH when adjusting for accelerometer wear-time, cohort, sex, age, and occupational status (odds ratio: 1.11 [95% CI, 1.02-1.22]). This association was no longer statistically significant when additionally adjusting for marital status, body mass index, and smoking. No significant associations were observed between changes in the PA variables during retirement transition and SRH at postretirement follow-ups.

CONCLUSIONS

This study showed a cross-sectional association between MVPA and greater odds of reporting better SRH before retirement. No longitudinal associations were observed between changes in the PA variables from before to after retirement and later changes in SRH.

Harmonization of three different accelerometers to classify the 24 h activity cycle

Increasing interest in measuring key components of the 24 h activity cycle (24-HAC) [sleep, sedentary behavior (SED), light physical activity (LPA), and moderate to vigorous physical activity (MVPA)] has led to a need for better methods. Single wrist-worn accelerometers and different self-report instruments can assess the 24-HAC but may not accurately classify time spent in the different components or be subject to recall errors.Objective. To overcome these limitations, the current study harmonized output from multiple complimentary research grade accelerometers and assessed the feasibility and logistical challenges of this approach.Approach. Participants (n= 108) wore an: (a) ActiGraph GT9X on the wrist, (b) activPAL3 on the thigh, and (c) ActiGraph GT3X+ on the hip for 7-10 d to capture the 24-HAC. Participant compliance with the measurement protocol was compared across devices and an algorithm was developed to harmonize data from the accelerometers. The resulting 24-HAC estimates were described within and across days.Main results. Usable data for each device was obtained from 94.3% to 96.7% of participants and 89.4% provided usable data from all three devices. Compliance with wear instructions ranged from 70.7% of days for the GT3X+ to 93.2% of days for the activPAL3. Harmonized estimates indicated that, on average, university students spent 34% of the 24 h day sleeping, 41% sedentary, 21% in LPA, and 4% in MVPA. These behaviors varied substantially by time of day and day of the week.Significance. It is feasible to use three accelerometers in combination to derive a harmonized estimate the 24-HAC. The use of multiple accelerometers can minimize gaps in 24-HAC data however, factors such as additional research costs, and higher participant and investigator burden, should also be considered.

Meeting 24-h movement behavior guidelines is linked to academic engagement, psychological functioning, and cognitive difficulties in youth with internalizing problems

BACKGROUND

This study aimed to investigate associations of meeting 24-h movement behavior (24-HMB: physical activity [PA], screen time [ST] in the school-aged youth, and sleep) guidelines with indicators of academic engagement, psychological functioning, and cognitive function in a national representative sample of U.S. youth.

METHODS

In this cross-sectional study, 1794 participants aged 6 to 17 years old were included for multivariable logistic regression to determine the above-mentioned associations, while adjusting for sociodemographic and health covariates.

RESULTS

The proportion of participants who met 24-HMB guideline(s) varied greatly (PA+ ST+ sleep = 34 [weighted 1.17 %], PA + ST = 23 [weighted 1.72 %], PA + sleep = 52 [weighted 2.15 %], PA = 34 [weighted 2.88 %], ST = 142 [weighted 7.5 %], ST+ sleep = 209 [weighted 11.86 %], sleep = 725 [weighted 35.5 %], none = 575 [weighted 37.22 %]). Participants who met ST guideline alone and integrated (ST + Sleep and ST + sleep + PA) guidelines demonstrated the consistently beneficial associations with learning interest/curiosity, caring for school performance, completing required homework, resilience, cognitive difficulties, self-regulation (ps < 0.05).

CONCLUSION

Meeting 24-HMB guidelines in an isolated or integrative manner was associated with improved academic engagement, psychological functioning, and reduced cognitive difficulties. These findings highlight the importance of the promotion of 24-HMB guidelines in youth with internalizing problems. Future longitudinal studies are needed to investigate whether changes or modifications of meeting specific 24-HMB guidelines (especially ST) is beneficial for youth with internalizing problems.

Exploring environmental cues to instigate physical movement in the workplace

Background

With the increase of sedentary jobs and the health risks associated with a sedentary lifestyle, finding novel methods to increase physical activity should be a priority. Environmental cues within the workplace can serve as cues to action for initiating light physical activity.

Aim

To qualitatively explore the environmental cues that can instigate light physical activity within an office workplace context. Identification of these cues can inform behaviour change programmes designed to promote habitual physical movement within the workplace.

Method

Purposive sampling was used to recruit full-time sedentary office workers who self-report as having a highly sedentary job. Interviews followed a semi-structured design and thematic analysis was used to explore environmental cues within commercial, home, and mixed office settings.

Results

Forty-three office workers were interviewed, 16 from a commercial office, 12 from a home office, and 15 with a flexible work arrangement whereby they worked from both a commercial and home office. The findings of this study indicate that across all three groups the main instigator of movement was influenced by office layout (e.g. getting up for beverages and taking bathroom breaks), social environment (e.g. informal and formal meetings), and taking active breaks, both job-related (e.g. printing and filing) and non-job-related (e.g. household chores).

Conclusions

These findings provide valuable insight for behaviour change programmes utilising environmental cues to inform habit-based interventions designed to instigate movement within the workplace.

Neuroscience meets behavior: A systematic literature review on magnetic resonance imaging of the brain combined with real-world digital phenotyping

A primary goal of neuroscience is to understand the relationship between the brain and behavior. While magnetic resonance imaging (MRI) examines brain structure and function under controlled conditions, digital phenotyping via portable automatic devices (PAD) quantifies behavior in real-world settings. Combining these two technologies may bridge the gap between brain imaging, physiology, and real-time behavior, enhancing the generalizability of laboratory and clinical findings. However, the use of MRI and data from PADs outside the MRI scanner remains underexplored. Herein, we present a Preferred Reporting Items for Systematic Reviews and Meta-Analysis systematic literature review that identifies and analyzes the current state of research on the integration of brain MRI and PADs. PubMed and Scopus were automatically searched using keywords covering various MRI techniques and PADs. Abstracts were screened to only include articles that collected MRI brain data and PAD data outside the laboratory environment. Full-text screening was then conducted to ensure included articles combined quantitative data from MRI with data from PADs, yielding 94 selected papers for a total of N = 14,778 subjects. Results were reported as cross-frequency tables between brain imaging and behavior sampling methods and patterns were identified through network analysis. Furthermore, brain maps reported in the studies were synthesized according to the measurement modalities that were used. Results demonstrate the feasibility of integrating MRI and PADs across various study designs, patient and control populations, and age groups. The majority of published literature combines functional, T1-weighted, and diffusion weighted MRI with physical activity sensors, ecological momentary assessment via PADs, and sleep. The literature further highlights specific brain regions frequently correlated with distinct MRI-PAD combinations. These combinations enable in-depth studies on how physiology, brain function and behavior influence each other. Our review highlights the potential for constructing brain-behavior models that extend beyond the scanner and into real-world contexts.

Cross-sectional associations between 24-hour movement behaviors and cardiometabolic health among adults with type 2 diabetes mellitus: A comparison according to weight status

OBJECTIVES

Type 2 diabetes mellitus (T2DM) is a chronic disease associated with overweight and obesity. Evidence suggests that 24-hour movement behaviors (24 h-MBs) play a crucial role in cardiometabolic health. However, it is not yet known if 24 h-MBs differ between weight status groups among people with T2DM (PwT2DM) and how 24 h-MBs are associated with their cardiometabolic health.

DESIGN

Cross-sectional study.

METHODS

Cardiometabolic variables (i.e. Body Mass Index (BMI), waist circumference (WC), HbA1c, fasting glucose, triglycerides, total-cholesterol, HDL-cholesterol, LDL-cholesterol, blood pressure) and 24 h-MBs (accelerometry and sleep-diary) of 1001 PwT2DM were collected. Regression models using compositional data analysis explored differences in 24 h-MBs between weight status groups and analyzed associations with cardiometabolic variables.

RESULTS

The 24 h-MBs of PwT2DM being obese consisted of less sleep, light physical activity (LPA) and moderate to vigorous physical activity (MVPA) and more sedentary time (ST) per day as compared to PwT2DM being overweight or normal weight (p < 0.001). Regardless of weight status, the largest associations were found when reallocating 20 min a day from ST into MVPA for BMI (-0.32 kg/m2; [-0.55; -0.09], -1.09 %), WC (-1.44 cm, [-2.26; -0.62], -1.35 %) and HDL-cholesterol (0.02 mmol/l, [0.01, 0.02], +1.59 %), as well as from ST into LPA for triglycerides (-0.04 mmol/l, [-0.05; -0.03], -2.3 %). Moreover, these associations were different when stratifying people by short-to-average (7.7 h/night) versus long sleep (9.3 h/night) period.

CONCLUSIONS

This study highlights the importance of 24 h-MBs in the cardiometabolic health of PwT2DM. Shifting time from ST and/or sleep toward LPA or MVPA might theoretically benefit cardiometabolic health among relatively inactive PwT2DM, irrespective of weight status.

Device-measured physical activity and cardiometabolic health: the Prospective Physical Activity, Sitting, and Sleep (ProPASS) consortium

BACKGROUND AND AIMS

Physical inactivity, sedentary behaviour (SB), and inadequate sleep are key behavioural risk factors of cardiometabolic diseases. Each behaviour is mainly considered in isolation, despite clear behavioural and biological interdependencies. The aim of this study was to investigate associations of five-part movement compositions with adiposity and cardiometabolic biomarkers.

METHODS

Cross-sectional data from six studies (n = 15 253 participants; five countries) from the Prospective Physical Activity, Sitting and Sleep consortium were analysed. Device-measured time spent in sleep, SB, standing, light-intensity physical activity (LIPA), and moderate-vigorous physical activity (MVPA) made up the composition. Outcomes included body mass index (BMI), waist circumference, HDL cholesterol, total:HDL cholesterol ratio, triglycerides, and glycated haemoglobin (HbA1c). Compositional linear regression examined associations between compositions and outcomes, including modelling time reallocation between behaviours.

RESULTS

The average daily composition of the sample (age: 53.7 ± 9.7 years; 54.7% female) was 7.7 h sleeping, 10.4 h sedentary, 3.1 h standing, 1.5 h LIPA, and 1.3 h MVPA. A greater MVPA proportion and smaller SB proportion were associated with better outcomes. Reallocating time from SB, standing, LIPA, or sleep into MVPA resulted in better scores across all outcomes. For example, replacing 30 min of SB, sleep, standing, or LIPA with MVPA was associated with -0.63 (95% confidence interval -0.48, -0.79), -0.43 (-0.25, -0.59), -0.40 (-0.25, -0.56), and -0.15 (0.05, -0.34) kg/m2 lower BMI, respectively. Greater relative standing time was beneficial, whereas sleep had a detrimental association when replacing LIPA/MVPA and positive association when replacing SB. The minimal displacement of any behaviour into MVPA for improved cardiometabolic health ranged from 3.8 (HbA1c) to 12.7 (triglycerides) min/day.

CONCLUSIONS

Compositional data analyses revealed a distinct hierarchy of behaviours. Moderate-vigorous physical activity demonstrated the strongest, most time-efficient protective associations with cardiometabolic outcomes. Theoretical benefits from reallocating SB into sleep, standing, or LIPA required substantial changes in daily activity.

Replacing device-measured sedentary time with physical activity is associated with lower risk of coronary heart disease regardless of genetic risk

BACKGROUND

Excess sedentary time (ST) is recognized as an important modifiable risk factor for coronary heart disease (CHD). However, whether the associations of genetic susceptibility with CHD incidence can be modified by replacing wearable-device-measured ST with physical activity (PA) is unknown.

OBJECTIVES

To examine the associations of wearable-device-measured ST replaced by PA with incident CHD across strata of genetic susceptibility.

METHODS

This study included 77,500 White British (57% female) with valid wrist-worn accelerometry and without prevalent CHD/stroke from UK Biobank. Genetic susceptibility to CHD was quantified through weighted polygenic risk scores for CHD based on 300 single-nucleotide polymorphisms. Wrist-worn accelerometer data were used to derive ST, light PA, and moderate-to-vigorous PA (MVPA).

RESULTS

Reallocation of 60 min/day of ST into the same amount of MVPA was associated with approximately 9% lower relative risk of CHD for all participants and across strata of genetic risk: replacement of 1 min/day of ST associated with <1% lower relative risk of CHD. No evidence of interaction (p: 0.784) was found between genetic risk and ST for CHD risk. Reallocating 60 min/day of ST into the same MVPA time was associated with greater absolute CHD risk reductions at high genetic risk (0.27%) versus low genetic risk (0.15%).

CONCLUSIONS

Replacing any amount of ST with an equal amount of MVPA time is associated with a lower relative risk of CHD, irrespective of genetic susceptibility to CHD. Reductions in CHD absolute risk for replacing ST with MVPA are greater at high genetic risk versus low genetic risk.

Association Between Daily Physical Education Attendance and Meeting 24-Hour Movement Guidelines in Adolescence and Adulthood

PURPOSE

To investigate the relationship between participation in physical education lessons (PELs), i.e., minutes or frequency per week, and meeting the 24-hour movement guidelines (i.e., physical activity, screen time, and sleep duration) during adolescence (12-17 years old) and adulthood (33-39 years old).

METHODS

We analyzed data from individuals who participated in Waves I (1994-1995) and V (2016-2018) of the National Longitudinal Study of Adolescent Health. We determined total weekly minutes of PELs and PELs participation by asking how many days adolescents attended PELs in an average week at school, with three possible responses as follows: 0, 1-4, or 5 days/week. Movement behaviors were assessed through self-completed questionnaires in both waves.

RESULTS

Daily PELs participation during adolescence was related to higher odds of meeting five of more weekly sessions of moderate-to-vigorous physical activity and all three guidelines in both sexes compared with adolescents who reported no days of PELs per week (men: incidence rate ratio [IRR] = 1.70, 95% CI 1.02-3.12; women: IRR = 3.81, 95% CI 1.65-8.77). Additionally, each additional weekly hour of PELs increased the likelihood of meeting all three recommendations (men: IRR = 1.11, 95% CI 1.05-1.35; women: IRR = 1.67, 95% CI 1.27-2.24). During adulthood, daily PELs was also related to a higher likelihood of meeting all three recommendations in both sexes (men: IRR = 1.04, 95% CI 1.01-1.07; women: IRR = 1.07, 95% CI 1.00-1.11). Each additional weekly hour of PELs increased the odds of meeting all three recommendations (men: IRR = 1.02, 95% CI 1.01-1.05; women: IRR = 1.03, 95% CI 1.01-1.06).

DISCUSSION

Daily PELs attendance was linked to healthy movement behaviors during adolescence, and these benefits could extend into adulthood.

The association between reallocations of time and health using compositional data analysis: a systematic scoping review with an interactive data exploration interface

BACKGROUND

How time is allocated influences health. However, any increase in time allocated to one behaviour must be offset by a decrease in others. Recently, studies have used compositional data analysis (CoDA) to estimate the associations with health when reallocating time between different behaviours. The aim of this scoping review was to provide an overview of studies that have used CoDA to model how reallocating time between different time-use components is associated with health.

METHODS

A systematic search of four electronic databases (MEDLINE, Embase, Scopus, SPORTDiscus) was conducted in October 2022. Studies were eligible if they used CoDA to examine the associations of time reallocations and health. Reallocations were considered between movement behaviours (sedentary behaviour (SB), light physical activity (LPA), moderate-to-vigorous physical activity (MVPA)) or various activities of daily living (screen time, work, household chores etc.). The review considered all populations, including clinical populations, as well as all health-related outcomes.

RESULTS

One hundred and three studies were included. Adiposity was the most commonly studied health outcome (n = 41). Most studies (n = 75) reported reallocations amongst daily sleep, SB, LPA and MVPA. While other studies reported reallocations amongst sub-compositions of these (work MVPA vs. leisure MVPA), activity types determined by recall (screen time, household chores, passive transport etc.) or bouted behaviours (short vs. long bouts of SB). In general, when considering cross-sectional results, reallocating time to MVPA from any behaviour(s) was favourably associated with health and reallocating time away from MVPA to any behaviour(s) was unfavourably associated with health. Some beneficial associations were seen when reallocating time from SB to both LPA and sleep; however, the strength of the association was much lower than for any reallocations involving MVPA. However, there were many null findings. Notably, most of the longitudinal studies found no associations between reallocations of time and health. Some evidence also suggested the context of behaviours was important, with reallocations of leisure time toward MVPA having a stronger favourable association for health than reallocating work time towards MVPA.

CONCLUSIONS

Evidence suggests that reallocating time towards MVPA from any behaviour(s) has the strongest favourable association with health, and reallocating time away from MVPA toward any behaviour(s) has the strongest unfavourable association with health. Future studies should use longitudinal and experimental study designs, and for a wider range of outcomes.

Compositional functional regression and isotemporal substitution analysis: Methods and application in time-use epidemiology

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 L 2 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.

Identifying the sociodemographic and work-related factors related to workers' daily physical activity using a decision tree approach

BACKGROUND

The social and behavioural factors related to physical activity among adults are well known. Despite the overlapping nature of these factors, few studies have examined how multiple predictors of physical activity interact. This study aimed to identify the relative importance of multiple interacting sociodemographic and work-related factors associated with the daily physical activity patterns of a population-based sample of workers.

METHODS

Sociodemographic, work, screen time, and health variables were obtained from five, repeated cross-sectional cohorts of workers from the Canadian Health Measures Survey (2007 to 2017). Classification and Regression Tree (CART) modelling was used to identify the discriminators associated with six daily physical activity patterns. The performance of the CART approach was compared to a stepwise multinomial logistic regression model.

RESULTS

Among the 8,909 workers analysed, the most important CART discriminators of daily physical activity patterns were age, job skill, and physical strength requirements of the job. Other important factors included participants' sex, educational attainment, fruit/vegetable intake, industry, work hours, marital status, having a child living at home, computer time, and household income. The CART tree had moderate classification accuracy and performed marginally better than the stepwise multinomial logistic regression model.

CONCLUSION

Age and work-related factors-particularly job skill, and physical strength requirements at work-appeared as the most important factors related to physical activity attainment, and differed based on sex, work hours, and industry. Delineating the hierarchy of factors associated with daily physical activity may assist in targeting preventive strategies aimed at promoting physical activity in workers.

Socioeconomic position as a predictor of youth's movement trajectory profiles between ages 10 and 14 years

BACKGROUND

Combinations of movement behaviors (i.e., physical activity, sedentary behavior, sleep) are associated with health and developmental outcomes in youth. Youth vary in how they accumulate these behaviors, both in volume and specific domains (e.g., sedentary time spent on recreational screen activities vs homework). The aim of this study was to examine how youth's combined general and domain-specific movement trajectories differ by socioeconomic position.

METHODS

We conducted a longitudinal, group-based multi-trajectory analysis to identify general and domain-specific movement trajectory profiles for 2457 youth from age 10 to 14 years from the Longitudinal Study of Australian Children from 2014-2018. We used multinomial logistic regression to test if socioeconomic position predicted profile membership.

RESULTS

We identified three general movement trajectory profiles for both sexes, four domain-specific profiles for males, and five for females. For general movement trajectories, females from lower socioeconomic positions were more likely to be a combination of less active and more sedentary than females from higher socioeconomic positions. Males across socioeconomic positions spend similar amounts of time in physical activity, sedentary time, and sleep. For domain-specific movement trajectories, youth from lower socioeconomic positions were likely to spend a combination of less time in education-based sedentary behavior and more time in recreational screen activities than their higher socioeconomic position peers.

CONCLUSION

Our results indicate that socioeconomic position predicted in which domains youth accumulate their movements. Future observational research and interventions targeting different socioeconomic groups should therefore consider domain-specific movement trajectories.

How do People Spend their Day? Sociodemographic Disparities in 24-hour Movement Guideline Adherence among US Adults Using 2017-2020 NHANES Data

INTRODUCTION

The 24-hour movement guidelines recommend that adults be physically active every day, get good sleep quality, and limit sedentary behavior to lower disease risk and improve quality of life. Adherence to these guidelines have not been evaluated among racially and ethnically diverse adults in the United States. The objectives were to: 1) estimate and compare the prevalence of guideline adherence among all adults and separated by age recommendations (ages 18-64; 65 + years); and 2) determine whether the odds of movement adherence differ by sociodemographics.

METHODS

Self-reported data from 2017-2020 National Health and Nutrition Examination Survey (NHANES) were analyzed (n = 9,627) using multivariate logistic regression for all adults and age stratified. Sedentary behavior was measured by minutes of sedentary activity per day (< 480 minutes adherent). Sleep was measured by hours per night (7-9 hours adherent ages 18-64; 7-8 hours adherent ages >  = 65). Physical activity was measured by minutes of recreational activity per week (150 + minutes adherent).

RESULTS

Guideline adherence among all adults was 23.7% (ages 18-64 = 26%: ages 65 +  = 14.7%). Guideline adherence was highest among non-Hispanic Asians (28.1%) and lowest among non-Hispanic Blacks (19.2%) (p = .0070). Males (25.8%) were more likely to meet movement guidelines than females (21.8%; p = .0009). In adjusted models, the odds of meeting movement guidelines were lower among non-Hispanic Blacks (OR = 0.81; 95%CI = 0.66-0.98) compared to Whites, females (OR = 0.84; 95%CI = 0.72-0.97) compared to males, and lower education (OR = 0.22; 95%CI = 0.14- 0.35) compared to adults with a college degree or higher.

RECOMMENDATION

Future interventions should be developed to improve guideline adherence tailored to particular at-risk groups.

Accelerometer-Assessed Physical Activity in People with Type 2 Diabetes: Accounting for Sleep when Determining Associations with Markers of Health

High physical activity levels during wake are beneficial for health, while high movement levels during sleep are detrimental to health. Our aim was to compare the associations of accelerometer-assessed physical activity and sleep disruption with adiposity and fitness using standardized and individualized wake and sleep windows. People (N = 609) with type 2 diabetes wore an accelerometer for up to 8 days. Waist circumference, body fat percentage, Short Physical Performance Battery (SPPB) test score, sit-to-stands, and resting heart rate were assessed. Physical activity was assessed via the average acceleration and intensity distribution (intensity gradient) over standardized (most active 16 continuous hours (M16h)) and individualized wake windows. Sleep disruption was assessed via the average acceleration over standardized (least active 8 continuous hours (L8h)) and individualized sleep windows. Average acceleration and intensity distribution during the wake window were beneficially associated with adiposity and fitness, while average acceleration during the sleep window was detrimentally associated with adiposity and fitness. Point estimates for the associations were slightly stronger for the standardized than for individualized wake/sleep windows. In conclusion, standardized wake and sleep windows may have stronger associations with health due to capturing variations in sleep durations across individuals, while individualized windows represent a purer measure of wake/sleep behaviors.

Cross-sectional and longitudinal associations of domain-specific physical activity composition with health-related quality of life in childhood and adolescence in Australia

BACKGROUND

Health benefits have been linked with physical activity (PA), as well as some domains of PA among youth (e.g. organized PA and active transport). However, less is known about whether some PA domains are more beneficial than others. There is also a lack of evidence about whether health outcomes are related to the composition of PA (i.e. the share of PA spent in different domains). This study aimed to identify: (1) how the absolute durations of organized PA, non-organized PA, active transport and active chores/work at 10-11y are individually associated with physical, psychosocial and total health-related quality of life (HRQOL) at 10-11y and 12-13y; and (2) how the domain-specific composition of PA at 10-11y is associated with HRQOL at 10-11y and 12-13y.

METHODS

Data from the Longitudinal Study of Australian Children were used in cross-sectional (n ≥ 2730) and longitudinal analyses (n ≥ 2376). Measurement included the Pediatric Quality of Life Inventory (PedsQL™) for HRQOL domains and one-day time-use diaries (TUDs) for PA domains. Robust linear regression models were used, controlling for age, sex, pubertal status, socioeconomic position, body mass index and TUD context (season and school attendance). Compositional models additionally adjusted for total PA duration and longitudinal models controlled for baseline PedsQL™ scores.

RESULTS

Non-compositional models indicated that the duration of organized PA, and to a lesser extent non-organized PA, were positively but weakly associated with some HRQOL outcomes at 10-11y. These trends were not reflected in longitudinal models, although a 30-min increase in non-organized PA per day did predict marginally better psychosocial HRQOL at 12-13y (+ 0.17%; 95%CI =  + 0.03%, + 0.32%). Compositional models revealed that a 30-min increase in organized PA relative to other domains was positively but weakly associated with physical (+ 0.32%; 95%CI =  + 0.01%, + 0.63%), psychosocial (+ 0.41%; 95%CI =  + 0.11%, + 0.72%) and total HRQOL (+ 0.39%; 95%CI =  + 0.12%, + 0.66%) at 10-11y. However, the overall PA composition at 10-11y was not related to HRQOL at 12-13y.

CONCLUSIONS

Non-compositional and compositional models generally concurred on the direction of cross-sectional and longitudinal relationships (and lack thereof) between PA domains and HRQOL outcomes. The strongest associations were cross-sectional between organized PA and HRQOL at 10-11y. However, all associations between PA domains and HRQOL outcomes were weak and may not be clinically meaningful.

Pet ownership and lifestyle behaviours of immunosuppressed individuals and their relatives in the context of COVID-19 pandemic

The COVID-19 pandemic and containment measures will likely have a detrimental impact on immunosuppressed individuals' lifestyle behaviours. Increasing evidence suggests that pet ownership is positively associated with healthier lifestyle. Yet, no study has investigated the potential benefits of pet ownership on lifestyle behaviours of immunosuppressed individuals, a population at increased risk of COVID-19 complications. This study aims to examine 1) changes in light, moderate and vigorous intensity physical activity (LPA, MPA, VPA), sedentary time (SED), and sleep duration, assessed by comparing "before COVID-19 pandemic" and "past 7 days" (i.e., current, during pandemic) self-reported behaviours in immunosuppressed individuals and their relatives; 2) to assess if changes in lifestyle behaviours are associated with pet ownership status and whether age is a moderator of these associations. A convenience sample of 132 participants (65.2% female, 41.3% ≥55 years of age) provided self-reported LPA, MPA, VPA (days/week), SED and sleep (min/day) and pet ownership status using an online questionnaire (May-August 2020). Descriptive analyses, paired T-tests, Cohen's d effect size and linear regressions were conducted. Results show that participants reported a decrease in VPA (-0.56 days/week, d = 0.34; p < 0.01) and an increase in SED (106.79 min/day, d = -0.81; p < 0.01). Stratified analysis revealed that having at least one dog, compared to not owning pets, is associated with a reduced decline in LPA, MPA and VPA and an increase in sleep in participants aged < 55 years old only. Having a dog appears to be positively associated with healthy lifestyle behaviours in younger and middle age immunosuppressed individuals.

Sleep Quality, Metabolic Function, Physical Activity, and Neurocognition Among Individuals with Resistant Hypertension

BACKGROUND

Resistant hypertension (RH) is a major risk factor for stroke, cognitive decline, and dementia. Sleep quality is increasingly suggested to play an important role linking RH to cognitive outcomes, although the mechanisms linking sleep quality to poor cognitive function have yet to be fully delineated.

OBJECTIVE

To delineate biobehavioral mechanisms linking sleep quality, metabolic function, and cognitive function among 140 overweight/obese adults with RH in the TRIUMPH clinical trial.

METHODS

Sleep quality was indexed using actigraphy measures of sleep quality and sleep fragmentation, as well as self-reported sleep quality from the Pittsburgh Sleep Quality Index (PSQI). Cognitive function was assessed using a 45-minute battery assessing executive function, processing speed, and memory. Participants were randomized to a cardiac rehabilitation-based lifestyle program (C-LIFE) or a standardized education and physician advice condition (SEPA) for 4 months.

RESULTS

Better sleep quality at baseline was associated with better executive function (B = 0.18 p = 0.027), as well as greater fitness (B = 0.27, p = 0.007) and lower HBA1c (B = -0.25, p = 0.010). Cross-sectional analyses revealed that the sleep quality executive function association was mediated by HBA1c (B = 0.71 [0.05, 2.05]). C-LIFE improved sleep quality (-1.1 [-1.5, -0.6] versus+-0.1 [-0.8, 0.7]) and actigraphy steps (+922 [529, 1316] versus+56 [-548, 661]), with actigraphy mediating improvements in executive function (B = 0.40 [0.02, 1.07]).

CONCLUSION

Better metabolic function and improved physical activity patterns levels play important roles linking sleep quality and executive function in RH.

Toward an Integrated Consideration of 24 h Movement Guidelines and Nutritional Recommendations

While physical activity, sleep and sedentary behaviors are almost always considered independently, they should be considered as integrated human behaviors. The 24 h Movement approach proposes a concomitant consideration of these behaviors to promote overall health. Not only do these behaviors impact energy expenditure, but they have also been shown to separately impact energy intake, which should be further explored when considering the entire integration of these movement behaviors under the 24 h movement approach. After an evaluation of the prevalence of meeting the 24 h Movement and dietary recommendations, this review summarizes the available evidence (using English publications indexed in PubMed/MEDLINE) regarding the association between the 24 h Movement Guidelines and eating habits. Altogether, the results clearly show the beneficial impact of promoting the 24 h guidelines simultaneously, highlighting that the higher the number of respected movement recommendations, the better eating behaviors in both children and adults. Importantly, our results point out the importance of emphasizing the need to reach sedentary guidelines for better eating habits. Movement and dietary behaviors appear closely related, and giving recommendations on one might impact the other. Combining the 24 h Movement with dietary Guidelines might be more efficient than promoting them separately in public health strategies.

Method for Activity Sleep Harmonization (MASH): a novel method for harmonizing data from two wearable devices to estimate 24-h sleep-wake cycles

Background

Daily 24-h sleep-wake cycles have important implications for health, however researcher preferences in choice and location of wearable devices for behavior measurement can make 24-h cycles difficult to estimate. Further, missing data due to device malfunction, improper initialization, and/or the participant forgetting to wear one or both devices can complicate construction of daily behavioral compositions. The Method for Activity Sleep Harmonization (MASH) is a process that harmonizes data from two different devices using data from women who concurrently wore hip (waking) and wrist (sleep) devices for ≥ 4 days.

Methods

MASH was developed using data from 1285 older community-dwelling women (ages: 60-72 years) who concurrently wore a hip-worn ActiGraph GT3X + accelerometer (waking activity) and a wrist-worn Actiwatch 2 device (sleep) for ≥ 4 days (N = 10,123 days) at the same time. MASH is a two-tiered process using (1) scored sleep data (from Actiwatch) or (2) one-dimensional convolutional neural networks (1D CNN) to create predicted wake intervals, reconcile sleep and activity data disagreement, and create day-level night-day-night pairings. MASH chooses between two different 1D CNN models based on data availability (ActiGraph + Actiwatch or ActiGraph-only). MASH was evaluated using Receiver Operating Characteristic (ROC) and Precision-Recall curves and sleep-wake intervals are compared before (pre-harmonization) and after MASH application.

Results

MASH 1D CNNs had excellent performance (ActiGraph + Actiwatch ROC-AUC = 0.991 and ActiGraph-only ROC-AUC = 0.983). After exclusions (partial wear [n = 1285], missing sleep data proceeding activity data [n = 269], and < 60 min sleep [n = 9]), 8560 days were used to show the utility of MASH. Of the 8560 days, 46.0% had ≥ 1-min disagreement between the devices or used the 1D CNN for sleep estimates. The MASH waking intervals were corrected (median minutes [IQR]: -27.0 [-115.0, 8.0]) relative to their pre-harmonization estimates. Most correction (-18.0 [-93.0, 2.0] minutes) was due to reducing sedentary behavior. The other waking behaviors were reduced a median (IQR) of -1.0 (-4.0, 1.0) minutes.

Conclusions

Implementing MASH to harmonize concurrently worn hip and wrist devices can minimizes data loss and correct for disagreement between devices, ultimately improving accuracy of 24-h compositions necessary for time-use epidemiology.

Substituting device-measured sedentary time with alternative 24-hour movement behaviours: compositional associations with adiposity and cardiometabolic risk in the ORISCAV-LUX 2 study

BACKGROUND

There is a considerable burden of sedentary time in European adults. We aimed to quantify the differences in adiposity and cardiometabolic health associated with theoretically exchanging sedentary time for alternative 24 h movement behaviours.

METHODS

This observational cross-sectional study included Luxembourg residents aged 18-79 years who each provided  ≥ 4 valid days of triaxial accelerometry (n = 1046). Covariable adjusted compositional isotemporal substitution models were used to examine if statistically replacing device-measured sedentary time with more time in the sleep period, light physical activity (PA), or moderate-to-vigorous PA (MVPA) was associated with adiposity and cardiometabolic health markers. We further investigated the cardiometabolic properties of replacing sedentary time which was accumulated in prolonged (≥ 30 min) with non-prolonged (< 30 min) bouts.

RESULTS

Replacing sedentary time with MVPA was favourably associated with adiposity, high-density lipoprotein cholesterol, fasting glucose, insulin, and clustered cardiometabolic risk. Substituting sedentary time with light PA was associated with lower total body fat, fasting insulin, and was the only time-exchange to predict lower triglycerides and a lower apolipoprotein B/A1 ratio. Exchanging sedentary time with more time in the sleep period was associated with lower fasting insulin, and with lower adiposity in short sleepers. There was no significant evidence that replacing prolonged with non-prolonged sedentary time was related to outcomes.

CONCLUSIONS

Artificial time-use substitutions indicate that replacing sedentary time with MVPA is beneficially associated with the widest range of cardiometabolic risk factors. Light PA confers some additional and unique metabolic benefit. Extending sleep, by substituting sedentary time with more time in the sleep period, may lower obesity risk in short sleepers.

The 24-Hour Movement Paradigm: An integrated approach to the measurement and promotion of daily activity in cancer clinical trials

Increased physical activity (PA), improved sleep, and decreased sedentary behavior (SB) are essential components of supportive care for cancer survivors. However, researchers and health care professionals have achieved limited success in improving these behaviors among cancer survivors. One potential reasoning is that, over the past two decades, guidelines for promoting and measuring PA, sleep, and SB have been largely siloed. With greater understanding of these three behaviors, health behavior researchers have recently developed a new paradigm: the 24-Hour movement approach. This approach considers PA, SB, and sleep as movement behaviors along a continuum that represent low through vigorous intensity activity. Together these three behaviors form the sum of an individual's movement across a 24-hour day. While this paradigm has been studied in the general population, its usage is still limited in cancer populations. Here, we seek to highlight (a) the potential benefits of this new paradigm for clinical trial design in oncology; (b) how this approach can allow for greater integration of wearable technology as a means of assessing and monitoring patient health outside the clinical setting, improving patient autonomy through self-monitoring of movement behavior. Ultimately, implementation of the 24-Hour movement paradigm will allow health behavior research in oncology to better promote and assess critical health behaviors to support the long-term well-being for cancer patients and survivors.

Analysis of the 24-h activity cycle: An illustration examining the association with cognitive function in the Adult Changes in Thought study

The 24-h activity cycle (24HAC) is a new paradigm for studying activity behaviors in relation to health outcomes. This approach inherently captures the interrelatedness of the daily time spent in physical activity (PA), sedentary behavior (SB), and sleep. We describe three popular approaches for modeling outcome associations with the 24HAC exposure. We apply these approaches to assess an association with a cognitive outcome in a cohort of older adults, discuss statistical challenges, and provide guidance on interpretation and selecting an appropriate approach. We compare the use of the isotemporal substitution model (ISM), compositional data analysis (CoDA), and latent profile analysis (LPA) to analyze 24HAC. We illustrate each method by exploring cross-sectional associations with cognition in 1,034 older adults (Mean age = 77; Age range = 65-100; 55.8% female; 90% White) who were part of the Adult Changes in Thought (ACT) Activity Monitoring (ACT-AM) sub-study. PA and SB were assessed with thigh-worn activPAL accelerometers for 7-days. For each method, we fit a multivariable regression model to examine the cross-sectional association between the 24HAC and Cognitive Abilities Screening Instrument item response theory (CASI-IRT) score, adjusting for baseline characteristics. We highlight differences in assumptions and the scientific questions addressable by each approach. ISM is easiest to apply and interpret; however, the typical ISM assumes a linear association. CoDA uses an isometric log-ratio transformation to directly model the compositional exposure but can be more challenging to apply and interpret. LPA can serve as an exploratory analysis tool to classify individuals into groups with similar time-use patterns. Inference on associations of latent profiles with health outcomes need to account for the uncertainty of the LPA classifications, which is often ignored. Analyses using the three methods did not suggest that less time spent on SB and more in PA was associated with better cognitive function. The three standard analytical approaches for 24HAC each have advantages and limitations, and selection of the most appropriate method should be guided by the scientific questions of interest and applicability of each model's assumptions. Further research is needed into the health implications of the distinct 24HAC patterns identified in this cohort.

Test-Retest Reliability and Internal Consistency of a Newly Developed Questionnaire to Assess Explanatory Variables of 24-h Movement Behaviors in Adults

A questionnaire on explanatory variables for each behavior of the 24-h movement behaviors (i.e., physical activity, sedentary behavior, sleep) was developed based on three levels of the socio-ecological model, i.e., the intrapersonal level, interpersonal level and the physical environmental level. Within these levels, different constructs were questioned, i.e., autonomous motivation, attitude, facilitators, internal behavioral control, self-efficacy, barriers, subjective norm, social modeling, social support, home environment, neighborhood, and work environment. The questionnaire was tested for test-retest reliability (i.e., intraclass correlation (ICC)) for each item and internal consistency for each construct (i.e., Cronbach's Alpha Coefficient) among a group of 35 healthy adults with a mean age of 42.9 (±16.1) years. The total questionnaire contained 266 items, consisting of 14 items on general information, 70 items on physical activity, 102 items on sedentary behavior, 45 items on sleep and 35 items on the physical environment. Seventy-one percent of the explanatory items showed moderate to excellent reliability (ICC between 0.50 and 0.90) and a majority of constructs had a good homogeneity among items (Cronbach's Alpha Coefficient ≥ 0.70). This newly developed and comprehensive questionnaire might be used as a tool to understand adults' 24-h movement behaviors.

Twenty-four-hour movement guidelines during middle adolescence and their association with glucose outcomes and type 2 diabetes mellitus in adulthood

PURPOSE

The aim of the present study was to determine the association between adherence to the 24-h movement guidelines during middle adolescence and glucose outcomes (glycated hemoglobin and fasting glucose) and type 2 diabetes mellitus (T2DM) in adulthood, 14 and 22 years later.

METHODS

We analyzed data from apparently healthy adolescents aged 12-18 years who participated in Waves I and II (1994-1996, n = 14,738), Wave IV (2008-2009, n = 8913), and Wave V (2016-2018, n = 3457) of the National Longitudinal Study of Adolescent to Adult Health (Add Health) in the United States. Physical activity, screen time, and sleep duration were measured using questionnaires, and the 24-h guidelines were defined as: 5 or more times moderate-to-vigorous physical activity per week, ≤2 h per day of screen time, and 9-11 h of sleep for 12-13 years and 8-10 h for 14-17 years. Capillary and venous whole blood was collected and analyzed to determine glycated hemoglobin and fasting glucose for Waves IV and V, respectively.

RESULTS

Only 2.1% of the adolescents met all the 3 guidelines, and 37.8% met none of them. In both waves IV and V, adolescents who met physical activity and screen time guidelines had lower odds of T2DM in adulthood than those who did not meet any of these guidelines (Wave IV; prevalence ratio (PR) = 0.57, 95% confidence interval (95%CI): 0.21-0.89; Wave V: PR = 0.43, 95%CI: 0.32-0.74). Only for Wave V did adolescents who met all 3 guidelines have lower odds of T2DM at follow-up compared with those who did not meet any of these guidelines (PR = 0.47, 95%CI: 0.24-0.91). Also, for each increase in meeting one of the 24-h recommendations, the odds of T2DM decreased by 18% (PR = 0.82, 95%CI: 0.61-0.99) and 15% (PR = 0.85, 95%CI: 0.65-0.98) in adulthood for Waves IV and V, respectively.

CONCLUSION

Promoting all 24-h movement guidelines in adolescence, especially physical activity and screen time, is important for lowering the potential risk of T2DM in adulthood.

Exploring the associations of daily movement behaviours and mid-life cognition: a compositional analysis of the 1970 British Cohort Study

BACKGROUND

Movement behaviours (eg, sedentary behaviour (SB), moderate and vigorous physical activity (MVPA), light intensity physical activity (LIPA) and sleep) are linked to cognition, yet the relative importance of each component is unclear, and not yet explored with compositional methodologies.

OBJECTIVE

To (i) assess the associations of different components of daily movement and participant's overall cognition, memory and executive function, and (ii) understand the relative importance of each individual component for cognition.

METHODS

The 1970 British Cohort Study (BCS70) is a prospective birth cohort study of UK-born adults. At age 46, participants consented to wear an accelerometer device and complete tests of verbal memory and executive function. Compositional linear regression was used to examine cross-sectional associations between 24-hour movement behaviours and standardised cognition scores. Isotemporal substitution was performed to model the effect of reallocating time between components of daily movement on cognition.

RESULTS

The sample comprised 4481 participants (52% female). Time in MVPA relative to SB, LIPA and sleep was positively associated with cognition after adjustments for education and occupational physical activity, but additional adjustment for health status attenuated associations. SB relative to all other movements was robustly positively associated with cognition. Modelling time reallocation between components revealed an increase in cognition centile after MVPA theoretically replaced 9 min of SB (OR=1.31; 95% CI 0.09 to 2.50), 7 min of LIPA (1.27; 0.07 to 2.46) or 7 min of sleep (1.20; 0.01 to 2.39).

CONCLUSIONS

Relative to time spent in other behaviours, greater MVPA and SB was associated with higher cognitive scores. Loss of MVPA time, given its smaller relative amount, appears most deleterious. Efforts should be made to preserve MVPA time, or reinforce it in place of other behaviours.

Health status of young adults with serious mental illness enrolled in integrated care

AIMS

People with serious mental illness (SMI) are more likely to develop chronic health conditions and die prematurely. Timely identification of modifiable health risk factors may enable early intervention. We aimed to describe the physical health characteristics and service utilization of young people with SMI.

METHODS

Young people with SMI enrolled in an integrated community mental health clinic (CMHC) and primary care program were assessed for physical and mental health history and past year service utilization.

RESULTS

A total of 122 participants, ages 16-35 (m = 27.0 ± 5.0 years), half male, 78.3% White were assessed. Half smoked cigarettes, half had obesity, almost half (47.5%, n = 56) had hypertension, and about a third had laboratory metabolic abnormalities. The group averaged 10.7 ± 5.1 h of sedentary behavior per day. Obesity was associated with high blood pressure, prediabetes, poor self-rated health abilities, sedentary behavior and low health satisfaction. Over half had been to the emergency department (ED) for a medical reason (55.0%, n = 66) and 24.6% had been hospitalized for a health condition in the past year. Over half had a lifetime cardiovascular risk score indicating a 50-67% chance of having a cardiovascular event; simply quitting smoking would reduce the number with this risk by almost half. Most physical health diagnoses were not recorded in the CMHC record.

CONCLUSION

Young people with SMI newly enrolled in integrated care had high rates of smoking, obesity, hypertension, and other cardio-metabolic abnormalities contributing to high risk for future disease. Research is needed to examine appealing, scalable interventions to improve health, reduce unnecessary medical care, and prevent disparate chronic disease in this group.

Association between intensity or accumulating pattern of physical activity and executive function in community-dwelling older adults: A cross-sectional study with compositional data analysis

Objective

Previous studies have suggested a positive association between physical activity (PA) and executive function in older adults. However, they did not adequately consider the compositional nature of daily time use and accumulated PA patterns. Therefore, this study aimed to examine the association between intensity or accumulated PA patterns and executive functions (inhibitory control, working memory, and cognitive flexibility) in community-dwelling older adults, considering the interaction of daily time spent in PA, sedentary behavior (SB), and sleep.

Method

This cross-sectional study used baseline data from a randomized controlled trial on the effect of exercise on cognitive function conducted between 2021 and 2022. Data from 76 community-dwelling older adults were used in the analysis. The time spent in PA and SB was assessed using an accelerometer, and sleep duration was self-reported. The Stroop task (inhibitory control), N-back task (working memory), and task-switching task (cognitive flexibility) were conducted to evaluate the subcomponents of executive function. Considering various potential confounders, compositional multiple linear regression analysis and compositional isotemporal substitution were performed to examine the association of PA with executive function and to estimate predicted changes in executive function in response to the hypothetical time-reallocation of movement behaviors, respectively.

Results

A longer time spent in light-intensity PA (LPA), relative to remaining behaviors, was associated with better Stroop task performance. Moreover, this association was stronger in LPA lasting longer than 10 min than in sporadic LPA. Additionally, theoretical 30 min/day time reallocation from SB or sleep to LPA was associated with better Stroop task performance (corresponding to approximately a 5%-10% increase). On the other hand, no significant associations of time spent in moderate- to vigorous-intensity PA with any subcomponents of executive function were observed.

Conclusion

LPA was positively associated with inhibitory control, and this association was stronger in bouts of LPA than in sporadic LPA. Moreover, reducing the time spent in SB or sleep and increasing the time spent in LPA, especially long-bout LPA, could be important measures for managing inhibitory control in late life. Future large longitudinal and intervention studies are needed to confirm these associations and reveal the causality and underlying mechanisms.

Physical activity, sedentary behaviour, and sleep in the Thai population: A compositional data analysis including 135,824 participants from two national time-use surveys

PURPOSE

To determine the amounts of time spent in physical activity (PA), sedentary behaviour (SB), and sleep in the Thai population, as well as their sociodemographic correlates and changes over time.

METHODS

We analysed cross-sectional data collected in a population-representative, stratified random sample of 135,824 Thais aged 10 years and over as part of the two most recent Thai National time-use surveys (2009 and 2015). Daily activities reported by the participants were coded using the International Classification of Activities for Time-Use Statistics (ICATUS) and categorised as PA, SB, or sleep.

RESULTS

In the latest survey, participants spent on average the largest amount of time sleeping (geometric mean [g] = 9.44 h/day; 95% confidence interval [CI]: 9.42, 9.47), followed by PA (g = 8.60 h/day; 95% CI: 8.55, 8.64) and SB (g = 5.96 h/day; 95% CI: 5.93, 6.00). The time spent in PA was higher on weekdays, while the amounts of SB and sleep were higher on weekends (p < 0.05). Males, older age groups, and unemployed people spent less time in PA and more time in SB, compared with other population groups (p < 0.05). We found a relatively large increase in SB (mean difference [d] = 39.64 min/day; 95% CI: 36.18, 42.98) and decrease in PA (d = 54.33 min/day; 95% CI: -58.88, -49.30) over time. These findings were consistent across most sociodemographic groups, with the most concerning shifts from active to sedentary lifestyle found among people with a higher education degree and on weekends.

CONCLUSIONS

Our findings revealed a shift to a more sedentary lifestyle in the Thai population. Public health interventions should focus on improving time use among males, older age groups, and unemployed people, while preventing the rapid decrease in PA and increase in SB among those with a higher education degree and on weekends.

Association between Sleep, Sedentary Time, Physical Activity, and Adiposity in Adolescents: A Prospective Observational Study

PURPOSE

This study aimed to examine the effects of substituting sedentary time with sleep or physical activity on adiposity in a longitudinal sample of adolescents.

METHODS

Adolescents (10-16 yr) were recruited for a prospective observational cohort. Parents and adolescents reported demographic characteristics and pubertal development. Accelerometry was used to measure sleep, physical activity, and sedentary time. Adiposity was quantified with imaging techniques. Isotemporal substitution modeling was conducted to examine the effect of substituting 10 min of sedentary time with sleep or differing intensities of physical activity. Results were stratified by sex and race and adjusted for covariates.

RESULTS

A total of 217 adolescents provided complete measures at both baseline and 2 yr later (58.1% White, 51.8% girls; 12.9 ± 1.9 yr at baseline). Sleep was negatively related to adiposity 2 yr later when considering other movement behaviors, but substituting baseline sedentary time with sleep was not related to future adiposity ( P > 0.05). In boys and non-White adolescents, substituting sedentary time with vigorous-intensity physical activity was related to lower adiposity 2 yr later ( P < 0.05). Substituting sedentary time for moderate- to vigorous-intensity physical activity was not associated with future adiposity.

CONCLUSIONS

Substituting sedentary time with vigorous-intensity physical activity was related to lower adiposity in later adolescence in certain groups. Opportunities to promote an adequate balance of sleep, sedentary time, and physical activity in all adolescents are encouraged for optimal development.

Adherence to 24-h Movement Guidelines and Depressive Status During the Coronavirus Disease Outbreak: A Cross-Sectional Japanese Survey

Objectives: The coronavirus disease 2019 (COVID-19) pandemic has affected people's physical activity, sedentary behavior, and sleep. This study aimed to clarify the association between combining these factors, integrated as adherence to 24-h movement guidelines, and depressive status during the COVID-19 pandemic. Methods: At the end of October 2020, we sent self-administered questionnaires to 1,711 adults aged ≥18. We assessed physical activity, sedentary behavior, sleep duration, adherence to 24-h movement guidelines, depressive status, and confounding factors. Results: Of the 640 valid responses, 90 (14.1%) reported a depressive status. Multivariable odds ratios (95% confidence interval) of depressive status were 0.22 (0.07, 0.71) for all three recommendations of the 24-h movement guidelines and those who met none of the recommendations as reference. The number of guidelines met was associated with depressive status in a dose-response fashion. Conclusion: Meeting the 24-h movement guidelines was associated with a lower prevalence of depressive status during the COVID-19 pandemic. Adults should adhere to these guidelines to maintain their mental health during future quarantine life.

Joint associations of physical activity and sedentary time with body mass index: A prospective study of mortality risk

Device-measured physical activity and sedentary time are suggested to be more important determinants of all-cause mortality compared to body mass index (BMI) in mainly older adults. However, the joint associations of physical activity and sedentary time with BMI in relation to mortality risk in relatively healthy middle-aged individuals are unclear. We followed 770 adults (56% women, mean age 55.6 years) from a population-based cohort study for up to 15.3 years. BMI categories were combined with tertiles of total, light, and moderate-to-vigorous physical activity and sedentary time. Cox proportional hazards models estimated hazard ratios (HR) of all-cause mortality with 95% confidence intervals (CI). High total and light intensity physical activity and low sedentary time were associated with a lower risk of mortality in normal weight individuals compared with low active overweight/obese; HR: 0.35 (CI: 0.14, 0.86), HR: 0.33 (CI: 0.12, 0.89), and HR: 0.34 (CI: 0.13, 0.92). Among overweight/obese individuals, those who were medium active in light physical activity had a lower mortality risk, HR: 0.36 (CI: 0.15, 0.83), compared with low active. Medium sedentary individuals had a lower risk, HR: 0.43 (CI: 0.20, 0.94) compared with those who were most sedentary. Associations among the most active or least sedentary tertiles were similar irrespective of BMI category. In conclusion, higher physical activity and lower sedentary time were associated with lower mortality risk irrespective of BMI. Physical activity should be promoted and prescribed to individuals with low physical activity levels irrespective of weight status.

Sedentary behaviour, physical activity, and sleep among office workers during the COVID-19 pandemic: a comparison of Brazil and Sweden

Background

The COVID-19 pandemic has affected the physical behaviours of office workers worldwide, but studies comparing physical behaviours between countries with similar restrictions policies are rare. This study aimed to document and compare the 24-hour time-use compositions of physical behaviours among Brazilian and Swedish office workers on working and non-working days during the pandemic.

Methods

Physical behaviours were monitored over 7 days using thigh-worn accelerometers in 73 Brazilian and 202 Swedish workers. Daily time-use compositions were exhaustively described in terms of sedentary behaviour (SED) in short (< 30 min) and long (≥30 min) bouts, light physical activity (LPA), moderate-to-vigorous physical activity (MVPA), and time-in-bed. We examined differences between countries using MANOVA on data processed according to compositional data analysis. As Swedish workers had the possibility to do hybrid work, we conducted a set of sensitivity analyses including only data from days when Swedish workers worked from home.

Results

During working days, Brazilian office workers spent more time SED in short (294 min) and long (478 min) bouts and less time in LPA (156 min) and MVPA (50 min) than Swedish workers (274, 367, 256 and 85 min, respectively). Time spent in bed was similar in both groups. Similar differences between Brazilians and Swedes were observed on non-working days, while workers were, in general, less sedentary, more active and spent more time-in-bed than during working days. The MANOVA showed that Brazilians and Swedes differed significantly in behaviours during working (p <  0.001, ηp2 = 0.36) and non-working days (p <  0.001, ηp2 = 0.20). Brazilian workers spent significantly more time in SED relative to being active, less time in short relative to long bouts in SED, and more time in LPA relative to MVPA, both during workdays and non-workdays. Sensitivity analyses only on data from days when participants worked from home showed similar results.

Conclusions

During the COVID-19 pandemic Brazilian office workers were more sedentary and less active than Swedish workers, both during working and non-working days. Whether this relates to the perception or interpretation of restrictions being different or to differences present even before the pandemic is not clear, and we encourage further research to resolve this important issue.

Trajectories of 24-h movement guidelines from middle adolescence to adulthood on depression and suicidal ideation: a 22-year follow-up study

Background:

The 24-h movement guidelines for youth and adults recommend the specific duration of physical activity, sedentary time, and sleep duration to ensure optimal health, but little is known about its relationship to mental health indicators. The aim of the study was to explore the association between 24-h movement guidelines in adolescence and its trajectories from middle adolescence (12–17 years old) to adulthood (33–39 years old) with depression and suicidal ideation in adulthood.

Methods:

This prospective cohort study included individuals who participated in Waves I (1994–1995) and V (2016–2018) of the National Longitudinal Study of Adolescent Health (Add Health) in the United States. Physical activity, screen time and sleep duration were measured using questionnaires. Adults were categorized as having depression if they had a self-reported history of depression and/or prescription medication-use for depression in the previous four weeks. Suicidal ideation was assessed by a self-reported single question in both waves. Poisson regression analyses were used to estimate the incidence rate ratio (IRR) of depression and suicidal ideation at adulthood, according to meeting specific and combinations of 24-h movement guidelines at Wave I and its trajectories from adolescence to adulthood.

Results:

The study included 7,069 individuals (56.8% women). Adolescents who met physical activity guidelines and all three guidelines at middle adolescence had lower risk of depression (IRR = 0.84, 95%CI 0.72 to 0.98) and suicidal ideation (IRR = 0.74, 95%CI 0.55 to 0.99) at adulthood than those who did not meet any of these guidelines, respectively. Individuals who met the guidelines for screen time and all three guidelines in both adolescence and adulthood had lower risk of depression (screen time, IRR = 0.87, 95% CI 0.72 to 0.98; all three, IRR = 0.37, 95% CI 0.15 to 0.92) and suicidal ideation (screen time, IRR = 0.74, 95% CI 0.51 to 0.97; all three, IRR = 0.12, 95% CI 0.06 to 0.33) than those who never met the guidelines. Additionally, individuals who did not meet all three guidelines in adolescence but met the guidelines in adulthood had lower risk of suicidal ideation than those who never met the guidelines (IRR = 0.81, 95%CI 0.45 to 0.89).

Conclusion:

Our findings highlight the importance of promoting and maintaining adherence to the 24-h movement guidelines from middle adolescence to adulthood to prevent mental health problems. However, our findings must be interpreted carefully due to declared limitations, e.g., the self-reported assessments which are subject to sources of error and bias or that the dataset used to gauge meeting a guidelines (1994–1996) was made later (2016).

Supplementary Information

The online version contains supplementary material available at 10.1186/s12966-022-01367-0.

A theory-based model of cumulative activity

Energy expenditure can be used to examine the health of individuals and the impact of environmental factors on physical activity. One of the more common ways to quantify energy expenditure is to process accelerometer data into some unit of measurement for this expenditure, such as Actigraph activity counts, and bin those measures into physical activity levels. However, accepted thresholds can vary between demographics, and some units of energy measurements do not currently have agreed upon thresholds. We present an approach which computes unique thresholds for each individual, using piecewise exponential functions to model the characteristics of their overall physical activity patterns corresponding to well established sedentary, light, moderate and vigorous activity levels from the literature. Models are fit using existing piecewise fitting techniques and software. Most participants’ activity intensity profile is exceptionally well modeled as piecewise exponential decay. Using this model, we find emergent groupings of participant behavior and categorize individuals into non-vigorous, consistent, moderately active, or extremely active activity intensity profiles. In the supplemental materials, we demonstrate that the parameters of the model correlate with demographics of age, household size, and level of education, inform behavior change under COVID lockdown, and are reasonably robust to signal frequency.

Changes in the 24-h movement behaviors during the transition to retirement: compositional data analysis

Background

Transition to retirement is shown to affect sleep, sedentary time and physical activity, but no previous studies have examined how retirement changes the distribution of time spent daily in these movement behaviors. The aim of this study was to examine longitudinally how the composition of 24-h movement behaviors changes during the transition to retirement using compositional data analysis (CoDA).

Methods

We included 551 retiring public sector workers (mean age 63.2 years, standard deviation 1.1) from the Finnish Retirement and Aging study. The study participants wore a wrist-worn ActiGraph accelerometer for one week 24 h per day before and after retirement, with one year between the measurements. The daily proportions to time spent sleeping, in sedentary behavior (SED), light physical activity (LPA) and moderate-to-vigorous physical activity (MVPA) were estimated using the GGIR package. Changes in the daily proportions of movement behaviors were examined using Compositional Data Analysis version of linear mixed models.

Results

In general, the proportion of time spent in active behaviors decreased relative to time spent in passive behaviors after retirement (p < .001). This change depended on occupation (occupation*time interaction p < .001). After retirement manual workers increased the proportions of both sleep and SED in relation to active behaviors, whereas non-manual workers increased the proportion of sleep in relation to active behaviors and SED. The proportion of MVPA decreased relatively more than the proportion of LPA (p = 0.01), independently of gender and occupation.

Conclusions

Retirement induced a decrease in the proportion of time spent in active behaviors, especially time spent in MVPA. Future studies are needed to find ways to maintain or increase daily physical activity levels at the cost of sedentary behaviors among retirees.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12966-022-01364-3.

Your best day: An interactive app to translate how time reallocations within a 24-hour day are associated with health measures

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.

Validity of the activPAL monitor to measure stepping activity and activity intensity: A systematic review

BACKGROUND

Accumulating step counts and engaging in moderate-to-vigorous intensity physical activity is positively associated with numerous health benefits. The activPAL is a thigh-worn monitor that is frequently used to measure physical activity.

RESEARCH QUESTION

Can the activPAL accurately measure stepping activity and identify physical activity intensity?

METHODS

We systematically reviewed validation studies examining the accuracy of activPAL physical activity outcomes relative to a criterion measure in adults (>18 years). Citations were not restricted to language or date of publication. Sources were searched up to May 16, 2021 and included Scopus, EMBASE, MEDLINE, CINAHL, and Academic Search Premier. The study was pre-registered in Prospero (ID# CRD42021248240). Study quality was determined using a modified Hagströmer Bowles checklist.

RESULTS

Thirty-nine studies (20 laboratory arms, 17 semi-structured arms, 11 uncontrolled protocol arms; 1272 total participants) met the inclusion criteria. Most studies demonstrated a high validity of the activPAL to measure steps across laboratory (12/15 arms), semi-structured (10/13 arms) and uncontrolled conditions (5/7 arms). Studies that demonstrated low validity were generally conducted in unhealthy populations, included slower walking speeds, and/or short walking distances. Few studies indicated that the activPAL accurately measured physical activity intensity across laboratory (0/6 arms), semi-structured (0/5 arms) and uncontrolled conditions (2/5 arms). Using the default settings, the activPAL overestimates light-intensity activity but underestimates moderate-to-vigorous intensity activity. The overall study quality was 11.5 ± 2.0 out of 19.

CONCLUSION

Despite heterogeneous methodological and statistical approaches, the included studies generally provide supporting evidence that the activPAL can accurately detect stepping activity but not physical activity intensity. Strategies that use alternative data processing methods have been developed to better characterize physical activity intensity, but all methods still underestimate vigorous-intensity activity.

Within-Person Associations Between Physical and Social Contexts With Movement Behavior Compositions in Adolescents: An Ecological Momentary Assessment Study Using a Compositional Data Analysis Approach

BACKGROUND

External contexts, including the social and physical contexts, are independent predictors of momentary physical activity and sedentary behaviors. However, no studies to date have examined how external contexts are related to overall momentary movement behavior compositions using compositional data analysis. Therefore, this study aimed to determine differences in momentary movement behavior compositions between different social and physical contexts in adolescents.

METHODS

Overall, 119 adolescents (mean age 14.7 y, SD = 1.44) provided details about their momentary physical and social contexts over 4 days using ecological momentary assessment. Sedentary behaviors, light-intensity physical activity, and moderate to vigorous physical activity were assessed using ActiGraph GT3X+ accelerometers. Compositional multivariate multilevel models were estimated to determine if movement behavior compositions differed between contexts.

RESULTS

Participants engaged in significantly less sedentary behaviors when outdoors compared with indoors and replaced it with moderate to vigorous physical activity. Participants also engaged in significantly less sedentary behaviors when with friends or friends and family and replaced it with light-intensity physical activity.

CONCLUSION

These results highlight the potential of targeting external contexts to increase physical activity and to reduce sedentary behavior in adolescents' daily lives. These factors could be targeted in mobile health and just-in-time adaptive interventions to improve young people's movement behavior compositions.

Meeting 24-h movement guidelines and markers of adiposity in adults from eight Latin America countries: the ELANS study

This study aimed to compare compliance with 24-h movement guidelines across countries and examine the associations with markers of adiposity in adults from eight Latin American countries. The sample consisted of 2338 adults aged 18-65 years. Moderate-to-vigorous physical activity (MVPA) and sedentary behavior (SB) data were objectively measured using accelerometers. Sleep duration was self-reported using a daily log. Body mass index and waist circumference were assessed as markers of adiposity. Meeting the 24-h movement guidelines was defined as ≥ 150 min/week of MVPA; ≤ 8 h/day of SB; and between 7 and 9 h/day of sleep. The number of guidelines being met was 0.90 (95% CI 0.86, 0.93) with higher value in men than women. We found differences between countries. Meeting two and three movement guidelines was associated with overweight/obesity (OR: 0.75, 95% CI 0.58, 0.97 and OR: 0.69, 95% CI 0.51, 0.85, respectively) and high waist circumference (OR: 0.74, 95% CI 0.56, 0.97 and OR: 0.77, 95% CI 0.62, 0.96). Meeting MVPA and SB recommendations were related to reduced adiposity markers but only in men. Future research is needed to gain insights into the directionality of the associations between 24-h movement guidelines compliance and markers of adiposity but also the mechanisms underlying explaining differences between men and women.

Associations of sedentary time and physical activity with adverse health conditions: Outcome-wide analyses using isotemporal substitution model

Background

As one of the most common lifestyles today, sedentary behaviour is a risk factor for many health conditions. To inform potential behavioural guideline development, we aimed to estimate the theoretical effects of replacing sedentary behaviour with different intensity of physical activity on risks of 45 common non-communicable diseases (NCDs).

Methods

A total of 360,047 participants (aged 37-73 years) in the UK Biobank free of the 45 common non-communicable diseases (NCDs) were included. Information on sedentary time (sum of television watching, computer using and driving behaviour) and physical activity (measured by International Physical Activity Questionnaire questionnaire) were collected by self-reported at baseline. Participants were followed up for 45 NCDs diagnosis according to the ICD-10 code using linkage to national health records until 2020. Isotemporal substitution models were used to investigate substituting sedentary time with light physical activity (LPA), moderate physical activity (MPA) and vigorous physical activity (VPA) after adjusting for potential confounders.

Finding

Participants who reported > 6 h/day compared with ≤ 2 h/day sedentary time had higher risks of 12 (26.7%) of 45 NCDs, including ischemic heart disease, diabetes, chronic obstructive pulmonary disease, asthma, chronic kidney disease, chronic liver disease, thyroid disorder, depression, migraine, gout, rheumatoid arthritis and diverticular disease. Theoretically, replacing sedentary time with equivalent LPA, MPA and VPA was associated with risk reductions in 4, 6 and 10 types of NCDs, respectively. Among long sedentary time (> 6 h/day), replacing 1 h/day sedentary time with equivalent VPA showed stronger associations with 5 NCDs (diabetes, depression, chronic liver disease, diverticular disease and sleep disorder), with a larger risk reduction of 11%-31%.

Interpretation

Sedentary time is associated with multiple adverse health conditions, replacing sedentary time with any equivalent amounts of VPA than LPA and MPA could be associated with risk reductions of more types of NCDs.

Funding

National Natural Science Foundation of China.

Effects of physical activity intervention on 24-h movement behaviors: a compositional data analysis

We utilized compositional data analysis (CoDA) to study changes in the composition of the 24-h movement behaviors during an activity tracker based physical activity intervention. A total of 231 recently retired Finnish retirees were randomized into intervention and control groups. The intervention participants were requested to use a commercial activity tracker bracelet with daily activity goal and inactivity alerts for 12 months. The controls received no intervention. The 24-h movement behaviors, i.e., sleep, sedentary time (SED), light physical activity (LPA), and moderate-to-vigorous physical activity (MVPA) were estimated from wrist-worn ActiGraph data using the GGIR R-package. Three balance coordinates describing the composition of movement behaviors were applied: ratio of active vs. passive behaviors, LPA vs. MVPA, and sleep vs. SED. A linear mixed model was used to study changes between the baseline and 6-month time point. Overall, the changes in the 24-h movement behaviors were small and did not differ between the groups. Only the ratio of LPA to MVPA tended to change differently between the groups (group*time interaction p = 0.08) as the intervention group increased LPA similarly to controls but decreased their MVPA. In conclusion, the use of a commercial activity tracker may not be enough to induce changes in the 24-h movement behaviors among retirees.

Validity and Reliability of the Daily Activity Behaviours Questionnaire (DABQ) for Assessment of Time Spent in Sleep, Sedentary Behaviour, and Physical Activity

Sleep, sedentary behaviour (SB), and physical activity are among key behavioural determinants of health. There is a need to evaluate questionnaires that capture movement behaviours across the full 24-h day. The aim of this study was to examine the measurement properties of the Daily Activity Behaviours Questionnaire (DABQ), a novel questionnaire (with a past seven-day recall period) for estimating the time spent in sleep, SB, light physical activity (LPA), and moderate-to-vigorous physical activity (MVPA) among adults. A sample of 126 adults was recruited. DABQ was administered to the participants on two occasions seven days apart to examine its test-retest reliability. The convergent validity of DABQ estimates was explored against activPAL4 accelerometer/inclinometer estimates. Intraclass correlation coefficients for absolute agreement and consistency between the times spent in sleep, SB, LPA, and MVPA estimated by DABQ in the test and re-test ranged from 0.59 to 0.69. Spearman’s correlations between the times spent in sleep, SB, LPA, and MVPA estimated by DABQ and activPAL4 ranged from 0.38 to 0.66. In terms of reliability and validity, DABQ is comparable with existing questionnaires; however, it has an important advantage of enabling a comprehensive assessment of all four 24-h movement behaviours. The measurement properties of DABQ make it suitable for large-scale epidemiological studies on 24-h movement behaviours.

Association between 24-h movement guidelines and cardiometabolic health in Chilean adults

This study aimed to examine the association between meeting 24-h movement guidelines and cardiometabolic health in Chilean adults. We used cross-sectional data of 2618 adults from the Chilean National Health Survey 2016–2017. Meeting the 24-h movement guidelines was defined as ≥ 600 MET-min/week of physical activity; ≤ 8 h/day of sitting time; and 7 to 9 h/day of sleep duration. Cardiometabolic health indicators were body mass index, waist circumference, high triglycerides, high blood pressure, type 2 diabetes, metabolic syndrome, and risk of cardiovascular disease in a 10-year period. Meeting none out of three 24-h movement guidelines (vs all three) was associated with higher odds of overweight/obesity (OR 1.67; 95%CI 1.45 to 1.89), high waist circumference (1.65; 1.40 to 1.90), hypertension (2.88; 2.23 to 3.53), type 2 diabetes (1.60; 1.26 to 1.94), metabolic syndrome (1.97; 1.54 to 2.40) and risk of cardiovascular disease (1.50; 1.20, 1.80). Meeting one guideline (vs three) was associated with higher odds of five of out seven cardiometabolic indicators. Our study found that the composition of movement behaviors within a 24-h period may have important implications for cardiometabolic health.