Associations of Physical Behaviours and Behavioural Reallocations with Markers of Metabolic Health: A Compositional Data Analysis

Reallocating just 10 min to moderate-to-vigorous physical activity from other components of 24-hour movement behaviors improves cardiovascular health in adults

BACKGROUND

As components of a 24-hour day, sedentary behavior (SB), physical activity (PA), and sleep are all independently linked to cardiovascular health (CVH). However, insufficient understanding of components' mutual exclusion limits the exploration of the associations between all movement behaviors and health outcomes. The aim of this study was to employ compositional data analysis (CoDA) approach to investigate the associations between 24-hour movement behaviors and overall CVH.

METHODS

Data from 581 participants, including 230 women, were collected from the 2005-2006 wave of the US National Health and Nutrition Examination Survey (NHANES). This dataset included information on the duration of SB and PA, derived from ActiGraph accelerometers, as well as self-reported sleep duration. The assessment of CVH was conducted in accordance with the criteria outlined in Life's Simple 7, encompassing the evaluation of both health behaviors and health factors. Compositional linear regression was utilized to examine the cross-sectional associations of 24-hour movement behaviors and each component with CVH score. Furthermore, the study predicted the potential differences in CVH score that would occur by reallocating 10 to 60 min among different movement behaviors.

RESULTS

A significant association was observed between 24-hour movement behaviors and overall CVH (p < 0.001) after adjusting for potential confounders. Substituting moderate-to-vigorous physical activity (MVPA) for other components was strongly associated with favorable differences in CVH score (p < 0.05), whether in one-for-one reallocations or one-for-remaining reallocations. Allocating time away from MVPA consistently resulted in larger negative differences in CVH score (p < 0.05). For instance, replacing 10 min of light physical activity (LPA) with MVPA was related to an increase of 0.21 in CVH score (95% confidence interval (95% CI) 0.11 to 0.31). Conversely, when the same duration of MVPA was replaced with LPA, CVH score decreased by 0.67 (95% CI -0.99 to -0.35). No such significance was discovered for all duration reallocations involving only LPA, SB, and sleep (p > 0.05).

CONCLUSIONS

MVPA seems to be as a pivotal determinant for enhancing CVH among general adult population, relative to other movement behaviors. Consequently, optimization of MVPA duration is an essential element in promoting overall health and well-being.

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.

Longitudinal Associations between 24-h Movement Behaviors and Cardiometabolic Biomarkers: A Natural Experiment over Retirement

INTRODUCTION

Physical activity, sedentary behavior, and sleep, that is, 24-h movement behaviors, often change in the transition from work to retirement, which may affect cardiometabolic health. This study investigates the longitudinal associations between changes in 24-h movement behaviors and cardiometabolic biomarkers during the retirement transition.

METHODS

Retiring public sector workers ( n = 212; mean (SD) age, 63.5 (1.1) yr) from the Finnish Retirement and Aging study used a thigh-worn Axivity accelerometer and filled out a diary to obtain data on daily time spent in sedentary behavior (SED), light physical activity (LPA), and moderate-to-vigorous physical activity (MVPA), and sleep before and after retirement (1 yr in-between). Cardiometabolic biomarkers, including LDL-cholesterol, HDL-cholesterol, total/HDL-cholesterol ratio, triglycerides, C-reactive protein, fasting glucose, and insulin, were measured. Associations between changes in 24-h movement behaviors and cardiometabolic biomarkers were analyzed using compositional robust regression and isotemporal substitution analysis.

RESULTS

Increasing LPA in relation to remaining behaviors was associated with an increase in HDL-cholesterol and decrease in total/HDL-cholesterol ratio ( P < 0.05 for both). For instance, reallocation of 30 min from sleep/SED to LPA was associated with an increase in HDL-cholesterol by 0.02 mmol·L -1 . Moreover, increasing MVPA in relation to remaining behaviors was associated with a decrease in triglycerides ( P = 0.02). Reallocation of 30 min from SED/sleep to MVPA was associated with 0.07-0.08 mmol·L -1 decrease in triglycerides. Findings related to LDL-cholesterol, C-reactive protein, fasting glucose, and insulin were less conclusive.

CONCLUSIONS

During the transition from work to retirement, increasing physical activity at the expense of passive behaviors was associated with a better lipid profile. Our findings suggest that life transitions like retirement could be utilized more as an optimal time window for promoting physical activity and health.

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.

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.

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.

Differentiating the influence of sedentary behavior and physical activity on brain health in late adulthood

Public health messaging calls for individuals to be more physically active and less sedentary, yet these lifestyle behaviors have been historically studied independently. Both physical activity (PA) and sedentary behavior (SB) are linked through time-use in a 24-hour day and are related to health outcomes, such as neurocognition. While the benefits of PA on brain health in late adulthood have been well-documented, the influence of SB remains to be understood. The purpose of this paper was to critically review the evolving work on SB and brain health in late adulthood and emphasize key areas of consideration to inform potential research. Overall, the existing literature studying the impact of SB on the components and mechanisms of brain health are mixed and inconclusive, provided largely by cross-sectional and observational work employing a variety of measurement techniques of SB and brain health outcomes. Further, many studies did not conceptually or statistically account for the role of PA in the proposed relationships. Therefore, our understanding of the way in which SB may influence neurocognition in late adulthood is limited. Future efforts should include more prospective longitudinal and randomized clinical trials with intentional methodological approaches to better understand the relationships between SB and the brain in late adulthood, and how these potential links are differentiated from PA.

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.

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.

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.

Time-use movement behaviors are associated with scores of depression/anxiety among adolescents: A compositional data analysis

Movement behaviors have been associated with mental health. The purposes of this study were to examine the association between movement behaviors and scores of depression/anxiety among adolescents and to determine the difference in depression/anxiety associated with reallocating time between different movement behaviors. This cross-sectional study included 217 Brazilian adolescents (15 to 18 years old, 49.3% female). Adolescents wore an accelerometer for one week to assess the four-movement behaviors which include sleep, sedentary behavior (SB), light physical activity (LPA), and moderate-to-vigorous physical activity (MVPA). The depression/anxiety score was calculated by factor analysis using the 12-item General Health Questionnaire. Compositional data analyses were used to examine the association between movement behavior and the depression/anxiety score. Compositional isotemporal substitution models estimated the change in depression/anxiety score associated with reallocating 10, 30, and 60 min between movement behaviors. The composition of movement behaviors was significantly associated with depression/anxiety scores (p < 0.05). Replacing time from SB to LPA was associated with improvement in the depression/anxiety score, while the inverse was associated with an increase in this score. Replacing time of LPA with MVPA was associated with worsening in the depression/anxiety score. The 24-h time distribution of the day may play a crucial role in mental health. Compositions with more time spent in LPA at the expense of less SB are associated with improvement in the scores of depression/anxiety. The type of MVPA may moderate its effects on depression/anxiety in adolescents. Holistic interventions including the full range of movement behaviors may be a gateway to reduce the levels of depression/anxiety in adolescence.

Revisiting the cross-sectional and prospective association of physical activity with body composition and physical fitness in preschoolers: A compositional data approach

BACKGROUND

Information is limited for the benefits of physical activity (PA) in preschoolers. Previous research using accelerometer-assessed PA may be affected for multicollinearity issues.

OBJECTIVES

This study investigated the cross-sectional and prospective associations of sedentary behaviour (SB) and PA with body composition and physical fitness using compositional data analysis.

METHODS

Baseline PA and SB were collected in 4-year-old (n = 315) using wrist-worn GT3X+ during seven 24 h-periods. Body composition (air-displacement plethysmography) and physical fitness (PREFIT test battery) were assessed at baseline and at the 12-month follow-up.

RESULTS

Increasing vigorous PA at expenses of lower-intensity behaviours for 4-year-old was associated with body composition and physical fitness at cross-sectional and longitudinal levels. For example, reallocating 15 min/day from lower intensities to vigorous PA at baseline was associated with higher fat-free mass index (+0.45 kg/m2 , 95% confidence intervals [CI]: 0.18-0.72 kg/m2 ), higher upper-body strength (+0.6 kg, 95% CI: 0.1-1.19 kg), higher lower-body strength (+8 cm, 95% CI: 3-13 cm), and shorter time in completing the motor fitness test (-0.4 s, 95% CI: -0.82 to [-0.01] s) at the 12-month follow-up. Pairwise reallocations of time indicated that the behaviour replaced was not relevant, as long as vigorous PA was increased.

CONCLUSIONS

More time in vigorous PA may imply short- and long-term benefits on body composition and physical fitness in preschoolers. These findings using compositional data analysis corroborate our previously published results using isotemporal substitution models.

A Compositional Analysis of Physical Activity, Sedentary Time, and Sleep and Associated Health Outcomes in Children and Adults with Cystic Fibrosis

This study sought to investigate the association of light physical activity (LPA), moderate-to-vigorous physical activity (MVPA), sedentary time (SED), and sleep with lung function in children and adults with CF. In total, 86 children (41 females; 13.6 ± 2.8 years; FEV1%predicted: 86 ± 1%) and 43 adults (21 females; 24.6 ± 4.7 years; FEV1%predicted: 63 ± 21%) with CF participated in this study. Wrist-worn accelerometery was used to assess PA, SED and sleep. Compositional linear regression models were conducted following normalisation via isometric log-ratio transformations. Sequential binary partitioning was applied to investigate the impact of reallocating 10 to 30 min between each behaviour on FEV1%predicted. A decline in FEV1%predicted was predicted with the reallocation of 30 min from MVPA to SED or LPA or sleep to any other behaviour in children (-3.04--0.005%) and adults (-3.58--0.005%). Conversely, improvements in FEV1%predicted were predicted when 30 min was reallocated to MVPA from LPA or SED in children (0.12-1.59%) and adults (0.77-2.10%), or when 30 min was reallocated to sleep from any other behaviour in both children (0.23-2.56%) and adults (1.08-3.58%). This study supports the importance of MVPA and sleep for maintaining and promoting lung function in people with CF.

Contrasting compositions of sitting, standing, stepping, and sleeping time: associations with glycaemic outcome by diabetes risk

BACKGROUND

Recent evidence suggests that prolonged sitting and its adverse impact on glycaemic indicators appear to be proportional to the degree of insulin resistance. To investigate this finding in a free-living context, we aimed to examine associations of device-measured 24-h time-use compositions of sitting, standing, stepping, and sleeping with fasting glucose (FPG) and 2 h post-load glucose (2hPLG) levels, and to examine separately the associations with time-use compositions among those at lower and at higher risk of developing type 2 diabetes.

METHODS

Cross-sectional analyses examined thigh-worn inclinometer data (activPAL, 7 day, 24 h/day protocol) from 648 participants (aged 36-80 years) at either lower (< 39 mmol/mol; < 5.7% HbA1c) or higher (≥39 mmol/mol; ≥5.7% HbA1c) diabetes risk from the 2011-2012 Australian Diabetes, Obesity and Lifestyle study. Multiple linear regression models were used to examine associations of differing compositions with FPG and 2hPLG, with time spent in each behaviour allowed to vary up to 60 min.

RESULTS

In general, the associations with the FPG within the time-use compositions were small, with statistically significant associations observed for sitting and sleeping (in the lower diabetes risk group) and standing (in higher diabetes risk group) only. For 2hPLG, statistically significant associations were observed for stepping only, with findings similar between lower (β = - 0.12 95%CI:-0.22, - 0.02) and higher (β = - 0.13 95%CI:-0.26, - 0.01) risk groups. Varying the composition had minimal impact on FPG; however 1 h less sitting time and equivalent increase in standing time was associated with attenuated FPG levels in higher risk only (Δ FPG% = - 1.5 95%CI: - 2.4, - 0.5). Large differences in 2hPLG were observed for both groups when varying the composition. One hour less sitting with equivalent increase in stepping was associated with attenuated 2hPLG, with estimations similar in lower (Δ 2hPLG% = - 3.8 95%CI: - 7.3, - 0.2) and higher (Δ 2hPLG% = - 5.0 95%CI: - 9.7, - 0.0) risk for diabetes.

CONCLUSIONS

In middle-aged and older adults, glycaemic control could be improved by reducing daily sitting time and replacing it with stepping. Standing could also be beneficial for those at higher risk of developing type 2 diabetes.

Standing is associated with insulin sensitivity in adults with metabolic syndrome

OBJECTIVES

To determine how components of accelerometer-measured sedentary behavior (SB) and physical activity (PA), and fitness are associated with insulin sensitivity in adults with metabolic syndrome.

DESIGN

Cross-sectional.

METHODS

Target population was middle-aged (40-65 years) sedentary adults with metabolic syndrome. SB, breaks in SB, standing, and PA were measured for four weeks with hip-worn accelerometers. VO₂max (ml/min/kg) was measured with maximal cycle ergometry. Insulin sensitivity was determined by hyperinsulinaemic-euglycaemic clamp (M-value) and fasting blood sampling (HOMA-IR, insulin). Multivariable regression was used for analyses.

RESULTS

Sixty-four participants (37 women; 58.3 [SD 6.8] years) were included. Participants spent 10.0 (1.0) h sedentary, 1.8 (0.6) h standing, and 2.7 (0.6) h in PA and took 5149 (1825) steps and 29 (8) breaks daily. In sex-, age- and accelerometer wear time-adjusted model SB, standing, steps and VO₂max were associated with M-value (β = -0.384; β = 0.400; β = 0.350; β = 0.609, respectively), HOMA-IR (β = 0.420; β = -0.548; β = -0.252; β = -0.449), and insulin (β = 0.433; β = -0.541; β = -0.252; β = -0.453); all p-values < 0.05. Breaks associated only with M-value (β = 0.277). When further adjusted for body fat %, only standing remained significantly associated with HOMA-IR (β = -0.381) and insulin (β = -0.366); significance was maintained even when further adjusted for SB, PA and fitness. Light and moderate-to-vigorous PA were not associated with insulin sensitivity.

CONCLUSIONS

Standing is associated with insulin sensitivity markers. The association with HOMA-IR and insulin is independent of adiposity, PA, SB and fitness. Further studies are warranted, but these findings encourage replacing sitting with standing for potential improvements in insulin sensitivity in adults at increased type 2 diabetes risk.

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

This systematic review determined if the composition of time spent in movement behaviours (i.e., sleep, sedentary behaviour (SED), light physical activity, and moderate-to-vigorous physical activity (MVPA)) is associated with health in adults. Five electronic databases were searched in August 2019. Studies were eligible for inclusion if they were peer-reviewed, examined community-dwelling adults, and used compositional data analysis to examine the associations between the composition of time spent in movement behaviours and health outcomes. Eight studies (7 cross-sectional, 1 prospective cohort) of >12 000 unique participants were included. Findings indicated that the 24-h movement behaviour composition was associated with all-cause mortality (1 of 1 analyses), adiposity (4 of 4 analyses), and cardiometabolic biomarkers (8 of 15 analyses). Reallocating time into MVPA from other movement behaviours was associated with favourable changes to most health outcomes and taking time out of SED and reallocating it into other movement behaviours was associated with favourable changes to all-cause mortality. The quality of evidence was very low for all health outcomes. In conclusion, these findings support the notion that the composition of movement across the entire 24-h day matters, and that recommendations for sleep, SED, and physical activity should be combined into a single public health guideline. (PROSPERO registration no.: CRD42019121641.) Novelty The 24-h movement behaviour composition is associated with a variety of health outcomes. Reallocating time into MVPA is favourably associated with health. Reallocating time out of SED is associated with favourable changes to mortality risk.

Association of daily composition of physical activity and sedentary behaviour with incidence of cardiovascular disease in older adults

BACKGROUND

Moderate-to-vigorous physical activity (MVPA) is proposed as key for cardiovascular diseases (CVD) prevention. At older ages, the role of sedentary behaviour (SB) and light intensity physical activity (LIPA) remains unclear. Evidence so far is based on studies examining movement behaviours as independent entities ignoring their co-dependency. This study examines the association between daily composition of objectively-assessed movement behaviours (MVPA, LIPA, SB) and incident CVD in older adults.

METHODS

Whitehall II accelerometer sub-study participants free of CVD at baseline (N = 3319, 26.7% women, mean age = 68.9 years in 2012-2013) wore a wrist-accelerometer from which times in SB, LIPA, and MVPA during waking period were extracted over 7 days. Compositional Cox regression was used to estimate the hazard ratio (HR) for incident CVD for daily compositions of movement behaviours characterized by 10 (20 or 30) minutes greater duration in one movement behaviour accompanied by decrease in another behaviour, while keeping the third behaviour constant, compared to reference composition. Analyses were adjusted for sociodemographic, lifestyle, cardiometabolic risk factors and multimorbidity index.

RESULTS

Of the 3319 participants, 299 had an incident CVD over a mean (SD) follow-up of 6.2 (1.3) years. Compared to daily movement behaviour composition with MVPA at recommended 21 min per day (150 min/week), composition with additional 10 min of MVPA and 10 min less SB was associated with smaller risk reduction - 8% (HR, 0.92; 95% CI, 0.87-0.99) - than the 14% increase in risk associated with a composition of similarly reduced time in MVPA and more time in SB (HR, 1.14; 95% CI, 1.02-1.27). For a given MVPA duration, the CVD risk did not differ as a function of LIPA and SB durations.

CONCLUSIONS

Among older adults, an increase in MVPA duration at the expense of time in either SB or LIPA was found associated with lower incidence of CVD. This study lends support to public health guidelines encouraging increase in MVPA or at least maintain MVPA at current duration.

Physical Activity Intensity and Type 2 Diabetes: Isotemporal Substitution Models in the "Seguimiento Universidad de Navarra" (SUN) Cohort

Which intensity of physical activity (PA) is associated with type 2 diabetes (T2D) prevention remains unclear. Isotemporal substitution models assess the relationship of replacing the amount of time spent in one activity for another. We aimed to assess T2D incidence associated with light-to-moderate physical activity (LMPA) and vigorous physical activity (VPA) using isotemporal substitution models of one hour (1 h) sitting by 1 h of LMPA or VPA. Furthermore, we evaluated the effect on T2D of an isotemporal substitution of 1 h sitting by 1 h of slow (light physical activity) or brisk–very brisk walking (moderate physical activity). In total, 20,060 participants (both sexes) of the SUN cohort (Spain) initially free of T2D followed-up during a median of 12 years were included. Cox regression models were fitted to assess the association between the substitution of 1 h LMPA, VPA, slow and brisk–very brisk pace by 1 h sitting and T2D. The replacement of 1 h sitting time by 1 h of VPA was associated with an adjusted HR of 0.52 (95% CI: 0.34–0.80), not observed for the substitution by 1 h of LMPA (HR 0.93; 95% CI: 0.73–1.20). An apparent inverse association was observed for the replacement of 1 h sitting time by 1 h of brisk/very brisk walking (HR: 0.69; 95% CI: 0.46–1.04), not observed by 1 h of slow pace. From equal conditions of duration and frequency of PA, the higher the intensity of PA, the greater the T2D prevention.

Modelling the Reallocation of Time Spent Sitting into Physical Activity: Isotemporal Substitution vs. Compositional Isotemporal Substitution

Isotemporal substitution modelling (ISM) and compositional isotemporal modelling (CISM) are statistical approaches used in epidemiology to model the associations of replacing time in one physical behaviour with time in another. This study’s aim was to use both ISM and CISM to examine and compare associations of reallocating 60 min of sitting into standing or stepping with markers of cardiometabolic health. Cross-sectional data collected during three randomised control trials (RCTs) were utilised. All participants (n = 1554) were identified as being at high risk of developing type 2 diabetes. Reallocating 60 min from sitting to standing and to stepping was associated with a lower BMI, waist circumference, and triglycerides and higher high-density lipoprotein cholesterol using both ISM and CISM (p < 0.05). The direction and magnitude of significant associations were consistent across methods. No associations were observed for hemoglobin A1c, total cholesterol, or low-density lipoprotein cholesterol for either method. Results of both ISM and CISM were broadly similar, allowing for the interpretation of previous research, and should enable future research in order to make informed methodological, data-driven decisions.

School-Time Movement Behaviors and Fundamental Movement Skills in Preschoolers: An Isotemporal Reallocation Analysis

Little is known of how reallocations of time spent in different movement behaviors during preschool might relate to preschoolers' fundamental movement skills (FMS), a key predictor of later physical activity (PA). Thus, the aim of this study was to examine (a) whether preschoolers' school-time movement was associated with their FMS and (b) the effects on FMS of reallocating time between PA and sedentary behavior (SB). This was a cross-sectional study, using intervention data with Brazilian low-income preschoolers. We observed Brazilian preschoolers of both sexes (M_age = 4.5, SD = 0.8 years-old; 101boys) over 10 hours of school-time and objectively assessed their PA and SB with Actigraph wGT3X and their FMS with the Test of Gross Motor Development - Second Edition. We explored the associations between school-time movement behaviors and FMS and between reallocated school-time movement behaviors and FES using compositional analysis in R (version 1.40-1), robCompositions (version 0.92-7), and lmtest (version 0.9-35) packages. This isotemporal reallocation showed that, for manipulative skills, reallocating time (5, 10, and 15 minutes, respectively) from light PA to SB was associated with increasing skill (0.14, 0.28, and 0.42 FMS units), raising questions as to whether fine motor activity occurred during SB. Thus, school-time movement significantly predicted FMS, with a modest increase in SB, at the expense of light PA eliciting improved manipulative skills.

Intensity Matters for Musculoskeletal Health: A Cross-Sectional Study on Movement Behaviors of Older Adults from High-Income Scottish and Low-Income South African Communities

This study aimed to investigate differences in physical activity (PA) patterns and the associations between objectively measured 24-h movement behaviors and musculoskeletal measures (muscle strength, muscle mass, physical performance, and bone mineral density) in a high-income and a low-income community. This cross-sectional study recruited independent living older adults aged 60-85 years from high-income Scottish (n = 150) and low-income South African (n = 138) settings. Participants completed demographic and health questionnaires, and testing included body composition and bone mineral density (dual energy X-ray absorptiometry), physical performance (grip strength, gait speed), and PA (accelerometry). Participants accumulated similar amounts of weekly total PA, however, the Scottish cohort engaged in more moderate-to-vigorous intensity PA (MVPA) and sedentary behavior (SB), while the South African cohort spent more time sleeping and in light intensity PA (LPA). From compositional data analysis, more time spent in MVPA relative to the other movement behaviors was positively associated with higher muscle mass (p < 0.001) and strength (p = 0.001) in the Scottish cohort. Conversely, more time spent in MVPA was associated with faster gait speed (p < 0.001) and greater hip bone mineral density (p = 0.011) in the South African cohort. Our findings confirm the beneficial role of MVPA in both high- and low-income cohorts, however, the relationship MVPA had with components of musculoskeletal health in older adults differed between settings.

GRANADA consensus on analytical approaches to assess associations with accelerometer-determined physical behaviours (physical activity, sedentary behaviour and sleep) in epidemiological studies

The inter-relationship between physical activity, sedentary behaviour and sleep (collectively defined as physical behaviours) is of interest to researchers from different fields. Each of these physical behaviours has been investigated in epidemiological studies, yet their codependency and interactions need to be further explored and accounted for in data analysis. Modern accelerometers capture continuous movement through the day, which presents the challenge of how to best use the richness of these data. In recent years, analytical approaches first applied in other scientific fields have been applied to physical behaviour epidemiology (eg, isotemporal substitution models, compositional data analysis, multivariate pattern analysis, functional data analysis and machine learning). A comprehensive description, discussion, and consensus on the strengths and limitations of these analytical approaches will help researchers decide which approach to use in different situations. In this context, a scientific workshop and meeting were held in Granada to discuss: (1) analytical approaches currently used in the scientific literature on physical behaviour, highlighting strengths and limitations, providing practical recommendations on their use and including a decision tree for assisting researchers’ decision-making; and (2) current gaps and future research directions around the analysis and use of accelerometer data. Advances in analytical approaches to accelerometer-determined physical behaviours in epidemiological studies are expected to influence the interpretation of current and future evidence, and ultimately impact on future physical behaviour guidelines.

24-hour movement behaviors and fitness in preschoolers: A compositional and isotemporal reallocation analysis

This study analyzed the associations between the 24-hour movement behaviors composition and fitness in preschoolers and investigated predicted changes in fitness when time in active behaviors is reallocated. This cross-sectional study was carried out with 270 preschoolers (132 boys; 3.97 ± 0.80 years-old). Light and moderate-to-vigorous physical activity (LPA and MVPA), and sedentary behavior (SB) were verified using an accelerometer. Sleep time was obtained through interviews with parents. Components of physical fitness (cardiorespiratory fitness-CRF, speed-agility, and lower-body muscular strength) were assessed using the PREFIT Battery. To verify the association between 24-hour movement behaviors and physical fitness, the compositional analysis was used, and for the time reallocation, the compositional isotemporal substitution analysis was used for active behaviors (LPA and MVPA). The daily composition, adjusted for body mass index, sex, and age, was significantly associated with CRF (P = .007; r²  = 0.29), speed-agility (P < .001; r²  = 0.14), and lower-body muscular strength (P = .01; r²  = 0.07). For CRF, the addition of MVPA, at the expense of any other behavior, was associated with significant improvements. For speed-agility and lower-body muscular strength, only reallocations between sleep and LPA yielded significant associations. The variation in CRF, speed-agility, and lower-body muscular strength was associated with the 24 hours movement composition, and reallocating 5, 10 or 15 minutes of SB or sleep for MVPA was significantly positive for CRF (P < .05). The present findings highlight the relevance of decreasing SB and increasing physical activity practice, particularly at high intensities, to promote a better CRF profile for preschoolers.

Time-Based Data in Occupational Studies: The Whys, the Hows, and Some Remaining Challenges in Compositional Data Analysis (CoDA)

Data on the use of time in different exposures, behaviors, and work tasks are common in occupational research. Such data are most often expressed in hours, minutes, or percentage of work time. Thus, they are constrained or ‘compositional’, in that they add up to a finite sum (e.g. 8 h of work or 100% work time). Due to their properties, compositional data need to be processed and analyzed using specifically adapted methods. Compositional data analysis (CoDA) has become a particularly established framework to handle such data in various scientific fields such as nutritional epidemiology, geology, and chemistry, but has only recently gained attention in public and occupational health sciences. In this paper, we introduce the reader to CoDA by explaining why CoDA should be used when dealing with compositional time-use data, showing how to perform CoDA, including a worked example, and pointing at some remaining challenges in CoDA. The paper concludes by emphasizing that CoDA in occupational research is still in its infancy, and stresses the need for further development and experience in the use of CoDA for time-based occupational exposures. We hope that the paper will encourage researchers to adopt and apply CoDA in studies of work exposures and health.

Are Reallocations between Sedentary Behaviour and Physical Activity Associated with Better Sleep in Adults Aged 55+ Years? An Isotemporal Substitution Analysis

Physical activity has been proposed as an effective alternative treatment option for the increasing occurrence of sleep problems in older adults. Although higher physical activity levels are associated with better sleep, the association between specific physical activity intensities and sedentary behaviour (SB) with sleep remains unclear. This study examines the associations of statistically modelled time reallocations between sedentary time and different physical activity intensities with sleep outcomes using isotemporal substitution analysis. Device-measured physical activity data and both objective and subjective sleep data were collected from 439 adults aged 55+ years. Replacing 30 min of SB with moderate to vigorous intensity physical activity (MVPA) was significantly associated with an increased number of awakenings. Moreover, a reallocation of 30 min between light physical activity (LPA) and MVPA was significantly associated with increased sleep efficiency. Furthermore, reallocating 30 min of SB to LPA showed a significant association with decreased sleep efficiency. There were no significant associations of time reallocations for wake time after sleep onset, length of awakenings, and sleep quality. These results improve our understanding of the interrelationships between different intensities of movement behaviours and several aspects of sleep in older adults.

Associations between multiple positive health behaviors and cardiometabolic risk using 3 alternative measures of physical activity: NHANES 2005-2006

The study aimed to investigate the association between clustered cardiometabolic risk (CCMR) and health-behavior indices comprising 3 different measures of physical activity, screen time, diet and sleep in NHANES 2005-2006. CCMR was calculated by standardizing and summarizing measures of blood pressure, fasting glucose, triglycerides, insulin, high-density lipoprotein and waist circumference to create a z score. Three health behavior indices were constructed with a single point allocated to each of the following lower risk behaviors: muscle strengthening activity, healthy eating score, sleep disorder/disruption, sleep duration, screen time and physical activity (self-reported moderate-to-vigorous physical activity [MVPA] (Index Score-SR), accelerometer-measured MVPA (Index Score-MVPA) or accelerometer-measured steps Index Score-Steps). Linear regression models explored associations between index scores and CCMR. In the sample (n = 1537, 52% male, aged 45.5 [SE: 0.9] years), reporting 0-5 vs. 6 health behaviors using Index Score-SR and Index Score-MVPA, and 0-4 vs. 6 health behaviors using Index Score-Steps, were associated with a significantly higher CCMR. The beta (β [95% CI]) for zero vs. 6 behaviors were Index Score-SR (2.86 [2.02, 3.69], Index Score-MVPA (2.41 [1.49, 3.33] and Index Score-Steps (2.41 [1.68, 3.15]). Irrespective of the measure of physical activity, engaging in fewer positive health behaviors was associated with greater CCMR. Novelty: Physical activity, screen time, diet and sleep may exert synergistic/cumulative effects on clustered cardiometabolic risk. A greater number of positive health behaviors was associated with a lower clustered cardiometabolic risk factor score. The reduction in cardiometabolic risk was similar irrespective of which physical activity measure was used.

Prospectively Reallocating Sedentary Time: Associations with Cardiometabolic Health

PURPOSE

This study aimed to investigate whether prospectively reallocating time away from sedentary behavior (SB) into different physical activity intensities is associated with 12-month change to cardiometabolic health in a cohort at high risk of type 2 diabetes (T2DM).

METHODS

Participants with known risk factors for T2DM were recruited from primary care (Leicestershire, United Kingdom) as part of the Walking Away from Type 2 Diabetes trial (n = 808). Participants were followed up at 12, 24, and 36 months. SB, light-intensity physical activity (LPA) and moderate-to-vigorous intensity physical activity (MVPA) were measured objectively by accelerometer. Postchallenge glucose, triglycerides, HDL cholesterol, systolic blood pressure, and waist circumference were analyzed individually and combined into a clustered cardiometabolic risk score (CMRS). Associations of changing SB over each consecutive 12-month period were analyzed taking account of repeated measures.

RESULTS

Reallocating 30 min from SB to LPA was associated with 0.21-cm (95% confidence interval, 0.03-0.38 cm) reduction in waist circumference, 0.09-mmol·L (0.04-0.13 mmol·L) reduction in 2-h glucose, 0.02-mmol·L (0.00-0.04 mmol·L) reduction in triglycerides, and 0.02 (0.01-0.03) reduction in CMRS. Every 30-min reallocation from SB to MVPA was associated with 1.23-cm (0.68-1.79 cm) reduction in waist circumference, 0.23-mmol·L (0.10-0.36 mmol·L) reduction in 2-h glucose, 0.04-mmol·L (0.00-0.09 mmol·L) reduction in triglycerides, and 0.07 (0.04-0.11) reduction in CMRS. Reallocating 30 min from LPA into MVPA was also associated with 1.02-cm (0.43-1.60 cm) reduction in waist circumference, 0.16-mmol·L (0.02-0.30 mmol·L) reduction in 2-h glucose, and 0.05 (0.01-0.09) reduction in CMRS.

CONCLUSION

Over 12 months, reallocating time away from SB into LPA or MVPA was associated with improved cardiometabolic health in a population at risk of T2DM, with the greatest benefits observed for MVPA.

Does sedentary time increase in older adults in the days following participation in intense exercise?

BACKGROUND

Older adults have the highest sedentary time across all age groups, and only a small portion is meeting the minimum recommendations for weekly physical activity. Little research to date has looked at how changes in one of these behaviours influences the other.

AIM

To assess changes in 24-h movement behaviours (sedentary time, light intensity physical activity (LPA), moderate-vigorous PA (MVPA) and sleep) over three consecutive days, following acute bouts of exercise of varying intensity in older adults.

METHODS

Participants (n = 28, 69.7 ± 6.5 years) completed a maximal exercise test and the following exercise protocols in random order: moderate continuous exercise (MOD), high-intensity interval exercise (HI) and sprint interval exercise (SPRT). A thigh-worn device (ActivPAL™) was used to measure movement behaviours at baseline and the 3 days following each exercise session.

RESULTS

Repeated measures analysis of variance indicated that compared to baseline, participants decreased MVPA in the 3 days following all exercise sessions and decreased LPA following HI and SPRT (p < 0.05). Over half of the sample had clinically meaningful increases in sedentary time (30 min/day) in the days following exercise participation.

DISCUSSION

Older adults who compensate for exercise participation by reducing physical activity and increasing sedentary time in subsequent days may require behavioural counseling to ensure that incidental and recreational physical activities are not reduced.

CONCLUSION

It appears that older adults compensate for acute exercise by decreasing MVPA and LPA, and increasing sedentary time in the days following exercise. Future research is needed to determine whether compensation persists with regular engagement.

Comparing 24 h physical activity profiles: Office workers, women with a history of gestational diabetes and people with chronic disease condition(s)

This study demonstrates a novel data-driven method of summarising accelerometer data to profile physical activity in three diverse groups, compared with cut-point determined moderate-to-vigorous physical activity (MVPA). GGIR was used to generate average daily acceleration, intensity gradient, time in MVPA and MX metrics (acceleration above which the most active X-minutes accumulate) from wrist-worn accelerometer data from three datasets: office-workers (OW, N = 697), women with a history of post-gestational diabetes (PGD, N = 267) and adults with ≥1 chronic disease (CD, N = 1,325). Average acceleration and MVPA were lower in CD, but not PGD, relative to OW (-5.2 mg and -30.7 minutes, respectively, P < 0.001). Both PGD and CD had poorer intensity distributions than OW (P < 0.001). Application of a cut-point to the M30 showed 7%, 17% and 28%, of OW, PGD and CD, respectively, accumulated 30 minutes of brisk walking per day. Radar plots showed OW had higher overall activity than CD. The relatively poor intensity distribution of PGD, despite similar overall activity to OW, was due to accumulation of more light and less higher intensity activity. These data-driven methods identify aspects of activity that differ between groups, which may be missed by cut-point methods alone. Abbreviations: CD: Adults with ≥1 chronic disease; mg: Milli-gravitational unit; MVPA: Moderate-to-vigorous physical activity; OW: Office workers; PGD: Women with a history of post-gestational diabetes; VPA: Vigorous physical activity.

Associations of physical activity and sedentary behavior with cardiometabolic biomarkers in prediabetes and type 2 diabetes: a compositional data analysis

Objectives: To investigate the associations between objectively measured sedentary behavior (SB), light-intensity physical activity (LIPA) and moderate-to-vigorous physical activity (MVPA) and cardiometabolic and endocrine biomarkers, and to estimate the associations of reallocating time from one behavior to another with cardiometabolic and endocrine biomarkers.Methods: Baseline data from participants diagnosed with prediabetes or type 2 diabetes, n = 175, 58% men, mean (SD) age = 64.4 (7.7), recruited to a physical activity intervention was used. Time spent in SB, LIPA and MVPA was measured by accelerometer and transformed into isometric log-ratio coordinates. The associations between time spent in SB, LIPA and MVPA and biomarkers were examined by linear regression models. The change in each outcome of reallocating time between the three behaviors was estimated.Results: The findings show strong positive associations of time spent in MVPA and negative associations of time spent in SB relative to time spent in the other behaviors with sagittal abdominal diameter (SAD) and homeostasis model assessment for insulin resistance (HOMA-IR) and negative associations of time spent in SB with high-density lipoprotein (HDL) cholesterol. Theoretically, reallocation of 19 minutes MVPA to SB or to LIPA was associated with a 17% and 17% larger SAD, 39% and 36% larger HOMA-IR values and 3.3% and 2.3% lower levels of HDL, respectively.Conclusion: In conclusion, our analysis from a time-use perspective supports the current evidence that sedentary time is devastating for the cardiometabolic health. While LIPA probably requires more time, maintaining or increasing time in MVPA are the most important features of the time use behaviors when promoting a favorable cardiometabolic risk profile in adults with prediabetes and type 2 diabetes.Trial registration: ClinicalTrials.gov, NCT02374788. Registered 2 March 2015 - Retrospectively registered, https://clinicaltrials.gov/ct2/show/NCT02374788.

Biohumoral Indicators Influenced by Physical Activity in the Elderly

In the scientific landscape, there is a growing interest in defining the role of several biomolecules and humoral indicators of the aging process and in the modifications of these biomarkers induced by physical activity and exercise. The main aim of the present narrative review is to collect the available evidence on the biohumoral indicators that could be modified by physical activity (PA) in the elderly. Online databases including Pubmed, Web of science (Medline), and Scopus were searched for relevant articles published in the last five years in English. Keywords and combination of these used for the search were the following: “biological”, “indicators”, “markers”, “physical”, “activity”, and “elderly”. Thirty-four papers were analyzed for inclusion. Twenty-nine studies were included and divided into four categories: cardiovascular (CV) biomarkers, metabolic biomarkers, inflammatory markers-oxidative stress molecules, and other markers. There are many distinct biomarkers influenced by PA in the elderly, with promising results concerning the metabolic and CV indexes, as a growing number of studies demonstrate the role of PA on improving parameters related to heart function and CV risk like atherogenic lipid profile. Furthermore, it is also a verified hypothesis that PA is able to modify the inflammatory status of the subject by decreasing the levels of pro-inflammatory cytokines, including interleukin-1 (IL-1), interleukin-6 (IL-6), and tumor necrosis factor-alpha (TNF-α). PA seems also to be able to have a direct effect on the immune system. There is a strong evidence of a positive effect of PA on the health of elderly people that could be evidenced and “quantified” by the modifications of the levels of several biohumoral indicators.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

TRIAL REGISTRATION

ClinicalTrials.gov (NCT01777893).

Isotemporal substitution of inactive time with physical activity and time in bed: cross-sectional associations with cardiometabolic health in the PREDIMED-Plus study

BACKGROUND

This study explored the association between inactive time and measures of adiposity, clinical parameters, obesity, type 2 diabetes and metabolic syndrome components. It further examined the impact of reallocating inactive time to time in bed, light physical activity (LPA) or moderate-to-vigorous physical activity (MVPA) on cardio-metabolic risk factors, including measures of adiposity and body composition, biochemical parameters and blood pressure in older adults.

METHODS

This is a cross-sectional analysis of baseline data from 2189 Caucasian men and women (age 55-75 years, BMI 27-40 Kg/m2) from the PREDIMED-Plus study (http://www.predimedplus.com/). All participants had ≥3 components of the metabolic syndrome. Inactive time, physical activity and time in bed were objectively determined using triaxial accelerometers GENEActiv during 7 days (ActivInsights Ltd., Kimbolton, United Kingdom). Multiple adjusted linear and logistic regression models were used. Isotemporal substitution regression modelling was performed to assess the relationship of replacing the amount of time spent in one activity for another, on each outcome, including measures of adiposity and body composition, biochemical parameters and blood pressure in older adults.

RESULTS

Inactive time was associated with indicators of obesity and the metabolic syndrome. Reallocating 30 min per day of inactive time to 30 min per day of time in bed was associated with lower BMI, waist circumference and glycated hemoglobin (HbA1c) (all p-values < 0.05). Reallocating 30 min per day of inactive time with 30 min per day of LPA or MVPA was associated with lower BMI, waist circumference, total fat, visceral adipose tissue, HbA1c, glucose, triglycerides, and higher body muscle mass and HDL cholesterol (all p-values < 0.05).

CONCLUSIONS

Inactive time was associated with a poor cardio-metabolic profile. Isotemporal substitution of inactive time with MVPA and LPA or time in bed could have beneficial impact on cardio-metabolic health.

TRIAL REGISTRATION

The trial was registered at the International Standard Randomized Controlled Trial (ISRCTN: http://www.isrctn.com/ISRCTN89898870) with number 89898870 and registration date of 24 July 2014, retrospectively registered.

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

BACKGROUND

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

METHOD

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

RESULTS

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

CONCLUSIONS

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

Sedentary Behavior and Prostate Cancer: A Systematic Review and Meta-Analysis of Prospective Cohort Studies

Prostate cancer is the second most common cancer in men worldwide, and sedentary behavior is widespread, yet reviews and meta-analyses summarizing the role of sedentary behavior as a potential risk factor for prostate cancer are scarce. We searched PubMed, Web of Science, and Cochrane databases for relevant articles up to January 2019. We pooled maximally adjusted risk estimates in a random effects model and performed meta-regression meta-analysis, assessed heterogeneity and publication bias using I², funnel plots, and Egger and Begg tests, and conducted sensitivity analyses and influence diagnostics. Data from 12 prospective cohort studies including a total of 30,810 prostate cancer cases were analyzed. We found no statistically significant association between high versus low sedentary behavior and prostate cancer incidence [RR = 1.07; 95% confidence interval (CI), 0.99-1.16; P = 0.10]. We noted that adjustment for body mass index (BMI) modified the relation of sedentary behavior to prostate cancer, particularly aggressive cancer. Sedentary behavior was related to a statistically significant increased risk of aggressive prostate cancer in analyses not adjusted for BMI (RR = 1.21; 95% CI, 1.03-1.43), whereas no association was apparent in BMI-adjusted analyses (RR = 0.98; 95% CI, 0.90-1.07), and the difference between those summary risk estimates was statistically significant (P _difference = 0.02). Sedentary behavior is not independently associated with prostate cancer. However, prolonged sedentary behavior may be related to increased risk of aggressive prostate cancer through a mechanism involving obesity. This finding represents a potentially important step toward considering sedentary behavior as a modifiable behavioral risk factor for aggressive prostate cancer.

Associations of Sensor-Derived Physical Behavior with Metabolic Health: A Compositional Analysis in the Record Multisensor Study

Previous studies about the effects of physical activity and sedentary behaviors on health rarely recorded the exact body postures and movements, although they might be of metabolic relevance. Moreover, few studies treated the time budget of behaviors as compositions and little was done to characterize the distribution of durations of behavior sequences in relation with health. Data from the RECORD (Residential Environment and CORonary heart Disease) study of two combined VitaMove accelerometers worn at the trunk and upper leg for a week by 154 male and female adults (age = 50.6 ± 9.6 years, BMI = 25.8 ± 3.9 kg/m²) were analyzed. Using both iso-temporal substitution and compositional analysis, we examined associations between five physical behaviors (lying, sitting, standing, low physical activity, moderate-to-vigorous activity) and seven health outcomes (fasting serum glucose, low- and high-density lipoprotein, and triglycerides levels, body mass index, and waist circumference). After adjustment for confounding variables, total standing time was positively associated with better lipid profile, and lying during the day with adiposity. No significant association was observed between breaking up moderate-to-vigorous physical activity and health. This study highlights the importance of refined categories of postures in research on physical activity and health, as well as the necessity for new tools to characterize the distribution of behavior sequence durations, considering both bouts and micro-sequences.