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

The pleasure of moving: A compositional data analysis of the association between replacing sedentary time with physical activity on affective valence in daily life

Although the independent within-person association between physical activity and sedentary behaviour with valence in daily life has been extensively studied, few studies have used compositional data analysis to examine how different movement behaviour compositions are related to valence in daily life. This study aimed to examine the within-person association between wake-time movement behaviour compositions with affective valence and the extent to which replacing time spent sedentary with physical activity was associated with valence within individuals in daily life. A 7-day ecological momentary study design was used whereby 94 Canadian university students (Mage = 19.45, SD = 2.21, 78.7 % female) reported on affective valence using an adapted version of the Feeling Scale at 7 randomly timed prompts each day. In addition, activPAL accelerometers were worn continuously by participants on their right thigh for the duration of the study to determine time spent engaging in sedentary behaviours and physical activity. Compositional data analysis with isotemporal substitution models were used to examine the within-person association between movement behaviour compositions and affective valence. The within-person association between movement behaviours and affective valence was weak (r2 = 0.013). Nevertheless, engaging in less sedentary time than usual and instead engaging in physical activity was significantly related to more positive affective valence. Considering light intensity physical activity (LPA) and moderate-to-vigorous intensity physical activity (MVPA) separately, replacing time spent sedentary with time engaged in MVPA and LPA both had a significant positive association on affective valence, although the association with MVPA was stronger than the association with LPA. The results provide unique insights into how replacing sedentary time with physical activity in daily life, especially MVPA, may be associated with more feelings of pleasure. These results may be useful to help inform the development of just-in-time adaptive interventions.

Analytic Methods for Understanding the Temporal Patterning of Dietary and 24-H Movement Behaviors: A Scoping Review

Dietary and movement behaviors [physical activity (PA), sedentary behavior (SED), and sleep] occur throughout a 24-h day and involve multiple contexts. Understanding the temporal patterning of these 24-h behaviors and their contextual determinants is key to determining their combined effect on health. A scoping review was conducted to identify novel analytic methods for determining temporal behavior patterns and their contextual correlates. We searched Embase, ProQuest, and EBSCOhost databases in July 2022 to identify studies published between 1997 and 2022 on temporal patterns and their contextual correlates (e.g., locational, social, environmental, personal). We included 14 studies after title and abstract (n = 33,292) and full-text (n = 135) screening, of which 11 were published after 2018. Most studies (n = 4 in adults; n = 5 in children and adolescents), examined waking behavior patterns (i.e., both PA and SED) of which 3 also included sleep and 6 included contextual correlates. PA and diet were examined together in only 1 study of adults. Contextual correlates of dietary, PA, and sleep temporal behavior patterns were also examined. Machine learning with various clustering algorithms and model-based clustering techniques were most used to determine 24-h temporal behavior patterns. Although the included studies used a diverse range of methods, behavioral variables, and assessment periods, results showed that temporal patterns characterized by high SED and low PA were linked to poorer health outcomes, than those with low SED and high PA. This review identified temporal behavior patterns, and their contextual correlates, which were associated with adiposity and cardiometabolic disease risk, suggesting these methods hold promise for the discovery of holistic lifestyle exposures important to health. Standardized reporting of methods and patterns and multidisciplinary collaboration among nutrition, PA, and sleep researchers; statisticians; and computer scientists were identified as key pathways to advance future research on temporal behavior patterns in relation to health.

Exploring Associations Between Device-Based Occupational Sedentary Behavior and Need for Recovery in White Collar Workers: A Compositional Data-Analysis

Objectives

White collar workers spend an increasing amount of time in occupational sedentary behavior (OSB) and are thereby at risk for adverse health outcomes. Nevertheless, the association between OSB and the need for recovery (NFR), an important indicator of wellbeing, is unknown and therefore examined.

Methods

Baseline data from a cluster randomized controlled trial was used. A subgroup of 89 white collar workers wore a triaxial accelerometer for 7 days. NFR was measured using the Questionnaire on the Experience and Evaluation of Work. Compositional data analysis was applied to determine the composition of different OSB bouts (short, medium and long) and occupational physical activity (OPA) (light, moderate and vigorous and standing). Linear regression analyses were performed to explore the associations between occupational compositions and NFR.

Results

Relatively more time spent in long OSB bouts was associated with a lower NFR (β: -11.30, 95% CI: -20.2 to -2.4). Short and medium OSB bouts and OPA were not associated with NFR.

Conclusion

Associations between OSB bouts, OPA and NFR hinted at contrasting trends, suggesting the need to consider different bout lengths of OSB in future studies.

The associations of chronic pain and 24-h movement behaviors with incident mental disorders: evidence from a large-scale cohort study

BACKGROUND

Chronic pain was associated with a higher risk of mental disorders (e.g., depression and anxiety). However, the role of 24-h movement behaviors in the association remains unclear.

METHODS

A total of 72,800 participants with accelerometer data and free of mental disorders from the UK Biobank were analyzed. The compositional mediation model and isotemporal substitution model were used to explore the associations between chronic pain, 24-h movement behaviors, and the incidence of overall mental disorders, depression, and anxiety.

RESULTS

With a median follow-up of 13.36 years, participants with chronic pain had a higher rate of incident overall mental disorders (hazard ratio (HR): 1.281, 95% confidence interval (CI): 1.219 to 1.344), anxiety (HR: 1.391, 95% CI: 1.280 to 1.536), and depression (HR: 1.703, 95% CI: 1.551 to 1.871). Increased sedentary behavior (SB) and reduced moderate-to-vigorous physical activity (MVPA) caused by chronic pain both increased the risk of mental disorders. Twenty-four-hour movement behaviors explained the relationship between chronic pain and overall mental disorders, depression, and anxiety by 10.77%, 5.70%, and 6.86%, respectively. Interaction effects were found between MVPA and chronic pain when predicting the incidence of depression and between MVPA, sleep (SLP), and chronic pain when predicting the incidence of mental disorders. People with chronic pain would recommend at least 0.5 h per day of MVPA and 7 h per day of SLP and restricting SB below 11.5 h per day.

CONCLUSIONS

Twenty-four-hour movement behaviors played a significant mediating role in the association between chronic pain and mental disorders. Individuals with chronic pain should engage in more MVPA, less sedentary behavior, and have 7-h sleep per day.

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.

Movement behaviour typologies and their associations with adiposity indicators in children and adolescents: a latent profile analysis of 24-h compositional data

OBJECTIVES

Growing evidence supports the important role of 24-hour movement behaviours (MB) in preventing childhood obesity. However, research to understand the heterogeneity and variability of MB among individuals and what kind of typologies of individuals are at risk of developing obesity is lacking. To bridge this gap, this study identified typologies of 24-hour MB in children and adolescents and investigated their associations with adiposity indicators.

METHODS

In this cross-sectional study, 374 children and 317 adolescents from the Czech Republic wore wrist-worn accelerometers for seven consecutive days. Time spent in moderate-to-vigorous physical activity (MVPA), light physical activity (LPA), sedentary behaviour (SB), and sleep was quantified using raw accelerometery data. Adiposity indicators included body mass index (BMI) z-score, fat mass percentage (FM%), fat mass index (FMI), and visceral adipose tissue (VAT). Bias-adjusted latent profile analysis was used on the 24-hour MB data to identify MB typologies and their associations with adiposity indicators. The models were adjusted for potential confounders. The identified typologies were labelled to reflect the behavioural profiles of bees to aid interpretability for the general public.

RESULTS

Two typologies were identified in children: highly active Workers characterised by high levels of MVPA and LPA, and inactive Queens characterised by low levels of MVPA and LPA, high levels of SB and longer sleep duration compared to Workers. In adolescents, an additional typology labelled as Drones was characterised by median levels of MVPA, LPA, SB and longest sleep duration. After controlling for covariates, we found that children labelled as Queens were associated with 1.38 times higher FM%, 1.43 times higher FMI, and 1.67 times higher VAT than Workers. In adolescents, Drones had 1.14 times higher FM% and Queens had 1.36 higher VAT in comparison with Workers, respectively.

CONCLUSION

Our study highlights the importance of promoting active lifestyles in children and adolescents to potentially reduce adiposity. These findings can provide insights for interventions aimed at promoting healthy MB and preventing childhood obesity.

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.

Is patients' activities of daily living self-care score in Norwegian home care a proxy for workers standing at work?

BACKGROUND

Prolonged standing at work may contribute to increased risk of musculoskeletal pain in home care workers. Patients' activities of daily living (ADL) score may be a proxy for home care workers' standing time at work. The objective of the present study was to investigate the association between patients' ADL self-care score, and workers standing time.

METHODS

This cross-sectional study measured time spent standing, sitting and in physical activity for seven days using thigh-worn accelerometers, among 14 home care workers. Patients' ADL self-care scores are routinely adjusted by home care nurses, and time intervals of home care visits are stored in home care services electronic patient journal. We collected ADL self-care scores and start and end time points of visits, and categorized ADL self-care scores as low (ADL ≤ 2.0), medium (ADL > 2.0 to 3.0) or high (ADL > 3.0). Physical behavior data were transformed to isometric log-ratios and a mixed-effect model was used to investigate differences in physical behavior between the three ADL self-care score categories.

RESULTS

We analyzed 931 patient visits and found that high ADL self-care scores were associated with longer standing times relative to sitting and physical activity, compared to low ADL score (0.457, p = 0.001). However, no significant differences in time spent standing were found between high and medium ADL patient visits (0.259, p = 0.260), nor medium and low (0.204, p = 0.288). High ADL score patients made up 33.4% of the total care time, despite only making up 7.8% of the number of patients.

CONCLUSION

Our findings suggest that caring for patients with high ADL self-care score requires workers to stand for longer durations and that this group of patients constitute a significant proportion of home care workers' total work time. The findings of this study can inform interventions to improve musculoskeletal health among home care workers by appropriate planning of patient visits.

Cross-sectional association between 24-hour movement guidelines and depressive symptoms in Chinese university students

Background

The world's first 24-h movement guidelines for adults were released on 15 October 2020 in Canada, though evidence of their associations with health indicators in young adults is sparse. This study aimed to report the prevalence of meeting the 24-h movement guidelines and associations with depressive symptoms in a sample of Chinese university students.

Methods

Cross-sectional data from 1,793 Chinese university students (mean age = 20.7 years, 63.6% female) were used. Sociodemographic information, movement behaviors (physical activity, sedentary behavior, and sleep duration), and depressive symptoms were collected using a self-reported questionnaire.

Results

The prevalence of meeting the 24-h movement guidelines was 27.8% in Chinese university students. Logistic regression results show that compared to those who met the 24-h movement guidelines, odds ratio (OR) for depressive symptoms in those who met fewer recommendations contained in the 24-h movement guidelines were significantly higher (OR for none = 3.4, 95% CI [2.1-5.5], p < 0.001; OR for one = 2.7, 95% CI [2.0-3.8], p < 0.001; OR for two = 1.5, 95% CI [1.1-2.1], p = 0.013).

Conclusion

The prevalence of meeting the 24-h movement guidelines in Chinese university students was relatively low and should be enhanced through multiple strategies. Meeting the 24-h movement guidelines was associated with lower risk for depression in Chinese young adults. It is suggested that moving more, sitting less and sleeping well in this population may reduce the occurrence of depression.

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.

Behavior reallocations within 24-h movement profiles and change in cardiometabolic biomarkers during pregnancy

OBJECTIVE

The goal of this study was to investigate associations of reallocations within 24-h movement profiles and changes in cardiometabolic biomarkers from early to late pregnancy.

METHODS

In 137 individuals with prepregnancy overweight/obesity, waking movement was measured using wrist-worn accelerometers, sleep was self-reported, and biomarkers were measured in fasting serum samples at 12 and 32 weeks' gestation. We used compositional isotemporal substitution models.

RESULTS

On average, biomarkers increased 21%-83% across pregnancy. For those with guideline-recommended moderate/vigorous-intensity physical activity (MVPA) in early pregnancy, reallocating 30 min from MVPA to sleep, sedentary behavior, or light-intensity physical activity (LPA) was associated with a 0.6 mmol/L greater increase in total cholesterol (95% CI: -0.1 to 1.2) and a 0.7 mmol/L greater increase in low-density lipoprotein (LDL) cholesterol (95% CI: 0.1 to 1.3) from early to late pregnancy. For those with low MVPA in early pregnancy, reallocating 30 min from sleep, sedentary behavior, or LPA to MVPA was associated with a 0.6 mmol/L lower increase in total cholesterol (95% CI: -1.3 to 0.1) and a 0.8 mmol/L lower increase in LDL cholesterol (95% CI: -1.4 to -0.1) from early to late pregnancy. There were no associations with change in glucose, insulin, homeostatic model assessment for insulin resistance, very low-density lipoprotein, or high-density lipoprotein cholesterol, triglycerides, or free fatty acids.

CONCLUSIONS

Maintaining or achieving a 24-h movement profile with guideline-recommended amounts of MVPA may be beneficial for reducing pregnancy-induced increases in total and LDL cholesterol.

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.

Associations between Parental Educational Attainment, Children's 24-h Behaviors and Children's Hyperactivity Behavior in the COVID-19 Pandemic

BACKGROUND

Parental Educational Attainment and children's 24-h behaviors significantly influenced children's hyperactivity symptoms. This study aimed to examine the mediating role of children's 24-h behavior changes due to the COVID-19 pandemic between Parental Educational Attainment and children's hyperactivity index. It also aimed to investigate the associations between Children's Physical Activity, digital media use, sleep, and hyperactivity index between two clusters of Parental Educational Attainments. The goal was to provide targeted behavioral optimization recommendations for caregivers to reduce the risk of children's hyperactivity.

METHODS

The study was a collaborative extension of the International iPreschooler Surveillance Study Among Asians and otheRs project and the Chinese Children and Adolescent Sports Health Promotion Action Project. The Parent-Surveillance of Digital Media in Childhood Questionnaire® and the Abbreviated Rating Scales from the Conners Parent Symptom Questionnaire were used to measure Parental Educational Attainment, children's behavior changes during the COVID-19 pandemic, and hyperactivity indexes. A total of 11,190 parents of 6-to-12-year-old children completed the online surveys in mainland China. A structural equation model was established by using Smart-PLS, and the linear regression model, and isotemporal substitution models were established by using a Compositional Data Analysis package with R program to achieve the research objectives.

RESULTS

Changes in children's 24-h behaviors due to the COVID-19 pandemic had a significant mediation effect on the negative associations between Parental Educational Attainment and children's hyperactivity index (β = 0.018, T = 4.521, p < 0.001) with a total effect (β = -0.046, T = 4.521, p < 0.001) and a direct effect (β = -0.064, T = 6.330, p < 0.001). Children's Digital Media use was significantly and negatively associated with hyperactivity index among all children. Reallocated time from digital media use to both sleep and physical activity decreased the hyperactivity index, and vice-versa. For parents without tertiary education (R2 = 0.09, p < 0.001), sleep was significantly and negatively associated with the hyperactivity index (βilr-CSL = -0.06, p < 0.001); for parents with tertiary education (R2 = 0.07, p < 0.001), physical activity was significantly and negatively associated with the hyperactivity index (βilr-CPA = -0.05, p < 0.001), and sleep was significantly and positively associated with the hyperactivity index (βilr-CSL = 0.03, p < 0.001). A significant increase in the hyperactivity index was detected when physical activity time was reallocated to sleep, with a significant decrease in the opposite direction.

CONCLUSIONS

Parental Educational Attainment and children's 24-h behaviors directly influenced children's hyperactivity index. However, a purposeful and targeted optimization of children's 24-h behaviors-namely, physical activity, digital media use, and sleep-could assist parents with different educational attainments to reduce their children's hyperactivity index and mitigate the risk of hyperactivity.

Reallocating desk workers' sitting time to standing or stepping: associations with work performance

BACKGROUND

Studies have suggested that sitting time at work may lead to underperformance but they may underestimate the benefits to desk workers' performance of reducing occupational sitting time without considering the relative effects of the specific activities replaced.

AIMS

To estimate differences in work performance (presenteeism, absenteeism and engagement) when occupational sitting time is reallocated to standing/stepping in desk workers.

METHODS

Data for middle-aged desk workers were from a Japan-wide online survey (n = 2228). Self-report proportion of occupational sitting and standing/stepping, work hours and work performance indicators, including absolute (ratings relating only to self) and relative (ratings of self, compared to others) presenteeism and absenteeism, and dimensions of work engagement, were collected. Partition and isotemporal substitution models were used to investigate the associations of occupational sitting and standing/stepping time with work performance, including their reallocation effects.

RESULTS

In partition models, longer occupational sitting time was associated with a lower absolute presenteeism score (i.e. less productivity), lower absolute absenteeism (i.e. longer-than-expected work hours), and lower engagement. Longer occupational standing/stepping time was associated with lower absolute absenteeism and more engagement. Isotemporal substitution models showed that each hour of occupational sitting reallocated to standing/stepping was favourably associated with overall work engagement (B = 0.087; 95% confidence interval 0.051, 0.122) and its dimensions (B ranged from 0.078 to 0.092), but was not associated with presenteeism or absenteeism.

CONCLUSIONS

These findings suggest that management support and practical initiatives to encourage desk workers to replace portions of their sitting time with standing/stepping may contribute to enhanced work engagement.

The whole day matters after stroke: Study protocol for a randomized controlled trial investigating the effect of a 'sit less, move more, sleep better' program early after stroke

BACKGROUND

Movement-related behaviours, including prolonged sedentary behaviour, physical inactivity, and poor sleep, are associated with worse functional outcomes poststroke. Addressing these co-dependent behaviours early after stroke may help to optimize recovery and improve overall quality of life for individuals with stroke.

OBJECTIVE

This study aims to determine the feasibility and effect of a 'sit less, move more, sleep better' program early after stroke on functional mobility and global disability outcomes, while also exploring imaging and behavioural markers that may influence walking recovery.

METHODS

The study is an assessor-blinded, single-center, parallel-group, randomized controlled trial to be completed within 24 months from July 12, 2023 to June 30, 2025. We will enroll 50 patients with acute ischemic stroke within 7 days from symptom onset, aged 18 years or older, and with ongoing walking goals. Demographic and stroke characteristics, including stroke risk factors, neuroimaging, and acute stroke treatments, will be determined and documented. All participants will wear an accelerometer for one week at three different time-points (baseline, 6, and 12 weeks) to assess movement-related behaviours. Following randomization, participants in the intervention arm will receive a 'sit less, move more, sleep better' program for up to 1 hour/day, 5 days/week, for 6 weeks to enhance self-efficacy for change. Participants in the control arm will receive usual inpatient and early supported stroke discharge care. The feasibility outcomes will include reach (enrolled/eligible), retention (completed/enrolled), adverse events, and program adherence. Other outcomes at 6 and 12 weeks include the modified Rankin Scale, Timed-Up and Go, movement-related behaviours, walking endurance, gait speed, cognition, stroke severity and quality of life. Mixed-effects models will assess changes in outcomes over time. Compositional associations between movement-related behaviours and outcomes will consider covariates such as imaging markers.

DISCUSSION

Adopting a whole-day approach to poststroke rehabilitation will provide valuable insights into the relationship between optimizing movement-related behaviours early after stroke and their impact on functional outcomes. Through exploring person-specific behavioural and imaging markers, this study may inform precision rehabilitation strategies, and guide clinical decision making for more tailored interventions.

TRIAL REGISTRATION

Clinical Trial registration (ClinicalTrials.gov Identifier: NCT05753761, March 3, 2023).

The Association Between Socioeconomic Status and Use of Time in Australian Children and Adolescents

PURPOSE

There are well-known socioeconomic status (SES) gradients in children and adolescents' health which may be associated with time use. Our aim was to evaluate the association between Australian children's 24-hour time use and SES using four separate surveys from 2005 to 2021.

METHODS

Time use was assessed in 4526 8-19-year-olds from the 2005 Health of Young Victorians, 2007 National Children's Nutrition and Physical Activity, 2015 Child Health CheckPoint, and 2019-21 Life on Holidays study. Each survey used the same reliable, valid, 24-hour recall instrument. SES was quantified using tertiles of household income, education, and postcode-level measures. Compositional data analysis was used to compare 24-hour time use between SES categories, adjusting for age, sex, and puberty.

RESULTS

Time-use compositions differed significantly by SES in each survey. Relative to the lowest SES, children from the highest SES accumulated on average 31 min/day more School-related time, 6 min/day more Passive Transport and 6 min/day more Self-care. Conversely, they accumulated 30 min/day less Screen Time (which included computer time), 11 min/day less sleep, and spent 7 min/day less in Domestic/Social activities. There were only small differences in Quiet Time and Physical Activity.

DISCUSSION

SES-related differences in time use were robust across ages 8-19, a 16-year timespan, diverse Australian geographical regions, and using different SES metrics. The exchange of about 30 min/day between School-related activities and Screen Time amounts to >180 hours extra exposure to School-related activities annually in the highest SES category relative to the lowest, equivalent to >6 weeks of school time per year.

Cross-sectional and prospective associations between children's 24-h time use and their health-related quality of life: a compositional isotemporal substitution approach

Background

Promoting active, balanced lifestyles among children may be an important approach to optimising their health-related quality of life (HRQoL). However, the relationships between children's movement behaviours and HRQoL remain unclear.

Methods

We examined the associations between movement behaviours (sleep, inactivity, light and moderate-to-vigorous intensity physical activity) assessed using accelerometers at ages 8 and 10 years and self-reported HRQoL scores (overall, and physical and emotional well-being, self-esteem, relationship with family and friends, and school functioning domains) at age 10 years among 370 children in a local birth cohort using compositional isotemporal substitution techniques.

Findings

Cross-sectionally, light and moderate-to-vigorous intensity physical activities were associated with better self-esteem (β = 15.94 [2.71, 29.18]) and relationship with friends (β = 10.28 [3.81, 16.74]) scores respectively. Prospectively, inactivity was associated with lower overall HRQoL (β = -10.00 [-19.13, -0.87]), relationship with friends (β = -16.41 [-31.60, -1.23]) and school functioning (β = -15.30 [-29.16, -1.44]) scores, while sleep showed a positive trend with overall HRQoL (β = 10.76 [-1.09, 22.61]) and school functioning (β = 17.12 [-0.87, 35.10]) scores. Children's movement behaviours were not associated with their physical and emotional well-being, or relationship with family scores. The isotemporal substitution analyses suggest that increasing time spent in physical activity and/or sleep at the expense of inactivity may benefit children's HRQoL.

Interpretation

Our findings suggest that sleep and physical activity may be associated with better HRQoL, with the inverse for inactivity. However, the relationship between children's movement behaviours and HRQoL is complex and warrants further research.

Funding

Singapore National Research Foundation, Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research.

Changes in Desk-Based Workers' Sitting, Standing, and Stepping Time: Short- and Longer-Term Effects on Musculoskeletal Pain

PURPOSE

Sitting at work can be associated with musculoskeletal pain, but the effect of reductions in sitting is not well understood. We examined relationships with musculoskeletal pain of changes in sitting, standing, stepping, and short and long bouts of these behaviors.

METHODS

Analyses pooled data from 224 desk workers (68.4% women; mean ± SD age = 45.5 ± 9.4 yr; body mass index = 28.1 ± 6.1 kg⋅m -2 ) in intervention trial. Device-assessed (activPAL3) sitting, standing, and stepping time and multisite musculoskeletal pain (Nordic Questionnaire; 12 body areas) were assessed at baseline, 3 months, and 12 months. Compositional data analyses in linear mixed-effects regressions examined relationships within 16 waking hours of the behaviors and their short and long bouts, with changes from baseline in acute and chronic multisite musculoskeletal pain at 3 and 12 months. Analyses were adjusted for initial group randomization and relevant covariates.

RESULTS

At 3 months, increased standing relative to changes in other compositions was significantly associated with increased multisite musculoskeletal pain (acute: β = 1.54, 95% confidence interval [CI] = 0.10 to 2.98; chronic: β = 1.49, 95% CI = 0.12 to 2.83). By contrast, increased stepping relative to changes in other compositions was significantly associated with reduced multisite musculoskeletal pain (acute: β = -1.49, 95% CI = -2.97 to -0.02; chronic: β = -1.87, 95% CI = -3.75 to -0.01). Neither sitting reduction relative to changes in other compositions nor changes in short bouts relative to long bouts of the behaviors were significantly associated with multisite musculoskeletal pain changes. At 12 months, there were no significant associations for any of the compositional changes.

CONCLUSIONS

In the short term, while increasing standing with reduced sitting time can be unfavorable, concurrently increasing stepping could potentially reduce musculoskeletal pain. In the longer term, musculoskeletal pain may not be increased by moderate reductions in sitting time through spending more time standing or stepping.

Are reallocations of time between physical activity, sedentary behaviour and sleep associated with low back pain? A compositional data analysis

Objectives

The aim of this cross-sectional study was to explore the associations of reallocating time between moderate- to vigorous-intensity physical activity (MVPA), light-intensity physical activity (LPA), sedentary behaviour (SB) and sleep with occurrence, frequency and intensity of low back pain (LBP) among adults using compositional isotemporal substitution analysis.

Methods

A total of 2333 participants from the general adult population completed the Daily Activity Behaviours Questionnaire asking about their time-use composition consisting of sleep, SB, LPA and MVPA, and they self-reported their frequency and intensity of LBP in the past year.

Results

Regression analyses adjusted for age, sex, body mass index, smoking, stress, education and socioeconomic status found that the time-use composition is associated with the frequency (p=0.009) and intensity of LBP (p<0.001). Reallocating time from SB or LPA to sleep was associated with lower frequency and intensity of LBP (p<0.05). Reallocating time from MVPA to sleep, SB or LPA and from SB to LPA was associated with a lower intensity of LBP (p<0.05). For example, reallocating 30 min/day from SB to sleep was associated with 5% lower odds (95% CI: 2% to 8%, p=0.001) of experiencing LBP more frequently, and 2% lower LBP intensity (95% CI: 1% to 3%, p<0.001).

Conclusion

LBP sufferers may benefit from getting additional sleep and spending more time in LPA, while engaging less in SB and MVPA. These reallocations of time may be meaningful from clinical and public health perspectives.

Association of meeting 24-hour movement guidelines with low back pain among adults

Background

According to recently published 24-hour movement guidelines, adults should spend: ≥150 minutes/week in moderate-to-vigorous physical activity (MVPA); <8 hours/day in sedentary behaviour (SB); and 7-9 hours/day sleeping.

Objective

We explored the association between meeting these recommendations and low back pain (LBP)-the most common musculoskeletal disorder.

Methods

We collected self-reported data from 2333 adults about: MVPA, SB and sleep duration; frequency and intensity of LBP; and sociodemographic and lifestyle characteristics.

Results

Meeting a combination of SB and sleep recommendations was associated with lower odds of LBP in the past week and past month (adjusted odds ratio [OR]: 0.64 and 0.52, respectively; p < 0.05 for both). Among LBP sufferers, meeting any combination of recommendations that includes sleep was associated with lower odds of frequent (OR range: 0.49-0.61; p < 0.05 for all) and intense (OR range: 0.39-0.66; p < 0.05 for all) LBP in the past week, while meeting a combination of SB and sleep recommendations or all three recommendations was associated with lower odds of intense LBP in the past month and past year (OR range: 0.50-0.68; p < 0.05 for all). The likelihood of experiencing higher frequency and intensity of LBP decreased with the number of recommendations met (p for linear trend < 0.05).

Conclusion

Meeting the SB and sleep recommendations in combination is associated with a lower likelihood of LBP, while adhering to the overall 24-hour movement guidelines or any combination of recommendations that includes sleep is associated with lower frequency and intensity of LBP among LBP sufferers.

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.

Modifications of 24-h movement behaviors to prevent obesity in retirement: a natural experiment using compositional data analysis

BACKGROUND

Retirement often leads to a more passive lifestyle and may therefore lead to weight gain. This study aims to investigate longitudinal associations between changes in 24-h movement behaviors and BMI and waist circumference in relation to the transition from work to retirement.

METHODS

The study population included 213 retiring public sector workers (mean age 63.5 years, standard deviation 1.1) from the Finnish Retirement and Aging study. Before and after retirement participants wore an Axivity accelerometer on their thigh and filled in a daily log for at least four days to measure daily time spent sleeping, in sedentary behavior (SED), light physical activity (LPA) and moderate-to-vigorous physical activity (MVPA). Also, their body mass index (BMI) and waist circumference were measured repeatedly. Compositional linear regression analysis and isotemporal substitution analysis were used to study associations between one-year changes in 24-h movement behaviors and concurrent changes in BMI and waist circumference.

RESULTS

An increase in MVPA in relation to sleep, SED and LPA was associated with a decreasing BMI (β = -0.60, p = 0.04) and waist circumference (β = -2.14, p = 0.05) over one year from before retirement to after retirement. In contrast, increasing sleep in relation to SED, LPA and MVPA was associated with an increasing BMI (β = 1.34, p = 0.02). Reallocating 60 min from MVPA to SED or sleep was estimated to increase BMI by on average 0.8-0.9 kg/m2 and waist circumference by 3.0 cm during one year.

CONCLUSIONS

During the transition from work to retirement, increasing MVPA was associated with a slight decrease in BMI and waist circumference, whereas increasing sleep was associated with an increasing BMI. Common life transitions, like retirement, should be considered when giving recommendations and guidance for physical activity and sleep.

Distributional data analysis via quantile functions and its application to modeling digital biomarkers of gait in Alzheimer's Disease

With the advent of continuous health monitoring with wearable devices, users now generate their unique streams of continuous data such as minute-level step counts or heartbeats. Summarizing these streams via scalar summaries often ignores the distributional nature of wearable data and almost unavoidably leads to the loss of critical information. We propose to capture the distributional nature of wearable data via user-specific quantile functions (QF) and use these QFs as predictors in scalar-on-quantile-function-regression (SOQFR). As an alternative approach, we also propose to represent QFs via user-specific L-moments, robust rank-based analogs of traditional moments, and use L-moments as predictors in SOQFR (SOQFR-L). These two approaches provide two mutually consistent interpretations: in terms of quantile levels by SOQFR and in terms of L-moments by SOQFR-L. We also demonstrate how to deal with multi-modal distributional data via Joint and Individual Variation Explained using L-moments. The proposed methods are illustrated in a study of association of digital gait biomarkers with cognitive function in Alzheimers disease. Our analysis shows that the proposed methods demonstrate higher predictive performance and attain much stronger associations with clinical cognitive scales compared to simple distributional summaries.

Do Sit-Stand Tables Affect Physical Behavior and Body Composition Similarly in Normal-Weight and Overweight Office Workers? A Pilot Study

OCCUPATIONAL APPLICATIONSSedentary behavior is a significant health concern among office workers. We completed the same 6-month sit-stand table intervention at work for groups of normal-weight and overweight workers, and compared it to not having sit-stand tables. The intervention caused the intended decrease in sitting time in both groups and a corresponding increase in standing. We did not find compensation effects on physical behavior outside of work. Furthermore, the intervention did not change the composition of fat, lean, and bone mass in either group. Thus, strategies including initiatives to increase physical activity are likely needed to have effects on body composition; and an intervention needs to be sustained for longer than six months for any changes in body composition to be observed.

Longitudinal Associations Between Timing of Physical Activity Accumulation and Health: Application of Functional Data Methods

Accelerometers are widely used for tracking human movement and provide minute-level (or even 30 Hz level) physical activity (PA) records for detailed analysis. Instead of using day-level summary statistics to assess these densely sampled inputs, we implement functional principal component analysis (FPCA) approaches to study the temporal patterns of PA data from 245 overweight/obese women at three visits over a 1-year period. We apply longitudinal FPCA to decompose PA inputs, incorporating subject-specific variability, and then test the association between these patterns and obesity-related health outcomes by multiple mixed effect regression models. With the proposed methods, the longitudinal patterns in both densely sampled inputs and scalar outcomes are investigated and connected. The results show that the health outcomes are strongly associated with PA variation, in both subject and visit-level. In addition, we reveal that timing of PA during the day can impact changes in outcomes, a finding that would not be possible with day-level PA summaries. Thus, our findings imply that the use of longitudinal FPCA can elucidate temporal patterns of multiple levels of PA inputs. Furthermore, the exploration of the relationship between PA patterns and health outcomes can be useful for establishing weight-loss guidelines.

Characteristics of 24-hour movement behaviours and their associations with mental health in children and adolescents

Background

Time-use estimates are typically used to describe 24-hour movement behaviours. However, these behaviours can additionally be characterised by other easily measured metrics. These include sleep quality (e.g., sleep efficiency), 24-hour rest-activity rhythmicity (e.g., between-day rhythm variability), and directly measured acceleration metrics (e.g., intensity gradient). Associations between these characteristics and youth mental health are unclear. This study aimed to [1] compare 24-hour movement behaviour characteristics by sex and age groups, [2] determine which movement behaviour characteristics were most strongly associated with mental health outcomes, and [3] investigate the optimal time-use behaviour compositions for different mental health outcomes.

Methods

Three-hundred-and-one children and adolescents (age 9-13 y; 60% girls) wore accelerometers for 24-hours/day over 7-days. Overall mental health, externalising, and internalising problems were self-reported using the Strengths and Difficulties Questionnaire. 24-hour movement behaviour characteristics were categorised as time-use estimates, sleep quality, 24-hour activity rhythmicity, and directly measured acceleration. Linear mixed models and compositional data analysis were used to analyse the data in alignment with the study aims.

Results

Time-use estimates, directly measured accelerations, and 24-hour rest-activity rhythm metrics indicated that children were significantly more physically active (p = .01-<0.001) than adolescents. Children were also less sedentary (p < .01), slept longer (p = .02-0.01), and had lower sleep efficiency. Boys were significantly more active than girls (p < .001) who in turn accrued more time in sleep (p = .02). The timing of peak activity was significantly later among adolescents (p = .047). Overall mental health and externalising problems were significantly associated with sleep, sedentary time, sleep efficiency, amplitude, and inter-daily stability (p = .04-0.01). The optimal time-use compositions were specific to overall mental health and externalising problems and were characterised by more sleep, light and vigorous physical activity, and less sedentary time and moderate physical activity than the sample's mean time-use composition.

Conclusions

Extracting and examining multiple movement behaviour characteristics from 24-hour accelerometer data can provide a more rounded picture of the interplay between different elements of movement behaviours and their relationships with mental health than single characteristics alone, such as time-use estimates. Applying multiple movement behaviour characteristics to the translation of research findings may enhance the impact of the data for research users.

Supplementary Information

The online version contains supplementary material available at 10.1186/s44167-023-00021-9.

Association Between 24-Hour Movement Behavior and Cognitive Function in Brazilian Middle-Aged and Older Adults: Findings From the ELSA-Brasil

Background and Objectives

The relationship between 24-hr movement behavior and specific domains of cognitive function is unclear. The purpose of this study was to identify the joint association of daily time spent in light (light-intensity physical activity [LPA]) and moderate-to-vigorous physical activity (MVPA), sedentary behavior (SB), and sleep with cognitive function in middle-aged and older adults.

Research Design and Methods

Cross-sectional data from Wave 3 (2017-2019) of the Brazilian Longitudinal Study of Adult Health were analyzed. The study included adults aged 41-84 years old. Physical activity was assessed using a waist-worn accelerometer. Cognitive function was examined using standardized tests to assess memory, language, and Trail-Making test. Global cognitive function score was calculated by averaging domain-specific scores. Compositional isotemporal substitution models were performed to identify the association between the reallocation of time spent in LPA, MVPA, sleep, and SB with cognitive function.

Results

Participants (n = 8,608) were 55.9% female (mean age 58.9 [8.6] years). Reallocating time from SB to MVPA was associated with higher cognitive function: Reallocating 15 min to MVPA by reducing 5 min from each other behavior was associated with increased odds of better cognitive function in both insufficient (<7 hr/day; odds ratio [OR]: 0.64; 95% confidence interval [CI]: 0.54-0.77) and sufficient (≥7 hr/day; OR: 0.62; 95% CI: 0.58-0.67) sleep groups. Among those with insufficient sleep, reallocating time to MVPA and sleep from SB was associated with higher global cognitive performance.

Discussion and Implications

Small reductions in SB and increments in MVPA were associated with higher cognitive function in middle-aged and older adults.

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.

Associations of activity, sedentary, and sleep behaviors with cognitive and social-emotional health in early childhood

Background

Early childhood is important for cognitive and social-emotional development, and a time in which to promote healthy movement behaviors (sedentary behavior, physical activity, and sleep). Movement behaviors may have interactive influences on cognition and social-emotional factors in young children, but most previous research has explored them independently. The purpose of this study was to determine if movement behaviors are associated with measures of cognitive and social-emotional health in young children and if so, to describe optimal compositions of movement behaviors of a daily cycle for such outcomes.

Methods

Children (n = 388, 33 to 70 months, 44.6% female) from a clinical trial (ClinicalTrials.gov ID: NCT03285880, first posted September 18, 2017) wore accelerometers on their wrists for 24-h for 9.56 ± 3.3 days. Movement behavior compositions consisted of time spent in sedentary behaviors, light intensity physical activity, moderate to vigorous intensity physical activity (MVPA), and sleep. Outcomes were cognitive (receptive vocabulary, declarative and procedural memory, and executive attention) and social-emotional measures (temperament and behavioral problems). Compositional linear regression models with isometric log ratios were used to investigate the relations between the movement behavior composition and the cognitive and social-emotional health measures. If a significant association was found between the composition and an outcome, we further explored the "optimal" 24-h time-use for said outcome.

Results

Movement behavior compositions were associated with receptive vocabulary. The composition associated with the predicted top five percent of vocabulary scores consisted of 12.1 h of sleep, 4.7 h of sedentary time, 5.6 h of light physical activity, and 1.7 h of MVPA.

Conclusions

While behavior compositions are related to vocabulary ability in early childhood, our findings align with the inconclusiveness of the current evidence regarding other developmental outcomes. Future research exploring activities within these four movement behaviors, that are meaningful to cognitive and social-emotional development, may be warranted.

Supplementary Information

The online version contains supplementary material available at 10.1186/s44167-023-00016-6.

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.

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.

A Wrinkle in Measuring Time Use for Cognitive Health: How should We Measure Physical Activity, Sedentary Behaviour and Sleep?

One new case of dementia is detected every 4 seconds and no effective drug therapy exists. Effective behavioural strategies to promote healthy cognitive ageing are thus essential. Three behaviours related to cognitive health which we all engage in daily are physical activity, sedentary behaviour and sleep. These time-use activity behaviours are linked to cognitive health in a complex and dynamic relationship not yet fully elucidated. Understanding how each of these behaviours is related to each other and cognitive health will help determine the most practical and effective lifestyle strategies for promoting healthy cognitive ageing. In this review, we discuss methods and analytical approaches to best investigate how these time-use activity behaviours are related to cognitive health. We highlight four key recommendations for examining these relationships such that researchers should include measures which (1) are psychometrically appropriate; (2) can specifically answer the research question; (3) include objective and subjective estimates of the behaviour and (4) choose an analytical method for modelling the relationships of time-use activity behaviours with cognitive health which is appropriate for their research question.

Life course research in physical activity: Pathway to Global Action Plan 2030

Current global trends in physical activity levels demonstrate that the world is not on track to achieve the 2030 target set by the Global Action Plan. The Action Plan posited that physical activity should be an integral component of "daily lives" of all individuals "across the life course." Potential contributions to achieve global physical activity goals include the utilization of compositional data analysis and life course epidemiology to provide a framework for the composite nature of physical activity and complex life course relationships. Combining these two traditionally disconnected fields represents a paradigm shift in physical activity research. Here, we discuss how these combined fields enable a reinterpretation of previous research findings and explore their impact on policy and potential advantages and challenges. Careful consideration needs to be given to the implications of both fields remaining disconnected and the alternate option of consolidation to realize ambitions.

Compositional PLS biplot based on pivoting balances: an application to explore the association between 24-h movement behaviours and adiposity

Movement behaviour data are compositional in nature, therefore the logratio methodology has been demonstrated appropriate for their statistical analysis. Compositional data can be mapped into the ordinary real space through new sets of variables (orthonormal logratio coordinates) representing balances between the original compositional parts. Geometric rotation between orthonormal logratio coordinates systems can be used to extract relevant information from any of them. We exploit this idea to introduce the concept of pivoting balances, which facilitates the construction and use of interpretable balances according to the purpose of the data analysis. Moreover, graphical representation through ternary diagrams has been ordinarily used to explore time-use compositions consisting of, or being amalgamated into, three parts. Data dimension reduction techniques can however serve well for visualisation and facilitate understanding in the case of larger compositions. We here develop suitable pivoting balance coordinates that in combination with an adapted formulation of compositional partial least squares regression biplots enable meaningful visualisation of more complex time-use patterns and their relationships with an outcome variable. The use and features of the proposed method are illustrated in a study examining the association between movement behaviours and adiposity from a sample of Czech school-aged girls. The results suggest that an adequate strategy for obesity prevention in this group would be to focus on achieving a positive balance of vigorous physical activity in combination with sleep against the other daily behaviours.

A 24-h activity profile and adiposity among children and adolescents: Does the difference between school and weekend days matter?

BACKGROUND

Twenty-four-hour movement behaviours are gaining attention in the research community. However, no study has addressed how 24-h activity profiles vary between structured and less structured days and whether an unfavourable activity profile is associated with childhood obesity. We aimed to analyse differences between school day and weekend day 24-h activity profiles and their associations with adiposity indicators among children and adolescents.

METHODS

Participants were 382 children and 338 adolescents who wore wrist accelerometers for 24 hours a day for seven consecutive days. The 24-h activity profile expressed by the average acceleration (AvAcc) and intensity gradient (IG) were estimated from multi-day raw accelerometer data. Adiposity indicators included body mass index (BMI) z-score, fat mass percentage (FM%), fat mass index (FMI), and visceral adipose tissue (VAT). Multiple linear regression of activity profile metrics and adiposity indicators was performed separately for school and weekend days.

RESULTS

Weekend days AvAcc and IG were lower compared to school days in both age groups (p <0.001 for all). Specifically, AvAcc was lower by 9.4% and 11.3% in children and adolescents, respectively. IG on weekend days was lower (more negative) by 3.4% in children and 3.1% in adolescents. Among children, on school days AvAcc and IG were negatively associated with FM%, FMI, and VAT, whilst on weekend days AvAcc was positively associated with BMI z-score, FMI, and VAT (p < 0.05 for all). Among adolescents, negative associations were found between weekend day AvAcc and IG and FM% and FMI (p < 0.05 for all), respectively.

CONCLUSIONS

This study confirms the importance of 24-h activity profile as a potentially protective factor against excess adiposity. The variability of movement behaviours during structured and less structured days should be considered when optimizing the 24-h movement behaviours to prevent childhood obesity.

Can home care work be organized to promote musculoskeletal health for workers? Study protocol for the Norwegian GoldiCare cluster randomized controlled trial

BACKGROUND

Home care workers perform physically strenuous tasks, in particular when handling patients with high care demands. Thus, musculoskeletal pain and sick leave is greater in this group than in the general population. To ease these issues, we will implement a Goldilocks Work intervention (GoldiCare), redistributing schedules between workers to achieve a "just right" weekly structure of physical work that can promote health. This protocol paper describes the content, design, implementation and evaluation of the cluster randomized controlled trial of the GoldiCare intervention in home care.

METHODS

The cluster randomized controlled trial is a 16-week workplace organizational intervention implemented through operations managers at the home care units. The operations managers will be introduced to the Goldilocks Work Principle and a GoldiCare tool, to assist the operations managers when composing a "just right" distribution of work schedules throughout the week. The GoldiCare tool provides an overview of the physical strain for each shift, based on the number of patients and their need for care. We expect to include 11 units, which will be randomized to either intervention or control at a 1:1 ratio. Home care workers assigned to the control group will continue to work as normal during the intervention period. Musculoskeletal pain in neck/shoulder and lower back will be the primary outcomes and we will also evaluate the composition of physical behaviors as well as fatigue after work as secondary outcomes. We will collect data using (1) daily questions regarding musculoskeletal pain and fatigue after work, (2) 7 days of objective measurements of physical behavior, (3) questionnaires about the participant's characteristics, health, and workplace psychosocial stressors and (4) information on the implementation of the GoldiCare tool. In addition, a process evaluation will be conducted using focus group discussions and individual interviews.

DISCUSSION

Due to the increasing aging population in need of care, measures that can improve the health of home care workers are paramount for the sustainability of this sector. This organizational intervention is based on information available nation-wide, and therefore has the potential to be scaled to all municipalities in Norway if proven effective.

TRIAL REGISTRATION

This clinical trial was registered on 08/05/2022 under NCT05487027 .

Compositional analysis of movement behaviors' association on high-sensitivity c-reactive protein: the Jackson heart study

PURPOSE

Movement behaviors (i.e. physical activity [PA], sedentary behavior [SB], and sleep) are intrinsically codependent, an issue resolved using compositional data analysis (CoDA). High-sensitivity C-reactive protein (hs-CRP) is a nonspecific inflammatory marker positively associated with cardiovascular diseases and affected by movement behaviors. Examine the relation between movement behaviors using CoDA and how time reallocation between two movement behaviors was associated with hs-CRP concentration.

METHODS

The Jackson Heart Study was designed to investigate cardiovascular disease risk factors among African American participants in the Jackson, MS area. PA and sleep were self-reported with SB calculated as the remaining time in the day.

RESULTS

The median untransformed hs-CRP concentration was 0.28 mg·dL^-1 (interquartile range; 0.11, 0.61). Reallocating 15 minutes of PA with SB, the hypothetical change in log hs-CRP concentration was 0.08 mg·dL^-1 (95% CIs; 0.04, 0.11) greater than the average log hs-CRP concentration. Substituting 15 minutes of SB or sleep with PA was associated with a hypothetical change in log hs-CRP concentration difference of -0.05 mg·dL^-1 (-0.08, -0.03) and -0.06 mg·dL^-1 (-0.08, -0.03), respectively. Reallocations between SB and sleep were not associated with the hypothetical difference in log hs-CRP concentration.

CONCLUSIONS

Modeling estimates suggest replacing 15 minutes of SB with PA is associated with lower inflammation.

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.

Twenty-four-hour time-use composition and cognitive function in older adults: Cross-sectional findings of the ACTIVate study

Introduction

Physical activity, sedentary behaviour and sleep are associated with cognitive function in older adults. However, these behaviours are not independent, but instead make up exclusive and exhaustive components of the 24-h day. Few studies have investigated associations between 24-h time-use composition and cognitive function in older adults. Of these, none have considered how the quality of sleep, or the context of physical activity and sedentary behaviour may impact these relationships. This study aims to understand how 24-h time-use composition is associated with cognitive function across a range of domains in healthy older adults, and whether the level of recreational physical activity, amount of television (TV) watching, or the quality of sleep impact these potential associations.

Methods

384 healthy older adults (age 65.5 ± 3.0 years, 68% female, 63% non-smokers, mean education = 16.5 ± 3.2 years) participated in this study across two Australian sites (Adelaide, n = 207; Newcastle, n = 177). Twenty-four-hour time-use composition was captured using triaxial accelerometry, measured continuously across 7 days. Total time spent watching TV per day was used to capture the context of sedentary behaviours, whilst total time spent in recreational physical activity was used to capture the context of physical activity (i.e., recreational accumulation of physical activity vs. other contexts). Sleep quality was measured using a single item extracted from the Pittsburgh Sleep Quality Index. Cognitive function was measured using a global cognition index (Addenbrooke's Cognitive Examination III) and four cognitive domain composite scores (derived from five tests of the Cambridge Neuropsychological Test Automated Battery: Paired Associates Learning; One Touch Stockings of Cambridge; Multitasking; Reaction Time; Verbal Recognition Memory). Pairwise correlations were used to describe independent relationships between time use variables and cognitive outcomes. Then, compositional data analysis regression methods were used to quantify associations between cognition and 24-h time-use composition.

Results

After adjusting for covariates and false discovery rate there were no significant associations between time-use composition and global cognition, long-term memory, short-term memory, executive function, or processing speed outcomes, and no significant interactions between TV watching time, recreational physical activity engagement or sleep quality and time-use composition for any cognitive outcomes.

Discussion

The findings highlight the importance of considering all activities across the 24-h day against cognitive function in older adults. Future studies should consider investigating these relationships longitudinally to uncover temporal effects.

The Associations between 24-Hour Movement Behaviours and Quality of Life in Preschoolers: A Compositional Analysis of Cross-Sectional Data from 2018-2021

Studies show that the quality of life (QoL) of preschoolers is closely related to physical activity (PA), sedentary behaviour (SB), and sleep (SL). Yet many researchers looked at these 24-h movement behaviours as behaviours that are independent of one another when examining the association of QoL with these behaviours. The main purpose of the present study was to describe the temporal trends in PA, SB, and SL in preschoolers and the concomitant association with QoL of children. Annual cross-sectional data on QoL and 24-h movement behaviours of 8045 Singaporean preschoolers were collected from 2018 to 2021. Compositional analysis, linear regression, and isotemporal replacement approaches were used to examine changes in PA, SB, and SL from 2018-2021 and how these changes were associated with QoL. Temporal trends in movement behaviours showed that PA and SL decreased after 2020. During 2018-2021, the association of PA and QoL in preschoolers was characterised by a 'U' curve (βPA-2018 = 3.06, p < 0.001; βPA-2019 = 1.43, p < 0.05; βPA-2020 = -0.43, p > 0.05; βPA-2021 = 2.82, p < 0.001), while SL and QoL were characterised by an inverted 'U' curve (βSL-2018 = -2.39, p < 0.001; βSL-2019 = -0.27, p > 0.05; βSL-2020 = 2.00, p < 0.01; βSL-2021 = -0.21, p > 0.05). SB was significantly and negatively associated with QoL after 2020, with 2020 identified as the inflection point for the change in SB (βSB-2018 = 0.67, p > 0.05; βSB-2019 = -1.16, p > 0.05; βSB-2020 = -1.56, p < 0.01; βSB-2021 = -2.61, p < 0.01). Using a time re-allocation technique to treat the 2021 data, reallocating time from SB to PA or to SL predicted improvements in QoL of preschoolers (Pall < 0.05). The study provided useful information on the temporal trends in PA, SB, SL, and QoL of preschoolers over four years. Additionally, these data provided insights into how changes in QoL are predicted by changes in duration in the 24-h movement behaviours.

Cooperating with the outgroup rather than the ingroup: The effects of status, individual mobility, and group mobility on resource allocation and trust in an interactional game

We describe a team game that implements a social dilemma between ingroup cooperation and defection by self-enriching outgroup exchange. We test hypotheses derived from social identity theory about how group status and belief about individual mobility and group mobility affect exchange behavior. We ran 60 experimental team games between rich and poor groups under one of four experiment conditions in a fully crossed design, manipulating the presence or absence of individual mobility and group mobility beliefs. Each game was played over 10 rounds in which participants generated wealth for self or group by allocating tokens to either the ingroup or outgroup bank or to outgroup individuals. We identify 10 exchange strategies via latent class analysis and show how class membership and resulting perceptions of group trust are predicted by the experimental conditions. The results show that rich status and individual mobility promote defecting exchanges with outgroup individuals, and that behavior under individual mobility beliefs weakens ingroup trust. In contrast, intergroup competition of the group mobility condition did not affect ingroup cooperation versus defection or trust.

Does occupational forward bending of the back increase long-term sickness absence risk? A 4-year prospective register-based study using device-measured compositional data analysis

OBJECTIVE

Forward bending of the back is common in many jobs and a risk factor for sickness absence. However, this knowledge is based on self-reported forward bending that is generally imprecise. Thus, we aimed to investigate the dose-response relation between device-measured forward bending at work and prospective register-based risk of long-term sickness absence (LTSA).

METHODS

At baseline, 944 workers (93% from blue-collar jobs) wore accelerometers on their upper back and thigh over 1-6 workdays to measure worktime with forward bending (>30˚ and >60˚) and body positions. The first event of LTSA (≥6 consecutive weeks) over a 4-year follow-up were retrieved from a national register. Compositional Cox proportional hazard analyses were used to model the association between worktime with forward bending of the back in an upright body position and LTSA adjusted for age, sex, body mass index (BMI), occupational lifting/carrying, type of work, and, in an additional step, for leisure time physical activity (PA) on workdays.

RESULTS

During a mean worktime of 457 minutes/day, the workers on average spent 40 and 10 minutes on forward bending >30˚ and >60˚ in the upright position, respectively. Five more minutes forward bending >30˚ and >60˚ at work were associated with a 4% [95% confidence interval (CI) 1.01-1.07] and 8% (95% CI 1.01-1.16) higher LTSA risk, respectively. Adjustment for leisure-time PA did not influence the results.

CONCLUSION

We found a dose-response association between device-measured forward bending of the back and prospective LTSA risk. This knowledge can be integrated into available feasible methods to measure forward bending of the back for improved workplace risk assessment and prevention.

Time of Dietary Energy and Nutrient Intake and Body Mass Index in Children: Compositional Data Analysis from the Childhood Obesity Project (CHOP) Trial

Meal timing is suggested to influence the obesity risk in children. Our aim was to analyse the effect of energy and nutrient distributions at eating occasions (EO), including breakfast, lunch, supper, and snacks, on the BMI z-score (zBMI) during childhood in 729 healthy children. BMI and three-day dietary protocols were obtained at 3, 4, 5, 6, and 8 years of age, and dietary data were analysed as the percentage of the mean total energy intake (TEI; %E). Intakes at EOs were transformed via an isometric log-ratio transformation and added as exposure variables to linear mixed-effects models. Stratified analyses by country and recategorization of EOs by adding intake from snacks to respective meals for further analyses were performed. The exclusion of subjects with less than three observations and the exclusion of subjects who skipped one EO or consumed 5% energy or less at one EO were examined in sensitivity analyses. Around 23% of the children were overweight at a given time point. Overweight and normal-weight children showed different distributions of dietary intakes over the day; overweight children consumed higher intakes at lunch and lower intakes of snacks. However, no significant effects of timing of EOs on zBMI were found in regression analyses.

Association between childcare movement behaviour compositions with health and development among preschoolers: Finding the optimal combinations of physical activities and sedentary time

Little is known about how wake-time movement behaviour compositions while in childcare relate to children's health and development. This study aimed to use compositional analysis to examine how childcare movement behaviour compositions were associated with standardised body mass index (zBMI) and physical and psychosocial functioning among children in the preschool setting. A total of 405 preschoolers wore accelerometers during childcare hours to measure their moderate-to-vigorous physical activity (MVPA), light intensity physical activity (LPA) and sedentary time. Compositional regression, isotemporal substitution models, and the "Goldilocks" approach was used to examine how wake-time childcare movement behaviour compositions related to each of the outcomes. Engaging in greater LPA relative to MVPA and sedentary time was associated with higher BMI z-scores, replacing sedentary time or time spent in MVPA with LPA was associated with greater physical functioning, and spending more time in sedentary behaviours relative to overall physical activity was related with greater psychosocial functioning. It is not clear what the optimal wake-time movement behaviour composition while in childcare is for health and development; however, LPA and sedentary time while in childcare may have some benefits. More research is needed to aid the development of childcare-specific guidelines for physical activity and sedentary behaviours.

Sociodemographic differences in 24-hour time-use behaviours in New Zealand children

BACKGROUND

The time that children spend in physical activity, sedentary behaviour, and sleep each day (i.e., 24-h time-use behaviours), is related to physical and mental health outcomes. Currently, there is no comprehensive evidence on New Zealand school-aged children's 24-h time-use behaviours, adherence to the New Zealand 24-h Movement Guidelines, and how these vary among different sociodemographic groups.

METHODS

This study utilises data from the 8-year wave of the Growing Up in New Zealand longitudinal study. Using two Axivity AX3 accelerometers, children's 24-h time-use behaviours were described from two perspectives: activity intensity and activity type. Compositional data analysis techniques were used to explore the differences in 24-h time-use compositions across various sociodemographic groups.

RESULTS

Children spent on average, 31.1%, 22.3%, 6.8%, and 39.8% of their time in sedentary, light physical activity, moderate-to-vigorous physical activity, and sleep, respectively. However, the daily distribution of time in different activity types was 33.2% sitting, 10.8% standing, 7.3% walking, 0.4% running, and 48.2% lying. Both the activity intensity and activity type compositions varied across groups of child ethnicity, gender, and household income or deprivation. The proportion of children meeting each of the guidelines was 90% for physical activity, 62.5% for sleep, 16% for screen time, and 10.6% for the combined guidelines. Both gender and residence location (i.e., urban vs. rural) were associated with meeting the physical activity guideline, whereas child ethnicity, mother's education and residence location were associated with meeting the screen time guideline. Child ethnicity and mother's education were also significantly associated with the adherence to the combined 24-h Movement Guidelines.

CONCLUSIONS

This study provided comprehensive evidence on how New Zealand children engage in 24-h time-use behaviours, adherence to the New Zealand 24-h Movement Guidelines, and how these behaviours differ across key sociodemographic groups. These findings should be considered in designing future interventions for promoting healthy time-use patterns in New Zealand children.

The association of physical activity, sleep, and screen time with mental health in Canadian adolescents during the COVID-19 pandemic: A longitudinal isotemporal substitution analysis

BACKGROUND

The impact of COVID-19 on adolescent mental health is a global concern. Increased screen time and reduced physical activity due to the lockdown measures have been linked to detrimental mental health outcomes; however, the literature remains limited by cross-sectional and retrospective designs, and consideration of behaviours in isolation. Prospective evidence is necessary to examine whether moderate-to-vigorous physical activity (MVPA), sleep and screen time influenced changes in mental health.

METHOD

Analyses used data from a prospective cohort study of secondary school students in Canada with baseline data from the 2018-2019 school year and linked follow-up data from online surveys completed during the initial COVID-19 outbreak (May-July 2020). Multilevel linear regression models were used to evaluate the within- and between-person isotemporal substitution effects of sleep, MVPA and screen time behaviours on depression, anxiety, subjective well-being, and trait emotional dysregulation.

RESULTS

Linked longitudinal data from 2645 students attending 44 schools were available. Between-person effects indicated that individuals who engaged in more MVPA and sleep while minimizing screen time had lower depression scores, less severe emotional dysregulation, and better subjective well-being. While controlling for between-person effects, within-person year-on-year change suggests those who increased screen time while decreasing either MVPA or sleep experienced mental health decline on all outcomes.

CONCLUSION

MVPA and sleep were associated with youth mental health during the early COVID-19 lockdown. Increasing MVPA and sleep (or at least mitigating the increase of screen time) compared to the prior year was associated with better mental health during the early pandemic. A limitation to consider is that the screen time measure represents a combination of screen behaviours, and effects of replacing screen time may have varied if distinctions were made.

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.

Data structuring may prevent ambiguity and improve personalized medical prognosis

Topics expected to influence personalized medicine (PM), where medical decisions, practices, and treatments are tailored to the individual patient, are reviewed. Lack of discrimination due to different biological conditions that express similar values of numerical variables (ambiguity) is regarded to be a major potential barrier for PM. This material explores possible causes and sources of ambiguity and offers suggestions for mitigating the impacts of uncertainties. Three causes of ambiguity are identified: (1) delayed adoption of innovations, (2) inadequate emphases, and (3) inadequate processes used when new medical practices are developed and validated. One example of the first problem is the relative lack of medical research on "compositional data" -the type that characterizes leukocyte data. This omission results in erroneous use of data abundantly utilized in medicine, such as the blood cell differential. Emphasis on data output ‒not biomedical interpretation that facilitates the use of clinical data‒ exemplifies the second type of problems. Reliance on tools generated in other fields (but not validated within biomedical contexts) describes the last limitation. Because reductionism is associated with these problems, non-reductionist alternatives are reviewed as potential remedies. Data structuring (converting data into information) is considered a key element that may promote PM. To illustrate a process that includes data-information-knowledge and decision-making, previously published data on COVID-19 are utilized. It is suggested that ambiguity may be prevented or ameliorated. Provided that validations are grounded on biomedical knowledge, approaches that describe certain criteria - such as non-overlapping data intervals of patients that experience different outcomes, immunologically interpretable data, and distinct graphic patterns - can inform, at personalized bases, earlier and/or with fewer observations.

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.