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.

The Annual Rhythms in Sleep, Sedentary Behavior, and Physical Activity of Australian Adults: A Prospective Cohort Study

BACKGROUND

Sleep, sedentary behavior, and physical activity have fundamental impacts on health and well-being. Little is known about how these behaviors vary across the year.

PURPOSE

To investigate how movement-related behaviors change across days of the week and seasons, and describe movement patterns across a full year and around specific temporal events.

METHODS

This cohort study included 368 adults (mean age = 40.2 years [SD = 5.9]) who wore Fitbit activity trackers for 12 months to collect minute-by-minute data on sleep, sedentary behavior, light physical activity (LPA), and moderate-to-vigorous physical activity (MVPA). Data were analyzed descriptively, as well as through multilevel mixed-effects linear regression to explore associations with specific temporal cycles (day-of-the-week, season) and events.

RESULTS

Movement patterns varied significantly by day-of-the-week and season, as well as during annual events like Christmas-New Year and daylight saving time (DST) transitions. For example, sleep was longer on weekends (+32 min/day), during autumn and winter relative to summer (+4 and +11 min/day), and over Christmas-New Year (+24 min/day). Sedentary behavior was longer on weekdays, during winter, after Christmas-New Year, and after DST ended (+45, +7, +12, and +8 min/day, respectively). LPA was shorter in autumn, winter, and during and after Christmas-New Year (-6, -15, -17, and -31 min/day, respectively). Finally, there was less MVPA on weekdays and during winter (-5 min/day and -2 min/day, respectively).

CONCLUSIONS

Across the year, there were notable variations in movement behaviors. Identifying high-risk periods for unfavorable behavior changes may inform time-targeted interventions and health messaging.

Cross-sectional associations between 24-hour time-use composition, grey matter volume and cognitive function in healthy older adults

BACKGROUND

Increasing physical activity (PA) is an effective strategy to slow reductions in cortical volume and maintain cognitive function in older adulthood. However, PA does not exist in isolation, but coexists with sleep and sedentary behaviour to make up the 24-hour day. We investigated how the balance of all three behaviours (24-hour time-use composition) is associated with grey matter volume in healthy older adults, and whether grey matter volume influences the relationship between 24-hour time-use composition and cognitive function.

METHODS

This cross-sectional study included 378 older adults (65.6 ± 3.0 years old, 123 male) from the ACTIVate study across two Australian sites (Adelaide and Newcastle). Time-use composition was captured using 7-day accelerometry, and T1-weighted magnetic resonance imaging was used to measure grey matter volume both globally and across regions of interest (ROI: frontal lobe, temporal lobe, hippocampi, and lateral ventricles). Pairwise correlations were used to explore univariate associations between time-use variables, grey matter volumes and cognitive outcomes. Compositional data analysis linear regression models were used to quantify associations between ROI volumes and time-use composition, and explore potential associations between the interaction between ROI volumes and time-use composition with cognitive outcomes.

RESULTS

After adjusting for covariates (age, sex, education), there were no significant associations between time-use composition and any volumetric outcomes. There were significant interactions between time-use composition and frontal lobe volume for long-term memory (p = 0.018) and executive function (p = 0.018), and between time-use composition and total grey matter volume for executive function (p = 0.028). Spending more time in moderate-vigorous PA was associated with better long-term memory scores, but only for those with smaller frontal lobe volume (below the sample mean). Conversely, spending more time in sleep and less time in sedentary behaviour was associated with better executive function in those with smaller total grey matter volume.

CONCLUSIONS

Although 24-hour time use was not associated with total or regional grey matter independently, total grey matter and frontal lobe grey matter volume moderated the relationship between time-use composition and several cognitive outcomes. Future studies should investigate these relationships longitudinally to assess whether changes in time-use composition correspond to changes in grey matter volume and cognition.

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.

Effectiveness of physical activity interventions for improving depression, anxiety and distress: an overview of systematic reviews

OBJECTIVE

To synthesise the evidence on the effects of physical activity on symptoms of depression, anxiety and psychological distress in adult populations.

DESIGN

Umbrella review.

DATA SOURCES

Twelve electronic databases were searched for eligible studies published from inception to 1 January 2022.

ELIGIBILITY CRITERIA FOR SELECTING STUDIES

Systematic reviews with meta-analyses of randomised controlled trials designed to increase physical activity in an adult population and that assessed depression, anxiety or psychological distress were eligible. Study selection was undertaken in duplicate by two independent reviewers.

RESULTS

Ninety-seven reviews (1039 trials and 128 119 participants) were included. Populations included healthy adults, people with mental health disorders and people with various chronic diseases. Most reviews (n=77) had a critically low A MeaSurement Tool to Assess systematic Reviews score. Physical activity had medium effects on depression (median effect size=-0.43, IQR=-0.66 to -0.27), anxiety (median effect size=-0.42, IQR=-0.66 to -0.26) and psychological distress (effect size=-0.60, 95% CI -0.78 to -0.42), compared with usual care across all populations. The largest benefits were seen in people with depression, HIV and kidney disease, in pregnant and postpartum women, and in healthy individuals. Higher intensity physical activity was associated with greater improvements in symptoms. Effectiveness of physical activity interventions diminished with longer duration interventions.

CONCLUSION AND RELEVANCE

Physical activity is highly beneficial for improving symptoms of depression, anxiety and distress across a wide range of adult populations, including the general population, people with diagnosed mental health disorders and people with chronic disease. Physical activity should be a mainstay approach in the management of depression, anxiety and psychological distress.

PROSPERO REGISTRATION NUMBER

CRD42021292710.

Association between the use of weight management strategies and weight change among Australian adults over 12 months: an observational study

BACKGROUND

Obesity is a growing, global public health issue. This study aimed to describe the weight management strategies used by a sample of Australian adults; examine the socio-demographic characteristics of using each strategy; and examine whether use of each strategy was associated with 12-month weight change.

METHODS

This observational study involved a community-based sample of 375 healthy adults (mean age: 40.1 ± 5.8 years, 56.8% female). Participants wore a Fitbit activity monitor, weighed themselves daily, and completed eight online surveys on socio-demographic characteristics. Participants also recalled their use of weight management strategies over the past month, at 8 timepoints during the 12-month study period.

RESULTS

Most participants (81%) reported using at least one weight management strategy, with exercise/physical activity being the most common strategy at each timepoint (40-54%). Those who accepted their current bodyweight were less likely to use at least one weight management strategy (Odds ratio = 0.38, 95% CI = 0.22-0.64, p < 0.01) and those who reported being physically active for weight maintenance had a greater reduction in bodyweight, than those who did not (between group difference: -1.2 kg, p < 0.01). The use of supplements and fasting were associated with poorer mental health and quality of life outcomes (p < 0.01).

CONCLUSIONS

The use of weight management strategies appears to be common. Being physically active was associated with greater weight loss. Individuals who accepted their current body weight were less likely to use weight management strategies. Fasting and the use of supplements were associated with poorer mental health. Promoting physical activity as a weight management strategy appears important, particularly considering its multiple health benefits.

Weekly, Seasonal, and Festive Period Weight Gain Among Australian Adults

Importance

Obesity is a major global health concern. A better understanding of temporal patterns of weight gain will enable the design and implementation of interventions with potential to alter obesity trajectories.

Objective

To describe changes in daily weight across 12 months among Australian adults.

Design, Setting, and Participants

This cohort study conducted between December 1, 2019, and December 31, 2021 in Adelaide, South Australia, involved 375 community-dwelling adults aged 18 to 65 years. Participants wore a fitness tracker and were encouraged to weigh themselves, preferably daily but at least weekly, using a body weight scale. Data were remotely gathered using custom-developed software.

Exposure

Time assessed weekly, seasonally, and at Christmas/New Year and Easter.

Main Outcomes and Measures

Data were visually inspected to assess the overall yearly pattern in weight change. Data were detrended (to remove systematic bias from intraindividual gradual increases or decreases in weight) by calculating a line of best fit for each individual's annual weight change relative to baseline and subtracting this from each participant's weight data. Multilevel mixed-effects linear regression analysis was used to compare weight across days of the week and seasons and at Christmas/New Year and Easter.

Results

Of 375 participants recruited, 368 (mean [SD] age, 40.2 [5.9] years; 209 [56.8%] female; mean [SD] baseline weight, 84.0 [20.5] kg) provided at least 7 days of weight data for inclusion in analyses. Across the 12-month period, participants gained a median of 0.26% body weight (218 g) (range, -29.4% to 24.0%). Weight fluctuated by approximately 0.3% (252 g) each week, with Mondays and Tuesdays being the heaviest days of the week. Relative to Monday, participants' weight gradually decreased from Tuesday, although not significantly so (mean [SE] weight change, 0.01% [0.03%]; P = .83), to Friday (mean [SE] weight change, -0.18% [0.03%]; P < .001) and increased across the weekend to Monday (mean [SE] weight change for Saturday, -0.16% [0.03%]; P < .001; mean [SE] weight change for Sunday, -0.10% [0.03%]; P < .001). Participants' weight increased sharply at Christmas/New Year (mean [SE] increase, 0.65% [0.03%]; z score, 25.30; P < .001) and Easter (mean [SE] weight change, 0.29% [0.02%], z score, 11.51; P < .001). Overall, participants were heaviest in summer (significantly heavier than in all other seasons), were lightest in autumn (mean [SE] weight change relative to summer, -0.47% [0.07%]; P < .001), regained some weight in winter (mean [SE] weight change relative to summer, -0.23% [0.07%]; P = .001), and became lighter in spring (mean [SE] weight change relative to summer, -0.27% [0.07%]; P < .001).

Conclusions and Relevance

In this cohort study of Australian adults with weekly and yearly patterns in weight gain observed across 12 months, high-risk times for weight gain were Christmas/New Year, weekends, and winter, suggesting that temporally targeted weight gain prevention interventions may be warranted.

Systematic review and meta-analysis of the effectiveness of chatbots on lifestyle behaviours

Chatbots (also known as conversational agents and virtual assistants) offer the potential to deliver healthcare in an efficient, appealing and personalised manner. The purpose of this systematic review and meta-analysis was to evaluate the efficacy of chatbot interventions designed to improve physical activity, diet and sleep. Electronic databases were searched for randomised and non-randomised controlled trials, and pre-post trials that evaluated chatbot interventions targeting physical activity, diet and/or sleep, published before 1 September 2022. Outcomes were total physical activity, steps, moderate-to-vigorous physical activity (MVPA), fruit and vegetable consumption, sleep quality and sleep duration. Standardised mean differences (SMD) were calculated to compare intervention effects. Subgroup analyses were conducted to assess chatbot type, intervention type, duration, output and use of artificial intelligence. Risk of bias was assessed using the Effective Public Health Practice Project Quality Assessment tool. Nineteen trials were included. Sample sizes ranged between 25-958, and mean participant age ranged between 9-71 years. Most interventions (n = 15, 79%) targeted physical activity, and most trials had a low-quality rating (n = 14, 74%). Meta-analysis results showed significant effects (all p < 0.05) of chatbots for increasing total physical activity (SMD = 0.28 [95% CI = 0.16, 0.40]), daily steps (SMD = 0.28 [95% CI = 0.17, 0.39]), MVPA (SMD = 0.53 [95% CI = 0.24, 0.83]), fruit and vegetable consumption (SMD = 0.59 [95% CI = 0.25, 0.93]), sleep duration (SMD = 0.44 [95% CI = 0.32, 0.55]) and sleep quality (SMD = 0.50 [95% CI = 0.09, 0.90]). Subgroup analyses showed that text-based, and artificial intelligence chatbots were more efficacious than speech/voice chatbots for fruit and vegetable consumption, and multicomponent interventions were more efficacious than chatbot-only interventions for sleep duration and sleep quality (all p < 0.05). Findings from this systematic review and meta-analysis indicate that chatbot interventions are efficacious for increasing physical activity, fruit and vegetable consumption, sleep duration and sleep quality. Chatbot interventions were efficacious across a range of populations and age groups, with both short- and longer-term interventions, and chatbot only and multicomponent interventions being efficacious.

Longitudinal reallocations of time between 24-h movement behaviours and their associations with inflammation in children and adolescents: the UP&DOWN study

BACKGROUND

While there is evidence that physical activity, sedentary behaviour (SB) and sleep may all be associated with modified levels of inflammatory markers in adolescents and children, associations with one movement behaviour have not always been adjusted for other movement behaviours, and few studies have considered all movement behaviours in the 24-hour day as an exposure.

PURPOSE

The aim of the study was to explore how longitudinal reallocations of time between moderate-to-vigorous physical activity (MVPA), light physical activity (LPA), SB and sleep are associated with changes in inflammatory markers in children and adolescents.

METHODS

A total of 296 children/adolescents participated in a prospective cohort study with a 3-year follow-up. MVPA, LPA and SB were assessed by accelerometers. Sleep duration was assessed using the Health Behavior in School-aged Children questionnaire. Longitudinal compositional regression models were used to explore how reallocations of time between movement behaviours are associated with changes in inflammatory markers.

RESULTS

Reallocations of time from SB to sleep were associated with increases in C3 levels (difference for 60 min/d reallocation [d₆₀] = 5.29 mg/dl; 95% confidence interval [CI] = 0.28, 10.29) and TNF-α (d₆₀ = 1.81 mg/dl; 95% CI = 0.79, 15.41) levels. Reallocations from LPA to sleep were also associated with increases in C3 levels (d₆₀ = 8.10 mg/dl; 95% CI = 0.79, 15.41). Reallocations from LPA to any of the remaining time-use components were associated with increases in C4 levels (d₆₀ ranging from 2.54 to 3.63 mg/dl; p < 0.05), while any reallocation of time away from MVPA was associated with unfavourable changes in leptin (d₆₀ ranging from 3088.44 to 3448.07 pg/ml; p < 0.05).

CONCLUSIONS

Reallocations of time between 24-h movement behaviours are prospectively associated with some inflammatory markers. Reallocating time away from LPA appears to be most consistently unfavourably associated with inflammatory markers. Given that higher levels of inflammation during childhood and adolescence are associated with an increased risk of chronic diseases in adulthood, children and adolescents should be encouraged to maintain or increase the level of LPA to preserve a healthy immune system.

How do 24-h movement behaviours change during and after vacation? A cohort study

BACKGROUND

For adults, vacations represent a break from daily responsibilities of work - offering the opportunity to re-distribute time between sleep, sedentary behaviour, light physical activity (LPA) and moderate-to-vigorous physical activity (MVPA) across the 24-h day. To date, there has been minimal research into how activity behaviour patterns change on vacation, and whether any changes linger after the vacation. This study examined how daily movement behaviours change from before, to during and after vacations, and whether these varied based on the type of vacation and vacation duration.

METHODS

Data collected during the Annual Rhythms In Adults' lifestyle and health (ARIA) study were used. 308 adults (mean age 40.4 years, SD 5.6) wore Fitbit Charge 3 fitness trackers 24 h a day for 13 months. Minute-by-minute movement behaviour data were aggregated into daily totals. Multi-level mixed-effects linear regressions were used to compare movement behaviours during and post-vacation (4 weeks) to pre-vacation levels (14 days), and to examine the associations with vacation type and duration.

RESULTS

Participants took an average of 2.6 (SD = 1.7) vacations of 12 (SD = 14) days' (N = 9778 days) duration. The most common vacation type was outdoor recreation (35%) followed by family/social events (31%), rest (17%) and non-leisure (17%). Daily sleep, LPA and MVPA all increased (+ 21 min [95% CI = 19,24] p < 0.001, + 3 min [95% CI = 0.4,5] p < 0.02, and + 5 min [95% CI = 3,6] p < 0.001 respectively) and sedentary behaviour decreased (-29 min [95% CI = -32,-25] p < 0.001) during vacation. Post-vacation, sleep remained elevated for two weeks; MVPA returned to pre-vacation levels; and LPA and sedentary behaviour over-corrected, with LPA significantly lower for 4 weeks, and sedentary behaviour significantly higher for one week. The largest changes were seen for "rest" and "outdoor" vacations. The magnitude of changes was smallest for short vacations (< 3 days).

CONCLUSIONS

Vacations are associated with favourable changes in daily movement behaviours. These data provide preliminary evidence of the health benefits of vacations.

TRIAL REGISTRATION

The study was prospectively registered on the Australian New Zealand Clinical Trial Registry (Trial ID: ACTRN12619001430123).

Effectiveness of wearable activity trackers to increase physical activity and improve health: a systematic review of systematic reviews and meta-analyses

Wearable activity trackers offer an appealing, low-cost tool to address physical inactivity. This systematic review of systematic reviews and meta-analyses (umbrella review) aimed to examine the effectiveness of activity trackers for improving physical activity and related physiological and psychosocial outcomes in clinical and non-clinical populations. Seven databases (Embase, MEDLINE, Ovid Emcare, Scopus, SPORTDiscus, the Cochrane Library, and Web of Science) were searched from database inception to April 8, 2021. Systematic reviews of primary studies using activity trackers as interventions and reporting physical activity, physiological, or psychosocial outcomes were eligible for inclusion. In total, 39 systematic reviews and meta-analyses were identified, reporting results from 163 992 participants spanning all age groups, from both healthy and clinical populations. Taken together, the meta-analyses suggested activity trackers improved physical activity (standardised mean difference [SMD] 0·3-0·6), body composition (SMD 0·7-2·0), and fitness (SMD 0·3), equating to approximately 1800 extra steps per day, 40 min per day more walking, and reductions of approximately 1 kg in bodyweight. Effects for other physiological (blood pressure, cholesterol, and glycosylated haemoglobin) and psychosocial (quality of life and pain) outcomes were typically small and often non-significant. Activity trackers appear to be effective at increasing physical activity in a variety of age groups and clinical and non-clinical populations. The benefit is clinically important and is sustained over time. Based on the studies evaluated, there is sufficient evidence to recommend the use of activity trackers.

Gamification in a Physical Activity App: What Gamification Features Are Being Used, by Whom, and Does It Make a Difference?

Background: Gamification is purported to enhance engagement with health behavior apps, ultimately improving their effectiveness. This study aimed to examine (1) whether the inclusion of gamification features in a physical activity smartphone app was associated with improved app usage and goal adherence, describe (2) use of the gamification features, and (3) by whom, and determine (4) whether engagement was associated with increased physical activity. Methods: Data from community-dwelling adult participants (mean age 42.1 years, standard deviation [SD 11.9], 74% female) in the gamified (n = 134) and nongamified (n = 155) conditions from a three-group randomized controlled trial were analyzed. Physical activity was assessed at baseline and 9 months using a survey and accelerometers. App usage (number of days steps were logged), goal adherence (number of days step count was ≥10,000), and behavioral engagement with gamification features were obtained from server logs. Multilevel modeling was used to examine the study aims. Results: Participants who received the gamified app showed more days of usage than those who received the nongamified app (M = 113 days [SD 88] vs. M = 81 days [SD 54], P = 0.006), whereas goal adherence did not differ between groups. The leaderboard and "status" gamification features were the most frequently used gamification features (M = 83 [SD 114] and M = 50 [SD 67] views, respectively). Older age (P = 0.008) and lower body mass index (P = 0.004) were associated with more status views. Participants who reported higher stress symptoms sent more gifts (P = 0.04). The use of gamification features was associated with increased physical activity (P = 0.04). Conclusion: The gamified app was used substantially longer than the nongamified app. Use of gamification features was positively associated with change in physical activity. Leaderboards promoting social comparison may be a promising form of gamification. Research on different forms of gamification is warranted.

Characterising activity and diet compositions for dementia prevention: protocol for the ACTIVate prospective longitudinal cohort study

INTRODUCTION

Approximately 40% of late-life dementia may be prevented by addressing modifiable risk factors, including physical activity and diet. Yet, it is currently unknown how multiple lifestyle factors interact to influence cognition. The ACTIVate Study aims to (1) explore associations between 24-hour time-use and diet compositions with changes in cognition and brain function; and (2) identify duration of time-use behaviours and the dietary compositions to optimise cognition and brain function.

METHODS AND ANALYSIS

This 3-year prospective longitudinal cohort study will recruit 448 adults aged 60-70 years across Adelaide and Newcastle, Australia. Time-use data will be collected through wrist-worn activity monitors and the Multimedia Activity Recall for Children and Adults. Dietary intake will be assessed using the Australian Eating Survey food frequency questionnaire. The primary outcome will be cognitive function, assessed using the Addenbrooke's Cognitive Examination-III. Secondary outcomes include structural and functional brain measures using MRI, cerebral arterial pulse measured with diffuse optical tomography, neuroplasticity using simultaneous transcranial magnetic stimulation and electroencephalography, and electrophysiological markers of cognitive control using event-related potential and time frequency analyses. Compositional data analysis, testing for interactions between time point and compositions, will assess longitudinal associations between dependent (cognition, brain function) and independent (time-use and diet compositions) variables.

CONCLUSIONS

The ACTIVate Study will be the first to examine associations between time-use and diet compositions, cognition and brain function. Our findings will inform new avenues for multidomain interventions that may more effectively account for the co-dependence between activity and diet behaviours for dementia prevention.

ETHICS AND DISSEMINATION

Ethics approval has been obtained from the University of South Australia's Human Research Ethics committee (202639). Findings will be disseminated through peer-reviewed manuscripts, conference presentations, targeted media releases and community engagement events.

TRIAL REGISTRATION NUMBER

Australia New Zealand Clinical Trials Registry (ACTRN12619001659190).

Should Facebook advertisements promoting a physical activity smartphone app be image or video-based, and should they promote benefits of being active or the app attributes?

Social media provides a convenient platform for health campaigns. However, practitioners designing such campaigns are faced with a number of decisions regarding advertising formats and appeals. This study set out to compare the effectiveness of two advertising formats (image vs. video) and two advertising appeals (benefits of being active vs. app attributes and features) for promoting a physical-activity smartphone app. The advertising experiment was conducted on Facebook and employed a 2 × 2 full-factorial experimental design, examining two advertising formats: image versus video and two advertising appeals: benefit versus attribute. Outcome measures were advertisement cost (number of viewers reached according to the amount spent) and consumer engagement (rates of advertisement click-through and app downloads). Chi-Square analysis revealed that advertisement cost was found to differ according to the type of advertising format used, with image advertisements achieving a greater audience reach than video advertisements (χ 2(1) = 905.292, p < .001). Consumer engagement also differed according to advertising format and appeal: images achieved high rates of advertisement click-through (2.7% vs. 1.9%; χ 2(1) = 196.9, p < .001) and app downloads (0.6% vs. 0.5%; χ 2(1) = 4.0, p = .044) compared with videos. Furthermore, benefit appeal advertisements were more effective than attribute appeals, yielding a greater rate of advertisement click-through (2.8% vs. 1.8%; χ 2(1) = 282.2, p < .001) and app downloads (0.7% vs. 0.4%; χ 2(1) =106.0, p < .001). Overall, image advertisements were seen to be the most cost-effective and engaging. Advertisements employing a benefit appeal achieved greater consumer engagement than and attribute appeal advertisements.

Goldilocks Days: optimising children's time use for health and well-being

BACKGROUND

One size rarely fits all in population health. Differing outcomes may compete for best allocations of time. Among children aged 11-12 years, we aimed to (1) describe optimal 24-hour time use for diverse physical, cognitive/academic and well-being outcomes, (2) pinpoint the 'Goldilocks Day' that optimises all outcomes and (3) develop a tool to customise time-use recommendations.

METHODS

In 2004, the Longitudinal Study of Australian Children recruited a nationally-representative cohort of 5107 infants with biennial follow-up waves. We used data from the cross-sectional Child Health CheckPoint module (2015-2016, n=1874, 11-12 years, 51% males). Time use was from 7-day 24-hour accelerometry. Outcomes included life satisfaction, psychosocial health, depressive symptoms, emotional problems, non-verbal IQ; vocabulary, academic performance, adiposity, fitness, blood pressure, inflammatory biomarkers, bone strength. Relationships between time use and outcomes were modelled using compositional regression.

RESULTS

Optimal daily durations varied widely for different health outcomes (sleep: 8.3-11.4 hours; sedentary: 7.3-12.2 hours; light physical activity: 1.7-5.1 hours; moderate-to-vigorous physical activity (MVPA): 0.3-2.7 hours, all models p≤0.04). In general, days with highest physical activity (predominantly MVPA) and low sedentary time were optimal for physical health, while days with highest sleep and lowest sedentary time were optimal for mental health. Days with highest sedentary time and lowest physical activity were optimal for cognitive health. The overall Goldilocks Day had 10 hours 21 min sleep, 9 hours 44 min sedentary time, 2 hours 26 min light physical activity and 1 hour 29 min MVPA. Our interactive interface allows personalisation of Goldilocks Days to an individual's outcome priorities.

CONCLUSION

'Goldilocks Days' necessitate compromises based on hierarchies of priorities for health, social and economic outcomes.

Evaluating the effectiveness of a physical activity social media advertising campaign using Facebook, Facebook Messenger, and Instagram

Technology-based physical activity programs are a novel solution to the major public health issue of physical inactivity. However, to be successful, there must be a large and population-appropriate uptake, which depends heavily on promotion. This study evaluates the effectiveness of an advertising campaign to disseminate a physical activity smartphone app. The experiment used a 3 × 3 × 3 full-factorial design, examining platforms (Facebook; Facebook Messenger; Instagram), selling-techniques (hard-sell-sending viewers directly to (a) Apple Store or (b) Google Play, and soft-sell-sending viewers from an ad to a (c) landing-page, then to an app store) and themes (Health and Wellbeing; Body and Self-Confidence; Social Enjoyment). Outcomes were reach, click-through, and app downloads. Advertisements reached 1,373,273 people, achieving 2,989 clicks and 667 downloads. Instagram and Facebook Messenger had higher reach compared to Facebook (F[2,27] = 27.17, p < .001), whilst Facebook and Facebook Messenger both produced higher click-through (F[2,27] = 8.98, p < .001) and downloads (F[2,27] = 4.649, p = .018). Selling-technique differed, with soft-selling ads producing greater reach (F[2,27] = 4,616.077, p < .001); however, both hard-selling ads (Apple Store and Google Play) had greater click-through (F[2,27] = 10.77, p < .001) and downloads (F[2,27] = 3.791, p < .001). Advertising theme varied, with Social Enjoyment themes producing less click-through (F[2,27] = 5.709, p = .009) and downloads (F[2,27] = 5.480, p = .010). We recommend future studies to consider Facebook and Facebook Messenger, using hard-selling techniques, with themes relating to Health and Wellbeing and Body and Self-Confidence.

Equivalence Curves for Healthy Lifestyle Choices

BACKGROUND

Understanding equivalence of time-use trade-offs may inform tailored lifestyle choices. We explored which time reallocations were associated with equivalent changes in children's health outcomes.

METHODS

Participants were from the cross-sectional Child Health CheckPoint Study (N = 1179; 11-12 years; 50% boys) nested within the population-based Longitudinal Study of Australian Children. Outcomes were adiposity (bioelectrical impedance analysis, BMI and waist girth), self-reported health-related quality of life (HRQoL; Pediatric Quality of Life Inventory), and academic achievement (standardized national tests). Participants' 24-hour time use (sleep, sedentary behavior, light physical activity, and moderate-to-vigorous physical activity [MVPA]) from 8-day 24-hour accelerometry was regressed against outcomes by using compositional log-ratio linear regression models.

RESULTS

Children with lower adiposity and higher HRQoL had more MVPA (both P ≤ .001) and sleep (P = .001; P < .02), and less sedentary time (both P < .001) and light physical activity (adiposity only; P = .03), each relative to remaining activities. Children with better academic achievement had less light physical activity, relative to remaining activities (P = .003). A 0.1 standardized decrease in adiposity was associated with either 52 minutes more sleep, 56 minutes less sedentary time, 65 minutes less light physical activity, or 17 minutes more MVPA. A 0.1 standardized increase in HRQoL was associated with either 68 minutes more sleep, 54 minutes less sedentary time, or 35 minutes more MVPA.

CONCLUSIONS

Equivalent differences in outcomes were associated with several time reallocations. On a minute-for-minute basis, MVPA was 2 to 6 times as potent as sleep or sedentary time.

A study on prospective associations between adiposity and 7-year changes in movement behaviors among older women based on compositional data analysis

INTRODUCTION

It is unclear whether adiposity leads to changes in movement behaviors, and there is a lack of compositional analyses of longitudinal data which focus on these associations. Using a compositional approach, this study aimed to examine the associations between baseline adiposity and 7-year changes in physical activity (PA) and sedentary behavior (SB) among elderly women. We also explored the longitudinal associations between change in adiposity and change in movement-behavior composition.

METHODS

This longitudinal study included 176 older women (mean baseline age 62.8 (4.1) years) from Central Europe. Movement behavior was assessed by accelerometers and adiposity was measured by bioelectrical impedance analysis at baseline and follow-up. A set of multivariate least-squares regression analyses was used to examine the associations of baseline adiposity and longitudinal changes in adiposity as explanatory variables with longitudinal changes in a 3-part movement-behavior composition consisting of SB, light PA (LPA) and moderate-to-vigorous PA (MVPA) as outcome variables.

RESULTS

No significant associations were found between baseline adiposity and longitudinal changes in the movement-behavior composition (p > 0.05). We found significant associations of changes in body mass index (BMI) and fat mass percentage (FM%) with changes in the movement-behavior composition. An increase in BMI was associated with an increase of SB at the expense of LPA and MVPA (β = 0.042, p = 0.009) and with a decrease of MVPA in favor of SB and LPA (β = - 0.059, p = 0.037). An increase in FM% was significantly associated only with an increase of SB at the expense of LPA and MVPA (β = 0.019, p = 0.031).

CONCLUSIONS

This study did not support the assumption that baseline adiposity is associated with longitudinal changes in movement behaviors among elderly women, but we found evidence for change-to-change associations, suggesting that a 7-year increase in adiposity is associated with a concurrent increase of SB at the expense of LPA and MVPA and with a concurrent decrease of MVPA in favor of LPA and SB. Public health interventions are needed to simultaneously prevent weight gain and promote physically active lifestyle among elderly women.

Changes in diet, activity, weight, and wellbeing of parents during COVID-19 lockdown

The COVID-19 pandemic has dramatically impacted lifestyle behaviour as public health initiatives aim to “flatten the curve”. This study examined changes in activity patterns (physical activity, sedentary time, sleep), recreational physical activities, diet, weight and wellbeing from before to during COVID-19 restrictions in Adelaide, Australia. This study used data from a prospective cohort of Australian adults (parents of primary school-aged children; n = 61, 66% female, aged 41±6 years). Participants wore a Fitbit Charge 3 activity monitor and weighed themselves daily using Wi-Fi scales. Activity and weight data were extracted for 14 days before (February 2020) and 14 days during (April 2020) COVID-19 restrictions. Participants reported their recreational physical activity, diet and wellbeing during these periods. Linear mixed effects models were used to examine change over time. Participants slept 27 minutes longer (95% CI 9–51), got up 38 minutes later (95% CI 25–50), and did 50 fewer minutes (95% CI -69–-29) of light physical activity during COVID-19 restrictions. Additionally, participants engaged in more cycling but less swimming, team sports and boating or sailing. Participants consumed a lower percentage of energy from protein (-0.8, 95% CI -1.5–-0.1) and a greater percentage of energy from alcohol (0.9, 95% CI 0.2–1.7). There were no changes in weight or wellbeing. Overall, the effects of COVID-19 restrictions on lifestyle were small; however, their impact on health and wellbeing may accumulate over time. Further research examining the effects of ongoing social distancing restrictions are needed as the pandemic continues.

Seasonal Differences in the Cost and Engagement of Facebook Advertisements for a Physical Activity Smartphone App

PURPOSE

To evaluate the performance of Facebook advertisements for a physical activity smartphone app at different times of the year.

DESIGN

A repeated cross-sectional study examined the cost and engagement levels of advertisements during 3 time points: Post-Easter _{April-May 2019}, Pre-Summer _{October 2019}, and New Year _{January 2020 .}

SETTING

Advertisements were delivered on Facebook.

SUBJECTS

The target population was Australian females aged 25-60 years.

MEASURES

Cost was evaluated in terms of reach per dollar. Engagement was evaluated in terms of click-through and app downloads per reach.

ANALYSIS

ANOVA and Chi-square were used to assess differences in reach per dollar, click-through, and app downloads per reach between time points.

RESULTS

Reach per dollar was highest in Post-Easter, but declined in Pre-Summer and New Year (reach/$ 34.8 vs 31.5 vs 27.5; p = .004). Click-through was highest in New Year followed by Post-Easter, then Pre-Summer (click-through 3.2% vs 1.9% vs 1.2%; p < .001). New Year and Post-Easter advertisements achieved higher app downloads per reach than Pre-Summer (downloads 0.9% vs 0.7% vs 0.3%; p < .001).

CONCLUSION

Facebook advertisements were cheaper in the first time-point, and appear to be getting more expensive (i.e. declining reach/$). Advertisements in the New Year achieved the highest click-through and app downloads per reach, suggesting a useful time of year to promote physical activity products.

Children's moderate-to-vigorous physical activity on weekdays versus weekend days: a multi-country analysis

Purpose

The Structured Days Hypothesis (SDH) posits that children’s behaviors associated with obesity – such as physical activity – are more favorable on days that contain more ‘structure’ (i.e., a pre-planned, segmented, and adult-supervised environment) such as school weekdays, compared to days with less structure, such as weekend days. The purpose of this study was to compare children’s moderate-to-vigorous physical activity (MVPA) levels on weekdays versus weekend days using a large, multi-country, accelerometer-measured physical activity dataset.

Methods

Data were received from the International Children’s Accelerometer Database (ICAD) July 2019. The ICAD inclusion criteria for a valid day of wear, only non-intervention data (e.g., baseline intervention data), children with at least 1 weekday and 1 weekend day, and ICAD studies with data collected exclusively during school months, were included for analyses. Mixed effects models accounting for the nested nature of the data (i.e., days within children) assessed MVPA minutes per day (min/day MVPA) differences between weekdays and weekend days by region/country, adjusted for age, sex, and total wear time. Separate meta-analytical models explored differences by age and country/region for sex and child weight-status.

Results/findings

Valid data from 15 studies representing 5794 children (61% female, 10.7 ± 2.1 yrs., 24% with overweight/obesity) and 35,263 days of valid accelerometer data from 5 distinct countries/regions were used. Boys and girls accumulated 12.6 min/day (95% CI: 9.0, 16.2) and 9.4 min/day (95% CI: 7.2, 11.6) more MVPA on weekdays versus weekend days, respectively. Children from mainland Europe had the largest differences (17.1 min/day more MVPA on weekdays versus weekend days, 95% CI: 15.3, 19.0) compared to the other countries/regions. Children who were classified as overweight/obese or normal weight/underweight accumulated 9.5 min/day (95% CI: 6.9, 12.2) and 10.9 min/day (95% CI: 8.3, 13.5) of additional MVPA on weekdays versus weekend days, respectively.

Conclusions

Children from multiple countries/regions accumulated significantly more MVPA on weekdays versus weekend days during school months. This finding aligns with the SDH and warrants future intervention studies to prioritize less-structured days, such as weekend days, and to consider providing opportunities for all children to access additional opportunities to be active.

Balancing time use for children's fitness and adiposity: Evidence to inform 24-hour guidelines for sleep, sedentary time and physical activity

PURPOSE

Daily time spent on one activity cannot change without compensatory changes in others, which themselves may impact on health outcomes. Optimal daily activity combinations may differ across outcomes. We estimated optimal daily activity durations for the highest fitness and lowest adiposity.

METHODS

Cross-sectional Child Health CheckPoint data (1182 11-12-year-olds; 51% boys) from the population-based Longitudinal Study of Australian Children were used. Daily activity composition (sleep, sedentary time, light physical activity [LPA], moderate-to-vigorous physical activity [MVPA]) was from 8-day, 24-hour accelerometry. We created composite outcomes for fitness (VO2max; standing long jump) and adiposity (waist-to-height ratio; body mass index; fat-to-fat-free log-ratio). Adjusted compositional models regressed activity log-ratios against each outcome. Best activity compositions (optimal time-use zones) were plotted in quaternary tetrahedrons; the overall optimal time-use composition was the center of the overlapping area.

RESULTS

Time-use composition was associated with fitness and adiposity (all measures p<0.001). Optimal time use differed for fitness and adiposity. While both maximized MVPA and minimized sedentary time, optimal fitness days had higher LPA (3.4 h) and shorter sleep (8.25 h), but optimal adiposity days had lower LPA (1.0 h) and longer sleep (10.9 h). Balancing both outcomes, the overall optimal time-use composition was (mean [range]): 10.2 [9.5; 10.5] h sleep, 9.9 [8.8; 11.2] h sedentary time, 2.4 [1.8; 3.2] h LPA and 1.5 [1.5; 1.5] h MVPA.

CONCLUSION

Optimal time use for children's fitness and adiposity involves trade-offs. To best balance both outcomes, estimated activity durations for sleep and LPA align with, but for MVPA exceed, 24-h guidelines.

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

BACKGROUND

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

METHODS

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

DISCUSSION

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

TRIAL REGISTRATION

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

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

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

Obesity, the new childhood disability? An umbrella review on the association between adiposity and physical function

The adverse physical impacts of childhood obesity are increasingly being recognized. The objective of this study is to examine relationships between physical function and adiposity in youth. An umbrella review searched seven databases from inception to May 2019 for systematic reviews examining associations between adiposity and physical function in 0-20-year-olds. Findings were synthesized using the International Classification of Functioning, Disability and Health Framework and NHMRC FORM. Seventeen of 21 systematic reviews reported impairments to body function, including cardiorespiratory fitness (CRF), muscle function, balance/coordination, gait biomechanics, pain and injury. Six reviews reported activity restrictions in motor skills, running speed/agility and functional mobility, and two found inverse associations between adiposity and physical health-related quality of life (p-HRQOL). Some causal relationships indicated that adiposity inversely predicted p-HRQOL/CRF and CRF/muscle function inversely predicted adiposity. Assessments of physical function were heterogeneous and impacts on participation in life situations meaningful to the individual were largely unknown. Substantial evidence associates childhood overweight/obesity with reduced physical function. Associations were mainly cross-sectional, with causative evidence for some outcomes. Comprehensive physical function assessments by qualified health professionals are needed, along with targeted interventions to address deficits. Research should further examine causality of relationships, underlying mechanisms and participation challenges in real-life contexts.

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

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

Electronic media use and academic performance in late childhood: A longitudinal study

INTRODUCTION

The effects of electronic media use on health has received much attention but less is known about links with academic performance. This study prospectively examines the effect of media use on academic performance in late childhood.

MATERIALS AND METHODS

1239 8- to 9-year-olds and their parents were recruited to take part in a prospective, longitudinal study. Academic performance was measured on a national achievement test at baseline and 10-11 years of age. Parents reported on their child's duration of electronic media use.

RESULTS

After control for baseline reading, watching more than two hours of television per day at 8-9 years of age predicted a 12-point lower performance in reading at 10-11 years, equivalent to the loss of a third of a year in learning. Using a computer for more than one hour a day predicted a similar 12-point lower numeracy performance. Regarding cross-sectional associations (presumed to capture short-term effects) of media use on numeracy, after controlling for prior media exposure, watching more than two hours of television per day at 10-11 years was concurrently associated with a 12-point lower numeracy score and using a computer for more than one hour per day with a 13-point lower numeracy performance. There was little evidence for concurrent effects on reading. There was no evidence of short- or long-term associations between videogame use and academic performance.

DISCUSSION

Cumulative television use is associated with poor reading and cumulative computer use with poorer numeracy. Beyond any links between heavy media use and health risks such as obesity, physical activity and mental health, these findings raise a possibility of additional risks of both television and computer use for learning in mid-childhood. These findings carry implications for parents, teachers and clinicians to consider the type and timing of media exposure in developing media plans for children.

A cross-sectional examination of the 24-hour movement behaviours in Canadian youth with physical and sensory disabilities

BACKGROUND

Canada's 24-Hour Movement Guidelines for Children and Youth provide daily recommendations for physical activity (PA), screen time, and sleep for optimal health. The appropriateness of such guidelines for youth with disabilities remains unknown.

OBJECTIVE

To cross-sectionally examine the 24-h movement behaviours and guideline adherence in youth (ages 12-21 years) with physical and sensory disabilities.

METHODS

54 youth with physical and sensory disabilities completed two, 24-h recalls to assess PA, sedentary behaviour, and sleep. Descriptive statistics were used to analyze behavioural patterns and guideline adherence. Gender and age differences were tested using analyses of variance and logistic regressions.

RESULTS

55.5%, 13.0%, and 53.7% of the sample met the individual guidelines for PA, sedentary behaviour, and sleep, respectively. 3.7% of the sample met all three movement guidelines. No significant gender or age differences in guideline achievement were found. Over a 24-h period, youth spent 77 (59) minutes engaging in moderate to vigorous PA, 252 (120) minutes engaging in sedentary activity, and 546 (90) minutes sleeping. Boys reported significantly more time (adjusted M_difference = 11 min) playing passive video games than girls.

CONCLUSION

Overall, our sample of youth with physical and sensory disabilities falls far short of meeting the Canadian 24-Hour Movement Guidelines for Children and Youth. The low proportion of youths' time spent engaging in sport and active play is concerning, highlighting the importance of creating access to these types of PA experiences for this population. Future population-based research is needed among children and youth with all types of disabilities to build an evidence-base of their movement behaviours.

Objectively measured sleep and telomere length in a population-based cohort of children and midlife adults

STUDY OBJECTIVES

Poor sleep patterns in older adults are associated with chromosomal telomere shortening, a marker of cellular senescence. However, studies have relied on self-reported sleep characteristics, with few data for younger individuals. We investigated whether sleep measured via actigraphy was cross-sectionally associated with telomere length in children and midlife adults.

METHODS

A population-based sample of 1874 11-12 year olds and midlife adults (mean age 44 years, SD 5.1) had biological and physical assessments at centers across Australia in 2015-2016. Sleep characteristics, including duration, onset, offset, day-to-day variability, and efficiency, were derived from actigraphy. Relative telomere length (T/S ratio) was measured by quantitative polymerase chain reaction on genomic DNA from peripheral blood. Multivariable regression models estimated associations, adjusting for prespecified confounders.

RESULTS

Both sleep and telomere data were available for 728 children and 1070 adults. Mean (SD) T/S ratio was 1.09 (0.55) in children and 0.81 (0.38) in adults. T/S ratio was not predicted by sleep duration (β 0.04, 95% confidence interval [CI] -0.02 to 0.09, p = .16, children; β -0.004, 95% CI -0.03 to 0.02, p = .70, adults) or most other sleep metrics. The only exception was a weak association between later sleep timing (the midpoint of sleep onset and offset) and longer telomeres in adults (β 0.03, 95% CI 0.01 to 0.06, p = .01).

CONCLUSIONS

Objective sleep characteristics show no convincing associations with telomere length in two largely healthy populations up to at least midlife. Sleep-telomere associations may be a late-life occurrence or may present only with a trigger such as presence of other morbidities.

Evidence for Protein Leverage in Children and Adolescents with Obesity

OBJECTIVE

The aim of this study was to test the protein leverage hypothesis in a cohort of youth with obesity.

METHODS

A retrospective study was conducted in a cohort of youth with obesity attending a tertiary weight management service. Validated food questionnaires revealed total energy intake (TEI) and percentage of energy intake from carbohydrates (%EC), fats (%EF), and proteins (%EP). Individuals with a Goldberg cutoff ≥ 1.2 of the ratio of reported TEI to basal metabolic rate from fat-free mass were included. A subgroup had accelerometer data. Statistics included modeling of percentage of energy from macronutrients and TEI, compositional data analysis to predict TEI from macronutrient ratios, and mixture models for sensitivity testing.

RESULTS

A total of 137 of 203 participants were included (mean [SD] age 11.3 [2.7] years, 68 females, BMI z score 2.47 [0.27]). Mean TEI was 10,330 (2,728) kJ, mean %EC was 50.6% (6.1%), mean %EF was 31.6% (4.9%), and mean %EP was 18.4% (3.1%). The relationship between %EP and TEI followed a power function (L coefficient -0.48; P < 0.001). TEI was inversely associated with increasing %EP. In the subgroup with < 60 min/d of moderate to vigorous physical activity (n = 48), lower BMI z scores were associated with higher %EP and moderate %EC.

CONCLUSIONS

In youth with obesity, protein dilution by either carbohydrates or fats increases TEI. Assessment of dietary protein may be useful to assist in reducing TEI and BMI in youth with obesity.

Breastfeeding and childhood obesity: A 12-country study

This study aimed to examine the association between breastfeeding and childhood obesity. A multinational cross‐sectional study of 4,740 children aged 9–11 years was conducted from 12 countries. Infant breastfeeding was recalled by parents or legal guardians. Height, weight, waist circumference, and body fat were obtained using standardized methods. The overall prevalence of obesity, central obesity, and high body fat were 12.3%, 9.9%, and 8.1%, respectively. After adjustment for maternal age at delivery, body mass index (BMI), highest maternal education, history of gestational diabetes, gestational age, and child's age, sex, birth weight, unhealthy diet pattern scores, moderate‐to‐vigorous physical activity, sleeping, and sedentary time, exclusive breastfeeding was associated with lower odds of obesity (odds ratio [OR] 0.76, 95% confidence interval, CI [0.57, 1.00]) and high body fat (OR 0.60, 95% CI [0.43, 0.84]) compared with exclusive formula feeding. The multivariable‐adjusted ORs based on different breastfeeding durations (none, 1–6, 6–12, and > 12 months) were 1.00, 0.74, 0.70, and 0.60 for obesity (P_trend = .020) and 1.00, 0.64, 047, and 0.64 for high body fat (P_trend = .012), respectively. These associations were no longer significant after adjustment for maternal BMI. Breastfeeding may be a protective factor for obesity and high body fat in 9‐ to 11‐year‐old children from 12 countries.

Validity and bias on the online active Australia survey: activity level and participant factors associated with self-report bias

Background

This study examined the criterion validity of the online Active Australia Survey, using accelerometry as the criterion, and whether self-report bias was related to level of activity, age, sex, education, body mass index and health-related quality of life.

Methods

The online Active Australia Survey was validated against the GENEActiv accelerometer as a direct measure of activity. Participants (n = 344) wore an accelerometer for 7 days, completed the Active Australia Survey, and reported their health and demographic characteristics. A Spearman’s rank coefficient examined the association between minutes of moderate-to-vigorous physical activity recorded on the Active Australia Survey and GENEActiv accelerometer. A Bland-Altman plot illustrated self-report bias (the difference between methods). Linear mixed effects modelling was used to examine whether participant factors predicted self-report bias.

Results

The association between moderate-to-vigorous physical activity reported on the online Active Australia Survey and accelerometer was significant (r_s = .27, p < .001). Participants reported 4 fewer minutes per day on the Active Australia Survey than was recorded by accelerometry (95% limits of agreement −104 – 96 min) but the difference was not significant (t(343) = −1.40, p = .16). Self-report bias was negatively associated with minutes of accelerometer-recorded moderate-to-vigorous physical activity and positively associated with mental health-related quality of life.

Conclusions

The online Active Australia Survey showed limited criterion validity against accelerometry. Self-report bias was related to activity level and mental health-related quality of life. Caution is recommended when interpreting studies using the online Active Australia Survey.

Analysing how physical activity competes: a cross-disciplinary application of the Duplication of Behaviour Law

Background

Despite the ongoing promotion of physical activity, the rates of physical inactivity remain high. Drawing on established methods of analysing consumer behaviour, this study seeks to understand how physical activity competes for finite time in a day – how Exercise and Sport compete with other everyday behaviours, and how engagement in physical activity is shared across Exercise and Sport activities. As targeted efforts are common in physical activity intervention and promotion, the existence of segmentation is also explored.

Methods

Time-use recall data (n = 2307 adults) is analysed using the Duplication of Behaviour Law, and tested against expected values, to document what proportion of the population that engage in one activity, also engage in another competing activity. Additionally, a Mean Absolute Deviation approach is used to test for segmentation.

Results

The Duplication of Behaviour Law is evident for everyday activities, and Exercise and Sport activities – all activities ‘compete’ with each other, and the prevalence of the competing activity determines the extent of competition. However, some activities compete more or less than expected, suggesting the combinations of activities that should be used or avoided in promotion efforts. Competition between everyday activities is predictable, and there are no specific activities that are sacrificed to engage in Exercise and Sport. How people share their physical activity across different Exercise and Sport activities is less predictable – Males and younger people (under 20 years) are more likely to engage in Exercise and Sport, and those who engage in Exercise and Sport are slightly more likely to Work and Study. High competition between Team Sports and Non-Team Sports suggests strong preferences for sports of different varieties. Finally, gender and age-based segmentation does not exist for Exercise and Sport relative to other everyday activities; however, segmentation does exist for Team Sports, Games, Active Play and Dance.

Conclusions

The Duplication of Behaviour Law demonstrates that population-level patterns of behaviour can yield insight into the competition between different activities, and how engagement in physical activity is shared across different Exercise and Sport activities. Such insights can be used to describe and predict physical activity behaviour and may be used to inform and evaluate promotion and intervention.

Research Combining Physical Activity and Sleep: A Bibliometric Analysis

This study used a bibliometric analysis through the Scopus database to examine papers that combined physical activity and sleep, published between 1979 and 2018. Bibliometric indicators of productivity included publication volume and citation distribution, top 10 authors, average authors per paper, single- and multicountry collaboration, collaborative index, top 10 countries, leading journals, highly cited papers and network visualization for coauthorship, international collaboration, and co-occurrence of author keywords. The initial search identified 1,509 papers, of which 607 passed through comprehensive screening and were included in the final analysis. Most of the papers were research articles (90.8%) and published in English (90.8%). Most papers (81.4%) were published within the past decade, 2009–2018. The mean number of papers published per year was 15.2, the mean number of citations per paper was 257.3, and the mean number of authors per paper was 5.5. International collaboration was evident for 21.6% of the papers, and 95.6% of papers were multiauthored. The most prolific publishing institutions and authors were from the United States, Canada, Australia, Switzerland, and Brazil. Keyword analysis suggested that almost all age groups and study designs were covered, but most papers focus on noncommunicable diseases. Although there has been a rise in scientific production on combined physical activity and sleep research in recent years, future work in this area should include researchers from developing countries.

Outdoor time and dietary patterns in children around the world

Background

Whether outdoor time is linked to dietary patterns of children has yet to be empirically tested. The objective of this study was to examine the association between outdoor time and dietary patterns of children from 12 countries around the world.

Methods

This multinational, cross-sectional study included 6229 children 9-11 years of age. Children self-reported the time that they spent outside before school, after school and on weekends. A composite score was calculated to reflect overall daily outdoor time. Dietary patterns were assessed using a food frequency questionnaire, and two components were used for analysis: healthy and unhealthy dietary pattern scores.

Results

On average, children spent 2.5 h outside per day. After adjusting for age, sex, parental education, moderate-to-vigorous physical activity, screen time and body mass index z-score, greater time spent outdoors was associated with healthier dietary pattern scores. No association was found between outdoor time and unhealthy dietary pattern scores. Similar associations between outdoor time and dietary patterns were observed for boys and girls and across study sites.

Conclusions

Greater time spent outside was associated with a healthier dietary pattern in this international sample of children. Future research should aim to elucidate the mechanisms behind this association.

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

BACKGROUND

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

METHOD

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

RESULTS

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

CONCLUSIONS

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

Sleep characteristics and health-related quality of life in 9- to 11-year-old children from 12 countries

INTRODUCTION

Previous studies have linked short sleep duration, poor sleep quality, and late sleep timing with lower health-related quality of life (HRQoL) in children. However, almost all studies relied solely on self-reported sleep information, and most studies were conducted in high-income countries. To address these gaps, we studied both device-measured and self-reported sleep characteristics in relation to HRQoL in a sample of children from 12 countries that vary widely in terms of economic and human development.

METHODS

The study sample included 6,626 children aged 9-11 years from Australia, Brazil, Canada, China, Colombia, Finland, India, Kenya, Portugal, South Africa, the United Kingdom, and the United States. Waist-worn actigraphy was used to measure total sleep time, bedtime, wake-up time, and sleep efficiency on both weekdays and weekends. Children also reported ratings of sleep quantity and quality. HRQoL was measured by the KIDSCREEN-10 survey. Multilevel regression models were used to determine the relationships between sleep characteristics and HRQoL.

RESULTS

Results showed considerable variation in sleep characteristics, particularly duration and timing, across study sites. Overall, we found no association between device-measured total sleep time, sleep timing or sleep efficiency, and HRQoL. In contrast, self-reported ratings of poor sleep quantity and quality were associated with HRQoL.

CONCLUSIONS

Self-reported, rather than device-based, measures of sleep are related to HRQoL in children. The discrepancy related to sleep assessment methods highlights the importance of considering both device-measured and self-reported measures of sleep in understanding its health effects.

Changes in weight status, quality of life and behaviours of South Australian primary school children: results from the Obesity Prevention and Lifestyle (OPAL) community intervention program

Background

Childhood obesity is a serious public health concern worldwide. Community-based obesity prevention interventions offer promise due to their focus on the broader social, cultural and environmental contexts rather than individual behaviour change and their potential for sustainability and scalability. This paper aims to determine the effectiveness of a South Australian community-based, multi-setting, multi-strategy intervention, OPAL (Obesity Prevention and Lifestyle), in increasing healthy weight prevalence in 9 to 11-year-olds.

Methods

A quasi-experimental repeated cross-sectional design was employed. This paper reports on the anthropometric, health-related quality of life (HRQoL) and behaviour outcomes of primary school children (9–11 years) after 2–3 years of intervention delivery. Consenting children from primary schools (20 intervention communities, INT; 20 matched comparison communities, COMP) completed self-report questionnaires on diet, activity and screen time behaviours. HRQoL was measured using the Child Health Utility 9D. Body Mass Index (BMI) z-score and weight status were determined from children’s measured height and weight. A multilevel mixed-effects model, accounting for clustering in schools, was implemented to determine intervention effect. Sequential Bonferroni adjustment was used to allow for multiple comparisons of the secondary outcomes.

Results

At baseline and final, respectively, 2611 and 1873 children completed questionnaires and 2353 and 1760 had anthropometric measures taken. The prevalence of children with healthy weight did not significantly change over time in INT (OR 1.11, 95%CI 0.92–1.35, p = 0.27) or COMP (OR 0.85, 95%CI 0.68–1.06, p = 0.14). Although changes in the likelihood of obesity, BMI z-score and HRQoL favoured the INT group, the differences were not significant after Bonferroni adjustment. There were also no significant differences between groups at final for behavioural outcomes.

Conclusions

OPAL did not have a significant impact on the proportion of 9 to 11-year-olds in the healthy weight range, nor children’s BMI z-score, HRQoL and behaviours. Long-term, flexible community-based program evaluation approaches are required .

Trial registration

ACTRN12616000477426 (12th April 2016, retrospectively registered).

Cross-sectional and longitudinal associations between active commuting and patterns of movement behaviour during discretionary time: A compositional data analysis

Background

Active living approaches seek to promote physical activity and reduce sedentary time across different domains, including through active travel. However, there is little information on how movement behaviours in different domains relate to each other. We used compositional data analysis to explore associations between active commuting and patterns of movement behaviour during discretionary time.

Methods and findings

We analysed cross-sectional and longitudinal data from the UK Biobank study. At baseline (2006–2010) and follow up (2009–2013) participants reported their mode of travel to work, dichotomised as active (walking, cycling or public transport) or inactive (car). Participants also reported activities performed during discretionary time, categorised as (i) screen time; (ii) walking for pleasure; and (iii) sport and do-it-yourself (DIY) activities, summed to produce a total. We applied compositional data analysis to test for associations between active commuting and the composition and total amount of discretionary time, using linear regression models adjusted for covariates. Adverse events were not investigated in this observational analysis. The survey response rate was 5.5%. In the cross-sectional analysis (n = 182,406; mean age = 52 years; 51% female), active commuters engaged in relatively less screen time than those who used inactive modes (coefficient -0.12, 95% confidence interval [CI] -0.13 to -0.11), equating to approximately 60 minutes less screen time per week. Similarly, in the longitudinal analysis (n = 4,323; mean age = 51 years; 49% female) there were relative reductions in screen time in those who used active modes at both time points compared with those who used inactive modes at both time points (coefficient -0.15, 95% confidence interval [CI] -0.24 to -0.06), equating to a difference between these commute groups of approximately 30 minutes per week at follow up. However, as exposures and outcomes were measured concurrently, reverse causation is possible.

Conclusions

Active commuting was associated with a more favourable pattern of movement behaviour during discretionary time. Active commuters accumulated 30–60 minutes less screen time per week than those using inactive modes. Though modest, this could have a cumulative effect on health over time.

Sleep: population epidemiology and concordance in Australian children aged 11-12 years and their parents

OBJECTIVES

To describe objectively measured sleep characteristics in children aged 11-12 years and in parents and to examine intergenerational concordance of sleep characteristics.

DESIGN

Population-based cross-sectional study (the Child Health CheckPoint), nested within the Longitudinal Study of Australian Children.

SETTING

Data were collected between February 2015 and March 2016 across assessment centres in Australian major cities and selected regional towns.

PARTICIPANTS

Of the participating CheckPoint families (n=1874), sleep data were available for 1261 children (mean age 12 years, 50% girls), 1358 parents (mean age 43.8 years; 88% mothers) and 1077 biological parent-child pairs. Survey weights were applied and statistical methods accounted for the complex sample design, stratification and clustering within postcodes.

OUTCOME MEASURES

Parents and children were asked to wear a GENEActive wrist-worn accelerometer for 8 days to collect objective sleep data. Primary outcomes were average sleep duration, onset, offset, day-to-day variability and efficiency. All sleep characteristics were weighted 5:2 to account for weekdays versus weekends. Biological parent-child concordance was quantified using Pearson's correlation coefficients in unadjusted models and regression coefficients in adjusted models.

RESULTS

The mean sleep duration of parents and children was 501 min (SD 56) and 565 min (SD 44), respectively; the mean sleep onset was 22:42 and 22:02, the mean sleep offset was 07:07 and 07:27, efficiency was 85.4% and 84.1%, and day-to-day variability was 9.9% and 7.4%, respectively. Parent-child correlation for sleep duration was 0.22 (95% CI 0.10 to 0.28), sleep onset was 0.42 (0.19 to 0.46), sleep offset was 0.58 (0.49 to 0.64), day-to-day variability was 0.25 (0.09 to 0.34) and sleep efficiency was 0.23 (0.10 to 0.27).

CONCLUSIONS

These normative values for objective sleep characteristics suggest that, while most parents and children show adequate sleep duration, poor-quality (low efficiency) sleep is common. Parent-child concordance was strongest for sleep onset/offset, most likely reflecting shared environments, and modest for duration, variability and efficiency.

Body composition: population epidemiology and concordance in Australian children aged 11-12 years and their parents

OBJECTIVES

Overweight and obesity remain at historically high levels, cluster within families and are established risk factors for multiple diseases. We describe the epidemiology and cross-generational concordance of body composition among Australian children aged 11-12 years and their parents.

DESIGN

The population-based cross-sectional Child Health CheckPoint study, nested within the Longitudinal Study of Australian Children (LSAC).

SETTING

Assessment centres in seven major Australian cities and eight regional cities, or home visits; February 2015-March 2016.

PARTICIPANTS

Of all participating CheckPoint families (n=1874), body composition data were available for 1872 children (49% girls) and 1852 parents (mean age 43.7 years; 88% mothers), including 1830 biological parent-child pairs.

MEASURES

Height, weight, body mass index (BMI), waist circumference and waist-to-height ratio for all participants; body fat and fat-free mass by four-limb bioimpedence analysis (BIA) at assessment centres, or body fat percentage by two-limb BIA at home visits. Analysis: parent-child concordance was assessed using (i) Pearson's correlation coefficients, and (ii) partial correlation coefficients adjusted for age, sex and socioeconomic disadvantage. Survey weights and methods accounted for LSAC's complex sample design.

RESULTS

20.7% of children were overweight and 6.2% obese, as were 33.5% and 31.6% of parents. Boys and girls showed similar distributions for all body composition measures but, despite similar BMI and waist-to-height ratio, mothers had higher proportions of total and truncal fat than fathers. Parent-child partial correlations were greatest for height (0.37, 95% CI 0.33 to 0.42). Other anthropometric and fat/lean measures showed strikingly similar partial correlations, ranging from 0.25 (95% CI 0.20 to 0.29) for waist circumference to 0.30 (95% CI 0.25 to 0.34) for fat-free percentage. Whole-sample and sex-specific percentile values are provided for all measures.

CONCLUSIONS

Excess adiposity remains prevalent in Australian children and parents. Moderate cross-generational concordance across all measures of leanness and adiposity is already evident by late childhood.

Physical activity and sedentary activity: population epidemiology and concordance in Australian children aged 11-12 years and their parents

OBJECTIVES

To describe the epidemiology and parent-child concordance of objectively measured physical activity in a population-based sample of Australian parent-child dyads.

DESIGN

Cross-sectional study (Child Health CheckPoint) nested within the Longitudinal Study of Australian Children.

SETTING

Assessment centres in seven Australian cities and eight regional towns or home visits; February 2015-March 2016.

PARTICIPANTS

Of all CheckPoint families (n=1874), 1261 children (50% girls) and 1358 parent (88% mothers) provided objectively measured activity data, comprising 1077 parent-child dyads.

OUTCOME MEASURES

Activity behaviour was assessed by GENEActiv accelerometer. Duration of moderate-to-vigorous physical activity (MVPA) and vigorous physical activity and sedentary behaviour (SB) were derived using Cobra custom software, along with MVPA/SB fragmentation and mean daily activity. Pearson's correlation coefficients and linear regression estimated parent-child concordance. Survey weights and methods accounted for the complex sample design and clustering.

RESULTS

Although parents had average lower accelerometry counts than children (mean [SD] 209 [46] vs 284 [71] g.min), 93% of parents met MVPA daily duration guidelines on published cutpoints (mean [SD] 125 [63] min/day MVPA), compared with only 15% of children (mean 32 [27] min). Parents showed less daily SB duration (parents: 540 [101], children: 681 [69] minutes) and less fragmented accumulation of MVPA (parents: α=1.85, children: α=2.00). Parent-child correlation coefficients were 0.16 (95% CI 0.11 to 0.22) for MVPA duration, 0.10 (95% CI 0.04 to 0.16) for MVPA fragmentation, 0.16 (95% CI 0.11 to 0.22) for SB duration and 0.18 (95% CI 0.12 to 0.23) for SB fragmentation.

CONCLUSIONS

Standardised cutpoints are needed for objective activity measures to inform activity guidelines across the lifecourse. This may reflect large amounts of time in non-shared environments (school and work).

The Association of the Body Composition of Children with 24-Hour Activity Composition

OBJECTIVES

To evaluate how the reallocation of time between sleep, sedentary time, light, and moderate-vigorous activities is associated with children's body composition.

STUDY DESIGN

Population-based cross-sectional Child Health CheckPoint within the Longitudinal Study of Australian Children (n = 938 11-12 year-olds, 50% boys). Twenty-four hour activity composition via accelerometry (minutes/day of sleep, sedentary time, light, and moderate-to-vigorous physical activity [MVPA]) and 3-part body composition (percentage truncal fat, percentage nontruncal fat, and percentage fat-free mass) via bioelectrical impedance analysis were measured. We estimated differences in 3-part body composition associated with the incremental reallocation of time between activities, using dual-compositional regression models adjusted for sex, age, puberty, and socioeconomic position.

RESULTS

Reallocation of time between MVPA and any other activity was strongly associated with differences in body composition. Adverse body composition differences were larger for a given MVPA decrease than were the beneficial differences for an equivalent MVPA increase. For example, 15 minutes less MVPA (relative to remaining activities) was associated with absolute percentage differences of +1.7% (95% CI 1.2; 2.4) for truncal fat, +0.8% (0.6; 1.2) for nontruncal fat, and -2.6% (-3.5; -1.9) for fat-free mass, and a 15-minute increase was associated with -0.7% (-0.9; -0.5) truncal fat, -0.4% (-0.5; -0.3) nontruncal fat, and +1.1% (0.9; 1.5) fat-free mass. Reallocations between sleep, sedentary time, and light physical activity were not associated with differences in body composition.

CONCLUSIONS

Preventing declines in MVPA during inactive periods (eg, holidays) may be an important intervention goal. More MVPA, instead of other activities, may benefit body composition.

International Study of Childhood Obesity, Lifestyle and the Environment (ISCOLE): Contributions to Understanding the Global Obesity Epidemic

The purpose of this review is to summarize the scientific contributions of the International Study of Childhood Obesity, Lifestyle and the Environment (ISCOLE) in extending our understanding about obesity in children from around the world. ISCOLE was a multi-national study of 9 to 11 year-old children from sites in 12 countries from all inhabited continents. The primary purpose was to investigate relationships between lifestyle behaviors and obesity, and the influence of higher-order characteristics such as behavioral settings, and physical, social and policy environments. ISCOLE has made several advances in scientific methodology related to the assessment of physical activity, dietary behavior, sleep and the neighborhood and school environments. Furthermore, ISCOLE has provided important evidence on (1) epidemiological transitions in obesity and related behaviors, (2) correlates of obesity and lifestyle behaviors at the individual, neighborhood and school levels, and (3) 24-h movement behaviors in relation to novel analytical techniques. A key feature of ISCOLE was the development of a platform for international training, data entry, and data quality for multi-country studies. Finally, ISCOLE represents a transparent model for future public-private research partnerships across low, middle and high-income countries.

Physical Education Classes, Physical Activity, and Sedentary Behavior in Children

PURPOSE

This study aimed to examine the associations between participation frequency in physical education (PE) classes and objective measures of physical activity (PA) and sedentary behavior (SB) in children from 12 countries at different levels of development.

METHODS

This multinational, cross-sectional study included 5874 children 9-11 yr old from sites in Australia, Brazil, Canada, China, Colombia, Finland, India, Kenya, Portugal, South Africa, the United Kingdom, and the United States. PA and SB were monitored for seven consecutive days using a waist-worn accelerometer. PA and SB data were presented for weekdays (times in and out of school) and weekend days. Participation frequency in PE classes was determined by questionnaire. Multilevel modeling analyses stratified by sex were used.

RESULTS

Overall, 24.8% of children self-reported participation in PE classes ≥3 times per week (25.3% in high-income countries [HIC] and 24.3% in low- and middle-income countries [LMIC]). After adjusting for age, sex, parental education, and body mass index z-score, results showed that children from low- and middle-income countries who took PE classes one to two times per week were more likely to present better indicators of PA and shorter time in SB in and out of school. In HIC, boys that participated in PE classes were more likely to meet the moderate-to-vigorous PA recommendations and to present better indicators of PA (in school) and shorter time in SB in and out of school. For girls in HIC, attending PE classes increased the likelihood of spending more time in moderate-to-vigorous PA, especially if they attended ≥3 times per week.

CONCLUSION

Attending PE classes is associated with a higher level of PA and a lower level of SB in and out of school during weekdays in children from countries at various levels of development.

Associations between meeting combinations of 24-hour movement recommendations and dietary patterns of children: A 12-country study

The purpose of this study was to examine whether meeting movement behavior recommendations (i.e., ≥60 min of moderate-to-vigorous physical activity [MVPA] per day, ≤2 h of recreational screen time per day, and between 9 and 11 h of nightly sleep), and combinations of these recommendations, are associated with dietary patterns of children. This cross-sectional study was conducted between 2011 and 2013 and included 5873 children 9-11 years of age from 12 countries around the world. MVPA and nightly sleep duration were measured using 24-hour waist-worn accelerometry. Screen time habits were assessed via self-report. A food frequency questionnaire was used to assess dietary patterns, and the whole diet was described by two components derived from principal component analysis: "healthy" and "unhealthy" dietary pattern scores. Covariates included in the multilevel statistical models included age, sex, highest parental education, and body mass index z-score. A healthier dietary pattern score was observed when more movement behavior recommendations were met. Among the three movement behaviors, limiting screen time habits to the recommended amount was most strongly associated with healthier dietary patterns. Similarly, a less unhealthy dietary pattern was observed when more movement behavior recommendations were met. Surprisingly, the highest unhealthy dietary pattern was associated with children meeting the MVPA recommendation alone. Combinations including ≤2 h of screen time per day were those most strongly associated with a less unhealthy dietary pattern. Findings were similar across study sites and in boys and girls. In conclusion, meeting more movement behavior recommendations is generally associated with better dietary patterns in children from around the world, with limiting screen time habits showing the strongest relationships.

Body Image Dissatisfaction and the Adrenarchal Transition

BACKGROUND

Puberty marks a transition in risk for body image disturbance and disordered eating. Yet few studies have examined these symptoms across puberty and none have examined links with adrenarche, the earliest phase in the pubertal hormonal cascade.

METHOD

Levels of adrenal androgens (dehydroepiandrosterone, dehydroepiandrosterone sulphate, and testosterone) were measured in a population-based study of 8- to 9-year-old children (516 males and 621 females). Body dissatisfaction was measured using the Kids' Eating Disorder Scale Silhouettes. Covariates included body mass index, age, and socioeconomic status.

RESULTS

There were significant associations between adrenal androgen levels and greater body dissatisfaction in both males and females. Specifically, females with more advanced levels of dehydroepiandrosterone and testosterone relative to peers, and males with more advanced levels of testosterone relative to peers, reported greater body dissatisfaction. However, after adjusting for covariates, hormones levels were no longer associated with body dissatisfaction, and only higher body mass index had a clear association with body dissatisfaction.

CONCLUSIONS

The adrenarchal transition brings a heightened risk for body dissatisfaction. Whether this arises from the neuroendocrine effects of adrenal androgens or as a reaction to the greater body mass that accompanies adrenarche requires further exploration.