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

Factors impacting physical activity among post-treatment pediatric cancer survivors with overweight and obesity

BACKGROUND

Pediatric cancer survivors (PCS) with overweight and obesity are at risk for various secondary chronic diseases. Although previous research has found physical activity (PA) as beneficial after treatment, the PA levels are low among PCS, highlighting the need for lifestyle interventions targeting PA.

METHODS

A secondary analysis of preliminary baseline data from a multi-site trial, NOURISH-T + , a healthy lifestyle intervention for PCS with overweight and obesity, and their caregivers, was conducted to assess factors related to PCS PA (i.e., moderate to vigorous intensity PA, MVPA). Kendall's Tau-b was used to assess correlations between PCS MVPA, health and treatment-related factors, and caregivers' sedentary behavior and MVPA. Wilcoxon Signed Ranks Test was used to assess the differences between PCS and caregiver sedentary behavior and MVPA. A multiple linear regression analysis was performed to determine predictors of PCS MVPA.

RESULTS

Seventy-three PCS-caregiver dyads were included in this analysis (N = 146). Many of the PCS were female, diagnosed with Acute Lymphoblastic Leukemia, stage 1, with a mean body mass index (BMI) percentile of 94.4 ± 4.7. Caregivers were female and parents to the PCS. Significant correlations were found between PCS MVPA, time since treatment, PCS weight change since COVID, caregiver sedentary behavior and MVPA. Significant differences were observed between PCS and caregiver sedentary behavior and MVPA. Household income, radiation treatment, and caregiver MVPA were significant predictors of PCS MVPA.   Conclusions: Demographics, cancer treatment type, and caregiver role modeling are important factors to consider when developing future lifestyle interventions for PCS. (NCT04656496, registered 12-07-2020).

WHAT IS KNOWN

• Parents/caregivers are presumed to be a potential influence on their children's physical activity What is new: • Parents/caregivers' moderate-to-vigorous physical activity is the strongest predictor of their children's (pediatric cancer survivors') physical activity.

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

BACKGROUND

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

AIMS

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

METHODS

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

RESULTS

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

CONCLUSION

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

Historical development of accelerometry measures and methods for physical activity and sedentary behavior research worldwide: A scoping review of observational studies of adults

This scoping review identified observational studies of adults that utilized accelerometry to assess physical activity and sedentary behavior. Key elements on accelerometry data collection were abstracted to describe current practices and completeness of reporting. We searched three databases (PubMed, Web of Science, and SPORTDiscus) on June 1, 2021 for articles published up to that date. We included studies of non-institutionalized adults with an analytic sample size of at least 500. The search returned 5686 unique records. After reviewing 1027 full-text publications, we identified and abstracted accelerometry characteristics on 155 unique observational studies (154 cross-sectional/cohort studies and 1 case control study). The countries with the highest number of studies included the United States, the United Kingdom, and Japan. Fewer studies were identified from the continent of Africa. Five of these studies were distributed donor studies, where participants connected their devices to an application and voluntarily shared data with researchers. Data collection occurred between 1999 to 2019. Most studies used one accelerometer (94.2%), but 8 studies (5.2%) used 2 accelerometers and 1 study (0.6%) used 4 accelerometers. Accelerometers were more commonly worn on the hip (48.4%) as compared to the wrist (22.3%), thigh (5.4%), other locations (14.9%), or not reported (9.0%). Overall, 12.7% of the accelerometers collected raw accelerations and 44.6% were worn for 24 hours/day throughout the collection period. The review identified 155 observational studies of adults that collected accelerometry, utilizing a wide range of accelerometer data processing methods. Researchers inconsistently reported key aspects of the process from collection to analysis, which needs addressing to support accurate comparisons across studies.

Associations between meeting 24-hour movement guidelines and academic achievement in Australian primary school-aged children

BACKGROUND

Few studies have investigated associations between academic achievement and meeting recommendations from the 24-hour (24-h) movement guidelines. The specific guidelines associated with the most benefit academic achievement are unknown. Utilizing both self-report and objective movement data, this study examined associations between academic achievement and meeting individual recommendations and combinations of recommendations from the 24-h movement guidelines (sleep, physical activity, and screen time).

METHODS

Data from CheckPoint, a cross-sectional study nested between Waves 6 and 7 of the Longitudinal Study of Australian Children, were used. Movement behaviors were measured using 24-h wrist-worn accelerometry (GENEActiv (Activinsights, Kimbolton, UK)) and were self-reported by children using the Multimedia Activity Recall for Children and Adolescents. Academic achievement was measured using a nationally administered standardized test in literacy and numeracy. Analysis of covariance, with t tests with sequential Bonferroni adjustments, was used to compare academic achievement with all possible combinations of meeting recommendations, adjusting for demographic confounders. Two models were considered: guideline compliance assessed by self-report (n = 1270, mean age = 11.99 years, 52% males) and by accelerometry (for moderate-to-vigorous intensity physical activity (MVPA) and sleep)) and self-report (screen time) in combination (n = 927, mean age = 11.97 years, 52% males).

RESULTS

Literacy achievement significantly differed based on self-report (F_{(7, 1258)} = 3.08, p = 0.003) and accelerometer derived (F_{(7, 915)} = 2.40, p = 0.02) guideline compliance. Numeracy achievement significantly differed based on self-report (F_{(7, 1258)} = 2.92, p = 0.005) but not accelerometer derived guideline compliance (F_{(7, 915)} = 0.80, p = 0.58). When assessed by self-report, children who met all guidelines (t₍₃₃₄₎ = -4.05, p = 0.0001) or met the screen time and sleep guidelines in combination (t₍₁₂₅₎ = -5.02, p < 0.001) had superior literacy achievement. Meeting the self-report MVPA guideline in any combination was associated with higher numeracy scores (p < 0.05). Post-hoc analyses showed no differences in academic achievement for any category of accelerometer derived guideline compliance.

CONCLUSION

The findings suggest that limiting recreational screen time is important for literacy achievement and that encouraging compliance with the MVPA guideline is important for numeracy achievement.

Association between objectively measured physical activity of parents and children: The 2015 Pelotas birth cohort

OBJECTIVE

The present study aims to verify the association between objectively measured physical activity (PA) of parents and child in the 2015 Pelotas Birth Cohort, a population-based Brazilian birth cohort.

METHODS

The main exposures were paternal moderate-to-vigorous PA (MVPA) collected when children were 1-year of age, and maternal MVPA when children were 2-years. The outcome was children's overall PA (ENMO in mg) at 4-years of age. PA was measured using wrist-worn ActiGraph accelerometers during seven complete days. Potential confounders were maternal age, maternal and paternal education, and household asset index. Crude and adjusted analyses were performed using linear regressions.

RESULTS

Our analytical sample comprised 1326 children with valid accelerometer data and with both parents. Mean child PA was 48.1 mg, being higher among boys compared with girls (Boys: 50 mg, 95% CI: 49.1; 50.9; Girls: 46 mg, 95% CI: 45.2; 46.8). Children's PA at 4 years was positively associated with maternal MVPA at age 2 years (p < 0.001) and paternal MVPA at age 1 year (p < 0.001). A child with both parents in the highest tertile of unbouted MVPA presented higher overall PA (p = 0.001). Similar results were found for boys; however, for girls, paternal unbouted MVPA was not associated with overall PA.

CONCLUSION

Overall, our results showed a positive impact of maternal and parental PA over 4-year-old children acceleration. These findings could be valuable when planning evidence-based interventions and policies to promote PA in young children, providing a broader perspective over the role of parents over children's behavior.

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.

Backyard benefits? A cross-sectional study of yard size and greenness and children's physical activity and outdoor play

BACKGROUND

The home environment is the most important location in young children's lives, yet few studies have examined the relationship between the outdoor home environment and child physical activity levels, and even fewer have used objectively measured exposures and outcomes. This study examined relationships between objectively assessed home yard size and greenness, and child physical activity and outdoor play.

METHODS

Data were drawn from the HealthNuts study, a longitudinal study of 5276 children in Melbourne, Australia. We used cross-sectional data from a sample at Wave 3 (2013-2016) when participants were aged 6 years (n = 1648). A sub-sample of 391 children had valid accelerometer data collected from Tri-axial GENEActive accelerometers worn on their non-dominant wrist for 8 consecutive days. Yard area and greenness were calculated using geographic information systems. Objective outcome measures were minutes/day in sedentary, light, and moderate-vigorous physical activity (weekday and weekend separately). Parent-reported outcome measures were minutes/day playing outdoors (weekend and weekday combined). Multi-level regression models (adjusted for child's sex, mother's age at the birth of child, neighbourhood socioeconomic index, maternal education, and maternal ethnicity) estimated effects of yard size and greenness on physical activity.

RESULTS

Data were available on outdoor play for 1648 children and usable accelerometer data for 391. Associations between yard size/greenness and components of physical activity were minimal. For example, during weekdays, yard size was not associated with daily minutes in sedentary behaviour (β: 2.4, 95% CI: - 6.2, 11.0), light physical activity (β: 1.4, 95% CI: - 5.7, 8.5) or MVPA (β: -2.4, 95% CI: - 6.5, 1.7), with similar patterns at weekends. There was no relationship between median annual yard greenness and physical activity or play.

CONCLUSION

In our study of young children residing in higher socio-economic areas of Melbourne yard characteristics did not appear to have a major impact on children's physical activity. Larger studies with greater variation in yard characteristics and identification of activity location are needed to better understand the importance of home outdoor spaces and guide sustainable city planning.

Maternal Education and Academic Achievement in Schoolchildren: The Role of Cardiorespiratory Fitness

OBJECTIVES

To examine the relationship between maternal education, cardiorespiratory fitness, and academic achievement in schoolchildren, specifically whether the association between maternal education and academic achievement is mediated by cardiorespiratory fitness.

STUDY DESIGN

This is a secondary analysis of a cross-sectional study including 478 Spanish schoolchildren aged 8-11 years. ANOVA was used to test differences in cardiorespiratory fitness by maternal education level. ANCOVA was used to test the differences in academic achievement by the educational level of mothers and the cardiorespiratory fitness of children, controlling for each other. A mediation analysis was used to test if the relationship between maternal education and academic achievement was explained by cardiorespiratory fitness.

RESULTS

A higher level of maternal education was associated with a higher cardiorespiratory fitness level and academic achievement in children; moreover, the cardiorespiratory fitness level in children was associated with better academic achievement (P < .05). Finally, cardiorespiratory fitness acted as a partial mediator of the relationship between maternal education and academic achievement in boys (z = 1.81; P = .03) but not in girls (z = 0.86; P = .19), explaining 6.54% of this relationship for the total sample and 6.67% for boys.

CONCLUSIONS

This study suggests that the benefits of maternal education on academic achievement are partially explained by the mediating role of cardiorespiratory fitness.

Are young children with asthma more likely to be less physically active?

BACKGROUND

Previous research suggests that children who experience asthma may be less physically active; however, results have been inconclusive. This study aimed to investigate whether the presence of asthma or wheeze is associated with lower physical activity levels in children, and whether sex, body mass index or earlier asthma or wheeze status modifies the association.

METHODS

This study was conducted in 391 HealthNuts participants in Melbourne, Australia. Asthma and wheeze data were collected via questionnaire at age 4 and 6, and physical activity was measured through accelerometry. Using adjusted linear regression models, the cross-sectional and longitudinal associations were investigated.

RESULTS

There was no evidence of a difference in time spent in moderate-to-vigorous physical activity (MVPA) at age 6 years between children with and without asthma at age 4; children with asthma spent 8.3 minutes more time physically active per day (95% CI: -5.6, 22.1, P = .24) than children without asthma. Similar results were seen for children with current wheeze (5.8 minutes per day more, 95% CI: -5.9, 17.5, P = .33) or ever wheeze or asthma (7.7 minutes per day more, 95% CI: -4.8, 20.2, P = .23) at age 4 years. Comparable null results were observed in the cross-sectional analyses. Interaction with BMI could not be assessed; however, previous asthma or wheeze status and sex were not found to modify these associations.

CONCLUSION

This analysis found no evidence of asthma hindering physical activity in these young children. These results are encouraging, as they indicate that the Australian asthma and physical activity public health campaigns are being effectively communicated and adopted by the public.

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.

Physical Activity Intensity Cut-Points for Wrist-Worn GENEActiv in Older Adults

Purpose: This study aims to (1) establish GENEActiv intensity cutpoints in older adults and (2) compare the classification accuracy between dominant (D) or non-dominant (ND) wrist, using both laboratory and free-living data.

Methods: Thirty-one older adults participated in the study. They wore a GENEActiv Original on each wrist and performed nine activities of daily living. A portable gas analyzer was used to measure energy expenditure for each task. Testing was performed on two occasions separated by at least 8 days. Some of the same participants (n = 13) also wore one device on each wrist during 3 days of free-living. Receiver operating characteristic analysis was performed to establish the optimal cutpoints.

Results: For sedentary time, both dominant and non-dominant wrist had excellent classification accuracy (sensitivity 0.99 and 0.97, respectively; specificity 0.91 and 0.86, respectively). For Moderate to Vigorous Physical Activity (MVPA), the non-dominant wrist device had better accuracy (ND sensitivity: 0.90, specificity 0.79; D sensitivity: 0.90, specificity 0.64). The corresponding cutpoints for sedentary-to-light were 255 and 375 g · min (epoch independent: 42.5 and 62.5 mg), and those for the light-to-moderate were 588 and 555 g · min (epoch-independent: 98.0 and 92.5 mg) for the non-dominant and dominant wrist, respectively. For free-living data, the dominant wrist device resulted in significantly more sedentary time and significantly less light and MVPA time compared to the non-dominant wrist.

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).

Sedentary Behavior in Children With Cerebral Palsy Between 1.5 and 12 Years: A Longitudinal Study

PURPOSE

To determine longitudinal change in sedentary behavior in children with cerebral palsy (CP) from 1.5 to 12 years.

METHODS

Ninety-one children, Gross Motor Function Classification System (GMFCS) levels I to III, who participated in a large longitudinal cohort study were participants. Longitudinal change was analyzed in objectively measured sedentary behavior and associations with sex, body mass index Z score, and socioeconomic status. Moderate-vigorous intensity physical activity (MVPA) was estimated at 8 to 12 years.

RESULTS

Average sedentary minutes/day peaked at 4 years in children at GMFCS I and 5 years in children at GMFCS II to III, then plateaued. Male sex was associated with increased sedentary behavior. At 8 to 12 years, children at GMFCS I, II, and III accumulated on average 54, 47, and 14 minutes/day, respectively, of MVPA.

CONCLUSIONS

When measured to 12 years, sedentary behavior peaks by 5 years for children with CP who are walking with differences in trajectory according to GMFCS.

Study protocol for a 9-month randomised controlled trial assessing the effects of almonds versus carbohydrate-rich snack foods on weight loss and weight maintenance

INTRODUCTION

Epidemiological studies indicate an inverse association between nut consumption and body mass index (BMI). However, clinical trials evaluating the effects of nut consumption compared with a nut-free diet on adiposity have reported mixed findings with some studies reporting greater weight loss and others reporting no weight change. This paper describes the rationale and detailed protocol for a randomised controlled trial assessing whether the inclusion of almonds or carbohydrate-rich snacks in an otherwise nut-free energy-restricted diet will promote weight loss during 3 months of energy restriction and limit weight regain during 6 months of weight maintenance.

METHODS AND ANALYSIS

One hundred and thirty-four adults aged 25-65 years with a BMI of 27.5-34.9 kg/m² will be recruited and randomly allocated to either the almond-enriched diet (AED) (15% energy from almonds) or a nut-free control diet (NFD) (15% energy from carbohydrate-rich snack foods). Study snack foods will be provided. Weight loss will be achieved through a 30% energy restriction over 3 months, and weight maintenance will be encouraged for 6 months by increasing overall energy intake by ~120-180 kcal/day (~500-750kJ/day) as required. Food will be self-selected, based on recommendations from the study dietitian. Body composition, resting energy expenditure, total daily energy expenditure (via doubly labelled water), physical activity, appetite regulation, cardiometabolic health, gut microbiome, liver health, inflammatory factors, eating behaviours, mood and personality, functional mobility and pain, quality of life and sleep patterns will be measured throughout the 9-month trial. The effects of intervention on the outcome measures over time will be analysed using random effects mixed models, with treatment (AED or NFD) and time (baseline, 3 months and 9 months) being the between and within factors, respectively in the analysis.

ETHICS AND DISSEMINATION

Ethics approval was obtained from the University of South Australia Human Research Ethics Committee (201436). Results from this trial will be disseminated through publication in peer-reviewed journals, national and international presentations.

TRIAL REGISTRATION NUMBER

Australian New Zealand Clinical Trials Registry (ACTRN12618001861246).

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.

Parent-Child Physical Activity Association in Families With 4-to 16-Year-Old Children

Background: The main aim of this study was to quantify the associations between parents’ and children’s physical activity by age, gender, and the day of the week on the basis of a pedometer-measured step count (SC). Methods: The sample comprised data from 4-to 16-year-old children and their parents from the Czech Republic (1102 mother-child dyads and 693 father-child dyads). The parents and their children wore the Yamax SW200 pedometer during seven days of monitoring. Results: The strongest SC association was found between mothers and daughters aged 4–7.9 years on weekdays (r_p = 0.402; p < 0.01) and at weekends (r_p = 0.577; p < 0.01). In children aged 8–16, the parent-child association is gender-specific, with the father-son relationship being dominant, especially at weekends (weekend SC: fathers-sons_{8–11.9 y} r_p = 0.416, p < 0.01; fathers-sons_{12–16 y} r_p = 0.443, p < 0.01). An increase of 1000 steps in the fathers (mothers) is associated with an increase of more than 400 (200) steps in their sons (daughters). Conclusions: This study confirms a strong parent-child SC relationship in children younger than eight years of age. In older children, the parent-child SC association is gender-specific and dominated by the father-son relationship, particularly on weekends. The SC associations that are revealed can be used for the development of physical activity programs for adolescents.

A Social Networking and Gamified App to Increase Physical Activity: Cluster RCT

INTRODUCTION

Appealing approaches to increasing physical activity levels are needed. This study evaluated whether a social and gamified smartphone app (Active Team) could be one such approach.

STUDY DESIGN

A 3-group cluster RCT compared the efficacy of Active Team with a basic self-monitoring app and waitlist control group.

SETTING/PARTICIPANTS

Australian adults (N=444, mean age of 41 years, 74% female) were recruited in teams (n=121) and randomly assigned (1:1:1) to the Active Team (n=141, 39 teams), self-monitoring app (n=160, 42 teams), or waitlist group (n=143, 40 teams). Data were collected in 2016-2017, and analysis was conducted in 2018-2019.

INTERVENTION

Active Team is a 100-day app-based, gamified, online social networking physical activity intervention.

MAIN OUTCOME MEASURES

The primary outcome was change in objective physical activity from baseline to 3-month follow-up. Secondary outcomes included objective physical activity at 9 months and self-reported physical activity, quality of life, depression, anxiety and stress, well-being, and engagement.

RESULTS

Mixed models indicated no significant differences in objective physical activity between groups at 3 (F=0.17, p=0.84; Cohen's d=0.03, 95% CI= -0.21, 0.26) or 9 months (F=0.23, p=0.92; d=0.06, 95% CI= -0.17, 0.29) and no significant differences for secondary outcomes of quality of life, depression, anxiety and stress, or well-being. Self-reported moderate-to-vigorous physical activity was significantly higher in the Active Team group at the 9-month follow-up (F=3.05, p=0.02; d=0.50, 95% CI=0.26, 0.73). Engagement was high; the Active Team group logged steps on an average of 72 (SD=35) days and used the social and gamified features an average of 89 (SD=118) times.

CONCLUSIONS

A gamified, online social networking physical activity intervention did not change objective moderate-to-vigorous physical activity, though it did increase self-reported moderate-to-vigorous physical activity and achieve high levels of engagement. Future work is needed to understand if gamification, online social networks, and app-based approaches can be leveraged to achieve positive behavior change.

TRIAL REGISTRATION

This study is registered at Australian and New Zealand Clinical Trial Registry (protocol: ANZCTR12617000113358).

Psychometric properties of the PERMA Profiler for measuring wellbeing in Australian adults

INTRODUCTION

This study evaluated the psychometric properties of the PERMA Profiler, a 15-item self-report measurement tool designed to measure Seligman's five pillars of wellbeing: Positive emotions, Relationships, Engagement, Meaning, and Accomplishment.

METHODS

Australian adults (N = 439) completed the PERMA Profiler and measures of physical and mental health (SF-12), depression, anxiety, stress (DASS 21), subjective physical activity (Active Australia Survey), and objective activity and sleep (GENEActiv accelerometer). Internal consistency was examined using Cronbach's alpha and associations between theoretically related constructs examined using Pearson's correlation. Model fit in comparison with theorised models was examined via Confirmatory Factor Analysis.

RESULTS

Results indicated acceptable internal consistency for overall PERMA Profiler scores and all subscales (α range = 0.80-0.93) except Engagement (α = 0.66). Moderate associations were found between PERMA Profiler wellbeing scores with subjective constructs (e.g. depression, anxiety, stress; r = -0.374 - -0.645, p = <0.001) but not objective physical activity or sleep. Data failed to meet model fit criteria for neither the theorised five-factor nor an alternative single-factor structure.

CONCLUSIONS

Findings were mixed, providing strong support for the scale's internal consistency and moderate support for congervent and divergent validity, albeit not in comparison to objectively captured activity outcomes. We could not replicate the theorised data structure nor an alternative, single factor structure. Results indicate insufficient psychometric properties of the PERMA Profiler.

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.

Population health bio-phenotypes in 11-12 year old children and their midlife parents: Growing Up in Australia's Child Health CheckPoint

In an ambitious undertaking, Growing Up in Australia's Child Health CheckPoint streamlined and implemented wide-ranging population phenotypes and biosamples relevant to non-communicable diseases in nearly 1900 parent-child dyads throughout Australia at child aged 11-12 years. This BMJ Open Special Issue describes the methodology, epidemiology and parent-child concordance of 14 of these phenotypes, spanning cardiovascular, respiratory, bone, kidney, hearing and language, body composition, metabolic profiles, telomere length, sleep, physical activity, snack choice and health-related quality of life. The Special Issue also includes a cohort summary and study methodology paper.

Child Health CheckPoint: cohort summary and methodology of a physical health and biospecimen module for the Longitudinal Study of Australian Children

OBJECTIVES

'Growing Up in Australia: The Longitudinal Study of Australian Children' (LSAC) is Australia's only nationally representative children's longitudinal study, focusing on social, economic, physical and cultural impacts on health, learning, social and cognitive development. LSAC's first decade collected wide-ranging repeated psychosocial and administrative data; here, we describe the Child Health CheckPoint, LSAC's dedicated biophysical module.

DESIGN, SETTING AND PARTICIPANTS

LSAC recruited a cross-sequential sample of 5107 infants aged 0-1 year and a sample of 4983 children aged 4-5 years in 2004, since completing seven biennial visits. CheckPoint was a cross-sectional wave that travelled Australia in 2015-2016 to reach LSAC's younger cohort at ages 11-12 years between LSAC waves 6 and 7. Parent-child pairs participated in comprehensive assessments at 15 Assessment Centres nationwide or, if unable to attend, a shorter home visit.

MEASURES

CheckPoint's intergenerational, multidimensional measures were prioritised to show meaningful variation within normal ranges and capture non-communicable disease (NCD) phenotype precursors. These included anthropometry, physical activity, fitness, time use, vision, hearing, and cardiovascular, respiratory and bone health. Biospecimens included blood, saliva, buccal swabs (also from second parent), urine, hair and toenails. The epidemiology and parent-child concordance of many measures are described in separate papers.

RESULTS

1874 (54% of eligible) parent-child pairs and 1051 second parents participated. Participants' geographical distribution mirrored the broader Australian population; however, mean socioeconomic position and parental education were higher and fewer reported non-English-speaking or Indigenous backgrounds. Application of survey weights partially mitigates that the achieved sample is less population representative than previous waves of LSAC due to non-random attrition. Completeness was uniformly high for phenotypic data (>92% of eligible), biospecimens (74%-97%) and consent (genetic analyses 98%, accessing neonatal blood spots 97%, sharing 96%).

CONCLUSIONS

CheckPoint enriches LSAC to study how NCDs develop at the molecular and phenotypic levels before overt disease emerges, and clarify the underlying dimensionality of health in childhood and mid-adulthood.