Publications by authors named "Timothy Olds"

134 Publications

Equivalence Curves for Healthy Lifestyle Choices.

Pediatrics 2021 Mar 26. Epub 2021 Mar 26.

Alliance for Research in Exercise, Nutrition and Activity, Allied Health and Human Performance, University of South Australia, Adelaide, South Australia, Australia;

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 ( = 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 ≤ .001) and sleep ( = .001; < .02), and less sedentary time (both < .001) and light physical activity (adiposity only; = .03), each relative to remaining activities. Children with better academic achievement had less light physical activity, relative to remaining activities ( = .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.
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http://dx.doi.org/10.1542/peds.2020-025395DOI Listing
March 2021

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

BMC Geriatr 2021 Mar 23;21(1):203. Epub 2021 Mar 23.

Institute for Health and Sport, Victoria University, Melbourne, Australia.

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.
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http://dx.doi.org/10.1186/s12877-021-02148-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7988941PMC
March 2021

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

PLoS One 2021 3;16(3):e0248008. Epub 2021 Mar 3.

Alliance for Research in Exercise, Nutrition and Activity, UniSA Allied Health and Human Performance, University of South Australia, Adelaide, SA, Australia.

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.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0248008PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7928513PMC
March 2021

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

Am J Health Promot 2021 Mar 1:890117121997304. Epub 2021 Mar 1.

Alliance for Research in Exercise, Nutrition and Activity, University of South Australia, Adelaide, Australia.

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 , Pre-Summer , and New Year

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.
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http://dx.doi.org/10.1177/0890117121997304DOI Listing
March 2021

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

Int J Behav Nutr Phys Act 2021 02 10;18(1):28. Epub 2021 Feb 10.

MRC Epidemiology Unit & Centre for Diet and Activity Research, University of Cambridge, Cambridge, UK.

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.
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http://dx.doi.org/10.1186/s12966-021-01095-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7877033PMC
February 2021

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

Transl Behav Med 2021 Apr;11(3):870-881

Alliance for Research in Exercise, Nutrition and Activity, University of South Australia, Adelaide, Australia.

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.
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http://dx.doi.org/10.1093/tbm/ibaa139DOI Listing
April 2021

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

PLoS One 2021 19;16(1):e0245501. Epub 2021 Jan 19.

Alliance for Research in Exercise, Nutrition and Activity (ARENA), Allied Health & Human Performance, University of South Australia, Adelaide, South Australia, Australia.

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.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0245501PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7815105PMC
January 2021

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.

BMC Public Health 2021 Jan 7;21(1):70. Epub 2021 Jan 7.

Alliance for Research in Exercise, Nutrition and Activity, UniSA Allied Health and Human Performance, University of South Australia, Adelaide, SA, Australia.

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.
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http://dx.doi.org/10.1186/s12889-020-10054-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7791783PMC
January 2021

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

Pediatr Allergy Immunol 2021 Feb 20;32(2):288-294. Epub 2020 Oct 20.

Allergy and Lung Health Unit, Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Heath, University of Melbourne, Parkville, Vic, Australia.

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.
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http://dx.doi.org/10.1111/pai.13383DOI Listing
February 2021

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

PLoS One 2020 2;15(9):e0237908. Epub 2020 Sep 2.

Murdoch Children's Research Institute, Melbourne, Victoria, Australia.

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.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0237908PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7467319PMC
October 2020

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

Disabil Health J 2021 Jan 5;14(1):100980. Epub 2020 Aug 5.

University of British Columbia, Department of Medicine, Faculty of Medicine, 1088 Discovery Avenue, Kelowna, BC, V1V 1V7, Canada; University of British Columbia, School of Health and Exercise Sciences, 1147 Research Road, Kelowna, BC, V1V 1V7, Canada; International Collaboration on Repair Discoveries (ICORD), University of British Columbia, Vancouver, BC, Canada.

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 = 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.
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http://dx.doi.org/10.1016/j.dhjo.2020.100980DOI Listing
January 2021

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

Obes Rev 2020 Dec 10;21(12):e13121. Epub 2020 Aug 10.

UniSA Allied Health and Human Performance, University of South Australia, Adelaide, South Australia, Australia.

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.
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http://dx.doi.org/10.1111/obr.13121DOI Listing
December 2020

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

J Bone Miner Res 2020 12 23;35(12):2393-2403. Epub 2020 Sep 23.

Allied Health & Human Performance, Alliance for Research in Exercise, Nutrition and Activity (ARENA), University of South Australia, Adelaide, Australia.

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).
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http://dx.doi.org/10.1002/jbmr.4143DOI Listing
December 2020

Sleep and physical activity: When a null finding is not really a null finding.

Sleep Med Rev 2020 06 11;51:101302. Epub 2020 Mar 11.

Alliance for Research in Exercise, Nutrition and Activity (ARENA), University of South Australia, Adelaide, Australia.

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http://dx.doi.org/10.1016/j.smrv.2020.101302DOI Listing
June 2020

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

Int J Environ Res Public Health 2020 03 26;17(7). Epub 2020 Mar 26.

Alliance for Research in Exercise, Nutrition and Activity (ARENA), University of South Australia, Adelaide 5001, Australia.

In recent years, the focus of activity behavior research has shifted away from univariate paradigms (e.g., physical activity, sedentary behavior and sleep) to a 24-h time-use paradigm that integrates all daily activity behaviors. Behaviors are analyzed relative to each other, rather than as individual entities. Compositional data analysis (CoDA) is increasingly used for the analysis of time-use data because it is intended for data that convey relative information. While CoDA has brought new understanding of how time use is associated with health, it has also raised challenges in how this methodology is applied, and how the findings are interpreted. In this paper we provide a brief overview of CoDA for time-use data, summarize current CoDA research in time-use epidemiology and discuss challenges and future directions. We use 24-h time-use diary data from Wave 6 of the Longitudinal Study of Australian Children (birth cohort, n = 3228, aged 10.9 ± 0.3 years) to demonstrate descriptive analyses of time-use compositions and how to explore the relationship between daily time use (sleep, sedentary behavior and physical activity) and a health outcome (in this example, adiposity). We illustrate how to comprehensively interpret the CoDA findings in a meaningful way.
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http://dx.doi.org/10.3390/ijerph17072220DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7177981PMC
March 2020

Evidence for Protein Leverage in Children and Adolescents with Obesity.

Obesity (Silver Spring) 2020 04 6;28(4):822-829. Epub 2020 Mar 6.

Murdoch Children's Research Institute, The Royal Children's Hospital, Parkville, Victoria, Australia.

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.
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http://dx.doi.org/10.1002/oby.22755DOI Listing
April 2020

Breastfeeding and childhood obesity: A 12-country study.

Matern Child Nutr 2020 07 5;16(3):e12984. Epub 2020 Mar 5.

Pennington Biomedical Research Center, Baton Rouge, Louisiana, USA.

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 = .020) and 1.00, 0.64, 047, and 0.64 for high body fat (P = .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.
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http://dx.doi.org/10.1111/mcn.12984DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7296809PMC
July 2020

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

BMC Med Res Methodol 2020 01 10;20(1). Epub 2020 Jan 10.

Alliance for Research in Exercise, Nutrition, and Activity, University of South Australia, GPO Box 2471, Adelaide, SA, 5001, Australia.

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 = .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.
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http://dx.doi.org/10.1186/s12874-020-0896-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6954551PMC
January 2020

The Association Between Time-Use Behaviors and Physical and Mental Well-Being in Adults: A Compositional Isotemporal Substitution Analysis.

J Phys Act Health 2020 02 1;17(2):197-203. Epub 2020 Feb 1.

Background: Substantial evidence links activity domains with health and well-being; however, research has typically examined time-use behaviors independently, rather than considering daily activity as a 24-hour time-use composition. This study used compositional data analysis to estimate the difference in physical and mental well-being associated with reallocating time between behaviors.

Methods: Participants (n = 430; 74% female; 41 [12] y) wore an accelerometer for 7 days and reported their body mass index; health-related quality of life (QoL); and symptoms of depression, anxiety, and stress. Regression models determined whether time-use composition, comprising sleep, sedentary behavior, light physical activity (LPA), and moderate to vigorous physical activity (MVPA), was associated with well-being. Compositional isotemporal substitution models estimated the difference in well-being associated with reallocating time between behaviors.

Results: Time-use composition was associated with body mass index and physical health-related QoL. Reallocating time to MVPA from sleep, sedentary behavior, and LPA showed favorable associations with body mass index and physical health-related QoL, whereas reallocations from MVPA to other behaviors showed unfavorable associations. Reallocations from LPA to sedentary behavior were associated with better physical health-related QoL and vice versa.

Conclusion: Results reinforce the importance of MVPA for physical health but do not suggest that replacing sedentary behavior with LPA is beneficial for health and well-being.
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http://dx.doi.org/10.1123/jpah.2018-0687DOI Listing
February 2020

Are longitudinal reallocations of time between movement behaviours associated with adiposity among elderly women? A compositional isotemporal substitution analysis.

Int J Obes (Lond) 2020 04 7;44(4):857-864. Epub 2020 Jan 7.

Faculty of Sports, University of Presov, Presov, Slovak Republic.

Background: This study aimed to use compositional data analysis to: (1) investigate the prospective associations between changes in daily movement behaviours and adiposity among elderly women; and (2) to examine how the reallocation of time between movement behaviours was associated with longitudinal changes in adiposity.

Subjects/methods: This is a 7-year longitudinal study in Central European older women (n = 158, baseline age 63.9 ± 4.4 years). At baseline and follow-up, light-intensity physical activity (LIPA), moderate-to-vigorous physical activity (MVPA) and sedentary behaviour were measured by accelerometer and body adiposity (body mass index [BMI], body fat percentage [%BF]) was assessed from measured height and weight and bioelectrical impedance analyser. Compositional regression with robust estimators and compositional longitudinal isotemporal substitution analysis explored if, and how, changes in movement behaviours were associated with adiposity.

Results: Over 7 years, the prevalence of obesity in the sample increased by 10.1% and 14.6% according to BMI and %BF, respectively, and time spent in sedentary behaviour increased by 14%, while time spent in LIPA and MVPA decreased by 14% and 21%, respectively. The increase in sedentary behaviour at the expense of LIPA and MVPA during the 7-year period was associated with higher BMI and %BF at follow-up (both p < 0.01). The increase in LIPA or MVPA at the expense of sedentary behaviour was associated with reduced BMI and %BF at follow-up. In our sample, the largest change in BMI (0.75 kg/m; 95% confidence interval [CI]: 0.37-1.13) and %BF (1.28 U; 95% CI: 0.48-2.09) was associated with longitudinal reallocation of 30 min from MVPA to sedentary behaviour.

Conclusions: We found an association between longitudinal changes in daily movement behaviours and adiposity among elderly women in Central Europe. Our findings support public health programmes to increase or maintain time spent in higher-intensity physical activity among elderly women.
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http://dx.doi.org/10.1038/s41366-019-0514-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7101282PMC
April 2020

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

Int J Behav Nutr Phys Act 2019 12 5;16(1):123. Epub 2019 Dec 5.

Alliance for Research in Exercise Nutrition and Activity (ARENA), Sansom Institute, School of Health Sciences, University of South Australia, Adelaide, South Australia, Australia.

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.
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http://dx.doi.org/10.1186/s12966-019-0847-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6894468PMC
December 2019

Research Combining Physical Activity and Sleep: A Bibliometric Analysis.

Percept Mot Skills 2020 02 25;127(1):154-181. Epub 2019 Nov 25.

Appleton Institute, Central Queensland University, Adelaide, Australia.

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http://dx.doi.org/10.1177/0031512519889780DOI Listing
February 2020

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

Sleep 2020 01;43(1)

Prevention Innovation, Murdoch Children's Research Institute, Parkville, Australia.

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.
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http://dx.doi.org/10.1093/sleep/zsz200DOI Listing
January 2020

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

Int J Behav Nutr Phys Act 2019 11 14;16(1):106. Epub 2019 Nov 14.

Institute for Health and Sport, Victoria University, Melbourne, Australia.

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.
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http://dx.doi.org/10.1186/s12966-019-0875-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6857154PMC
November 2019

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

Sleep Health 2020 02 4;6(1):4-14. Epub 2019 Nov 4.

Pennington Biomedical Research Center, Baton Rouge, Louisiana, USA.

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.
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http://dx.doi.org/10.1016/j.sleh.2019.09.006DOI Listing
February 2020

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.

BMC Public Health 2019 Oct 22;19(1):1338. Epub 2019 Oct 22.

Nutrition and Dietetics, College of Nursing and Health Sciences, Flinders University, GPO Box 2100, Adelaide, SA, 5001, Australia.

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).
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http://dx.doi.org/10.1186/s12889-019-7710-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6805510PMC
October 2019

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

PLoS One 2019 16;14(8):e0216650. Epub 2019 Aug 16.

School of Health Sciences, University of South Australia, Adelaide, South Australia, Australia.

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.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0216650PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6697339PMC
March 2020

Use of time in people with a life-limiting illness: A longitudinal cohort feasibility pilot study.

Palliat Med 2019 12 1;33(10):1319-1324. Epub 2019 Aug 1.

Alliance for Research in Exercise, Nutrition and Activity (ARENA), School of Health Sciences, University of South Australia, Adelaide, SA, Australia.

Background: To date, time-use studies in palliative care have been limited to exploration of time commitments of caregivers. Understanding time-use in people with a life-limiting illness might provide insight into disease progression, symptom management and quality of life.

Aim: To determine the feasibility of a repeated-measures, time-use study in people with a life-limiting illness, and their primary caregivers, and to explore associations between time-use and perceived quality of life.

Design: An observational repeated-measures feasibility pilot study. A priori criteria were established for study uptake (70%), retention (80%) and study value/burden (⩾7 Numerical Rating Scale 0-10). Burden and value of the study, use of time (Multimedia Activity Recall for Children and Adults with adjunctive accelerometry) and quality of life data (EuroQol-5 Dimension-5-Level Health Questionnaire and Australia-modified Karnofsky Performance Status scale) were assessed at time-points across five consecutive months.

Setting/participants: People living with a life-limiting illness and caregivers recruited from Southern Adelaide Palliative Services outpatient clinics.

Results: A total of 10 participants (2 caregivers and 8 people with a life-limiting illness) enrolled in the study. All but one of the criteria thresholds was met: 66% of participants who consented to be screened were enrolled in the study, 80% of enrolled participants ( = 8) completed all assessments (two participants died during the study) and mean Numerical Rating Scale scores for acceptable burden and value of the study exceeded the criteria thresholds at every time-point.

Conclusion: A repeated-measures time-use study design is feasible and was not unduly burdensome for caregivers and people living with a life-limiting illness.
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http://dx.doi.org/10.1177/0269216319867214DOI Listing
December 2019

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

BMJ Open 2019 07 4;9(Suppl 3):136-146. Epub 2019 Jul 4.

Sansom Institute, Alliance for Research in Exercise, Nutrition and Activity (ARENA), University of South Australia, Adelaide, South Australia, Australia.

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 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).
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http://dx.doi.org/10.1136/bmjopen-2018-023194DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6624037PMC
July 2019

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

BMJ Open 2019 07 4;9(Suppl 3):127-135. Epub 2019 Jul 4.

Sansom Institute, Alliance for Research in Exercise, Nutrition and Activity (ARENA), University of South Australia, Adelaide, South Australia, Australia.

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.
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http://dx.doi.org/10.1136/bmjopen-2017-020895DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6624061PMC
July 2019