Publications by authors named "François Fraysse"

47 Publications

The EPIPHA-KNEE trial: Explaining Pain to target unhelpful pain beliefs to Increase PHysical Activity in KNEE osteoarthritis - a protocol for a multicentre, randomised controlled trial with clinical- and cost-effectiveness analysis.

BMC Musculoskelet Disord 2021 Aug 28;22(1):738. Epub 2021 Aug 28.

Centre for Health, Exercise and Sports Medicine, Department of Physiotherapy, The University of Melbourne, Victoria, Australia.

Background: Despite well-established benefits of physical activity for knee osteoarthritis (OA), nine of ten people with knee OA are inactive. People with knee OA who are inactive often believe that physical activity is dangerous, fearing that it will further damage their joint(s). Such unhelpful beliefs can negatively influence physical activity levels. We aim to evaluate the clinical- and cost-effectiveness of integrating physiotherapist-delivered pain science education (PSE), an evidence-based conceptual change intervention targeting unhelpful pain beliefs by increasing pain knowledge, with an individualised walking, strengthening, and general education program.

Methods: Two-arm, parallel-design, multicentre randomised controlled trial involving 198 people aged ≥50 years with painful knee OA who do not meet physical activity guideline recommendations or walk regularly for exercise. Both groups receive an individualised physiotherapist-led walking, strengthening, and OA/activity education program via 4x weekly in-person treatment sessions, followed by 4 weeks of at-home activities (weekly check-in via telehealth), with follow-up sessions at 3 months (telehealth) and 5 and 9 months (in-person). The EPIPHA-KNEE group also receives contemporary PSE about OA/pain and activity, embedded into all aspects of the intervention. Outcomes are assessed at baseline, 12 weeks, 6 and 12 months. Primary outcomes are physical activity level (step count; wrist-based accelerometry) and self-reported knee symptoms (WOMAC Total score) at 12 months. Secondary outcomes are quality of life, pain intensity, global rating of change, self-efficacy, pain catastrophising, depression, anxiety, stress, fear of movement, knee awareness, OA/activity conceptualisation, and self-regulated learning ability. Additional measures include adherence, adverse events, blinding success, COVID-19 impact on activity, intention to exercise, treatment expectancy/perceived credibility, implicit movement/environmental bias, implicit motor imagery, two-point discrimination, and pain sensitivity to activity. Cost-utility analysis of the EPIPHA-KNEE intervention will be undertaken, in addition to evaluation of cost-effectiveness in the context of primary trial outcomes.

Discussion: We will determine whether the integration of PSE into an individualised OA education, walking, and strengthening program is more effective than receiving the individualised program alone. Findings will inform the development and implementation of future delivery of PSE as part of best practice for people with knee OA.

Trial Registration: Australian New Zealand Clinical Trials Registry: ACTRN12620001041943 (13/10/2020).
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http://dx.doi.org/10.1186/s12891-021-04561-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8401372PMC
August 2021

Corrigendum to "Sleep and cardiometabolic health in children and adults: examining sleep as a component of the 24-hour day" [Sleep Med 78 (2020) 63-74].

Sleep Med 2021 Aug 21. Epub 2021 Aug 21.

Allied Health and Human Performance, 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.sleep.2021.07.038DOI Listing
August 2021

Annual, seasonal, cultural and vacation patterns in sleep, sedentary behaviour and physical activity: a systematic review and meta-analysis.

BMC Public Health 2021 07 13;21(1):1384. Epub 2021 Jul 13.

Alliance for Research in Exercise, Nutrition and Activity (ARENA), University of South Australia, City East Campus, GPO Box 2471, Adelaide, SA, 5001, Australia.

Background: Time spent in daily activities (sleep, sedentary behaviour and physical activity) has important consequences for health and wellbeing. The amount of time spent varies from day to day, yet little is known about the temporal nature of daily activity patterns in adults. The aim of this review is to identify the annual rhythms of daily activity behaviours in healthy adults and explore what temporal factors appear to influence these rhythms.

Methods: Six online databases were searched for cohort studies exploring within-year temporal patterns (e.g. season effects, vacation, cultural festivals) in sleep, sedentary behaviour or physical activity in healthy 18 to 65-year-old adults. Screening, data extraction, and risk of bias scoring were performed in duplicate. Extracted data was presented as mean daily minutes of each activity type, with transformations performed as needed. Where possible, meta-analyses were performed using random effect models to calculate standardised mean differences (SMD).

Results: Of the 7009 articles identified, 17 studies were included. Studies were published between 2003 and 2019, representing 14 countries and 1951 participants, addressing variation in daily activities across season (n = 11), Ramadan (n = 4), vacation (n = 1) and daylight savings time transitions (n = 1). Meta-analyses suggested evidence of seasonal variation in activity patterns, with sleep highest in autumn (+ 12 min); sedentary behaviour highest in winter (+ 19 min); light physical activity highest in summer (+ 19 min); and moderate-to-vigorous physical activity highest in summer (+ 2 min) when compared to the yearly mean. These trends were significant for light physical activity in winter (SMD = - 0.03, 95% CI - 0.58 to - 0.01, P = 0.04). Sleep appeared 64 min less during, compared to outside Ramadan (non-significant). Narrative analyses for the impact of vacation and daylight savings suggested that light physical activity is higher during vacation and that sleep increases after the spring daylight savings transition, and decreases after the autumn transition.

Conclusions: Research into temporal patterns in activity behaviours is scarce. Existing evidence suggests that seasonal changes and periodic changes to usual routine, such as observing religious events, may influence activity behaviours across the year. Further research measuring 24-h time use and exploring a wider variety of temporal factors is needed.
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http://dx.doi.org/10.1186/s12889-021-11298-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8276421PMC
July 2021

Are all MVPA minutes equal? Associations between MVPA characteristics, independent of duration, and childhood adiposity.

BMC Public Health 2021 07 6;21(1):1321. Epub 2021 Jul 6.

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

Background: The inverse relationship between moderate-to-vigorous physical activity (MVPA) duration and childhood adiposity is well established. Less is known about how characteristics of MVPA accumulation may be associated with adiposity, independent of MVPA duration. This study aimed to investigate how the MVPA characteristics of children, other than duration (bout length, time of day, day-to-day consistency, intensity), were associated with adiposity.

Methods: Cross-sectional study of the Australian arm of the International Study of Childhood Obesity, Lifestyle and the Environment (ISCOLE) (participants: n = 424, age range 9-11, 44% male). Adiposity was determined by percent body fat via bioelectrical impedance. MVPA duration and characteristics (bout length, time of day, consistency, intensity) were derived from 7-day, 24-h accelerometry. Generalised estimating equations were used to examine the individual and multivariate associations between MVPA characteristics and adiposity.

Results: Univariate analyses showed that higher MVPA duration (β range = - 0.26,-0.15), longer bouts of MVPA (β range = 0.15,0.22) and higher MVPA intensity (β range = - 0.20,-0.13) were all inversely associated with adiposity (all p < 0.05). When models were adjusted for MVPA duration, only MVPA intensity (β range = - 0.16,-0.04) showed consistent significant associations with adiposity.

Conclusions: Characteristics of MVPA other than duration and intensity appear to be unrelated to adiposity.
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http://dx.doi.org/10.1186/s12889-021-11420-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8259325PMC
July 2021

Changes in 24-Hour Physical Activity Patterns and Walking Gait Biomechanics After Primary Total Hip Arthroplasty: A 2-Year Follow-up Study.

J Bone Joint Surg Am 2021 Jul;103(13):1166-1174

Centre for Orthopaedic and Trauma Research, The University of Adelaide, Adelaide, South Australia, Australia.

Background: Despite marked improvements in self-reported pain, perceived functional ability, and gait function following primary total hip arthroplasty (THA), it remains unclear whether these improvements translate into improved physical activity and sleep behaviors. The aim of this study was to determine the change in 24-hour activity profile (waking activities and sleep) and laboratory-based gait function from preoperatively to 2 years following the THA.

Methods: Fifty-one patients undergoing primary THA at a single public hospital were recruited. All THAs were performed using a posterior surgical approach with the same prosthesis type. A wrist-worn accelerometer was used to capture 24-hour activity profiles preoperatively and at 1 and 2 years postoperatively. Three-dimensional gait analysis was performed to determine changes in temporospatial and kinematic parameters of the hip and pelvis.

Results: Patients showed improvements in all temporospatial and kinematic parameters with time. Preoperatively, patients were sedentary or asleep for a mean time (and standard deviation) of 19.5 ± 2.2 hours per day. This remained unchanged up to 2 years postoperatively (19.6 ± 1.3 hours per day). Sleep efficiency remained suboptimal (<85%) at all time points and was worse at 2 years (77% ± 10%) compared with preoperatively (84% ± 5%). More than one-quarter of the sample were sedentary for >11 hours per day at 1 year (32%) and 2 years (41%), which was greater than the preoperative percentage (21%). Patients accumulated their activity performing light activities; however, patients performed less light activity at 2 years compared with preoperative levels. No significant differences (p = 0.935) were observed for moderate or vigorous activity across time.

Conclusions: Together with improvements in self-reported pain and perceived physical function, patients had significantly improved gait function postoperatively. However, despite the opportunity for patients to be more physically active postoperatively, patients were more sedentary, slept worse, and performed less physical activity at 2 years compared with preoperative levels.

Level Of Evidence: Therapeutic Level IV. See Instructions for Authors for a complete description of levels of evidence.
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http://dx.doi.org/10.2106/JBJS.20.01679DOI Listing
July 2021

Development and evaluation of a method to define a tibial coordinate system through the fitting of geometric primitives.

Int Biomech 2021 12;8(1):12-18

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

Coordinate system definition is a critical element of biomechanical modeling of the knee, and cases of skeletal trauma present major technical challenges. This paper presents a method to define a tibial coordinate system by fitting geometric primitives to surface anatomy requiring minimal user input. The method presented here utilizes a conical fit to both the tibial shaft and femoral condyles to generate independent axes forming the basis of a tibial coordinate system. Definition of the tibial axis showed high accuracy when shape fitting to ≥50 mm of shaft with <3° of angular variation from the axis obtained using the full tibia. Repeatability and reproducibility of the axis was compared using intraclass correlation coefficients which showed excellent intra- and inter-observer agreement across cases. Additionally, shape fitting to the distal femoral condyles showed high accuracy compared to the reference axis established automatically through identifying the medial and lateral epicondyles (<4°). Utilizing geometric primitives to estimate functional axes for the tibia and femur removes reliance on anatomical landmarks that can be displaced by fracture or inaccurately identified by observers. Furthermore, fitting of such primitives provides a more complete understanding of the true bony anatomy, which cannot be done through simple landmark identification.
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http://dx.doi.org/10.1080/23335432.2021.1916406DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8130718PMC
December 2021

Comparisons of Daily Energy Intake vs. Expenditure Using the GeneActiv Accelerometer in Elite Australian Football Athletes.

J Strength Cond Res 2021 May;35(5):1273-1278

Bond Institute of Health and Sport, Faculty of Health Sciences and Medicine Bond University, Robina, Queensland, Australia.

Abstract: Salagaras, BS, Mackenzie-Shalders, KL, Nelson, MJ, Fraysse, F, Wycherley, TP, Slater, GJ, McLellan, C, Kumar, K, and Coffey, VG. Comparisons of daily energy intake vs. expenditure using the GeneActiv accelerometer in elite Australian Football athletes. J Strength Cond Res 35(5): 1273-1278, 2021-To assess validity of the GeneActiv accelerometer for use within an athlete population and compare energy expenditure (EE) with energy and macronutrient intake of elite Australian Football athletes during a competition week. The GeneActiv was first assessed for utility during high-intensity exercise with indirect calorimetry. Thereafter, 14 professional Australian Football athletes (age, 24 ± 4 [SD] y; height, 1.87 ± 0.08 m; body mass, 86 ± 10 kg) wore the accelerometer and had dietary intake assessed via dietitian-led 24-hour recalls throughout a continuous 7 days of competition period (including match day). There was a significant relationship between metabolic equivalents and GeneActiv g·min-1 (SEE 1.77 METs; r2 = 0.64; p < 0.0001). Across the in-season week a significant difference only occurred on days 3 and 4 (day 3: energy intake [EI] EI 137 ± 31 kJ·kg-1·d-1; 11,763 ± 2,646 kJ·d-1 and EE: 186 ± 14 kJ·kg-1·d-1; 16,018 ± 1973 kJ·d-1; p < 0.05; d = -1.4; day 4: EI: 179 ± 44 kJ·kg-1·d-1, 15,413 ± 3,960 kJ·d-1 and EE: 225 ± 42 kJ·kg-1·d-1; 19,313 ± 3,072 kJ·d-1; d = -0.7). Carbohydrate intake (CI) was substantially below current sports nutrition recommendations on 6 of 7 days with deficits ranging from -1 to -7.2 g·kg-1·d-1 (p < 0.05), whereas daily protein and fat intake was adequate. In conclusion, the GeneActiv provides effective estimation of EE during weekly preparation for a professional team sport competition. Australian Footballers attempt to periodize dietary EI to varying daily training loads but fail to match expenditure on higher-training load days. Specific dietary strategies to increase CI may be beneficial to achieve appropriate energy balance and macronutrient distribution, particularly on days where athletes undertake multiple training sessions.
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http://dx.doi.org/10.1519/JSC.0000000000003945DOI Listing
May 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

Compliance With Mobile Ecological Momentary Assessment of Self-Reported Health-Related Behaviors and Psychological Constructs in Adults: Systematic Review and Meta-analysis.

J Med Internet Res 2021 03 3;23(3):e17023. Epub 2021 Mar 3.

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

Background: Mobile ecological momentary assessment (mEMA) permits real-time capture of self-reported participant behaviors and perceptual experiences. Reporting of mEMA protocols and compliance has been identified as problematic within systematic reviews of children, youth, and specific clinical populations of adults.

Objective: This study aimed to describe the use of mEMA for self-reported behaviors and psychological constructs, mEMA protocol and compliance reporting, and associations between key components of mEMA protocols and compliance in studies of nonclinical and clinical samples of adults.

Methods: In total, 9 electronic databases were searched (2006-2016) for observational studies reporting compliance to mEMA for health-related data from adults (>18 years) in nonclinical and clinical settings. Screening and data extraction were undertaken by independent reviewers, with discrepancies resolved by consensus. Narrative synthesis described participants, mEMA target, protocol, and compliance. Random effects meta-analysis explored factors associated with cohort compliance (monitoring duration, daily prompt frequency or schedule, device type, training, incentives, and burden score). Random effects analysis of variance (P≤.05) assessed differences between nonclinical and clinical data sets.

Results: Of the 168 eligible studies, 97/105 (57.7%) reported compliance in unique data sets (nonclinical=64/105 [61%], clinical=41/105 [39%]). The most common self-reported mEMA target was affect (primary target: 31/105, 29.5% data sets; secondary target: 50/105, 47.6% data sets). The median duration of the mEMA protocol was 7 days (nonclinical=7, clinical=12). Most protocols used a single time-based (random or interval) prompt type (69/105, 65.7%); median prompt frequency was 5 per day. The median number of items per prompt was similar for nonclinical (8) and clinical data sets (10). More than half of the data sets reported mEMA training (84/105, 80%) and provision of participant incentives (66/105, 62.9%). Less than half of the data sets reported number of prompts delivered (22/105, 21%), answered (43/105, 41%), criterion for valid mEMA data (37/105, 35.2%), or response latency (38/105, 36.2%). Meta-analysis (nonclinical=41, clinical=27) estimated an overall compliance of 81.9% (95% CI 79.1-84.4), with no significant difference between nonclinical and clinical data sets or estimates before or after data exclusions. Compliance was associated with prompts per day and items per prompt for nonclinical data sets. Although widespread heterogeneity existed across analysis (I>90%), no compelling relationship was identified between key features of mEMA protocols representing burden and mEMA compliance.

Conclusions: In this 10-year sample of studies using the mEMA of self-reported health-related behaviors and psychological constructs in adult nonclinical and clinical populations, mEMA was applied across contexts and health conditions and to collect a range of health-related data. There was inconsistent reporting of compliance and key features within protocols, which limited the ability to confidently identify components of mEMA schedules likely to have a specific impact on compliance.
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http://dx.doi.org/10.2196/17023DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7970161PMC
March 2021

3D modelling of tibial plateau fractures: Variability in fracture location and characteristics across Schatzker fracture types.

Injury 2021 Aug 14;52(8):2415-2424. Epub 2021 Jan 14.

Centre for Orthopaedic and Trauma Research, University of Adelaide, Adelaide, SA 5000, Australia; Department of Orthopaedics and Trauma, Royal Adelaide Hospital, Adelaide, SA 5000, Australia.

Introduction: Numerous classifications have been developed to assess tibial plateau fractures (TPF). Of these, the Schatzker system is the most widely reported in the literature yet this system is limited in its characterisation of morphological fracture features underlying the fracture location. The purpose of this study was to compare 3D morphological features of TPFs across different Schatzker types.

Methods: This study retrospectively analysed preoperative TPF imaging data to reconstruct 3D models of the fractures. Ninety-one fractures (29 female, 62 male) were analysed and classified using Schatzker. Fracture location across Schatzker types was compared based on division of the articular surface into six 'zones'. Additionally, morphological characteristics of the fractures were compared based on fracture type, including; the number, volume and shape of the fragments.

Results: Schatzker II, IV and VI fractures were most common, making up 41%, 16% and 20%, respectively. Type II fractures commonly involved both the lateral and central aspect of the tibial plateau, similarly, type IV fractures incorporated the lateral condyle in most cases. Considering the morphological metrics, statistically significant differences were observed between Schatzker types for the number of; total, articular, cortical and volumetrically significant (all P < 0.001) fragments along with the volume of both primary (P < 0.001) and secondary (P = 0.02) fragments.

Discussion: Assessment of underlying fracture characteristics in addition to fracture location can serve to provide greater detail relating to fracture morphology, which has the potential to assist with both surgical decision making and assessment of postoperative outcomes. Incorporating this information as part of a hierarchical or multifactorial framework for classifying fractures may help distinguish subtle differences between fracture types that are classifiable using the most current systems.
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http://dx.doi.org/10.1016/j.injury.2021.01.019DOI Listing
August 2021

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

Front Sports Act Living 2020 15;2:579278. Epub 2021 Jan 15.

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

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. 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 ( = 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. 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.
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http://dx.doi.org/10.3389/fspor.2020.579278DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7843957PMC
January 2021

Sleep and cardiometabolic risk: a cluster analysis of actigraphy-derived sleep profiles in adults and children.

Sleep 2021 07;44(7)

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

Study Objectives: Sleep plays an important role in cardiometabolic health. Although the importance of considering sleep as a multidimensional construct is widely appreciated, studies have largely focused on individual sleep characteristics. The association between actigraphy-derived sleep profiles and cardiometabolic health in healthy adults and children has not been examined.

Methods: This study used actigraphy-measured sleep data collected between February 2015 and March 2016 in the Child Health CheckPoint study. Participants wore actigraphy monitors (GENEActiv Original, Cambs, UK) on their nondominant wrist for 7 days and sleep characteristics (period, efficiency, timing, and variability) were derived from raw actigraphy data. Actigraphy-derived sleep profiles of 1,043 Australian children aged 11-12 years and 1,337 adults were determined using K-means cluster analysis. The association between cluster membership and biomarkers of cardiometabolic health (blood pressure, body mass index, apolipoproteins, glycoprotein acetyls, composite metabolic syndrome severity score) were assessed using Generalized Estimating Equations, adjusting for geographic clustering, with sex, socioeconomic status, maturity stage (age for adults, pubertal status for children), and season of data collection as covariates.

Results: Four actigraphy-derived sleep profiles were identified in both children and adults: short sleepers, late to bed, long sleepers, and overall good sleepers. The overall good sleeper pattern (characterized by adequate sleep period time, high efficiency, early bedtime, and low day-to-day variability) was associated with better cardiometabolic health in the majority of comparisons (80%).

Conclusion: Actigraphy-derived sleep profiles are associated with cardiometabolic health in adults and children. The overall good sleeper pattern is associated with more favorable cardiometabolic health.
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http://dx.doi.org/10.1093/sleep/zsab014DOI Listing
July 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 01 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

Sleep and cardiometabolic health in children and adults: examining sleep as a component of the 24-h day.

Sleep Med 2021 02 7;78:63-74. Epub 2020 Dec 7.

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

Study Objectives: Sleep, physical activity and sedentary time are all known to play a role in cardiometabolic health. Compositional data analysis (CoDA) enables us to examine associations between 24-h use of time and health outcomes.

Methods: Data were collected in the Child Health CheckPoint study, a one-off national population-cohort study conducted between February 2015 and March 2016. Wrist-worn actigraphy monitors (GENEActiv Original, Cambs, UK) were used to measure activity behaviours (sleep, physical activity and sedentary time) and sleep characteristics (sleep variability, midsleep, efficiency). CoDA was applied to determine the association between 24-h use of time and cardiometabolic risk markers (blood pressure; body mass index; apolipoprotein B/A1; glycoprotein acetyls; and composite metabolic syndrome score). Substitution modelling (one-for-remaining and one-for-one) examined the associations of reallocating sleep time with other activity behaviours.

Results: Data were available for 1073 Australian children aged 11-12 years (50% male) and 1337 adults (13% male). Strong association was found between 24-h use of time and all cardiometabolic health outcomes. Longer sleep was associated with more favourable cardiovascular health. Sleep characteristics other than duration (efficiency, timing, variability) were weakly and inconsistently associated with outcomes. Reallocating time from sleep to moderate-vigorous physical activity (MVPA) had favourable associations with cardiometabolic health, but reallocating from sleep to sedentary time was associated with less favourable cardiometabolic health.

Conclusion: The 24-h activity composition is strongly associated with cardiometabolic health in children and adults. Days with more sleep and MVPA are associated with improved cardiometabolic health.
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http://dx.doi.org/10.1016/j.sleep.2020.12.001DOI Listing
February 2021

Postoperative lower limb joint kinematics following tibial plateau fracture: A 2-year longitudinal study.

Gait Posture 2021 01 10;83:20-25. Epub 2020 Oct 10.

Centre for Orthopaedic and Trauma Research, The University of Adelaide, SA, Australia.

Background: The goal of postoperative tibial plateau fracture (TPF) management is to ensure surgical fixation is maintained while returning patients to normal function as soon as possible, allowing patients to resume their normal activities of daily living. The aim of this study was to investigate longitudinal changes in lower limb joint kinematics following TPF and determine how these kinematics relate to self-reported function.

Methods: Patients presenting with a TPF were recruited (n = 18) and undertook gait analysis at six postoperative time points (two weeks, six weeks, three months, six months, one and two years). Lower limb joint kinematics were assessed at each time point based on gait data. Statistical parametric mapping (SPM) was undertaken to investigate the change in joint kinematic traces with time. The Knee Injury and Osteoarthritis Outcome Score (KOOS) was assessed at each time point to obtain self-reported outcomes. A healthy reference was also analyzed and used for qualitative comparison of joint kinematics.

Results And Significance: Knee kinematics showed improvements with time, however only minor changes were noted after six weeks at the hip, and six months at the knee and ankle relative to two weeks postoperative. SPM identified significant improvements with time in hip (p < 0.001) and knee (p = 0.003) flexion. No significant changes were observed with time at the ankle however, when compared to the healthy reference, participants showed reduced plantarflexion at two years. Lower limb joint ROM showed significant weak to moderate correlation with the ADL sub-scale of the KOOS (hip r = 0.442, knee r = 0.303, ankle r = 0.367). The lack of significant changes with time and overall reduced plantarflexion at the ankle potentially reduces propulsive capacity during gait up to two years postoperative. In this study, we see a deficiency in joint kinematics in TPF patients up to two years when compared to a healthy reference, especially at the ankle.
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http://dx.doi.org/10.1016/j.gaitpost.2020.10.005DOI Listing
January 2021

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

Pediatr Allergy Immunol 2021 02 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

Sleep profiles of Australian children aged 11-12 years and their parents: sociodemographic characteristics and lifestyle correlates.

Sleep Med 2020 09 8;73:53-62. Epub 2020 May 8.

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

Background: Good sleep is a growing public health focus. Given the multidimensional nature of sleep, it is of interest to examine population sleep profiles and determine sociodemographic and lifestyle correlates.

Methods: This study uses actigraphy-measured sleep data collected between February 2015 and March 2016 in the Child Health CheckPoint study. Participants wore actigraphy monitors (GENEActiv Original, Cambs, UK) on their non-dominant wrist for seven days and sleep characteristics (duration, efficiency, timing, and variability) were derived from raw actigraphy data. Sleep profiles of 1043 Australian children aged 11-12 years and their parents were determined using K-means cluster analysis. The association between cluster membership and potential sociodemographic and lifestyle correlates were assessed using Generalised Estimating Equations, adjusting for geographic clustering.

Results: Four sleep profiles were identified: Short sleepers, Late to bed, Long sleepers, and Overall good sleepers. Compared to Overall good sleepers, Late to bed cluster were of lower socioeconomic position and had the least favourable diet and activity patterns. Compared to Overall good sleepers, those in the Late to bed cluster had higher sedentary time, lower levels of moderate-vigorous physical activity and a higher consumption of savoury snacks. In contrast, sugary drink consumption was higher in Late to bed children and Long sleeper adults.

Conclusion: Examining sleep profiles may provide a more holistic way of monitoring sleep at the population level. Future health promotion strategies may be best to consider sleep in terms of profiles, with emphasis on sleep timing and duration.
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http://dx.doi.org/10.1016/j.sleep.2020.04.017DOI Listing
September 2020

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.

BMJ Open 2020 07 19;10(7):e036542. Epub 2020 Jul 19.

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

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/m 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).
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http://dx.doi.org/10.1136/bmjopen-2019-036542DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7371143PMC
July 2020

Longitudinal changes in lower limb joint loading up to two years following tibial plateau fracture.

Gait Posture 2020 05 6;78:72-79. Epub 2020 Apr 6.

Centre for Orthopaedic and Trauma Research, University of Adelaide, Adelaide, SA, 5000, Australia.

Background: Tibial plateau fractures are one of the most common intra-articular fractures resulting from high or low energy impact trauma. Few studies have assessed postoperative outcomes of these fractures with respect to changes in knee joint loading post-surgery. This gait analysis study compared lower limb joint loading up to two years post-surgery.

Methods: Twenty patients (range 27-67 years; 9:11(male:female)) were treated with open reduction internal fixation and instructed to weight bear as tolerated immediately following surgery. Joint loading at the hip, knee and ankle were assessed at six time points post-operatively up to two years. Gait analyses were performed at each time point and a musculoskeletal model was used to compute external joint moments for the lower limb.

Results: Hip flexion and extension (P = <0.001, P = <0.001), knee flexion (P = 0.014) and ankle plantarflexion moments (P = <0.001) showed significant increases with time. The hip flexion moment increased between six months and one year (mean difference = 0.16 Nm/kg) but did not increase thereafter (mean difference = 0.01 Nm/kg). Knee flexion and extension, and ankle plantarflexion moments increased up to six months (mean difference = 0.22 Nm/kg, 0.14 Nm/kg, 0.80 Nm/kg, respectively), but no further differences were seen with time from six months postoperative.

Discussion: The greatest changes in joint loads were observed at the hip and ankle within the first six months, likely a result of mechanical adaptations attempting to account for limited motion at the knee. Knee joint loading plateaued beyond six months suggesting functional outcomes are largely reliant on postoperative management within the initial three months while the bone is healing.
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http://dx.doi.org/10.1016/j.gaitpost.2020.03.008DOI Listing
May 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

The sedentary behaviour and physical activity patterns of survivors of a critical illness over their acute hospitalisation: An observational study.

Aust Crit Care 2020 05 6;33(3):272-280. Epub 2019 Dec 6.

University of South Australia, Adelaide, South Australia, Australia. Electronic address:

Background: Physical function is often poor in intensive care unit (ICU) survivors, yet objective descriptions of sedentary behaviour and physical activity during acute hospitalisation are lacking.

Objective: The objective of this study was to examine sedentary and activity patterns during patients' hospital-based recovery from a critical illness and associations with physical function, muscle strength, and length of stay (LOS).

Methods: This was a prospective cohort study in a tertiary ICU and acute hospital wards, which recruited 40 adults who required ≥5 days of mechanical ventilation. Data were collected at awakening (T1), ICU discharge (T2), and hospital discharge (T3), which included monitoring of body posture (sedentary behaviour) using the activPAL and activity intensity using the GENEActiv. Data were reported as time spent lying/sitting and upright, with the number of sit-to-stand transitions and upright bouts. Statistical analysis was conducted using repeated-measures analysis of variance and Spearman's rho.

Results: From awakening to hospital discharge (T1-T3, n = 23), there was a mean [95% confidence interval] decrease in % time spent lying/sitting (-3.0% [-4.6% to1.4%], p ≤ 0.001) corresponding to increased time spent upright (43.0 min [19.9, 66.1], p ≤ 0.001). Sit-to-stand transitions increased (18 [11, 28], p ≤ 0.001). The number of upright bouts ≥2 and ≥ 5 min increased (both p ≤ 0.001), but only from ICU to hospital discharge (T2-T3, 5.3 [3.1, 7.6] and 2.3 [0.9, 3.8] respectively). At ICU discharge (T2), less % of time spent lying/sitting, more minutes spent upright, and more transitions were associated with better physical function (Physical Function in Intensive Care Test-scored and de Morton Mobility Index; all rho ≥+/-0.730, p ≤ 0.001) and muscle strength (hand grip, Medical Research Council sum-score; all rho≥+/-0.505, p ≤ 0.001). There were no associations between accelerometry and hospital LOS.

Conclusions: ICU survivors' transition from highly sedentary behaviour to low intensity activity over their acute hospitalisation. Sedentary breaks may be not spread over the day such that modifying sedentary behaviour to break up prolonged lying/sitting may be a focus for future research.

Clinical Trial Registration: NCT02881801.
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http://dx.doi.org/10.1016/j.aucc.2019.10.006DOI Listing
May 2020

User Engagement and Attrition in an App-Based Physical Activity Intervention: Secondary Analysis of a Randomized Controlled Trial.

J Med Internet Res 2019 11 27;21(11):e14645. Epub 2019 Nov 27.

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

Background: The success of a mobile phone app in changing health behavior is thought to be contingent on engagement, commonly operationalized as frequency of use.

Objective: This subgroup analysis of the 2 intervention arms from a 3-group randomized controlled trial aimed to examine user engagement with a 100-day physical activity intervention delivered via an app. Rates of engagement, associations between user characteristics and engagement, and whether engagement was related to intervention efficacy were examined.

Methods: Engagement was captured in a real-time log of interactions by users randomized to either a gamified (n=141) or nongamified version of the same app (n=160). Physical activity was assessed via accelerometry and self-report at baseline and 3-month follow-up. Survival analysis was used to assess time to nonuse attrition. Mixed models examined associations between user characteristics and engagement (total app use). Characteristics of super users (top quartile of users) and regular users (lowest 3 quartiles) were compared using t tests and a chi-square analysis. Linear mixed models were used to assess whether being a super user was related to change in physical activity over time.

Results: Engagement was high. Attrition (30 days of nonuse) occurred in 32% and 39% of the gamified and basic groups, respectively, with no significant between-group differences in time to attrition (P=.17). Users with a body mass index (BMI) in the healthy range had higher total app use (mean 230.5, 95% CI 190.6-270.5; F=8.67; P<.001), compared with users whose BMI was overweight or obese (mean 170.6, 95% CI 139.5-201.6; mean 132.9, 95% CI 104.8-161.0). Older users had higher total app use (mean 200.4, 95% CI 171.9-228.9; F=6.385; P=.01) than younger users (mean 155.6, 95% CI 128.5-182.6). Super users were 4.6 years older (t=3.6; P<.001) and less likely to have a BMI in the obese range (χ=15.1; P<.001). At the 3-month follow-up, super users were completing 28.2 (95% CI 9.4-46.9) more minutes of objectively measured physical activity than regular users (F=4.76; P=.03).

Conclusions: Total app use was high across the 100-day intervention period, and the inclusion of gamified features enhanced engagement. Participants who engaged the most saw significantly greater increases to their objectively measured physical activity over time, supporting the theory that intervention exposure is linked to efficacy. Further research is needed to determine whether these findings are replicated in other app-based interventions, including those experimentally evaluating engagement and those conducted in real-world settings.

Trial Registration: Australian New Zealand Clinical Trials Registry ACTRN12617000113358; https://www.anzctr.org.au/ACTRN12617000113358.aspx.
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http://dx.doi.org/10.2196/14645DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6906621PMC
November 2019

Life on holidays: study protocol for a 3-year longitudinal study tracking changes in children's fitness and fatness during the in-school versus summer holiday period.

BMC Public Health 2019 Oct 23;19(1):1353. Epub 2019 Oct 23.

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

Background: Emerging evidence suggests that children become fatter and less fit over the summer holidays but get leaner and fitter during the in-school period. This could be due to differences in diet and time use between these distinct periods. Few studies have tracked diet and time use across the summer holidays. This study will measure rates of change in fatness and fitness of children, initially in Grade 4 (age 9 years) across three successive years and relate these changes to changes in diet and time use between in-school and summer holiday periods.

Methods: Grade 4 Children attending Australian Government, Catholic and Independent schools in the Adelaide metropolitan area will be invited to participate, with the aim of recruiting 300 students in total. Diet will be reported by parents using the Automated Self-Administered 24-h Dietary Assessment Tool. Time use will be measured using 24-h wrist-worn accelerometry (GENEActiv) and self-reported by children using the Multimedia Activity Recall for Children and Adults (e.g. chores, reading, sport). Measurement of diet and time use will occur at the beginning (Term 1) and end (Term 4) of each school year and during the summer holiday period. Fitness (20-m shuttle run and standing broad jump) and fatness (body mass index z-score, waist circumference, %body fat) will be measured at the beginning and end of each school year. Differences in rates of change in fitness and fatness during in-school and summer holiday periods will be calculated using model parameter estimate contrasts from linear mixed effects model. Model parameter estimate contrasts will be used to calculate differences in rates of change in outcomes by socioeconomic position (SEP), sex and weight status. Differences in rates of change of outcomes will be regressed against differences between in-school and summer holiday period diet and time use, using compositional data analysis. Analyses will adjust for age, sex, SEP, parenting style, weight status, and pubertal status, where appropriate.

Discussion: Findings from this project may inform new, potent avenues for intervention efforts aimed at addressing childhood fitness and fatness. Interventions focused on the home environment, or alternatively extension of the school environment may be warranted.

Trial Registration: Australia New Zealand Clinical Trials Registry, identifier ACTRN12618002008202 . Retrospectively registered on 14 December 2018.
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http://dx.doi.org/10.1186/s12889-019-7671-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6813137PMC
October 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

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

J Pediatr 2019 05 28;208:43-49.e9. Epub 2019 Jan 28.

Alliance for Research in Exercise, Nutrition and Activity (ARENA), University of South Australia, Adelaide, South Australia, Australia; Murdoch Children's Research Institute, Parkville, Victoria, Australia.

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

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

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

Conclusions: Preventing declines in MVPA during inactive periods (eg, holidays) may be an important intervention goal. More MVPA, instead of other activities, may benefit body composition.
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http://dx.doi.org/10.1016/j.jpeds.2018.12.030DOI Listing
May 2019

Promoting physical activity in rural Australian adults using an online intervention.

J Sci Med Sport 2019 Jan 10;22(1):70-75. Epub 2018 Jul 10.

Alliance for Research in Exercise, Nutrition and Activity (ARENA), Sansom Institute for Health Research, University of South Australia, Australia. Electronic address:

Objectives: Rural Australian adults are consistently identified as insufficiently active, likely due to challenges implementing community-based physical activity programs in rural settings. On-line strategies to promote physical activity may be particularly effective in rural settings where isolation and scarcity of qualified support are potential barriers. The Rural Environments and Community Health (REACH) study evaluated the effectiveness of an online-delivered walking intervention among South Australian rural adults.

Design: Randomised controlled study design.

Methods: A twelve-week intervention, with six- and twelve-month follow-up, was conducted. Participants (n=171; 50.6±12.5years), recruited through flyers, local newspapers and radio, were randomised to comparison or intervention groups and received a pedometer. The intervention group received access to the REACH website and personalised step goals based on ratings of perceived exertion and daily affect. The comparison group received a paper diary and generic step goals. Outcome measures were accelerometry-assessed sedentary, light (LPA) and moderate-to-vigorous (MVPA) physical activity. Linear mixed models assessed changes over the intervention and follow-ups.

Results: Sedentary time decreased, and LPA and MVPA increased in both groups across the intervention (p<0.05). The intervention group demonstrated a larger increase in LPA at six-month follow-up relative to comparison (p<0.05). Both groups decreased sedentary time, overall and in bouts ≥30min, between baseline and twelve-month follow-up (p<0.05). From baseline to twelve-month follow-up, MVPA (total min and bouts ≥10min) declined more in the comparison group than the intervention group (p<0.05).

Conclusion: While increased physical activity and decreased sedentary time were observed in both groups during the intervention period, maintenance was only observed for LPA at six-month follow-up in the intervention group. By twelve-month follow-up, post-intervention improvements had largely disappeared, suggesting that additional research is needed to identify ways to improve long-term adherence.
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http://dx.doi.org/10.1016/j.jsams.2018.07.002DOI Listing
January 2019

Bone health, activity and sedentariness at age 11-12 years: Cross-sectional Australian population-derived study.

Bone 2018 07 16;112:153-160. Epub 2018 Apr 16.

Murdoch Children Research Institute, Parkville, VIC, Australia; The University of Melbourne, Parkville, VIC, Australia; The Dept of Paediatrics and Liggins Institute, University of Auckland, New Zealand. Electronic address:

Aim: To examine cross-sectional associations of children's bone health (size, density, strength) with moderate-vigorous physical activity (MVPA) and sedentary behaviour by considering: (1) duration of activity, (2) fragmentation, and (3) duration/fragmentation combined.

Methods: Design: Population-based cross-sectional study.

Participants: 11-12 year-olds in the Longitudinal Study of Australian Children's Child Health CheckPoint. Exposures: MVPA and sedentary behaviour (7-day accelerometry), yielding (1) daily average durations (min/day) and (2) fragmentations (the parameter alpha, representing the relationship between activity bout frequency and bout length).

Outcomes: Tibial peripheral quantitative computed tomography (bone density, geometry, strength).

Analysis: Multivariable regression models including activity durations and fragmentations separately and combined.

Results: Of 1357 children attending the CheckPoint, 864 (64%) provided both bone and accelerometry data (mean age 11.4 years (standard deviation (SD) 0.5); 49% male). Mean daily MVPA and sedentary behaviour durations were 34.4 min/day (SD 28.3) and 667.9 min/day (SD 71.9) respectively for boys and girls combined. Each additional daily hour of MVPA was associated with small bone health benefits comprising greater periosteal and endosteal circumference (standardised effect sizes 0.25, 95% CI 0.10 to 0.40 and 0.21, 95% CI 0.03 to 0.39, respectively) and bone strength (0.26, 95% CI 0.14 to 0.38). Sedentary duration and fragmentation of either MVPA or sedentary behaviour showed little association with bone health.

Conclusions: In early adolescence, MVPA duration showed associations with better bone health that, while modest, could be of population-level importance. MVPA fragmentation and sedentary behaviour duration and fragmentation seemed less important.
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http://dx.doi.org/10.1016/j.bone.2018.04.011DOI Listing
July 2018

A systematic literature review of tibial plateau fractures: What classifications are used and how reliable and useful are they?

Injury 2018 Mar 31;49(3):473-490. Epub 2018 Jan 31.

Centre for Orthopaedic and Trauma Research, The University of Adelaide, Adelaide, SA 5000, Australia; Department of Orthopaedics and Trauma, Royal Adelaide Hospital, Adelaide, SA 5000, Australia.

Introduction: Classification systems such as the Schatzker and AO/OTA have been proposed for standardised assessment of tibial plateau fractures and to guide clinical decision making. However, there has been no comprehensive literature review of all classification systems for tibial plateau fractures, including assessment of their reliability. The aim of this systematic review was to identify and appraise previously established classification systems for tibial plateau fractures and determine their reliability for fracture classification.

Methods: Six databases were searched from inception until October 2016. Classification systems for tibial plateau fractures were identified. No restriction was placed on imaging modality (plain film X-ray, CT, MRI). Data synthesis was performed to identify common features of the systems, their prevalence within the literature and studies of intra and inter-rater reliability of fracture classification using Kappa coefficient (κ).

Results: Thirty-eight classification systems were identified, five of which were a sub-classification of a single fracture type from a previous tool. The Schatzker and AO/OTA classification systems were the most commonly reported. Of the tools identified only five have been tested for inter and intra-observer reliability (Schatzker, AO/OTA, Duparc, Hohl and Luo). Reliability of more simplistic classification systems, such as that by Luo et al. (three-column) was typically high (intra-κ = 0.67-0.81, inter-κ = 0.71-0.87), but with the disadvantage of providing less information on fracture patterns and morphology. Intra and inter-observer reliability using plain film X-ray was frequently moderate (κ = 0.40-0.60), with 2D and 3D CT typically improving reliability of classification. Only 11 of the 32 complete classification systems identified association of fracture classification with clinical outcome.

Discussion: Frequently used systems for classification of tibial plateau fractures display moderate intra and inter-observer reliability. More sophisticated imaging modalities such as 2D and 3D CT typically improve reliability estimates. Using fracture classification based on imaging findings to predict clinical outcome was not a commonly reported goal of newly developed systems. More detailed assessment of fracture patterns and morphology, in conjunction with information on surgical fixation, may be desirable for predicting outcomes and to guide clinical decision making.
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http://dx.doi.org/10.1016/j.injury.2018.01.025DOI Listing
March 2018

Usage of Sit-Stand Workstations and Associations Between Work and Nonwork Sitting Time: An Observational Study.

J Occup Environ Med 2018 05;60(5):e268-e272

Sansom Institute for Health Research, University of South Australia, Adelaide, South Australia, Australia (Mr Mazzotta, Dr McEvoy); Alliance for Research in Exercise, Nutrition and Activity (ARENA), School of Health Sciences, University of South Australia, Adelaide, South Australia, Australia (Drs Ferrar, Fraysse); Department of Physiotherapy, College of Nursing and Health Sciences, Flinders University, Adelaide, South Australia, Australia (Dr Lewis).

Objective: No studies have objectively measured habitual usage of sit-stand workstations.

Methods: Eighteen full-time office workers participated (47.9 ± 9.2 years, 61% female). Sitting time was objectively measured (activPAL, 24 h/7 days), and time at desk, desk position, and perceptions of desk use were self-reported.

Results: Participants sat for 39% of their daily workstation time, and changed workstation position twice daily. The most common reasons for standing included back pain (44%) and tiredness (22%). The majority of participants received no workstation occupational health (72%) or educational (61%) information. Workstation standing time had a significant moderate correlation with total daily standing time (P = 0.02).

Conclusion: Office workers with sit-stand workstations rarely change desk position, and there is no relationship between the time spent sitting at the workstation, and total daily sitting time. Education about the workstations was limited.
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http://dx.doi.org/10.1097/JOM.0000000000001252DOI Listing
May 2018
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