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Background and Aims: Understanding the amounts of intensity-specific movement needed to attenuate the association between sedentary time and mortality may help to inform personalized prescription and behavioral counselling. Herein, we examined the joint associations of sedentary time and intensity-specific physical activity with all-cause and cardiovascular disease (CVD) mortality., Methods: Prospective cohort study including 73,729 adults from the UK Biobank who wore an Axivity AX3 accelerometer on their dominant wrist for at least 3 days, being one a weekend day, between June 2013 and December 2015. We considered the median tertile values of sedentary time and physical activity in each intensity band to determine the amount of physical activity needed to attenuate the association between sedentary time and mortality., Results: During a median of 6.9 years of follow-up (628,807 person-years), we documented 1521 deaths, including 388 from CVD. Physical activity of any intensity attenuated the detrimental association of sedentary time with mortality. Overall, at least a median of 6 min/day of vigorous physical activity, 30 min/day of MVPA, 64 min/day of moderate physical activity, or 163 min/day of light physical activity (mutually-adjusted for other intensities) attenuated the association between sedentary time and mortality. High sedentary time was associated with higher risk of CVD mortality only among participants with low MVPA (HR 1.96; 95% CI 1.23 to 3.14)., Conclusions: Different amounts of each physical activity intensity may attenuate the association between high sedentary time and mortality., (© 2024. The Author(s).)

Background: Physical behaviors such physical activity, sedentary behavior, and sleep are associated with mortality, but there is a lack of epidemiological data and knowledge using device-measured physical behaviors., Purpose: To assess the feasibility of baseline data collection using the Prospective Physical Activity, Sitting, and Sleep consortium (ProPASS) protocols in the specific context of Saudi Arabia. ProPASS is a recently developed global platform for collaborative research that aims to harmonize retrospective and prospective data on device-measured behaviors and health. Using ProPASS methods for collecting data to perform such studies in Saudi Arabia will provide standardized data from underrepresented countries., Method: This study explored the feasibility of baseline data collection in Saudi Arabia between November and December 2022 with a target recruitment of 50 participants aged ≥ 30 years. Established ProPASS methods were used to measure anthropometrics, measure blood pressure, collect blood samples, carry out physical function test, and measure health status and context of physical behaviors using questionnaires. The ActivPal™ device was used to assess physical behaviors and the participants were asked to attend two sessions at (LHRC). The feasibility of the current study was assessed by evaluating recruitment capability, acceptability, suitability of study procedures, and resources and abilities to manage and implement the study. Exit interviews were conducted with all participants., Result: A total of 75 participants expressed an interest in the study, out of whom 54 initially agreed to participate. Ultimately, 48 participants were recruited in the study (recruitment rate: 64%). The study completion rate was 87.5% of the recruited participants; 95% participants were satisfied with their participation in the study and 90% reported no negative feelings related to participating in the study. One participant reported experiencing moderate skin irritation related to placement of the accelerometer. Additionally, 96% of participants expressed their willingness to participate in the study again., Conclusion: Based on successful methodology, data collection results, and participants' acceptability, the ProPASS protocols are feasible to administer in Saudi Arabia. These findings are promising for establishing a prospective cohort in Saudi Arabia., (© 2024. The Author(s).)

Background: Combinations of movement behaviors (i.e., physical activity, sedentary behavior, sleep) are associated with health and developmental outcomes in youth. Youth vary in how they accumulate these behaviors, both in volume and specific domains (e.g., sedentary time spent on recreational screen activities vs homework). The aim of this study was to examine how youth's combined general and domain-specific movement trajectories differ by socioeconomic position., Methods: We conducted a longitudinal, group-based multi-trajectory analysis to identify general and domain-specific movement trajectory profiles for 2457 youth from age 10 to 14 years from the Longitudinal Study of Australian Children from 2014-2018. We used multinomial logistic regression to test if socioeconomic position predicted profile membership., Results: We identified three general movement trajectory profiles for both sexes, four domain-specific profiles for males, and five for females. For general movement trajectories, females from lower socioeconomic positions were more likely to be a combination of less active and more sedentary than females from higher socioeconomic positions. Males across socioeconomic positions spend similar amounts of time in physical activity, sedentary time, and sleep. For domain-specific movement trajectories, youth from lower socioeconomic positions were likely to spend a combination of less time in education-based sedentary behavior and more time in recreational screen activities than their higher socioeconomic position peers., Conclusion: Our results indicate that socioeconomic position predicted in which domains youth accumulate their movements. Future observational research and interventions targeting different socioeconomic groups should therefore consider domain-specific movement trajectories., (© 2023. The Author(s).)

Background: Over the last decade use of raw acceleration metrics to assess physical activity has increased. Metrics such as Euclidean Norm Minus One (ENMO), and Mean Amplitude Deviation (MAD) can be used to generate metrics which describe physical activity volume (average acceleration), intensity distribution (intensity gradient), and intensity of the most active periods (MX metrics) of the day. Presently, relatively little comparative data for these metrics exists in youth. To address this need, this study presents age- and sex-specific reference percentile values in England youth and compares physical activity volume and intensity profiles by age and sex., Methods: Wrist-worn accelerometer data from 10 studies involving youth aged 5 to 15 y were pooled. Weekday and weekend waking hours were first calculated for youth in school Years (Y) 1&2, Y4&5, Y6&7, and Y8&9 to determine waking hours durations by age-groups and day types. A valid waking hours day was defined as accelerometer wear for ≥ 600 min·d -1 and participants with ≥ 3 valid weekdays and ≥ 1 valid weekend day were included. Mean ENMO- and MAD-generated average acceleration, intensity gradient, and MX metrics were calculated and summarised as weighted week averages. Sex-specific smoothed percentile curves were generated for each metric using Generalized Additive Models for Location Scale and Shape. Linear mixed models examined age and sex differences., Results: The analytical sample included 1250 participants. Physical activity peaked between ages 6.5-10.5 y, depending on metric. For all metrics the highest activity levels occurred in less active participants (3 rd -50 th percentile) and girls, 0.5 to 1.5 y earlier than more active peers, and boys, respectively. Irrespective of metric, boys were more active than girls (p < .001) and physical activity was lowest in the Y8&9 group, particularly when compared to the Y1&2 group (p < .001)., Conclusions: Percentile reference values for average acceleration, intensity gradient, and MX metrics have utility in describing age- and sex-specific values for physical activity volume and intensity in youth. There is a need to generate nationally-representative wrist-acceleration population-referenced norms for these metrics to further facilitate health-related physical activity research and promotion., (© 2023. The Author(s).)

Background: The complexity of sleep hinders the formulation of sleep guidelines. Recent studies suggest that different unhealthy sleep characteristics jointly increase the risks for cardiovascular disease (CVD). This study aimed to estimate the differences in CVD-free life expectancy between people with different sleep profiles., Methods: We included 308,683 middle-aged adults from the UK Biobank among whom 140,181 had primary care data linkage. We used an established composite sleep score comprising self-reported chronotype, duration, insomnia complaints, snoring, and daytime sleepiness to derive three sleep categories: poor, intermediate, and healthy. We also identified three clinical sleep disorders captured by primary care and inpatient records within 2 years before enrollment in the cohort: insomnia, sleep-related breathing disorders, and other sleep disorders. We estimated sex-specific CVD-free life expectancy with three-state Markov models conditioning on survival at age 40 across different sleep profiles and clinical disorders., Results: We observed a gradual loss in CVD-free life expectancy toward poor sleep such as, compared with healthy sleepers, poor sleepers lost 1.80 [95% CI 0.96-2.75] and 2.31 [1.46-3.29] CVD-free years in females and males, respectively, while intermediate sleepers lost 0.48 [0.41-0.55] and 0.55 [0.49-0.61] years. Among men, those with clinical insomnia or sleep-related breathing disorders lost CVD-free life by 3.84 [0.61-8.59] or 6.73 [5.31-8.48] years, respectively. Among women, sleep-related breathing disorders or other sleep disorders were associated with 7.32 [5.33-10.34] or 1.43 [0.20-3.29] years lost, respectively., Conclusions: Both self-reported and doctor-diagnosed poor sleep are negatively associated with CVD-free life, especially pronounced in participants with sleep-related breathing disorders., (© 2023. The Author(s).)

Background: Understanding the developmental trajectories of outdoor time, screen time and sleep is necessary to inform early interventions that promote healthy behaviours. This study aimed to describe concurrent trajectories of outdoor time, screen time and sleep across the early childhood period and their maternal predictors., Methods: Data across five time points at child age 4, 9, 19, 42 and 60 months from the INFANT intervention were analysed. Mothers reported their child's usual outdoor time, screen time and sleep duration, in addition to a range of maternal beliefs, attitudes, expectations and behaviours. Group-based multi-trajectory modelling was used to model concurrent trajectories of children's behaviours. Multinomial logistic regression models determined the associations of maternal predictors with trajectory groups, adjusting for child sex and baseline age, intervention allocation, and clustering by recruitment., Results: Of the 542 children recruited, 528 had data for outdoor time, screen time and sleep at one or more time points and were included in trajectory analyses Four trajectories were identified: 'unstable sleep, increasing outdoor time, low screen' (~ 22% of sample), 'high outdoor time, low screen, high sleep' (~ 24%), 'high sleep, increasing outdoor time, low screen' (~ 45%), 'high screen, increasing outdoor time, high sleep' (~ 10%). The 'high sleep, increasing outdoor time, low screen' group, comprising the largest percentage of the sample, demonstrated the healthiest behaviours. Predictors of group membership included: views of physically active children, screen time knowledge, screen time use, self-efficacy, physical activity optimism, future expectations for children's physical activity and screen time, perceptions of floor play safety, and maternal physical activity, screen time, and sleep quality., Conclusions: Four distinct trajectories of outdoor time, screen time and sleep were identified, with the most common (and healthiest) characterized by high levels of sleep. Maternal beliefs, attitudes, expectations and behaviours are important in the development of movement behaviour trajectories across early childhood. Future interventions and public policy may benefit from targeting these factors to support healthy movement behaviours from a young age., (© 2022. The Author(s).)

Background: Reliable estimates of habitual sleep, physical activity, and sedentary time are essential to investigate the associations between these behaviours and health outcomes. While the number of days needed and hours/day for estimates of physical activity and sedentary time are generally known, the criteria for sleep estimates are more uncertain. The objective of this study was to identify the number of nights needed to obtain reliable estimates of habitual sleep behaviour using the GENEActiv wrist worn accelerometer. The number of days to obtain reliable estimate of physical activity was also examined., Methods: Data was used from a two-year longitudinal study. Children wore an accelerometer for up to 8 days 24 h/day across three timepoints. The sample included 2,745 children (51 % girls) between the ages of 7-12-years-old (mean = 9.8 years, SD = 1.1 year) with valid accelerometer data from any timepoint. Reliability estimates were calculated for sleep duration, sleep efficiency, sleep onset, wake time, time in bed, light physical activity, moderate physical activity, moderate-to-vigorous physical activity, vigorous physical activity, and sedentary time., Results: Intraclass correlations and the Spearman Brown prophecy formula were used to determine the nights and days needed for reliable estimates. We found that between 3 and 5 nights were needed to achieve acceptable reliability (ICC = 0.7) in sleep outcomes, while physical activity and sedentary time outcomes required between 3 and 4 days., Conclusions: To obtain reliable estimates, researchers should consider these minimum criteria when designing their studies and prepare strategies to ensure sufficient wear time compliance.

Background: The restrictions associated with the 2020 COVID-19 pandemic has resulted in changes to young children's daily routines and habits. The impact on their participation in movement behaviours (physical activity, sedentary screen time and sleep) is unknown. This international longitudinal study compared young children's movement behaviours before and during the COVID-19 pandemic., Methods: Parents of children aged 3-5 years, from 14 countries (8 low- and middle-income countries, LMICs) completed surveys to assess changes in movement behaviours and how these changes were associated with the COVID-19 pandemic. Surveys were completed in the 12 months up to March 2020 and again between May and June 2020 (at the height of restrictions). Physical activity (PA), sedentary screen time (SST) and sleep were assessed via parent survey. At Time 2, COVID-19 factors including level of restriction, environmental conditions, and parental stress were measured. Compliance with the World Health Organizations (WHO) Global guidelines for PA (180 min/day [≥60 min moderate- vigorous PA]), SST (≤1 h/day) and sleep (10-13 h/day) for children under 5 years of age, was determined., Results: Nine hundred- forty-eight parents completed the survey at both time points. Children from LMICs were more likely to meet the PA (Adjusted Odds Ratio [AdjOR] = 2.0, 95%Confidence Interval [CI] 1.0,3.8) and SST (AdjOR = 2.2, 95%CI 1.2,3.9) guidelines than their high-income country (HIC) counterparts. Children who could go outside during COVID-19 were more likely to meet all WHO Global guidelines (AdjOR = 3.3, 95%CI 1.1,9.8) than those who were not. Children of parents with higher compared to lower stress were less likely to meet all three guidelines (AdjOR = 0.5, 95%CI 0.3,0.9)., Conclusion: PA and SST levels of children from LMICs have been less impacted by COVID-19 than in HICs. Ensuring children can access an outdoor space, and supporting parents' mental health are important prerequisites for enabling pre-schoolers to practice healthy movement behaviours and meet the Global guidelines.

Background: COVID-19 lockdowns may lead to physical inactivity, a major risk factor for non-communicable diseases. This study aims to determine: 1) the trajectory in daily step counts before, during and after the lockdown in China, and 2) the characteristics associated with the trajectories., Methods: From December 2019 to July 2020, smartphone-based step counts were continuously collected in 815 Chinese adults residing in Shanghai over 202 days across three phases: before, during, and after the lockdown. Participant characteristics were reported, and height, weight and body composition measured before the lockdown. A 'sharp' regression discontinuity design with cluster robust standard errors was used to test the effect of the lockdown and reopening on daily steps and a linear mixed model was used to examine the characteristics associated with trajectories during the observed period., Results: Based on 164,630 person-days of data, we found a sharp decline in daily step counts upon the lockdown (24/01/2020) by an average of 3796 (SE = 88) steps, followed by a significant trend of increase by 34 steps/day (SE = 2.5; p < .001) until the end of the lockdown (22/03/2020). This increasing trend continued into the reopening phase at a slower rate of 5 steps per day (SE = 2.3; p = 0.029). Those who were older, married, university educated, insufficiently active, had an 'at risk' body composition, and those in the control group, were slower at recovering step counts during the lockdown, and those who were older, married, without university education and with an 'at risk' body composition recovered step counts at a slower pace after the reopening., Conclusions: Despite later increases in step counts, COVID-19 lockdown led to a sustained period of reduced physical activity, which may have adverse health implications. Governments and health professionals around the world should continue to encourage and facilitate physical activity during the pandemic.

Background: Physical activity and sedentary behavior are related with psycho-social variables among youth, however its relationship with bullying victimization is unclear. The aim of the study was to clarify the associations between physical activity and sedentary behaviors with bullying victimization among children and adolescents., Methods: Two independent authors searched in four databases. The studies were selected/included only if participants were children and/or adolescents and the relationship between physical activity and/or sedentary behavior with bullying victimization was reported. Random-effects meta-analyses were used., Results: A total of 18 cross-sectional studies (including 386,740 children and adolescents, 51.8% females) were reviewed. Our study found that not meeting the physical activity guidelines (Odds Ratio [OR] = 1.14, 95% confidence interval [CI], 1.04 to 1.23) and excessive sedentary behavior (i.e., 2 h per day or more of screen time) (OR = 1.21, 95% CI, 1.14 to 1.28) were associated with 14 and 21% higher bullying victimization, respectively. Consistent associations were also found when we analyzed specific forms of bullying for sedentary behavior, including traditional and cyberbullying., Conclusions: The present study establishes the first quantitative framework for understanding the influence of physical activity and sedentary behavior on bullying victimization, and lays the groundwork for future studies and interventions aimed to its promotion., Trial Registration: CRD42018099388 .

Background: The impact of declining physical activity and increased sedentary behaviour in children and adolescents globally prompted the development of national and international physical activity guidelines. This research aims to systematically identify and compare national and international physical activity guidelines for children and adolescents and appraise the quality of the guidelines to promote best practice in guideline development., Methods: This systematic review was registered in the International Prospective Register of Systematic Reviews (PROSPERO) and reported using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. Only national, or international physical activity and/or sedentary behaviour guidelines were included in the review. Included guidelines targeted children and adolescents aged between 5 and 18 years. A grey literature search was undertaken incorporating electronic databases, custom Google search engines, targeted websites and international expert consultation. Guideline quality was assessed using the Appraisal of Guidelines for Research and Evaluation II Instrument (AGREE II)., Results: The search resulted in 50 national or international guidelines being identified. Twenty-five countries had a national guideline and there were three international guidelines (European Union, Nordic countries (used by Iceland, Norway and Sweden), World Health Organization (WHO)). Nineteen countries and the European Union adopted the WHO guidelines. Guidelines varied in relation to date of release (2008 to 2019), targeted age group, and guideline wording regarding: type, amount, duration, intensity, frequency and total amount of physical activity. Twenty-two countries included sedentary behaviour within the guidelines and three included sleep. Total scores for all domains of the AGREE II assessment for each guideline indicated considerable variability in guideline quality ranging from 25.8 to 95.3%, with similar variability in the six individual domains. Rigorous guideline development is essential to ensure appropriate guidance for population level initiatives., Conclusions: This review revealed considerable variability between national/international physical activity guideline quality, development and recommendations, highlighting the need for rigorous and transparent guideline development methodologies to ensure appropriate guidance for population-based approaches. Where countries do not have the resources to ensure this level of quality, the adoption or adolopment (framework to review and update guidelines) of the WHO guidelines or guidelines of similar quality is recommended., Trial Registration: Review registration: PROSPERO 2017 CRD42017072558.

Background: Excessive engagement with digital screens is harmful to children's health. However, new evidence suggests that exposure at moderate levels may not be harmful and may even provide benefit. Therefore, our objective was to determine if there are curvilinear relationships between different types of screen time and a diverse set of outcomes, including health and education., Methods: We address our objective using a repeated measures design. Children (N = 4013), initially aged 10-11 were assessed every 2 years between 2010 and 2014. Children's screen time behavior was measured using time-use diaries, and categorized into five types: social, passive, interactive, educational, or other. We used measures of children's physical health, health-related quality of life, socio-emotional outcomes, and school achievement. The analysis plan was pre-registered. Models were adjusted for gender, socio-economic status, ethnicity, number of siblings, and housing factors., Results: There were linear associations between total screen time and all outcomes, such that more screen time was associated with worse outcomes. However, there was variability when examined by screen time type. Passive screen time (e.g., TV) was associated with worse outcomes, educational screen time (e.g., computer for homework) was associated with positive educational outcomes and had no negative relations with other outcomes. Interactive screen time (e.g., video games) had positive associations with educational outcomes but negative associations with other outcomes. In all instances, these significant associations were small or very small, with standardised effects < 0.07. We found little evidence of curvilinear relationships., Conclusions: The small effects of screen time on children's outcomes appear to be moderated by the type of screen time. Policy makers, educators, and parents should consider the type of screen time when considering the benefits and harms of use.

Background: Physical activity and sedentary behaviour have been suggested to independently affect a number of health outcomes. To what extent different combinations of physical activity and sedentary behaviour may influence physical function and frailty outcomes in older adults is unknown. The aim of this study was to examine the combination of mutually exclusive categories of accelerometer-measured physical activity and sedentary time on physical function and frailty in older adults., Methods: 771 older adults (54% women; 76.8 ± 4.9 years) from the Toledo Study for Healthy Aging participated in this cross-sectional study. Physical activity and sedentary time were measured by accelerometry. Physically active was defined as meeting current aerobic guidelines for older adults proposed by the World Health Organization. Low sedentary was defined as residing in the lowest quartile of the light physical activity-to-sedentary time ratio. Participants were then classified into one of four mutually exclusive movement patterns: (1) 'physically active & low sedentary', (2) 'physically active & high sedentary', (3) 'physically inactive & low sedentary', and (4) 'physically inactive & high sedentary'. The Short Physical Performance Battery was used to measure physical function and frailty was assessed using the Frailty Trait Scale., Results: 'Physically active & low sedentary' and 'physically active & high sedentary' individuals had significantly higher levels of physical function (β = 1.73 and β = 1.30 respectively; all p < 0.001) and lower frailty (β = - 13.96 and β = - 8.71 respectively; all p < 0.001) compared to 'physically inactive & high sedentary' participants. Likewise, 'physically inactive & low sedentary' group had significantly lower frailty (β = - 2.50; p = 0.05), but significance was not reached for physical function., Conclusions: We found a dose-response association of the different movement patterns analysed in this study with physical function and frailty. Meeting the physical activity guidelines was associated with the most beneficial physical function and frailty profiles in our sample. Among inactive people, more light intensity relative to sedentary time was associated with better frailty status. These results point out to the possibility of stepwise interventions (i.e. targeting less strenuous activities) to promote successful aging, particularly in inactive older adults.

Background: Understanding the early roots of physical activity and sedentary behaviors is critical to developing intervention programs that promote healthy lifestyle habits in infants and children. There is, however, no evidence on how these behaviors cluster and develop together during early childhood. The aim of this study was to identify single and joint longitudinal trajectories in physical activity and screen time amongst children aged 0 to 9 years, their social-demographic predictors and their prospective health-related quality-of-life and socio-emotional outcomes., Methods: Three waves of data from The Longitudinal Study of Australian Children, a national study tracking two cohorts every 2 years (B-cohort, 0-5 years, n = 4,164; K-cohort, 4-9 years, n = 3,974) were analysed. Growth mixture modelling was applied to longitudinal time-use diary data to identify joint trajectories in children's physical activity and screen time over Waves 1-3. Key socio-demographic variables measured at Wave 1 were used to predict membership in different trajectories. The prospective consequences (at Wave 3) of time-use trajectories on health-related quality-of-life and socio-emotional outcomes were assessed., Results: Three physical-activity/screen-time trajectories were identified for both cohorts: Cluster-A-children who maintained low levels of physical activity and screen time (∽50% of the sample), Cluster-B-children who progressively increased physical activity and maintained low screen-time levels (∽25%), and Cluster-C-children who maintained low physical-activity levels and increased screen time (∽25%). Children in Cluster-B experienced the best health-related quality-of-life and socio-emotional outcomes, while those in Cluster-C experienced the worst. Children who were female, Indigenous, from non-English-speaking backgrounds, not living with two biological parents, in more affluent households and neighbourhoods, without siblings and with parents with poor mental health were at greater risk of falling into Cluster-A or Cluster-C., Conclusion: Our findings identified which children are most at-risk of falling into time-use trajectories that lead to poor health-related quality-of-life and socio-emotional outcomes later in life, increasing our ability to monitor, detect and prevent these suboptimal behaviours prior to their onset.

Background: There is little evidence of whether or not those who have attended cardiac rehabilitation (CR) are meeting the physical activity guidelines recommended for secondary prevention of cardiovascular disease. In healthy individuals, there is evidence, that even if individuals are meeting the physical activity guidelines, the harmfulness of too much sedentary behaviour remains (active couch potato (ACP) phenomenon). Currently, there appears to be no evidence of the ACP phenomenon in those attending CR. The aims of the study are to examine the level of physical activity and sedentary behaviour in those with coronary heart disease (CHD) who have attended CR, and to investigate the potential independent associations between these behaviours and cardio-metabolic health, health-related quality of life, exercise capacity, anxiety and depression., Methods: A prospective cohort study will be conducted in Australia over 12-months. Baseline data from this study will contribute to an international, multi-centre cross-sectional study (Australia, New Zealand, United States of America, South Africa, Spain, and Portugal). Adults currently enrolled in a 6-week phase II cardiac rehabilitation program with stable CHD and receiving optimal medical treatment +/- revascularisation will be recruited. Outcome measures will be taken at baseline (commence CR), 6 weeks (complete CR), 6 and 12-months. Physical activity and sedentary behaviour will be measured using accelerometry and two questionnaires (Active Australia Survey, Past-Day Adults' Sedentary Time questionnaire). Health outcomes will include body mass index, waist-to-hip ratio, lipid profile, blood glucose level, quality-of-life (MacNew), exercise capacity (6-min walk test), anxiety and depression (Hospital Anxiety and Depression Scale)., Discussion: There has been limited investigation of the physical activity levels and sedentary behaviour of individuals with CHD attending CR. There are no studies assessing the relationship of these behaviours with health outcomes over the short and medium-term. As in healthy individuals, physical activity and sedentary behaviour may have independent effects on cardiovascular risk factors in people with CHD, which may contribute to recurrent cardiovascular events. If this is so, reducing sedentary behaviour may be a feasible first-line, additional and more achievable strategy to improve the health of those with CHD, alongside traditional recommendations to increase the time spent in moderate-to-vigorous intensity physical activity., Trial Registration: Australian New Zealand Clinical Trials Registry (ANZCTR): ACTRN12615000995572.