How European Fans in Training (EuroFIT), a lifestyle change program for men delivered in football clubs, achieved its effect: a mixed methods process evaluation embedded in a randomised controlled trial.

BACKGROUND: A randomised trial of European Fans in Training (EuroFIT), a 12-week healthy lifestyle program delivered in 15 professional football clubs in the Netherlands, Norway, Portugal, and the United Kingdom, successfully increased physical activity and improved diet but did not reduce sedentary time. To guide future implementation, this paper investigates how those effects were achieved. We ask: 1) how was EuroFIT implemented? 2) what were the processes through which outcomes were achieved? METHODS: We analysed qualitative data implementation notes, observations of 29 of 180 weekly EuroFIT deliveries, semi-structured interviews with 16 coaches and 15 club representatives, and 30 focus group discussions with participants (15 post-program and 15 after 12 months). We descriptively analysed quantitative data on recruitment, attendance at sessions and logs of use of the technologies and survey data on the views of participants at baseline, post program and after 12 months. We used a triangulation protocol to investigate agreement between data from difference sources, organised around meeting 15 objectives within the two research questions. RESULTS: We successfully recruited clubs, coaches and men to EuroFIT though the draw of the football club seemed stronger in the UK and Portugal. Advertising that emphasized getting fitter, club-based deliveries, and not 'standing out' worked and attendance and fidelity were good, so that coaches in all countries were able to deliver EuroFIT flexibly as intended. Coaches in all 15 clubs facilitated the use of behaviour change techniques and interaction between men, which together enhanced motivation. Participants found it harder to change sedentary time than physical activity and diet. Fitting changes into daily routines, planning for setbacks and recognising the personal benefit of behaviour change were important to maintain changes. Bespoke technologies were valued, but technological hitches frustrated participants. CONCLUSION: EuroFIT was delivered as planned by trained club coaches working flexibly in all countries. It worked as expected to attract men and support initiation and maintenance of changes in physical activity and diet but the use of bespoke, unstable, technologies was frustrating. Future deliveries should eliminate the focus on sedentary time and should use only proven technologies to support self-monitoring and social interaction. TRIAL REGISTRATION: ISRCTN81935608, registered 16/06/2015.

Effects of a comprehensive lifestyle intervention on cardiovascular health: the TANSNIP-PESA trial.

AIMS: To investigate the effectiveness of a 3-year worksite lifestyle intervention on cardiovascular metrics and to study whether outcomes are influenced by baseline subclinical atherosclerosis (SA) by non-invasive imaging. METHODS AND RESULTS: A randomized controlled trial was performed to compare a lifestyle intervention with standard of care in asymptomatic middle-aged subjects, stratified by SA. The intervention consisted of nine motivational interviews during the first year, followed by three further sessions between Years 1 and 3. The primary outcome was the change in a pre-specified adaptation of the Fuster-BEWAT score (Blood pressure, Exercise, Weight, Alimentation, and Tobacco) between baseline and follow-up Years 1-3. A total of 1020 participants (mean age 50 ± 4 years) were enrolled, of whom 510 were randomly assigned to the intervention and 510 to the control group. The baseline adapted Fuster-BEWAT score was 16.2 ± 3.7 points in the intervention group and 16.5 ± 3.5 points in the control group. At Year 1, the score improved significantly in intervention participants compared with controls [estimate 0.83 (95% CI 0.52-1.15) points]. However, intervention effectiveness decreased to non-significant levels at Year 3 [0.24 (95% CI -0.10 to 0.59) points]. Over the 3-year period, the intervention was effective in participants having low baseline SA [0.61 (95% CI 0.30-0.93) points] but not in those with high baseline SA [0.19 (95% CI -0.26 to 0.64) points]. CONCLUSION: In middle-aged asymptomatic adults, a lifestyle intervention was associated with a significant improvement in cardiovascular health and behavioural metrics. The effect attenuated after 1 year as the intensity of the intervention was reduced. TRIAL REGISTRATION: ClinicalTrials.gov (NCT02561065).

Participation of people living with disabilities in physical activity: a global perspective.

Approximately 1·5 billion people worldwide live with a physical, mental, sensory, or intellectual disability, about 80% of which are in low-income and middle-income countries. This Series paper provides a global overview of the prevalence, benefits, and promotion policies for physical activity for people living with disabilities (PLWD). PLWD are 16-62% less likely to meet physical activity guidelines and are at higher risk of serious health problems related to inactivity than people without disabilities. Meta-analyses have shown that physical activity has beneficial effects on cardiovascular fitness (average standardised mean difference [SMD] 0·69 [95% CI 0·31-1·01]), musculoskeletal fitness (0·59 [0·31-0·87]), cardiometabolic risk factors (0·39 [0·04-0·75]), and brain and mental health outcomes (0·47 [0·21-0·73]). These meta-analyses also show that health benefits can be achieved even with less than 150 min of physical activity per week, and suggest that some physical activity is better than none. Meta-analyses of interventions to increase physical activity for PLWD have reported effect sizes ranging from SMD 0·29 (95% CI 0·17-0·41, k=10) to 1·00 (0·46-1·53, k=10). There is increasing awareness among policy makers of the needs of PLWD for full participation in physical activity. Physical activity action plans worldwide must be adequately resourced, monitored, and enforced to truly advance the fundamental rights of PLWD to fully participate in physical activity.

The effectiveness of physical activity interventions using activity trackers during or after inpatient care: a systematic review and meta-analysis of randomized controlled trials.

BACKGROUND: Promoting physical activity (PA) in patients during and/or after an inpatient stay appears important but challenging. Interventions using activity trackers seem promising to increase PA and enhance recovery of physical functioning. OBJECTIVE: To review the effectiveness of physical activity interventions using activity trackers on improving PA and physical functioning, compared to usual care in patients during and/or after inpatient care. In addition, it was determined whether the following intervention characteristics increase the effectiveness of these interventions: the number of behaviour change techniques (BCTs) used, the use of a theoretical model or the addition of coaching by a health professional. DESIGN: Systematic review and meta-analysis. DATA SOURCES: PubMed, EMBASE, Cinahl, SportDiscus and Web of Science databases were searched in March 2020 and updated in March 2021. ELIGIBILITY CRITERIA FOR SELECTING STUDIES: Randomized controlled trials (RCTs) including interventions using activity trackers and feedback on PA in adult patients during, or less than 3 months after, hospitalization or inpatient rehabilitation. METHODS: Following database search and title and abstract screening, articles were screened on full text for eligibility and then assessed for risk of bias by using the Physiotherapy Evidence Database (PEDro) scale. Meta-analyses, including subgroup analysis on intervention characteristics, were conducted for the outcomes PA and physical functioning. RESULTS: Overall, 21 RCTs totalling 2355 patients were included. The trials covered a variety of clinical areas. There was considerable heterogeneity between studies. For the 13 studies that measured PA as an outcome variable(N = 1435), a significant small positive effect in favour of the intervention was found (standardized mean difference (SMD) = 0.34; 95%CI 0.12-0.56). For the 13 studies that measured physical functioning as an outcome variable (N = 1415) no significant effect was found (SMD = 0.09; 95%CI -0.02 - 0.19). Effectiveness on PA seems to improve by providing the intervention both during and after the inpatient period and by using a theoretical model, multiple BCTs and coaching by a health professional. CONCLUSION: Interventions using activity trackers during and/or after inpatient care can be effective in increasing the level of PA. However, these improvements did not necessarily translate into improvements in physical functioning. Several intervention characteristics were found to increase the effectiveness of PA interventions. TRIAL REGISTRATION: Registered in PROSPERO ( CRD42020175977 ) on March 23th, 2020.

Barriers and facilitators influencing the implementation of the occupational health intervention 'Dynamic Work': a qualitative study.

BACKGROUND: Sedentary behavior is associated with an increased risk of morbidity and mortality. To reduce occupational sitting time of office workers, the multi-component intervention 'Dynamic Work' was implemented in a Dutch insurance company. Although the results showed no significant reductions in sitting time, associations were found between higher levels of implementation and reductions in sitting time. Building upon these findings, this qualitative study aimed to identify barriers and facilitators from an organizational perspective for the implementation of Dynamic Work. In addition, we explored differences in barriers and facilitators between departments with a low, middle and high level of implementation. METHODS: In total, eighteen semi-structured interviews were conducted with two Dynamic Work coordinators, three occupational physiotherapists who delivered the intervention, and thirteen department managers. All participants were purposively sampled. The data was coded in Atlas.ti and a thematic analysis was performed guided by The Integrated Checklist of Determinants (TICD). RESULTS: Implementation factors were related to the organization; working culture and financial support facilitated implementation. Factors related to the implementing department mainly hindered implementation, i.e. lack of information at start of the project, late delivery of Dynamic Work equipment, large group sizes, employee's workload and work tasks, and an ongoing reorganization. The facilitating role of managers was experienced as both enabling and hindering. The pre-existing familiarity of the occupational physiotherapists with the departments and alignment amongst the three implementers facilitated implementation. Yet, the non-obligatory nature of the intervention as well as limited availability and technical problems of equipment did not support implementation. CONCLUSIONS: Various barriers and facilitators influenced the implementation of the Dynamic Work intervention, where the key role of the department manager, late delivery of dynamic work equipment and groups sizes varied between low and high implementing departments. These results can contribute to developing and improving implementation strategies in order to increase the effectiveness of future occupational health interventions. TRIAL REGISTRATION: The study protocol was registered on April 14, 2017 in the ClinicalTrials.gov Protocol Registration and Results System under registration number NCT03115645 .

Contributions of changes in physical activity, sedentary time, diet and body weight to changes in cardiometabolic risk.

BACKGROUND: Increased physical activity (PA), reduced time spent sedentary (SED), healthier diet and reduced body weight may all have a positive impact on cardiometabolic risk. The relative importance of change in each of these variables on cardiometabolic risk, however, is unclear. We therefore sought to investigate the relative contributions of changes in PA, SED, diet and body weight on cardiometabolic risk. METHODS: This is a secondary analysis of data collected from the EuroFIT randomised controlled trial, which was a 12-week group-based lifestyle intervention for overweight middle-aged men delivered by coaches in football club stadia aiming to improve PA, SED, diet, and body weight. PA and SED were assessed by accelerometry, diet using the Dietary Instrument for Nutrition Education (DINE). An overall cardiometabolic risk score was derived from combining z-scores for glucose, HbA1c, insulin, lipids and blood pressure. In total, 707 men (from the overall cohort of 1113) with complete data for these variables at baseline and 12-month follow-up were included in the multivariable linear regression analyses. RESULTS: In multivariable analyses, change in number of steps (explaining 5.1% of R2) and dietary factors (less alcohol, fatty and sugary food, and more fruit and vegetables) (together explaining 4.5% of R2), but not changes in standing time or SED, were significantly associated with change in body weight. Changes in number of steps (R2 = 1.7%), fatty food score (R2 = 2.4%), and sugary food score (R2 = 0.4%) were significantly associated with change in cardiometabolic risk score in univariable models. However, in multivariable models which included changes in weight as well as changes in steps and dietary variables, change in weight explained a substantially larger proportion of the change in cardiometabolic risk score, explaining 14.1% of R2 (out of an overall model R2 of 19.0%). When baseline (as well as change) values were also included in the model, 38.8% of R2 for change in cardiometabolic risk score was explained overall, with 14.1% of R2 still explained by change in weight. CONCLUSION: Change in body weight, together with baseline cardiometabolic risk explained most of the change in cardiometabolic risk. Thus, the benefits of increasing physical activity and improving diet on cardiometabolic risk appear to act largely via an effect on changes in body weight. TRIAL REGISTRATION: International Standard Randomised Controlled Trials, ISRCTN-81935608. Registered 06052015. https://www.isrctn.com/ISRCTN81935608?q=&filters=recruitmentCountry:Portugal&sort=&offset=7&totalResults=92&page=1&pageSize=10&searchType=basic-search.

Digitally enabled aged care and neurological rehabilitation to enhance outcomes with Activity and MObility UsiNg Technology (AMOUNT) in Australia: A randomised controlled trial.

BACKGROUND: Digitally enabled rehabilitation may lead to better outcomes but has not been tested in large pragmatic trials. We aimed to evaluate a tailored prescription of affordable digital devices in addition to usual care for people with mobility limitations admitted to aged care and neurological rehabilitation. METHODS AND FINDINGS: We conducted a pragmatic, outcome-assessor-blinded, parallel-group randomised trial in 3 Australian hospitals in Sydney and Adelaide recruiting adults 18 to 101 years old with mobility limitations undertaking aged care and neurological inpatient rehabilitation. Both the intervention and control groups received usual multidisciplinary inpatient and post-hospital rehabilitation care as determined by the treating rehabilitation clinicians. In addition to usual care, the intervention group used devices to target mobility and physical activity problems, individually prescribed by a physiotherapist according to an intervention protocol, including virtual reality video games, activity monitors, and handheld computer devices for 6 months in hospital and at home. Co-primary outcomes were mobility (performance-based Short Physical Performance Battery [SPPB]; continuous version; range 0 to 3; higher score indicates better mobility) and upright time as a proxy measure of physical activity (proportion of the day upright measured with activPAL) at 6 months. The dataset was analysed using intention-to-treat principles. The trial was prospectively registered with the Australian New Zealand Clinical Trials Registry (ACTRN12614000936628). Between 22 September 2014 and 10 November 2016, 300 patients (mean age 74 years, SD 14; 50% female; 54% neurological condition causing activity limitation) were randomly assigned to intervention (n = 149) or control (n = 151) using a secure online database (REDCap) to achieve allocation concealment. Six-month assessments were completed by 258 participants (129 intervention, 129 control). Intervention participants received on average 12 (SD 11) supervised inpatient sessions using 4 (SD 1) different devices and 15 (SD 5) physiotherapy contacts supporting device use after hospital discharge. Changes in mobility scores were higher in the intervention group compared to the control group from baseline (SPPB [continuous, 0-3] mean [SD]: intervention group, 1.5 [0.7]; control group, 1.5 [0.8]) to 6 months (SPPB [continuous, 0-3] mean [SD]: intervention group, 2.3 [0.6]; control group, 2.1 [0.8]; mean between-group difference 0.2 points, 95% CI 0.1 to 0.3; p = 0.006). However, there was no evidence of a difference between groups for upright time at 6 months (mean [SD] proportion of the day spent upright at 6 months: intervention group, 18.2 [9.8]; control group, 18.4 [10.2]; mean between-group difference -0.2, 95% CI -2.7 to 2.3; p = 0.87). Scores were higher in the intervention group compared to the control group across most secondary mobility outcomes, but there was no evidence of a difference between groups for most other secondary outcomes including self-reported balance confidence and quality of life. No adverse events were reported in the intervention group. Thirteen participants died while in the trial (intervention group: 9; control group: 4) due to unrelated causes, and there was no evidence of a difference between groups in fall rates (unadjusted incidence rate ratio 1.19, 95% CI 0.78 to 1.83; p = 0.43). Study limitations include 15%-19% loss to follow-up at 6 months on the co-primary outcomes, as anticipated; the number of secondary outcome measures in our trial, which may increase the risk of a type I error; and potential low statistical power to demonstrate significant between-group differences on important secondary patient-reported outcomes. CONCLUSIONS: In this study, we observed improved mobility in people with a wide range of health conditions making use of digitally enabled rehabilitation, whereas time spent upright was not impacted. TRIAL REGISTRATION: The trial was prospectively registered with the Australian New Zealand Clinical Trials Register; ACTRN12614000936628.

Invest in physical activity to protect and promote health: the 2020 WHO guidelines on physical activity and sedentary behaviour.

In this editorial we discuss the new 2020 World Health Organization guidelines on physical activity and sedentary behaviour and a series of related papers that are published simultaneously in IJBNPA. The new guidelines reaffirm that physical activity is a 'best buy' for public health and should be used to support governments to increase investment in policy and research to promote and ensure physical activity opportunities are available for everyone. New recommendations on sedentary behaviour and inclusion of specific guidelines for people living with disability and/or chronic disease and pregnant and postpartum women are major developments since 2010. We discuss research priorities, as well as policy implementation and the contribution to the sustainable development agenda. The new guidelines can catalyse the paradigm shifts needed to enable equitable opportunities to be physically active for everyone, everywhere, every day.

New global guidelines on sedentary behaviour and health for adults: broadening the behavioural targets.

BACKGROUND: In 2018, the World Health Organisation (WHO) commenced a program of work to update the 2010 Global Recommendations on Physical Activity for Health, for the first-time providing population-based guidelines on sedentary behaviour. This paper briefly summarizes and highlights the scientific evidence behind the new sedentary behaviour guidelines for all adults and discusses its strengths and limitations, including evidence gaps/research needs and potential implications for public health practice. METHODS: An overview of the scope and methods used to update the evidence is provided, along with quality assessment and grading methods for the eligible new systematic reviews. The literature search update was conducted for WHO by an external team and reviewers used the AMSTAR 2 (Assessment of Multiple Systematic Reviews) tool for critical appraisal of the systematic reviews under consideration for inclusion. The Grading of Recommendations Assessment, Development and Evaluation (GRADE) method was used to rate the certainty (i.e. very low to high) of the evidence. RESULTS: The updated systematic review identified 22 new reviews published from 2017 up to August 2019, 14 of which were incorporated into the final evidence profiles. Overall, there was moderate certainty evidence that higher amounts of sedentary behaviour increase the risk for all-cause, cardiovascular disease (CVD) and cancer mortality, as well as incidence of CVD, cancer, and type 2 diabetes. However, evidence was deemed insufficient at present to set quantified (time-based) recommendations for sedentary time. Moderate certainty evidence also showed that associations between sedentary behaviour and all-cause, CVD and cancer mortality vary by level of moderate-to-vigorous physical activity (MVPA), which underpinned additional guidance around MVPA in the context of high sedentary time. Finally, there was insufficient or low-certainty systematic review evidence on the type or domain of sedentary behaviour, or the frequency and/or duration of bouts or breaks in sedentary behaviour, to make specific recommendations for the health outcomes examined. CONCLUSIONS: The WHO 2020 guidelines are based on the latest evidence on sedentary behaviour and health, along with interactions between sedentary behaviour and MVPA, and support implementing public health programmes and policies aimed at increasing MVPA and limiting sedentary behaviour. Important evidence gaps and research opportunities are identified.

Five-year cost-effectiveness analysis of the European Fans in Training (EuroFIT) physical activity intervention for men versus no intervention.

OBJECTIVES: Increasing physical activity reduces the risk of chronic illness including Type 2 diabetes, cardiovascular disease and certain types of cancer. Lifestyle interventions can increase physical activity but few successfully engage men. This study aims to investigate the 5 year cost-effectiveness of EuroFIT, a program to improve physical activity tailored specifically for male football (soccer) fans compared to a no intervention comparison group. METHODS: We developed a Markov cohort model in which the impact of improving physical activity on five chronic health conditions (colorectal cancer, Type 2 diabetes, coronary heart disease, stroke and depression) and mortality was modelled. We estimated costs from a societal perspective and expressed benefits as quality adjusted life years (QALYs). We obtained data from a 4-country (England, Netherlands, Portugal and Norway) pragmatic randomised controlled trial evaluating EuroFIT, epidemiological and cohort studies, and meta-analyses. We performed deterministic and probabilistic sensitivity analyses to assess the impact of uncertainty in the model's parameter values on the cost-effectiveness results. We used Monte Carlo simulations to estimate uncertainty and presented this using cost-effectiveness acceptability curves (CEACs). We tested the robustness of the base case analysis using five scenario analyses. RESULTS: Average costs over 5 years per person receiving EuroFIT were €14,663 and per person receiving no intervention €14,598. Mean QALYs over 5 years were 4.05 per person for EuroFIT and 4.04 for no intervention. Thus, the average incremental cost per person receiving EuroFIT was €65 compared to no intervention, while the average QALY gain was 0.01. This resulted in an ICER of €5206 per QALY gained. CEACs show that the probability of EuroFIT being cost-effective compared to no intervention is 0.53, 0.56 and 0.58 at thresholds of €10,000, €22,000 and €34,000 per QALY gained, respectively. When using a time horizon of 10 years, the results suggest that EuroFIT is more effective and less expensive compared to (i.e. dominant over) no intervention with a probability of cost-effectiveness of 0.63 at a threshold of €22,000 per QALY gained. CONCLUSIONS: We conclude the EuroFIT intervention is not cost-effective compared to no intervention over a period of 5 years from a societal perspective, but is more effective and less expensive (i.e. dominant) after 10 years. We thus suggest that EuroFIT can potentially improve public health in a cost-effective manner in the long term.

Advancing the global physical activity agenda: recommendations for future research by the 2020 WHO physical activity and sedentary behavior guidelines development group.

BACKGROUND: In July, 2019, the World Health Organization (WHO) commenced work to update the 2010 Global Recommendations on Physical Activity for Health and established a Guideline Development Group (GDG) comprising expert public health scientists and practitioners to inform the drafting of the 2020 Guidelines on Physical Activity and Sedentary Behavior. The overall task of the GDG was to review the scientific evidence and provide expert advice to the WHO on the amount of physical activity and sedentary behavior associated with optimal health in children and adolescents, adults, older adults (> 64 years), and also specifically in pregnant and postpartum women and people living with chronic conditions or disabilities. METHODS: The GDG reviewed the available evidence specific to each sub-population using systematic protocols and in doing so, identified a number of gaps in the existing literature. These proposed research gaps were discussed and verified by expert consensus among the entire GDG. RESULTS: Evidence gaps across population sub-groups included a lack of information on: 1) the precise shape of the dose-response curve between physical activity and/or sedentary behavior and several of the health outcomes studied; 2) the health benefits of light-intensity physical activity and of breaking up sedentary time with light-intensity activity; 3) differences in the health effects of different types and domains of physical activity (leisure-time; occupational; transportation; household; education) and of sedentary behavior (occupational; screen time; television viewing); and 4) the joint association between physical activity and sedentary time with health outcomes across the life course. In addition, we acknowledge the need to conduct more population-based studies in low- and middle-income countries and in people living with disabilities and/or chronic disease, and to identify how various sociodemographic factors (age, sex, race/ethnicity, socioeconomic status) modify the health effects of physical activity, in order to address global health disparities. CONCLUSIONS: Although the 2020 WHO Guidelines for Physical Activity and Sedentary Behavior were informed by the most up-to-date research on the health effects of physical activity and sedentary time, there is still substantial work to be done in advancing the global physical activity agenda.

Heritability of objectively assessed and self-reported sedentary behavior.

Understanding the sources of the large individual differences in sedentary behavior is of great importance as this behavior is associated with pre-mature mortality and non-communicable diseases. Here, we report on the contribution of genetic and environmental factors to the variation in objectively assessed (accelerometer) sedentary behavior and self-reported sitting and their shared genetic basis. In addition, the overlap of the genetic risk factors influencing sedentary time and moderate-to-vigorous physical activity (MVPA) was estimated. A sample of 800 individuals (twins and their siblings) was equipped with an Actigraph accelerometer for 7 days and reported on their sitting time and time spent on MVPA on those days using the IPAQ-SF. Genetic factors explained 56% (CI: 44%, 65%) of the individual differences in objective sedentary behavior (Actigraph) and 26% (CI: 0%, 51%) of the individual differences in self-reported sedentary behavior (IPAQ-SF). A modest correlation (0.33) was found between these measures, which was for 45% accounted for by genetic influences. The genetic correlation was 0.49 reflecting a partly overlapping set of genes that influenced both measurements. A modest correlation (-0.27) between Actigraph-derived sedentary time and MVPA was found, which was 13% accounted for by genetic effects. The genetic correlation was -0.31, indicating that there are overlapping genetic variants that increase sedentary time and decrease MVPA or vice versa. To conclude, more than half of the individual differences in objective sedentary time could be attributed to genetic differences, while for self-reported sitting this was much lower. In addition, using objective measurements, this study confirms that sedentary time is not simply the inverse of MVPA. Future studies are needed to understand the pathways translating genomic variation into variation in these behaviors and how this knowledge might feed into the development of health promotion interventions.

World Health Organization 2020 guidelines on physical activity and sedentary behaviour.

OBJECTIVES: To describe new WHO 2020 guidelines on physical activity and sedentary behaviour. METHODS: The guidelines were developed in accordance with WHO protocols. An expert Guideline Development Group reviewed evidence to assess associations between physical activity and sedentary behaviour for an agreed set of health outcomes and population groups. The assessment used and systematically updated recent relevant systematic reviews; new primary reviews addressed additional health outcomes or subpopulations. RESULTS: The new guidelines address children, adolescents, adults, older adults and include new specific recommendations for pregnant and postpartum women and people living with chronic conditions or disability. All adults should undertake 150-300 min of moderate-intensity, or 75-150 min of vigorous-intensity physical activity, or some equivalent combination of moderate-intensity and vigorous-intensity aerobic physical activity, per week. Among children and adolescents, an average of 60 min/day of moderate-to-vigorous intensity aerobic physical activity across the week provides health benefits. The guidelines recommend regular muscle-strengthening activity for all age groups. Additionally, reducing sedentary behaviours is recommended across all age groups and abilities, although evidence was insufficient to quantify a sedentary behaviour threshold. CONCLUSION: These 2020 WHO guidelines update previous WHO recommendations released in 2010. They reaffirm messages that some physical activity is better than none, that more physical activity is better for optimal health outcomes and provide a new recommendation on reducing sedentary behaviours. These guidelines highlight the importance of regularly undertaking both aerobic and muscle strengthening activities and for the first time, there are specific recommendations for specific populations including for pregnant and postpartum women and people living with chronic conditions or disability. These guidelines should be used to inform national health policies aligned with the WHO Global Action Plan on Physical Activity 2018-2030 and to strengthen surveillance systems that track progress towards national and global targets.

Correction: The effect of a programme to improve men's sedentary time and physical activity: The European Fans in Training (EuroFIT) randomised controlled trial.

[This corrects the article DOI: 10.1371/journal.pmed.1002736.].

The effect of a programme to improve men's sedentary time and physical activity: The European Fans in Training (EuroFIT) randomised controlled trial.

BACKGROUND: Reducing sitting time as well as increasing physical activity in inactive people is beneficial for their health. This paper investigates the effectiveness of the European Fans in Training (EuroFIT) programme to improve physical activity and sedentary time in male football fans, delivered through the professional football setting. METHODS AND FINDINGS: A total of 1,113 men aged 30-65 with self-reported body mass index (BMI) ≥27 kg/m2 took part in a randomised controlled trial in 15 professional football clubs in England, the Netherlands, Norway, and Portugal. Recruitment was between September 19, 2015, and February 2, 2016. Participants consented to study procedures and provided usable activity monitor baseline data. They were randomised, stratified by club, to either the EuroFIT intervention or a 12-month waiting list comparison group. Follow-up measurement was post-programme and 12 months after baseline. EuroFIT is a 12-week, group-based programme delivered by coaches in football club stadia in 12 weekly 90-minute sessions. Weekly sessions aimed to improve physical activity, sedentary time, and diet and maintain changes long term. A pocket-worn device (SitFIT) allowed self-monitoring of sedentary time and daily steps, and a game-based app (MatchFIT) encouraged between-session social support. Primary outcome (objectively measured sedentary time and physical activity) measurements were obtained for 83% and 85% of intervention and comparison participants. Intention-to-treat analyses showed a baseline-adjusted mean difference in sedentary time at 12 months of -1.6 minutes/day (97.5% confidence interval [CI], -14.3-11.0; p = 0.77) and in step counts of 678 steps/day (97.5% CI, 309-1.048; p < 0.001) in favor of the intervention. There were significant improvements in diet, weight, well-being, self-esteem, vitality, and biomarkers of cardiometabolic health in favor of the intervention group, but not in quality of life. There was a 0.95 probability of EuroFIT being cost-effective compared with the comparison group if society is willing to pay £1.50 per extra step/day, a maximum probability of 0.61 if society is willing to pay £1,800 per minute less sedentary time/day, and 0.13 probability if society is willing to pay £30,000 per quality-adjusted life-year (QALY). It was not possible to blind participants to group allocation. Men attracted to the programme already had quite high levels of physical activity at baseline (8,372 steps/day), which may have limited room for improvement. Although participants came from across the socioeconomic spectrum, a majority were well educated and in paid work. There was an increase in recent injuries and in upper and lower joint pain scores post-programme. In addition, although the five-level EuroQoL questionnaire (EQ-5D-5L) is now the preferred measure for cost-effectiveness analyses across Europe, baseline scores were high (0.93), suggesting a ceiling effect for QALYs. CONCLUSION: Participation in EuroFIT led to improvements in physical activity, diet, body weight, and biomarkers of cardiometabolic health, but not in sedentary time at 12 months. Within-trial analysis suggests it is not cost-effective in the short term for QALYs due to a ceiling effect in quality of life. Nevertheless, decision-makers may consider the incremental cost for increase in steps worth the investment. TRIAL REGISTRATION: International Standard Randomised Controlled Trials, ISRCTN-81935608.

Effectiveness of interventions using self-monitoring to reduce sedentary behavior in adults: a systematic review and meta-analysis.

BACKGROUND: Sedentary behavior occurs largely subconsciously, and thus specific behavior change techniques are needed to increase conscious awareness of sedentary behavior. Chief amongst these behavior change techniques is self-monitoring of sedentary behavior. The aim of this systematic review and meta-analysis was to evaluate the short-term effectiveness of existing interventions using self-monitoring to reduce sedentary behavior in adults. METHODS: Four electronic databases (PubMed, Embase, Web of Science, and The Cochrane Library) and grey literature (Google Scholar and the International Clinical Trials Registry Platform) were searched to identify appropriate intervention studies. Only (cluster-)randomized controlled trials that 1) assessed the short-term effectiveness of an intervention aimed at the reduction of sedentary behavior, 2) used self-monitoring as a behavior change technique, and 3) were conducted in a sample of adults with an average age ≥ 18 years, were eligible for inclusion. Relevant data were extracted, and Hedge's g was used as the measure of effect sizes. Random effects models were performed to conduct the meta-analysis. RESULTS: Nineteen intervention studies with a total of 2800 participants met the inclusion criteria. Results of the meta-analyses showed that interventions using self-monitoring significantly reduced total sedentary time (Hedges g = 0,32; 95% CI = 0,14 - 0,50; p = 0,001) and occupational sedentary time (Hedge's g = 0,56; 95% CI = 0,07 - 0,90; p = 0,02) on the short term. Subgroup analyses showed that significant intervention effects were only found if objective self-monitoring tools were used (g = 0,40; 95% CI = 0,19 - 0,60; p < 0,001), and if the intervention only targeted sedentary behavior (g = 0,45; 95% CI = 0,15-0,75; p = 0,004). No significant intervention effects were found on the number of breaks in sedentary behavior. CONCLUSIONS: Despite the small sample sizes, and the large heterogeneity, results of the current meta-analysis suggested that interventions using self-monitoring as a behavior change technique have the potential to reduce sedentary behavior in adults. If future - preferably large-scale studies - can prove that the reductions in sedentary behavior are attributable to self-monitoring and can confirm the sustainability of this behavior change, multi-level interventions including self-monitoring may impact public health by reducing sedentary behavior.

The evolution of time use approaches for understanding activities of daily living in a public health context.

This Supplement aims to raise awareness and knowledge of how time use surveys may be applied to studying health behaviours such as physical activity, sedentary behaviour, and eating. This commentary provides an overview and discussion of the papers in this Supplement about time use and health research, and considers possible future directions for the field.

Prevalence and correlates of domain-specific sedentary time of adults in the Netherlands: findings from the 2006 Dutch time use survey.

BACKGROUND: Relatively little is known about how total sedentary time is accumulated in different domains and if correlates of sedentary time differ across domains. Time use surveys present a unique opportunity to study sedentary time in more detail. This study aimed to use the 2006 Dutch time use survey to 1) describe the (sedentary) time use of Dutch adults, and 2) explore socio-demographic and health-related correlates of total (non-occupational) and domain-specific sedentary time. METHODS: The Dutch time use survey randomly selected participants from a population-representative research sample of Dutch households. Participants reported daily activities on seven consecutive days using a time use diary and socio-demographic and health-related characteristics during telephone interviews. All reported activities were coded for activity domain (i.e. education; household; leisure; occupation; sleep; transport; voluntary work) and activity intensity (i.e. sedentary; light intensity physical activity; moderate-to-vigorous intensity physical activity). As occupational activities were not specified in sufficient detail, the intensity of these activities was unknown. We described the time spent in different domains and intensities, and assessed the socio-demographic and health-related correlates of high levels of total (non-occupational), household, leisure, and transport sedentary time using logistic regression analyses. RESULTS: The final dataset consisted of 1614 adult (18+) participants. On average, participants spent 8.0 h (61.1%) of their daily waking non-occupational time on sedentary activities. More than 87% of leisure time was spent sedentary. Men, participants aged 18-34 and 65+ years, full-time employed participants and obese participants had higher levels of total non-occupational sedentary time. The correlates of household, leisure and transport sedentary time differed by domain. CONCLUSIONS: This study reports high levels of total non-occupational sitting time of Dutch adults. The large proportion of sedentary leisure activities might indicate the potential of strategies aiming to reduce leisure sedentary time. The difference in correlates across sedentary behaviour domains demonstrates the importance of targeting these domains differently in interventions and policies.

Physical workload and obesity have a synergistic effect on work ability among construction workers.

PURPOSE: Obesity and high physical workload are both associated with poor work ability, but the interaction between obesity and high physical workload on work ability is not yet fully understood. Obesity and high physical workload may share a common mechanical pathway, possibly leading to a synergistic negative effect on work ability. The purpose of this study was to investigate the effect of obesity on work ability in workers with high versus low physical work load. METHODS: A longitudinal study was conducted among 36,435 Dutch construction workers who participated in at least two periodic medical examinations during the years 2008-2015. Logistic regression analyses were used to investigate the effect of manual material handling and strenuous work postures in sports on the association between obesity and work ability. Work ability was measured using the self-reported Work Ability Index consisting of seven dimensions. Confounding effects were tested for age, educational level, smoking, vigorous physical activity, psychosocial work demands, and working hours. Additive interaction between obesity and physical workload on work ability was tested using the relative excess risk due to interaction (RERI). RESULTS: Construction workers with overweight (OR = 1.09; 95% CI 1.02-1.16) or obesity (OR = 1.27; 95% CI 1.17-1.38) had an increased risk of poor/moderate work ability. Exposure to manual material handling (OR = 1.58; 95% CI 1.49-1.68) or strenuous work postures (OR = 1.80; 95% CI 1.70-1.90) also increased the risk of poor/moderate work ability. The effect of the combination of obesity with high physical workload was greater than the sum of the individual effects (strenuous work postures: RERI = 0.39; 95% CI 0.10-0.67; manual material handling: RERI = 0.26; 95% CI 0.02-0.51). CONCLUSIONS: Obesity and high physical workload were associated with poor work ability and had a synergistic, negative effect on work ability. Interventions that prevent obesity and high physical workload might have a beneficial effect on work ability.

The Dynamic Work study: study protocol of a cluster randomized controlled trial of an occupational health intervention aimed at reducing sitting time in office workers.

BACKGROUND: Large volumes of sitting time have been associated with multiple health risks. To reduce sitting time of office workers working for a Dutch insurance company, the Dynamic Work intervention was developed. The primary objective of this paper is to describe the study protocol of the Dynamic Work study, which aims to evaluate if this multicomponent intervention is (cost-)effective in reducing total sitting time on the short-term (≈3 months) and longer-term (≈12 months) compared to usual practice. METHODS/DESIGN: This two-arm cluster randomized controlled trial will recruit 250 desk-based office workers working at different locations of an insurance company in the Netherlands. After baseline measurements, departments will be matched in pairs and each pair will be randomly assigned to the control or intervention condition. The multicomponent intervention contains organizational (i.e. face to face session with the head of the department), work environmental (i.e. the introduction of sit-stand desks and cycling workstations), and individual elements (i.e. counselling and activity/sitting tracker with a self-help program booklet). The counselling involves two group intervention sessions and four on-site department consultations with an occupational physiotherapist. Sitting time (primary outcome), upright time and step counts will be assessed objectively using the activPAL activity monitor at baseline, short-term (approximately 3 months) and longer-term (12 months). Other outcomes will include: self-reported lifestyle behaviours, anthropometrics, work-related outcomes (i.e. absenteeism, presenteeism, work performance, work-related stress), health-related outcomes (i.e. vitality, musculoskeletal symptoms, need for recovery, quality of life), and costs from both company and societal perspective. The study will include economic and process evaluations. DISCUSSION: This study will assess the longer-term (cost-) effectiveness of a multicomponent workplace intervention aimed at reducing sitting time in comparison with usual practice. Furthermore, the process evaluation will provide insights in factors associated with successful implementation of this intervention. TRIAL REGISTRATION: ClinicalTrials.gov NCT03115645 ; Registered 13 April 2017. Retrospectively registered.