Interventions promoting active transport to school in children: A systematic review and meta-analysis

The systematic review investigated the effectiveness of active travel (AT) interventions on physical activity and fitness in primary school children. The review assessed intervention effectiveness, design, complexity, and study quality. Searches were conducted in five databases on 30/08/2018. Studies with an AT intervention compared to an inactive control, in 4 to 11 year olds, measuring AT or fitness outcomes were included. Two-stage screening identified relevant studies. Relevant data were extracted using Cochrane Extraction Form, Quality Assessment Tool for Quantitative Studies, Active Living by Design model, and intervention Complexity Assessment Tool for Systematic Reviews. Meta-analysis and Cohen's D effect size assessed effectiveness. Seventeen eligible studies were included. Effectiveness assessment found a statistically significant standardised mean difference (SMD) in AT outcomes in favour of the intervention (continuous AT - SMD 0.78 (CI 0.11–1.46); frequency AT - SMD 1.87 (CI 0.88–2.86)). Cohen's D calculation concurred with this finding. Fifteen studies had SMD favouring the intervention – two studies had SMD favouring the control. Sixteen studies received a weak quality rating - one study rated moderate. Active travel shows promise in increasing physical activity in primary school children. The review found walking school buses and educational strategies most effective for increasing relevant outcomes, although overall study quality was weak. Effect size did not associate with the complexity of an intervention, therefore supporting efforts to promote active travel through interventions may be easier to scale. Further intervention studies of greater methodological quality are necessary to confirm these findings due to the limited evidence available

Individual and environmental correlates of objectively measured sedentary time in Dutch and Belgian adults

As the detrimental health effects of sedentary behaviour are well established, insight into the individual and environmental factors that influence adults' sedentary behaviour is needed. Most studies to date rely on self-reported measures of sedentary time. Therefore, the aim of the current study was to examine individual and environmental correlates of objectively measured sedentary time in Dutch and Belgian adults. Between March and August 2014, Belgian (n = 133) and Dutch (n = 223) adults, recruited as sub-sample of the SPOTLIGHT survey, wore an ActiGraph accelerometer to provide objectively measured sedentary and moderate to vigorous physical activity time. Participants completed a questionnaire assessing sociodemographic (country of residence, age, gender and educational level), lifestyle (sleep, smoking, sugar-containing beverage consumption, alcohol intake), health (body mass index, self-rated health), work (employment status and type of work), happiness, physical environmental (owning a car, number of screens, socioeconomic status and residential density) and social environmental factors (social network, social cohesion). Univariate and multivariable regression analyses showed that Belgian participants had a lower odds of being sedentary for at least 9 hours per day compared to Dutch participants. Women, older participants and those meeting the WHO recommendation for physical activity were also less likely to sit for 9 hours or more per day. Participants doing (heavy) manual work or being in education, homemaker, unemployed had lower odds of being sedentary for at least 9 hours per day compared to participants with a sitting job. Those with a higher self-reported social network also had lower odds for sedentary time. No associations between physical and other social environmental characteristics and sedentary time were found. Our findings add to the growing evidence of factors associated with prolonged sedentary time in adults. These findings may be used to inform the development of strategies and interventions aimed at reducing sedentary time, and to identify high risk groups

The Dutch Obesity Intervention in Teenagers (DOiT) cluster controlled implementation trial: intervention effects and mediators and moderators of adiposity and energy balance-related behaviours

Background: The Dutch Obesity Intervention in Teenagers (DOiT) programme is an evidence-based obesity prevention programme tailored to adolescents attending the first two years of prevocational education in the Netherlands. The initial programme showed promising results during an effectiveness trial. The programme was adapted and prepared for nationwide dissemination. To gain more insight into the process of translating evidence-based approaches into ‘real world’ (i.e., ‘natural’) conditions, our research aims were to evaluate the impact of the DOiT-implementation programme on adolescents’ adiposity and energy balance-related behaviours during natural dissemination and to explore the mediating and moderating factors underlying the DOiT intervention effects.Methods: We conducted a cluster-controlled implementation trial with 20 voluntary intervention schools (n=1002 adolescents) and 9 comparable control schools (n = 484 adolescents). We measured adolescents’ body height and weight, skinfold thicknesses, and waist circumference. We assessed adolescents’ dietary and physical activity behaviours by means of self-report. Data were collected at baseline and at 20-months follow-up. We used multivariable multilevel linear or logistic regression analyses to evaluate the intervention effects and to test the hypothesised behavioural mediating factors. We checked for potential effect modification by gender, ethnicity and education level.Results: We found no significant intervention effects on any of the adiposity measures or behavioural outcomes. Furthermore, we found no mediating effects by any of the hypothesised behavioural mediators. Stratified analyses for gender showed that the intervention was effective in reducing sugar-containing beverage consumption in girls (B = -188.2 ml/day; 95% CI = -344.0; -32.3). In boys, we found a significant positive intervention effect on breakfast frequency (B = 0.29 days/week; 95% CI = 0.01; 0.58). Stratified analyses for education level showed an adverse intervention effect (B = 0.09; 95% CI = 0.02; 0.16) on BMI z-scores for adolescents attending the vocational education track.Conclusions: Although not successful in changing adolescents’ adiposity, the DOiT-implementation programme had some beneficial effects on specific obesity-related behaviours in subgroups. This study underlines the difficulty of translating intervention effectiveness in controlled settings to real world contexts. Adaptations to the implementation strategy are needed in order to promote implementation as intended by the teachers

Objectively measured physical environmental neighbourhood factors are not associated with accelerometer-determined total sedentary time in adults

Background: The physical neighbourhood environment may influence adults' sedentary behaviour. Yet, most studies examining the association between the physical neighbourhood environment and sedentary behaviour rely on self-reported data of either the physical neighbourhood environment and/or sedentary behaviour. The aim of this study was to investigate the associations between objectively measured physical environmental neighbourhood factors and accelerometer-determined total sedentary time in adults. Methods: In total, 219 Dutch and 128 Belgian adults (mean age +/- SD: 55.8 +/- 15.4 years) were recruited between March and August 2014 as part of the European SPOTLIGHT project. Physical environmental neighbourhood factors, grouped into eight domains, i.e. walking, cycling, public transport, aesthetics, land use mix, grocery stores, food outlets and recreational facilities, were assessed using the SPOTLIGHT Virtual Audit Tool. Sedentary time was collected using ActiGraph GT3X+ accelerometers. General linear mixed models were conducted to examine associations between physical environmental neighbourhood factors and total sedentary time. Results: Participants were sedentary, on average, for 542.9 min/day (SD: 84.3), or 9.1 h/day. None of the examined physical environmental neighbourhood factors were significantly related to total sedentary time. Conclusions: Our findings do not support associations of objectively measured physical environmental neighbourhood factors with adults' objectively sedentary time in Dutch and Belgian adults. More research on sedentary behaviours in settings such as the home and work setting is needed to examine the influence of more specific physical environmental factors on these context-specific sedentary behaviours

Implementing Exercise = Medicine in routine clinical care; needs for an online tool and key decisions for implementation of Exercise = Medicine within two Dutch academic hospitals

Background There is much evidence to implement physical activity interventions for medical reasons in healthcare settings. However, the prescription of physical activity as a treatment, referring to as 'Exercise is Medicine' (E = M) is currently mostly absent in routine hospital care in The Netherlands. To support E = M prescription by clinicians in hospitals, this study aimed: (1) to develop an E = M-tool for physical activity advice and referrals to facilitate the E = M prescription in hospital settings; and (2) to provide an E = M decision guide on key decisions for implementation to prepare for E = M prescription in hospital care. Methods A mixed method design was used employing a questionnaire and face-to-face interviews with clinicians, lifestyle coaches and hospital managers, a patient panel and stakeholders to assess the needs regarding an E = M-tool and key decisions for implementation of E = M. Based on the needs assessment, a digital E = M-tool was developed. The key decisions informed the development of an E = M decision guide. Results An online supportive tool for E = M was developed for two academic hospitals. Based on the needs assessment, linked to the different patients' electronic medical records and tailored to the two local settings (University Medical Center Groningen, Amsterdam University Medical Centers). The E = M-tool existed of a tool algorithm, including patient characteristics assessed with a digital questionnaire (age, gender, PA, BMI, medical diagnosis, motivation to change physical activity and preference to discuss physical activity with their doctor) set against norm values. The digital E = M-tool provided an individual E = M-prescription for patients and referral options to local PA interventions in- and outside the hospital. An E = M decision guide was developed to support the implementation of E = M prescription in hospital care. Conclusions This study provided insight into E = M-tool development and the E = M decision-making to support E = M prescription and facilitate tailoring towards local E = M treatment options, using strong stakeholder participation. Outcomes may serve as an example for other decision support guides and interventions aimed at E = M implementation.</p

Implementing Exercise = Medicine in routine clinical care; needs for an online tool and key decisions for implementation of Exercise = Medicine within two Dutch academic hospitals

BACKGROUND: There is much evidence to implement physical activity interventions for medical reasons in healthcare settings. However, the prescription of physical activity as a treatment, referring to as 'Exercise is Medicine' (E = M) is currently mostly absent in routine hospital care in The Netherlands. To support E = M prescription by clinicians in hospitals, this study aimed: (1) to develop an E = M-tool for physical activity advice and referrals to facilitate the E = M prescription in hospital settings; and (2) to provide an E = M decision guide on key decisions for implementation to prepare for E = M prescription in hospital care. METHODS: A mixed method design was used employing a questionnaire and face-to-face interviews with clinicians, lifestyle coaches and hospital managers, a patient panel and stakeholders to assess the needs regarding an E = M-tool and key decisions for implementation of E = M. Based on the needs assessment, a digital E = M-tool was developed. The key decisions informed the development of an E = M decision guide. RESULTS: An online supportive tool for E = M was developed for two academic hospitals. Based on the needs assessment, linked to the different patients' electronic medical records and tailored to the two local settings (University Medical Center Groningen, Amsterdam University Medical Centers). The E = M-tool existed of a tool algorithm, including patient characteristics assessed with a digital questionnaire (age, gender, PA, BMI, medical diagnosis, motivation to change physical activity and preference to discuss physical activity with their doctor) set against norm values. The digital E = M-tool provided an individual E = M-prescription for patients and referral options to local PA interventions in- and outside the hospital. An E = M decision guide was developed to support the implementation of E = M prescription in hospital care. CONCLUSIONS: This study provided insight into E = M-tool development and the E = M decision-making to support E = M prescription and facilitate tailoring towards local E = M treatment options, using strong stakeholder participation. Outcomes may serve as an example for other decision support guides and interventions aimed at E = M implementation

What Do Secondary Schools Need to Create Healthier Canteens? The Development of an Implementation Plan

Introduction: The Netherlands Nutrition Centre developed guidelines to improve the availability and accessibility of healthier food products in Dutch canteens. This paper describes the development of an implementation plan to facilitate implementation of Guidelines for Healthier Canteens in Dutch secondary schools.Materials and Methods: In cooperation with stakeholders (i.e., school/caterer managers/employees, school canteen advisors, researchers) and based on theory, we developed an implementation plan in three steps. First, we identified factors that impede/facilitate stakeholders to create a healthier school canteen during 14 interviews. Second, 25 experts discussed and prioritized these identified factors in an expert meeting. Third, we translated these factors into tools to be included in the implementation plan, by making use of behavior change taxonomies and evidence-based implementation strategies.Results: The plan aims to support stakeholders in implementing healthier school canteens and consists of five tools: (1) tailored advice based on an online questionnaire to assess schools' and stakeholders' context and the Canteen Scan (i.e., an online tool to assess the availability and accessibility of food/drink products); (2) communication materials with information and examples; (3) online community for support by sharing experiences/questions; (4) digital newsletter as reminder/support; (5) fact sheet with students' needs/wishes to tailor the canteen.Discussion: This study illustrates how collaboration between science, policy and practice resulted in a tailored implementation plan aimed to support schools to adhere to school canteen policy. This development serves as a good example for researchers, health promotion policymakers, and practitioners how to create an implementation plan that fits the needs of stakeholders

Facilitators and barriers for the implementation of exercise are medicine in routine clinical care in Dutch university medical centres:a mixed methodology study on clinicians' perceptions

Objectives Despite the many proven advantages of a physically active lifestyle in patient populations, prescription of exercise is currently not widely implemented in routine clinical practice. The aims of this study were twofold: (1) to assess perceptions of clinicians on the current practice of exercise is medicine (E=M) prescription in two Dutch university medical centres and (2) to determine their perceived barriers and facilitators for the implementation of E=M in routine clinical care in Dutch university medical centres. Design A mixed methodologies study, using both online questionnaires and semi-structured interviews. Setting Dutch university medical centres. Participants Clinicians working within the departments of medical oncology, orthopaedics and rehabilitation medicine of two university medical centres. Results Forty-five clinicians (response rate of 51%) completed the questionnaire, and 19 clinicians were interviewed. The results showed that even though clinicians had a positive attitude towards prescribing E=M, only a few reported to regularly prescribe E=M to their patients. The 52 identified facilitators and barriers for implementation of E=M were categorised into four main themes: (1) beliefs toward the implementation of E=M (eg, clinicians knowledge and skills, and social support), (2) factors related to the patient perspective (eg, patient priorities or motivation), (3) factors related to the referral options (eg, knowledge of and trust in local referral options) and (4) practical considerations when implementing E=M (eg, time constraints). Conclusions Our study showed that even though many clinicians have a positive attitude toward an active lifestyle, many are not prescribing E=M on a regular basis. In order for clinicians to effectively implement E=M, strategies should focus on increasing clinicians E=M referral skills, improving clinicians knowledge of E=M referral options and develop a support system to ensure that E=M is high on the priority list of clinicians

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

Funding This project has received funding from the European Union’s Seventh Framework Program for research, technological development, and demonstration under grant agreement number 602170. The Health Services Research Unit, University of Aberdeen, receives core funding from the Chief Scientist Office of the Scottish Government Health Directorates. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Acknowledgements We are grateful to participants who took part in the research, coaches and club managers at fifteen football clubs and UEFA’s Football and Social Responsibility department for supporting the proposal at bidding stage. Ciaran Clissman of Pintail Ltd managed the project and provided invaluable editorial input into the funding application and delivery of the program. Prof Nanette Mutrie was substantially involved in the development of the EuroFIT program. Dr Lisa Macauley administered the UK data collection in the UK and Alan Pollok supported some UK data collection. Dr Mattias Rost and Prof Mathew Chalmers were substantially involved in the development of MatchFIT and Drs Douglas Maxwell and Nikos Mourselas of PAL Technologies in the technical development of the SitFIT. Views and opinions expressed are those of the authors and do not necessarily reflect those of the European Union.Peer reviewedPublisher PD