Interventions to prevent obesity in children aged 5 to 11 years old.

BACKGROUND: Prevention of obesity in children is an international public health priority given the prevalence of the condition (and its significant impact on health, development and well-being). Interventions that aim to prevent obesity involve behavioural change strategies that promote healthy eating or 'activity' levels (physical activity, sedentary behaviour and/or sleep) or both, and work by reducing energy intake and/or increasing energy expenditure, respectively. There is uncertainty over which approaches are more effective and numerous new studies have been published over the last five years, since the previous version of this Cochrane review. OBJECTIVES: To assess the effects of interventions that aim to prevent obesity in children by modifying dietary intake or 'activity' levels, or a combination of both, on changes in BMI, zBMI score and serious adverse events. SEARCH METHODS: We used standard, extensive Cochrane search methods. The latest search date was February 2023. SELECTION CRITERIA: Randomised controlled trials in children (mean age 5 years and above but less than 12 years), comparing diet or 'activity' interventions (or both) to prevent obesity with no intervention, usual care, or with another eligible intervention, in any setting. Studies had to measure outcomes at a minimum of 12 weeks post baseline. We excluded interventions designed primarily to improve sporting performance. DATA COLLECTION AND ANALYSIS: We used standard Cochrane methods. Our outcomes were body mass index (BMI), zBMI score and serious adverse events, assessed at short- (12 weeks to < 9 months from baseline), medium- (9 months to < 15 months) and long-term (≥ 15 months) follow-up. We used GRADE to assess the certainty of the evidence for each outcome. MAIN RESULTS: This review includes 172 studies (189,707 participants); 149 studies (160,267 participants) were included in meta-analyses. One hundred forty-six studies were based in high-income countries. The main setting for intervention delivery was schools (111 studies), followed by the community (15 studies), the home (eight studies) and a clinical setting (seven studies); one intervention was conducted by telehealth and 31 studies were conducted in more than one setting. Eighty-six interventions were implemented for less than nine months; the shortest was conducted over one visit and the longest over four years. Non-industry funding was declared by 132 studies; 24 studies were funded in part or wholly by industry. Dietary interventions versus control Dietary interventions, compared with control, may have little to no effect on BMI at short-term follow-up (mean difference (MD) 0, 95% confidence interval (CI) -0.10 to 0.10; 5 studies, 2107 participants; low-certainty evidence) and at medium-term follow-up (MD -0.01, 95% CI -0.15 to 0.12; 9 studies, 6815 participants; low-certainty evidence) or zBMI at long-term follow-up (MD -0.05, 95% CI -0.10 to 0.01; 7 studies, 5285 participants; low-certainty evidence). Dietary interventions, compared with control, probably have little to no effect on BMI at long-term follow-up (MD -0.17, 95% CI -0.48 to 0.13; 2 studies, 945 participants; moderate-certainty evidence) and zBMI at short- or medium-term follow-up (MD -0.06, 95% CI -0.13 to 0.01; 8 studies, 3695 participants; MD -0.04, 95% CI -0.10 to 0.02; 9 studies, 7048 participants; moderate-certainty evidence). Five studies (1913 participants; very low-certainty evidence) reported data on serious adverse events: one reported serious adverse events (e.g. allergy, behavioural problems and abdominal discomfort) that may have occurred as a result of the intervention; four reported no effect. Activity interventions versus control Activity interventions, compared with control, may have little to no effect on BMI and zBMI at short-term or long-term follow-up (BMI short-term: MD -0.02, 95% CI -0.17 to 0.13; 14 studies, 4069 participants; zBMI short-term: MD -0.02, 95% CI -0.07 to 0.02; 6 studies, 3580 participants; low-certainty evidence; BMI long-term: MD -0.07, 95% CI -0.24 to 0.10; 8 studies, 8302 participants; zBMI long-term: MD -0.02, 95% CI -0.09 to 0.04; 6 studies, 6940 participants; low-certainty evidence). Activity interventions likely result in a slight reduction of BMI and zBMI at medium-term follow-up (BMI: MD -0.11, 95% CI -0.18 to -0.05; 16 studies, 21,286 participants; zBMI: MD -0.05, 95% CI -0.09 to -0.02; 13 studies, 20,600 participants; moderate-certainty evidence). Eleven studies (21,278 participants; low-certainty evidence) reported data on serious adverse events; one study reported two minor ankle sprains and one study reported the incident rate of adverse events (e.g. musculoskeletal injuries) that may have occurred as a result of the intervention; nine studies reported no effect. Dietary and activity interventions versus control Dietary and activity interventions, compared with control, may result in a slight reduction in BMI and zBMI at short-term follow-up (BMI: MD -0.11, 95% CI -0.21 to -0.01; 27 studies, 16,066 participants; zBMI: MD -0.03, 95% CI -0.06 to 0.00; 26 studies, 12,784 participants; low-certainty evidence) and likely result in a reduction of BMI and zBMI at medium-term follow-up (BMI: MD -0.11, 95% CI -0.21 to 0.00; 21 studies, 17,547 participants; zBMI: MD -0.05, 95% CI -0.07 to -0.02; 24 studies, 20,998 participants; moderate-certainty evidence). Dietary and activity interventions compared with control may result in little to no difference in BMI and zBMI at long-term follow-up (BMI: MD 0.03, 95% CI -0.11 to 0.16; 16 studies, 22,098 participants; zBMI: MD -0.02, 95% CI -0.06 to 0.01; 22 studies, 23,594 participants; low-certainty evidence). Nineteen studies (27,882 participants; low-certainty evidence) reported data on serious adverse events: four studies reported occurrence of serious adverse events (e.g. injuries, low levels of extreme dieting behaviour); 15 studies reported no effect. Heterogeneity was apparent in the results for all outcomes at the three follow-up times, which could not be explained by the main setting of the interventions (school, home, school and home, other), country income status (high-income versus non-high-income), participants' socioeconomic status (low versus mixed) and duration of the intervention. Most studies excluded children with a mental or physical disability. AUTHORS' CONCLUSIONS: The body of evidence in this review demonstrates that a range of school-based 'activity' interventions, alone or in combination with dietary interventions, may have a modest beneficial effect on obesity in childhood at short- and medium-term, but not at long-term follow-up. Dietary interventions alone may result in little to no difference. Limited evidence of low quality was identified on the effect of dietary and/or activity interventions on severe adverse events and health inequalities; exploratory analyses of these data suggest no meaningful impact. We identified a dearth of evidence for home and community-based settings (e.g. delivered through local youth groups), for children living with disabilities and indicators of health inequities.

Interventions to prevent obesity in children aged 12 to 18 years old.

BACKGROUND: Prevention of obesity in adolescents is an international public health priority. The prevalence of overweight and obesity is over 25% in North and South America, Australia, most of Europe, and the Gulf region. Interventions that aim to prevent obesity involve strategies that promote healthy diets or 'activity' levels (physical activity, sedentary behaviour and/or sleep) or both, and work by reducing energy intake and/or increasing energy expenditure, respectively. There is uncertainty over which approaches are more effective, and numerous new studies have been published over the last five years since the previous version of this Cochrane Review. OBJECTIVES: To assess the effects of interventions that aim to prevent obesity in adolescents by modifying dietary intake or 'activity' levels, or a combination of both, on changes in BMI, zBMI score and serious adverse events. SEARCH METHODS: We used standard, extensive Cochrane search methods. The latest search date was February 2023. SELECTION CRITERIA: Randomised controlled trials in adolescents (mean age 12 years and above but less than 19 years), comparing diet or 'activity' interventions (or both) to prevent obesity with no intervention, usual care, or with another eligible intervention, in any setting. Studies had to measure outcomes at a minimum of 12 weeks post baseline. We excluded interventions designed primarily to improve sporting performance. DATA COLLECTION AND ANALYSIS: We used standard Cochrane methods. Our outcomes were BMI, zBMI score and serious adverse events, assessed at short- (12 weeks to < 9 months from baseline), medium- (9 months to < 15 months) and long-term (≥ 15 months) follow-up. We used GRADE to assess the certainty of the evidence for each outcome. MAIN RESULTS: This review includes 74 studies (83,407 participants); 54 studies (46,358 participants) were included in meta-analyses. Sixty studies were based in high-income countries. The main setting for intervention delivery was schools (57 studies), followed by home (nine studies), the community (five studies) and a primary care setting (three studies). Fifty-one interventions were implemented for less than nine months; the shortest was conducted over one visit and the longest over 28 months. Sixty-two studies declared non-industry funding; five were funded in part by industry. Dietary interventions versus control The evidence is very uncertain about the effects of dietary interventions on body mass index (BMI) at short-term follow-up (mean difference (MD) -0.18, 95% confidence interval (CI) -0.41 to 0.06; 3 studies, 605 participants), medium-term follow-up (MD -0.65, 95% CI -1.18 to -0.11; 3 studies, 900 participants), and standardised BMI (zBMI) at long-term follow-up (MD -0.14, 95% CI -0.38 to 0.10; 2 studies, 1089 participants); all very low-certainty evidence. Compared with control, dietary interventions may have little to no effect on BMI at long-term follow-up (MD -0.30, 95% CI -1.67 to 1.07; 1 study, 44 participants); zBMI at short-term (MD -0.06, 95% CI -0.12 to 0.01; 5 studies, 3154 participants); and zBMI at medium-term (MD 0.02, 95% CI -0.17 to 0.21; 1 study, 112 participants) follow-up; all low-certainty evidence. Dietary interventions may have little to no effect on serious adverse events (two studies, 377 participants; low-certainty evidence). Activity interventions versus control Compared with control, activity interventions do not reduce BMI at short-term follow-up (MD -0.64, 95% CI -1.86 to 0.58; 6 studies, 1780 participants; low-certainty evidence) and probably do not reduce zBMI at medium- (MD 0, 95% CI -0.04 to 0.05; 6 studies, 5335 participants) or long-term (MD -0.05, 95% CI -0.12 to 0.02; 1 study, 985 participants) follow-up; both moderate-certainty evidence. Activity interventions do not reduce zBMI at short-term follow-up (MD 0.02, 95% CI -0.01 to 0.05; 7 studies, 4718 participants; high-certainty evidence), but may reduce BMI slightly at medium-term (MD -0.32, 95% CI -0.53 to -0.11; 3 studies, 2143 participants) and long-term (MD -0.28, 95% CI -0.51 to -0.05; 1 study, 985 participants) follow-up; both low-certainty evidence. Seven studies (5428 participants; low-certainty evidence) reported data on serious adverse events: two reported injuries relating to the exercise component of the intervention and five reported no effect of intervention on reported serious adverse events. Dietary and activity interventions versus control Dietary and activity interventions, compared with control, do not reduce BMI at short-term follow-up (MD 0.03, 95% CI -0.07 to 0.13; 11 studies, 3429 participants; high-certainty evidence), and probably do not reduce BMI at medium-term (MD 0.01, 95% CI -0.09 to 0.11; 8 studies, 5612 participants; moderate-certainty evidence) or long-term (MD 0.06, 95% CI -0.04 to 0.16; 6 studies, 8736 participants; moderate-certainty evidence) follow-up. They may have little to no effect on zBMI in the short term, but the evidence is very uncertain (MD -0.09, 95% CI -0.2 to 0.02; 3 studies, 515 participants; very low-certainty evidence), and they may not reduce zBMI at medium-term (MD -0.05, 95% CI -0.1 to 0.01; 6 studies, 3511 participants; low-certainty evidence) or long-term (MD -0.02, 95% CI -0.05 to 0.01; 7 studies, 8430 participants; low-certainty evidence) follow-up. Four studies (2394 participants) reported data on serious adverse events (very low-certainty evidence): one reported an increase in weight concern in a few adolescents and three reported no effect. AUTHORS' CONCLUSIONS: The evidence demonstrates that dietary interventions may have little to no effect on obesity in adolescents. There is low-certainty evidence that activity interventions may have a small beneficial effect on BMI at medium- and long-term follow-up. Diet plus activity interventions may result in little to no difference. Importantly, this updated review also suggests that interventions to prevent obesity in this age group may result in little to no difference in serious adverse effects. Limitations of the evidence include inconsistent results across studies, lack of methodological rigour in some studies and small sample sizes. Further research is justified to investigate the effects of diet and activity interventions to prevent childhood obesity in community settings, and in young people with disabilities, since very few ongoing studies are likely to address these. Further randomised trials to address the remaining uncertainty about the effects of diet, activity interventions, or both, to prevent childhood obesity in schools (ideally with zBMI as the measured outcome) would need to have larger samples.

Research outcomes informing the selection of public health interventions and strategies to implement them: A cross-sectional survey of Australian policy-maker and practitioner preferences.

BACKGROUND: A key role of public health policy-makers and practitioners is to ensure beneficial interventions are implemented effectively enough to yield improvements in public health. The use of evidence to guide public health decision-making to achieve this is recommended. However, few studies have examined the relative value, as reported by policy-makers and practitioners, of different broad research outcomes (that is, measures of cost, acceptability, and effectiveness). To guide the conduct of research and better inform public health policy and practice, this study aimed at describing the research outcomes that Australian policy-makers and practitioners consider important for their decision-making when selecting: (a) public health interventions; (b) strategies to support their implementation; and (c) to assess the differences in research outcome preferences between policy-makers and practitioners. METHOD: An online value-weighting survey was conducted with Australian public health policy-makers and practitioners working in the field of non-communicable disease prevention. Participants were presented with a list of research outcomes and were asked to select up to five they considered most critical to their decision-making. They then allocated 100 points across these - allocating more points to outcomes perceived as more important. Outcome lists were derived from a review and consolidation of evaluation and outcome frameworks in the fields of public health knowledge translation and implementation. We used descriptive statistics to report relative preferences overall and for policy-makers and practitioners separately. RESULTS: Of the 186 participants; 90 primarily identified as policy-makers and 96 as public health prevention practitioners. Overall, research outcomes of effectiveness, equity, feasibility, and sustainability were identified as the four most important outcomes when considering either interventions or strategies to implement them. Scores were similar for most outcomes between policy-makers and practitioners. CONCLUSION: For Australian policy-makers and practitioners working in the field of non-communicable disease prevention, outcomes related to effectiveness, equity, feasibility, and sustainability appear particularly important to their decisions about the interventions they select and the strategies they employ to implement them. The findings suggest researchers should seek to meet these information needs and prioritize the inclusion of such outcomes in their research and dissemination activities. The extent to which these outcomes are critical to informing the decision of policy-makers and practitioners working in other jurisdictions or contexts warrants further investigation.

Assessing the scalability of evidence-based healthy eating and physical activity interventions in early childhood education and care: A cross-sectional study of end-user perspectives.

OBJECTIVES: To describe early childhood education and care (ECEC) services: i) perceptions regarding the scalability of healthy eating and physical activity interventions; and ii) associations between scalability and service characteristics. METHODS: A cross-sectional survey was conducted with a randomly selected sample of ECEC services across Australia. The scalability of 12 healthy eating and physical activity interventions was assessed using items based on the Intervention Scalability Assessment Tool. Higher scores represented higher perceived scalability. RESULTS: From 453 participants, the highest scoring healthy eating and physical activity interventions were 'providing healthy eating education and activities for children' (M43.05) (out of 50) and 'providing sufficient opportunities for child physical activity' (M41.43). The lowest scoring was 'providing families with lunchbox guidelines' (M38.99) and 'engaging families in activities to increase child physical activity' (M38.36). Services located in rural areas, compared to urban areas, scored the overall scalability of both healthy eating and physical activity interventions significantly lower. CONCLUSIONS: Perceptions regarding the scalability of healthy eating and physical activity interventions in the ECEC setting vary according to service characteristics. IMPLICATIONS FOR PUBLIC HEALTH: Findings identify where government investment and implementation efforts may be prioritised to facilitate scale-up. An investigation into the barriers and support required for lower-scoring interventions is warranted.

The Effectiveness of Strategies to Improve User Engagement With Digital Health Interventions Targeting Nutrition, Physical Activity, and Overweight and Obesity: Systematic Review and Meta-Analysis.

BACKGROUND: Digital health interventions (DHIs) are effective in improving poor nutrition, physical inactivity, overweight and obesity. There is evidence suggesting that the impact of DHIs may be enhanced by improving user engagement. However, little is known about the overall effectiveness of strategies on engagement with DHIs. OBJECTIVE: This study aims to assess the overall effectiveness of strategies to improve engagement with DHIs targeting nutrition, physical activity, and overweight or obesity and explore associations between strategies and engagement outcomes. The secondary aim was to explore the impact of these strategies on health risk outcomes. METHODS: The MEDLINE, Embase, PsycINFO, CINAHL, CENTRAL, Scopus, and Academic Source Complete databases were searched up to July 24, 2023. Eligible studies were randomized controlled trials that evaluated strategies to improve engagement with DHIs and reported on outcomes related to DHI engagement (use or user experience). Strategies were classified according to behavior change techniques (BCTs) and design features (eg, supplementary emails). Multiple-variable meta-analyses of the primary outcomes (usage and user experience) were undertaken to assess the overall effectiveness of strategies. Meta-regressions were conducted to assess associations between strategies and use and user experience outcomes. Synthesis of secondary outcomes followed the "Synthesis Without Meta-Analysis" guidelines. The methodological quality and evidence was assessed using the Cochrane risk-of-bias tool, and the Grading of Recommendations Assessment, Development, and Evaluation tool respectively. RESULTS: Overall, 54 studies (across 62 publications) were included. Pooled analysis found very low-certainty evidence of a small-to-moderate positive effect of the use of strategies to improve DHI use (standardized mean difference=0.33, 95% CI 0.20-0.46; P<.001) and very low-certainty evidence of a small-to-moderate positive effect on user experience (standardized mean difference=0.29, 95% CI 0.07-0.52; P=.01). A significant positive association was found between the BCTs social support (effect size [ES]=0.40, 95% CI 0.14-0.66; P<.001) and shaping knowledge (ES=0.39, 95% CI 0.03-0.74; P=.03) and DHI use. A significant positive association was found among the BCTs social support (ES=0.70, 95% CI 0.18-1.22; P=.01), repetition and substitution (ES=0.29, 95% CI 0.05-0.53; P=.03), and natural consequences (ES=0.29, 95% CI 0.05-0.53; P=.02); the design features email (ES=0.29, 95% CI 0.05-0.53; P=.02) and SMS text messages (ES=0.34, 95% CI 0.11-0.57; P=.01); and DHI user experience. For secondary outcomes, 47% (7/15) of nutrition-related, 73% (24/33) of physical activity-related, and 41% (14/34) of overweight- and obesity-related outcomes reported an improvement in health outcomes. CONCLUSIONS: Although findings suggest that the use of strategies may improve engagement with DHIs targeting such health outcomes, the true effect is unknown because of the low quality of evidence. Future research exploring whether specific forms of social support, repetition and substitution, natural consequences, emails, and SMS text messages have a greater impact on DHI engagement is warranted. TRIAL REGISTRATION: PROSPERO CRD42018077333; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=77333.

Interventions to prevent or cease electronic cigarette use in children and adolescents.

BACKGROUND: The prevalence of e-cigarette use has increased globally amongst children and adolescents in recent years. In response to the increasing prevalence and emerging evidence about the potential harms of e-cigarettes in children and adolescents, leading public health organisations have called for approaches to address increasing e-cigarette use. Whilst evaluations of approaches to reduce uptake and use regularly appear in the literature, the collective long-term benefit of these is currently unclear. OBJECTIVES: The co-primary objectives of the review were to: (1) evaluate the effectiveness of interventions to prevent e-cigarette use in children and adolescents (aged 19 years and younger) with no prior use, relative to no intervention, waitlist control, usual practice, or an alternative intervention; and (2) evaluate the effectiveness of interventions to cease e-cigarette use in children and adolescents (aged 19 years and younger) reporting current use, relative to no intervention, waitlist control, usual practice, or an alternative intervention. Secondary objectives were to: (1) examine the effect of such interventions on child and adolescent use of other tobacco products (e.g. cigarettes, cigars types, and chewing tobacco); and (2) describe the unintended adverse effects of the intervention on individuals (e.g. physical or mental health of individuals), or on organisations (e.g. intervention displacement of key curricula or learning opportunities for school students) where such interventions are being implemented. SEARCH METHODS: We searched CENTRAL, Ovid MEDLINE, Ovid Embase, Ovid PsycINFO, EBSCO CINAHL, and Clarivate Web of Science Core Collection from inception to 1 May 2023. Additionally, we searched two trial registry platforms (WHO International Clinical Trials Registry Platform; US National Institutes of Health Ongoing Trials Register ClinicalTrials.gov), Google Scholar, and the reference lists of relevant systematic reviews. We contacted corresponding authors of articles identified as ongoing studies. SELECTION CRITERIA: We included randomised controlled trials (RCTs), including cluster-RCTs, factorial RCTs, and stepped-wedge RCTs. To be eligible, the primary targets of the interventions must have been children and adolescents aged 19 years or younger. Interventions could have been conducted in any setting, including community, school, health services, or the home, and must have sought to influence children or adolescent (or both) e-cigarette use directly. Studies with a comparator of no intervention (i.e. control), waitlist control, usual practice, or an alternative intervention not targeting e-cigarette use were eligible. We included measures to assess the effectiveness of interventions to: prevent child and adolescent e-cigarette use (including measures of e-cigarette use amongst those who were never-users); and cease e-cigarette use (including measures of e-cigarette use amongst children and adolescents who were e-cigarette current-users). Measures of e-cigarette use included current-use (defined as use in the past 30 days) and ever-use (defined as any lifetime use). DATA COLLECTION AND ANALYSIS: Two review authors independently screened the titles and abstracts of references, with any discrepancies resolved through consensus. Pairs of review authors independently assessed the full-text articles for inclusion in the review. We planned for two review authors to independently extract information from the included studies and assess risk of bias using the Cochrane RoB 2 tool. We planned to conduct multiple meta-analyses using a random-effects model to align with the co-primary objectives of the review. First, we planned to pool interventions to prevent child and adolescent e-cigarette use and conduct two analyses using the outcome measures of 'ever-use' and 'current-use'. Second, we planned to pool interventions to cease child and adolescent e-cigarette use and conduct one analysis using the outcome measure of 'current-use'. Where data were unsuitable for pooling in meta-analyses, we planned to conduct a narrative synthesis using vote-counting approaches and to follow the Cochrane Handbook for Systematic Reviews of Interventions and the Synthesis Without Meta-analysis (SWiM) guidelines. MAIN RESULTS: The search of electronic databases identified 7141 citations, with a further 287 records identified from the search of trial registries and Google Scholar. Of the 110 studies (116 records) evaluated in full text, we considered 88 to be ineligible for inclusion for the following reasons: inappropriate outcome (27 studies); intervention (12 studies); study design (31 studies); and participants (18 studies). The remaining 22 studies (28 records) were identified as ongoing studies that may be eligible for inclusion in a future review update. We identified no studies with published data that were eligible for inclusion in the review. AUTHORS' CONCLUSIONS: We identified no RCTs that met the inclusion criteria for the review, and as such, there is no evidence available from RCTs to assess the potential impact of interventions targeting children and adolescent e-cigarette use, tobacco use, or any unintended adverse effects. Evidence from studies employing other trial designs (e.g. non-randomised) may exist; however, such studies were not eligible for inclusion in the review. Evidence from studies using non-randomised designs should be examined to guide actions to prevent or cease e-cigarette use. This is a living systematic review. We search for new evidence every month and update the review when we identify relevant new evidence. Please refer to the Cochrane Database of Systematic Reviews for the current status of this review.

Disseminating health research to public health policy-makers and practitioners: a survey of source, message content and delivery modality preferences.

BACKGROUND: Understanding the views of policy-makers and practitioners regarding how best to communicate research evidence is important to support research use in their decision-making. AIM: To quantify and describe public health policy-makers and practitioners' views regarding the source, content and form of messages describing public health research findings to inform their decision-making. We also sought to examine differences in preferences between public health policy-makers and practitioners. METHODS: A cross sectional, value-weighting survey of policy-makers and practitioners was conducted. Participants were asked to allocate a proportion of 100 points across different (i) sources of research evidence, (ii) message content and (iii) the form in which evidence is presented. Points were allocated based on their rating of influence, usefulness and preference when making decisions about health policy or practice. RESULTS: A total of 186 survey responses were received from 90 policy-makers and 96 practitioners. Researchers and government department agencies were the most influential source of research evidence based on mean allocation of points, followed by knowledge brokers, professional peers and associations. Mean point allocation for perceived usefulness of message content was highest for simple summary of key findings and implications, and then evidence-based recommendations and data and statistical summaries. Finally, based on mean scores, policy-makers and practitioners preferred to receive research evidence in the form of peer-reviewed publications, reports, evidence briefs and plain language summaries. There were few differences in scores between policy-makers and practitioners across source, message content or form assessments or those with experience in different behavioural areas. CONCLUSIONS: The findings should provide a basis for the future development and optimization of dissemination strategies to this important stakeholder group.

Dissemination of public health research evidence and guidelines to Australian Early Childhood Education and Care staff: Views about source, content and format.

ISSUE ADDRESSED: Effective dissemination of public health research and evidence-based guidelines to Early Childhood Education and Care (ECEC) staff is critical for promoting research transfer and uptake and achieving positive outcomes for children. METHODS: A cross-sectional study was conducted during August 2021 to March 2022, with a sub-sample of Australian ECEC services participating in a larger survey completed online and via Computer-Assisted Telephone Interview. Survey items assessed: influential source for receiving research, type of content that would influence decisions to adopt research and preferred formats for receiving research. RESULTS: Overall, 993 service managers or staff from 1984 (50.0%) invited and eligible services completed the larger survey. Of these, 463 randomly allocated services (46.7%) had staff complete the dissemination items. The Australian Children's Education and Care Quality Authority, ECEC agencies and Government Departments were most frequently selected as influential sources of research evidence. Staff were most interested in content providing evidence-based recommendations for future actions and descriptions of health issues addressed. Workshops or conferences and webinars were the preferred format for receiving research. CONCLUSIONS: Findings highlight the importance of tailoring dissemination strategies to meet ECEC staff needs and engaging influential sources to disseminate research evidence. SO WHAT?: Understanding dissemination preferences of ECEC staff is crucial for supporting uptake of evidence-based health promotion in this setting. By developing tailored strategies based on ECEC preferences, research transfer and evidence-based decision making can be supported more effectively. These findings contribute to bridging the evidence-practice gap and improving the quality of care and health outcomes for children in ECEC settings.

The effectiveness of implementation strategies in improving preconception and antenatal preventive care: a systematic review.

BACKGROUND: Clinical guideline recommendations for addressing modifiable risk factors are not routinely implemented into preconception and antenatal care. This review assessed the effectiveness of implementation strategies in improving health professional provision of preconception and antenatal care addressing tobacco smoking, weight management and alcohol consumption. METHODS: A systematic review of randomised and non-randomised studies with a parallel comparison group was conducted. Eligible studies used implementation strategy/ies targeted at health professionals to improve at least one element of preconception and/or antenatal care (smoking: ask, advise, assess, assist, arrange; weight/alcohol: assess, advise, refer) compared to usual practice/control or alternative strategies. Eligible studies were identified via CENTRAL, MEDLINE, EMBASE, Maternity and Infant Care, CINAHL and other sources. Random-effects meta-analyses were conducted where appropriate, with other findings summarised using the direction of effect. The certainty of the pooled evidence was assessed using the GRADE approach. RESULTS: Fourteen studies were included in the review. Thirteen were in the antenatal period and 12 tested multiple implementation strategies (median: three). Meta-analyses of RCTs found that implementation strategies compared to usual practice/control probably increase asking (OR: 2.52; 95% CI: 1.13, 5.59; 3 studies; moderate-certainty evidence) and advising (OR: 4.32; 95% CI: 3.06, 6.11; 4 studies; moderate-certainty evidence) about smoking and assessing weight gain (OR: 57.56; 95% CI: 41.78, 79.29; 2 studies; moderate-certainty evidence), and may increase assessing (OR: 2.55; 95% CI: 0.24, 27.06; 2 studies; low-certainty evidence), assisting (OR: 6.34; 95% CI: 1.51, 26.63; 3 studies; low-certainty evidence) and arranging support (OR: 3.55; 95% CI: 0.50, 25.34; 2 studies; low-certainty evidence) for smoking. The true effect of implementation strategies in increasing advice about weight gain (OR: 3.37; 95% CI: 2.34, 4.84; 2 non-randomised studies; very low-certainty evidence) and alcohol consumption (OR: 10.36; 95% CI: 2.37, 41.20; 2 non-randomised studies; very low-certainty evidence) is uncertain due to the quality of evidence to date. CONCLUSIONS: Review findings provide some evidence to support the effectiveness of implementation strategies in improving health professional delivery of antenatal care addressing smoking and weight management. Rigorous research is needed to build certainty in the evidence for improving alcohol and weight gain advice, and in preconception care. TRIAL REGISTRATION: PROSPERO-CRD42019131691.

Interventions to prevent obesity in school-aged children 6-18 years: An update of a Cochrane systematic review and meta-analysis including studies from 2015-2021.

Background: Childhood obesity remains a global public health priority due to the enormous burden it generates. Recent surveillance data suggests there has been a sharp increase in the prevalence of childhood obesity during the COVID-19 pandemic. The Cochrane review of childhood obesity prevention interventions (0-18 years) updated to 2015 is the most rigorous and comprehensive review of randomised controlled trials (RCTs) on this topic. A burgeoning number of high quality studies have been published since that are yet to be synthesised. Methods: An update of the Cochrane systematic review was conducted to include RCT studies in school-aged children (6-18 years) published to 30 June 2021 that assessed effectiveness on child weight (PROSPERO registration: CRD42020218928). Available cost-effectiveness and adverse effect data were extracted. Intervention effects on body mass index (BMI) were synthesised in random effects meta-analyses by setting (school, after-school program, community, home), and meta-regression examined the association of study characteristics with intervention effect. Findings: Meta-analysis of 140 of 195 included studies (183,063 participants) found a very small positive effect on body mass index for school-based studies (SMD -0·03, 95%CI -0·06,-0·01; trials = 93; participants = 131,443; moderate certainty evidence) but not after-school programs, community or home-based studies. Subgroup analysis by age (6-12 years; 13-18 years) found no differential effects in any setting. Meta-regression found no associations between study characteristics (including setting, income level) and intervention effect. Ten of 53 studies assessing adverse effects reported presence of an adverse event. Insufficient data was available to draw conclusions on cost-effectiveness. Interpretation: This updated synthesis of obesity prevention interventions for children aged 6-18 years, found a small beneficial impact on child BMI for school-based obesity prevention interventions. A more comprehensive assessment of interventions is required to identify mechanisms of effective interventions to inform future obesity prevention public health policy, which may be particularly salient in for COVID-19 recovery planning. Funding: This research was funded by the National Health and Medical Research Council (NHMRC), Australia (Application No APP1153479).

Strategies for enhancing the implementation of school-based policies or practices targeting diet, physical activity, obesity, tobacco or alcohol use.

BACKGROUND: Several school-based interventions are effective in improving child diet and physical activity, and preventing excessive weight gain, and tobacco or harmful alcohol use. However, schools are frequently unsuccessful in implementing such evidence-based interventions. OBJECTIVES: 1. To evaluate the benefits and harms of strategies aiming to improve school implementation of interventions to address student diet, physical activity, tobacco or alcohol use, and obesity. 2. To evaluate the benefits and harms of strategies to improve intervention implementation on measures of student diet, physical activity, obesity, tobacco use or alcohol use; describe their cost or cost-effectiveness; and any harms of strategies on schools, school staff or students. SEARCH METHODS: We used standard, extensive Cochrane search methods. The latest search was between 1 September 2016 and 30 April 2021 to identify any relevant trials published since the last published review. SELECTION CRITERIA: We defined 'Implementation' as the use of strategies to adopt and integrate evidence-based health interventions and to change practice patterns within specific settings. We included any trial (randomised controlled trial (RCT) or non-randomised controlled trial (non-RCT)) conducted at any scale, with a parallel control group that compared a strategy to implement policies or practices to address diet, physical activity, overweight or obesity, tobacco or alcohol use by students to 'no intervention', 'usual' practice or a different implementation strategy. DATA COLLECTION AND ANALYSIS: We used standard Cochrane methods. Given the large number of outcomes reported, we selected and included the effects of a single outcome measure for each trial for the primary (implementation) and secondary (student health behaviour and obesity) outcomes using a decision hierarchy. Where possible, we calculated standardised mean differences (SMDs) to account for variable outcome measures with 95% confidence intervals (CI). For RCTs, we conducted meta-analyses of primary and secondary outcomes using a random-effects model, or in instances where there were between two and five studies, a fixed-effect model. The synthesis of the effects for non-randomised studies followed the 'Synthesis without meta-analysis' (SWiM) guidelines. MAIN RESULTS: We included an additional 11 trials in this update bringing the total number of included studies in the review to 38. Of these, 22 were conducted in the USA. Twenty-six studies used RCT designs. Seventeen trials tested strategies to implement healthy eating, 12 physical activity and six a combination of risk factors. Just one trial sought to increase the implementation of interventions to delay initiation or reduce the consumption of alcohol. All trials used multiple implementation strategies, the most common being educational materials, educational outreach and educational meetings. The overall certainty of evidence was low and ranged from very low to moderate for secondary review outcomes. Pooled analyses of RCTs found, relative to a control, the use of implementation strategies may result in a large increase in the implementation of interventions in schools (SMD 1.04, 95% CI 0.74 to 1.34; 22 RCTs, 1917 participants; low-certainty evidence). For secondary outcomes we found, relative to control, the use of implementation strategies to support intervention implementation may result in a slight improvement on measures of student diet (SMD 0.08, 95% CI 0.02 to 0.15; 11 RCTs, 16,649 participants; low-certainty evidence) and physical activity (SMD 0.09, 95% CI -0.02 to 0.19; 9 RCTs, 16,389 participants; low-certainty evidence). The effects on obesity probably suggest little to no difference (SMD -0.02, 95% CI -0.05 to 0.02; 8 RCTs, 18,618 participants; moderate-certainty evidence). The effects on tobacco use are very uncertain (SMD -0.03, 95% CIs -0.23 to 0.18; 3 RCTs, 3635 participants; very low-certainty evidence). One RCT assessed measures of student alcohol use and found strategies to support implementation may result in a slight increase in use (odds ratio 1.10, 95% CI 0.77 to 1.56; P = 0.60; 2105 participants). Few trials reported the economic evaluations of implementation strategies, the methods of which were heterogeneous and evidence graded as very uncertain. A lack of consistent terminology describing implementation strategies was an important limitation of the review. AUTHORS' CONCLUSIONS: The use of implementation strategies may result in large increases in implementation of interventions, and slight improvements in measures of student diet, and physical activity. Further research is required to assess the impact of implementation strategies on such behavioural- and obesity-related outcomes, including on measures of alcohol use, where the findings of one trial suggest it may slightly increase student risk. Given the low certainty of the available evidence for most measures further research is required to guide efforts to facilitate the translation of evidence into practice in this setting.

Exploring the application of behaviour change technique taxonomies in childhood obesity prevention interventions: A systematic scoping review.

Behaviour change technique (BCT) taxonomies provide one approach to unpack the complexity of childhood obesity prevention interventions. This scoping review sought to examine how BCT taxonomies have been applied to understand childhood obesity prevention interventions targeting children aged 12 years or under and/or their caregivers. A systematic search was conducted in Medline, Embase, PsycINFO, Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews, CINAHL and PROSPERO, to capture all eligible research up to February 2021. No limits were placed on country, language, publication dates, or full text availability. Eligible studies included any study design that applied a BCT taxonomy and evaluated behavioural childhood obesity prevention interventions targeting children aged 12 years or under and/or their parents or caregivers. Sixty-three records, describing 54 discrete studies were included; 32 applied a BCT taxonomy prospectively (i.e., to design interventions) and 23 retrospectively (i.e., to assess interventions), 1 study did both. There was substantial variation in the methods used to apply BCT taxonomies and to report BCT-related methods and results. There was a paucity of detail reported in how BCTs were selected in studies applying BCT taxonomies prospectively. Our review provides important insight into the application of BCT taxonomies in childhood obesity prevention and several ongoing challenges, pointing to the need for best practice reporting guidance.

The benefits of data sharing and ensuring open sources of systematic review data.

AIMS: The benefits of increasing public access to data from clinical trials are widely accepted. Such benefits extend to the sharing of data from high-quality systematic reviews, given the time and cost involved with undertaking reviews. We describe the application of open sources of review data, outline potential challenges and highlight efforts made to address these challenges, with the intent of encouraging publishers, funders and authors to consider sharing review data more broadly. RESULTS: We describe the application of systematic review data in: (i) advancing understanding of clinical trials and systematic review methods, (ii) repurposing of data to answer public health policy and practice relevant questions, (iii) identification of research gaps and (iv) accelerating the conduct of rapid reviews to inform decision making. While access, logistical, motivational and legal challenges exist, there has been progress made by systematic review, academic and funding agencies to incentivise data sharing and create infrastructure to support greater access to systematic review data. CONCLUSION: There is opportunity to maximize the benefits of research investment in undertaking systematic reviews by ensuring open sources of systematic review data. Efforts to create such systems should draw on learnings and principles outlined for sharing clinical trial data.

Increased use of knowledge translation strategies is associated with greater research impact on public health policy and practice: an analysis of trials of nutrition, physical activity, sexual health, tobacco, alcohol and substance use interventions.

BACKGROUND: Greater use of knowledge translation (KT) strategies is recommended to improve the research impact of public health trials. The purpose of this study was to describe (1) the research impact of setting-based public health intervention trials on public health policy and practice; (2) the association between characteristics of trials and their research impact on public health policy and practice; and (3) the association between the use of KT strategies and research impacts on public health policy and practice. METHODS: We conducted a survey of authors of intervention trials targeting nutrition, physical activity, sexual health, tobacco, alcohol or substance use. We assessed the use of KT strategies aligned to domains of the Knowledge-To-Action Framework. We defined "research impact" on health policy and practice as any one or more of the following: citation in policy documents or announcements, government reports, training materials, guidelines, textbooks or court rulings; or endorsement by a (non)governmental organization; use in policy or practice decision-making; or use in the development of a commercial resource or service. RESULTS: Of the included trials, the authors reported that 65% had one or more research impacts. The most frequently reported research impact was citation in a policy document or announcement (46%). There were no significant associations between the effectiveness of the intervention, trial risk of bias, setting or health risk and trial impact. However, for every one unit increase in the total KT score (range 0-8), reflecting greater total KT activity, the odds of a health policy or practice research impact increased by approximately 30% (OR = 1.30, 95% CI: 1.02, 1.66; p = 0.031). Post hoc examination of KT domain scores suggests that KT actions focused on providing tailored support to facilitate program implementation and greater use of research products and tools to disseminate findings to end-users may be most influential in achieving impact. CONCLUSIONS: Trials of public health interventions frequently have public health impacts, and the use of more comprehensive KT strategies may facilitate greater research impact.

Compliance with telephone-based lifestyle weight loss programs improves low back pain but not knee pain outcomes: complier average causal effects analyses of 2 randomised trials.

ABSTRACT: We conducted a complier average causal effect (CACE) analyses for 2 pragmatic randomised controlled trials. We aimed to assess the effectiveness of telephone-based lifestyle weight loss interventions compared with usual care among compliers. Participants from 2 trials with low back pain (n = 160) and knee osteoarthritis (n = 120) with a body mass index ≥27 kg/m2 were included. We defined adherence to the telephone-based lifestyle weight loss program as completing 60% (6 from 10) of telephone health coaching calls. The primary outcomes for CACE analyses were pain intensity (0-10 Numerical Rating Scale) and disability (Roland Morris Disability Questionnaire for low back pain and Western Ontario and McMaster Universities Osteoarthritis Index for knee osteoarthritis). Secondary outcomes were weight, physical activity, and diet. We used an instrumental variable approach to estimate CACE in compliers. From the intervention groups of the trials, 29% of those with low back pain (n = 23/80) and 34% of those with knee osteoarthritis (n = 20/60) complied. Complier average causal effect estimates showed potentially clinically meaningful effects, but with low certainty because of wide confidence intervals, for pain intensity (-1.4; 95% confidence interval, -3.1, 0.4) and small but also uncertain effects for disability (-2.1; 95% confidence interval, -8.6, 4.5) among compliers in the low back pain trial intervention compared with control but not in the knee osteoarthritis trial. Our findings showed that compliers of a telephone-based weight loss intervention in the low back pain trial generally had improved outcomes; however, there were inconsistent effects in compliers from the knee osteoarthritis trial. Complier average causal effect estimates were larger than intention-to-treat results but must be considered with caution.

School-Based Nutrition Interventions in Children Aged 6 to 18 Years: An Umbrella Review of Systematic Reviews.

Schools are identified as a key setting to influence children's and adolescents' healthy eating. This umbrella review synthesised evidence from systematic reviews of school-based nutrition interventions designed to improve dietary intake outcomes in children aged 6 to 18 years. We undertook a systematic search of six electronic databases and grey literature to identify relevant reviews of randomized controlled trials. The review findings were categorised for synthesis by intervention type according to the World Health Organisation Health Promoting Schools (HPS) framework domains: nutrition education; food environment; all three HPS framework domains; or other (not aligned to HPS framework domain). Thirteen systematic reviews were included. Overall, the findings suggest that school-based nutrition interventions, including nutrition education, food environment, those based on all three domains of the HPS framework, and eHealth interventions, can have a positive effect on some dietary outcomes, including fruit, fruit and vegetables combined, and fat intake. These results should be interpreted with caution, however, as the quality of the reviews was poor. Though these results support continued public health investment in school-based nutrition interventions to improve child dietary intake, the limitations of this umbrella review also highlight the need for a comprehensive and high quality systematic review of primary studies.

Australian children are not meeting recommended physical activity levels at school: Analysis of objectively measured physical activity data from a cross sectional study.

This study aimed to quantify, and examine grade level (Grade Kindergarten-2 vs. 3-6) and sex differences in the daily minutes of moderate-to-vigorous physical activity (MVPA) of primary school children, and the proportion of children meeting MVPA recommendations, across the school day and in break times. Consenting children in Kindergarten to Grade 6 from 12 Catholic primary schools within the Hunter region of New South Wales, Australia (February-April 2017) wore accelerometers during school hours (approx. 9am-3 pm) for five school days. Differences in student physical activity by Grade (Kindergarten-2; Grade 3-6) and sex were analysed using regression mixed modelling for the whole school day, during class time and break time. Valid data was available for 1862 students. Mean (SD) minutes of MVPA were consistently higher for Grade K-2 compared to Grade 3-6 students respectively, 37.02 (12.4) and 32.6 (12.2) across the school day; 20.4 (8.4) and 15.3 (7.6) minutes within breaks. Over the whole school day 69.7% of Grade K-2 and 54.1% of Grade 3-6 met the recommended 30 min of MVPA. Boys had higher MVPA than girls and a higher proportion of boys met MVPA recommendations than girls with 68.9% and 52.4% over whole school day and 6.43% and 0.98% respectively during break times. A large percentage of Australian children are not meeting physical activity guidelines whilst at school, with declining levels of physical activity from Grade K-2 to Grade 3-6 especially evident in girls.

Improving implementation of school-based healthy eating and physical activity policies, practices, and programs: a systematic review.

Although best practice recommendations exist regarding school-based healthy eating and physical activity policies, practices, and programs, research indicates that implementation is poor. As the field of implementation science is rapidly evolving, an update of the recent review of strategies to improve the implementation of healthy eating and physical activity interventions in schools published in the Cochrane Library in 2017 was required. The primary aim of this review was to examine the effectiveness of strategies that aim to improve the implementation of school-based policies, practices, or programs to address child diet, physical activity, or obesity. A systematic review of articles published between August 31, 2016 and April 10, 2019 utilizing Cochrane methodology was conducted. In addition to the 22 studies included in the original review, eight further studies were identified as eligible. The 30 studies sought to improve the implementation of healthy eating (n = 16), physical activity (n = 11), or both healthy eating and physical activity (n = 3). The narrative synthesis indicated that effect sizes of strategies to improve implementation were highly variable across studies. For example, among 10 studies reporting the proportion of schools implementing a targeted policy, practice, or program versus a minimal or usual practice control, the median unadjusted effect size was 16.2%, ranging from -0.2% to 66.6%. Findings provide some evidence to support the effectiveness of strategies in enhancing the nutritional quality of foods served at schools, the implementation of canteen policies, and the time scheduled for physical education.