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.

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 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.

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.

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.

Interventions for increasing fruit and vegetable consumption in children aged five years and under.

BACKGROUND: Insufficient consumption of fruits and vegetables in childhood increases the risk of future non-communicable diseases, including cardiovascular disease. Testing the effects of interventions to increase consumption of fruit and vegetables, including those focused on specific child-feeding strategies or broader multicomponent interventions targeting the home or childcare environment is required to assess the potential to reduce this disease burden. OBJECTIVES: To assess the effectiveness, cost effectiveness and associated adverse events of interventions designed to increase the consumption of fruit, vegetables or both amongst children aged five years and under. SEARCH METHODS: We searched CENTRAL, MEDLINE, Embase and two clinical trials registries to identify eligible trials on 25 January 2020. We searched Proquest Dissertations and Theses in November 2019. We reviewed reference lists of included trials and handsearched three international nutrition journals. We contacted authors of included trials to identify further potentially relevant trials. SELECTION CRITERIA: We included randomised controlled trials, including cluster-randomised controlled trials and cross-over trials, of any intervention primarily targeting consumption of fruit, vegetables or both among children aged five years and under, and incorporating a dietary or biochemical assessment of fruit or vegetable consumption. Two review authors independently screened titles and abstracts of identified papers; a third review author resolved disagreements. DATA COLLECTION AND ANALYSIS: Two review authors independently extracted data and assessed the risks of bias of included trials; a third review author resolved disagreements. Due to unexplained heterogeneity, we used random-effects models in meta-analyses for the primary review outcomes where we identified sufficient trials. We calculated standardised mean differences (SMDs) to account for the heterogeneity of fruit and vegetable consumption measures. We conducted assessments of risks of bias and evaluated the quality of evidence (GRADE approach) using Cochrane procedures. MAIN RESULTS: We included 80 trials with 218 trial arms and 12,965 participants. Fifty trials examined the impact of child-feeding practices (e.g. repeated food exposure) in increasing child vegetable intake. Fifteen trials examined the impact of parent nutrition education only in increasing child fruit and vegetable intake. Fourteen trials examined the impact of multicomponent interventions (e.g. parent nutrition education and preschool policy changes) in increasing child fruit and vegetable intake. Two trials examined the effect of a nutrition education intervention delivered to children in increasing child fruit and vegetable intake. One trial examined the impact of a child-focused mindfulness intervention in increasing vegetable intake. We judged 23 of the 80 included trials as free from high risks of bias across all domains. Performance, detection and attrition bias were the most common domains judged at high risk of bias for the remaining trials. There is low-quality evidence that child-feeding practices versus no intervention may have a small positive effect on child vegetable consumption, equivalent to an increase of 5.30 grams as-desired consumption of vegetables (SMD 0.50, 95% CI 0.29 to 0.71; 19 trials, 2140 participants; mean post-intervention follow-up = 8.3 weeks). Multicomponent interventions versus no intervention has a small effect on child consumption of fruit and vegetables (SMD 0.32, 95% CI 0.09 to 0.55; 9 trials, 2961 participants; moderate-quality evidence; mean post-intervention follow-up = 5.4 weeks), equivalent to an increase of 0.34 cups of fruit and vegetables a day. It is uncertain whether there are any short-term differences in child consumption of fruit and vegetables in meta-analyses of trials examining parent nutrition education versus no intervention (SMD 0.13, 95% CI -0.02 to 0.28; 11 trials, 3050 participants; very low-quality evidence; mean post-intervention follow-up = 13.2 weeks). We were unable to pool child nutrition education interventions in meta-analysis; both trials reported a positive intervention effect on child consumption of fruit and vegetables (low-quality evidence). Very few trials reported long-term effectiveness (6 trials), cost effectiveness (1 trial) or unintended adverse consequences of interventions (2 trials), limiting our ability to assess these outcomes. Trials reported receiving governmental or charitable funds, except for four trials reporting industry funding. AUTHORS' CONCLUSIONS: Despite identifying 80 eligible trials of various intervention approaches, the evidence for how to increase children's fruit and vegetable consumption remains limited in terms of quality of evidence and magnitude of effect. Of the types of interventions identified, there was moderate-quality evidence that multicomponent interventions probably lead to, and low-quality evidence that child-feeding practice may lead to, only small increases in fruit and vegetable consumption in children aged five years and under. It is uncertain whether parent nutrition education or child nutrition education interventions alone are effective in increasing fruit and vegetable consumption in children aged five years and under. Our confidence in effect estimates for all intervention approaches, with the exception of multicomponent interventions, is limited on the basis of the very low to low-quality evidence. Long-term follow-up of at least 12 months is required and future research should adopt more rigorous methods to advance the field. This is a living systematic review. Living systematic reviews offer a new approach to review updating, in which the review is continually updated, incorporating relevant new evidence as it becomes available. Please refer to the Cochrane Database of Systematic Reviews for the current status of this review.

Strategies to improve the implementation of healthy eating, physical activity and obesity prevention policies, practices or programmes within childcare services.

BACKGROUND: Despite the existence of effective interventions and best-practice guideline recommendations for childcare services to implement evidence-based policies, practices and programmes to promote child healthy eating, physical activity and prevent unhealthy weight gain, many services fail to do so. OBJECTIVES: The primary aim of the review was to examine the effectiveness of strategies aimed at improving the implementation of policies, practices or programmes by childcare services that promote child healthy eating, physical activity and/or obesity prevention. The secondary aims of the review were to: 1. Examine the cost or cost-effectiveness of such strategies; 2. Examine any adverse effects of such strategies on childcare services, service staff or children; 3. Examine the effect of such strategies on child diet, physical activity or weight status. 4. Describe the acceptability, adoption, penetration, sustainability and appropriateness of such implementation strategies. SEARCH METHODS: We searched the following electronic databases on February 22 2019: Cochrane Central Register of Controlled trials (CENTRAL), MEDLINE, MEDLINE In Process, Embase, PsycINFO, ERIC, CINAHL and SCOPUS for relevant studies. We searched reference lists of included studies, handsearched two international implementation science journals, the World Health Organization International Clinical Trials Registry Platform (www.who.int/ictrp/) and ClinicalTrials.gov (www.clinicaltrials.gov). SELECTION CRITERIA: We included any study (randomised or nonrandomised) with a parallel control group that compared any strategy to improve the implementation of a healthy eating, physical activity or obesity prevention policy, practice or programme by staff of centre-based childcare services to no intervention, 'usual' practice or an alternative strategy. Centre-based childcare services included preschools, nurseries, long daycare services and kindergartens catering for children prior to compulsory schooling (typically up to the age of five to six years). DATA COLLECTION AND ANALYSIS: Two review authors independently screened study titles and abstracts, extracted study data and assessed risk of bias; we resolved discrepancies via consensus. We performed meta-analysis using a random-effects model where studies with suitable data and homogeneity were identified; otherwise, findings were described narratively. MAIN RESULTS: Twenty-one studies, including 16 randomised and five nonrandomised, were included in the review. The studies sought to improve the implementation of policies, practices or programmes targeting healthy eating (six studies), physical activity (three studies) or both healthy eating and physical activity (12 studies). Studies were conducted in the United States (n = 12), Australia (n = 8) and Ireland (n = 1). Collectively, the 21 studies included a total of 1945 childcare services examining a range of implementation strategies including educational materials, educational meetings, audit and feedback, opinion leaders, small incentives or grants, educational outreach visits or academic detailing, reminders and tailored interventions. Most studies (n = 19) examined implementation strategies versus usual practice or minimal support control, and two compared alternative implementation strategies. For implementation outcomes, six studies (one RCT) were judged to be at high risk of bias overall. The review findings suggest that implementation strategies probably improve the implementation of policies, practices or programmes that promote child healthy eating, physical activity and/or obesity prevention in childcare services. Of the 19 studies that compared a strategy to usual practice or minimal support control, 11 studies (nine RCTs) used score-based measures of implementation (e.g. childcare service nutrition environment score). Nine of these studies were included in pooled analysis, which found an improvement in implementation outcomes (SMD 0.49; 95% CI 0.19 to 0.79; participants = 495; moderate-certainty evidence). Ten studies (seven RCTs) used dichotomous measures of implementation (e.g. proportion of childcare services implementing a policy or specific practice), with seven of these included in pooled analysis (OR 1.83; 95% CI 0.81 to 4.11; participants = 391; low-certainty evidence). Findings suggest that such interventions probably lead to little or no difference in child physical activity (four RCTs; moderate-certainty evidence) or weight status (three RCTs; moderate-certainty evidence), and may lead to little or no difference in child diet (two RCTs; low-certainty evidence). None of the studies reported the cost or cost-effectiveness of the intervention. Three studies assessed the adverse effects of the intervention on childcare service staff, children and parents, with all studies suggesting they have little to no difference in adverse effects (e.g. child injury) between groups (three RCTs; low-certainty evidence). Inconsistent quality of the evidence was identified across review outcomes and study designs, ranging from very low to moderate. The primary limitation of the review was the lack of conventional terminology in implementation science, which may have resulted in potentially relevant studies failing to be identified based on the search terms used. AUTHORS' CONCLUSIONS: Current research suggests that implementation strategies probably improve the implementation of policies, practices or programmes by childcare services, and may have little or no effect on measures of adverse effects. However such strategies appear to have little to no impact on measures of child diet, physical activity or weight status.

Effectiveness of embedding a specialist preventive care clinician in a community mental health service in increasing preventive care provision: A randomised controlled trial.

OBJECTIVE: Clinical practice guidelines recommend that community mental health services provide preventive care for clients' chronic disease risk behaviours; however, such care is often not routinely provided. This study aimed to assess the effectiveness of offering clients an additional consultation with a specialist clinician embedded within a community mental health service, in increasing client-reported receipt of, and satisfaction with, preventive care. METHOD: A randomised controlled trial was undertaken in one Australian community mental health service. Participants (N = 811) were randomised to receive usual care (preventive care in routine consultations; n = 405) or usual care plus the offer of an additional consultation with a specialist preventive care clinician (n = 406). Blinded interviewers assessed at baseline and 1-month follow-up the client-reported receipt of preventive care (assessment, advice and referral) for four key risk behaviours individually (smoking, poor nutrition, alcohol overconsumption and physical inactivity) and all applicable risks combined, acceptance of referrals and satisfaction with preventive care received. RESULTS: Analyses indicated significantly greater increases in 12 of the 18 preventive care delivery outcomes in the intervention compared to the usual care condition from baseline to follow-up, including assessment for all risks combined (risk ratio = 4.00; 95% confidence interval = [1.57, 10.22]), advice for all applicable risks combined (risk ratio = 2.40; 95% confidence interval = [1.89, 6.47]) and offer of referral to applicable telephone services combined (risk ratio = 20.13; 95% confidence interval = [2.56, 158.04]). For each component of care, there was a significant intervention effect for at least one of the individual risk behaviours. Participants reported high levels of satisfaction with preventive care received, ranging from 77% (assessment) to 87% (referral), with no significant differences between conditions. CONCLUSION: The intervention had a significant effect on the provision of the majority of recommended elements of preventive care. Further research is needed to maximise its impact, including identifying strategies to increase client uptake.

Effectiveness of Technology-Enabled Knowledge Translation Strategies in Improving the Use of Research in Public Health: Systematic Review.

BACKGROUND: Knowledge translation (KT) aims to facilitate the use of research evidence in decision making. Changes in technology have provided considerable opportunities for KT strategies to improve access and use of evidence in decision making by public health policy makers and practitioners. Despite this opportunity, there have been no reviews that have assessed the effects of digital technology-enabled KT (TEKT) in the field of public health. OBJECTIVE: This study aims to examine the effectiveness of digital TEKT strategies in (1) improving the capacity for evidence-based decision making by public health policy makers and practitioners, (2) changing public health policy or practice, and (3) changes in individual or population health outcomes. METHODS: A search strategy was developed to identify randomized trials assessing the effectiveness of digital TEKT strategies in public health. Any primary research study with a randomized trial design was eligible. Searches for eligible studies were undertaken in multiple electronic bibliographic databases (Medical Literature Analysis and Retrieval System Online [MEDLINE], Excerpta Medica dataBASE [EMBASE], PsycINFO, Cumulative Index to Nursing and Allied Health Literature [CINAHL], and Scopus) and the reference lists of included studies. A hand search of 2 journals (Implementation Science and Journal of Medical Internet Research) and a gray literature search were also conducted. Pairs of independent review authors screened studies, assessed the risk of bias, and extracted data from relevant studies. RESULTS: Of the 6819 citations screened, 8 eligible randomized trials were included in the review. The studies examined the impact of digital TEKT strategies on health professionals, including nurses, child care health consultants, physiotherapists, primary health care workers, and public health practitioners. Overall, 5 of the interventions were web-training programs. The remaining 3 interventions included simulation games, access to digital resource materials and the use of tailored messaging, and a web-based registry. The findings suggest that digital TEKT interventions may be effective in improving the knowledge of public health professionals, relative to control, and may be as effective as a face-to-face KT approach. The effectiveness of digital TEKT strategies relative to a control or other digital KT interventions on measures of health professional self-efficacy to use evidence to enhance practice behavior or behavioral intention outcomes was mixed. The evidence regarding the effects on changes to health policy or practice following exposure to digital TEKT was mixed. No trials assessed the effects on individual or population-level health outcomes. CONCLUSIONS: This review is the first to synthesize the effectiveness of digital TEKT interventions in a public health setting. Despite its potential, relatively few trials have been undertaken to investigate the impacts of digital TEKT interventions. The findings suggest that although a digital TEKT intervention may improve knowledge, the effects of such interventions on other outcomes are equivocal.

Real-time video counselling for smoking cessation.

BACKGROUND: Real-time video communication software such as Skype and FaceTime transmits live video and audio over the Internet, allowing counsellors to provide support to help people quit smoking. There are more than four billion Internet users worldwide, and Internet users can download free video communication software, rendering a video counselling approach both feasible and scalable for helping people to quit smoking. OBJECTIVES: To assess the effectiveness of real-time video counselling delivered individually or to a group in increasing smoking cessation, quit attempts, intervention adherence, satisfaction and therapeutic alliance, and to provide an economic evaluation regarding real-time video counselling. SEARCH METHODS: We searched the Cochrane Tobacco Addiction Group Specialised Register, CENTRAL, MEDLINE, PubMed, PsycINFO and Embase to identify eligible studies on 13 August 2019. We searched the World Health Organization International Clinical Trials Registry Platform and ClinicalTrials.gov to identify ongoing trials registered by 13 August 2019. We checked the reference lists of included articles and contacted smoking cessation researchers for any additional studies. SELECTION CRITERIA: We included randomised controlled trials (RCTs), randomised trials, cluster RCTs or cluster randomised trials of real-time video counselling for current tobacco smokers from any setting that measured smoking cessation at least six months following baseline. The real-time video counselling intervention could be compared with a no intervention control group or another smoking cessation intervention, or both. DATA COLLECTION AND ANALYSIS: Two authors independently extracted data from included trials, assessed the risk of bias and rated the certainty of the evidence using the GRADE approach. We performed a random-effects meta-analysis for the primary outcome of smoking cessation, using the most stringent measure of smoking cessation measured at the longest follow-up. Analysis was based on the intention-to-treat principle. We considered participants with missing data at follow-up for the primary outcome of smoking cessation to be smokers. MAIN RESULTS: We included two randomised trials with 615 participants. Both studies delivered real-time video counselling for smoking cessation individually, compared with telephone counselling. We judged one study at unclear risk of bias and one study at high risk of bias. There was no statistically significant treatment effect for smoking cessation (using the strictest definition and longest follow-up) across the two included studies when real-time video counselling was compared to telephone counselling (risk ratio (RR) 2.15, 95% confidence interval (CI) 0.38 to 12.04; 2 studies, 608 participants; I2 = 66%). We judged the overall certainty of the evidence for smoking cessation as very low due to methodological limitations, imprecision in the effect estimate reflected by the wide 95% CIs and inconsistency of cessation rates. There were no significant differences between real-time video counselling and telephone counselling reported for number of quit attempts among people who continued to smoke (mean difference (MD) 0.50, 95% CI -0.60 to 1.60; 1 study, 499 participants), mean number of counselling sessions completed (MD -0.20, 95% CI -0.45 to 0.05; 1 study, 566 participants), completion of all sessions (RR 1.13, 95% CI 0.71 to 1.79; 1 study, 43 participants) or therapeutic alliance (MD 1.13, 95% CI -0.24 to 2.50; 1 study, 398 participants). Participants in the video counselling arm were more likely than their telephone counselling counterparts to recommend the programme to a friend or family member (RR 1.06, 95% CI 1.01 to 1.11; 1 study, 398 participants); however, there were no between-group differences on satisfaction score (MD 0.70, 95% CI -1.16 to 2.56; 1 study, 29 participants). AUTHORS' CONCLUSIONS: There is very little evidence about the effectiveness of real-time video counselling for smoking cessation. The existing research does not suggest a difference between video counselling and telephone counselling for assisting people to quit smoking. However, given the very low GRADE rating due to methodological limitations in the design, imprecision of the effect estimate and inconsistency of cessation rates, the smoking cessation results should be interpreted cautiously. High-quality randomised trials comparing real-time video counselling to telephone counselling are needed to increase the confidence of the effect estimate. Furthermore, there is currently no evidence comparing real-time video counselling to a control group. Such research is needed to determine whether video counselling increases smoking cessation.

Interventions for increasing fruit and vegetable consumption in children aged five years and under.

BACKGROUND: Insufficient consumption of fruits and vegetables in childhood increases the risk of future non-communicable diseases, including cardiovascular disease. Interventions to increase consumption of fruit and vegetables, such as those focused on specific child-feeding strategies and parent nutrition education interventions in early childhood may therefore be an effective strategy in reducing this disease burden. OBJECTIVES: To assess the effectiveness, cost effectiveness and associated adverse events of interventions designed to increase the consumption of fruit, vegetables or both amongst children aged five years and under. SEARCH METHODS: We searched CENTRAL, MEDLINE, Embase and two clinical trials registries to identify eligible trials on 25 August 2019. We searched Proquest Dissertations and Theses in May 2019. We reviewed reference lists of included trials and handsearched three international nutrition journals. We contacted authors of included trials to identify further potentially relevant trials. SELECTION CRITERIA: We included randomised controlled trials, including cluster-randomised controlled trials and cross-over trials, of any intervention primarily targeting consumption of fruit, vegetables or both among children aged five years and under, and incorporating a dietary or biochemical assessment of fruit or vegetable consumption. Two review authors independently screened titles and abstracts of identified papers; a third review author resolved disagreements. DATA COLLECTION AND ANALYSIS: Two review authors independently extracted data and assessed the risks of bias of included trials; a third review author resolved disagreements. Due to unexplained heterogeneity, we used random-effects models in meta-analyses for the primary review outcomes where we identified sufficient trials. We calculated standardised mean differences (SMDs) to account for the heterogeneity of fruit and vegetable consumption measures. We conducted assessments of risks of bias and evaluated the quality of evidence (GRADE approach) using Cochrane procedures. MAIN RESULTS: We included 78 trials with 214 trial arms and 13,746 participants. Forty-eight trials examined the impact of child-feeding practices (e.g. repeated food exposure) in increasing child vegetable intake. Fifteen trials examined the impact of parent nutrition education in increasing child fruit and vegetable intake. Fourteen trials examined the impact of multicomponent interventions (e.g. parent nutrition education and preschool policy changes) in increasing child fruit and vegetable intake. Two trials examined the effect of a nutrition education intervention delivered to children in increasing child fruit and vegetable intake. One trial examined the impact of a child-focused mindfulness intervention in increasing vegetable intake. We judged 20 of the 78 included trials as free from high risks of bias across all domains. Performance, detection and attrition bias were the most common domains judged at high risk of bias for the remaining trials. There is very low-quality evidence that child-feeding practices versus no intervention may have a small positive effect on child vegetable consumption equivalent to an increase of 4.45 g as-desired consumption of vegetables (SMD 0.42, 95% CI 0.23 to 0.60; 18 trials, 2004 participants; mean post-intervention follow-up = 8.2 weeks). Multicomponent interventions versus no intervention has a small effect on child consumption of fruit and vegetables (SMD 0.34, 95% CI 0.10 to 0.57; 9 trials, 3022 participants; moderate-quality evidence; mean post-intervention follow-up = 5.4 weeks), equivalent to an increase of 0.36 cups of fruit and vegetables per day. It is uncertain whether there are any short-term differences in child consumption of fruit and vegetables in meta-analyses of trials examining parent nutrition education versus no intervention (SMD 0.12, 95% CI -0.03 to 0.28; 11 trials, 3078 participants; very low-quality evidence; mean post-intervention follow-up = 13.2 weeks). We were unable to pool child nutrition education interventions in meta-analysis; both trials reported a positive intervention effect on child consumption of fruit and vegetables (low-quality evidence). Very few trials reported long-term effectiveness (6 trials), cost effectiveness (1 trial) and unintended adverse consequences of interventions (2 trials), limiting their assessment. Trials reported receiving governmental or charitable funds, except for four trials reporting industry funding. AUTHORS' CONCLUSIONS: Despite identifying 78 eligible trials of various intervention approaches, the evidence for how to increase children's fruit and vegetable consumption remains limited. There was very low-quality evidence that child-feeding practice may lead to, and moderate-quality evidence that multicomponent interventions probably lead to small increases in fruit and vegetable consumption in children aged five years and younger. It is uncertain whether parent nutrition education interventions are effective in increasing fruit and vegetable consumption in children aged five years and younger. Given that the quality of the evidence is very low or low, future research will likely change estimates and conclusions. Long-term follow-up of at least 12 months is required and future research should adopt more rigorous methods to advance the field. This is a living systematic review. Living systematic reviews offer a new approach to review updating, in which the review is continually updated, incorporating relevant new evidence as it becomes available. Please refer to the Cochrane Database of Systematic Reviews for the current status of this review.

Family-based prevention programmes for alcohol use in young people.

BACKGROUND: Alcohol use in young people is a risk factor for a range of short- and long-term harms and is a cause of concern for health services, policy-makers, youth workers, teachers, and parents. OBJECTIVES: To assess the effectiveness of universal, selective, and indicated family-based prevention programmes in preventing alcohol use or problem drinking in school-aged children (up to 18 years of age).Specifically, on these outcomes, the review aimed:• to assess the effectiveness of universal family-based prevention programmes for all children up to 18 years ('universal interventions');• to assess the effectiveness of selective family-based prevention programmes for children up to 18 years at elevated risk of alcohol use or problem drinking ('selective interventions'); and• to assess the effectiveness of indicated family-based prevention programmes for children up to 18 years who are currently consuming alcohol, or who have initiated use or regular use ('indicated interventions'). SEARCH METHODS: We identified relevant evidence from the Cochrane Central Register of Controlled Trials (CENTRAL), in the Cochrane Library, MEDLINE (Ovid 1966 to June 2018), Embase (1988 to June 2018), Education Resource Information Center (ERIC; EBSCOhost; 1966 to June 2018), PsycINFO (Ovid 1806 to June 2018), and Google Scholar. We also searched clinical trial registers and handsearched references of topic-related systematic reviews and the included studies. SELECTION CRITERIA: We included randomised controlled trials (RCTs) and cluster RCTs (C-RCTs) involving the parents of school-aged children who were part of the general population with no known risk factors (universal interventions), were at elevated risk of alcohol use or problem drinking (selective interventions), or were already consuming alcohol (indicated interventions). Psychosocial or educational interventions involving parents with or without involvement of children were compared with no intervention, or with alternate (e.g. child only) interventions, allowing experimental isolation of parent components. DATA COLLECTION AND ANALYSIS: We used standard methodological procedures expected by Cochrane. MAIN RESULTS: We included 46 studies (39,822 participants), with 27 classified as universal, 12 as selective, and seven as indicated. We performed meta-analyses according to outcome, including studies reporting on the prevalence, frequency, or volume of alcohol use. The overall quality of evidence was low or very low, and there was high, unexplained heterogeneity.Upon comparing any family intervention to no intervention/standard care, we found no intervention effect on the prevalence (standardised mean difference (SMD) 0.00, 95% confidence interval (CI) -0.08 to 0.08; studies = 12; participants = 7490; I² = 57%; low-quality evidence) or frequency (SMD -0.31, 95% CI -0.83 to 0.21; studies = 8; participants = 1835; I² = 96%; very low-quality evidence) of alcohol use in comparison with no intervention/standard care. The effect of any parent/family interventions on alcohol consumption volume compared with no intervention/standard care was very small (SMD -0.14, 95% CI -0.27 to 0.00; studies = 5; participants = 1825; I² = 42%; low-quality evidence).When comparing parent/family and adolescent interventions versus interventions with young people alone, we found no difference in alcohol use prevalence (SMD -0.39, 95% CI -0.91 to 0.14; studies = 4; participants = 5640; I² = 99%; very low-quality evidence) or frequency (SMD -0.16, 95% CI -0.42 to 0.09; studies = 4; participants = 915; I² = 73%; very low-quality evidence). For this comparison, no trials reporting on the volume of alcohol use could be pooled in meta-analysis.In general, the results remained consistent in separate subgroup analyses of universal, selective, and indicated interventions. No adverse effects were reported. AUTHORS' CONCLUSIONS: The results of this review indicate that there are no clear benefits of family-based programmes for alcohol use among young people. Patterns differ slightly across outcomes, but overall, the variation, heterogeneity, and number of analyses performed preclude any conclusions about intervention effects. Additional independent studies are required to strengthen the evidence and clarify the marginal effects observed.

Causal mechanisms of a healthy lifestyle intervention for patients with musculoskeletal pain who are overweight or obese.

PURPOSE: To assess the causal mechanisms of a healthy lifestyle intervention for patients with chronic low back pain and knee osteoarthritis, who are overweight or obese. METHODS: We conducted causal mediation analyses of aggregated data from two randomized controlled trials (RCTs); which included 160 patients with chronic low back pain, and 120 patients with knee osteoarthritis. The intervention consisted of brief advice and referral to a six-month telephone-based healthy lifestyle coaching service. We used causal mediation to estimate the indirect, direct and path-specific effects of hypothesized mediators including: self-reported weight, diet, physical activity, and pain beliefs. Outcomes were pain intensity, disability, and quality of life (QoL). RESULTS: The intervention did not reduce weight, improve diet or physical activity or change pain beliefs, and these mediators were not associated with the outcomes. Sensitivity analyses showed that our estimates were robust to the possible effects of unknown and unmeasured confounding. CONCLUSIONS: Our findings show that the intervention did not cause a meaningful change in the hypothesized mediators, and these mediators were not associated with patient-reported outcomes.

Interventions for increasing fruit and vegetable consumption in children aged five years and under.

BACKGROUND: Insufficient consumption of fruits and vegetables in childhood increases the risk of future chronic diseases, including cardiovascular disease. OBJECTIVES: To assess the effectiveness, cost effectiveness and associated adverse events of interventions designed to increase the consumption of fruit, vegetables or both amongst children aged five years and under. SEARCH METHODS: We searched the Cochrane Central Register of Controlled Trials (CENTRAL) in the Cochrane Library, MEDLINE and Embase to identify eligible trials on 25 September 2017. We searched Proquest Dissertations and Theses and two clinical trial registers in November 2017. We reviewed reference lists of included trials and handsearched three international nutrition journals. We contacted authors of included studies to identify further potentially relevant trials. SELECTION CRITERIA: We included randomised controlled trials, including cluster-randomised controlled trials and cross-over trials, of any intervention primarily targeting consumption of fruit, vegetables or both among children aged five years and under, and incorporating a dietary or biochemical assessment of fruit or vegetable consumption. Two review authors independently screened titles and abstracts of identified papers; a third review author resolved disagreements. DATA COLLECTION AND ANALYSIS: Two review authors independently extracted data and assessed the risks of bias of included studies; a third review author resolved disagreements. Due to unexplained heterogeneity, we used random-effects models in meta-analyses for the primary review outcomes where we identified sufficient trials. We calculated standardised mean differences (SMDs) to account for the heterogeneity of fruit and vegetable consumption measures. We conducted assessments of risks of bias and evaluated the quality of evidence (GRADE approach) using Cochrane procedures. MAIN RESULTS: We included 55 trials with 154 trial arms and 11,108 participants. Thirty-three trials examined the impact of child-feeding practices (e.g. repeated food exposure) in increasing child vegetable intake. Thirteen trials examined the impact of parent nutrition education in increasing child fruit and vegetable intake. Eight studies examined the impact of multicomponent interventions (e.g. parent nutrition education and preschool policy changes) in increasing child fruit and vegetable intake. One study examined the effect of a nutrition intervention delivered to children in increasing child fruit and vegetable intake.We judged 14 of the 55 included trials as free from high risks of bias across all domains; performance, detection and attrition bias were the most common domains judged at high risk of bias for the remaining studies.Meta-analysis of trials examining child-feeding practices versus no intervention revealed a positive effect on child vegetable consumption (SMD 0.38, 95% confidence interval (CI) 0.15 to 0.61; n = 1509; 11 studies; very low-quality evidence), equivalent to a mean difference of 4.03 g of vegetables. There were no short-term differences in child consumption of fruit and vegetables in meta-analyses of trials examining parent nutrition education versus no intervention (SMD 0.11, 95% CI -0.05 to 0.28; n = 3023; 10 studies; very low-quality evidence) or multicomponent interventions versus no intervention (SMD 0.28, 95% CI -0.06 to 0.63; n = 1861; 4 studies; very low-quality evidence).Insufficient data were available to assess long-term effectiveness, cost effectiveness and unintended adverse consequences of interventions. Studies reported receiving governmental or charitable funds, except for three studies reporting industry funding. AUTHORS' CONCLUSIONS: Despite identifying 55 eligible trials of various intervention approaches, the evidence for how to increase children's fruit and vegetable consumption remains sparse. There was very low-quality evidence that child-feeding practice interventions are effective in increasing vegetable consumption in children aged five years and younger, however the effect size was very small and long-term follow-up is required. There was very low-quality evidence that parent nutrition education and multicomponent interventions are not effective in increasing fruit and vegetable consumption in children aged five years and younger. All findings should be considered with caution, given most included trials could not be combined in meta-analyses. Given the very low-quality evidence, future research will very likely change estimates and conclusions. Such research should adopt more rigorous methods to advance the field.This is a living systematic review. Living systematic reviews offer a new approach to review updating, in which the review is continually updated, incorporating relevant new evidence as it becomes available. Please refer to the Cochrane Database of Systematic Reviews for the current status of this review.

Interventions for increasing fruit and vegetable consumption in children aged five years and under.

BACKGROUND: Insufficient consumption of fruits and vegetables in childhood increases the risk of future non-communicable diseases, including cardiovascular disease. Interventions to increase consumption of fruit and vegetables, such as those focused on specific child-feeding strategies and parent nutrition education interventions in early childhood may therefore be an effective strategy in reducing this disease burden. OBJECTIVES: To assess the effectiveness, cost effectiveness and associated adverse events of interventions designed to increase the consumption of fruit, vegetables or both amongst children aged five years and under. SEARCH METHODS: We searched CENTRAL, MEDLINE, Embase and two clinical trials registries to identify eligible trials on 25 January 2018. We searched Proquest Dissertations and Theses in November 2017. We reviewed reference lists of included trials and handsearched three international nutrition journals. We contacted authors of included studies to identify further potentially relevant trials. SELECTION CRITERIA: We included randomised controlled trials, including cluster-randomised controlled trials and cross-over trials, of any intervention primarily targeting consumption of fruit, vegetables or both among children aged five years and under, and incorporating a dietary or biochemical assessment of fruit or vegetable consumption. Two review authors independently screened titles and abstracts of identified papers; a third review author resolved disagreements. DATA COLLECTION AND ANALYSIS: Two review authors independently extracted data and assessed the risks of bias of included studies; a third review author resolved disagreements. Due to unexplained heterogeneity, we used random-effects models in meta-analyses for the primary review outcomes where we identified sufficient trials. We calculated standardised mean differences (SMDs) to account for the heterogeneity of fruit and vegetable consumption measures. We conducted assessments of risks of bias and evaluated the quality of evidence (GRADE approach) using Cochrane procedures. MAIN RESULTS: We included 63 trials with 178 trial arms and 11,698 participants. Thirty-nine trials examined the impact of child-feeding practices (e.g. repeated food exposure) in increasing child vegetable intake. Fourteen trials examined the impact of parent nutrition education in increasing child fruit and vegetable intake. Nine studies examined the impact of multicomponent interventions (e.g. parent nutrition education and preschool policy changes) in increasing child fruit and vegetable intake. One study examined the effect of a nutrition education intervention delivered to children in increasing child fruit and vegetable intake.We judged 14 of the 63 included trials as free from high risks of bias across all domains; performance, detection and attrition bias were the most common domains judged at high risk of bias for the remaining studies.There is very low quality evidence that child-feeding practices versus no intervention may have a small positive effect on child vegetable consumption equivalent to an increase of 3.50 g as-desired consumption of vegetables (SMD 0.33, 95% CI 0.13 to 0.54; participants = 1741; studies = 13). Multicomponent interventions versus no intervention may have a very small effect on child consumption of fruit and vegetables (SMD 0.35, 95% CI 0.04 to 0.66; participants = 2009; studies = 5; low-quality evidence), equivalent to an increase of 0.37 cups of fruit and vegetables per day. It is uncertain whether there are any short-term differences in child consumption of fruit and vegetables in meta-analyses of trials examining parent nutrition education versus no intervention (SMD 0.12, 95% CI -0.03 to 0.28; participants = 3078; studies = 11; very low-quality evidence).Insufficient data were available to assess long-term effectiveness, cost effectiveness and unintended adverse consequences of interventions. Studies reported receiving governmental or charitable funds, except for four studies reporting industry funding. AUTHORS' CONCLUSIONS: Despite identifying 63 eligible trials of various intervention approaches, the evidence for how to increase children's fruit and vegetable consumption remains limited. There was very low- and low-quality evidence respectively that child-feeding practice and multicomponent interventions may lead to very small increases in fruit and vegetable consumption in children aged five years and younger. It is uncertain whether parent nutrition education interventions are effective in increasing fruit and vegetable consumption in children aged five years and younger. Given that the quality of the evidence is very low or low, future research will likely change estimates and conclusions. Long-term follow-up is required and future research should adopt more rigorous methods to advance the field.This is a living systematic review. Living systematic reviews offer a new approach to review updating, in which the review is continually updated, incorporating relevant new evidence as it becomes available. Please refer to the Cochrane Database of Systematic Reviews for the current status of this review.

Strategies to improve the implementation of workplace-based policies or practices targeting tobacco, alcohol, diet, physical activity and obesity.

BACKGROUND: Given the substantial period of time adults spend in their workplaces each day, these provide an opportune setting for interventions addressing modifiable behavioural risk factors for chronic disease. Previous reviews of trials of workplace-based interventions suggest they can be effective in modifying a range of risk factors including diet, physical activity, obesity, risky alcohol use and tobacco use. However, such interventions are often poorly implemented in workplaces, limiting their impact on employee health. Identifying strategies that are effective in improving the implementation of workplace-based interventions has the potential to improve their effects on health outcomes. OBJECTIVES: To assess the effects of strategies for improving the implementation of workplace-based policies or practices targeting diet, physical activity, obesity, tobacco use and alcohol use.Secondary objectives were to assess the impact of such strategies on employee health behaviours, including dietary intake, physical activity, weight status, and alcohol and tobacco use; evaluate their cost-effectiveness; and identify any unintended adverse effects of implementation strategies on workplaces or workplace staff. SEARCH METHODS: We searched the following electronic databases on 31 August 2017: CENTRAL; MEDLINE; MEDLINE In Process; the Campbell Library; PsycINFO; Education Resource Information Center (ERIC); Cumulative Index to Nursing and Allied Health Literature (CINAHL); and Scopus. We also handsearched all publications between August 2012 and September 2017 in two speciality journals: Implementation Science and Journal of Translational Behavioral Medicine. We conducted searches up to September 2017 in Dissertations and Theses, the WHO International Clinical Trials Registry Platform, and the US National Institutes of Health Registry. We screened the reference lists of included trials and contacted authors to identify other potentially relevant trials. We also consulted experts in the field to identify other relevant research. SELECTION CRITERIA: Implementation strategies were defined as strategies specifically employed to improve the implementation of health interventions into routine practice within specific settings. We included any trial with a parallel control group (randomised or non-randomised) and conducted at any scale that compared strategies to support implementation of workplace policies or practices targeting diet, physical activity, obesity, risky alcohol use or tobacco use versus no intervention (i.e. wait-list, usual practice or minimal support control) or another implementation strategy. Implementation strategies could include those identified by the Effective Practice and Organisation of Care (EPOC) taxonomy such as quality improvement initiatives and education and training, as well as other strategies. Implementation interventions could target policies or practices directly instituted in the workplace environment, as well as workplace-instituted efforts encouraging the use of external health promotion services (e.g. gym membership subsidies). DATA COLLECTION AND ANALYSIS: Review authors working in pairs independently performed citation screening, data extraction and 'Risk of bias' assessment, resolving disagreements via consensus or a third reviewer. We narratively synthesised findings for all included trials by first describing trial characteristics, participants, interventions and outcomes. We then described the effect size of the outcome measure for policy or practice implementation. We performed meta-analysis of implementation outcomes for trials of comparable design and outcome. MAIN RESULTS: We included six trials, four of which took place in the USA. Four trials employed randomised controlled trial (RCT) designs. Trials were conducted in workplaces from the manufacturing, industrial and services-based sectors. The sample sizes of workplaces ranged from 12 to 114. Workplace policies and practices targeted included: healthy catering policies; point-of-purchase nutrition labelling; environmental supports for healthy eating and physical activity; tobacco control policies; weight management programmes; and adherence to guidelines for staff health promotion. All implementation interventions utilised multiple implementation strategies, the most common of which were educational meetings, tailored interventions and local consensus processes. Four trials compared an implementation strategy intervention with a no intervention control, one trial compared different implementation interventions, and one three-arm trial compared two implementation strategies with each other and a control. Four trials reported a single implementation outcome, whilst the other two reported multiple outcomes. Investigators assessed outcomes using surveys, audits and environmental observations. We judged most trials to be at high risk of performance and detection bias and at unclear risk of reporting and attrition bias.Of the five trials comparing implementation strategies with a no intervention control, pooled analysis was possible for three RCTs reporting continuous score-based measures of implementation outcomes. The meta-analysis found no difference in standardised effects (standardised mean difference (SMD) -0.01, 95% CI -0.32 to 0.30; 164 participants; 3 studies; low certainty evidence), suggesting no benefit of implementation support in improving policy or practice implementation, relative to control. Findings for other continuous or dichotomous implementation outcomes reported across these five trials were mixed. For the two non-randomised trials examining comparative effectiveness, both reported improvements in implementation, favouring the more intensive implementation group (very low certainty evidence). Three trials examined the impact of implementation strategies on employee health behaviours, reporting mixed effects for diet and weight status (very low certainty evidence) and no effect for physical activity (very low certainty evidence) or tobacco use (low certainty evidence). One trial reported an increase in absolute workplace costs for health promotion in the implementation group (low certainty evidence). None of the included trials assessed adverse consequences. Limitations of the review included the small number of trials identified and the lack of consistent terminology applied in the implementation science field, which may have resulted in us overlooking potentially relevant trials in the search. AUTHORS' CONCLUSIONS: Available evidence regarding the effectiveness of implementation strategies for improving implementation of health-promoting policies and practices in the workplace setting is sparse and inconsistent. Low certainty evidence suggests that such strategies may make little or no difference on measures of implementation fidelity or different employee health behaviour outcomes. It is also unclear if such strategies are cost-effective or have potential unintended adverse consequences. The limited number of trials identified suggests implementation research in the workplace setting is in its infancy, warranting further research to guide evidence translation in this setting.

Economic evaluation of telephone-based weight loss support for patients with knee osteoarthritis: a randomised controlled trial.

BACKGROUND: The prevalence of knee osteoarthritis is increasing worldwide. Obesity is an important modifiable risk factor for both the incidence and progression of knee osteoarthritis. Consequently, international guidelines recommend all patients with knee osteoarthritis who are overweight receive support to lose weight. However, few overweight patients with this condition receive care to support weight loss. Telephone-based interventions are one potential solution to provide scalable care to the many patients with knee osteoarthritis. The objective of this study is to evaluate, from a societal perspective, the cost-utility and cost-effectiveness of a telephone-based weight management and healthy lifestyle service for patients with knee osteoarthritis, who are overweight or obese. METHODS: An economic evaluation was undertaken alongside a pragmatic randomised controlled trial. Between May 19 and June 30, 2015, 120 patients with knee osteoarthritis were randomly assigned to an intervention or usual care control group in a 1:1 ratio. Participants in the intervention group received a referral to an existing non-disease specific 6-month telephone-based weight management and healthy lifestyle service. Quality-adjusted life years (QALYs) was the utility measure and knee pain intensity, disability, weight, and body mass index (BMI) were the clinical measures of effect. Costs included intervention costs, healthcare utilisation costs (healthcare services and medication use) and absenteeism costs due to knee pain. Data was collected at baseline, 6 weeks and 26 weeks. The primary cost-effectiveness analysis was performed from the societal perspective. RESULTS: Mean cost differences between groups (intervention minus control) were $493 (95%CI: -3513 to 5363) for healthcare costs, $-32 (95%CI: -73 to 13) for medication costs, and $125 (95%CI: -151 to 486) for absenteeism costs. The total mean difference in societal costs was $1197 (95%CI: -2887 to 6106). For QALYs and all clinical measures of effect, the probability of the intervention being cost-effective compared with usual care was less than 0.36 at all willingness-to-pay values. CONCLUSIONS: From a societal perspective, telephone-based weight loss support, provided using an existing non-disease specific 6-month weight management and healthy lifestyle service was not cost-effective in comparison with usual care for overweight and obese patients with knee osteoarthritis. TRIAL REGISTRATION NUMBER: ACTRN12615000490572 , registered 18th May 2015.

Interventions for increasing fruit and vegetable consumption in children aged five years and under.

BACKGROUND: Insufficient consumption of fruits and vegetables in childhood increases the risk of future chronic diseases, including cardiovascular disease. OBJECTIVES: To assess the effectiveness, cost effectiveness and associated adverse events of interventions designed to increase the consumption of fruit, vegetables or both amongst children aged five years and under. SEARCH METHODS: We searched the Cochrane Central Register of Controlled Trials (CENTRAL) in the Cochrane Library, MEDLINE, Embase Classic and Embase to identify eligible trials on 30 September 2016. We searched CINAHL and PsycINFO in July 2016, Proquest Dissertations and Theses in November 2016 and three clinical trial registers in November 2016 and June 2017. We reviewed reference lists of included trials and handsearched three international nutrition journals. We contacted authors of included studies to identify further potentially relevant trials. SELECTION CRITERIA: We included randomised controlled trials, including cluster-randomised controlled trials and cross-over trials, of any intervention primarily targeting consumption of fruit, vegetables or both among children aged five years and under, and incorporating a dietary or biochemical assessment of fruit or vegetable consumption. Two review authors independently screened titles and abstracts of identified papers; a third review author resolved disagreements. DATA COLLECTION AND ANALYSIS: Two review authors independently extracted data and assessed the risks of bias of included studies; a third review author resolved disagreements. Due to unexplained heterogeneity, we used random-effects models in meta-analyses for the primary review outcomes where we identified sufficient trials. We calculated standardised mean differences (SMDs) to account for the heterogeneity of fruit and vegetable consumption measures.We conducted assessments of risks of bias and evaluated the quality of evidence (GRADE approach) using Cochrane procedures. MAIN RESULTS: We included 50 trials with 137 trial arms and 10,267 participants. Thirty trials examined the impact of child-feeding practices (e.g. repeated food exposure) in increasing child vegetable intake. Eleven trials examined the impact of parent nutrition education in increasing child fruit and vegetable intake. Eight studies examined the impact of multicomponent interventions (e.g. parent nutrition education and preschool policy changes) in increasing child fruit and vegetable intake. One study examined the effect of a nutrition intervention delivered to children in increasing child fruit and vegetable intake.Thirteen of the 50 included trials were judged as free from high risks of bias across all domains; performance, detection and attrition bias were the most common domains judged at high risk of bias of remaining studies.Meta-analysis of trials examining child-feeding practices versus no intervention revealed a positive effect on child vegetable consumption (SMD 0.38, 95% CI 0.15 to 0.61; n = 1509; 11 studies; very low-quality evidence), equivalent to a mean difference of 4.03 grams of vegetables. There were no short-term differences in child consumption of fruit and vegetables in meta-analyses of trials examining parent nutrition education versus no intervention (SMD 0.11, 95% CI -0.05 to 0.28; n = 3023; 10 studies; very low-quality evidence) or multicomponent interventions versus no intervention (SMD 0.28, 95% CI -0.06 to 0.63; n = 1861; 4 studies; very low-quality evidence).Insufficient data were available to assess long-term effectiveness, cost effectiveness and unintended adverse consequences of interventions.Studies reported receiving governmental or charitable funds, except for two studies reporting industry funding. AUTHORS' CONCLUSIONS: Despite identifying 50 eligible trials of various intervention approaches, the evidence for how to increase fruit and vegetable consumption of children remains sparse. There was very low-quality evidence child-feeding practice interventions are effective in increasing vegetable consumption of children aged five years and younger, however the effect size was very small and long-term follow-up is required. There was very low-quality evidence that parent nutrition education and multicomponent interventions are not effective in increasing fruit and vegetable consumption of children aged five years and younger. All findings should be considered with caution, given most included trials could not be combined in meta-analyses. Given the very low-quality evidence, future research will very likely change estimates and conclusions. Such research should adopt more rigorous methods to advance the field.This is a living systematic review. Living systematic reviews offer a new approach to review updating, in which the review is continually updated, incorporating relevant new evidence as it becomes available. Please refer to the Cochrane Database of Systematic Reviews for the current status of this review.

Strategies for enhancing the implementation of school-based policies or practices targeting risk factors for chronic disease.

BACKGROUND: A number of school-based policies or practices have been found to be effective in improving child diet and physical activity, and preventing excessive weight gain, tobacco or harmful alcohol use. Schools, however, frequently fail to implement such evidence-based interventions. OBJECTIVES: The primary aims of the review are to examine the effectiveness of strategies aiming to improve the implementation of school-based policies, programs or practices to address child diet, physical activity, obesity, tobacco or alcohol use.Secondary objectives of the review are to: Examine the effectiveness of implementation strategies on health behaviour (e.g. fruit and vegetable consumption) and anthropometric outcomes (e.g. BMI, weight); describe the impact of such strategies on the knowledge, skills or attitudes of school staff involved in implementing health-promoting policies, programs or practices; describe the cost or cost-effectiveness of such strategies; and describe any unintended adverse effects of strategies on schools, school staff or children. SEARCH METHODS: All electronic databases were searched on 16 July 2017 for studies published up to 31 August 2016. We searched the following electronic databases: Cochrane Library including the Cochrane Central Register of Controlled Trials (CENTRAL); MEDLINE; MEDLINE In-Process & Other Non-Indexed Citations; Embase Classic and Embase; PsycINFO; Education Resource Information Center (ERIC); Cumulative Index to Nursing and Allied Health Literature (CINAHL); Dissertations and Theses; and SCOPUS. We screened reference lists of all included trials for citations of other potentially relevant trials. We handsearched all publications between 2011 and 2016 in two specialty journals (Implementation Science and Journal of Translational Behavioral Medicine) and conducted searches of the WHO International Clinical Trials Registry Platform (ICTRP) (http://apps.who.int/trialsearch/) as well as the US National Institutes of Health registry (https://clinicaltrials.gov). We consulted with experts in the field to identify other relevant research. SELECTION CRITERIA: 'Implementation' was defined 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 or non-randomised) 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 school staff to 'no intervention', 'usual' practice or a different implementation strategy. DATA COLLECTION AND ANALYSIS: Citation screening, data extraction and assessment of risk of bias was performed by review authors in pairs. Disagreements between review authors were resolved via consensus, or if required, by a third author. Considerable trial heterogeneity precluded meta-analysis. We narratively synthesised trial findings by describing the effect size of the primary outcome measure for policy or practice implementation (or the median of such measures where a single primary outcome was not stated). MAIN RESULTS: We included 27 trials, 18 of which were conducted in the USA. Nineteen studies employed randomised controlled trial (RCT) designs. Fifteen trials tested strategies to implement healthy eating policies, practice or programs; six trials tested strategies targeting physical activity policies or practices; and three trials targeted tobacco policies or practices. Three trials targeted a combination of risk factors. None of the included trials sought to increase the implementation of interventions to delay initiation or reduce the consumption of alcohol. All trials examined multi-strategic implementation strategies and no two trials examined the same combinations of implementation strategies. The most common implementation strategies included educational materials, educational outreach and educational meetings. For all outcomes, the overall quality of evidence was very low and the risk of bias was high for the majority of trials for detection and performance bias.Among 13 trials reporting dichotomous implementation outcomes-the proportion of schools or school staff (e.g. classes) implementing a targeted policy or practice-the median unadjusted (improvement) effect sizes ranged from 8.5% to 66.6%. Of seven trials reporting the percentage of a practice, program or policy that had been implemented, the median unadjusted effect (improvement), relative to the control ranged from -8% to 43%. The effect, relative to control, reported in two trials assessing the impact of implementation strategies on the time per week teachers spent delivering targeted policies or practices ranged from 26.6 to 54.9 minutes per week. Among trials reporting other continuous implementation outcomes, findings were mixed. Four trials were conducted of strategies that sought to achieve implementation 'at scale', that is, across samples of at least 50 schools, of which improvements in implementation were reported in three trials.The impact of interventions on student health behaviour or weight status were mixed. Three of the eight trials with physical activity outcomes reported no significant improvements. Two trials reported reductions in tobacco use among intervention relative to control. Seven of nine trials reported no between-group differences on student overweight, obesity or adiposity. Positive improvements in child dietary intake were generally reported among trials reporting these outcomes. Three trials assessed the impact of implementation strategies on the attitudes of school staff and found mixed effects. Two trials specified in the study methods an assessment of potential unintended adverse effects, of which, they reported none. One trial reported implementation support did not significantly increase school revenue or expenses and another, conducted a formal economic evaluation, reporting the intervention to be cost-effective. Trial heterogeneity, and the lack of consistent terminology describing implementation strategies, were important limitations of the review. AUTHORS' CONCLUSIONS: Given the very low quality of the available evidence, it is uncertain whether the strategies tested improve implementation of the targeted school-based policies or practices, student health behaviours, or the knowledge or attitudes of school staff. It is also uncertain if strategies to improve implementation are cost-effective or if they result in unintended adverse consequences. Further research is required to guide efforts to facilitate the translation of evidence into practice in this setting.