Prevention of childhood obesity is an international public health priority given the significant impact of obesity on acute and chronic diseases, general health, development and well-being. The international evidence base for strategies that governments, communities and families can implement to prevent obesity, and promote health, has been accumulating but remains unclear. This review primarily aims to update the previous Cochrane review of childhood obesity prevention research and determine the effectiveness of evaluated interventions intended to prevent obesity in children, assessed by change in Body Mass Index (BMI). Secondary aims were to examine the characteristics of the programs and strategies to answer the questions "What works for whom, why and for what cost?" The searches were re-run in CENTRAL, MEDLINE, EMBASE, PsychINFO and CINAHL in March 2010 and searched relevant websites. Non-English language papers were included and experts were contacted. The review includes data from childhood obesity prevention studies that used a controlled study design (with or without randomisation). Studies were included if they evaluated interventions, policies or programs in place for twelve weeks or more. If studies were randomised at a cluster level, 6 clusters were required. Two review authors independently extracted data and assessed the risk of bias of included studies. Data was extracted on intervention implementation, cost, equity and outcomes. Outcome measures were grouped according to whether they measured adiposity, physical activity (PA)-related behaviours or diet-related behaviours. Adverse outcomes were recorded. A meta-analysis was conducted using available BMI or standardised BMI (zBMI) score data with subgroup analysis by age group (0-5, 6-12, 13-18 years, corresponding to stages of developmental and childhood settings). This review includes 55 studies (an additional 36 studies found for this update). The majority of studies targeted children aged 6-12 years. The meta-analysis included 37 studies of 27,946 children and demonstrated that programmes were effective at reducing adiposity, although not all individual interventions were effective, and there was a high level of observed heterogeneity (I(2)=82%). Overall, children in the intervention group had a standardised mean difference in adiposity (measured as BMI or zBMI) of -0.15kg/m(2) (95% confidence interval (CI): -0.21 to -0.09). Intervention effects by age subgroups were -0.26kg/m(2) (95% CI:-0.53 to 0.00) (0-5 years), -0.15kg/m(2) (95% CI -0.23 to -0.08) (6-12 years), and -0.09kg/m(2) (95% CI -0.20 to 0.03) (13-18 years). Heterogeneity was apparent in all three age groups and could not explained by randomisation status or the type, duration or setting of the intervention. Only eight studies reported on adverse effects and no evidence of adverse outcomes such as unhealthy dieting practices, increased prevalence of underweight or body image sensitivities was found. Interventions did not appear to increase health inequalities although this was examined in fewer studies. We found strong evidence to support beneficial effects of child obesity prevention programmes on BMI, particularly for programmes targeted to children aged six to 12 years. However, given the unexplained heterogeneity and the likelihood of small study bias, these findings must be interpreted cautiously. A broad range of programme components were used in these studies and whilst it is not possible to distinguish which of these components contributed most to the beneficial effects observed, our synthesis indicates the following to be promising policies and strategies:· school curriculum that includes healthy eating, physical activity and body image· increased sessions for physical activity and the development of fundamental movement skills throughout the school week· improvements in nutritional quality of the food supply in schools· environments and cultural practices that support children eating healthier foods and being active throughout each day· support for teachers and other staff to implement health promotion strategies and activities (e.g. professional development, capacity building activities)· parent support and home activities that encourage children to be more active, eat more nutritious foods and spend less time in screen based activitiesHowever, study and evaluation designs need to be strengthened, and reporting extended to capture process and implementation factors, outcomes in relation to measures of equity, longer term outcomes, potential harms and costs.Childhood obesity prevention research must now move towards identifying how effective intervention components can be embedded within health, education and care systems and achieve long term sustainable impacts.

Prevention of childhood obesity is an international public health priority given the significant impact of obesity on acute and chronic diseases, general health, development and well-being. The international evidence base for strategies to prevent obesity is very large and is accumulating rapidly. This is an update of a previous review. To determine the effectiveness of a range of interventions that include diet or physical activity components, or both, designed to prevent obesity in children. We searched CENTRAL, MEDLINE, Embase, PsychINFO and CINAHL in June 2015. We re-ran the search from June 2015 to January 2018 and included a search of trial registers. Randomised controlled trials (RCTs) of diet or physical activity interventions, or combined diet and physical activity interventions, for preventing overweight or obesity in children (0-17 years) that reported outcomes at a minimum of 12 weeks from baseline. Two authors independently extracted data, assessed risk-of-bias and evaluated overall certainty of the evidence using GRADE. We extracted data on adiposity outcomes, sociodemographic characteristics, adverse events, intervention process and costs. We meta-analysed data as guided by the Cochrane Handbook for Systematic Reviews of Interventions and presented separate meta-analyses by age group for child 0 to 5 years, 6 to 12 years, and 13 to 18 years for zBMI and BMI. We included 153 RCTs, mostly from the USA or Europe. Thirteen studies were based in upper-middle-income countries (UMIC: Brazil, Ecuador, Lebanon, Mexico, Thailand, Turkey, US-Mexico border), and one was based in a lower middle-income country (LMIC: Egypt). The majority (85) targeted children aged 6 to 12 years.Children aged 0-5 years: There is moderate-certainty evidence from 16 RCTs (n = 6261) that diet combined with physical activity interventions, compared with control, reduced BMI (mean difference (MD) -0.07 kg/m2, 95% confidence interval (CI) -0.14 to -0.01), and had a similar effect (11 RCTs, n = 5536) on zBMI (MD -0.11, 95% CI -0.21 to 0.01). Neither diet (moderate-certainty evidence) nor physical activity interventions alone (high-certainty evidence) compared with control reduced BMI (physical activity alone: MD -0.22 kg/m2, 95% CI -0.44 to 0.01) or zBMI (diet alone: MD -0.14, 95% CI -0.32 to 0.04; physical activity alone: MD 0.01, 95% CI -0.10 to 0.13) in children aged 0-5 years.Children aged 6 to 12 years: There is moderate-certainty evidence from 14 RCTs (n = 16,410) that physical activity interventions, compared with control, reduced BMI (MD -0.10 kg/m2, 95% CI -0.14 to -0.05). However, there is moderate-certainty evidence that they had little or no effect on zBMI (MD -0.02, 95% CI -0.06 to 0.02). There is low-certainty evidence from 20 RCTs (n = 24,043) that diet combined with physical activity interventions, compared with control, reduced zBMI (MD -0.05 kg/m2, 95% CI -0.10 to -0.01). There is high-certainty evidence that diet interventions, compared with control, had little impact on zBMI (MD -0.03, 95% CI -0.06 to 0.01) or BMI (-0.02 kg/m2, 95% CI -0.11 to 0.06).Children aged 13 to 18 years: There is very low-certainty evidence that physical activity interventions, compared with control reduced BMI (MD -1.53 kg/m2, 95% CI -2.67 to -0.39; 4 RCTs; n = 720); and low-certainty evidence for a reduction in zBMI (MD -0.2, 95% CI -0.3 to -0.1; 1 RCT; n = 100). There is low-certainty evidence from eight RCTs (n = 16,583) that diet combined with physical activity interventions, compared with control, had no effect on BMI (MD -0.02 kg/m2, 95% CI -0.10 to 0.05); or zBMI (MD 0.01, 95% CI -0.05 to 0.07; 6 RCTs; n = 16,543). Evidence from two RCTs (low-certainty evidence; n = 294) found no effect of diet interventions on BMI.Direct comparisons of interventions: Two RCTs reported data directly comparing diet with either physical activity or diet combined with physical activity interventions for children aged 6 to 12 years and reported no differences.Heterogeneity was apparent in the results from all three age groups, which could not be entirely explained by setting or duration of the interventions. Where reported, interventions did not appear to result in adverse effects (16 RCTs) or increase health inequalities (gender: 30 RCTs; socioeconomic status: 18 RCTs), although relatively few studies examined these factors.Re-running the searches in January 2018 identified 315 records with potential relevance to this review, which will be synthesised in the next update. Interventions that include diet combined with physical activity interventions can reduce the risk of obesity (zBMI and BMI) in young children aged 0 to 5 years. There is weaker evidence from a single study that dietary interventions may be beneficial.However, interventions that focus only on physical activity do not appear to be effective in children of this age. In contrast, interventions that only focus on physical activity can reduce the risk of obesity (BMI) in children aged 6 to 12 years, and adolescents aged 13 to 18 years. In these age groups, there is no evidence that interventions that only focus on diet are effective, and some evidence that diet combined with physical activity interventions may be effective. Importantly, this updated review also suggests that interventions to prevent childhood obesity do not appear to result in adverse effects or health inequalities.The review will not be updated in its current form. To manage the growth in RCTs of child obesity prevention interventions, in future, this review will be split into three separate reviews based on child age.

Background: One out of ten of China's population are migrants, moving from rural to urban areas. Many leave their families behind resulting in millions of school children living in their rural home towns without one or both their parents. Little is known about the health status of these left behind children (LBC). This study compares the health status and health-related behaviours of left behind adolescent school children and their counterparts in a rural area in Southern China. Methods: A cross-sectional study was conducted among middle school students in Fuyang Township, Guangdong, China (2007-2008). Information about health behaviours, parental migration and demographic characteristics was collected using a self-administered questionnaire. Overweight/obesity and stunting were defined based on measurements of height and weight. Univariate and multivariate analyses were used to estimate the differences in health outcomes between LBC and non-LBC. Results: 18.1% of the schoolchildren had one or both parents working away from home. Multivariate analysis showed that male LBC were at higher risk of skipping breakfast, higher levels of physical inactivity, internet addiction, having ever smoked tobacco, suicide ideation, and being overweight. LBC girls were more likely to drink excessive amounts of sweetened beverage, to watch more TV, to have ever smoked or currently smoke tobacco, to have ever drunk alcohol and to binge drinking. They were also more likely to be unhappy, to think of planning suicide and consider leaving home. Conclusions: Our findings suggest that parental migration is a risk factor for unhealthy behaviours amongst adolescent school children in rural China. Further research is required in addition to the consideration of the implications for policies and programmes to protect LBC.

Purpose.: China is urbanizing rapidly, and the prevalence of myopia is high. This study was conducted to identify the reasons for observed differences in the prevalence of myopia among urban versus rural Chinese children. Methods.: All children with uncorrected acuity of 6/12 or worse and a 50% random sample of children with vision better than 6/12 at all secondary schools in mixed rural–urban Liangying Township, Guangdong, underwent cycloplegic refraction, and provided data on age, gender, parental education, weekly near work and time outdoors, and urban development level of respondents' neighborhoods (12-item questionnaire). Population density of 32 villages and urban zones in Liangying was calculated from census figures (mean population density, 217 persons/km²; range, 94–957; mean for Guangdong, 486). Results.: Among 5844 eligible children, 4612 (78.9%) had parental consent and completed examinations; 2957 were refracted per protocol, and 2480 (83.9%) of these had questionnaire data. Those with completed examinations were more likely to be girls (P < 0.001), and questionnaire respondents were more myopic (P = 0.02), but otherwise did not differ significantly from nonrespondents. In multivariate models, older age (P < 0.001), more near work (P = 0.02), and higher population density (P = 0.003), but not development index, parental education, or time outdoors were significantly associated with more myopic refractive error. Conclusions.: Higher population density appears to be associated with myopia risk, independent of academic activity, time spent outdoors, familial educational level, or economic development, factors that have been thought to explain higher myopia prevalence among urban children. Mechanisms for this apparent association should be sought.

Background: Community engagement plays a vital role in global immunization strategies, offering the potential to overcome vaccination hesitancy and enhance vaccination confidence. Although there is significant backing for community engagement in health promotion, the evidence supporting its effectiveness in vaccination promotion is fragmented and of uncertain quality. Objective: This review aims to systematically examine the effectiveness of different contents and extent of community engagement for promoting vaccination rates. Methods: This study was performed in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. A comprehensive and exhaustive literature search was performed in 4 English databases (PubMed, Embase, Web of Science, and Cochrane Library) and 2 Chinese databases (CNKI and Wan Fang) to identify all possible articles. Original research articles applying an experimental study design that investigated the effectiveness of community engagement in vaccination promotion were eligible for inclusion. Two reviewers independently performed the literature search, study selection, quality assessment, and data extraction. Discrepancies were resolved through discussion, with the arbitration of a third reviewer where necessary. Results: A total of 20 articles out of 11,404 records from 2006 to 2021 were retrieved. The studies used various designs: 12 applied single-group pre-post study designs, 5 were cluster randomized controlled trials (RCTs), and 3 were non-RCTs. These studies targeted multiple vaccines, with 8 focusing on children’s immunization, 8 on human papillomavirus vaccine, 3 on hepatitis B virus vaccine, and 1 on COVID-19 vaccine. The meta-analysis revealed significant increases in vaccination rates both in pre-post comparison (rate difference [RD] 0.34, 95% CI 0.21-0.47, I2=99.9%, P<.001) and between-group comparison (RD 0.18, 95% CI 0.07-0.29, I2=98.4%, P<.001). The meta-analysis revealed that participant recruitment had the largest effect size (RD 0.51, 95% CI 0.36-0.67, I2=99.9%, P<.001), followed by intervention development (RD 0.36, 95% CI 0.23-0.50, I2=100.0%, P<.001), intervention implementation (RD 0.35, 95% CI 0.22-0.47, I2=99.8%, P<.001), and data collection (RD 0.34, 95% CI 0.19-0.50, I2=99.8%, P<.001). The meta-analysis indicated that high community engagement extent yielded the largest effect size (RD 0.49, 95% CI 0.17-0.82, I2=100.0%, P<.001), followed by moderate community engagement extent (RD 0.45, 95% CI 0.33-0.58, I2=99.6%, P<.001) and low community engagement extent (RD 0.15, 95% CI 0.05-0.25, I2=99.2%, P<.001). The meta-analysis revealed that “health service support” demonstrated the largest effect sizes (RD 0.45, 95% CI 0.25-0.65, I2=99.9%, P<.001), followed by “health education and discussion” (RD 0.39, 95% CI 0.20-0.58, I2=99.7%, P<.001), “follow-up and reminder” (RD 0.33, 95% CI 0.23-0.42, I2=99.3%, P<.001), and “social marketing campaigns and community mobilization” (RD 0.24, 95% CI 0.06-0.41, I2=99.9%, P<.001). Conclusions: The results of this meta-analysis supported the effectiveness of community engagement in vaccination promotion with variations in terms of engagement contents and extent. Community engagement required a “fit-for-purpose” approach rather than a “one-size-fits-all” approach to maximize the effectiveness of vaccine promotion. Trial Registration: PROSPERO CRD42022339081; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=339081