NUTRITION RESEARCH PAPER TOPIC: Obesity among adolescents

What childhood obesity prevention programmes work? A systematic review and meta-analysis

Y. Wang1,2,3,4, L. Cai2,5, Y. Wu2,3, R. F. Wilson6, C. Weston6, O. Fawole6, S. N. Bleich6, L. J. Cheskin3, N. N. Showell7, B. D. Lau8, D. T. Chiu2, A. Zhang6, and J. Segal4,6

1Department of Epidemiology and Environmental Health (formerly the Department of Social and Preventive Medicine), School of Public Health and Health Professions, University at Buffalo, State University of New York, Buffalo, NY, USA

2Johns Hopkins Global Center on Childhood Obesity, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA

3Department of Health, Behavior and Society, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA

4Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA

5Department of Maternal and Child Health, School of Public Health, Sun Yat-Sen University, Guangzhou, China

6Department of Health Policy and Management, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA

7Division of General Pediatrics and Adolescent Medicine, Johns Hopkins School of Medicine, Baltimore, MD, USA

8Department of Surgery, Johns Hopkins University School of Medicine, Baltimore, MD, USA

Summary

Previous reviews of childhood obesity prevention have focused largely on schools and findings

have been inconsistent. Funded by the US Agency for Healthcare Research and Quality (AHRQ)

and the National Institutes of Health, we systematically evaluated the effectiveness of childhood

obesity prevention programmes conducted in high-income countries and implemented in various

settings. We searched MEDLINE®, Embase, PsycINFO, CINAHL®, ClinicalTrials.gov and the

Cochrane Library from inception through 22 April 2013 for relevant studies, including

Address for correspondence: Professor Y Wang, Department of Epidemiology and Environmental Health, School of Public Health and Health Professions, University at Buffalo, State University of New York, Kimball Tower 816, 3435 Main St., Buffalo, NY 14214-8028, USA., youfawan@buffalo.edu.

Conflict of interest statement No conflict of interest was declared.

Authors’ contributions Youfa Wang is the study’s principal investigator. RFW is the project manager. Yang Wu is the project coordinator. Study concept and design were contributed by Youfa Wang, JS, LJC, RFW and Yang Wu. All authors and some other research team members were responsible for acquisition of data. All authors participated in the analysis and interpretation of data. Youfa Wang, RFW, Yang Wu, JS and LC drafted the manuscript. All authors were responsible for the critical revision of the manuscript for important intellectual content. LC, OF, BDL, RFW and Youfa Wang performed statistical analysis. Youfa Wang, RFW and JS conducted administrative, technical or material support. Study supervision was provided by Youfa Wang and RFW.

HHS Public Access Author manuscript Obes Rev. Author manuscript; available in PMC 2015 September 07.

Published in final edited form as: Obes Rev. 2015 July ; 16(7): 547–565. doi:10.1111/obr.12277.

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randomized controlled trials, quasi-experimental studies and natural experiments, targeting diet,

physical activity or both, and conducted in children aged 2–18 in high-income countries. Two

reviewers independently abstracted the data. The strength of evidence (SOE) supporting

interventions was graded for each study setting (e.g. home, school). Meta-analyses were

performed on studies judged sufficiently similar and appropriate to pool using random effect

models. This paper reported our findings on various adiposity-related outcomes. We identified 147

articles (139 intervention studies) of which 115 studies were primarily school based, although

other settings could have been involved. Most were conducted in the United States and within the

past decade. SOE was high for physical activity-only interventions delivered in schools with home

involvement or combined diet–physical activity interventions delivered in schools with both home

and community components. SOE was moderate for school-based interventions targeting either

diet or physical activity, combined interventions delivered in schools with home or community

components or combined interventions delivered in the community with a school component. SOE

was low for combined interventions in childcare or home settings. Evidence was insufficient for

other interventions. In conclusion, at least moderately strong evidence supports the effectiveness

of school-based interventions for preventing childhood obesity. More research is needed to

evaluate programmes in other settings or of other design types, especially environmental, policy

and consumer health informatics-oriented interventions.

Keywords

Childhood; obesity; prevention; systematic review

Introduction

Childhood obesity persists as a serious threat to public health worldwide (1–5). In the United

States, over two-thirds of adults and one-third of children are overweight or obese.

Childhood obesity has many health consequences (6,7). Obesity is the result of biological,

behavioural, social, environmental and economic factors and the complex interactions

between them, which can produce a positive energy balance (8,9). Several leading health

organizations and expert panels, including the World Health Organization (10) and Institute

of Medicine (IOM), have recommended comprehensive interventions to combat childhood

obesity (11,12).

Some prior systematic reviews have summarized findings of childhood obesity prevention

studies (13–16); however, findings have been mixed and often limited either by the length of

follow-up, exclusively focusing on a specific intervention setting (e.g. school) or certain

outcomes (e.g. body mass index [BMI]), or by including only a small number of studies.

The present study aimed to systematically evaluate the effectiveness of all childhood obesity

prevention programmes implemented in various settings or designs (e.g. school, home,

primary care, childcare, community, consumer health informatics [CHI]) conducted in high-

income countries. Our original systematic review that served as the basis for the present

study was funded by the Agency for Healthcare Research and Quality (AHRQ) of the US

Department of Health and Human Services. Our full 835-page research report for AHRQ

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includes a literature review for six intervention settings and designs and was published in

June 2013 (17). (For the present study, we conducted a new literature search for studies

published after the completion of our AHRQ report and included them in analyses.) We

reviewed studies implemented in any setting (or design) that tested obesity prevention

interventions targeting diet, physical activity (PA) or a combination of both behaviours.

In our original AHRQ-funded study, we assessed various key outcomes including certain

adiposity-related measures, behaviours such as dietary consumption, PA and sedentary

behaviours, and some other health markers such as blood lipid levels and blood pressure.

The present study focuses on the effects of the interventions on adiposity outcomes and aims

to provide the variety of readers (e.g. researchers, health professionals and policy makers) a

refined, comprehensive review of findings to help guide future interventions and research,

particularly in children of high-income countries.

The present study provides new knowledge and possesses additional features and strengths

compared with previous reviews on childhood obesity prevention including our full AHRQ

report published in June 2013. This study is more encompassing as it included studies set in

various settings, it assessed a wide variety of outcome measures and it followed a rigorous

protocol – that required of AHRQ-funded comparative effectiveness reviews. More details

on our research methods and findings can be found in our full AHRQ report (17).

Methods

Our large research team consisted of epidemiologists, clinicians, nutritionists,

biostatisticians and health policy researchers from multiple institutions. We followed

standardized procedures developed by the AHRQ Effective Healthcare Program and

benefited from the input of experts in the field, with the AHRQ and other stakeholders,

throughout the project’s stages. For example, we developed our key questions (KQs) with

the input of a key informant panel that included experts in childhood nutrition policy,

academic clinicians treating obese children, representatives from public school systems,

parents of obese children, representatives from professional societies focusing on nutrition

and obesity, and AHRQ staff. In addition, we also formed a technical expert panel of leading

experts and other stakeholders in the field, which provided input on the development of our

study protocol. Our full report was reviewed by both experts and the public and

improvements were made based on their feedback. Additional details are provided in the full

AHRQ manuscript (17).

Search strategy and selection criteria

We searched MEDLINE®, EMBASE®, PsycINFO, CINAHL® and the Cochrane Library

from inception through 22 April 2013. We developed a search strategy based on medical

subject heading (MeSH®) terms and the text of key articles we had identified a priori. We

reviewed the reference lists of all included articles and all pertinent review articles to

identify articles the database searches may have missed. We uploaded all articles into

DistillerSR (Evidence Partners, Ottawa, Ontario, Canada), a web-based software application

developed for systematic review and data management. We also conducted a grey literature

search in ClinicalTrials.gov to identify relevant unpublished research through 23 July 2012.

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We identified studies conducted in high-income countries, defined as those with a very high

human development index (18), that evaluated interventions to prevent obesity (or

‘excessive weight gain’) in children aged 2–18 years. We only included randomized

controlled trials (RCTs), quasi-experimental studies and natural experiments that reported

intervention effects on adiposity-related outcomes. The studies also needed to follow

participants for at least 1 year from baseline measures, or for six or more months in school-

based interventions (considering the length of the school year). Studies targeting only

overweight or obese children or children with medical conditions (e.g. diabetes) were

excluded.

Data extraction

Two independent reviewers conducted title, abstract and full article reviews to assess

inclusion eligibility. Standardized forms were used for data abstraction. Each article was

double reviewed during this phase: the second reviewer confirmed or corrected the first

reviewer’s data abstractions for completeness and accuracy. Information on the study

characteristics, subjects, eligibility criteria, intervention components, outcome measures and

method of ascertainment regarding body weight status were abstracted.

Primary adiposity-related outcomes of interest were BMI, BMI z-score, BMI percentile,

waist circumference (WC), percent body fat (%BF), skin-fold thickness and prevalence of

overweight or obesity. Secondary outcomes (not reported on in this paper) were intermediate

behavioural outcomes (i.e. dietary intakes, PA and sedentary behaviours) and obesity-related

clinical outcomes (e.g. blood pressure and blood lipid levels).

Quality (risk of bias) assessment of individual studies

Two independent reviewers used the Downs and Black Checklist for Measuring Quality,

summarized here, to assess risk of study bias (ROB) for each included study (19): (i) low

ROB: when a study fulfilled all of the following: clearly stated the objective, described the

main outcomes, described the characteristics of the enrolled subjects, clearly described the

interventions, described the main findings, randomized the subjects to the intervention

group, concealed the intervention assignment until recruitment was complete and had at

least partially described the distributions of (potential) confounders in each treatment group;

(ii) moderate ROB: if a study did not fulfil one of the aforementioned items, or if such could

not be verified and (iii) high ROB: if a study did not fulfil more than one of the

aforementioned items.

Data synthesis

For each intervention setting, we created a set of detailed evidence tables containing the

information extracted from all eligible studies fitting that setting (or design). We aggregated

the studies by the primary setting where the interventions took place. Within each setting,

we grouped the interventions into three groups by strategy: (i) ‘diet-only interventions’,

those who aimed to alter dietary intake only; (ii) ‘PA-only interventions’, those who aimed

to increase PA and/or reduce sedentary activity only and (iii) ‘diet–PA combined

interventions’, those who targeted both diet and PA for change.

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When more than three comparable studies were available for a given intervention strategy

and setting(s), we conducted meta-analyses using STATA (version 11.0; Stata Corp.,

College Station, TX, USA). We used random-effect models applying the DerSimonian and

Laird approach due to the heterogeneity present among studies (20). A study was not

included in the meta-analysis if it (i) was not an RCT; (ii) induced substantial heterogeneity

when included in the analysis (i.e. I2 >50% or P-value <0.1 from chi-square tests assessing

the heterogeneity of effect sizes across interventions) or (iii) did not report sufficient data.

Strength of the body of evidence

We graded the quantity, quality and consistency of the best available evidence of

interventions for each setting by adapting an evidence-grading scheme recommended in the

Methods Guide for Conducting Comparative Effectiveness Reviews (21). We assigned

grades for all adiposity-related outcomes by first constructing a hierarchy of outcomes.

Using the hierarchy, each study contributed only one (the highest ranked) adiposity-related

measure for grading. We considered four domains in our evaluation of strength of evidence

(SOE): ROB, direction of the body of evidence, consistency of outcomes across studies and

precision of the pooled estimate or individual study estimates.

We determined an overall ROB for each setting and intervention target (i.e. diet, PA or both)

combination based on where most studies in their respective groupings fell. We decided that

all of the included studies provided evidence of a direct effect. We considered the body of

studies to be consistent in direction if more than 70% of the studies in a grouping had an

effect in the same direction. We considered an individual study to be precise if the results for

the given outcome were significant (P < 0.05) or if estimates had narrow confidence

intervals (CI) that excluded the null. If more than 70% of the individual studies were precise,

we considered the body of evidence to be precise.

SOE was classified into four categories: (i) ‘high’, indicating high confidence that the

evidence reflects the true effect and further research is very unlikely to change our

confidence in the estimate of the effect; (ii) ‘moderate’, indicating moderate confidence and

further research may change our confidence and the estimate; (iii) ‘low’, meaning low

confidence and further research is likely to change our confidence and the estimate and (iv)

‘insufficient’, reflecting that either a body of evidence is unavailable or there was only one

study for this setting and it had moderate or high ROB.

Results

Results of the literature search and intervention studies

We identified 42,221 unique citations, which resulted in 7,392 abstracts and, later, 677

articles after screening. A final 139 intervention studies described in 147 articles (21.7%)

met our inclusion criteria (Fig. 1). This included 115 studies that assessed school-based

interventions, six home-based interventions, three primary care-based interventions, five

child care-based interventions and 10 community-based interventions. Seven studies were

interventions using CHI, which we combined and described under other intervention settings

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(see Fig. 1, Appendix A, Table 1). None of the unpublished studies met our selection

criteria.

The majority of the 139 studies (104 or 75%) evaluated diet–PA combined interventions, 28

evaluated PA-only interventions and seven evaluated diet-only interventions (Table 2). As

described in detail below, 76 of the 115 studies (66%) evaluating school-based interventions

showed favourable intervention effects on adiposity-related outcomes, but only 42 of them

(36%) were statistically significant. None of the home-based studies reported statistically

significant favourable results. One out of three (33%) primary care-based studies, two out of

five (40%) child care-based studies and five out of 10 (50%) community-based studies

reported significant and favourable effects on adiposity-related outcomes (Table 2). Multi-

setting studies had statistically significant favourable results more often than single-setting

studies (44 vs. 35%) (Table 3).

Effectiveness of school-based interventions

School only-based interventions—Sixty-one studies (60,576 participants) took place in a school-only setting, including 40 RCTs and 21 non-RCTs. Most enrolled elementary or

middle school-aged children. Three RCTs, described in four articles, evaluated diet-only

interventions (22–25) and showed a decrease in BMIs or BMI z-scores. They were designed

to prevent weight gain and focused on promoting a healthy diet and reducing the

consumption of carbonated drinks.

Eighteen studies tested PA-only interventions (Appendix A1). PA-only interventions had an

impact on BMI (26), WC in girls (27), skin-fold thickness (28) and %BF (29) in children.

One study with a significant effect on %BF (29) enrolled pre-pubertal girls in daily physical

education classes. Some of the PA interventions also affected clinical outcomes by lowering

systolic blood pressure (30) or affected intermediate outcomes by increasing PA and

reducing sedentary activities (31,32).

Forty studies assessed the effect of combined strategy interventions (Appendix A2). These

included intensive classroom PA lessons led by trained teachers, moderate-to-vigorous PA

sessions, distribution of nutritional education materials and provision of healthful foods.

Children who participated in longer term intervention programmes generally showed

significant improvements in physical performance (e.g. shuttle run minutes) (33–37),

whereas shorter studies mostly had non-significant results.

Five of the combined interventions were RCTs, reported BMI z-score as an outcome and had

sufficient data for meta-analysis (38–42). Together, they showed an overall difference in

BMI z-score of −0.05 (95% CI: −0.10, −0.01, P = 0.025) in favour of the intervention groups

(Fig. 2a).

Nine of the combined interventions reported on BMI and were RCTs with sufficient data for

meta-analysis (41–49). They showed an overall mean difference in BMI of −0.30 kg m−2

(95% CI: −0.45, −0.15, P < 0.001) in favour of the intervention (Fig. 2b).

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Overall, SOE was moderate that interventions targeting diet or PA only in a school-only

setting prevent obesity in children. SOE was presently insufficient that school only-based

interventions using a combined strategy prevent obesity.

School-based interventions with a home component—Thirty-two studies (36,272 participants) implemented interventions in schools and included a home component,

including 21 RCTs (Appendix A3). Only one study evaluated a diet-only intervention (50),

where the most intensive of its two intervention arms showed a reduction in the prevalence

of overweight and obesity. Three studies tested PA-only interventions (51–53). All four

reported statistically significant beneficial effects of the intervention on adiposity-related

outcomes.

Ten (36%) of the 28 studies that tested combined strategy interventions reported statistically

significant beneficial effects (Table 1). Among the 18 studies that measured BMI change, 16

showed reduced BMI due to the intervention with differences ranging from −0.10 to −1.60

kg m−2. However, only in five studies were these changes statistically significant.

Only one of the 28 examined studies reported a significant, desirable intervention effect on

the combined prevalence of overweight and obesity (adjusted odds ratio [OR] = 0.67; 95%

CI: 0.47, 0.96, P < 0.03) (54). Another study found a statistically significant difference in

the prevalence of both overweight (3.7%, P < 0.05) and obesity (2.3%, P < 0.05), again

favouring the intervention (55).

Eight combined intervention studies reported sufficient data for meta-analysis of BMI (56–

63). The weighted mean BMI difference was −0.25 kg m−2 (95% CI: −0.68, 0.17, P = 0.237)

favouring the interventions (Fig. 2c).

SOE was insufficient that diet-only interventions prevent obesity when implemented in a

school setting with a home component. SOE was high that PA-only interventions prevent

obesity, but was moderate regarding diet–PA combined interventions.

School-based interventions with home and community components—We identified 10 studies (14,605 participants) that were school based and included both home

and community components, including five RCTs (Appendix A4). Most of the combined

interventions focused on providing education to improve diet and PA. SOE was insufficient

that PA-only interventions prevent obesity as there was only one study found with a

moderate ROB. SOE was high that combined interventions prevent obesity as the only study

had a low ROB and the other studies, which mostly had moderate ROB, showed favourable

intervention effects.

School-based interventions with a community component—Six studies (10,087 participants) were school-based with a community component, including three RCTs

(Appendix A5). One RCT tested a diet-only intervention and showed significant

improvements in BMI and obesity prevalence (64). Another RCT testing PA-only

interventions found positive but insignificant improvements in triceps skin-fold thickness

and body weight, but no improvements in BMI or %BF (65). Four studies evaluating

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combined interventions generally showed non-significant improvements in adiposity-related

outcomes.

SOE was insufficient that diet- or PA-only interventions prevent obesity given only one

study for each. SOE was moderate that combined interventions prevent obesity as two of the

four studies with moderate ROB both showed favourable effects.

School-based interventions with a consumer health informatics component— We identified five studies (3,615 participants) that were school based with a CHI component

(Appendix A6). One reported a significant difference in BMI between the intervention and

control groups (66). SOE was insufficient regarding such interventions.

School-based interventions with home and consumer health informatics components—One non-RCT evaluated a combined intervention (589 participants) in a school setting with both home and CHI components, but detected no beneficial effects on

adiposity-related outcomes (67). Hence, SOE was insufficient.

Key findings from non-school-based interventions

Home only-based interventions—We identified four home-based intervention studies (321 participants) and all were RCTs (Appendix A7). One examined a diet-only intervention

and three tested combined interventions. None of the studies detected a statistically

significant beneficial intervention effect on adiposity-related outcomes. SOE was

insufficient for diet-only interventions. SOE was low that combined interventions at home to

prevent obesity.

Home-based interventions with school and community components—We identified one RCT intervention study (1,323 participants), which was home based and

included both school and community components. It reported no effect of a diet–PA

combined intervention on BMI (68). SOE was insufficient that such interventions prevent

obesity in these settings.

Home-based studies with primary care and consumer health informatics components—One RCT (878 participants) was home based with both primary care and CHI components. It reported no effect of a combined diet and PA intervention on BMI z-

score (69). SOE was insufficient for this intervention strategy.

Primary care only-based interventions—We identified one quasi-experimental study (600 participants) that was only primary care based (70). It did not reduce obesity rates.

Thus, SOE was insufficient regarding interventions in this setting.

Primary care-based interventions with a home component—Two RCTs (71,72) (253 participants) assessed the effect of combined interventions performed in a primary care

setting with a home component. Only one found significant differences in BMI z-score in

favour of the intervention group (72). Thus, SOE was insufficient for such interventions.

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Child care centre only-based interventions—We identified five child care centre- based intervention studies (3,220 participants) (73–77), three of which were RCTs (73–75)

and two non-RCTs. The two non-RCTs both assessed the effects of PA-only interventions.

One of them found significant differences in BMI and %BF between the intervention and

control groups (76). The other one found positive but insignificant differences in BMI

between intervention and control (P = 0.09 for weight and intervention interaction).

However, with only two studies, SOE was insufficient regarding the PA-only interventions.

The three RCT studies (73–75) all evaluated diet–PA combined interventions, but only one

(75) showed significant beneficial effects on adiposity-related outcomes. SOE was low for

combined interventions as these RCTs had moderate ROB and inconsistent results.

Community-based or environmental-level interventions—We identified 10 community-based or environmental-level intervention studies (Appendix A8). The strongest

evidence came from three studies that took place in the community with school involvement

(78–80). Two were RCTs with one conducted in the Netherlands (1,108 participants) (78)

and the other in the United States (mean enrolment of 1,109 participants across 24 schools)

(79). The third was a non-RCT in the United States (80). The US RCT (79) and the one non-

RCT (80) detected statistically significant, beneficial intervention effects.

SOE was moderate that community-based, diet–PA combined interventions that include a

school component prevent obesity. SOE was insufficient for interventions implemented in

the community alone or with support from other settings.

Consumer health informatics interventions—Seven CHI studies were identified and they took place primarily in the school or home setting. Only one (66) school-based CHI

study showed a significant reduction in BMI in the intervention group.

Discussion

To our knowledge, this is the most comprehensive study that has been performed to evaluate

the success of various childhood obesity prevention programmes. We included 139 studies

conducted in multiple settings in high-income countries over the past three decades,

focusing on adiposity-related outcomes and SOE. The study followed the rigorous protocol

required by the AHRQ for systematic reviews and provides important findings to help

various stakeholders understand the effectiveness of obesity prevention programmes for

children and to offer insights for future research and intervention development. This study

has a number of principal strengths and makes some unique contributions to the field (see

below). Our key findings include:

First, we find that a large number of childhood obesity prevention studies have been

performed, but the majority are school based and conducted in the United States and within

the most recent decade. In total, we identified 139 intervention studies, 115 (83%) of which

were school based.

Second, we find at least moderate SOE to support the effectiveness of school-based

interventions. About half of the studies reported statistically significant beneficial

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intervention effects for at least some of the adiposity-related measures. Interventions

implemented in schools with home involvement had the highest proportion of studies with

favourable results.

Third, overall, a greater proportion of multi-setting studies demonstrated significant and

beneficial results compared with single-setting interventions. All settings combined, the

highest proportion of significant and favourable impacts on adiposity-related outcomes was

attributable to diet-only interventions while the lowest proportion of successes lies in PA-

only interventions.

Fourth, the SOE varied by intervention strategy and setting. SOE for PA-only interventions

delivered in schools with home involvement and diet–PA combined interventions delivered

in schools with both home and community components to prevent obesity were high. SOE

for school only-based interventions targeting either diet or PA, combined diet–PA school-

based interventions with home or community components, and combined diet–PA

community-based interventions with a school component to prevent obesity was moderate.

SOE for combined interventions in a child care or home setting to prevent obesity was low.

In general, some intervention groupings had low SOE due to the small number of relevant

studies conducted of their type. The SOE for the effectiveness of interventions in other

settings was insufficient due to the small number of published research found, the moderate

or high ROB and conflicting results across studies.

In general, our main findings are consistent with previous systematic reviews that school-

based interventions can help prevent obesity in children. This supports the IOM’s

recommendations (12) that schools be the focal point for childhood obesity prevention.

However, discrepancies between our findings and previous reviews exist, especially

regarding the SOE and the magnitude of intervention effects. Although our study generally

found an insufficient-to-moderate SOE supporting the intervention effects of school-based

interventions (although there were a few exceptions of large intervention effects in some

cases), the most recent Cochrane review found strong evidence to support the beneficial

effects of school-based intervention programmes, particularly among children aged 6–12

(16). However, another systematic review of 18 controlled trials did not find any significant

improvements in BMI with school-based PA interventions (81). The discrepancies may stem

from differences in study selection criteria and, therefore, included studies, as well as from

differences in the outcomes being examined.

Although some of the intervention studies we reviewed reported large effect sizes in changes

in BMI and obesity/overweight prevalence, overall, our meta-analyses, which was based on

all available studies meeting our inclusion criteria, suggest the effect size of these

interventions to be small. For example, our findings presented in Fig. 2 imply improvements

of about 0.05 z-score and 0.25 BMI. Especially compared with the increase in BMI and the

rates of overweight and obesity over the last three decades in many countries, these

intervention effects are slight. Thus, the effectiveness of interventions to reverse the tide of

the epidemic is likely to be small as many large social and environmental changes are

driving the trend towards increasing obesity. In general, our reported effect sizes were

similar to those reported by other reviews of preventive interventions, although there are

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also reviews that did not find any significant improvements in BMI with school-based

interventions (81).

Our findings have some important implications for clinical decision and policy making. This

review can help clinical and public health practitioners, researchers and policy makers

decide on appropriate intervention strategies with which to combat the prevailing obesity

epidemic in developed countries. It may also help provide insights for future research. We

need more research to test non-school-based interventions and those utilizing innovative

designs and approaches. Strong, promising results suggest that school-based childhood

obesity prevention programmes may fight the rise in childhood obesity. After careful review

of the individual components of the successful studies, healthcare professionals may

replicate the results in new settings, which could lead to broader implementation.

The cost-effectiveness of the interventions was infrequently studied. Only a few of our

included studies mentioned such analyses and none of the studies we reviewed reported

estimates of the resources used (costs) to achieve the observed effects. It is likely that few

studies collected data on the costs associated with their interventions. Given the complexity

of many programmes, it is understandably challenging to determine which costs should be

accounted for (e.g. programme development, implementation, maintenance costs) and,

subsequently, assessed and reported. Nevertheless, it would be important to know how

stakeholders (e.g. parents, schools, public health professionals, government agencies) would

calculate the real value of an intervention. It would also be important to figure out how

researchers may help in such assessments. This is a critical gap in the current literature. In

the future, we recommend researchers, journal editors and funding agencies to encourage the

collection and reporting of data on the cost-effectiveness of interventions.

The sustainability of interventions and their beneficial effects are another important, albeit

complex and controversial, issue that is less studied. Very few studies measured or showed

that intervention effects were sustained beyond the active intervention period. More future

research, including systematic reviews, is needed in this area.

Intervention programmes may also have potential harms, although few were reported. For

example, programmes may unintentionally cause stigmas; most interventions achieved only

small or no effects but weighed and measured many youth. Some of the youth may have

anticipated improvement in their weight status, but could have experienced no significant

improvements or benefits. Thus, it is foreseeable that some youth could feel a sense of

failure with this or an associated loss in self-esteem. Although, we did not observe any

reports of this in the literature. Nonetheless, future research into the potential harms of

interventions would be useful.

In addition, it is possible that some intervention approaches may elicit the desire to respond

favourably in some children, particularly those from families with higher educational

attainment and/or greater financial resources. This may lead to disproportionate behavioural

and weight improvements in these groups. Future research is needed to assess this

possibility and better understand the issue to help enhance intervention effectiveness.

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This study has several limitations. First, it was limited in scope by focusing only on studies

from high-income countries. However, this restriction makes the findings all the more

applicable to the examined population. Second, there was great heterogeneity in the included

studies in terms of intervention setting, design, sample size and characteristics, intervention

approach, primary measures used to assess intervention effects, length of follow-up, and

statistical and analytical approaches taken. Such variability made it challenging for cross-

comparisons. Third, given that we identified so few studies outside of the school setting, we

were only able to conduct meta-analyses for KQ1 (school-based interventions) and only on a

small number of studies at that.

Fourth, we stratified analyses first based on study setting and then by intervention strategy

taken (diet, PA or both combined). However, due to limited sample sizes, we could not

further stratify analyses – for example, to explore the comparative effectiveness of specific

intervention approaches (e.g. educational interventions vs. environmental interventions) with

pooled analyses or compare effects in specific intermediate outcomes (e.g. changes in fruit

and vegetable intake vs. total energy intake).

Fifth, we used BMI and BMI-related measures, such as BMI z-score and BMI percentile, as

well as the prevalence of overweight and obesity based on BMI cut-points, as the primary

outcomes of interest. This was performed given its more common reporting across included

studies. But, BMI has its limitations. It is an indirect measure of adiposity and not an ideal

indicator for health risk. In addition, studies used different BMI cut-points to define

overweight and obesity.

Sixth, related to study heterogeneity, another challenge was that studies assessed

intervention effects in different ways. Some did so by comparing changes in the outcomes

between the intervention and control groups while other studies compared between-group

differences in weight outcomes only at follow-up. Still others reported on ORs of being

overweight and/or obese and other studies did so on between-group difference in continuous

outcome measures such as BMI. This again made comparing and pooling results

challenging.

Seventh, we included some studies that did not state obesity prevention among their original

intervention goals but rather stated they aimed to reduce cardiovascular risk. We kept these

studies in the review because they also implemented diet and/or PA interventions and

reported on body weight-related outcomes for their results. By employing similar strategies

on similar outcomes, they could also shed some light on the potential effects of childhood

obesity interventions. However, because of the differences in original study intents, these

studies may differ slightly with those originally designed to primarily target childhood

obesity.

Lastly, considering the comparability of studies conducted in different locales, we limited

our review to only those studies conducted in high-income countries. Thus, our findings may

not be generalizable to lower income countries. In addition, we decided to reduce the

inclusion requirement for length of follow-up time to 6 months for school-based studies

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considering the usual length of school years. However, we recognize 6 months may be too

short a time to observe intervention effects on weight-related outcomes.

Despite these many limitations, our study was systematic and rigorous. We followed

standardized procedures from the AHRQ Effective Healthcare Program and utilized input

from various experts and stakeholders in the field of childhood obesity prevention. Only

experimental studies, quasi-experimental studies and natural experiments were included in

our analyses to minimize confounding and maximize utilization of available evidence. Our

study assessed the effects of the interventions on multiple adiposity-related outcomes while

most other reviews have focused only on BMI or other select outcomes. We have also

identified a number of future research priorities for the field (see Table 4 for our

recommendations).

In conclusion, a large number of childhood obesity intervention studies have been conducted

in high-income countries, but they have been predominantly conducted in schools and in the

United States. The following intervention points are supported by a body of evidence of at

least a moderate level of strength to be effective for childhood obesity prevention: (i)

schools are an important setting in which to implement effective intervention programmes

and concomitant involvement of the home/family and community is desirable; (ii)

improving access to PA facilities and healthful food choices such as fruits and vegetables

both at school and home is effective and (iii) home or parental and family involvement is

important. Overall, there is moderate-to-high SOE to support the idea that diet and/or PA

interventions implemented in schools prevent obesity. However, the evidence on the

effectiveness of interventions implemented in other settings is generally insufficient. Other

analyses and findings from this systematic review on other outcomes such as on blood

pressure and blood lipids can be found and were reported recently elsewhere (82,83).

Future research is needed to evaluate interventions conducted in settings other than in

schools, especially those implementing wide-ranging changes through regional and national

policy and environmental changes. Research into the delivery and effectiveness of

innovative intervention strategies, such as those taking advantage of and applying new

technologies and approaches (e.g. health communication and social marketing, urban

planning), established behavioural theories and novel methodologies (e.g. systems science)

is also of great importance.

Acknowledgments

This study was primarily funded under contract no. 290-2007-10061-I from the Agency for Healthcare Research and Quality (AHRQ), US Department of Health and Human Services. Youfa Wang, Yang Wu, LC and LJC’s efforts were also supported in part by research grants from the National Institute of Health (research grants 1R01HD064685-01A1 and U54HD070725 from the Eunice Kennedy Shriver National Institute of Child Health & Human Development [NICHD]). The U54 project was co-funded by the NICHD and the Office of Behavioral and Social Sciences Research (OBSSR). LC also received support from the China Scholarship Council, Peking University and Johns Hopkins University for her research as a postdoctoral fellow working with Youfa Wang at Johns Hopkins University, who is the principal investigator of the project. The authors are fully responsible for the content of this report. Statements herein should not be construed as opinions of the funders. We thank Dr. Christine Chang from AHRQ for her steadfast support and assistance to the study. We also thank our technical experts and stakeholders for their contributions and feedback to our study through providing input on refining the key research questions, protocol and our full research report submitted to the AHRQ.

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Appendix A References for studies cited in the Result section (A1–A8)

This systematic review included 147 articles, which described 139 intervention studies.

Appendix A provided additional references that were not included in the paper due to the

journal’s page limit.

Appendix A1 PA-only interventions implemented in a school only-based

setting

References

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2. Donnelly JE, Greene JL, Gibson CA, et al. Physical Activity Across the Curriculum (PAAC): a randomized controlled trial to promote physical activity and diminish overweight and obesity in elementary school children. Prev Med. 2009; 49:336–341. [PubMed: 19665037]

3. Stenevi-Lundgren S, Daly RM, Linden C, Gardsell P, Karlsson MK. Effects of a daily school based physical activity intervention program on muscle development in prepubertal girls. Eur J Appl Physiol. 2009; 105:533–541. [PubMed: 19018558]

4. Reed KE, Warburton DE, Macdonald HM, Naylor PJ, McKay HA. Action Schools! BC: a school- based physical activity intervention designed to decrease cardiovascular disease risk factors in children. Prev Med. 2008; 46:525–531. [PubMed: 18377970]

5. Heelan KA, Abbey BM, Donnelly JE, Mayo MS, Welk GJ. Evaluation of a walking school bus for promoting physical activity in youth. J Phys Act Health. 2009; 6:560–567. [PubMed: 19953832]

6. Chiodera P, Volta E, Gobbi G, et al. Specifically designed physical exercise programs improve children’s motor abilities. Scand J Med Sci Sports. 2008; 18:179–187. [PubMed: 17490452]

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17. Robbins LB, Pfeiffer KA, Maier KS, Lo YJ, Wesolek Ladrig SM. Pilot intervention to increase physical activity among sedentary urban middle school girls: a two-group pretest-posttest quasi- experimental design. J Sch Nurs. 2012; 28:302–315. [PubMed: 22472632]

18. Vandongen R, Jenner DA, Thompson C, et al. A controlled evaluation of a fitness and nutrition intervention program on cardiovascular health in 10- to 12-year-old children. Prev Med. 1995; 24:9–22. [PubMed: 7740021]

Appendix A2 Combined interventions implemented in a school only-based

setting

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19. Bonsergent E, Agrinier N, Thilly N, et al. Overweight and obesity prevention for adolescents: a cluster randomized controlled trial in a school setting. Am J Prev Med. 2013; 44:30–39. [PubMed: 23253647]

20. Foster GD, Linder B, Baranowski T, et al. A school-based intervention for diabetes risk reduction. N Engl J Med. 2010; 363:443–453. [PubMed: 20581420]

21. Rosario R, Oliveira B, Araujo A, et al. The impact of an intervention taught by trained teachers on childhood overweight. Int J Environ Res Public Health. 2012; 9:1355–1367. [PubMed: 22690198]

22. Amaro S, Viggiano A, Di Costanzo A, et al. Kaledo, a new educational board-game, gives nutritional rudiments and encourages healthy eating in children: a pilot cluster randomized trial. Eur J Pediatr. 2006; 165:630–635. [PubMed: 16733670]

23. Lubans DR, Morgan PJ, Okely AD, et al. Preventing obesity among adolescent girls: one-year outcomes of the Nutrition and Enjoyable Activity for Teen Girls (NEAT Girls) cluster randomized controlled trial. Arch Pediatr Adolesc Med. 2012; 166:821–827. [PubMed: 22566517]

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24. Gutin B, Yin Z, Johnson M, Barbeau P. Preliminary findings of the effect of a 3-year after-school physical activity intervention on fitness and body fat: the Medical College of Georgia Fitkid Project. Int J Pediatr Obes. 2008; 3(Suppl 1):3–9. [PubMed: 18278626]

25. Barbeau P, Johnson MH, Howe CA, et al. Ten months of exercise improves general and visceral adiposity, bone, and fitness in black girls. Obesity (Silver Spring). 2007; 15:2077–2085. [PubMed: 17712126]

26. Magnusson KT, Hrafnkelsson H, Sigurgeirsson I, Johannsson E, Sveinsson T. Limited effects of a 2-year school-based physical activity intervention on body composition and cardiorespiratory fitness in 7-year-old children. Health Educ Res. 2012; 27:484–494. [PubMed: 22456632]

27. Morgan PJ, Saunders KL, Lubans DR. Improving physical self-perception in adolescent boys from disadvantaged schools: psychological outcomes from the Physical Activity Leaders randomized controlled trial. Pediatr Obes. 2012; 7:e27–e32. [PubMed: 22492681]

28. Busch V, De Leeuw RJ, Schrijvers AJ. Results of a multibehavioral health-promoting school pilot intervention in a Dutch secondary school. J Adolesc Health. 2013; 52:400–406. [PubMed: 23299009]

29. Neumark-Sztainer DR, Friend SE, Flattum CF, et al. New moves-preventing weight-related problems in adolescent girls a group-randomized study. Am J Prev Med. 2010; 39:421–432. [PubMed: 20965379]

30. Llargues E, Recasens A, Franco R, et al. Medium-term evaluation of an educational intervention on dietary and physical exercise habits in schoolchildren: the Avall 2 study. Endocrinol Nutr. 2012; 59:288–295. [PubMed: 22521298]

31. Howe CA, Harris RA, Gutin B. A 10-month physical activity intervention improves body composition in young black boys. J Obes. 2011; 2011:358581. [PubMed: 20981151]

32. Manios Y, Kafatos A. Health and nutrition education in primary schools in Crete: 10 years follow- up of serum lipids, physical activity and macronutrient intake. Br J Nutr. 2006; 95:568–575. [PubMed: 16578934]

33. Manios Y, Moschandreas J, Hatzis C, Kafatos A. Evaluation of a health and nutrition education program in primary school children of Crete over a three-year period. Prev Med. 1999; 28:149– 159. [PubMed: 10048106]

34. Manios Y, Moschandreas J, Hatzis C, Kafatos A. Health and nutrition education in primary schools of Crete: changes in chronic disease risk factors following a 6-year intervention programme. Br J Nutr. 2002; 88:315–324. [PubMed: 12207842]

35. Sollerhed AC, Ejlertsson G. Physical benefits of expanded physical education in primary school: findings from a 3-year intervention study in Sweden. Scand J Med Sci Sports. 2008; 18:102–107. [PubMed: 17490464]

36. Graf C, Koch B, Falkowski G, et al. School-based prevention: effects on obesity and physical performance after 4 years. J Sports Sci. 2008; 26:987–994. [PubMed: 18608843]

37. Haerens L, Deforche B, Maes L, Stevens V, Cardon G, De Bourdeaudhuij I. Body mass effects of a physical activity and healthy food intervention in middle schools. Obesity (Silver Spring). 2006; 14:847–854. [PubMed: 16855194]

38. Kain J, Leyton B, Cerda R, Vio F, Uauy R. Two-year controlled effectiveness trial of a school- based intervention to prevent obesity in Chilean children. Public Health Nutr. 2009; 12:1451– 1461. [PubMed: 19102808]

39. Trevino RP, Hernandez AE, Yin Z, Garcia OA, Hernandez I. Effect of the Bienestar Health Program on physical fitness in low-income Mexican American children. Hispanic J Behav Sci. 2005; 27:120–132.

40. Kafatos A, Manios Y, Moschandreas J. Health and nutrition education in primary schools of Crete: follow-up changes in body mass index and overweight status. Eur J Clin Nutr. 2005; 59:1090– 1092. [PubMed: 16015265]

41. Stock S, Miranda C, Evans S, et al. Healthy Buddies: a novel, peer-led health promotion program for the prevention of obesity and eating disorders in children in elementary school. Pediatrics. 2007; 120:e1059–e1068. [PubMed: 17908726]

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42. Muckelbauer R, Libuda L, Clausen K, Toschke AM, Reinehr T, Kersting M. Promotion and provision of drinking water in schools for overweight prevention: randomized, controlled cluster trial. Pediatrics. 2009; 123:e661–e667. [PubMed: 19336356]

43. Newton RL Jr, Han H, Anton SD, et al. An environmental intervention to prevent excess weight gain in African-American students: a pilot study. Am J Health Promot. 2010; 24:340–343. [PubMed: 20465148]

44. Skybo TA, Ryan-Wenger N. A school-based intervention to teach third grade children about the prevention of heart disease. Pediatr Nurs. 2002; 28:223–229. 235. [PubMed: 12087641]

45. Walter HJ, Hofman A, Connelly PA, Barrett LT, Kost KL. Primary prevention of chronic disease in childhood: changes in risk factors after one year of intervention. Am J Epidemiol. 1985; 122:772–781. [PubMed: 4050769]

46. Sahota P, Rudolf MC, Dixey R, Hill AJ, Barth JH, Cade J. Randomised controlled trial of primary school based intervention to reduce risk factors for obesity. BMJ. 2001; 323:1029–1032. [PubMed: 11691759]

47. Gortmaker SL, Peterson K, Wiecha J, et al. Reducing obesity via a school-based interdisciplinary intervention among youth: Planet Health. Arch Pediatr Adolesc Med. 1999; 153:409–418. [PubMed: 10201726]

48. Madsen J, Sallis JF, Rupp JW, et al. Relationship between self-monitoring of diet and exercise change and subsequent risk factor changes in children and adults. Patient Educ Couns. 1993; 21:61–69. [PubMed: 8337206]

49. Bush PJ, Zuckerman AE, Theiss PK, et al. Cardiovascular risk factor prevention in black schoolchildren: two-year results of the ‘Know Your Body’ program. Am J Epidemiol. 1989; 129:466–482. [PubMed: 2916540]

50. Bronikowski M, Bronikowska M. Will they stay fit and healthy? A three-year follow-up evaluation of a physical activity and health intervention in Polish youth. Scand J Public Health. 2011; 39:704–713. [PubMed: 21948996]

51. Burguera B, Colom A, Pinero E, et al. ACTYBOSS: activity, behavioral therapy in young subjects – after-school intervention pilot project on obesity prevention. Obes Facts. 2011; 4:400–406. [PubMed: 22166761]

52. Coleman KJ, Shordon M, Caparosa SL, Pomichowski ME, Dzewaltowski DA. The healthy options for nutrition environments in schools (Healthy ONES) group randomized trial: using implementation models to change nutrition policy and environments in low income schools. Int J Behav Nutr Phys Act. 2012; 9:80. [PubMed: 22734945]

53. DeBar LL, Schneider M, Drews KL, et al. Student public commitment in a school-based diabetes prevention project: impact on physical health and health behavior. BMC Public Health. 2011; 11:711. [PubMed: 21933431]

54. Fung C, Kuhle S, Lu C, et al. From ‘best practice’ to ‘next practice’: the effectiveness of school- based health promotion in improving healthy eating and physical activity and preventing childhood obesity. Int J Behav Nutr Phys Act. 2012; 9:27. [PubMed: 22413778]

55. Klish WJ, Karavias KE, White KS, et al. Multicomponent school-initiated obesity intervention in a high-risk, Hispanic elementary school. J Pediatr Gastroenterol Nutr. 2012; 54:113–116. [PubMed: 21857252]

56. Lubans DR, Morgan PJ, Callister R. Potential moderators and mediators of intervention effects in an obesity prevention program for adolescent boys from disadvantaged schools. J Sci Med Sport. 2012; 15:519–525. [PubMed: 22575499]

57. Rush E, Reed P, McLennan S, Coppinger T, Simmons D, Graham D. A school-based obesity control programme: Project Energize. Two-year outcomes. Br J Nutr. 2012; 107:581–587. [PubMed: 21733268]

58. Tucker S, Lanningham-Foster L, Murphy J, et al. A school based community partnership for promoting healthy habits for life. J Community Health. 2011; 36:414–422. [PubMed: 20976532]

59. Warren JM, Henry CJ, Lightowler HJ, Bradshaw SM, Perwaiz S. Evaluation of a pilot school programme aimed at the prevention of obesity in children. Health Promot Int. 2003; 18:287–296. [PubMed: 14695360]

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60. Dämon S, Dietrich S, Widhalm K. PRESTO – Prevention Study of Obesity: a project to prevent obesity during childhood and adolescence. Acta Paediatr Suppl. 2005; 94:47–48. [PubMed: 16175809]

Appendix A3 Interventions implemented in schools and included a home

component

References

61. Trevino RP, Yin Z, Hernandez A, Hale DE, Garcia OA, Mobley C. Impact of the Bienestar school- based diabetes mellitus prevention program on fasting capillary glucose levels: a randomized controlled trial. Arch Pediatr Adolesc Med. 2004; 158:911–917. [PubMed: 15351759]

62. Caballero B, Clay T, Davis SM, et al. Pathways: a school-based, randomized controlled trial for the prevention of obesity in American Indian schoolchildren. Am J Clin Nutr. 2003; 78:1030–1038. [PubMed: 14594792]

63. Hendy HM, Williams KE, Camise TS. Kid’s Choice Program improves weight management behaviors and weight status in school children. Appetite. 2011; 56:484–494. [PubMed: 21277924]

64. Robinson TN. Reducing children’s television viewing to prevent obesity: a randomized controlled trial. JAMA. 1999; 282:1561–1567. [PubMed: 10546696]

65. Manios Y, Kafatos A, Mamalakis G. The effects of a health education intervention initiated at first grade over a 3 year period: physical activity and fitness indices. Health Educ Res. 1998; 13:593– 606. [PubMed: 10345909]

66. Burke V, Milligan RA, Thompson C, et al. A controlled trial of health promotion programs in 11- year-olds using physical activity ‘enrichment’ for higher risk children. J Pediatr. 1998; 132:840– 848. [PubMed: 9602197]

67. Dzewaltowski DA, Rosenkranz RR, Geller KS, et al. HOP’N after-school project: an obesity prevention randomized controlled trial. Int J Behav Nutr Phys Act. 2010; 7:90. [PubMed: 21144055]

68. Siegrist M, Lammel C, Haller B, Christle J, Halle M. Effects of a physical education program on physical activity, fitness, and health in children: the JuvenTUM project. Scand J Med Sci Sports. 2011; 23:2241–2249.

69. Story M, Hannan PJ, Fulkerson JA, et al. Bright Start: description and main outcomes from a group-randomized obesity prevention trial in American Indian children. Obesity (Silver Spring). 2012; 20:2241–2249. [PubMed: 22513491]

70. Hatzis CM, Papandreou C, Kafatos AG. School health education programs in Crete: evaluation of behavioural and health indices a decade after initiation. Prev Med. 2010; 51:262–267. [PubMed: 20566355]

71. Mihas C, Mariolis A, Manios Y, et al. Evaluation of a nutrition intervention in adolescents of an urban area in Greece: short- and long-term effects of the VYRONAS study. Public Health Nutr. 2010; 13:712–719. [PubMed: 19781127]

72. Llargues E, Franco R, Recasens A, et al. Assessment of a school-based intervention in eating habits and physical activity in school children: the AVall study. J Epidemiol Community Health. 2011; 65:896–901. [PubMed: 21398682]

73. Centis E, Marzocchi R, Di Luzio R, et al. A controlled, class-based multicomponent intervention to promote healthy lifestyle and to reduce the burden of childhood obesity. Pediatr Obes. 2012; 7:436–445. [PubMed: 22911919]

74. Elinder LS, Heinemans N, Hagberg J, Quetel AK, Hagstromer M. A participatory and capacity- building approach to healthy eating and physical activity- SCIP-school: a 2-year controlled trial. Int J Behav Nutr Phys Act. 2012; 9:145. [PubMed: 23245473]

75. Rappaport EB, Daskalakis C, Sendecki JA. Using routinely collected growth data to assess a school-based obesity prevention strategy. Int J Obes (Lond). 2013; 37:79–85. [PubMed: 22945605]

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76. Shofan Y, Kedar O, Branski D, Berry E, Wilschanski M. A school-based program of physical activity may prevent obesity. Eur J Clin Nutr. 2011; 65:768–770. [PubMed: 21427748]

77. Danielzik S, Pust S, Muller MJ. School-based interventions to prevent overweight and obesity in prepubertal children: process and 4-years outcome evaluation of the Kiel Obesity Prevention Study (KOPS). Acta Paediatr Suppl. 2007; 96:19–25. [PubMed: 17313410]

78. Simonetti D’Arca A, Tarsitani G, Cairella M, et al. Prevention of obesity in elementary and nursery school children. Public Health. 1986; 100:166–173. [PubMed: 3737864]

79. Kriemler S, Zahner L, Schindler C, et al. Effect of school based physical activity programme (KISS) on fitness and adiposity in primary schoolchildren: cluster randomised controlled trial. BMJ. 2010; 340:c785. [PubMed: 20179126]

80. Hollar D, Messiah SE, Lopez-Mitnik G, Hollar TL, Almon M, Agatston AS. Effect of a two-year obesity prevention intervention on percentile changes in body mass index and academic performance in low-income elementary school children. Am J Public Health. 2010; 100:646–653. [PubMed: 20167892]

81. Hoelscher DM, Springer AE, Ranjit N, et al. Reductions in child obesity among disadvantaged school children with community involvement: the Travis County CATCH Trial. Obesity (Silver Spring). 2010; 18(Suppl 1):S36–S44. [PubMed: 20107459]

82. Nader PR, Stone EJ, Lytle LA, et al. Three-year maintenance of improved diet and physical activity: the CATCH cohort. Child and Adolescent Trial for Cardiovascular Health. Arch Pediatr Adolesc Med. 1999; 153:695–704. [PubMed: 10401802]

83. Lionis C, Kafatos A, Vlachonikolis J, Vakaki M, Tzortzi M, Petraki A. The effects of a health education intervention program among Cretan adolescents. Prev Med. 1991; 20:685–699. [PubMed: 1766941]

84. Schetzina KE, Dalton WT 3rd, Lowe EF, et al. A coordinated school health approach to obesity prevention among Appalachian youth: the Winning with Wellness Pilot Project. Fam Community Health. 2009; 32:271–285. [PubMed: 19525708]

85. Marcus C, Nyberg G, Nordenfelt A, Karpmyr M, Kowalski J, Ekelund U. A 4-year, cluster- randomized, controlled childhood obesity prevention study: STOPP. Int J Obes (Lond). 2009; 33:408–417. [PubMed: 19290010]

86. Brandstetter S, Klenk J, Berg S, et al. Overweight prevention implemented by primary school teachers: a randomised controlled trial. Obes Facts. 2012; 5:1–11. [PubMed: 22433612]

87. Lloyd JJ, Wyatt KM, Creanor S. Behavioural and weight status outcomes from an exploratory trial of the Healthy Lifestyles Programme (HeLP): a novel school-based obesity prevention programme. BMJ Open. 2012:2.

88. Williamson DA, Champagne CM, Harsha DW, et al. Effect of an environmental school-based obesity prevention program on changes in body fat and body weight: a randomized trial. Obesity (Silver Spring). 2012; 20:1653–1661. [PubMed: 22402733]

89. Simon C, Schweitzer B, Oujaa M, et al. Successful overweight prevention in adolescents by increasing physical activity: a 4-year randomized controlled intervention. Int J Obes (Lond). 2008; 32:1489–1498. [PubMed: 18626482]

90. Foster GD, Sherman S, Borradaile KE, et al. A policy-based school intervention to prevent overweight and obesity. Pediatrics. 2008; 121:e794–e802. [PubMed: 18381508]

91. Speroni KG, Earley C, Atherton M. Evaluating the effectiveness of the Kids Living Fit program: a comparative study. J Sch Nurs. 2007; 23:329–336. [PubMed: 18052518]

92. Hopper CA, Munoz KD, Gruber MB, Nguyen KP. The effects of a family fitness program on the physical activity and nutrition behaviors of third-grade children. Res Q Exerc Sport. 2005; 76:130–139. [PubMed: 16128481]

93. Coleman KJ, Tiller CL, Sanchez J, et al. Prevention of the epidemic increase in child risk of overweight in low-income schools: the El Paso coordinated approach to child health. Arch Pediatr Adolesc Med. 2005; 159:217–224. [PubMed: 15753263]

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Appendix A4 School-based interventions with home and community

components

References

94. Angelopoulos PD, Milionis HJ, Grammatikaki E, Moschonis G, Manios Y. Changes in BMI and blood pressure after a school based intervention: the CHILDREN study. Eur J Public Health. 2009; 19:319–325. [PubMed: 19208697]

95. Greening L, Harrell KT, Low AK, Fielder CE. Efficacy of a school-based childhood obesity intervention program in a rural southern community: TEAM Mississippi Project. Obesity (Silver Spring). 2011; 19:1213–1219. [PubMed: 21233806]

96. Jansen W, Borsboom G, Meima A, et al. Effectiveness of a primary school-based intervention to reduce overweight. Int J Pediatr Obes. 2011; 6:e70–e77. [PubMed: 21609245]

97. De Coen V, De Bourdeaudhuij I, Vereecken C, et al. Effects of a 2-year healthy eating and physical activity intervention for 3–6-year-olds in communities of high and low socio-economic status: the POP (Prevention of Overweight among Pre-school and school children) project. Public Health Nutr. 2012; 15:1737–1745. [PubMed: 22397833]

98. Wright K, Giger JN, Norris K, Suro Z. Impact of a nurse-directed, coordinated school health program to enhance physical activity behaviors and reduce body mass index among minority children: a parallel-group, randomized control trial. Int J Nurs Stud. 2013; 50:727–737. [PubMed: 23021318]

99. de Meij JS, Chinapaw MJ, van Stralen MM, van der Wal MF, van Dieren L, van Mechelen W. Effectiveness of JUMP-in, a Dutch primary school-based community intervention aimed at the promotion of physical activity. Br J Sports Med. 2010; 45:1052–1057. [PubMed: 21112875]

100. Sanigorski AM, Bell AC, Kremer PJ, Cuttler R, Swinburn BA. Reducing unhealthy weight gain in children through community capacity-building: results of a quasi-experimental intervention program, Be Active Eat Well. Int J Obes (Lond). 2008; 32:1060–1067. [PubMed: 18542082]

101. Millar L, Kremer P, de Silva-Sanigorski A, et al. Reduction in overweight and obesity from a 3- year community-based intervention in Australia: the ‘It’s Your Move!’ project. Obes Rev. 2011; 12(Suppl 2):20–28. [PubMed: 22008556]

102. Naul R, Schmelt D, Dreiskaemper D, Hoffmann D, l’Hoir M. ‘Healthy children in sound communities’ (HCSC/gkgk) – a Dutch-German community-based network project to counteract obesity and physical inactivity. Fam Pract. 2012; 29(Suppl 1):i110–i116. [PubMed: 22399539]

103. Tomlin D, Naylor PJ, McKay H, Zorzi A, Mitchell M, Panagiotopoulos C. The impact of Action Schools! BC on the health of Aboriginal children and youth living in rural and remote communities in British Columbia. Int J Circumpolar Health. 2012; 71:17999. [PubMed: 22456048]

Appendix A5 School-based interventions with a community component

References

104. Muckelbauer R, Libuda L, Clausen K, Reinehr T, Kersting M. A simple dietary intervention in the school setting decreased incidence of overweight in children. Obes Facts. 2009; 2:282–285. [PubMed: 20057194]

105. Webber LS, Catellier DJ, Lytle LA, et al. Promoting physical activity in middle school girls: Trial of Activity for Adolescent Girls. Am J Prev Med. 2008; 34:173–184. [PubMed: 18312804]

106. Crespo NC, Elder JP, Ayala GX, et al. Results of a multi-level intervention to prevent and control childhood obesity among Latino children: the Aventuras Para Ninos Study. Ann Behav Med. 2012; 43:84–100. [PubMed: 22215470]

107. Macaulay AC, Paradis G, Potvin L, et al. The Kahnawake Schools Diabetes Prevention Project: intervention, evaluation, and baseline results of a diabetes primary prevention program with a native community in Canada. Prev Med. 1997; 26:779–790. [PubMed: 9388789]

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108. Madsen KA, Thompson HR, Wlasiuk L, Queliza E, Schmidt C, Newman TB. After-school program to reduce obesity in minority children: a pilot study. J Child Health Care. 2009; 13:333– 346. [PubMed: 19833672]

109. Utter J, Scragg R, Robinson E, et al. Evaluation of the Living 4 Life project: a youth-led, school- based obesity prevention study. Obes Rev. 2011; 12(Suppl 2):51–60. [PubMed: 22008559]

Appendix A6 School-based interventions with a consumer health

informatics component

References

110. Spiegel SA, Foulk D. Reducing overweight through a multi-disciplinary school-based intervention. Obesity (Silver Spring). 2006; 14:88–96. [PubMed: 16493126]

111. Ezendam NP, Brug J, Oenema A. Evaluation of the web-based computer-tailored FATaintPHAT intervention to promote energy balance among adolescents: results from a school cluster randomized trial. Arch Pediatr Adolesc Med. 2012; 166:248–255. [PubMed: 22064878]

112. Schneider M, Dunton GF, Bassin S, Graham DJ, Eliakim AF, Cooper DM. Impact of a school- based physical activity intervention on fitness and bone in adolescent females. J Phys Act Health. 2007; 4:17–29. [PubMed: 17489004]

113. Prins RG, Brug J, van Empelen P, Oenema A. Effectiveness of YouRAction, an intervention to promote adolescent physical activity using personal and environmental feedback: a cluster RCT. PLoS One. 2012; 7:e32682. [PubMed: 22403695]

114. Whittemore R, Jeon S, Grey M. An internet obesity prevention program for adolescents. J Adolesc Health. 2013; 52:439–447. [PubMed: 23299003]

Appendix A7 Home only-based interventions

References

115. Epstein LH, Gordy CC, Raynor HA, Beddome M, Kilanowski CK, Paluch R. Increasing fruit and vegetable intake and decreasing fat and sugar intake in families at risk for childhood obesity. Obes Res. 2001; 9:171–178. [PubMed: 11323442]

116. Lappe JM, Rafferty KA, Davies KM, Lypaczewski G. Girls on a high-calcium diet gain weight at the same rate as girls on a normal diet: a pilot study. J Am Diet Assoc. 2004; 104:1361–1367. [PubMed: 15354150]

117. French SA, Gerlach AF, Mitchell NR, Hannan PJ, Welsh EM. Household obesity prevention: Take Action – a group-randomized trial. Obesity (Silver Spring). 2011; 19:2082–2088. [PubMed: 21212771]

118. Fitzgibbon ML, Stolley MR, Schiffer L, et al. Family-based hip-hop to health: outcome results. Obesity (Silver Spring). 2012; 21:274–283. [PubMed: 23532990]

Appendix A8 Community-based or environmental-level interventions

References

119. Klesges RC, Obarzanek E, Kumanyika S, et al. The Memphis Girls’ health Enrichment Multi-site Studies (GEMS): an evaluation of the efficacy of a 2-year obesity prevention program in African American girls. Arch Pediatr Adolesc Med. 2010; 164:1007–1014. [PubMed: 21041593]

120. Eiholzer U, Meinhardt U, Petro R, Witassek F, Gutzwiller F, Gasser T. High-intensity training increases spontaneous physical activity in children: a randomized controlled study. J Pediatr. 2010; 156:242–246. [PubMed: 19846114]

121. Singh AS, Chin A, Paw M, Brug J, van Mechelen W. Dutch obesity intervention in teenagers: effectiveness of a school-based program on body composition and behavior. Arch Pediatr Adolesc Med. 2009; 163:309–317. [PubMed: 19349559]

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122. Sallis JF, McKenzie TL, Conway TL, et al. Environmental interventions for eating and physical activity: a randomized controlled trial in middle schools. Am J Prev Med. 2003; 24:209–217. [PubMed: 12657338]

123. Chomitz VR, McGowan RJ, Wendel JM, et al. Healthy Living Cambridge Kids: a community- based participatory effort to promote healthy weight and fitness. Obesity (Silver Spring). 2010; 18(Suppl 1):S45–S53. [PubMed: 20107461]

124. Economos CD, Hyatt RR, Goldberg JP, et al. A community intervention reduces BMI z-score in children: Shape Up Somerville first year results. Obesity (Silver Spring). 2007; 15:1325–1336. [PubMed: 17495210]

125. Robinson TN, Matheson DM, Kraemer HC, et al. A randomized controlled trial of culturally tailored dance and reducing screen time to prevent weight gain in low-income African American girls: Stanford GEMS. Arch Pediatr Adolesc Med. 2010; 164:995–1004. [PubMed: 21041592]

126. de Silva-Sanigorski AM, Bell AC, Kremer P, et al. Reducing obesity in early childhood: results from Romp & Chomp, an Australian community-wide intervention program. Am J Clin Nutr. 2010; 91:831–840. [PubMed: 20147472]

127. Chang DI, Gertel-Rosenberg A, Drayton VL, Schmidt S, Angalet GB. A statewide strategy to battle child obesity in Delaware. Health Aff (Millwood). 2010; 29:481–490. [PubMed: 20194990]

128. Pettman T, Magarey A, Mastersson N, Wilson A, Dollman J. Improving weight status in childhood: results from the eat well be active community programs. Int J Public Health. 2014; 59:43–50. [PubMed: 23529384]

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t

Figure 1. Results of the literature search on childhood obesity prevention studies/interventions in

high-income countries. *Sum of excluded abstracts exceeds 6,175 because reviewers were

not required to agree on reasons for exclusion. #Sum of excluded abstracts exceeds 530

because reviewers were not required to agree on reasons for exclusion. The key questions

(KQs) of this review were organized by study setting/design as follows: What is the

comparative effectiveness of school-based interventions (KQ1), home-based interventions

(KQ2), primary care-based interventions (KQ3), childcare setting-based interventions (KQ4)

and community-based interventions (KQ5) for the prevention of obesity or overweight in

children? Note that our original Agency for Healthcare Research and Quality study also

included KQ6 ‘What is the comparative effectiveness of consumer health informatics

applications for the prevention of obesity or overweight in children?’ and KQ7 ‘What is the

comparative effectiveness of multi-setting interventions for the prevention of obesity or

overweight in children?’, but, in the present study, the interventions previously classified

Wang et al. Page 27

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under these headings were grouped into KQ1 or KQ2 based on if the intervention was

primarily school or home based, or another KQ based on the key intervention setting. We

merged KQ6 and KQ7 with the other KQ groups to help simplify the presentation of

information and because of the relatively small number of studies originally grouped into

KQ6 and KQ7.

Wang et al. Page 28

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t

Figure 2. Meta-analyses of changes in body mass index (BMI) and BMI z-score of school-based, diet–

physical activity combined childhood obesity prevention studies. (a) Change in BMI z-score

in studies taking place only in school. (b) Change in BMI in studies taking place only in

school. (c) Change in BMI in studies taking place in school with a home-based intervention

component.

WMD, weighted mean difference.

Wang et al. Page 29

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Wang et al. Page 30

T a b

le 1

S um

m ar

y of

t he

r es

ul ts

o f

th e

13 9

ch il

dh oo

d ob

es it

y pr

ev en

ti on

s tu

di es

o n

ad ip

os it

y- re

la te

d ou

tc om

es * †

S et

ti n

g T

yp e

of in

te rv

en ti

on ,

n u

m b

er o

f st

u d

ie s

Y ea

rs o

f p

u b

li ca

ti on

E n

ro ll

ed p

ar ti

ci p

an ts

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d ie

s w

it h

lo w

/m od

er at

e/ h

ig h

ri sk

o f

b ia

s (n

)

% w

it h

f av

ou ra

b le

ou tc

om e

(P <

0 .0

5) %

w it

h f

av ou

ra b

le ou

tc om

e (P

< 0

.0 5

n ot

n ec

es sa

ry )

R is

k o

f b

ia s

C on

si st

en cy

P re

ci si

on S

tr en

gt h

o f

ev id

en ce

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oo l

ba se

d

S

ch oo

l on

ly D

, 3 19

95 –2

01 2

2, 42

3 1/

2/ 0

67 10

0 M

od er

at e

C on

si st

en t

Im pr

ec is

e M

od er

at e

P A

, 1 8

19 93

–2 01

3 10

,4 88

0/ 14

/4 22

72 M

od er

at e

C on

si st

en t

Im pr

ec is

e M

od er

at e

C , 4

0 19

85 –2

01 3

47 ,6

65 2/

29 /9

44 53

M od

er at

e In

co ns

is te

nt Im

pr ec

is e

In su

ff ic

ie nt

S

ch oo

l an

d ho

m e

D , 1

19 86

1, 32

1 0/

1/ 0

10 0

10 0

M od

er at

e N

A P

re ci

se In

su ff

ic ie

nt

P A

, 3 19

99 –2

01 0

1, 65

4 1/

2/ 0

10 0

10 0

M od

er at

e C

on si

st en

t P

re ci

se H

ig h

C , 2

8 19

91 –2

01 3

33 ,2

97 2/

20 /6

36 79

M od

er at

e C

on si

st en

t Im

pr ec

is e

M od

er at

e

S

ch oo

l, h

om e

an d

co m

m un

it y

P A

, 1 20

10 2,

82 9

0/ 1/

0 0

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od er

at e

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ec is

e In

su ff

ic ie

nt

C , 9

20 08

–2 01

3 11

,7 76

1/ 5/

3 11

83 M

od er

at e

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si st

en t

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ec is

e H

ig h

S

ch oo

l an

d co

m m

un it

y D

, 1 20

09 2,

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0/ 1/

0 10

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0 M

od er

at e

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ci se

In su

ff ic

ie nt

P A

, 1 20

08 1,

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0/ 0/

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ig h

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ec is

e In

su ff

ic ie

nt

C , 4

19 97

–2 01

2 5,

41 6

0/ 2/

2 25

75 H

ig h

C on

si st

en t

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ec is

e M

od er

at e

S

ch oo

l an

d co

ns um

er h

ea lt

h in

fo rm

at ic

s (C

H I)

P A

, 2 20

07 –2

01 2

1, 33

5 0/

2/ 0

0 0

M od

er at

e In

co ns

is te

nt Im

pr ec

is e

In su

ff ic

ie nt

C , 3

20 06

–2 01

3 2,

28 0

0/ 3/

0 33

33 M

od er

at e

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ns is

te nt

Im pr

ec is

e In

su ff

ic ie

nt

S

ch oo

l, h

om e

an d

C H

I C

, 1 20

11 58

9 0/

0/ 1

0 0

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h N

A Im

pr ec

is e

In su

ff ic

ie nt

H om

e ba

se d

H

om e

on ly

D , 1

20 04

59 0/

1/ 0

0 0

M od

er at

e N

A Im

pr ec

is e

In su

ff ic

ie nt

C , 3

20 01

–2 01

2 26

2 0/

2/ 1

0 33

M od

er at

e In

co ns

is te

nt Im

pr ec

is e

L ow

H

om e,

s ch

oo l

an d

co m

m un

it y

C , 1

20 09

1, 32

3 0/

0/ 1

0 0

H ig

h N

A Im

pr ec

is e

In su

ff ic

ie nt

H

om e,

p ri

m ar

y ca

re a

nd C

H I

C , 1

20 06

87 8

1/ 0/

0 0

U na

bl e

to d

et er

m in

e L

ow N

A Im

pr ec

is e

In su

ff ic

ie nt

P ri

m ar

y ca

re s

et ti

ng

P

ri m

ar y

ca re

C , 1

20 09

60 0

0/ 1/

0 0

0 M

od er

at e

N A

Im pr

ec is

e In

su ff

ic ie

nt

P

ri m

ar y

ca re

a nd

h om

e C

, 2 20

12 25

3 1/

1/ 0

50 50

M od

er at

e In

co ns

is te

nt Im

pr ec

is e

In su

ff ic

ie nt

C hi

ld c

ar e

se tt

in g

C

hi ld

c ar

e P

, 2 20

07 –2

01 2

82 7

0/ 0/

2 50

50 H

ig h

In co

ns is

te nt

Im pr

ec is

e In

su ff

ic ie

nt

C , 3

20 09

–2 01

2 2,

39 3

1/ 2/

0 33

33 M

od er

at e

In co

ns is

te nt

Im pr

ec is

e L

ow

C om

m un

it y

ba se

d

Obes Rev. Author manuscript; available in PMC 2015 September 07.

A u th

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Wang et al. Page 31

S et

ti n

g T

yp e

of in

te rv

en ti

on ,

n u

m b

er o

f st

u d

ie s

Y ea

rs o

f p

u b

li ca

ti on

E n

ro ll

ed p

ar ti

ci p

an ts

S tu

d ie

s w

it h

lo w

/m od

er at

e/ h

ig h

ri sk

o f

b ia

s (n

)

% w

it h

f av

ou ra

b le

ou tc

om e

(P <

0 .0

5) %

w it

h f

av ou

ra b

le ou

tc om

e (P

< 0

.0 5

n ot

n ec

es sa

ry )

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k o

f b

ia s

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si st

en cy

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ci si

on S

tr en

gt h

o f

ev id

en ce

C

om m

un it

y on

ly P

A , 1

20 10

46 0/

1/ 0

0 0

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er at

e N

A Im

pr ec

is e

In su

ff ic

ie nt

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om m

un it

y an

d sc

ho ol

C , 3

19 97

–2 01

0 2,

96 6

pl us

2 4

sc ho

ol s

(m ea

n en

ro lm

en t

11 09

) 0/

3/ 0

66 66

M od

er at

e In

co ns

is te

nt Im

pr ec

is e

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er at

e

C

om m

un it

y, s

ch oo

l an

d ho

m e

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20 07

–2 00

8 1,

32 6

0/ 1/

0 10

0 10

0 M

od er

at e

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ci se

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ff ic

ie nt

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om m

un it

y an

d ho

m e

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20 10

56 4

0/ 1/

1 0

0 H

ig h

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si st

en t

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ec is

e In

su ff

ic ie

nt

C

om m

un it

y, h

om e,

p ri

m ar

y ca

re a

nd c

hi ld

c ar

e C

, 1 20

10 43

,8 11

0/ 1/

0 10

0 10

0 M

od er

at e

N A

P re

ci se

In su

ff ic

ie nt

C

om m

un it

y, s

ch oo

l, p

ri m

ar y

ca re

a nd

c hi

ld c

ar e

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20 10

N R

0/ 0/

1 10

0 10

0 H

ig h

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P re

ci se

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ff ic

ie nt

C

om m

un it

y, h

om e,

s ch

oo l

an d

ch il

d ca

re C

, 1 20

13 2,

63 1

0/ 0/

1 0

50 H

ig h

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ec is

e In

su ff

ic ie

nt

R is

k o

f b

ia s:

T he

D ow

ns a

nd B

la ck

C he

ck li

st f

or M

ea su

ri ng

Q ua

li ty

w as

u se

d to

a ss

es s

th e

ri sk

o f

bi as

i n

th e

in cl

ud ed

s tu

di es

.

C on

si st

en cy

: T

he b

od y

of e

vi de

nc e

w as

c on

si de

re d

to b

e co

ns is

te nt

i n

di re

ct io

n if

≥ 70

% o

f th

e st

ud ie

s ha

d an

e ff

ec t

in t

he s

am e

di re

ct io

n.

P re

ci si

on :

W e

co ns

id er

ed t

he b

od y

of e

vi de

nc e

pr ec

is e

if ≥

70 %

o f

th e

st ud

ie s

re po

rt ed

s ta

ti st

ic al

ly s

ig ni

fi ca

nt r

es ul

ts (

P <

0 .0

5) o

r ha

d na

rr ow

c on

fi de

nc e

in te

rv al

s th

at e

xc lu

de d

th e

nu ll

.

S tr

en gt

h o

f th

e ev

id en

ce :

W e

co ns

id er

ed t

he f

ou r

re co

m m

en de

d do

m ai

ns :

(i )

ri sk

o f

bi as

i n

th e

in cl

ud ed

s tu

di es

; (i

i) d

ir ec

ti on

o f

th e

ev id

en ce

; (i

ii )

co ns

is te

nc y

ac ro

ss s

tu di

es a

nd (

iv )

pr ec

is io

n of

t he

p oo

le d

es ti

m at

e or

t he

i nd

iv id

ua l

st ud

y es

ti m

at es

. W e

id en

ti fi

ed a

ll s

tu di

es a

s pr

ov id

in g

di re

ct e

vi de

nc e

si nc

e al

l of

t he

s tu

di ed

i nt

er ve

nt io

ns d

ir ec

tl y

af fe

ct ed

o ne

o f

th e

st ud

y’ s

pr im

ar y

ou tc

om es

o f

in te

re st

.

* A

di po

si ty

-r el

at ed

o ut

co m

es :

fo r

ex am

pl e,

b od

y m

as s

in de

x (B

M I)

, B M

I z-

sc or

e, w

ai st

c ir

cu m

fe re

nc e

an d

sk in

-f ol

d th

ic kn

es s.

† O

ur o

ri gi

na l

K Q

6 fo

cu se

d on

c on

su m

er h

ea lt

h in

fo rm

at ic

s- ba

se d

in te

rv en

ti on

s. T

he se

r es

ul ts

a re

r ep

or te

d he

re u

nd er

o th

er K

Q s

ba se

d on

p ri

m ar

y se

tt in

g.

C , d

ie t–

P A

c om

bi ne

d in

te rv

en ti

on s;

D , d

ie t-

on ly

i nt

er ve

nt io

n; N

A , n

ot a

pp li

ca bl

e; N

R , n

ot r

ep or

te d;

P A

, P A

-o nl

y in

te rv

en ti

on .

Obes Rev. Author manuscript; available in PMC 2015 September 07.

A u th

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t A

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t A

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t

Wang et al. Page 32

T a b

le 2

P er

ce nt

ag e

(% )

of c

hi ld

ho od

o be

si ty

p re

ve nt

io n

st ud

ie s

sh ow

in g

fa vo

ur ab

le a

di po

si ty

-r el

at ed

o ut

co m

es b

y pr

im ar

y in

te rv

en ti

on s

et ti

ng a

nd t

yp e

of i

nt er

ve nt

io n*

S et

ti n

g T

yp e

of i

n te

rv en

ti on

, n u

m b

er of

s tu

d ie

s %

w it

h s

ta ti

st ic

al ly

s ig

n if

ic an

t an

d f

av ou

ra b

le r

es u

lt s

(P <

0 .0

5) %

w it

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lt s

(P <

0 .0

5 n

ot n

ec es

sa ry

)

D ie

t- on

ly in

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ly in

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on s

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b in

ed d

ie t–

P A

in te

rv en

ti on

s T

ot al

D ie

t- on

ly in

te rv

en ti

on s

P A

-o n

ly in

te rv

en ti

on s

C om

b in

ed d

ie t–

P A

in te

rv en

ti on

s T

ot al

S ch

oo l

ba se

d D

, 5 ;

P A

, 2 5;

C , 8

5; T

ot al

, 1 15

80 28

36 36

10 0

64 64

66

H om

e ba

se d

D , 1

; P

A , 0

; C

, 5 ;

T ot

al , 6

0 –

0 0

0 –

20 17

P ri

m ar

y ca

re b

as ed

D , 0

; P

A , 0

; C

, 3 ;

T ot

al , 3

– –

33 33

– –

33 33

C hi

ld c

ar e

ba se

d D

, 0 ;

P A

, 2 ;

C , 3

; T

ot al

, 5 –

50 33

40 –

50 33

40

C om

m un

it y

ba se

d D

, 1 ;

P A

, 1 ;

C , 8

; T

ot al

, 1 0

10 0

0 50

50 10

0 0

63 60

T ot

al D

, 7 ;

P A

, 2 8;

C , 1

04 ;

T ot

al , 1

39 71

29 35

36 86

61 60

62

* O

ur o

ri gi

na l

K Q

6/ se

tt in

g fo

cu se

d on

c on

su m

er h

ea lt

h in

fo rm

at ic

s- ba

se d

in te

rv en

ti on

s. T

he se

r es

ul ts

a re

r ep

or te

d he

re u

nd er

o th

er K

Q s

ba se

d on

p ri

m ar

y se

tt in

g.

C , d

ie t–

P A

c om

bi ne

d in

te rv

en ti

on s;

D , d

ie t-

on ly

i nt

er ve

nt io

n; P

A , P

A -o

nl y

in te

rv en

ti on

.

Obes Rev. Author manuscript; available in PMC 2015 September 07.

A u th

o r M

a n u scrip

t A

u th

o r M

a n u scrip

t A

u th

o r M

a n u scrip

t A

u th

o r M

a n u scrip

t

Wang et al. Page 33

T a b

le 3

P er

ce nt

ag e

(% )

of c

hi ld

ho od

o be

si ty

p re

ve nt

io n

st ud

ie s

sh ow

in g

fa vo

ur ab

le a

di po

si ty

-r el

at ed

o ut

co m

es b

y in

te rv

en ti

on s

et ti

ng (s

) an

d ty

pe o

f in

te rv

en ti

on

S et

ti n

g( s)

T yp

e of

i n

te rv

en ti

on , n

u m

b er

of s

tu d

ie s

% w

it h

s ta

ti st

ic al

ly s

ig n

if ic

an t

an d

f av

ou ra

b le

r es

u lt

s (P

< 0

.0 5)

% w

it h

f av

ou ra

b le

r es

u lt

s (d

o n

ot n

ee d

t o

b e

P <

0 .0

5)

D ie

t- on

ly in

te rv

en ti

on s

P A

-o n

ly in

te rv

en ti

on s

D ie

t– P

A c

om b

in ed

in te

rv en

ti on

s T

ot al

D ie

t- on

ly in

te rv

en ti

on s

P A

-o n

ly in

te rv

en ti

on s

D ie

t– P

A c

om b

in ed

in te

rv en

ti on

s T

ot al

1. S

in gl

e se

tt in

g in

te rv

en ti

on s

S

ch oo

l on

ly D

, 3 ;

P A

, 1 8;

C , 4

0; T

ot al

, 6 1

67 22

44 39

10 0

72 53

61

H

om e

on ly

D , 1

; P

A , 0

; C

, 3 ;

T ot

al , 4

0 –

0 0

0 –

33 25

P

ri m

ar y

ca re

o nl

y D

, 0 ;

P A

, 0 ;

C , 1

; T

ot al

, 1 –

– 0

0 –

– 0

0

C

hi ld

c ar

e on

ly D

, 0 ;

P A

, 2 ;

C , 3

; T

ot al

, 5 –

50 33

40 –

50 33

40

C

om m

un it

y on

ly D

, 0 ;

P A

, 1 ;

C , 0

; T

ot al

, 1 –

0 –

0 –

0 –

0

A

ll s

in g le

s et

ti n g i

n te

rv en

ti o n s

(o ve

ra ll

) D

, 4 ;

P A

, 2 1;

C , 4

7; T

ot al

, 7 2

50 24

39 35

75 67

49 56

2. M

ul ti

pl e

se tt

in g

in te

rv en

ti on

s*

S

ch oo

l an

d ho

m e

D , 1

; P

A , 3

; C

, 2 8;

T ot

al , 3

2 10

0 10

0 36

44 10

0 10

0 79

81

S

ch oo

l an

d co

m m

un it

y D

, 1 ;

P A

, 1 ;

C , 7

; T

ot al

, 9 10

0 0

43 44

10 0

0 71

67

C

om m

un it

y an

d ho

m e

D , 0

; P

A , 0

; C

, 2 ;

T ot

al , 2

– 0

– 0

– 0

– 0

S

ch oo

l, h

om e

an d

co m

m un

it y

D , 0

; P

A , 1

; C

, 1 1;

T ot

al , 1

2 –

0 18

17 –

0 77

71

A

ll m

u lt

ip le

s et

ti n g i

n te

rv en

ti o n s

(o ve

ra ll

) D

, 2 ;

P A

, 5 ;

C , 4

8; T

ot al

, 5 5

10 0

60 40

44 10

0 60

74 74

T ot

al D

, 6 ;

P A

, 2 6;

C , 9

5; T

ot al

, 1 27

67 31

39 39

83 65

62 63

* S

ch oo

l an

d co

m m

un it

y, b

ot h

‘S ch

oo l

an d

C om

m un

it y’

a nd

‘ C

om m

un it

y an

d S

ch oo

l’ b

as ed

i nt

er ve

nt io

ns . S

ch oo

l an

d ho

m e

an d

co m

m un

it y,

‘ S

ch oo

l, H

om e

an d

C om

m un

it y’

, ‘ H

om e,

S ch

oo l

an d

C om

m un

it y’

, a nd

‘ C

om m

un it

y, S

ch oo

l an

d H

om e’

b as

ed i

nt er

ve nt

io ns

.

C , d

ie t–

P A

c om

bi ne

d in

te rv

en ti

on s;

D , d

ie t-

on ly

i nt

er ve

nt io

n; P

A , P

A -o

nl y

in te

rv en

ti on

.

Obes Rev. Author manuscript; available in PMC 2015 September 07.

A u th

o r M

a n u scrip

t A

u th

o r M

a n u scrip

t A

u th

o r M

a n u scrip

t A

u th

o r M

a n u scrip

t

Wang et al. Page 34

Table 4

Recommendations for future research in childhood obesity prevention based on our systematic review

Although we have found promising effects for school-based interventions for childhood obesity prevention, many questions still remain unanswered. We recommend additional research in the following areas:

1 Intervention studies conducted in non-school-based settings: The literature on interventions that take place in settings other than schools is sparse. We need more studies that test environmental and policy-based interventions. Also, very few preventive studies took place in clinical settings such as in primary care practices. Primary healthcare providers could play an important role in childhood obesity prevention by providing healthful eating and exercise guidelines to children and their parents, as well as by regularly monitoring body weight.

2 Innovative study design and intervention approaches: Drawing upon established behavioural theories and strategies when designing interventions may help researchers increase their success in childhood obesity prevention. For example, only a few studies used social marketing to inform the delivery of messages on nutrition, PA and health. Studies may integrate this approach with other intervention components to promote healthful lifestyle changes. Consumer health informatics may have promise. However, only seven studies used consumer health informatics in our study and only one significantly reduced obesity risk.

3 Systems science-guided intervention studies: Obesity is the result of a complex mix of biological, behavioural, social, economic and environmental factors. An effective and sustainable strategy for obesity prevention may have to target many factors. Applying a systems science approach in intervention design, implementation and evaluation can take into account multiple risk factors as well as the complex interactions and feedback loops between them.

4 Potential differential effects of interventions across subgroups: Research into population subgroups (e.g. given gender, age, race/ ethnicity or socioeconomic status) and the potentially different responses across groups to the same intervention may help tailor and target future interventions to maximize beneficial impacts. Most of the studies included in this review did not report their results by population subgroup.

5 Programmes of greater statistical power: Interventions with larger sample sizes and lengthier follow-up are important. Most of the interventions we reviewed resulted in modest behavioural changes. Many factors can potentially affect individual dietary and PA behaviours so the study sample or follow-up time may not be sufficiently large or long enough for an intervention’s impact to be seen.

6 Publication of intervention process evaluation results: Publication of process evaluation results from the intervention’s implementation should be encouraged. Such knowledge is important to carry out translational research and for the scaling up of public health interventions. Very few of the studies we reviewed here reported process evaluation results. Future studies may consider building in process evaluation during the intervention design, data collection and final analysis stages.

7 Application of rigorous analytical approaches: More rigorous analytical approaches are needed to better analyse repeated measures often collected during longer term follow-up periods, to control for potential confounding variables remaining after randomization and to test for effect modification and heterogeneity in the treatment or intervention effect.

8 Assessment of the intervention cost-effectiveness: Although challenging, cost-effectiveness analyses will add important value to an intervention’s evaluation. Such information is also important for the promotion and dissemination of effective interventions as well as for informing policymakers’ decisions. Very few studies reported obesity prevention programme costs.

9 Obesity prevention research in adolescents: Obesity in adolescents has been found to be more predictive of obesity during adulthood than obesity in younger children. Adolescence is an important stage of life when young people are exposed to various social and environmental factors that establish lifelong life habits. Although studies examined in this review included children aged 2–18, analyses could not be limited to teens as results were not reported in this manner. As recommended earlier, subgroup-oriented research may offer in-depth information on obesity prevention important to consider for this life stage.

10 Potential harms: The implementation of intervention programmes may also have potential harms, such as inciting stigma when implemented on a large scale to many children but to little or no effects (as was observed with most studies included in our review). Children enrolled in obesity prevention programmes are weighed and/or measured and may anticipate improvements. If no significant improvements (or benefits) were observed, some may feel a sense of failure or lowered self-esteem. Although we did not see evidence of this in the studies we reviewed, future research is needed to examine this issue more in-depth.

PA, physical activity.

Obes Rev. Author manuscript; available in PMC 2015 September 07.