Browse Subject Areas

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here.

  • Loading metrics

Early childhood obesity prevention efforts through a life course health development perspective: A scoping review

  • Sheri Volger ,

    Roles Conceptualization, Data curation, Formal analysis, Methodology, Writing – original draft, Writing – review & editing

    Affiliation Department of Clinical and Preventive Nutrition Sciences, School of Health Professions, Biomedical and Health Sciences, Rutgers University, Newark, New Jersey, United States of America

  • Diane Rigassio Radler,

    Roles Conceptualization, Methodology, Supervision, Writing – original draft, Writing – review & editing

    Affiliation Department of Clinical and Preventive Nutrition Sciences, School of Health Professions, Biomedical and Health Sciences, Rutgers University, Newark, New Jersey, United States of America

  • Pamela Rothpletz-Puglia

    Roles Conceptualization, Data curation, Methodology, Supervision, Writing – original draft, Writing – review & editing

    Affiliation Department of Clinical and Preventive Nutrition Sciences, School of Health Professions, Biomedical and Health Sciences, Rutgers University, Newark, New Jersey, United States of America

Early childhood obesity prevention efforts through a life course health development perspective: A scoping review

  • Sheri Volger, 
  • Diane Rigassio Radler, 
  • Pamela Rothpletz-Puglia


17 Jan 2019: Volger S, Rigassio Radler D, Rothpletz-Puglia P (2019) Correction: Early childhood obesity prevention efforts through a life course health development perspective: A scoping review. PLOS ONE 14(1): e0211288. View correction



The obesity rate in preschool children in the United States (US) is 13.9%, while even higher rates are associated with racial and ethnic minorities and children from low-income families. These prevalence patterns underscore the need to identify effective childhood obesity prevention programs.


A scoping review was conducted following Arksey and O’Malley’s framework to provide an overview of the types, effectiveness and cost-effectiveness of obesity prevention interventions and policies in children up to 6 years old. Inclusion criteria were studies at least 6-months duration; included a weight-based outcome, conducted in the US, English publications from January 2001 to February 2018. Exclusions: studies in overweight/obese children and obesity treatments, no comparator group. Evidence was characterized across the early life course and multiple-levels of influence.


From the 2,180 records identified, 34 met the inclusion criteria. Less than half of the interventions initiated during pregnancy, infancy or preschool reported a significant improvement in a weight-based outcome. All interventions included strategies to influence individual- or interpersonal-level health behaviors, yet few removed obstacles in the healthcare system, physical/built environment, or sociocultural environment. The majority (78%) of the interventions occurred during preschool years, with 63% conducted in early childcare education settings serving low-income families. The health impact of the state-wide and national policies on children under age 6 years remains unclear. There was considerable uncertainty around estimates of the health and economic impacts of obesity prevention interventions and policies.


There is a need to intensify early childhood obesity preventive efforts during critical periods of health development in the US. Future studies should estimate the feasibility, program effectiveness, and cost of implementing multilevel obesity prevention interventions and policies. Addressing these research gaps will provide stakeholders with the scientific evidence necessary to facilitate funding and policy decisions to decrease the prevalence of early childhood obesity.


Despite recommendations to prioritize obesity prevention efforts, [14] epidemiological data from the 2015–2016 National Health and Nutrition Examination Survey (NHANES) found that the prevalence of early childhood obesity remains at a 10-year high [5]. Furthermore, obesity rates among school-aged children aged 6–11 years are approximately 25% higher compared with preschool children aged 2–5 years [5]. In addition, even higher obesity rates are differentially associated with minorities and children from low-income families [6]. These prevalence patterns underscore the need to focus on early childhood obesity prevention efforts with the goal of meeting the Healthy People 2020 obesity rate target of 9.4% [2]

The evaluation of such efforts should be guided by framework models that consider the various levels that influence an individual’s health trajectory [7, 8]. For example, the National Institute on Minority Health and Health Disparities (NIMHD) Research Framework represents the multiple levels of modifiable and interacting determinants that contribute to health disparities (Fig 1) [9]. While the multi-level Life Course Health Development Framework perspective also recognizes that health-development unfolds over the life course, is sensitive to time and environment, adaptive, and requires a balance among all levels of health [10]. Together, these models are well-suited for evaluating and characterizing childhood obesity prevention efforts and informing future interventions.

Fig 1. Framework used to characterize components of early childhood obesity prevention interventions across the early life course.

Adapted from The National Institute on Minority Health and Health Disparities (NIMHD) Research Framework [9].

We conducted a scoping review to provide an overview of the current state of obesity prevention efforts in the United States (US) with children less than 6 years of age, and to answer two questions: “What types of interventions and policies are being used for obesity prevention across the early life course and at multiple levels of influence?” and “How effective are they?” The secondary aim was to describe the best available evidence on the cost and cost-effectiveness of implementing obesity prevention interventions and policies.


A scoping review was conducted to expand on previous systematic and narrative reviews of obesity prevention efforts in young children and to identify scientific evidence from a broad range of interventional studies, government and non-governmental programs, and local and national policies in the US. The scoping study design was chosen because it offers a framework to identify, “map”, merge evidence, and synthesize a broad range of evidence. Furthermore, the scoping review methodology is focused on providing conceptual clarity and allows researchers to focus on questions with relevance to target populations and locations [1112].

The scoping review process is based on the Arksey and O’Malley’s 5-stage methodological framework [11]. The 5-stages that served as a roadmap for the present review are: 1. identifying the research question; 2. identifying relevant studies; 3. study selection; 4. charting the data, and 5. collating, summarizing and reporting the results. [11]. While the Joanna Briggs Institute’s Reviewer’s Manual of best research practice guidelines for conducting a systematic scoping review, served as a guide for the present review [12]. To ensure consistency, transparency, and reproducibility an a priori scoping review protocol was developed and directed the review process.

Data sources

After formulating the review objectives and the research questions (Stage 1), a literature search was conducted to identify relevant studies (Stage 2) in the Cochrane Central Register of Controlled Trials, MEDLINE PubMed, CINAHL, PsycINFO, and EconLit databases from January 2001 to February 2018. The timeframe was chosen because in 2001 the Department of Health and Human Services published “The Surgeon General's Call To Action To Prevent and Decrease Overweight and Obesity” [13] prioritizing the public health response to the growing obesity epidemic.

Search strategy

A search strategy was devised with the assistance of an Information & Education Librarian (MG) for PubMed using keywords from obesity prevention articles and modified for the additional electronic databases. Table 1 shows the search syntax and strategy.

Study selection

During study selection (Stage 3), publication titles and abstracts were screened, duplicates deleted, and full-text articles reviewed for eligibility based on the review’s inclusion criteria. References from the bibliographies of included trials were hand searched. Two researchers (SV, PRP) independently reviewed, discussed, and agreed upon the eligibility of all studies. While systematic reviews adhere to rigid inclusion criteria, scoping studies’ inclusion criteria are broad to allow for the evaluation of a wide range of information [12]. Eligible studies were included if they incorporated a comparator group; were conducted in children with a normal or healthy weight (BMI-for-age percentile between the 5th percentile to less than the 85th percentile); children under the age of 6 or woman in any setting, and reported at least one weight-based outcome measure of growth or weight status (Table 1). While critical appraisal of methodology is not the focus of scoping reviews, we followed a standardized research protocol and applied the Dixon Woods threshold to exclude articles judged "fatally flawed" [14].

Data extraction

Data extraction (Stage 4) was done using a two-step process. First, a Microsoft Excel, version 2016 (Microsoft, Redmond, WA) data extraction template was developed to chart continuous and categorical variables and perform summary statistics. S1 Appendix shows a list of the key data extraction variables. Next, included articles were imported into Nvivo 11 Pro (QRS International, Doncaster, Australia) and qualitative data were extracted by selecting, coding and creating nodes (files) representing key concepts. A coding structure and organizational hierarchy was created to characterize major themes by life course, concepts and context pertaining to the NIMHD Framework (Fig 1).


Collating, summarizing and reporting the results (Stage 5)

Fig 2 describes the literature search and study selection process. We identified a total of 2,467 records. After removing duplicate records, the titles and abstracts of 2,180 records were screened for inclusion. The full text of 73 articles were reviewed for eligibility and 34 studies were included in the review.

Fig 2. Flow diagram showing literature and study selection.

Adapted from Moher D, Liberati A, Tetzlaff J, Altman DG. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. BMJ (Clinical research ed). 2009;339:b2535, [15].

Study characteristics

The included studies examined the collective experiences of approximately 900 pregnant women, 1,600 infants and 10,000 preschool aged children across 16 states, in 10 urban centers, and a mix of suburban and rural communities (Tables 24). The interventions (n = 25) were initiated during three stages in the early life course: pregnancy (n = 3),[1618], infancy (n = 3), [1921] and preschool (n = 19), [2240]. The majority (88%, 22/25) of the interventions used an experimental study design (19–40).

We identified 6 publications examining the impact of city, state and national obesity prevention policies [4146]. Three additional studies calculated the net cost or cost-effectiveness of obesity prevention interventions [4749].

In total, 11 (44%) interventions reported a positive benefit on a weight-based measure of growth or weight status (e.g., weight, weight/weight percentiles, BMI/ BMI z-score, and BMI categories) [17, 19, 20, 2225, 28, 31, 36, 38]. The effectiveness of the interventions was inconsistent and contradictory across all stages of the early life course. Tables 24 provide descriptions of the characteristics and outcomes of the interventions.

Studies initiated during pregnancy

This review identified 3 studies initiated during pregnancy conducted in children from low-income families and members of racial-ethnic minority groups who are at higher risk of obesity [6] and in a variety of settings [urban healthcare clinic-bases [16]; community-wide plus home-visits [17]; community-wide plus primary care practice], (Table 2), [18)]. All three interventions focused on similar individual- and interpersonal-level behaviors (preventing excess gestational weight gain [16, 18] and accelerated infant growth [1618]), two studies also focused on community-level influences [1718] but only the one study [17] that implemented interventional components at multilevel domains of influence demonstrated a positive effect on Body Mass Index z-score (BMI-z) in American Indian/Alaskan Native tribal communities in the multi-level, community wide-plus home-visit intervention.

Interventions during infancy

Two [19, 20] of the three [1921] studies identified were initiated during infancy and showed a positive effect on infant growth (Table 3). All studies included behavioral strategies at the individual and interpersonal level aimed at increasing knowledge of healthy food choices and appropriate growth patterns. The Well Baby Group (WBG) intervention also targeted community levels of influence by delivering sociocultural adapted nutrition education and providing a peer social support network while maximizing the physical environment and healthcare system resources at a federally qualified community health center [19]. At two years, the infants of low-income, predominately Hispanic mothers attending the WBG were significantly less likely to have a BMI-for-age ≥ 85th percentile compared with a randomly selected comparisons group of infants. Also, at one year, infants of mothers who received both the home-based intervention Soothe/Sleep and Introduction to Solids interventions had lower mean weight-for-length percentiles (33rd vs. 50th) compared to the no intervention group [20].

Interventions in preschool aged children

Childcare center-based interventions.

Over half (63%, 12/19) of the preschool-aged interventions enrolled children from low-income, racially and ethnically diverse families from Head Start centers (n = 7), YMCA-affiliated childcare centers (n = 2) or other subsidized childcare programs (n = 3), (Table 4). The childcare center-based interventions included in this review were designed with interventional components that primarily focused on influencing individual- or interpersonal-level health behaviors of the children and preschool teachers. Only 42% (5/12) of these interventions reported a significant improvement in either BMI-z score [22], BMI [2324, 28] and BMI percentile [36].

Of the interventions demonstrating a positive effect on BMI, two studies administered 30 minutes of moderate to vigorous physical activity (MVPA) for primarily African American (AA) children attending YMCA-affiliated preschools [23, 24]. Similarly, the “Hip-Hop to Health” efficacy trial [28] enrolled predominately AA preschoolers attending Head Start and used trained educators to deliver 20-minute healthy-lifestyle behavior themed lessons and 20 minutes of directed physical activity (PA). However, the same intervention did not have a beneficial effect on BMI in Latino preschoolers [29], nor did other similar effectiveness trial in Latino [30] and AA preschoolers [33, 50]. Another study found that five, 1-hour long healthy-lifestyle themed workshops presented by trained nurse childcare health consultant to parents, childcare teachers and staff, significantly decreased mean BMI-z scores in children from underserved minority families [22]. Finally, a multilevel, childcare-based intervention [36] showed a significantly smaller increase in the BMI percentile when intervention centers implemented early childcare center policies focused on modifying individual-level child, parent, and teacher behaviors with physical/built and sociocultural environment changes.

Primary care providers clinic-based.

Two primary care clinic-based studies [25, 37] reported contradictory results. Both studies targeted individual- and interpersonal-level behavioral changes, implemented in a healthcare environment. Only Cloutier and colleagues found a significantly greater reduction in BMI percentile in the intervention group that participated in bilingual, culturally adapted, motivational interviewing (MI) sessions during primary care provider (PCP) visits and phone-coaching session [25].

Community center-based.

Similarly, two interpersonal-level, family-based studies were conducted a community center-based environment with mixed results. Slusser and colleagues [38] randomized Latino mothers of preschoolers to receive nine culturally tailored, Spanish language, parent-training sessions or be in a Wait List Group (WLG). Despite reporting 33.3% attrition, the intervention group experienced a greater reduction in BMI percentile differences compared with the WLG at nine months. In contrast, Haines and colleagues [32] failed to demonstrate a significant improvement in BMI with a family-based, community health center intervention.

Other settings.

Additional preschool-aged interventions were conducted at a WIC site [40], online [39] and in the home and over the telephone [31]. Only one study reported a positive effect on BMI. In the “Healthy Habit, Healthy Home” [31] health educators used MI coaching techniques during home and phone coaching sessions, along with text messages to promote interpersonal-level changes in healthy family routines and PA, encourage family meals and beverage choices, adequate sleep and change the physical-built environment by asking families to remove TVs from the child’s bedroom. Although a WIC-based intervention within the community-wide Massachusetts Childhood Obesity Research Demonstration [51] found no effect on BMI-z scores, a post-hoc analysis excluding Asians (due to disproportionate distribution of Asian children in the comparison community) found a significant improvement in BMI-z scores [40].

Costs of obesity prevention interventions.

Table 5 includes a summary of three studies appraising the cost of preventing obesity. Cradock and colleagues [47] estimated the total annual cost per child associated with implementing and nationally disseminating the PA component of the childcare center-based “Hip-Hop Jr.” PA intervention was $22.65 yearly [33]. Also, Wright and colleagues [45] calculated the net cost of a primary-care based intervention [52], aimed at reducing obesity related behaviors and BMI in overweight and young, obese children at $196 per child [49]. In the third study, Ma and Frick [48] modeled the breakeven point of a hypothetical intervention producing a 1% reduction in the prevalence of obesity among children 0–6 years. Accounting for future medical costs, population-based interventions could cost up to $339 per child and still have a favorable health benefit/cost profile.

Policy interventions.

Six studies [4146] estimated the cost and health benefits of city-wide, and state and national policies aimed at preventing future weight gain and obesity (Table 5). Kuo and colleagues [41] developed a simulation model estimating the impact on annual weight gain in Los Angeles (LA) County of a California menu law mandating large restaurant chains to display the caloric content of menu items. The model assumed 10% of all customers would consume 100 calories less per meal and found the law was projected to avert as much as 500,000 lbs. of the estimated annual LA County population weight gain (1.25 million lbs.) in children 5 to 17 years old.

The Northeast Iowa Food and Fitness program enacted multilevel changes during a 6-year long program. The changes targeted schools and home meals and PA, established school gardens, and at the community-level provided access to outdoor recreational spaces and programs, local farmers markets and affordable healthy food. It was shown that children ages 4–12 years who had longer periods of program exposures (2 to 6 years) demonstrated a greater improvement in appropriate growth rate compared with children with shorter periods of program exposure (0 to 1 year) [46].

Dharmasena et al. utilized an economic demand model based on household purchasing habits to assess the impact of a 20% tax on SSB consumption, caloric intake and weight. Results using the most conservative estimate showed an overall reduction in SSB with corresponding increases in fruit juice and low-fat milk consumption. The interrelated changes in beverage consumption patterns was forecast to produce an average reduction of 449 calories per month resulting in a mean body weight reduction of 1.54 lbs/year.

Costs and cost effectiveness analysis.

Finally, three studies describe the economic impact and health consequences of obesity prevention policies using a Markov-based cohort model to estimate the cost effectiveness of: an excise tax on SSBs, [44] eliminating the tax subsidy for TV advertising, [42] and implementing a set of hypothetical childcare center-based policy changes [45], (Table 5). Sonneville and colleagues [42] found that eliminating the ability of food manufactures to deduct the cost of advertising unhealthy foods would result in a mean BMI reduction 0.028 per child [42]. Likewise, Wright and colleagues [45] estimated that a hypothetical childcare center-based policy (eliminating SSBs, limiting fruit juice, serving low-fat milk, limiting screen time and increasing MVPA) would result in a mean BMI reduction of 0.019 BMI units per child [45]. Finally, Long and colleagues [44] estimated that a tax of $0.01/ounce on SSBs would reduce the total calories consumed by children ages 2–4 and 5–9 years, by -1 to -13 kcal/day, respectively, and result in a mean reduction in BMI of approximately 0.16 units for children 2–19 years. The cost per unit BMI reduction based on these policies ranged from $1.16 for eliminating the advertising subsidy to $57.80 for the childcare center-based policy.


This scoping review identified the characteristics and effectiveness of obesity prevention interventions, programs and policies across the early life course and at multiple levels of influence in the US. There were a number of key findings (S2 Appendix). We found slightly less than half of the interventions initiated during pregnancy, infancy or preschool were effective at improving a weight-based measure of growth or weight status in young children [17, 19, 20, 2225, 28, 31, 36, 38]. All interventions included strategies to influence health behaviors at an individual or interpersonal level. However, few studies removed obstacles in the physical/built environment, sociocultural environment or healthcare system. The majority of the interventions were conducted in children at higher risk of obesity, in early childcare education settings. The impact of menu labeling laws, taxing SSBs and eliminating incentives for TV advertising of unhealthy foods, on a direct weight-based measure of growth or weight status in children under age 6 years remains unclear. Finally, this review confirmed the lack of available data on the cost of implementing obesity preventions efforts in the US.

We used the NIMHD Research framework [53] to guide our examination of obesity prevention efforts considering factors relevant to obesity and health equality research. We found that all interventions initiated during pregnancy and infancy focused on modifying biological risk factors of obesity by enhancing individual-level knowledge of healthy eating patterns, appropriate gestational weight gain, prolonged breastfeeding, delayed introduction of complementary feeding, responsive feeding techniques and appropriate infant growth patterns [19, 20]. For example, in the primary care setting, MI coaching techniques were applied to reduce obesogenic behaviors [25, 37], while in the childcare center setting, parents and teachers gained the necessary knowledge and skills to serve as role-models of healthy-lifestyle behaviors [19, 28, 36, 38]. Also, preschool children were encouraged to modify their behaviors using culturally adapted, nutrition and PA lessons [19, 28, 31, 36, 38], food group-themed, hand puppet activities [29], English and Spanish-language CDs [30], healthy snacks [22, 28, 36] and structured MVPA [23, 24, 28].

All effective interventions identified in this review incorporated interpersonal-level strategies affecting family behaviors and home routines. Parental and family participation was either a primary or secondary component of all successful interventions. Parents attended culturally tailored education sessions [38], home visits [17, 20, 31], or were assigned homework, received instructional handouts and newsletters promoting frequent family meals, adequate sleep, family PA and limiting screen time [20, 22, 25, 28, 31, 36, 38]. The inclusion of parent-direct strategies in successful interventions is consistent with the findings of a recent review of obesity prevention interventions in early childcare centers. Ward and colleagues [54] found that higher parent engagement in the early childcare settings enhanced the effectiveness of interventions by achieving a positive weight related outcome [54].

Recognizing the influence of physical environments on the risk of childhood obesity and health disparities is critical to the design of multilevel obesity prevention interventions. Yet, less than one-third of the studies aimed to modify a component in the physical/built environment. These interventions effectively removed barriers to facilitate healthier lifestyle behaviors. They included components such as removing TVs from bedrooms, providing alternative playtime activities, and implementing childcare centers polices limiting SSBs, serving water, low-fat milk, fruits and vegetables as snacks; increasing hours of PA, and limiting screen time [22, 31, 36]. At the community-level, Karanja and colleagues [17] enacted tribal-wide policies providing access to breast feeding rooms and reallocating resources by stocking vending machines with water and providing water coolers at community-sponsored activities. Collectively, these types of physical environment changes rendered healthy behaviors as the default behavior.

Approximately half of the interventions integrated strategies to change sociocultural environmental-level factors, with considerable variability in the intensity of the components. Few included primary objectives examining the effectiveness of culturally-tailored training programs [38, 39] or other high-intensity activities such as media campaigns encouraging drinking water and breastfeeding as cultural values [17] or establishing group sessions intended to support shared sociocultural values [19]. While the majority of studies included the following types of moderate- to low-intensity components: using bi-cultural/bilingual interventionalist [19, 25, 29, 30, 32, 36, 38, 39], culturally adapted curriculum [25, 26, 2831, 33, 34, 36, 38, 39] and providing culturally relevant recipes [19, 25, 26, 35, 39].

Healthcare system-level changes facilitate access to healthcare resources, engage parents in healthcare decisions and improve parent-healthcare provider relationships. Furthermore, the early initiation of interventions in the healthcare setting might alter the course of health and disease, and reduce future health disparities [55]. Yet, of the 5 healthcare-based interventions [16, 19, 21, 25, 37], only two reported improvements in a measure of obesity. One was informed by the chronic care model and used brief MI format [25], while the other used a patient-centered approach and group sessions [19]. In contrast, others failed to improve childhood growth trajectories [16, 21, 37]. Such results suggest that even in a healthcare setting, the intensity of the program and study population are important considerations for the success of any intervention.

This review identified studies that estimated the health and economic impact of regional and national SSBs pricing strategies, labeling laws and food marketing policies. These strategies were shown to change purchasing behavior and improve the prevalence of obesity, and potentially to generate tax revenue, drive the reformulation of unhealthy foods, and change social norms [42, 44]. Although the population reach and societal-level impact of obesity prevention policies are high, the long-term outcome on the prevalence of early childhood obesity remains uncertain.

None of the included interventions reported on the costs or cost effectiveness of the study. The lack of economic evaluations is a surprising finding given that the annual cost of obesity-related medical spending was estimated to exceed $147 billion [56]. Consistent with our findings, Wolfenden and colleagues [57] noted that 88% of the systematic reviews of obesity prevention intervention in children did not report whether a cost analysis has been conducted. In the absence of CEA data, a reliable cost threshold could assist stakeholders to determine the amount of money to spend on obesity prevention interventions. Ma and Frick [48] established the break-even cost of $339 per child as a “good value” for interventions resulting in a 1% reduction in childhood obesity prevalence.

There were several limitations to our review. First, our scoping review presented a comprehensive overview of the quantity and context of current childhood obesity prevention efforts in the US, which limits the generalizability of our findings to other countries. Next, our review did not identify any obesity prevention interventions conducted during pre-pregnancy and identified very few studies conducted during pregnancy. It is likely that our search strategy may not have been sensitive enough to identify the full breadth of research activities during these early life stages. Since we followed standardized methodology for scoping reviews, we did not assess the effect size of the interventions or systematical evaluate the quality of the individual studies including the risk of bias quality. We acknowledge that many of the studies were of varying quality based on study design, sample size, intensity, analytical approaches, high attrition rates and low parent attendance rates. Although we excluded studies judged to be fatally flawed, our results are subject to a range of biases due to these many threats to the internal and external validity of the study results. Furthermore, given that studies reporting positive results are more likely to be published, conclusions may also be subject to publication bias [44]. Finally, our synthesis was based on interventions reporting a weight-based measure of growth or weight status in normal weight children. Because we did not consider favorable behavioral or PA outcomes the generalization of our results may be limited.


This review presents an overview of the current state of obesity prevention efforts across multiple levels of influence and the early life course in the US. The majority of efforts focused on individual and interpersonal-level health behavior changes in preschoolers. Thus, there is a need to intensify obesity preventive efforts during critical periods of health development and target multiple levels of influence, especially regarding physical, sociocultural and healthcare system-level obesity risk factors. Furthermore, there is considerable uncertainty around estimates of the economic impacts of obesity prevention interventions and policies. Future studies should estimate the feasibility, effectiveness, and cost-effectiveness of obesity prevention interventions and policies. Addressing these research gaps may provide government agencies, policy makers, and healthcare payers with the necessary scientific evidence to make informed decisions regarding the allocation of funds for initiatives aimed at decreasing the prevalence of early childhood obesity.

Supporting information

S1 Appendix. Table of data extraction information for interventions.



We thank Mina Ghajar (Librarian, George F. Smith Library of the Health Sciences, University Libraries Rutgers) for her assistance with the literature search strategy.


  1. 1. Committee on Accelerating Progress in Obesity Prevention, Food and Nutrition Board, Institute of Medicine; Glickman D, Parker L, Sim LJ, Del Valle Cook H, Miller EA, (eds.). Accelerating Progress in Obesity Prevention: Solving the Weight of the Nation. 2012. Washington, DC: The National Academies Press. Available from:
  2. 2. Healthy People 2020 [Internet]. U.S. Department of Health and Human Services, Office of Disease Prevention and Health Promotion Washington, DC: [July 27, 2018]. Available from:
  3. 3. White House Task Force on Childhood Obesity Report to the President, Solving the Problem of Childhood Obesity. 2010. Office of the President of the United States. Available from
  4. 4. Office of the Surgeon General (US). The Surgeon General's Vision for a Healthy and Fit Nation. Rockville (MD): Office of the Surgeon General (US); 2010. Available from
  5. 5. Hales CM, Fryar CD, Carroll MD, Freedman DS, Ogden CL. Trends in obesity and severe obesity prevalence in US youth and adults by sex and age, 2007–2008 to 2015–2016. JAMA. 2018;319(16):1723–1725. pmid:29570750
  6. 6. Hales CM, Carroll MD, Fryar CD, Ogden CL. Prevalence of obesity among adults and youth: United States, 2015–2016. NCHS data brief. 2017;288:1–8.
  7. 7. Anderson NB. Levels of analysis in health science. A framework for integrating sociobehavioral and biomedical research. Annals of the New York Academy of Sciences. 1998;840:563–76. pmid:9629283
  8. 8. Halfon N, Hochstein M. Life Course Health Development: An integrated framework for developing health, policy, and research. The Milbank Quarterly. 2002;80(3):433–79. pmid:12233246
  9. 9. National Institute of Health. Nathional Institute on Minority Health and Health Disparities Research Framework [Available from:
  10. 10. Halfon N., Forrest C.B. The Emerging Theoretical Framework of Life Course Health Development. In: Halfon N., Forrest C., Lerner R., Faustman E. (eds) Handbook of Life Course Health Development. Springer, Cham; 2018: Chapter 2.
  11. 11. Arksey H, O'Malley L. Scoping Studies: towards a methodological framework. International Journal of Social Research Methodology. 2005;8(1):19–32.
  12. 12. Peters MDJ GC, McInerney P, Baldini Soares C, Khalil H, Parker D. Chapter 11: Scoping reviews. 2017. In: Joanna Briggs Institute Reviewer's Manual [Internet]. The Joanna Briggs Institute. Available from: Available from
  13. 13. U.S. Department of Health and Human Services. The Surgeon General’s call to action to prevent and decrease overweight and obesity. Rockville, MD: U.S. Department of Health and Human Services, Public Health Service, Office of the Surgeon General; 2001. Available from:
  14. 14. Dixon-Woods M, Cavers D, Agarwal S, Annandale E, Arthur A, Harvey J, et al. Conducting a critical interpretive synthesis of the literature on access to healthcare by vulnerable groups. BMC Medical Research Methodology. 2006;6:35. pmid:16872487
  15. 15. Moher D, Liberati A, Tetzlaff J, Altman DG. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. BMJ (Clinical research ed). 2009;339:b2535.
  16. 16. Gregory EF, Goldshore MA, Henderson JL, Weatherford RD, Showell NN. Infant growth following maternal participation in a gestational weight management intervention. Childhood Obesity. 2016;12(3):219–25. pmid:27123956
  17. 17. Karanja N, Lutz T, Ritenbaugh C, Maupome G, Jones J, Becker T, et al. The TOTS community intervention to prevent overweight in American Indian toddlers beginning at birth: a feasibility and efficacy study. Journal of Community Health. 2010;35(6):667–75. pmid:20508978
  18. 18. Olson CM, Baker IR, Demment MM, Graham ML, May JJ, Strawderman MS, et al. The healthy start partnership: an approach to obesity prevention in young families. Family & Community health. 2014;37(1):74–85.
  19. 19. Machuca H, Arevalo S, Hackley B, Applebaum J, Mishkin A, Heo M, et al. Well Baby Group Care: evaluation of a promising intervention for primary obesity prevention in toddlers. Childhood Obesity. 2016;12(3):171–8. pmid:27035857
  20. 20. Paul IM, Savage JS, Anzman SL, Beiler JS, Marini ME, Stokes JL, et al. Preventing obesity during infancy: a pilot study. Obesity. 2011;19(2):353–61. pmid:20725058
  21. 21. Schroeder N, Rushovich B, Bartlett E, Sharma S, Gittelsohn J, Caballero B. Early obesity prevention: a randomized trial of a practice-based intervention in 0-24-month infants. Journal of Obesity. 2015;2015:795859. pmid:26078877
  22. 22. Alkon A, Crowley AA, Neelon SE, Hill S, Pan Y, Nguyen V, et al. Nutrition and physical activity randomized control trial in child care centers improves knowledge, policies, and children's body mass index. BMC Public Health. 2014;14:215. pmid:24580983
  23. 23. Annesi JJ, Smith AE, Tennant GA. Reducing high BMI in African American preschoolers: effects of a behavior-based physical activity intervention on caloric expenditure. Southern Medical Journal. 2013;106(8):456–9. pmid:23912139
  24. 24. Annesi JJ, Smith AE, Tennant GA. Effects of a cognitive–behaviorally based physical activity treatment for 4- and 5-Year-old children attending US preschools. International Journal of Behavioral Medicine. 2013;20(4):562–6. pmid:24114718
  25. 25. Cloutier MM, Wiley J, Huedo-Medina T, Ohannessian CM, Grant A, Hernandez D, et al. Outcomes from a pediatric primary care weight management program: Steps to Growing Up Healthy. The Journal of pediatrics. 2015;167(2):372–7.e1. pmid:26073106
  26. 26. Davis SM, Myers OB, Cruz TH, Morshed AB, Canaca GF, Keane PC, et al. CHILE: Outcomes of a group randomized controlled trial of an intervention to prevent obesity in preschool Hispanic and American Indian children. Preventive medicine. 2016;89:162–8. pmid:27222162
  27. 27. Esquivel M, Nigg CR, Fialkowski MK, Braun KL, Li F, Novotny R. Head Start wellness policy intervention in Hawaii: a project of the children's healthy living program. Childhood Obesity. 2016;12(1):26–32. pmid:26771119
  28. 28. Fitzgibbon ML, Stolley MR, Schiffer L, Van Horn L, KauferChristoffel K, Dyer A. Two-year follow-up results for Hip-Hop to Health Jr.: a randomized controlled trial for overweight prevention in preschool minority children. The Journal of pediatrics. 2005;146(5):618–25. pmid:15870664
  29. 29. Fitzgibbon ML, Stolley MR, Schiffer L, Van Horn L, KauferChristoffel K, Dyer A. Hip-Hop to Health Jr. for Latino preschool children. Obesity. 2006;14(9):1616–25. pmid:17030973
  30. 30. Fitzgibbon ML, Stolley MR, Schiffer L, Kong A, Braunschweig CL, Gomez-Perez SL, et al. Family-based Hip-Hop to Health: outcome results. Obesity. 2013;21(2):274–83. pmid:23532990
  31. 31. Haines J, McDonald J, O'Brien A, Sherry B, Bottino CJ, Schmidt ME, et al. Healthy Habits, Happy Homes: randomized trial to improve household routines for obesity prevention among preschool-aged children. JAMA Pediatrics. 2013;167(11):1072–9. pmid:24019074
  32. 32. Haines J, Rifas-Shiman SL, Gross D, McDonald J, Kleinman K, Gillman MW. Randomized trial of a prevention intervention that embeds weight-related messages within a general parenting program. Obesity. 2016;24(1):191–9. pmid:26638185
  33. 33. Kong A, Buscemi J, Stolley MR, Schiffer LA, Kim Y, Braunschweig CL, et al. Hip-Hop to Health Jr. randomized effectiveness trial: 1-year follow-up results. American Journal of Preventive Medicine. 2016;50(2):136–44. pmid:26385162
  34. 34. Lumeng JC, Miller AL, Horodynski MA. Improving self-regulation for obesity prevention in Head Start: a randomized controlled trial. Pediatrics. 2017;139(5):1–10.
  35. 35. Natale RA, Lopez-Mitnik G, Uhlhorn SB, Asfour L, Messiah SE. Effect of a child care center-based obesity prevention program on body mass index and nutrition practices among preschool-aged children. Health Promotion Practice. 2014;15(5):695–705. pmid:24662896
  36. 36. Natale RA, Messiah SE, Asfour LS, Uhlhorn SB, Englebert NE, Arheart KL. Obesity prevention program in childcare centers: two-year follow-up. American Journal of Health Promotion. 2017;31(6):502–10. pmid:27630110
  37. 37. Sherwood NE, Meghan M, JaKa MS, Crain AL, Martinson BC, Hayes MG, Anderson JD. Pediatric primary care-based obesity prevention for parents of preschool children: a pilot study. Childhood Obesity. 2015;11(6):674–82. pmid:26478951
  38. 38. Slusser W, Frankel F, Robison K, Fischer H, Cumberland WG, Neumann C. Pediatric overweight prevention through a parent training program for 2–4 year old Latino children. Childhood Obesity. 2012;8(1):52–9. pmid:22799481
  39. 39. Sun A, Cheng J, Bui Q, Liang Y, Ng T, Chen J-L. Home-based and technology-centered childhood obesity prevention for Chinese mothers with preschool-aged children. Journal of Transcultural Nursing. 2017;28(6):616–24.
  40. 40. Woo Baidal JA, Nelson CC, Perkins M, Colchamiro R, Leung-Strle P, Kwass JA, et al. Childhood obesity prevention in the women, infants, and children program: Outcomes of the MA-CORD study. Obesity. 2017;25(7):1167–74. pmid:28653498
  41. 41. Kuo T, Jarosz CJ, Simon P, Fielding JE. Menu labeling as a potential strategy for combating the obesity epidemic: a health impact assessment. American Journal of Public Health. 2009;99(9):1680–6. pmid:19608944
  42. 42. Sonneville KR, Long MW, Ward ZJ, Resch SC, Wang YC, Pomeranz JL, et al. BMI and healthcare cost impact of eliminating tax subsidy for advertising unhealthy food to youth. American Journal of Preventive Medicine. 2015;49(1):124–34. pmid:26094233
  43. 43. Dharmasena S, Capps O Jr. Intended and unintended consequences of a proposed national tax on sugar-sweetened beverages to combat the U.S. obesity problem. Health Economics. 2012;21(6):669–94. pmid:21538676
  44. 44. Long MW, Gortmaker SL, Ward ZJ, Resch SC, Moodie ML, Sacks G, et al. Cost effectiveness of a sugar-sweetened beverage excise tax in the U.S. American Journal of Preventive Medicine. 2015;49(1):112–23. pmid:26094232
  45. 45. Wright DR, Kenney EL, Giles CM, Long MW, Ward ZJ, Resch SC, et al. Modeling the cost effectiveness of child care policy changes in the U.S. American Journal of Preventive Medicine. 2015;49(1):135–47. pmid:26094234
  46. 46. Toussaint LL, Housholder K, Janssen K, Mansfield A, Lynch BA. Slowing BMI growth trajectories in elementary school-aged children: The Northeast Iowa Food and Fitness Initiative. Family & Community Health. 2017;40(3):192–7.
  47. 47. Cradock AL, Barrett JL, Kenney EL, Giles CM, Ward ZJ, Long MW, et al. Using cost-effectiveness analysis to prioritize policy and programmatic approaches to physical activity promotion and obesity prevention in childhood. Preventive Medicine. 2017;95 Suppl:S17–s27. pmid:27773710
  48. 48. Ma S, Frick KD. A simulation of affordability and effectiveness of childhood obesity interventions. Academic Pediatrics. 2011;11(4):342–50. pmid:21764018
  49. 49. Wright DR, Taveras EM, Gillman MW, Horan CM, Hohman KH, Gortmaker SL, et al. The cost of a primary care-based childhood obesity prevention intervention. Bmc Health Services Research. 2014;14:44. pmid:24472122
  50. 50. Fitzgibbon ML, Stolley MR, Schiffer LA, Braunschweig CL, Gomez SL, Van Horn L, et al. Hip-Hop to Health Jr. obesity prevention effectiveness trial: postintervention results. Obesity. 2011;19(5):994–1003. pmid:21193852
  51. 51. Taveras EM, Blaine RE, Davison KK, Gortmaker S, Anand S, Falbe J, et al. Design of the Massachusetts Childhood Obesity Research Demonstration (MA-CORD) study. Childhood Obesity. 2015;11(1):11–22. pmid:25469676
  52. 52. Taveras EM, Gortmaker SL, Hohman KH, Horan CM, Kleinman KP, Mitchell K, et al. Randomized controlled trial to improve primary care to prevent and manage childhood obesity: the High Five for Kids study. Archives of Pediatrics & Adolescent Medicine. 2011;165(8):714–22.
  53. 53. Moss B, Yeaton W. Early childhood healthy and obese weight status: potentially protective benefits of breastfeeding and delaying solid foods. Maternal & Child Health Journal. 2014;18(5):1224–32.
  54. 54. Ward DS, Welker E, Choate A, Henderson KE, Lott M, Tovar A, et al. Strength of obesity prevention interventions in early care and education settings: A systematic review. Preventive Medicine. 2017;95 Suppl:S37–s52. pmid:27693295
  55. 55. Braveman P, Barclay C. Health disparities beginning in childhood: a life-course perspective. Pediatrics. 2009;124 Suppl 3:S163–75.
  56. 56. Finkelstein EA, Trogdon JG, Cohen JW, Dietz W. Annual medical spending attributable to obesity: payer-and service-specific estimates. Health Affairs (Project Hope). 2009;28(5):w822–31.
  57. 57. Wolfenden L, Jones J, Williams CM, Finch M, Wyse RJ, Kingsland M, et al. Strategies to improve the implementation of healthy eating, physical activity and obesity prevention policies, practices or programmes within childcare services. The Cochrane Database of Systematic Reviews. 2016;10:Cd011779. pmid:27699761