U.S. flag

A .gov website belongs to an official government organization in the United States.

A lock ( ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

  • Preventing Childhood Obesity
  • Health Care Strategies
  • About Obesity
  • What Can Be Done
  • Obesity Data and Statistics

Related Topics:

  • View All Home
  • About Healthy Weight and Growth
  • Body Mass Index (BMI)
  • About Nutrition
  • About Physical Activity

Childhood Obesity Facts

At a glance.

  • Approximately 1 in 5 U.S. children and adolescents have obesity.
  • Obesity affects some groups more than others, including adolescents, Hispanic and non-Hispanic Black children, and children in families with lower incomes.
  • Health care for obesity is expensive for patients and the health care system.

Doctor measuring young girl's height

Many U.S. children have obesity

From 2017 to March 2020, the prevalence of obesity among U.S. children and adolescents was 19.7% 1 . This means that approximately 14.7 million U.S. youths aged 2–19 years have obesity.

For children, obesity is defined as having a body mass index (BMI) at or above the 95th percentile for age and sex.

Obesity affects some groups more than others

The prevalence of obesity increased with age. From 2017 to March 2020, obesity prevalence was 12.7% among U.S. children 2–5 years old, 20.7% among those 6–11, and 22.2% among adolescents 12–19. [1]

Race and ethnicity

Overall, obesity prevalence was highest in Hispanic children (26.2%) and non-Hispanic Black children (24.8%) followed by non-Hispanic white (16.6%) and non-Hispanic Asian (9.0%) children. [1]

Among U.S. girls, obesity prevalence was highest among non-Hispanic Black girls (30.8%). Among U.S. boys, obesity prevalence was highest among Hispanic boys (29.3%). [1]

Family income

Obesity prevalence increased as family income decreased. Obesity prevalence was:

  • 11.5% among U.S. children with family income more than 350% of the Federal Poverty Level (FPL).
  • 21.2% among children with family income 130% to 350% of FPL.
  • 25.8% among children with family income 130% or less of FPL. [1]

Obesity data among young children‎

Health care for obesity is expensive.

Health care for obesity is expensive for patients and the health care system. In 2019 dollars, the estimated annual medical cost of obesity among U.S. children was $1.3 billion. Medical costs for children with obesity were $116 higher per person per year than for children with healthy weight. Medical costs for children with severe obesity were $310 higher per person per year than for children with healthy weight. [2]

Related information

Adult Obesity Facts

Information about obesity among adults in the U.S.

About Child and Teen BMI

What BMI is, how it is used, and how it is interpreted.

Child and Teen BMI Calculator

Calculate BMI, BMI percentile, and BMI category for children and adolescents 2–19.

Person-first language‎

  • Stierman B, Afful J, Carroll MD, et al. National Health and Nutrition Examination Survey 2017–March 2020 prepandemic data files development of files and prevalence estimates for selected health outcomes . Natl Health Stat Report . 2021;158.
  • Ward ZJ, Bleich S, Long MW, Gortmaker SL. Association of body mass index with health care expenditures in the United States by age and sex. PLoS One . 2021;16(3):e0247307.

CDC's obesity prevention efforts focus on policy and environmental strategies to make healthy eating and active living accessible for everyone.

For Everyone

Health care providers, public health.

U.S. flag

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

  • Publications
  • Account settings
  • My Bibliography
  • Collections
  • Citation manager

Save citation to file

Email citation, add to collections.

  • Create a new collection
  • Add to an existing collection

Add to My Bibliography

Your saved search, create a file for external citation management software, your rss feed.

  • Search in PubMed
  • Search in NLM Catalog
  • Add to Search

Childhood obesity: A review of current and future management options

Affiliations.

  • 1 Department of Paediatric Endocrinology, Alder Hey Children's Hospital, Liverpool, UK.
  • 2 Centre for Endocrinology, William Harvey Research Institute, Barts and the London School of Medicine, Queen Mary University of London, London, UK.
  • 3 Department of Paediatric Dietetics, Alder Hey Children's Hospital, Liverpool, UK.
  • 4 Department of Paediatric Clinical Psychology, Alder Hey Children's Hospital, Liverpool, UK.
  • PMID: 34750858
  • DOI: 10.1111/cen.14625

Obesity is becoming increasingly prevalent in paediatric populations worldwide. In addition to increasing prevalence, the severity of obesity is also continuing to rise. Taken together, these findings demonstrate a worrying trend and highlight one of the most significant challenges to public health. Childhood obesity affects multiple organs in the body and is associated with both significant morbidity and ultimately premature mortality. The prevalence of complications associated with obesity, including dyslipidaemia, hypertension, fatty liver disease and psychosocial complications are becoming increasingly prevalent within the paediatric populations. Treatment guidelines currently focus on intervention with lifestyle and behavioural modifications, with pharmacotherapy and surgery reserved for patients who are refractory to such treatment. Research into adult obesity has established pharmacological novel therapies, which have been approved and established in clinical practice; however, the research and implementation of such therapies in paediatric populations have been lagging behind. Despite the relative lack of widespread research in comparison to the adult population, newer therapies are being trialled, which should allow a greater availability of treatment options for childhood obesity in the future. This review summarizes the current evidence for the management of obesity in terms of medical and surgical options. Both future therapeutic agents and those which cause weight loss but have an alternative indication are also included and discussed as part of the review. The review summarizes the most recent research for each intervention and demonstrates the potential efficacy and limitations of each treatment option.

Keywords: BMI; childhood obesity; lifestyle interventions; paediatrics; pharmacotherapy.

© 2021 John Wiley & Sons Ltd.

PubMed Disclaimer

Similar articles

  • The effectiveness of web-based programs on the reduction of childhood obesity in school-aged children: A systematic review. Antwi F, Fazylova N, Garcon MC, Lopez L, Rubiano R, Slyer JT. Antwi F, et al. JBI Libr Syst Rev. 2012;10(42 Suppl):1-14. doi: 10.11124/jbisrir-2012-248. JBI Libr Syst Rev. 2012. PMID: 27820152
  • Treatment Options for Severe Obesity in the Pediatric Population: Current Limitations and Future Opportunities. Ryder JR, Fox CK, Kelly AS. Ryder JR, et al. Obesity (Silver Spring). 2018 Jun;26(6):951-960. doi: 10.1002/oby.22196. Epub 2018 May 7. Obesity (Silver Spring). 2018. PMID: 29732716 Review.
  • The future of Cochrane Neonatal. Soll RF, Ovelman C, McGuire W. Soll RF, et al. Early Hum Dev. 2020 Nov;150:105191. doi: 10.1016/j.earlhumdev.2020.105191. Epub 2020 Sep 12. Early Hum Dev. 2020. PMID: 33036834
  • Real-World Strategies to Treat Hypertension Associated with Pediatric Obesity. Binka E, Brady TM. Binka E, et al. Curr Hypertens Rep. 2019 Feb 12;21(2):18. doi: 10.1007/s11906-019-0922-2. Curr Hypertens Rep. 2019. PMID: 30747290 Free PMC article. Review.
  • Screening and Interventions for Childhood Overweight [Internet]. Whitlock EP, Williams SB, Gold R, Smith P, Shipman S. Whitlock EP, et al. Rockville (MD): Agency for Healthcare Research and Quality (US); 2005 Jul. Rockville (MD): Agency for Healthcare Research and Quality (US); 2005 Jul. PMID: 20722132 Free Books & Documents. Review.
  • Is oxidative stress - antioxidants imbalance the physiopathogenic core in pediatric obesity? Lupu A, Fotea S, Jechel E, Starcea IM, Ioniuc I, Knieling A, Salaru DL, Sasaran MO, Cirstea O, Revenco N, Mihai CM, Lupu VV, Nedelcu AH. Lupu A, et al. Front Immunol. 2024 Aug 8;15:1394869. doi: 10.3389/fimmu.2024.1394869. eCollection 2024. Front Immunol. 2024. PMID: 39176098 Free PMC article. Review.
  • The Prevention of Childhood Obesity Is a Priority: The Preliminary Results of the "EpPOI: Education to Prevent Childhood Obesity" Project. Porri D, Luppino G, Morabito LA, La Rosa E, Pepe G, Corica D, Valenzise M, Messina MF, Zirilli G, Li Pomi A, Alibrandi A, Di Mauro D, Aversa T, Wasniewska MG. Porri D, et al. Nutrients. 2024 Aug 2;16(15):2538. doi: 10.3390/nu16152538. Nutrients. 2024. PMID: 39125417 Free PMC article.
  • Comparative Efficacy and Safety of Glucagon-like Peptide-1 Receptor Agonists in Children and Adolescents with Obesity or Overweight: A Systematic Review and Network Meta-Analysis. Liu L, Shi H, Shi Y, Wang A, Guo N, Tao H, Nahata MC. Liu L, et al. Pharmaceuticals (Basel). 2024 Jun 24;17(7):828. doi: 10.3390/ph17070828. Pharmaceuticals (Basel). 2024. PMID: 39065679 Free PMC article. Review.
  • Analysis of Prescription Trends for Narcotic Appetite Suppressants: Utilizing the Narcotics Information Management System. Oh KS, Han E. Oh KS, et al. Yonsei Med J. 2024 Aug;65(8):480-487. doi: 10.3349/ymj.2023.0335. Yonsei Med J. 2024. PMID: 39048324 Free PMC article.
  • The Impact of Excessive Fructose Intake on Adipose Tissue and the Development of Childhood Obesity. Azevedo-Martins AK, Santos MP, Abayomi J, Ferreira NJR, Evangelista FS. Azevedo-Martins AK, et al. Nutrients. 2024 Mar 25;16(7):939. doi: 10.3390/nu16070939. Nutrients. 2024. PMID: 38612973 Free PMC article. Review.
  • NHS Digital. National Statistics: National Child Measurement Programme, England. 2017/18. Accessed April, 2021. https://digital.nhs.uk/data-and-information/publications/statistical/nat...
  • Viner RM, Kinra S, Christie D, et al. Improving the assessment and management of obesity in UK children and adolescents: the PROMISE research programme including a RCT. Programme Grants for Applied Research, No. 8.3. 2020.
  • Baker C. Briefing paper: obesity statistics. House of Commons Library. 2019;3336:1-20.
  • Styne DM, Arslanian SA, Connor EL, et al. Pediatric obesity-assessment, treatment, and prevention: an Endocrine Society Clinical Practice Guideline. J Clin Endocrinol Metab. 2017;102(3):709-757.
  • Gungor NK. Overweight and obesity in children and adolescents. J Clin Res Pediatr Endocrinol. 2014;6(3):129-143.

Publication types

  • Search in MeSH

Related information

Linkout - more resources, full text sources.

  • Ovid Technologies, Inc.
  • MedlinePlus Health Information

full text provider logo

  • Citation Manager

NCBI Literature Resources

MeSH PMC Bookshelf Disclaimer

The PubMed wordmark and PubMed logo are registered trademarks of the U.S. Department of Health and Human Services (HHS). Unauthorized use of these marks is strictly prohibited.

Doctor using a stethoscope on a patient

The overall mission of the Duke Center for Childhood Obesity Research (DCCOR) is to advance effective and equitable obesity prevention and treatment by conducting innovative interdisciplinary research to achieve optimal health for all children.

DCCOR conducts groundbreaking research that seeks to change practice and policy to help children lead healthier lives. Three pillars form the foundation for our research:

  • Causes, consequences, and correlates of childhood obesity
  • Prevention of obesity and its related morbidities
  • Treatment of childhood obesity across the lifespan

Across all pillars, we approach research relative to the following intersecting themes, in order to achieve optimal obesity-related health outcomes: 

  • Reducing stigma and bias
  • Improving health equity
  • Establishing policy
  • Training the next generation of researchers

In support of our overarching mission, the center’s goals are to:

  • Embrace  innovative research strategies and support interdisciplinary collaboration  by intentionally seeking out collaborators across different departments.
  • Discover and deliver  effective obesity prevention and treatment to populations of children across the age spectrum from pre-conception through early adulthood  by identifying the physical, mental, social, and economic factors that affect parents and/or children in ways that lead to weight gain.
  • Close disparities in optimal nutrition and activity that exist for children from diverse racial, ethnic, and economic diverse backgrounds  by developing culturally-sensitive intervention materials and focus on reducing barriers and facilitating access to opportunities for healthy eating and activity.
  • Combat stigma and bias  against those affected by obesity by exploring implicit attitudes and their effects on beliefs, behaviors, and health.
  • Educate learners at all levels about obesity --its causes and effects, weight stigma, and healthy lifestyles by developing a curriculum for children and/or parents that can be used in schools or other settings.
  • Train future leaders in the field of child obesity research  by offering training opportunities and mentorship of junior researchers.
  • Engage with schools and local health partners to ensure research efforts are community-based  by involving non-university and non-academic collaborators at various steps of the research process.
  • Encourage the development of policies that will benefit child health and promote healthy lifestyle habits  by collaborating with legislators and key decision-makers and providing them with expertise and advice.
  • Publicize our research and disseminate the findings to a wide audience  through rigorous scientific channels, center-created newsletters and informational resources, and social media platforms.

With the creation of the Duke Center for Childhood Obesity Research (DCCOR) in January 2017 under the leadership of Eliana Perrin, MD, MPH, the Department of Pediatrics and School of Medicine strengthened its commitment to the multidisciplinary research necessary to develop effective and efficient evidence-based behavioral interventions to prevent childhood obesity. Additional Center revenue and project funding is generated by grant awards from sources such as The Duke Endowment and the National Institutes of Health (NIH). The Center is currently co-directed by  Sarah Armstrong, MD , director of the Duke Healthy Lifestyles clinical and research programs and Division Chief of General Pediatrics and Adolescent Health in the Department of Pediatrics, and  Asheley Skinner, PhD , Professor of Population Health Sciences and Director of Graduate Studies for Population Health Sciences. The Center is conducting impactful, multidisciplinary research on the causes, consequences, correlates, prevention and treatment of childhood obesity.

Research Environment

DCCOR, which is an integral part of the Department of Pediatrics in the Duke University School of Medicine, is strategically positioned to conduct innovative and groundbreaking research in pediatric obesity. Duke University has a strong reputation as one of the top research institutions in the country. In 2021, the Duke School of Medicine received more than $608 million in NIH funding, ranking third in the nation. Ranking first nationally in NIH research grant funding for pediatrics clinical science departments, Duke’s Department of Pediatrics received nearly $210 million in NIH grants in 2021.

Duke University is highly supportive of research collaboration among faculty members across disciplines, departments, and schools. With the introduction of the 2006 strategic plan “Making a Difference,” Duke began to build university-wide interdisciplinary institutes, initiatives, and centers with the intention of taking novel approaches to problem-focused research. These interdisciplinary entities are supported with core funding from the Office of the Provost, sharing infrastructures that facilitate the work being accomplished by the faculty and students within them. Further evidence of Duke’s support of facilitating interdisciplinary partnerships is the School of Medicine’s interdisciplinary colloquia awards, which aim to connect faculty members from a variety departments to share knowledge and collaborate on common interests.

Duke’s expansive research infrastructure and history of supporting interdisciplinary collaborations will provide DCCOR with a strong foundation to successfully engage in innovative research, make critical advancements and discoveries, and become a leader in the field of pediatric obesity research and prevention.

Login to your account

If you don't remember your password, you can reset it by entering your email address and clicking the Reset Password button. You will then receive an email that contains a secure link for resetting your password

If the address matches a valid account an email will be sent to __email__ with instructions for resetting your password

Property Value
Status
Version
Ad File
Disable Ads Flag
Environment
Moat Init
Moat Ready
Contextual Ready
Contextual URL
Contextual Initial Segments
Contextual Used Segments
AdUnit
SubAdUnit
Custom Targeting
Ad Events
Invalid Ad Sizes
  • Submit Article

Access provided by

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

Download started

  • Download PDF Download PDF

Interpretation

  • Childhood obesity
  • Public health
  • Systematic review

Evidence before this study

Added value of this study, implications of all the available evidence, introduction, study inclusion criteria, search methods, study selection, data collection, assessment of risk of bias and quality of evidence, data analysis and synthesis, role of the funding source.

Figure 1

Author year CountryStudy characteristics Design (cluster type) Setting Age group years (mean age) GenderNumber of participantsIntervention Treatment armsTargeted behaviourTheory DurationComparatorOutcomes Weight outcomes (length of follow up from baseline category) Adverse effects Cost/cost-effectiveness
RandomisedAnalysed
Adab 2018
UK
Design: C-RCT (School)
Setting: School * + Home + Community
Age group: 6-12 (6·3)
Gender: mixed
2462837Arms: 1
Target: DPA
Theory: NR
Duration: ≤ 12 months
Control: usual practiceBMI-z (>12 months)†
Adverse assessed: Yes
Adverse effect: Quality of life (no evidence of harm).
Cost: Total adjusted incremental mean cost per child at 30 months (£155 (95% confidence interval [CI]: £139, £171)), incremental mean QALYs gained per child (0·006 (95% CI: -0·024, 0·036)). Incremental cost-effectiveness at 30 months per QALY (£26,815). Using a standard willingness to pay threshold of £30,000 per QALY, there was a 52% chance that the intervention was cost-effective.
Amaro 2006
Italy
Design: C-RCT (Classroom)
Setting: School
Age group: 6-12 (12·4)
Gender: mixed
291241Arms: 1
Target: Diet
Theory: NR
Duration: ≤ 12 months
Control: no interventionBMI-z (≤ 12 months)†
Adverse: NR
Cost: NR
Andrade 2014
Ecuador
Design: C-RCT (School)
Setting: School
Age group: 13-18 (intv = 12·8, control = 12·9)
Gender: mixed
14401060Arms: 1
Target: DPA
Theory: SCT, IMB model, Control theory, TTM and TPB
Duration: > 12 months
Control: usual careBMI-z (> 12 months)†
Adverse: NR
Cost: NR
Arlinghaus
2021
US
Design: RCT
Setting: School
Age group: 6-12 (weekday 12·10, weekend 12·06)
Gender: mixed
491329Arms: 1
Target: PA
Theory: SCT
Duration: ≤ 12 months
Control: usual careBMI-z (≤ 12 months)
Adverse: NR
Cost: NR
Baranowski 2003
USA
Design: RCT
Setting: Community* + Home
Age group: 6-12 (intv = 8·3, control = 8·4)
Gender: Girls only
3531Arms: 1
Target: DPA
Theory: SCT and FST
Duration: ≤ 12 months
Control: usual day campBMI (≤ 12 months)†
Adverse: NR
Cost: NR
Baranowski 2011
USA
Design: RCT
Setting: Home
Age group: 6-12 (42·5% = 10; 32·7% = 11; 24·8% = 12)
Gender: mixed
153134Arms: 1
Target: DPA
Theory: SCT, Self-determination and Persuasion theories
Duration: ≤ 12 months
Control: health-related video gamesBMI-z (≤ 12 months)†
Adverse: NR
Cost: NR
Barbeau 2007
USA
Design: RCT
Setting: School (ASP)
Age group: 6-12 (9·5)
Gender: Girls only
309201Arms: 1
Target: PA
Theory: NR
Duration: ≤ 12 months
Control: no interventionBMI (≤ 12 months)†
Adverse: NR
Cost: NR
Barnes 2015
Australia
Design: RCT
Setting: Community* + Home
Age group: 6-12 (8·49)
Gender: Girls only
4848Arms: 1
Target: PA
Theory: SCT
Duration: ≤ 12 months
Control: WaitlistBMI-z(≤ 12 months)†
Adverse: NR
Cost: NR
Beech 2003
USA
Design: RCT
Setting: Community
Age group: 6-12 (8·9)
Gender: Girls only
6060Arms: 2
Target: DPA
Theory: SCT and FST
Duration: ≤ 12 months
Control: Attention control (focus on self-esteem)BMI (≤ 12 months)†
Adverse assessed: Yes
Adverse effect: Visit to healthcare provider, unhealthy weight concern and injuries (similar between children in intervention and control)
Cost: NR
Black 2010
USA
Design: RCT
Setting: Home* + Community
Age group: 13-18 (13·3)
Gender: mixed
235184Arms: 1
Target: DPA
Theory: SCT and MI
Duration: ≤ 12 months
Control: No interventionBMI-z (≤ 12 months)†
Adverse: NR
Cost: NR
Bogart 2016
USA
Design: C-RCT (School)
Setting: School + Home
Age group: 6-12 (12·2)
Gender: mixed
32721368Arms: 1
Target: Diet
Theory: SCT, ecological influences and community-based participatory research
Duration: ≤ 12 months
Control: WaitlistBMI percentiles (>12 months)
Adverse: NR
Cost: NR
Bohnert 2013
USA
Design: RCT
Setting: School (ASP)
Age group: 6-12 (intv = 9·02, control = 9·38)
Gender: Girls only
13376Arms: 1
Target: DPA
Theory: SCT and Sociocultural theory
Duration: ≤ 12 months
Control: No interventionBMI-z (≤ 12 months)†
Adverse: NR
Cost: NR
Bonsergent 2013
France
Design: C-RCT (School)
Setting: School* + Health Service + Community
Age group: 13-18 (15·8)
Gender: mixed
53543538Arms: 3
Target: DPA
Theory: NR
Duration: > 12 months
Control: No interventionBMI and BMIz (> 12 months)†
Adverse: NR
Cost: NR
Brandstetter 2012
Germany
Design: C-RCT (Classroom)
Setting: School* + Health Service + Home
Age group: 6-12 (intv = 7·61, control = 7·53)
Gender: mixed
1119945Arms: 1
Target: DPA
Theory: SCT
Duration: ≤ 12 months
Control: Usual careBMI (≤ and > 12 months)†
Adverse: NR
Cost: NR
Branscum 2013
USA
Design: C-RCT (School)
Setting: School (ASP)
Age group: 6-12 (NR)
Gender: mixed
7171Arms: 1
Target: DPA
Theory: SCT
Duration: ≤ 12 months
CE: Knowledge based programBMI percentiles only (≤ 12 months)
Adverse: NR
Cost: NR
Breheny 2020
UK
Design: C-RCT (School)
Setting: School
Age group: 6-12 (8·9)
Gender: mixed
22801670Arms: 1
Target: PA
Theory: BCT
Duration: ≤ 12 months
Control: No active interventionBMI-z (≤ 12 months)†
Adverse assessed: Yes
Adverse effect: No adverse events were reported
Cost: Chance of cost-effectiveness using standard UK thresholds (76%). Highly cost-effective in girls (£2,492 per QALY), but not in boys.
Brito Beck da Silva 2019
Brazil
Design: C-RCT (School)
Setting: School* + Home
Age group: 13-18 (14·5)
Gender: mixed
895602Arms: 1
Target: DPA
Theory: CBT
Duration: ≤ 12 months
Control: WaitlistBMI (≤ 12 months)†
Adverse: NR
Cost: NR
Brown 2013
UK
Design: RCT
Setting: Community* + School (ASP)
Age group: 6-12 (11·4)
Gender: mixed
7663Arms: 1
Target: DPA
Theory: TTM-Stages of Change and SCT
Duration: ≤ 12 months
Control: Attention control (alcohol and drug comparison)BMI and BMIz (≤ 12 months)†
Adverse: NR
Cost: NR
Caballero 2003
USA
Design: C-RCT (School)
Setting: School* + Home
Age group: 6-12 (7·6)
Gender: mixed
17141409Arms: 1
Target: DPA
Theory: SLT, and principles of American Indian culture and
practice
Duration: > 12 months
Control: Usual care presumed (no details provided but school-based
Intervention)
BMI (> 12 months)†
Adverse: NR
Cost: NR
Cao 2015
China
Design: C-RCT (School)
Setting: School* + Home
Age group: 6-12 (intv = 7·01, control = 6·81)
Gender: mixed
24451813Arms: 1
Target: DPA
Theory: NR
Duration: > 12 months
Control: No interventionBMI-z (> 12 months)†
Adverse: NR
Cost: NR
Carlin 2018
Northern Ireland
Design: C-RCT (School)
Setting: School
Age group: 6-12 (12·4)
Gender: Girls only
199197Arms: 1
Target: PA
Theory: SCT
Duration: ≤ 12 months
Control: Usual PA, waitlist controlBMI (≤ 12 months)
Adverse: NR
Cost: NR
Chai 2019
Australia
Design: RCT
Setting: Home
Age group: 6-12 (9.0)
Gender: mixed
4646Arms: 2
Target: Diet
Theory: CALO-RE taxonomy of behaviour change techniques, BCT
Duration: ≤ 12 months
Control: WaitlistBMI-z (≤ 12 months)†
Adverse: NR
Cost: NR
Chen 2010
USA
Design: RCT
Setting: Community
Age group: 6-12 (8·97)
Gender: mixed
6767Arms: 1
Target: DPA
Theory: behaviour-change techniques related to healthy eating
Duration: ≤ 12 months
Control: WaitlistBMI (≤ 12 months)†
Adverse: NR
Cost: NR
Chen 2011
USA
Design: RCT
Setting: Home
Age group: 13-18 (12·52)
Gender: mixed
5450Arms: 1
Target: DPA
Theory: TTM-Stages of Change and SCT
Duration: ≤ 12 months
Control: Attention control. General health information related to nutrition,
dental care, safety, skin care, and risk-taking behaviours
BMI (≤ 12 months)†
Adverse: NR
Cost: NR
Choo 2020
South Korea
Design: C-RCT (Community centre)
Setting: Community* + Home
Age group: 6-12 (10·0)
Gender: mixed
107104Arms: 1
Target: DPA
Theory: Ecological perspective, cognitive learning theory
Duration: ≤ 12 months
Control: Usual careBMI-z (≤ 12 months)†
Adverse: NR
Cost: NR
Christiansen 2013
Denmark
Design: C-RCT (School)
Setting: School + Community
Age group: 13-18 (12·6)
Gender: mixed
1348989Arms: 1
Target: PA
Theory: Social Ecological
Duration: > 12 months
Control: Usual careWaist circumference (> 12 months)
Adverse: NR
Cost: Upgrades to school outdoor areas (10 000–20 000 €) and established Playspots (65 000–250 000 €).
Clemes 2020
UK
Design: C-RCT (School)
Setting: School
Age group: 6-12 years (9·3)
Gender: mixed
176168Arms: 1
Target: PA
Theory: COM-B with BCW, TDF
Duration: ≤ 12 months
Control: Usual practiceBMI (≤ 12 months)†
Adverse assessed: Yes
Adverse effect: No serious adverse events were reported.
Cost: NR
Coleman 2005
USA
Design: C-RCT (School)
Setting: School
Age group: 6-12 years (8·3)
Gender: mixed
896744Arms: 1
Target: DPA
Theory: NR
Duration: >12 months
Control: No intervention (financial incentive to participate)BMI (>12 months)
Adverse: NR
Cost: Cost-effectiveness ratio (US$900(US$903 using Hispanic parameters)), net benefit (US$68,125 (US$43,239 using Hispanic parameters))
Coleman 2012
USA
Design: C-RCT (School)
Setting: School (during hours* and ASP)
Age group: 6-12 (8·9)
Gender: mixed
579424Arms: 1
Target: Diet
Theory: Ecological and Developmental Systems Theories and BEM
Duration: >12 months
Control: Usual care presumed as no details but school-based
intervention
BMI z score (>12 months)
Adverse: NR
Cost: NR
Cunha 2013
Brazil
Design: C-RCT (Classroom)
Setting: School* + Home
Age group: 6-12 (intv = 11·2, control = 11·2)
Gender: mixed
574559Arms: 1
Target: Diet
Theory: TTM
Duration: ≤ 12 months
Control: No interventionBMI (≤ 12 months)
Adverse: NR
Cost: NR
Damsgaard 2014
Denmark
Design: C-RCT - crossover (School)
Setting: School
Age group: 6-12 (10·0)
Gender: mixed
823823Arms: 1
Target: Diet
Theory: NR
Duration: ≤ 12 months
Control: Usual care (packed lunch from home)BMI-z (≤ 12 months)†
Adverse: NR
Cost: NR
Davis 2021
US
Design: C-RCT (School)
Setting: School
Age group: 6-12 (9·23)
Gender: mixed
31353135Arms: 1
Target: Diet
Theory: Social ecological-transactional model
Duration: ≤ 12 months
Control: Delayed inteventionBMI-z (≤ 12 months)†
Adverse: NR
Cost: NR
de Greeff 2016
Netherlands
Design: C-RCT (Classroom)
Setting: School
Age group: 6-12 (8·1)
Gender: mixed
376376Arms: 1
Target: PA
Theory: NR
Duration: ≤ 12 months
Control: Assume usual practiceBMI (≤ 12 months)†
Adverse: NR
Cost: NR
De Heer 2011
USA
Design: C-RCT (Classroom)
Setting: School (ASP)
Age group: 6-12 (intv = 9·24, control = 9·10)
Gender: mixed
646568Arms: 1
Target: DPA
Theory: Ecological principles, SCT
Duration: ≤ 12 months
Control: Attention control. Health workbooks and incentivesBMI (≤ 12 months)†
Adverse: NR
Cost: NR
de Ruyter 2012
Netherlands
Design: RCT
Setting: School* + Home
Age group: 6-12 (intv = 8·2, control = 8·2)
Gender: mixed
641641Arms: 1
Target: Diet
Theory: NR
Duration: > 12 months
Control: Similar sugar-containing drink in participants
who commonly drank them
BMI-z (> 12 months)†
Adverse assessed: Yes
Adverse effect: Adverse events were minor. Six participants discontinued the study due to weight gain (four in the sugar group and two in the sugar-free group).
Cost: NR
Dewar 2013
Australia
Design: C-RCT (School)
Setting: School* + Home
Age group: 13-18 (intv = 13·20, control = 13·15)
Gender: Girls only
357294Arms: 1
Target: DPA
Theory: SCT
Duration: ≤ 12 months
Control: Usual care presumed as no details but schoolbased interventionBMI and BMIz (≤ 12 months)†
Adverse: NR
Cost: Yes. Standard equipment pack (USD 1300).
Donnelly 2009
USA
Design: C-RCT (School)
Setting: School
Age group: 6-12 (Grade 2: intv female = 7·7, control female = 7·8; intv male = 7·7, control male = 7·8. Grade 3: intv female = 8·7, control female = 8·7; intv male = 8·7, control male = 8·8)
Gender: mixed
15271490Arms: 1
Target: PA
Theory: NR
Duration: > 12 months
Control: Usual care - regular classroom instruction without
physically active lessons
BMI (> 12 months)†
Adverse: NR
Cost: NR
Drummy 2016
Northern Ireland
Design: C-RCT (Classroom)
Setting: School
Age group: 6-12 (9·5)
Gender: mixed
120107Arms: 1
Target: PA
Theory: NR
Duration: ≤ 12 months
Control: Usual practiceBMI (≤ 12 months)†
Adverse: NR
Cost: NR
Duncan 2019
New Zealand
Design: C-RCT (School)
Setting: School* + Home
Age group: 6-12 (intv = 8·71, control = 8·74)
Gender: mixed
675589Arms: 1
Target: DPA
Theory: SCT, theory of reasoned action and planned behaviour
Duration: ≤ 12 months
Control: WaitlistBMI (≤ 12 months)†
Adverse: NR
Cost: NR
Dunker 2018
Brazil
Design: C-RCT (School)
Setting: School (ASP)* + Home
Age group: 13-18 (13·39)
Gender: Girls only
270270Arms: 1
Target: DPA
Theory: SCT
Duration: ≤ 12 months
Control: Usual practiceBMI (≤ 12 months)†
Adverse assessed: Yes
Adverse effect: No observed harm or unintended effects that could be directly attributed tothe intervention.
Cost: NR
Ebbeling 2006
USA
Design: RCT
Setting: Home
Age group: 13-18 (intv = 16·0, control = 15·8)
Gender: mixed
103103Arms: 1
Target: Diet
Theory: NR
Duration: ≤ 12 months
Control: Usual drink consumptionBMI (≤ 12 months)†
Adverse: NR
Cost: NR
El Ansarai 2010
Egypt
Design: RCT
Setting: School (ASP)
Age group: 13-18 (15·7)
Gender: mixed
160160Arms: 1
Target: PA
Theory: NR
Duration: ≤ 12 months
Control: Usual care ‘normal’ exercise schedule provided by
the school
BMI (≤ 12 months)†
Adverse: NR
Cost: NR
Elder 2014
USA
Design: C-RCT (Recreation centre)
Setting: Community* + Home
Age group: 6-12 (6·6)
Gender: mixed
541489Arms: 1
Target: DPA
Theory: NR
Duration: > 12 months
Control: No intervention - measurement onlyBMI-z (> 12 months)†
Adverse: NR
Cost: NR
Epstein 2001
USA
Design: RCT
Setting: Home* + Community
Age group: 6-12 (low fat/sugar = 8·8, fruit/vegetables = 8.6)
Gender: mixed
2626Target: Diet
Theory: NR
Duration: ≤ 12 months
CE: D (fat and sugar)Percentage overweight and BMI (≤ 12 months)
Adverse: NR
Cost: NR
Ezendam 2012
Netherlands
Design: C-RCT (School)
Setting: School
Age group: 13-18 (intv = 12·7, control = 12·6)
Gender: mixed
883676Arms: 1
Target: DPA
Theory: TPB, Precaution Adoption Process Model, Implementation intentions
Duration: ≤ 12 months
Control: No interventionBMI (>12 months)†
Adverse: NR
Cost: NR
Fairclough 2013
UK
Design: C-RCT (School)
Setting: School
Age group: 6-12 (intv = 10·6, control = 10·7)
Gender: mixed
318230Arms: 1
Target: DPA
Theory: SCT
Duration: ≤ 12 months
Control: Did not teach a specific unit focused on healthy
eating and PA
BMI and BMIz (≤ 12 months)†
Adverse: NR
Cost: NR
Farias 2015
Brazil
Design: C-RCT (Classroom)
Setting: School
Age group: 13-18 (intv = 15·9, control = 16·0)
Gender: mixed
567386Arms: 1
Target: PA
Theory: NR
Duration: < 12 months (one school year, no further details)
Control: Usual care physical activity at school% body fat, fat mass, waist circumference and % overweight (< 12 months)
Adverse: NR
Cost: NR
Farmer 2017
New Zealand
Design: C-RCT (School)
Setting: School
Age group: 6-12 (intv = 8.0, control = 7·9)
Gender: mixed
902715Arms: 1
Target: PA
Theory: NR
Duration: ≤ 12 months
Control: Usual practiceBMI-z (> 12 months)†
Adverse: NR
Cost: Initial start-up funds (NZD$15 000). Reported majority of recommendations involved no to little cost
Ford 2013
UK
Design: RCT
Setting: School
Age group: 6-12 (NR)
Gender: mixed
174152Arms: 1
Target: PA
Theory: NR
Duration: ≤ 12 months
Control: Nornal lessonsBMI (≤ 12 months)†
Adverse: NR
Cost: NR
Foster 2008
USA
Design: C-RCT (School)
Setting: School
Age group: 6-12 (intv = 11·13, control = 11·2)
Gender: mixed
1349843Arms: 1
Target: DPA
Theory: settings-based approach; CDC Guidelines to Promote Lifelong
Healthy Eating and PA
Duration: > 12 months
Control: No interventionBMI and BMIz (> 12 months)†
Adverse assessed: Yes
Adverse effect: Proportion of underweight children and body satisfaction (no evidence of adverse impact).
Cost: NR
French 2011
USA
Design: C-RCT (Home)
Setting: Home* + Community
Age group: 13-18 (NR)
Gender: mixed
7575Arms: 1
Target: DPA
Theory: NR
Duration: ≤ 12 months
Control: No interventionBMI-z (≤ 12 months)†
Adverse: NR
Cost: NR
Fulkerson 2010
USA
Design: RCT
Setting: Community* + Home
Age group: 6-12 (NR)
Gender: mixed
4444Arms: 1
Target: Diet
Theory: SCT
Duration: ≤ 12 months
Control: No interventionBMI-z (≤ 12 months)
Adverse: NR
Cost: NR
Fulkerson 2015
USA
Design: RCT
Setting: Community* + Home
Age group: 6-12 (10·3)
Gender: mixed
160149Arms: 1
Target: Diet
Theory: Social Cognitive Theory and a socio-ecological framework, BCT
Duration: ≤ 12 months
Control: Attention only - received a monthly family -focused newsletter and and did not receive the HOME Plus intervention programBMI-z (≤ 12 months)†
Adverse assessed: Yes
Adverse effect: No serious adverse events were reported.
Cost: Program costs per famiy (personnel training = $20, program materials = $49, intervention delivery = $44 per session. Childcare costs $20 per session for up to 6 children, transportation $12·50 per session)
Gentile 2009
USA
Design: C-RCT (School)
Setting: School* + Community + Home
Age group: 6-12 (intv = 9·6, control = 9·6)
Gender: mixed
13231201Arms: 1
Target: DPA
Theory: SEM
Duration: ≤ 12 months
Control: Community component onlyBMI (≤ 12 months)†
Adverse: NR
Cost: Yes. Print based manuals and resources (approximately $60 per student)
Gortmaker 1999a
USA
Design: C-RCT (School)
Setting: School + Home
Age group: 6-12 (11·7)
Gender: Girls only
15601295Arms: 1
Target: DPA
Theory: Behavioural Choice and SCT
Duration: > 12 months
Control: Usual care, health curricula and PE classesPrevalence of obesity (> 12 months)
Adverse assessed: Yes
Adverse effect: Extreme dieting behaviour (students reported similarly low levels)
Cost: Intervention cost ($33,677), intervention cost per student per year ($14), cost per QALY saved ($4305), estimated net saving to society ($7313)
Greve 2015
Denmark
Design: C-RCT (School)
Setting: School* + Home
Age group: 6-12 (intv = 10·07, control = 10·22)
Gender: mixed
Unclear9438Arms: 1
Target: DPA
Theory: NR
Duration: > 12 months
Control: Usual practiceBMI (> 12 months)†
Adverse: NR
Cost: Schools received subsidies based on completion of intervention tasks (DKK80 per student in 2008/09, 2009/10 and DKK40 per student in 2010/2011.
Griffin 2019
UK
Design: RCT
Setting: Community
Age group: 6-12 (7·7)
Gender: mixed
4322Arms: 1
Target: DPA
Theory: Family systems theory and SCT
Duration: ≤ 12 months
Control: Attention control - voucher for a single family visit to a leisure centreBMI-z (≤ 12 months)
Adverse assessed: Yes
Adverse effect: No adverse events requiring hospitalisastion or medical attention during the intervention.
Cost: Per-family program delivery cost (ranged from £150 for 15 families to £235 for 8 families excluding training)
Grydeland 2014
Norway
Design: C-RCT (School)
Setting: School* + Home
Age group: 6-12 (intv = 11·2, control = 11·2)
Gender: mixed
21651361Arms: 1
Target: DPA
Theory: SEM
Duration: > 12 months
Control: Usual care presumed as no details but school-based
intervention
BMI and BMIz (> 12 months)†
Adverse: NR
Cost: NR
Gustafson 2019
USA
Design: C-RCT (School)
Setting: Home
Age group: 13-18 (15·0)
Gender: mixed
530411Arms: 1
Target: Diet
Theory: NR
Duration: ≤ 12 months
Control: WaitlistBMI-z percentile (unclear)
Adverse: NR
Cost: Incentives for text message communications ($5 per student per week).
Gutin 2008
USA
Design: C-RCT (School)
Setting: School (ASP)
Age group: 6-12 (8·5)
Gender: mixed
601447Arms: 1
Target: PA
Theory: Environmental change
Duration: > 12 months
Control: No intervention presumed as no details (afterschool
intervention)
BMI (> 12 months)
Adverse: NR
Cost: Intervention cost ($174,070, $558 per student). Intervention cost per student who attended > or = 40% of the intervention sessions ($956), usual after-school care costs ($639/student).
Students who attended > or = 40% of the intervention reduced % BF by 0·76% (95%CI: -1·42 to -0·09) at an additional cost of $317/student.
Habib-Mourad 2014
Lebanon
Design: C-RCT (School)
Setting: School* + Home
Age group: 6-12 (intv = 10·39, control = 10·1)
Gender: mixed
374363Arms: 1
Target: DPA
Theory: SCT
Duration: ≤ 12 months
Control: Usual curriculumBMI (≤ 12 months)†
Adverse: NR
Cost: NR
Habib-Mourad 2020
Lebanon
Design: C-RCT (School)
Setting: School* + Home
Age group: 6-12 (9·95)
Gender: mixed
1239974Arms: 1
Target: DPA
Theory: SCT
Duration: > 12 months
Control: WaitlistBMI (> 12 months)
Adverse: NR
Cost: NR
Haerens 2006
Belgium
Design: C-RCT (School)
Setting: School* + Home
Age group: 13-18 (13·1)
Gender: mixed
28402291Arms: 1
Target: DPA
Theory: an ecological framework
Duration: > 12 months
Control: Usual care presumed as no details but school-based
intervention
BMI-Z (> 12 months)†
Adverse: NR
Cost: NR
Haire-Joshu 2010
USA
Design: C-RCT (Community settings)
Setting: Community* + Home
Age group: 6-12 (intv = 8·3, control = 8·7)
Gender: mixed
782451Arms: 1
Target: DPA
Theory: SCT, ecological model
Duration: ≤ 12 months
Control: Usual careBMI-z (≤ 12 months)
Adverse: NR
Cost: NR
Haire-Joshu 2015
USA
Design: C-RCT (Communities)
Setting: Home* + School
Age group: 13-18 (17·8)
Gender: Girls only
1325814Arms: 1
Target: DPA
Theory: SCT and an ecological framework
Duration: ≤ 12 months
Control: Usual careBMI success - as maintaining or reducing BMI (≤ 12 months)
Adverse: NR
Cost: NR
Han 2006
China
Design: C-RCT (School)
Setting: School
Age group: 6-12 (NR)
Gender: mixed
28002670Arms: 1
Target: Diet
Theory: NR
Duration: >12 months
Control: Usual care presumed as no details but school-basedUnclear (>12 months)
Adverse: NR
Cost: NR
Hannon 2018
USA
Design: RCT
Setting: Community* + Home
Age group: 6-12 (mothers only group = 11·3, mothers and children group = 11.8)
Gender: mixed
128100Arms: 1
Target: DPA
Theory: NR
Duration: ≤ 12 months
CE: Mothers onlyBMI percentiles (≤ 12 months)
Adverse: NR
Cost: NR
Harrington 2018
UK
Design: C-RCT (School)
Setting: School
Age group: 13-18 (12·8)
Gender: Girls only
17531361Arms: 1
Target: PA
Theory: SCT
Duration: ≤ 12 months
Control: Usual practiceBMI-z (≥ 12 months)†
Adverse assessed: Yes
Adverse effect: No serious adverse events reported.
Cost: Intervention cost per school (£1054 to £3498 per year).
HEALTHY Study Gp 2010
USA
Design: C-RCT (School)
Setting: School
Age group: 6-12 (intv = 11·3, control = 11·3)
Gender: mixed
64134603Arms: 1
Target: DPA
Theory: NR
Duration: > 12 months
Control: No intervention - assessment onlyBMI-z (> 12 months)†
Adverse assessed: Yes
Adverse effect: Adverse events associated with health screening (<3%, reports proportion nearly equivalent in intervention and control schools). Extreme dieting (similar low levels in control and intervention groups).
“One 8th-grade girl in a control school committed suicide. The site investigators, the investigators from the National Institute of Diabetes and Digestive and Kidney Diseases, and the data and safety monitoring board determined that the event was unrelated to the study.”
Cost: NR
Hendy 2011
USA
Design: RCT
Setting: School
Age group: 6-12 (NR)
Gender: mixed
382312Arms: 1
Target: DPA
Theory: SCT, Self-determination theory, Group Socialization theory
Duration: ≤ 12 months
Control: Token rewards for three “Good Citizenship Behaviors.”BMI percentiles (≤ 12 months)
Adverse: NR
Cost: Estimated dollar costs per child for small prizes (2 USD per month). Additional cost for pedometers per child (5 USD per month)
Herscovici 2013
Argentina
Design: C-RCT (School)
Setting: School
Age group: 6-12 (intv = 9·64, control = 9·76)
Gender: mixed
405369Arms: 1
Target: DPA
Theory: NR
Duration: ≤ 12 months
Control: Usual care presumed as no details but school-based
intervention
BMI and BMIz (≤ 12 months)†
Adverse: NR
Cost: NR
Hollis 2016
Australia
Design: C-RCT (School)
Setting: School* + Community + Home
Age group: 6-12 (12·0)
Gender: mixed
1233985Arms: 1
Target: PA
Theory: SCT and socio-ecological theory
Duration: > 12 months
Control: Usual practiceBMI-z (> 12 months)†
Adverse assessed: Yes
Adverse effect: Underweight students (no evidence of adverse effects. Proportion of underweight students decreased).

Cost: Intervention cost (AUD $329,952 over 24 months, or AUD$394 per student). Cost effectiveness ratio (AUD$56 ($35–$147) per additional minute of MVPA, AUD$1 ($0·6–$2·7) per MET hour gained per person per day, AUD$1408 ($788–$6,570) per BMI unit avoided, AUD$563 ($282–$3,942) per 10 % reduction in BMI z-score)
Hovell 2018
USA and Mexico
Design: C-RCT (Orthodontist practices)
Setting: Health care service
Age group: 6-12 (12·1)
Gender: mixed
693468Arms: 1
Target: DPA
Theory: BEM and Geoffrey Rose model
Duration: > 12 months
Control: Attention control - tobacco and second hand smoke avoidanceBMI z-score (> 12 months)
Adverse: NR
Cost: Overall intervention cost was not reported. Offices received payment per a prescription health message per patient ($1·50)
Howe 2011
USA
Design: RCT
Setting: School (ASP)
Age group: 6-12 (9·75)
Gender: Boys only
106106Arms: 1
Target: PA
Theory: NR
Duration: ≤ 12 months
Control: No intervention and were not allowed to stay for
the after-school intervention but rather instructed
not to change their daily after-school routine
BMI (≤ 12 months)†
Adverse: NR
Cost: NR
Hull 2018
USA
Design: C-RCT (Family)
Setting: Community* + Home
Age group: 6-12 (6.2)
Gender: mixed
319206Arms: 1
Target: DPA
Theory: SCT, behavioural choice theory and food preference theory
Duration: ≤ 12 months
Control: Attention control - oral health interventionBMI-z (≥12 months)
Adverse: NR
Cost: NR
Ickovics 2019
USA
Design: C-RCT (School)
Setting: School* + Community + Home
Age group: 6-12 (10·9)
Gender: mixed
756595Arms: 3
Target: Diet, PA, DPA
Theory: NR
Duration: > 12 months
Control: Attention control - delayed intervention schools health-focused messages not related with obesity prevention were implementedBMI-z score and BMI percentile (> 12 months)
Adverse assessed: Yes
Adverse effect: There were no adverse effects reported.
Cost: Intervention cost was not reported. Schools received $500/year to support a member of the school community to lead a School Wellness Team.
James 2004
UK
Design: C-RCT (Classroom)
Setting: School
Age group: 6-12 (8·7)
Gender: mixed
644574Arms: 1
Target: Diet
Theory: NR
Duration: ≤ 12 months
Control: Usual care presumed as no details but school-based
intervention
BMI and BMIz (> 12 months)†
Adverse: NR
Cost: NR
Jansen 2011
Netherlands
Design: C-RCT (School)
Setting: School
Age group: 6-12 (Grade 3-5: intv = 7·7, control = 7·8; Grade 6-8: intv = 10·8, control = 10·8)
Gender: mixed
27702622Arms: 1
Target: DPA
Theory: TPB, Ecological Model
Duration: ≤ 12 months
Control: Usual care curriculumBMI (≤ 12 months)†
Adverse: NR
Cost: NR
Johnston 2013
USA
Design: C-RCT (School)
Setting: School* + Community + Home
Age group: 6-12 (intv = 7·8, control = 7·7)
Gender: mixed
835629Arms: 1
Target: DPA
Theory: NR
Duration: > 12 months
Control: Self-helpBMI-z (> 12 months)†
Adverse: NR
Cost: NR
Jones 2015
Australia
Design: RCT
Setting: School (ASP)* + Home
Age group: 6-12 (girls = 9·6, boys = 9·9)
Gender: mixed
3737Arms: 2
Target: PA
Theory: SCT
Duration: ≤ 12 months
CE: Healthy lifestyle (HL) education programs (active comparison group)BMI-z (≤ 12 months)†
Adverse assessed: Yes
Adverse effect: There were no adverse events reported.
Cost: NR
Kain 2014
Chile
Design: C-RCT (School)
Setting: School
Age group: 6-12 (6·6)
Gender: mixed
19491468Arms: 1
Target: DPA
Theory: NR
Duration: ≤ 12 months
Control: Usual care presumed as no details but school-based
intervention
BMI-z (≤ 12 months)†
Adverse: NR
Cost: NR
Kennedy 2018
Australia
Design: C-RCT (School)
Setting: School* + Home
Age group: 13-18 (14·1)
Gender: mixed
607600Arms: 1
Target: PA
Theory: SCT and social-determination theory
Duration: ≤ 12 months
Control: WaitlistBMI-z (≤ 12 months)†
Adverse assessed: Yes
Adverse effect: There were no injuries or adverse events reported.
Cost: NR
Khan 2014
USA
Design: RCT
Setting: Community
Age group: 6-12 (intv = 8·8, control = 8·8)
Gender: mixed
220220Arms: 1
Target: PA
Theory: NR
Duration: ≤ 12 months
Control: Maintain regular after-school routine, financial incentive
for measurements
BMI and BMIz (≤ 12 months)†
Adverse: NR
Cost: NR
Kipping 2008
UK
Design: C-RCT (School)
Setting: School
Age group: 6-12 (9·4)
Gender: mixed
531472Arms: 1
Target: DPA
Theory: SCT and Behavioural Choice theory
Duration: ≤ 12 months
Control: WaitlistBMI (≤ 12 months)†
Adverse: NR
Cost: Cost of teacher training (£110 per teacher), cost of resources (£2 per pupil)
Kipping 2014
UK
Design: C-RCT (School)
Setting: School* + Home
Age group: 6-12 (9·5)
Gender: mixed
22211825Arms: 1
Target: DPA
Theory: SCT
Duration: ≤ 12 months
Control: Standard teachingBMI-z (≤ 12 months)†
Adverse: NR
Cost: NR
Klesges 2010
USA
Design: RCT
Setting: Community
Age group: 6-12 (9·3)
Gender: Girls only
303243Arms: 1
Target: DPA
Theory: NR
Duration: > 12 months
Control: Attention control, self-esteem and social efficacyBMI (> 12 months)†
Adverse: NR
Cost: NR
Kobel 2017
Germany
Design: C-RCT (Classroom)
Setting: School* + Home
Age group: 6-12 (7·1)
Gender: mixed
525479Arms: 1
Target: DPA
Theory: Bandura's social cognitive theory
Duration: ≤ 12 months
Control: Regular school curriculumBMI (≤ 12 months)†
Adverse: NR
Cost: Intervention cost per child/year (€25.04). Costs per incidental case of averted abdominal obesity (varied between €1515
and €1993, depending on the size of the target group)
Kocken 2016
The Netherlands
Design: C-RCT (School)
Setting: School* + Home
Age group: 6-12 (intv = 9·2, control = 9·1)
Gender: mixed
1112
790Arms: 1
Target: DPA
Theory: TPB, Behavior change theory
Duration: ≤ 12 months
Control: Usual curriculumBMI-z (> 12 months)†
Adverse: NR
Cost: NR
Kriemler 2010
Switzerland
Design: C-RCT (School)
Setting: School* + Home
Age group: 6-12 (1st graders = 6·9; 5 graders intv = 11·0, control = 11·3)
Gender: mixed
502502Arms: 1
Target: PA
Theory: SEM
Duration: ≤ 12 months
Control: Not informed of an intervention groupBMI (≤ 12 months)†
Adverse: NR
Cost: NR
Kubik 2021
US
Design: RCT
Setting: School (ASP)* + Home
Age group: 6-12 (9·3)
Gender: mixed
132122Arms: 1
Target: DPA
Theory: Social–ecological framework, healthy learner model for student chronic condition management
Duration: ≤ 12 months
Control: Newsletter onlyBMI-z (≤ 12 months)†
Adverse assessed: Yes
Adverse effect: There were no serious adverse events reported.
Cost: NR
Lana 2014
Spain and Mexico
Design: RCT
Setting: School* + Home
Age group: 13-18 (intv: 26·6% = 12, 38·5% = 13, 25·7% = 14, 9·2% = ≥15; control: 20·5% = 12, 42·7% = 13, 27·4% = 14, 9·4% = ≥15)
Gender: mixed
2001737Arms: 1
Target: DPA
Theory: ASE, TTM
Duration: ≤ 12 months
Control: No intervention presumed as no detailsBMI - reported as prevalence of obesity not BMI (≤ 12 months)
Adverse: NR
Cost: NR
Lappe 2017
USA
Design: RCT
Setting: Community
Age group: 13-18 (intv = 13·5, control = 13·5)
Gender: Girls only
274274Arms: 1
Target: Diet
Theory: NR
Duration: ≤ 12 months
Control: Asked to continue usual diet, avoid calcium supplementsBMI percentiles (≤ 12 months)
Adverse assessed: Yes
Adverse effect: There were no study-related adverse events.
Cost: NR
Lazaar 2007
France
Design: C-RCT (School)
Setting: School
Age group: 6-12 (7·4)
Gender: mixed
425428Arms: 1
Target: PA
Theory: NR
Duration: ≤ 12 months
Control: Usual care presumed as no details but school-based
intervention
BMI (≤ 12 months)†
Adverse: NR
Cost: NR
Leme 2016
Brazil
Design: C-RCT (School)
Setting: School* + Home
Age group: 13-18 (16·05)
Gender: Girls only
253194Arms: 1
Target: DPA
Theory: SCT
Duration: ≤ 12 months
Control: WaitlistBMI-z (≤ 12 months)†
Adverse assessed: Yes
Adverse effect: No injuries or adverse effects were reported
Cost: NR
Lent 2014
USA
Design: C-RCT (School-store)
Setting: Community* + School
Age group: 6-12 (intv = 10·97, control = 10·99)
Gender: mixed
767511Arms: 1
Target: Diet
Theory: SCT
Duration: > 12 months
Control: No interventionBMI-z (> 12 months)†
Adverse: NR
Cost: NR
Levy 2012
Mexico
Design: C-RCT (School)
Setting: School
Age group: 6-12 (intv 78·6% = 10; control: 75·3% = 10)
Gender: mixed
1020997Arms: 1
Target: DPA
Theory: NR
Duration: ≤ 12 months
Control: Usual care presumed as no details but school-based
intervention
BMI (≤ 12 months)†
Adverse: NR
Cost: NR
Li 2010a
China
Design: C-RCT (School)
Setting: School
Age group: 6-12 (9·3)
Gender: mixed
47004187Arms: 1
Target: PA
Theory: NR
Duration: ≤ 12 months
Control: No interventionBMI and BMIz (≤ 12 months)†
Adverse assessed: Yes
Adverse effect: Underweight/ health of underweight children (No effect on BMI-z of underweight children). Physical injuries (no effect).
Cost: NR
Li 2019
China
Design: C-RCT (School)
Setting: School* + Home
Age group: 6-12 (intv = 6·15, control = 6·14)
Gender: mixed
16411581Arms: 1
Target: DPA
Theory: Behaviour change techniques, social marketing principles, MRC framework
Duration: ≤ 12 months
Control: Usual practiceBMI-z (≤ 12 months)†
Adverse assessed: Yes
Adverse effect: There was no evidence of adverse effects or harms.
Cost: Cost effectiveness (estimated £1,760 per QALY with the probability of the intervention being cost effective compared with usual care being at least 95% at a willingness to pay threshold of £20,000 to 30,000 per QALY)
Lichtenstein 2011
Germany
Design: C-RCT (School)
Setting: School* + Home
Age group: 6-12 (7·3)
Gender: mixed
445414Arms: 1
Target: DPA
Theory: NR
Duration: ≤ 12 months
Control: No interventionBMIz (≤ 12 months)†
Adverse: NR
Cost: NR
Liu 2019
China
Design: C-RCT (School)
Setting: School
Age group: 6-12 (9·0)
Gender: mixed
18891839Arms: 1
Target: DPA
Theory: ANGELO framework, SCT
Duration: ≤ 12 months
Control: No interventionBMI-z (≤ 12 months)†
Adverse assessed: Yes
Adverse effect: Percentage underweight (4·9% in intervention vs. 5·3% in control, p = 0·75). There were no adverse events reported.
Cost: NR
Llargues 2012
Spain
Design: C-RCT (School)
Setting: School
Age group: 6-12 (6·03)
Gender: mixed
704509Arms: 1
Target: DPA
Theory: Investigation, Vision, Action and Change (IVAC) Methodology
Duration: > 12 months
Control: Usual care presumed as no details but school-based
intervention
BMI (> 12 months)†
Adverse: NR
Cost: Average cost per treated child (245·8€). Ratio of net intervention costs and net intervention effects (41€/1·13 kg/m2 or 25·6€/kg)
Lloyd 2018
England
Design: C-RCT (School)
Setting: School* + Home
Age group: 6-12 (intv = 9·8, control = 9·7)
Gender: mixed
13241265Arms: 1
Target: DPA
Theory: Intervention mapping approach, behaviour change theories, HPSF
Duration: ≤ 12 months
Control: Usual practiceBMI-z (≥ 12 months)†
Adverse assessed: Yes
Adverse effect: One adverse event was reported by a concerned parent about her child's eating and activity behaviours (overexercising and restricting food intake). After discussion with the chief investigator, the parent was happy for their child to remain in the study and continue
to participate in the intervention.
Cost: Intervention cost (£210 per child). The intervention was not cost-effective compared with control.
Lubans 2011
Australia
Design: C-RCT (School)
Setting: School* + Home
Age group: 13-18 (intv = 14·4, control = 14·2)
Gender: boys only
100100Arms: 1
Target: PA
Theory: SCT
Duration: ≤ 12 months
Control: WaitlistBMI and BMIz (≤ 12 months)†
Adverse assessed: Yes
Adverse effect: There were no injuries or adverse effects reported during the activity sessions or assessments.
Cost: NR
Luszczynska 2016
Poland
Design: RCT
Setting: School
Age group: 13-18 (16·35)
Gender: mixed
702506Arms: 2
Target: Diet
Theory: SCT, BCT, self efficacy or planning
Duration: ≤ 12 months
Control: Attention control. In the group component, participants were asked to read the materials and fill in the forms provided. Participants received a set of educational materials (including crosswords) about healthy nutrition, which focused on FV consumptionBMI (≥ 12 months)†
Adverse: NR
Cost: NR
Luszczynska 2016b
Poland
Design: RCT
Setting: School
Age group: 13-18 (16·45)
Gender: mixed
12171217Arms: 3
Target: PA
Theory: SCT, BCT, planning or self efficacy
Duration: ≤ 12 months
Control: Attention control - Education only.
Reported as body fat outcome (≥ 12 months)
Adverse: NR
Cost: NR
Lynch 2016
USA
Design: C-RCT (Classroom)
Setting: School
Age group: 6-12 (Median = 8)
Gender: mixed
5150Arms: 1
Target: DPA
Theory: NR
Duration: ≤ 12 months
Control: Assume usual practiceBMI (≤ 12 months)
Adverse: NR
Cost: NR
Macias-Cervantes 2009
Mexico
Design: RCT
Setting: Community* + Home
Age group: 6-12 (Median intv = 8·0, control = 7·5)
Gender: mixed
7662Arms: 1
Target: PA
Theory: NR
Duration: ≤ 12 months
Control: Maintain the same level of physical activityBMI (≤12 months)†
Adverse: NR
Cost: NR
Madsen 2013
USA
Design: C-RCT (School)
Setting: School (ASP)
Age group: 6-12 (intv = 9·8, control = 9·8)
Gender: mixed
156150Arms: 1
Target: PA
Theory: NR
Duration: ≤ 12 months
Control: No intervention presumed as no details providedBMI-z (≤ 12 months)
Adverse: NR
Cost: NR
Madsen 2015
USA
Design: C-RCT (School)
Setting: School* + Community
Age group: 6-12 (NR)
Gender: mixed
1079676Arms: 1
Target: DPA
Theory: NR
Duration: > 12 months
Control: WaitlistBMI-z (> 12 months)†
Adverse: NR
Cost: NR
Madsen 2021
USA
Design: C-RCT (School)
Setting: School* + Home
Age group: 6-12 (NR)
Gender: mixed
2048216622Arms: 1
Target: BMI
Theory: NR
Duration: ≤ 12 months
Control: Screening onlyBMI-z (≤ 12 months)†
Adverse assessed: Yes
Adverse effect: Weight satisfaction (declined after 2 years compared to control), peer weight talk (increased after 1 year compared to control), and weight control behaviours (declined after 1 year compared to control).
Cost: NR
Magnusson 2012
Iceland
Design: C-RCT (School)
Setting: School
Age group: 6-12 (intv = 7·3, control = 7·4)
Gender: mixed
321185Arms: 1
Target: DPA
Theory: NR
Duration: > 12 months
Control: Usual practice + incentivesBMI (> 12 months)†
Adverse: NR
Cost: NR
Marcus 2009
Sweden
Design: C-RCT (School)
Setting: School* and ASP)
Age group: 6-12 (intv = 7·4, control = 7·5)
Gender: mixed
31352838Arms: 1
Target: DPA
Theory: NR
Duration: > 12 months
Control: Normal curriculumBMI (> 12 months)
Adverse assessed: Yes
Adverse effect: There were no adverse effects reported. BMI of lean children and unhealthy food restraint (no adverse effects). There were no adverse effects reported.
Cost: NR
Martinez-Vizcaino 2014
Spain
Design: C-RCT (School)
Setting: School (ASP)
Age group: 6-12 (intv = 9·4, control = 9·5)
Gender: mixed
1592912Arms: 1
Target: PA
Theory: SEM
Duration: ≤ 12 months
Control: Standard physical education curriculum(2 h/week of physical activity at low to moderate intensity)BMI (> 12 months)†
Adverse assessed: Yes
Adverse effect: No important adverse events were reported.
Percentage of underweight children (no difference.
RR 1·00 (0·53, 1·88) Baseline RR 1·03 (95%
CI 0.57 to 1·86). Dizziness during baseline venipuncture occurred in 2% of the children at baseline, and in 1·1% of the children at the end of the study. No other adverse events were reported by students during health examinations.
Two minor ankle sprains occurred during the sessions of the program (9 months incidence risk: 0·4 %). One boy was expelled from the program for aggressive behavior toward peers; his parents and the School Board made the decision by consensus.
Cost: Intervention cost (28 euros/month per child)
Mauriello 2010
USA
Design: C-RCT (School)
Setting: School
Age group: 13-18 (NR)
Gender: mixed
18001182Arms: 1
Target: DPA
Theory: TTM of Behaviour Change
Duration: ≤ 12 months
Control: No interventionBMI (≤ 12 months)
Adverse: NR
Cost: NR
Melnyk 2013
USA
Design: C-RCT (School)
Setting: School + Home
Age group: 13-18 (intv = 14·75, control = 14·74)
Gender: mixed
807627Arms: 1
Target: DPA
Theory: Cognitive theory
Duration: ≤ 12 months
Control: Attention control programme – safety and common health topics/issues
BMI (≤ 12 months)†
Adverse assessed: Yes
Adverse effect: Depressive and anxiety symptoms (no adverse effect). Note: subgroup analysis was conducted for teens with severe depression at baseline. The COPE group had significantly lower depressive symptom (within normal range at 12 months) compared with Healthy Teens group depression scores (COPE=42·39 (SE 3·94);Healthy Teens =57·90 (SE 3·77)), p-value =0.03.
Cost: NR
Meng 2020
USA
Design: C-RCT (School)
Setting: School* + Home
Age group: 6-12 (intv = 9·12, control = 9·18)
Gender: mixed
121109Arms: 1
Target: DPA
Theory: NR in this paper
Duration: ≤ 12 months
Control: Assume usual practiceBMI-z (≤ 12 months)†
Adverse: NR
Cost: NR
Mihas 2010
Greece
Design: RCT
Setting: School
Age group: 13-18 (intv = 13·1, control = 13·3)
Gender: mixed
213191Arms: 1
Target: Diet
Theory: Social Learning theory
Duration: ≤ 12 months
Control: Usual care presumed as no details but school-based
intervention
BMI (≤ 12 months)†
Adverse: NR
Cost: NR
Morgan 2011
Australia
Design: RCT
Setting: Community
Age group: 6-12 (8·2)
Gender: mixed
7171Arms: 1
Target: DPA
Theory: SCT
Duration: ≤ 12 months
Control: WaitlistBMI-Z (≤ 12 months)†
Adverse: NR
Cost: NR
Morgan 2014
Australia
Design: RCT
Setting: Community
Age group: 6-12 (8·1)
Gender: mixed
132132Arms: 1
Target: DPA
Theory: SCT, FST
Duration: ≤ 12 months
Control: WaitlistBMI-z (≤ 12 months)†
Adverse: NR
Cost: NR
Muckelbauer 2010
Germany
Design: C-RCT (School)
Setting: School
Age group: 6-12 (intv = 8·26, control = 8·34)
Gender: mixed
38172950Arms: 1
Target: Diet
Theory: TPB
Duration: ≤ 12 months
Control: No interventionBMI (≤ 12 months)
Adverse assessed: Yes
Adverse effect: There were no adverse effects reported.
Cost: Initial costs per water fountain (∼2500 euros), long-term costs per enrolled child (∼13 euros per year)
Muller 2016
Germany
Design: C-RCT (Classroom)
Setting: School
Age group: 6-12 (11·0)
Gender: mixed
366236Arms: 1
Target: PA
Theory: NR
Duration: > 12 months
Control: Usual practice. Standard curriculumBMI percentile (> 12 months)
Adverse: NR
Cost: NR
Muller 2019
South Africa
Design: C-RCT (School)
Setting: School
Age group: 6-12 (intv 1 = 10.0, intv 2 = 10.1, control = 9·9)
Gender: mixed
1009519Arms: 3
Target: PA
Theory: NR
Duration: ≤ 12 months
Control: Usual practiceBMIz (>12 months)†
Adverse assessed: Yes
Adverse effect: There were no adverse events reported.
Cost: NR
Muzaffar 2019
USA
Design: C-RCT (After school care group)
Setting: School (ASP)
Age group: 6-12 (11·6)
Gender: mixed
109101Arms: 1
Target: DPA
Theory: SCT and Stages of Change model
Duration: ≤ 12 months
CE: Adult-led interventionBMI percentile (≤ 12 months)
Adverse: NR
Cost: NR
Nct 2014
USA
Design: C-RCT (Practice)
Setting: Health care service* + Home
Age group: 6-12 (10·6)
Gender: mixed
430219Arms: 1
Target: DPA
Theory: NR
Duration: ≤ 12 months
Control: Usual practiceBMI-z (≤ 12 months)
Adverse assessed: Yes
Adverse effect: One enrolled patient death occurred during the study period (not related to participation in the research study).
Cost: NR
Neumark-Sztainer 2003
USA
Design: C-RCT (School)
Setting: School* + Home
Age group: 13-18 (intv = 14·9, control = 15·8)
Gender: Girls only
201190Arms: 1
Target: DPA
Theory: SCT
Duration: ≤ 12 months
Control: Regular physical education class and minimal intervention
(written materials on healthy eating
and physical activity at baseline)
BMI (≤ 12 months)
Adverse assessed: Yes
Adverse effect: Unhealthy behaviours in last month, binge eating, self-acceptance/self-worth (no difference between groups)
Cost: NR
Neumark-Sztainer 2010
USA
Design: C-RCT (School)
Setting: School* + Home
Age group: 13-18 (15·8)
Gender: Girls only
356336Arms: 1
Target: DPA
Theory: SCT, Stages of Change
Duration: > 12 months
Control: All-girls PE class during the first semester then usual PEBMI (> 12 months)
Adverse assessed: Yes
Adverse effect: Unhealthy weight control behaviours, binge eating, body satisfaction (no difference between groups).
Improved self worth (Harter
scale (scale 5-20), mean intervention=15·3, n=182; Control=14·4, n=174; effect size=−0·9, difference between control and intervention at follow-up, P=0·024)
Cost: NR
Newton 2014
USA
Design: RCT
Setting: Home
Age group: 6-12 (8·7)
Gender: mixed
2727Arms: 1
Target: PA
Theory: NR
Duration: ≤ 12 months
Attention control - access to websiteBMI-z (≤ 12 months)†
Adverse: NR
Cost: NR
Nollen 2014
USA
Design: RCT
Setting: Home
Age group: 6-12 (intv = 11·3, control = 11·3)
Gender: Girls only
5144Arms: 1
Target: DPA
Theory: ‘Behavioural weight control principles’
Duration: ≤ 12 months
Attention control - same content in a written manual but no promptingBMI (≤ 12 months)†
Adverse: NR
Cost: NR
Nyberg 2015
Sweden
Design: C-RCT (Classroom)
Setting: School* + Home
Age group: 6-12 (intv = 6·2, control = 6·2)
Gender: mixed
243239Arms: 1
Target: DPA
Theory: SCT
Duration: ≤ 12 months
Control: WaitlistBMI-z (≤ 12 months)
Adverse assessed: Yes
Adverse effect: Prevalence of underweight (reported no change)
Cost: NR
Nyberg 2016
Sweden
Design: C-RCT (Classroom)
Setting: Preschool*+ Home
Age group: 6-12 (6.3)
Gender: mixed
378332Arms: 1
Target: DPA
Theory: SCT
Duration: ≤ 12 months
Control: WaitlistBMI-z (≤ 12 months)†
Adverse: NR
Cost: NR
O'Connor 2020
USA
Design: RCT
Setting: Community* + Home
Age group: 6-12 (8·5)
Gender: mixed
6446Arms: 1
Target: DPA
Theory: SCT, FST
Duration: ≤ 12 months
Control: WaitlistBMI-z (≤ 12 months)†
Adverse: NR
Cost: NR
Paineau 2008
France
Design: C-RCT (School)
Setting: Home* + School
Age group: 6-12 (intv A = 7·7, intv B = 7·8, control = 7·6)
Gender: mixed
1013949Arms: 2
Target: Diet
Theory: NR
Duration: ≤ 12 months
Control: No adviceBMI-Z (≤ 12 months)†
Adverse: NR
Cost: NR
Papadaki 2010
Netherlands, Denmark, UK,
Greece, Germany, Spain, Bulgaria, and Czech Republic
Design: RCT
Setting: Community
Age group: 6-12 (boys = 11·9, girls = 12·4)
Gender: mixed
800460Arms: 4
Target: Diet
Theory: NR
Duration: ≤ 12 months
Control: Usual care. National dietary guidelines, with medium protein
content and no specific instructions on glycaemic
index
BMI and BMIz (≤ 12 months)†
Adverse: NR
Cost: NR
Pate 2005
USA
Design: C-RCT (School)
Setting: School + Home Ccommunity
Age group: 13-18 (13·6)
Gender: Girls only
16041539Arms: 1
Target: PA
Theory: SEM drawn from SCT
Duration: ≤ 12 months
Control: Usual care. Enrolled in PE classReported as % in each BMI percentile (≤ 12 months)
Adverse: NR
Cost: NR
Patrick 2006
USA
Design: RCT
Setting: Home* + Health care service
Age group: 13-18 (intv girls = 12·8, boys = 12·6; control girls = 12·6, boys = 12·8)
Gender: mixed
819690Arms: 1
Target: DPA
Theory: Behavioural Determinants model; SCT; TTM Behaviour Change
Duration: ≤ 12 months
Control: Attention control - Sun protection plus lottery tickets for small cash prizesBMI z-score (≤ 12 months)
Adverse: NR
Cost: NR
Peralta 2009
Australia
Design: RCT
Setting: School* + Home
Age group: 13-18 (12·5)
Gender: Boys only
3333Arms: 1
Target: DPA
Theory: SCT
Duration: ≤ 12 months
Control: Usual care. Physical activity curriculum sessionsBMI (≤ 12 months)†
Adverse: NR
Cost: NR
Pfeiffer 2019
USA
Design: C-RCT (School)
Setting: School (ASP)
Age group: 6-12 (12·05)
Gender: Girls only
15191519Arms: 1
Target: PA
Theory: Health promotion model, self-determination theory
Duration: ≤ 12 months
Control: Usual practiceBMI-z (≤ 12 months)†
Adverse: NR
Cost: NR
Polonsky 2019
USA
Design: C-RCT (School)
Setting: School* + Community + Home
Age group: 6-12 (10·8)
Gender: mixed
1362793Arms: 1
Target: Diet
Theory: NR
Duration: > 12 months
Control: Usual practiceBMI-z (> 12 months)†
Adverse assessed: Yes
Adverse effect: Child weight status (approximately 3-fold increase in incidence of obesity in the intervention group)
Cost: NR
Prina 2014
Mexico
Design: RCT
Setting: School* + Home
Age group: 6-12 (basic = 9·80, risk = 9·84, compare = 9·85, control = 9·78)
Gender: mixed
27462462Arms: 3
Target: DPA
Theory: Health Belief Model
Duration: ≤ 12 months
Control: No interventionBMI (≤ 12 months)†
Adverse assessed: Yes
Adverse effect: Yes. No adverse effects reported.
Cost: NR
Ramirez-Rivera 2021
Mexico
Design: RCT
Setting: School* + Home
Age group: 6-12 (10·2)
Gender: mixed
4141Arms: 1
Target: DPA
Theory: NR
Duration: ≤ 12 months
Control: General nutrition recommendationsBMI-z (≤ 12 months)†
Adverse assessed: Yes
Adverse effect: No adverse effects were observed.
Costs: NR
Reed 2008
Canada
Design: C-RCT (School)
Setting: School* + Home
Age group: 6-12 (NR)
Gender: mixed
268237Arms: 1
Target: PA
Theory: SEM
Duration: ≤ 12 months
Control: Usual careBMI (≤ 12 months)†
Adverse: NR
Cost: NR
Rerksuppaphol 2017
Thailand
Design: RCT
Setting: School*
Age group: 6-12 (10·7)
Gender: mixed
218217Arms: 1
Target: DPA
Theory: NR
Duration: ≤ 12 months
Control: Feedback only from research assistants. No interaction with online softwareBMI-z (≤ 12 months)†
Adverse: NR
Cost: NR
Rhodes 2019
Canada
Design: RCT
Setting: Home
Age group: 6-12 (8·93)
Gender: mixed
102102Arms: 1
Target: PA
Theory: Health Action Process Approach and the Multi-Process Action Control Approach
Duration: ≤ 12 months
Attention control education onlyBMI (≤ 12 months)†
Adverse assessed: Yes
Adverse effect: Yes reported. No participants cited harms associated with the study
Cost: NR
Robbins 2006
USA
Design: C-RCT (Grade)
Setting: School* + Home
Age group: 6-12 (intv grade 6 = 11·45, grade 7 = 12·37, grade 8 = 13·00; control grade 6 = 11·25, grade 7 = 12·27, grade 8 = 13·44)
Gender: Girls only
7777Arms: 1
Target: PA
Theory: Health Promotion Model and TTM
Duration: ≤ 12 months
Attention control: Handout listing the PA recommendationsBMI (≤ 12 months)†
Adverse: NR
Cost: NR
Robinson 2003
USA
Design: RCT
Setting: Community* + Home
Age group: 6-12 (9·5)
Gender: Girls only
6160Arms: 1
Target: DPA
Theory: SCT
Duration: ≤ 12 months
Attention control: health education programme
to promote healthful diet and activity patterns via
newsletters and delivering health education lectures
BMI (≤ 12 months)†
Adverse: NR
Cost: NR
Robinson 2010
USA
Design: RCT
Setting: Community* + Home
Age group: 6-12 (intv = 9·5, control = 9·4)
Gender: Girls only
261225Arms: 1
Target: PA
Theory: SCM
Duration: > 12 months
Attention control: Information-based health educationBMI and BMIz (> 12 months)†
Adverse assessed: Yes
Adverse effect: Weight concerns (no effect), percent underweight (no difference), body dissatisfaction (no effect), depressive symptoms (reduced for intervention group). No injuries or illness were judged to be probably or definitely related to study participation.
Cost: NR
Rodearmel 2006
USA
Design: RCT (Family)
Setting: Home
Age group: 6-12 (intv target girls = 10·1, target boys = 9·8, other girls = 12·8, other boys = 11·8; control target girls = 9·9, target boys = 9·9, other girls = 11·8, other boys = 12·0)
Gender: mixed
11888Arms: 1
Target: DPA
Theory: NR
Duration: ≤ 12 months
Control: Maintain usual eating and step patterns (given step counter and logs same as intervention group)Reports % BMI-for-age as outcome (≤ 12 months)
Adverse: NR
Cost: NR
Rosario 2012
Portugal
Design: C-RCT (School)
Setting: School
Age group: 6-12 (8·3)
Gender: mixed
464294Arms: 1
Target: Diet
Theory: Health Promotion Model and SCT
Duration: ≤ 12 months
Control: Usual care presumed as no details but school-based
intervention
BMI-z (≤ 12 months)†
Adverse: NR
Cost: NR
Rosenkranz 2010
USA
Design: C-RCT (Girl scout troops)
Setting: Community* + Home
Age group: 6-12 (intv = 10·6, control = 10·5)
Gender: Girls only
7672Arms: 1
Target: DPA
Theory: SCT
Duration: ≤ 12 months
Control: No intervention presumed (Girl Scouts USA)BMI and BMIz (≤ 12 months)†
Adverse: NR
Cost: NR
Rush 2012
New Zealand
Design: C-RCT (School)
Setting: School* + Home
Age group: 6-12 (NR)
Gender: mixed
33521352Arms: 1
Target: DPA
Theory: NR
Duration: > 12 months
Control: No additional resourcing or informationBMI-z (> 12 months)
Adverse: NR
Cost: Intervention cost (<$40 New Zealand dollars per child per year)
Safdie 2013
Mexico
Design: C-RCT (School)
Setting: School
Age group: 6-12 (intv plus = 9·7, intv basic = 9·7, control = 9·8)
Gender: mixed
886830Arms: 2
Target: DPA
Theory: Ecological principles, Theory of Planned Behaviour, SCT, Health Belief Model
Duration: > 12 months
Control: No changes were made to existing nutrition or physical activity practicesBMI (> 12 months)†
Adverse: NR
Cost: NR
Sahota 2001
UK
Design: C-RCT - crossover (School)
Setting: School
Age group: 6-12 (intv = 8·36, control = 8·42)
Gender: mixed
613595Arms: 1
Target: PA
Theory: multi-component health promotion programme, based on the Health Promoting Schools concept
Duration: ≤ 12 months
Control: Usual care presumed as no details but school-based
intervention
BMI-z (≤ 12 months)†
Adverse assessed: Yes
Adverse effect: BMI, psychological measures and dieting behaviours (no difference between groups). Global self-worth (higher in obese children in intervention group).
Cost: NR
Sahota 2019
England
Design: C-RCT (School)
Setting: School
Age group: 6-12 (year 2 intv = 6·2, control = 6·3; year 4 = 8·3; overall 7·2)
Gender: mixed
358311Arms: 1
Target: DPA
Theory: Behaviour Theory, BCW
Duration: > 12 months
Control: Usual practiceBMI-z (> 12 months)†
Adverse assessed: Yes
Adverse effect: Body shape and dieting behavior (results suggest no negative impact)
Cost: NR
Sallis 1993
USA
Design: C-RCT (School)
Setting: School
Age group: 6-12 (9·25)
Gender: mixed
745549Arms: 2
Target: PA
Theory: Behaviour Change and self-management
Duration: > 12 months
Control: Usual care PEBMI (> 12 months)
Adverse: NR
Cost: NR
Salmon 2008
Australia
Design: C-RCT (Classroom)
Setting: School
Age group: 6-12 (10·7)
Gender: mixed
295268Arms: 3
Target: PA
Theory: SCT and Behavioural Choice theory
Duration: ≤ 12 months
Control: Usual care curriculumBMI (≤ 12 months)
Adverse assessed: Yes
Adverse effect: Happiness with body weight and shape and eating to gain or lose weight (no effect).
Cost: NR
Santos 2014
Canada
Design: C-RCT (School)
Setting: School
Age group: 6-12 (intv = 9·3, control = 8·8)
Gender: mixed
687647Arms: 1
Target: DPA
Theory: NR
Duration: ≤ 12 months
Control: Usual care regular curriculumBMI-z (≤ 12 months)†
Adverse: NR
Cost: NR
Sekhavat 2014
Canada
Design: RCT
Setting: Health care service
Age group: 6-12 years (8·9)
Gender: mixed
168106Arms: 1
Target: DPA
Theory: NR
Duration: ≤ 12 months
Control: WaitlistBMI-z (≤ 12 months)
Adverse: NR
Cost: NR
Sevinc 2011
Turkey
Design: C-RCT (group – 2 schools in each group schools)
Setting: School
Age group: 6-12 (NR)
Gender: mixed
68476366Arms: 2
Target: Diet and DPA
Theory: NR
Duration: ≤ 12 months
Control: Usual care presumed as no details but school-based
intervention
BMI (≤ 12 months)†
Adverse: NR
Cost: NR
Sgambato 2019
Brazil
Design: C-RCT (School)
Setting: School* + Home
Age group: 6-12 (NR)
Gender: mixed
27432276Arms: 1
Target: DPA
Theory: NR
Duration: ≤ 12 months
Control: Assume usual practiceBMI (≤ 12 months)
Adverse assessed: Yes
Adverse effect: BMI (increased more in the intervention group than in the control group (Δ=0·3 kg/m2; P=0·05) with a greater decrease in %body fat among boys (Δ=–0·6 %; P=0·03) in the control group). The subgroup that received both the school and home interventions had an increase in % body fat greater than in the control group (Δ=0·89 %; P=0·01).
Cost: NR
Sherwood 2019
USA
Design: RCT
Setting: Home* + Health care service
Age group: 6-12 (6·6)
Gender: mixed
421363Arms: 1
Target: DPA
Theory: SCT, MI informed
Duration: ≤ 12 months
Attention control: intervention focused on general health, safety, and injury preventionBMI-z (≤ 12 months)†
Adverse: NR
Cost: NR
Shin 2015
USA
Design: RCT
Setting: Community
Age group: 13-18 (13·0)
Gender: mixed
242152Arms: 1
Target: Diet
Theory: SCT
Duration: ≤ 12 months
Control: No interventionBMI percentile (≤ 12 months)
Adverse: NR
Cost: NR
Shomaker 2019
USA
Design: RCT
Setting: Community
Age group: 13-18 (mindfulness = 13·97, health education = 14·49)
Gender: mixed
5454Arms:
Target: Mindfulness
Theory: Mindfulness-based
Duration: ≤ 12 months
Control: Health education control group - which met for six one-hour sessions, once per week. control condition matched for instruction time and designed to parallel health knowledge presented in a middle/high school health class. sessions covered six topics: alcoBMIz (≤ 12 months)†
Adverse: NR
Cost: NR
Sichieri 2008
Brazil
Design: C-RCT (School)
Setting: School
Age group: 6-12 (10·9)
Gender: mixed
1134927Arms: 1
Target: Diet
Theory: NR
Duration: ≤ 12 months
Attention control: 2×1-h general sessions on health issues and printed general advices regarding healthy dietsBMI (≤ 12 months)†
Adverse: NR
Cost: NR
Siegrist 2013
Germany
Design: C-RCT (School)
Setting: School* + Home
Age group: 6-12 (8·4)
Gender: mixed
826724Arms: 1
Target: DPA
Theory: NR
Duration: ≤ 12 months
Control: Usual careBMI and BMIz (≤ 12 months)†
Adverse assessed: Yes
Adverse effect: Underweight (“children below the 10th centile for weight, and several underweight children in both intervention and control groups showed a decrease in waist circumference. There were no significant differences between the intervention and control groups however. This suggests that these reductions were not related to the intervention”)
Cost: NR
Siegrist 2018
Germany
Design: C-RCT (School)
Setting: School* + Home
Age group: 6-12 (11·1)
Gender: mixed
620434Arms: 1
Target: DPA
Theory: SCT
Duration: > 12 months
Control: Usual practice - normal PE programBMI (> 12 months)†
Adverse: NR

Cost: NR
Simon 2008
France
Design: C-RCT (School)
Setting: School* + ASP
Age group: 6-12 (intv = 11·7, control = 11·6)
Gender: mixed
954954Arms: 1
Target: PA
Theory: Behaviour Change and SEM
Duration: > 12 months
Control: Usual care school curriculumBMI (> 12 months)†
Adverse: NR
Cost: NR
Simons 2015
The Netherlands
Design: RCT
Setting: Home
Age group: 13-18 (13·9)
Gender: mixed
270257Arms: 1
Target: PA
Theory: NR
Duration: ≤ 12 months
Control: WaitlistBMI-z (≤ 12 months)†
Adverse assessed: Yes
Adverse effect: Injuries (bruises or strained muscles/tendons while playing Move video games, 20%)
Cost: NR
Singh 2009
The Netherlands
Design: C-RCT (School)
Setting: School
Age group: 13-18 (intv boys = 12·8, girls = 12·6; control boys = 12·9, girls = 12·7)
Gender: mixed
11081108Arms: 1
Target: DPA
Theory: Intervention mapping protocol, Behaviour Change and Environmental frameworks
Duration: ≤ 12 months
Control: Usual care regular curriculumBMI (≤ 12 months)†
Adverse: NR
Cost: NR
Smith 2014
Australia
Design: C-RCT (School)
Setting: School* + Home
Age group: 13-18 (12·7)
Gender: Boys only
361361Arms: 1
Target: PA
Theory: Self-determination theory and SCT
Duration: ≤ 12 months
Control: Waitlist and usual practice (i.e. regularly scheduled
school sports and PE)
BMI (≤ 12 months)†
Adverse assessed: Yes
Adverse effect: No adverse events or injuries were reported during the school sports sessions, lunchtime leadership sessions, or assessments. Psychological wellbeing (small but significant positive effect)
Cost: Cost of fitness equipment pack provided to schools (1500 AUD)
Spiegel 2006
USA
Design: C-RCT (Classroom)
Setting: School* + Home
Age group: 6-12 (NR)
Gender: mixed
11911013Arms: 1
Target: DPA
Theory: Theory of Reasoned Action, Constructivism
Duration: ≤ 12 months
Control: Data collection onlyBMI-z (≤ 12 months)
Adverse: NR
Cost: NR
Stettler 2015
USA
Design: C-RCT (Practice)
Setting: Health care service
Age group: 6-12 (beverage-only intervention = 10·8, multiple behaviour intervention = 10·7, control = 10·8)
Gender: mixed
173121Arms: 2
Target: DPA
Theory: Behavioral economics
Duration: ≤ 12 months
Control: Attention control - control intervention of the same intensity unrelated to weight (friendship making intervention)BMI-z (≤ 12 months)†
Adverse: NR
Cost: Payment to clinician per completed session ($35).
Story 2003a
USA
Design: RCT
Setting: School (ASP)* + Home
Age group: 6-12 (intv = 9·4, control = 9·1)
Gender: Girls only
5353Arms: 1
Target: DPA
Theory: SCT, youth development, and resiliency based approach
Duration: ≤ 12 months
Control: “active placebo,” non-nutrition/PA condition, promoting self-esteem and cultural enrichmentBMI (≤ 12 months)†
Adverse assessed: Yes
Adverse effect: Weight concern behaviours (Higher moderate and less healthy weight concern behaviours in intervention group at follow-up)
Cost: NR
Telford 2012
Australia
Design: C-RCT (Schools)
Setting: School
Age group: 6-12 (NR)
Gender: mixed
Unclear620Arms: 1
Target: PA
Theory: NR
Duration: > 12 months
Control: Usual care, common practice PEOutcome reported as percentage change of body fat (> 12 months)
Adverse: NR
Cost: NR
TenHoor 2018
The Netherlands
Design: C-RCT (School)
Setting: School
Age group: 13-18 (12·97)
Gender: mixed
695293Arms: 1
Target: PA
Theory: NR
Duration: ≤ 12 months
Control: Usual curriculumOnly weight kg and fat mass reported (≤ 12 months)
Adverse: NR
Cost: NR
Thivel 2011
France
Design: C-RCT (School)
Setting: School
Age group: 6-12 (NR)
Gender: mixed
457457Arms: 1
Target: PA
Theory: NR
Duration: ≤ 12 months
Control: Not aware of the intervention in other schoolsBMI (≤ 12 months)†
Adverse: NR
Cost: NR
Treviño 2004
USA
Design: C-RCT (School)
Setting: School* + Home
Age group: 6-12 (intv = 9·79, control = 9·77)
Gender: mixed
19931221Arms: 1
Target: DPA
Theory: SCT and a socio-ecological framework
Duration: ≤ 12 months
Control: Assume usual practiceBody fat % (≤ 12 months)
Adverse: NR
Cost: NR
Velez 2010
USA
Design: RCT
Setting: School
Age group: 13-18 (16·14)
Gender: mixed
3128Arms: 1
Target: PA
Theory: NR
Duration: ≤ 12 months
Control: No interventionBMI (≤ 12 months)†
Adverse: NR
Cost: NR
Viggiano 2015
Italy
Design: C-RCT (School)
Setting: School
Age group: 13-18 (intv = 13·3, control = 13·0)
Gender: mixed
31102156Arms: 1
Target: DPA
Theory: NR
Duration: ≤ 12 months
Control: No interventionBMI-z (≤ 12 months)†
Adverse: NR
Cost: NR
Viggiano 2018
Italy
Design: C-RCT (School)
Setting: School
Age group: 6-12 (NR)
Gender: mixed
13131007Arms: 1
Target: DPA
Theory: NR
Duration: ≤ 12 months
Control: No interventionBMI-z (≤ 12 months)†
Adverse: NR
Cost: NR
Vizcaino 2008
Spain
Design: C-RCT (School)
Setting: School (ASP)
Age group: 6-12 (intv boys = 9·4, girls = 9·4; control boys = 9·5, girls = 9·4)
Gender: mixed
11191044Arms: 1
Target: PA
Theory: NR
Duration: ≤ 12 months
Control: Standard PE curriculum (3 h/week of PA at low to moderate intensity)BMI (≤ 12 months)†
Adverse: NR
Cost: Intervention cost
(EUR 28 per child per month)
Wang 2012
China
Design: C-RCT (Schools)
Setting: School
Age group: 6-12 (NR)
Gender: mixed
1003931Arms: 1
Target: DPA
Theory: NR
Duration: ≤ 12 months
Control: Usual care presumed as no details but school-based
intervention (translated)
Prevalence of overweight/obesity (≤ 12 months)
Adverse: NR
Cost: NR
Wang 2018
China
Design: C-RCT (School)
Setting: School* + Community + Home
Age group: 6-12 (10·5)
Gender: mixed
100919858Arms: 1
Target: DPA
Theory: NR
Duration: ≤ 12 months
Control: No interventionBMI-z (≤ 12 months)†
Adverse assessed: Yes
Adverse effect: stated no adverse events were reported.
Cost: NR
Warren 2003
England
Design: RCT
Setting: School* + Home
Age group: 6-12 (6·1)
Gender: mixed
218172Arms: 3
Target: Diet, PA, DPA
Theory: Social Learning theory
Duration: > 12 months
Control: Educational programme about food in a ‘non-nutrition’ = Be Smart
sense
Reported as percentage overweight/obese (> 12 months)
Adverse: NR
Cost: NR
Waters 2017
Australia
Design: C-RCT (School)
Setting: School* + Community + Home
Age group: 6-12 (NR)
Gender: mixed
32222743Arms: 1
Target: DPA
Theory: Health Promoting Schools Framework (based on health promotion theory and consistent with a socio-environmental theoretical framework) and International Obesity Task Force ‘10 guiding principles for obesity prevention'
Duration: > 12 months
Control: Usual practiceBMI-z (> 12 months)†
Adverse assessed: Yes
Adverse effect: Body image sensitivity protocol (no findings reported)
Cost: Estimated cost (discounted) of a community development worker ($55,868 per school over study period, $229 per student)
Weeks 2012
Australia
Design: RCT
Setting: School
Age group: 13-18 (boys = 13·8, girls = 13·7)
Gender: Boys only
9981Arms: 1
Target: PA
Theory: NR
Duration: ≤ 12 months
Control: Regular PE warm-upBMI (≤ 12 months)†
Adverse: NR
Cost: NR
Wendel 2016
USA
Design: C-RCT (Classroom)
Setting: School
Age group: 6-12 (8·8)
Gender: mixed
343111Arms: 3
Target: PA
Theory: NR
Duration: > 12 months
Control: No interventionBMI (> 12 months)†
Adverse assessed: Yes
Adverse effect: Reports “no harm to students”
Cost: NR
White 2019
USA
Design: RCT
Setting: Community* + Home
Age group: 6-12 (9·35)
Gender: mixed
228125Arms: 1
Target: DPA
Theory: SCT, experiential 4-H learning model
Duration: > 12 months
Control: No interventionBMI-z (> 12 months)†
Adverse: NR

Cost: NR
Whittemore 2013
USA
Design: C-RCT (Classroom)
Setting: School* + Home
Age group: 13-18 (15·31)
Gender: mixed
384365Arms: 1
Target: DPA
Theory: Theory of interactive technology, Social Learning theory
Duration: ≤ 12 months
Attention control: health education and behavioral supportBMI (≤ 12 months)†
Adverse: NR
Cost: NR
Wieland 2018
USA
Design: RCT
Setting: Home
Age group: 13-18 (13·5)
Gender: mixed
8166Arms: 1
Target: DPA
Theory: SCT
Duration: ≤ 12 months
Control: Delayed interventionBMI (≤ 12 months)†
Adverse: NR
Cost: NR
Wilksch 2015
Australia
Design: C-RCT (Classroom)
Setting: School
Age group: 13-18 (13·21)
Gender: mixed
820820Arms: 1
Target: DPA
Theory: NR
Duration: ≤ 12 months
Control: Usual school classBMI (≤ 12 months)†
Adverse assessed: Yes
Adverse effect: Concerns about shape and weight, risk of eating disorders (Girls in the Life Skills intervention reported higher eating concern at 12-month follow-up compared to the control group). High weight and shape concern participants had higher levels of eating concern at 12-month follow-up in the intervention group compared to control
Cost: NR
Williamson 2012
USA
Design: C-RCT (School)
Setting: School* + Home
Age group: 6-12 (PP = 10·5, SP = 10·5, control = 10·6)
Gender: mixed
20601697Arms: 2
Target: DPA
Theory: SLT
Duration: > 12 months
Control: No interventionBMI-z (> 12 months)†
Adverse: NR
Cost: NR
Xu 2015
China
Design: C-RCT (School)
Setting: School* + Home
Age group: 6-12 (10·2)
Gender: mixed
11821108Arms: 1
Target: DPA
Theory: NR
Duration: ≤ 12 months
Control: Usual practiceBMI (≤ 12 months)†
Adverse assessed: Yes
Adverse effect: There was no observable adverse event in the intervention group.
Cost: NR
Xu 2017
China
Design: C-RCT (School)
Setting: School* + Home
Age group: 6-12 (9·2)
Gender: mixed
98678573Arms: 3
Target: Diet, PA, DPA
Theory: NR
Duration: ≤ 12 months
Control: no interventionBMI and BMIz (≤ 12 months)†
Adverse assessed: Yes
Adverse effect: Effect on malnourished students (no negative effect observed. > increase in BMI and BMI-z score in intervention group)
Cost: Cost-effectiveness ratio in combined intervention ($120·3 for 1 kg/m BMI reduction, $249·3 for one unit of BMI-z score reduction), cost for avoiding one overweight and obesity case ($1308·90). Cost utility ratio (¥11,505·9, $1646·0) per QALY, cost-benefit ratio (¥1·2 benefit per ¥1 cost), and net saving (¥73,659·6, $10,537·9) for combined intervention.
Zhou 2019
China
Design: C-RCT (School)
Setting: School* (some groups ASP) + Home
Age group: 13-18 (12·66)
Gender: mixed
758681Arms: 3
Target: DPA
Theory: SEM, CMT
Duration: ≤12 months
Control: Usual careOnly weight kg and body fat % reported (≤12 months)
Adverse: NR
Cost: NR
Zota 2016
Greece
Design: C-RCT (School)
Setting: School* + Home
Age group: 6-12; 13-18 (NR)
Gender: mixed
212613627Arms: 1
Target: Diet
Theory: NR
Duration: ≤12 months
Attention control: environmental intervention (received a healthy daily meal)Reported as underweight vs. overweight/obese (≤12 months)
Adverse assessed: Yes
Adverse effect: Percentage of children and adolescents improving BMI from underweight to normal (Higher in multicomponent intervention group compared to environmental intervention only).
Cost: Average cost of meals (€1·50)
  • Open table in a new tab

Figure 2

 StudiesParticipantsSMD (95% CI)*I Test of subgroupGRADE certainty of evidence
School93131443 · · · 56%NA⊕⊕⊕
Moderate
Subgroup: age 6–12 years72114451 · · · 21%Chi  = 0·17 (P = 0·68) 
Subgroup: age 13–18 years2116992-0·05 [-0·14, 0·04]84%NA 
Sensitivity: ROB4254132 · · · 13%NA 
Sensitivity: excl change scores82116127 · · · 59%NA 
Sensitivity: correlation est 0·8093131443 · · · 57%NA 
Sensitivity: correlation est 0·9093131443 · · · 59%NA 
Sensitivity: ICC=093131443 · · · 65%NA 
Subgroup: Intv duration <= 12 months6790478 ·04 · · 64%Chi  = 2·10 (P = 0·15) 
Subgroup: Intv duration > 12 months2640965-0·02 [-0·04, 0·01]0%NA 
Subgroup: Intv type - Diet only1114999-0·00 [-0·07, 0·06]51%Chi  = 1·22 (P = 0·75) 
Subgroup: Intv type - PA only2516935 · · · 37%NA 
Subgroup: Intv type - Diet + PA5882887 · · · 1 61%NA 
Subgroup: Intv type - Other116622-0·03 [-0·08, 0·02]-NA 
Subgroup: Continent Africa1519-0·23 [-0·45, -0·01]-Chi  = 2·02 (P = 0·73) 
Subgroup: Continent Asia1035905-0·04 [-0·09, 0·01]53%NA 
Subgroup: Continent Australia117167-0·04 [-0·10, 0·03]25%NA 
Subgroup: Continent Europe4243979-0·04 [-0·09, 0·00]72%NA 
Subgroup: Continent North America2339253-0·02 [-0·04, 0·01]0%NA 
Subgroup: Continent South America64620-0·00 [-0·07, 0·06]0%NA 
After-school program125066-0·09 [-0·22, 0·04]76%NA
Very low
Subgroup: age 6–12 years104636-0·02 [-0·09, 0.05]15%Chi  = 1·89 (P = 0·17) 
Subgroup: age 13–18 years2430-0·67 [-1·60, 0·25]93%NA 
Sensitivity: ROB94316-0·14 [-0·30, 0·01]79%NA 
Sensitivity: excl change scoresNANANANANA 
Sensitivity: correlation est 0·80NANANANANA 
Sensitivity: correlation est 0·90NANANANANA 
Sensitivity: ICC=0125066-0·09 [-0·22, 0·04]76%NA 
Subgroup: Intv duration <= 12 months125066-0·09 [-0·22, 0·04]76%NA 
Subgroup: Intv duration > 12 monthsNANANANANA 
Subgroup: Intv type - Diet onlyNANANANANA 
Subgroup: Intv type - PA only73977 · · · 82%Chi  = 4·20 (P = 0·04) 
Subgroup: Intv type - Diet + PA510890·08 [-0·10, 0·26]27%NA 
Subgroup: Intv type - Other00NA NA 
Subgroup: Continent Africa1160-1·14 [-1·48, -0·81]-Chi  = 0·36 (P = 0·55) 
Subgroup: Continent Australia135-0·60 [-1·28, 0·08]-NA 
Subgroup: Continent Europe21956-0·04 [-0·13, 0·05]0%NA 
Subgroup: Continent North America72645-0·00 [-0·10, 0·11]16%NA 
Subgroup: Continent South America1270-0·20 [-0·54, 0·14]-NA 
Community213292-0·04 [-0·11, 0·04]0%n/a⊕⊕
Low
Subgroup: age 6–12 years203238-0·04 [-0·12, 0·03]0%NA 
Subgroup: age 13–18 years1540·11 [-0·42, 0·65]-NA 
Sensitivity: ROB121211-0·02 [-0·12, 0·09]0%NA 
Sensitivity: excl change scores172816-0·04 [-0·13, 0·05]0%NA 
Sensitivity: correlation est 0·80213292-0·02 [-0·09, 0·04]0%NA 
Sensitivity: correlation est 0·90213292-0·02 [-0·07, 0·04]0%NA 
Sensitivity: ICC=0213292-0·05 [-0·12, 0·02]0%NA 
Subgroup: Intv duration <= 12 months161699-0·03 [-0·13, 0·06]0%Chi  = 0·01 (P = 0·92) 
Subgroup: Intv duration > 12 months51593-0·04 [-0·16, 0·07]0%NA 
Subgroup: Intv type - Diet only41174-0·07 [-0·22, 0·09]0%Chi  = 0·38 (P = 0·82) 
Subgroup: Intv type - PA only4555-0·00 [-0·15, 0·14]0%NA 
Subgroup: Intv type - Diet + PA131563-0·04 [-0·15, 0·06]0%NA 
Subgroup: Intv type - Other00NA-NA 
Subgroup: Continent Asia1104-0·31 [-0·72, 0·10]-Chi  = 1·75 (P = 0·42) 
Subgroup: Continent Australia3251-0·08 [-0·28, 0·11]0%NA 
Subgroup: Continent Europe2523-0·14 [-0·35, 0·07]0%NA 
Subgroup: Continent North America1524140·00 [-0·09, 0·09]0%NA 
Home1324000·01 [-0·07, 0·09]0%NA⊕⊕
Low
Subgroup: age 6–12 years71665-0·04 [-0·14, 0·06]0%Chi  = 2·99 (P = 0·08) 
Subgroup: age 13–18 years67350·11 [-0·03, 0·25]0%NA 
Sensitivity: ROB719270·02 [-0·11, 0·14]33%NA 
Sensitivity: excl change scores912550·05 [-0·08, 0·18]19%NA 
Sensitivity: correlation est 0·801324000·00 [-0·07, 0·07]0%NA 
Sensitivity: correlation est 0·90132400-0·01 [-0·08, 0·06]10%NA 
Sensitivity: ICC=01324000·00 [-0·07, 0·07]0%NA 
Subgroup: Intv duration <= 12 months1448620·01 [-0·07, 0·09]0%NA 
Subgroup: Intv duration > 12 months00NA-NA 
Subgroup: Intv type - Diet only31098-0·04 [-0·16, 0·08]0%Chi  = 5·80 (P = 0·05) 
Subgroup: Intv type - PA only33860·22 [0·02, 0·42]0%NA 
Subgroup: Intv type - Diet + PA83378-0·02 [-0·15, 0·11]0%NA 
Subgroup: Intv type - Other00NA-NA 
Subgroup: Continent Australia146-0·19 [-0·81, 0·43]-Chi  = 0·51 (P = 0·47) 
Subgroup: Continent Europe212060·12 [-0·21, 0·45]83%NA 
Subgroup: Continent North America101148-0·01 [-0·12, 0·10]0%NA 
Health care service1121-0·48 [-0·95, -0·01]-NA⊕⊕
Low
Subgroup: age 6–12 years00NA-NA 
Subgroup: age 13–18 years1121-0·48 [-0·95, -0·01]-NA 
Sensitivity: ROB00NA-NA 
Sensitivity: excl change scoresNANANA-NA 
Sensitivity: correlation est 0·80NANANA-NA 
Sensitivity: correlation est 0·90NANANA-NA 
Sensitivity: ICC=0NANANA-NA 
Subgroup: Intv duration <= 12 months1121-0·48 [-0·95, -0·01]-NA 
Subgroup: Intv type - Diet + PA1121-0·48 [-0·95, -0·01]-NA 

Contributors

Declaration of interests, acknowledgements, appendix supplementary materials (1), article metrics.

  • Download Hi-res image
  • Download .PPT
  • Institutional Access: Log in to ScienceDirect
  • New Subscriber: Claim access with activation code. New subscribers select Claim to enter your activation code.

The Lancet Choice

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • View all journals
  • Explore content
  • About the journal
  • Publish with us
  • Sign up for alerts
  • Review Article
  • Published: 23 September 2024

Early life factors that affect obesity and the need for complex solutions

  • Kylie D. Hesketh   ORCID: orcid.org/0000-0002-2702-7110 1 ,
  • Miaobing Zheng 1 &
  • Karen J. Campbell 1  

Nature Reviews Endocrinology ( 2024 ) Cite this article

43 Accesses

9 Altmetric

Metrics details

  • Risk factors

The prevalence of obesity increases with age but is apparent even in early life. Early childhood is a critical period for development that is known to influence future health. Even so, the focus on obesity in this phase, and the factors that affect the development of obesity, has only emerged over the past two decades. Furthermore, there is a paucity of iterative work in this area that would move the field forward. Obesity is a complex condition involving the interplay of multiple influences at different levels: the individual and biological level, the sociocultural level, and the environmental and system levels. This Review provides a brief overview of the evidence for these factors with a focus on aspects specific to early life. By spotlighting the complex web of interactions between the broad range of influences, both causal and risk markers, we highlight the complex nature of the condition. Much work in the early life field remains observational and many of the intervention studies are limited by a focus on single influences and a disjointed approach to solutions. Yet the complexity of obesity necessitates coordinated multi-focused solutions and joined-up action across the first 2,000 days from conception, and beyond.

A large proportion of obesity risk originates in early life, making this life phase an opportune time for primary prevention.

Obesity risk factors occur across individual and biological, sociocultural, and environmental and system levels; some are unique to early childhood (such as breastfeeding) whereas others are relevant across the life cycle (such as diet and movement behaviours).

The interplay of risk factors contributes to the complexity of obesity and its development and highlights the need for complex solutions.

Focusing the narrative on supporting health behaviours rather than on obesity and weight might be more palatable and result in greater engagement from practitioners and families.

It is time to move beyond single behaviour interventions, which have limited effectiveness in early childhood, to focus on more complex multi-behaviour interventions, tailored to individual or specific population needs, to tackle the multiple influences on obesity.

This is a preview of subscription content, access via your institution

Access options

Access Nature and 54 other Nature Portfolio journals

Get Nature+, our best-value online-access subscription

24,99 € / 30 days

cancel any time

Subscribe to this journal

Receive 12 print issues and online access

195,33 € per year

only 16,28 € per issue

Buy this article

  • Purchase on SpringerLink
  • Instant access to full article PDF

Prices may be subject to local taxes which are calculated during checkout

childhood obesity research

Similar content being viewed by others

childhood obesity research

Core outcome set for early intervention trials to prevent obesity in childhood (COS-EPOCH): Agreement on “what” to measure

childhood obesity research

Understanding childhood obesity in the US: the NIH environmental influences on child health outcomes (ECHO) program

childhood obesity research

Maternal and infant prediction of the child BMI trajectories; studies across two generations of Northern Finland birth cohorts

Phelps, N. H. et al. Worldwide trends in underweight and obesity from 1990 to 2022: a pooled analysis of 3663 population-representative studies with 222 million children, adolescents, and adults. Lancet 403 , 1027–1050 (2024).

Article   Google Scholar  

Hesketh, K., Wake, M., Waters, E., Carlin, J. & Crawford, D. Stability of body mass index in Australian children: a prospective cohort study across the middle childhood years. Public. Health Nutr. 7 , 303–309 (2004).

Article   PubMed   Google Scholar  

Kain, J., Leyton, B., Baur, L., Lira, M. & Corvalán, C. Demographic, social and health-related variables that predict normal-weight preschool children having overweight or obesity when entering primary education in Chile. Nutrients 11 , 1277 (2019).

Article   PubMed   PubMed Central   Google Scholar  

Magarey, A. M., Daniels, L. A., Boulton, T. J. & Cockington, R. A. Predicting obesity in early adulthood from childhood and parental obesity. Int. J. Obes. 27 , 505–513 (2003).

Hales, C. N. et al. Fetal and infant growth and impaired glucose tolerance at age 64. BMJ 303 , 1019–1022 (1991).

Barker, D. J. P. The origins of the developmental origins theory. J. Intern. Med. 261 , 412–417 (2007).

Hoffman, D. J., Powell, T. L., Barrett, E. S. & Hardy, D. B. Developmental origins of metabolic diseases. Physiol. Rev. 101 , 739–795 (2021).

Esdaile, E. K., Rissel, C., Baur, L. A., Wen, L. M. & Gillespie, J. Intergovernmental policy opportunities for childhood obesity prevention in Australia: perspectives from senior officials. PLoS ONE 17 , e0267701 (2022).

McGuire, S. Institute of Medicine (IOM) early childhood obesity prevention policies. Washington, DC: the National Academies Press; 2011. Adv. Nutr. 3 , 56–57 (2012).

Buklijas, T. & Al-Gailani, S. A fetus in the world: physiology, epidemiology, and the making of fetal origins of adult disease. Hist. Philos. Life Sci. 45 , 44 (2023).

The Australian Prevention Partnership Centre. Why invest in prevention in the first 2000 days? The Australian Prevention Partnership Centre preventioncentre.org.au/wp-content/uploads/2022/08/First-2000-days-Policy-Brief-FINAL.pdf (2022).

World Health Organization. Obesity and overweight: Key facts. WHO www.who.int/news-room/fact-sheets/detail/obesity-and-overweight (2024).

Gortmaker, S. L., Dietz, W. H. Jr., Sobol, A. M. & Wehler, C. A. Increasing pediatric obesity in the United States. Am. J. Dis. Child. 141 , 535–540 (1987).

PubMed   Google Scholar  

Lazarus, R., Wake, M., Hesketh, K. & Waters, E. Change in body mass index in Australian primary school children, 1985–1997. Int. J. Obes. 24 , 679–684 (2000).

Chinn, S. & Rona, R. J. Secular trends in weight, weight-for-height and triceps skinfold thickness in primary schoolchildren in England and Scotland from 1972 to 1980. Ann. Hum. Biol. 14 , 311–319 (1987).

Swinburn, B. & Wood, A. Progress on obesity prevention over 20 years in Australia and New Zealand. Obes. Rev. 14 , 60–68 (2013).

UNICEF. The State of the world’s children 2019. Children, food and nutrition: growing well in a changing world. UNICEF www.unicef.org/media/106506/file/The%20State%20of%20the%20World%E2%80%99s%20Children%202019.pdf (2019).

National Health and Medical Research Council. Acting on Australia’s Weight: A Strategic Plan for the Prevention of Overweight and Obesity (Australian Government Publishing Service, 1997).

US Centers for Disease Control and Prevention. Adult obesity prevalence maps. CDC www.cdc.gov/obesity/php/data-research/adult-obesity-prevalence-maps.html (2023).

US Centers for Disease Control and Prevention. Childhood obesity facts. CDC www.cdc.gov/obesity/php/data-research/childhood-obesity-facts.html (2024).

NCD Risk Factor Collaboration. Worldwide trends in body-mass index, underweight, overweight, and obesity from 1975 to 2016: a pooled analysis of 2416 population-based measurement studies in 128.9 million children, adolescents, and adults. Lancet 390 , 2627–2642 (2017).

Australian Institute of Health and Welfare. Aboriginal and Torres Strait Islander Health Performance Framework: summary report July 2023. Tier 2 - Determinants of health. 2.22 Overweight and obesity. Australian Institute of Health and Welfare www.indigenoushpf.gov.au/measures/2-22-overweight-obesity#:~:Text=Childhood%20weight,7 (2023).

UNICEF, World Health Organization & The World Bank. Levels and trends in child malnutrition: key findings of the 2020 edition of the Joint Child Malnutrition Estimates. WHO iris.who.int/bitstream/handle/10665/331621/9789240003576-eng.pdf (2020).

UNICEF, World Health Organization & The World Bank. Levels and trends in child malnutrition: UNICEF/WHO/World Bank Group Joint Child Malnutrition Estimates: key findings of the 2023 edition. WHO iris.who.int/bitstream/handle/10665/368038/9789240073791-eng.pdf (2023).

Caprio, S. et al. Influence of race, ethnicity, and culture on childhood obesity: implications for prevention and treatment: a consensus statement of Shaping America’s Health and the Obesity Society. Diabetes Care 31 , 2211–2221 (2008).

Peña, M. M., Dixon, B. & Taveras, E. M. Are you talking to ME? The importance of ethnicity and culture in childhood obesity prevention and management. Child. Obes. 8 , 23–27 (2012).

World Health Organization. Report of the Commission on Ending Childhood Obesity. WHO iris.who.int/bitstream/handle/10665/204176/9789241510066_eng.pdf (2016).

Manohar, N., Hayen, A., Fahey, P. & Arora, A. Obesity and dental caries in early childhood: a systematic review and meta-analyses. Obes. Rev. 21 , e12960 (2020).

Berenson, G. S. et al. Association between multiple cardiovascular risk factors and atherosclerosis in children and young adults. The Bogalusa Heart Study. N. Engl. J. Med. 338 , 1650–1656 (1998).

Davison, K. K. & Birch, L. L. Weight status, parent reaction, and self-concept in five-year-old girls. Pediatrics 107 , 46–53 (2001).

Budd, G. M. & Hayman, L. L. Addressing the childhood obesity crisis: a call to action. Am. J. Matern. Child. Nurs. 33 , 111–118 (2008).

Craigie, A. M., Lake, A. A., Kelly, S. A., Adamson, A. J. & Mathers, J. C. Tracking of obesity-related behaviours from childhood to adulthood: a systematic review. Maturitas 70 , 266–284 (2011).

Brown, T. et al. Interventions for preventing obesity in children. Cochrane Database Syst. Rev. 7 , Cd001871 (2019).

Hesketh, K., Waters, E., Green, J., Salmon, L. & Williams, J. Healthy eating, activity and obesity prevention: a qualitative study of parent and child perceptions in Australia. Health Promot. Int. 20 , 19–26 (2005).

Patro-Gołąb, B. et al. Nutritional interventions or exposures in infants and children aged up to 3 years and their effects on subsequent risk of overweight, obesity and body fat: a systematic review of systematic reviews. Obes. Rev. 17 , 1245–1257 (2016).

Woo Baidal, J. A. et al. Risk factors for childhood obesity in the first 1,000 days: a systematic review. Am. J. Prev. Med. 50 , 761–779 (2016).

Weng, S. F., Redsell, S. A., Swift, J. A., Yang, M. & Glazebrook, C. P. Systematic review and meta-analyses of risk factors for childhood overweight identifiable during infancy. Arch. Dis. Child. 97 , 1019–1026 (2012).

Olsen, N. J. et al. A literature review of evidence for primary prevention of overweight and obesity in healthy weight children and adolescents: a report produced by a working group of the Danish Council on Health and Disease Prevention. Obes. Rev. 25 , e13641 (2024).

Sarni, R. O. S., Kochi, C. & Suano-Souza, F. I. Childhood obesity: an ecological perspective. J. Pediatr. 98 , S38–S46 (2022).

Golden, S. D. & Earp, J. A. Social ecological approaches to individuals and their contexts: twenty years of health education & behavior health promotion interventions. Health Educ. Behav. 39 , 364–372 (2012).

Naukkarinen, J., Rissanen, A., Kaprio, J. & Pietiläinen, K. H. Causes and consequences of obesity: the contribution of recent twin studies. Int. J. Obes. 36 , 1017–1024 (2012).

Loos, R. J. F. & Yeo, G. S. H. The genetics of obesity: from discovery to biology. Nat. Rev. Genet. 23 , 120–133 (2022).

Vourdoumpa, A., Paltoglou, G. & Charmandari, E. The genetic basis of childhood obesity: a systematic review. Nutrients 15 , 1416 (2023).

Zhou, F., Tian, G., Cui, Y., He, S. & Yan, Y. Development of genome-wide association studies on childhood obesity and its indicators: a scoping review and enrichment analysis. Pediatr. Obes. 18 , e13077 (2023).

Stryjecki, C., Alyass, A. & Meyre, D. Ethnic and population differences in the genetic predisposition to human obesity. Obes. Rev. 19 , 62–80 (2018).

Larqué, E. et al. From conception to infancy – early risk factors for childhood obesity. Nat. Rev. Endocrinol. 15 , 456–478 (2019).

Li, A. et al. Parental and child genetic contributions to obesity traits in early life based on 83 loci validated in adults: the FAMILY study. Pediatr. Obes. 13 , 133–140 (2018).

Igo, R. P. Jr., Kinzy, T. G. & Cooke Bailey, J. N. Genetic risk scores. Curr. Protoc. Hum. Genet. 104 , e95 (2019).

Fang, J. et al. Polygenic risk, adherence to a healthy lifestyle, and childhood obesity. Pediatr. Obes. 14 , e12489 (2019).

Heslehurst, N. et al. The association between maternal body mass index and child obesity: a systematic review and meta-analysis. PLoS Med. 16 , e1002817 (2019).

Howell, K. R. & Powell, T. L. Effects of maternal obesity on placental function and fetal development. Reproduction 153 , R97–R108 (2017).

Mou, S. S. et al. Association between HbA1c levels and fetal macrosomia and large for gestational age babies in women with gestational diabetes mellitus: a systematic review and meta-analysis of 17,711 women. J. Clin. Med. 12 , 3852 (2023).

Amir, L. H. & Donath, S. A systematic review of maternal obesity and breastfeeding intention, initiation and duration. BMC Pregnancy Childbirth 7 , 9 (2007).

Yu, Z. B. et al. Birth weight and subsequent risk of obesity: a systematic review and meta-analysis. Obes. Rev. 12 , 525–542 (2011).

Zheng, M. et al. Rapid weight gain during infancy and subsequent adiposity: a systematic review and meta-analysis of evidence. Obes. Rev. 19 , 321–332 (2018).

Martín-Calvo, N., Goni, L., Tur, J. A. & Martínez, J. A. Low birth weight and small for gestational age are associated with complications of childhood and adolescence obesity: systematic review and meta-analysis. Obes. Rev. 23 , e13380 (2022).

Martin, A., Connelly, A., Bland, R. M. & Reilly, J. J. Health impact of catch-up growth in low-birth weight infants: systematic review, evidence appraisal, and meta-analysis. Matern. Child. Nutr. 13 , e12297 (2017).

Geserick, M. et al. Acceleration of BMI in early childhood and risk of sustained obesity. N. Engl. J. Med. 379 , 1303–1312 (2018).

Michael, N. et al. Longitudinal characterization of determinants associated with obesogenic growth patterns in early childhood. Int. J. Epidemiol. 52 , 426–439 (2022).

Article   PubMed Central   Google Scholar  

Zheng, M. et al. Understanding the pathways between prenatal and postnatal factors and overweight outcomes in early childhood: a pooled analysis of seven cohorts. Int. J. Obes. 47 , 574–582 (2023).

Zheng, M. et al. Relative effects of postnatal rapid growth and maternal factors on early childhood growth trajectories. Paediatr. Perinat. Epidemiol. 33 , 172–180 (2019).

Rolland-Cachera, M. F., Deheeger, M., Maillot, M. & Bellisle, F. Early adiposity rebound: causes and consequences for obesity in children and adults. Int. J. Obes. 30 , S11–S17 (2006).

Zhou, J. et al. Age at adiposity rebound and the relevance for obesity: a systematic review and meta-analysis. Int. J. Obes. 46 , 1413–1424 (2022).

Victora, C. G. et al. Breastfeeding in the 21st century: epidemiology, mechanisms, and lifelong effect. Lancet 387 , 475–490 (2016).

Qiao, J., Dai, L. J., Zhang, Q. & Ouyang, Y. Q. A meta-analysis of the association between breastfeeding and early childhood obesity. J. Pediatr. Nurs. 53 , 57–66 (2020).

Zheng, M. et al. Breastfeeding and the longitudinal changes of body mass index in childhood and adulthood: a systematic review. Adv. Nutr. 15 , 100152 (2024).

Zheng, M. et al. Early infant feeding and BMI trajectories in the first 5 years of life. Obesity 28 , 339–346 (2020).

Zheng, M., Campbell, K. J., Baur, L., Rissel, C. & Wen, L. M. Infant feeding and growth trajectories in early childhood: the application and comparison of two longitudinal modelling approaches. Int. J. Obes. 45 , 2230–2237 (2021).

Martin, R. M. et al. Effects of promoting long-term, exclusive breastfeeding on adolescent adiposity, blood pressure, and growth trajectories: a secondary analysis of a randomized clinical trial. JAMA Pediatr. 171 , e170698 (2017).

UNICEF. Global breastfeeding scorecard 2023. UNICEF www.unicef.org/media/150586/file/Global%20breastfeeding%20scorecard%202023.pdf (2023).

Daniels, L., Mallan, K. M., Fildes, A. & Wilson, J. The timing of solid introduction in an ‘obesogenic’ environment: a narrative review of the evidence and methodological issues. Aust. N. Z. J. Public. Health 39 , 366–373 (2015).

D’Hollander, C. J. et al. Timing of introduction to solid food, growth, and nutrition risk in later childhood. J. Pediatr. 240 , 102–109 (2022).

Zheng, M. et al. Protein intake during infancy and subsequent body mass index in early childhood: results from the Melbourne InFANT Program. J. Acad. Nutr. Diet. 121 , 1775–1784 (2021).

Stokes, A. et al. Protein intake from birth to 2 years and obesity outcomes in later childhood and adolescence: a systematic review of prospective cohort studies. Adv. Nutr. 12 , 1863–1876 (2021).

Weber, M. et al. Lower protein content in infant formula reduces BMI and obesity risk at school age: follow-up of a randomized trial. Am. J. Clin. Nutr. 99 , 1041–1051 (2014).

Totzauer, M. et al. Effect of lower versus higher protein content in infant formula through the first year on body composition from 1 to 6 years: follow-up of a randomized clinical trial. Obesity 26 , 1203–1210 (2018).

Houtman, T. A., Eckermann, H. A., Smidt, H. & de Weerth, C. Gut microbiota and BMI throughout childhood: the role of Firmicutes, Bacteroidetes, and short-chain fatty acid producers. Sci. Rep. 12 , 3140 (2022).

Indiani, C. et al. Childhood obesity and Firmicutes/Bacteroidetes ratio in the gut microbiota: a systematic review. Child. Obes. 14 , 501–509 (2018).

Riva, A. et al. Pediatric obesity is associated with an altered gut microbiota and discordant shifts in Firmicutes populations. Environ. Microbiol. 19 , 95–105 (2017).

Liu, B. N., Liu, X. T., Liang, Z. H. & Wang, J. H. Gut microbiota in obesity. World J. Gastroenterol. 27 , 3837–3850 (2021).

Maher, S. E. et al. The association between the maternal diet and the maternal and infant gut microbiome: a systematic review. Br. J. Nutr. 129 , 1491–1499 (2023).

Rutayisire, E., Huang, K., Liu, Y. & Tao, F. The mode of delivery affects the diversity and colonization pattern of the gut microbiota during the first year of infants’ life: a systematic review. BMC Gastroenterol. 16 , 86 (2016).

Princisval, L. et al. Association between the mode of delivery and infant gut microbiota composition up to 6 months of age: a systematic literature review considering the role of breastfeeding. Nutr. Rev. 80 , 113–127 (2021).

Morreale, C. et al. Effects of perinatal antibiotic exposure and neonatal gut microbiota. Antibiotics 12 , 258 (2023).

Vander Wyst, K. B., Ortega-Santos, C. P., Toffoli, S. N., Lahti, C. E. & Whisner, C. M. Diet, adiposity, and the gut microbiota from infancy to adolescence: a systematic review. Obes. Rev. 22 , e13175 (2021).

Mehta, S., Huey, S. L., McDonald, D., Knight, R. & Finkelstein, J. L. Nutritional interventions and the gut microbiome in children. Annu. Rev. Nutr. 41 , 479–510 (2021).

Morgado, M. C., Sousa, M., Coelho, A. B., Costa, J. A. & Seabra, A. Exploring gut microbiota and the influence of physical activity interventions on overweight and obese children and adolescents: a systematic review. Healthcare 11 , 2459 (2023).

Cho, K. Y. Lifestyle modifications result in alterations in the gut microbiota in obese children. BMC Microbiol. 21 , 10 (2021).

Fang, K., Mu, M., Liu, K. & He, Y. Screen time and childhood overweight/obesity: a systematic review and meta-analysis. Child. Care Health Dev. 45 , 744–753 (2019).

Miller, M. A., Bates, S., Ji, C. & Cappuccio, F. P. Systematic review and meta-analyses of the relationship between short sleep and incidence of obesity and effectiveness of sleep interventions on weight gain in preschool children. Obes. Rev. 22 , e13113 (2021).

Reilly, J. J., Hughes, A. R., Gillespie, J., Malden, S. & Martin, A. Physical activity interventions in early life aimed at reducing later risk of obesity and related non-communicable diseases: a rapid review of systematic reviews. Obes. Rev. 20 , 61–73 (2019).

Poitras, V. J. et al. Systematic review of the relationships between sedentary behaviour and health indicators in the early years (0–4 years). BMC Public. Health 17 , 65–89 (2017).

Chaput, J.-P. et al. Systematic review of the relationships between sleep duration and health indicators in the early years (0–4 years). BMC Public. Health 17 , 91–107 (2017).

Kuzik, N. et al. Systematic review of the relationships between combinations of movement behaviours and health indicators in the early years (0-4 years). BMC Public. Health 17 , 849 (2017).

Liberali, R., Kupek, E. & Altenburg de Assis, M. A. Dietary patterns and childhood obesity risk: a systematic review. Child. Obes. 16 , 70–85 (2020).

Lioret, S. et al. Lifestyle patterns begin in early childhood, persist and are socioeconomically patterned, confirming the importance of early life interventions. Nutrients 12 , 724 (2020).

Litterbach, E. K., Zheng, M., Campbell, K. J., Laws, R. & Spence, A. C. Mealtime TV use is associated with higher discretionary food intakes in young Australian children: a two-year prospective study. Nutrients 14 , 2606 (2022).

Pedišić, Ž., Dumuid, D. & Olds, T. S. Integrating sleep, sedentary behaviour, and physical activity research in the emerging field of time-use epidemiology: definitions, concepts, statistical methods, theoretical framework, and future directions. Kinesiology 49 , 252–269 (2017).

Google Scholar  

D’Souza, N. J. et al. A systematic review of lifestyle patterns and their association with adiposity in children aged 5-12 years. Obes. Rev. 21 , e13029 (2020).

Leech, R. M., McNaughton, S. A. & Timperio, A. The clustering of diet, physical activity and sedentary behavior in children and adolescents: a review. Int. J. Behav. Nutr. Phys. Act. 11 , 4 (2014).

Zheng, M. et al. Association between longitudinal trajectories of lifestyle pattern and BMI in early childhood. Obesity 29 , 879–887 (2021).

Larsen, J. K., Sleddens, E. F. C., Vink, J. M., Fisher, J. O. & Kremers, S. P. J. General parenting styles and children’s obesity risk: changing focus. Front. Psychol. 9 , 2119 (2018).

Sokol, R. L., Qin, B. & Poti, J. M. Parenting styles and body mass index: a systematic review of prospective studies among children. Obes. Rev. 18 , 281–292 (2017).

Shloim, N., Edelson, L. R., Martin, N. & Hetherington, M. M. Parenting styles, feeding styles, feeding practices, and weight status in 4-12 year-old children: a systematic review of the literature. Front. Psychol. 6 , 1849 (2015).

Burnett, A. J., Lamb, K. E., McCann, J., Worsley, A. & Lacy, K. E. Parenting styles and the dietary intake of pre-school children: a systematic review. Psychol. Health 35 , 1326–1345 (2020).

Davids, E. L. & Roman, N. V. A systematic review of the relationship between parenting styles and children’s physical activity. Afr. J. Phys. Health Educ. Recreat. Dance 20 , 228–246 (2014).

Bergamini, M. et al. Complementary feeding caregivers’ practices and growth, risk of overweight/obesity, and other non-communicable diseases: a systematic review and meta-analysis. Nutrients 14 , 2646 (2022).

Ruzicka, E. B., Darling, K. E. & Sato, A. F. Controlling child feeding practices and child weight: a systematic review and meta-analysis. Obes. Rev. 22 , e13135 (2021).

Mahmood, L., Flores-Barrantes, P., Moreno, L. A., Manios, Y. & Gonzalez-Gil, E. M. The influence of parental dietary behaviors and practices on children’s eating habits. Nutrients 13 , 1138 (2021).

Petersen, T. L., Møller, L. B., Brønd, J. C., Jepsen, R. & Grøntved, A. Association between parent and child physical activity: a systematic review. Int. J. Behav. Nutr. Phys. Act. 17 , 67 (2020).

Davison, K. K. et al. Fathers’ representation in observational studies on parenting and childhood obesity: a systematic review and content analysis. Am. J. Public. Health 106 , e14–e21 (2016).

Freeman, E. et al. Preventing and treating childhood obesity: time to target fathers. Int. J. Obes. 36 , 12–15 (2012).

Walsh, A. D., Hesketh, K. D., Hnatiuk, J. A. & Campbell, K. J. Paternal self-efficacy for promoting children’s obesity protective diets and associations with children’s dietary intakes. Int. J. Behav. Nutr. Phys. Act. 16 , 53 (2019).

Patro, B. et al. Maternal and paternal body mass index and offspring obesity: a systematic review. Ann. Nutr. Metab. 63 , 32–41 (2013).

Stahlmann, K. et al. Family structure in relation to body mass index and metabolic score in European children and adolescents. Pediatr. Obes. 17 , e12963 (2022).

Jang, M., Owen, B. & Lauver, D. R. Different types of parental stress and childhood obesity: a systematic review of observational studies. Obes. Rev. 20 , 1740–1758 (2019).

Newton, S., Braithwaite, D. & Akinyemiju, T. F. Socio-economic status over the life course and obesity: systematic review and meta-analysis. PLoS ONE 12 , e0177151 (2017).

Wang, Y. & Lim, H. The global childhood obesity epidemic and the association between socio-economic status and childhood obesity. Int. Rev. Psychiatry 24 , 176–188 (2012).

Cameron, A. J. et al. A review of the relationship between socioeconomic position and the early-life predictors of obesity. Curr. Obes. Rep. 4 , 350–362 (2015).

Alkhatib, A. & Obita, G. Childhood obesity and its comorbidities in high-risk minority populations: prevalence, prevention and lifestyle intervention guidelines. Nutrients 16 , 1730 (2024).

Bolton, K. A., Kremer, P., Laws, R., Campbell, K. J. & Zheng, M. Longitudinal analysis of growth trajectories in young children of Chinese-born immigrant mothers compared with Australian-born mothers living in Victoria, Australia. BMJ Open. 11 , e041148 (2021).

Raju, S., Cowdell, F. & Dyson, J. Barriers and facilitators to healthy gestational weight gain amongst pregnant women from ethnic minority groups: a systematic search and narrative synthesis. Midwifery 135 , 104051 (2024).

Kumanyika, S. K. Unraveling common threads in obesity risk among racial/ethnic minority and migrant populations. Public. Health 172 , 125–134 (2019).

O’Dea, J. A. Gender, ethnicity, culture and social class influences on childhood obesity among Australian schoolchildren: implications for treatment, prevention and community education. Health Soc. Care Community 16 , 282–290 (2008).

Chakona, G. Social circumstances and cultural beliefs influence maternal nutrition, breastfeeding and child feeding practices in South Africa. Nutr. J. 19 , 47 (2020).

Dennis, C. L. et al. Breastfeeding rates in immigrant and non-immigrant women: a systematic review and meta-analysis. Matern. Child. Nutr. 15 , e12809 (2019).

Bolton, K. A. et al. Differences in infant feeding practices between Chinese-born and Australian-born mothers living in Australia: a cross-sectional study. BMC Pediatr. 18 , 209 (2018).

Tulpule, C., Zheng, M., Campbell, K. J. & Bolton, K. A. Differences in infant feeding practices between Indian-born mothers and Australian-born mothers living in Australia: a cross-sectional study. BMC Public. Health 22 , 934 (2022).

Bigman, G., Wilkinson, A. V., Perez, A. & Homedes, N. Acculturation and breastfeeding among Hispanic American women: a systematic review. Matern. Child. Health J. 22 , 1260–1277 (2018).

Kirk, S. F., Penney, T. L. & McHugh, T. L. Characterizing the obesogenic environment: the state of the evidence with directions for future research. Obes. Rev. 11 , 109–117 (2010).

Swinburn, B. A. et al. The global syndemic of obesity, undernutrition, and climate change: the Lancet Commission report. Lancet 393 , 791–846 (2019).

Ambikapathi, R. et al. Global food systems transitions have enabled affordable diets but had less favourable outcomes for nutrition, environmental health, inclusion and equity. Nat. Food 3 , 764–779 (2022).

Jia, P. et al. Fast-food restaurant, unhealthy eating, and childhood obesity: a systematic review and meta-analysis. Obes. Rev. 22 , e12944 (2021).

Pineda, E., Bascunan, J. & Sassi, F. Improving the school food environment for the prevention of childhood obesity: what works and what doesn’t. Obes. Rev. 22 , e13176 (2021).

Kininmonth, A. R. et al. The relationship between the home environment and child adiposity: a systematic review. Int. J. Behav. Nutr. Phys. Act. 18 , 4 (2021).

Sadeghirad, B., Duhaney, T., Motaghipisheh, S., Campbell, N. R. & Johnston, B. C. Influence of unhealthy food and beverage marketing on children’s dietary intake and preference: a systematic review and meta-analysis of randomized trials. Obes. Rev. 17 , 945–959 (2016).

Malacarne, D. et al. The built environment as determinant of childhood obesity: a systematic literature review. Obes. Rev. 23 , e13385 (2022).

Wilding, S. et al. Are environmental area characteristics at birth associated with overweight and obesity in school-aged children? Findings from the SLOPE (Studying Lifecourse Obesity Predictors) population-based cohort in the south of England. BMC Med. 18 , 43 (2020).

Park, S. H., Park, C. G., Bahorski, J. S. & Cormier, E. Factors influencing obesity among preschoolers: multilevel approach. Int. Nurs. Rev. 66 , 346–355 (2019).

Schalkwijk, A. A. H., van der Zwaard, B. C., Nijpels, G., Elders, P. J. M. & Platt, L. The impact of greenspace and condition of the neighbourhood on child overweight. Eur. J. Public. Health 28 , 88–94 (2018).

Lovasi, G. S. et al. Neighborhood safety and green space as predictors of obesity among preschool children from low-income families in New York City. Prev. Med. 57 , 189–193 (2013).

OECD Family Database. PF3.2: Enrolment in childcare and pre-school, in public policies for families and children. OECD www.oecd.org/content/dam/oecd/en/data/datasets/family-database/pf3_2_enrolment_childcare_preschool.pdf (2019).

Zhang, Z. et al. Environmental characteristics of early childhood education and care centres and young children’s weight status: a systematic review. Prev. Med. 106 , 13–25 (2018).

Jackson, J. K. et al. Obesity prevention within the early childhood education and care setting: a systematic review of dietary behavior and physical activity policies and guidelines in high income countries. Int. J. Environ. Res. Public. Health 18 , 838 (2021).

Thow, A. M., Downs, S. & Jan, S. A systematic review of the effectiveness of food taxes and subsidies to improve diets: understanding the recent evidence. Nutr. Rev. 72 , 551–565 (2014).

Lake, A. A. Neighbourhood food environments: food choice, foodscapes and planning for health. Proc. Nutr. Soc. 77 , 239–246 (2018).

Bhattacharya, S., Saleem, S. M. & Bera, O. P. Prevention of childhood obesity through appropriate food labeling. Clin. Nutr. ESPEN 47 , 418–421 (2022).

Ferdinand, A. O., Sen, B., Rahurkar, S., Engler, S. & Menachemi, N. The relationship between built environments and physical activity: a systematic review. Am. J. Public. Health 102 , e7–e13 (2012).

Summerbell, C. D. et al. Evidence-based recommendations for the development of obesity prevention programs targeted at preschool children. Obes. Rev. 13 , 129–132 (2012).

World Health Organization. European Food and Nutrition Action Plan 2015–2020. WHO iris.who.int/bitstream/handle/10665/329405/9789289051231-eng.pdf (2014).

World Health Organization. Physical Activity Strategy for the WHO European Region 2016–2025. WHO iris.who.int/bitstream/handle/10665/329407/9789289051477-eng.pdf (2016).

Wickramasinghe, K. et al. Childhood overweight and obesity abatement policies in Europe. Obes. Rev. 22 , e13300 (2021).

Department of Health. A healthy weight for Ireland: Obesity Policy and Action Plan 2016–2025. gov.ie assets.gov.ie/10073/ccbd6325268b48da80b8a9e5421a9eae.pdf (2016).

Ministry of Solidarity and Health. National Health Nutrition Program 2019–2023 (PNNS) (Ministry of Solidarity and Health, 2019).

Fortin-Miller, S., Plonka, B., Gibbs, H., Christifano, D. & Hull, H. Prenatal interventions and the development of childhood obesity. Pediatr. Obes. 18 , e12981 (2023).

Johnson, L. G., Cho, H., Lawrence, S. M. & Keenan, G. M. Early childhood (1–5 years) obesity prevention: a systematic review of family-based multicomponent behavioral interventions. Prev. Med. 181 , 107918 (2024).

Feng, J., Zheng, C., Sit, C. H.-P., Reilly, J. J. & Huang, W. Y. Associations between meeting 24-hour movement guidelines and health in the early years: a systematic review and meta-analysis. J. Sports Sci. 39 , 2545–2557 (2021).

Asghari, G., Mirmiran, P., Yuzbashian, E. & Azizi, F. A systematic review of diet quality indices in relation to obesity. Br. J. Nutr. 117 , 1055–1065 (2017).

Boushey, C. et al. Dietary patterns and growth, size, body composition, and/or risk of overweight or obesity: a systematic review. USDA www.ncbi.nlm.nih.gov/books/NBK577644/pdf/Bookshelf_NBK577644.pdf (2020).

Vandenbroeck, I. P., Goossens, J. & Clemens, M. Foresight. Tackling obesities: future choices – building the obesity system map. Government Office for Science assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/295154/07-1179-obesity-building-system-map.pdf (2007).

Jayasinghe, S. et al. Domains of capacity building in whole-systems approaches to prevent obesity – a “systematized” review. Int. J. Environ. Res. Public. Health 19 , 10337 (2022).

Li, B. et al. Comprehensive application of a systems approach to obesity prevention: a scoping review of empirical evidence. Front. Public. Health 11 , 1015492 (2023).

Garner, C. D. et al. Discontinuity of breastfeeding care: “There’s no captain of the ship”. Breastfeed. Med. 11 , 32–39 (2016).

Love, P., Laws, R., Adam, M., Esdaile, E. & Campbell, K. J. A call for joined-up action to promote nutrition across the first 2000 days of life using a food systems approach. Public. Health Res. Pract. 32 , e3232226 (2022).

Nader, P. R. et al. Next steps in obesity prevention: altering early life systems to support healthy parents, infants, and toddlers. Child. Obes. 8 , 195–204 (2012).

Bouyé, M., Harmeling, S. & Schulz, N.-S. Connecting the dots: Elements for a joined-up implementation of the 2030 Agenda and Paris Agreement. World Resources Institute files.wri.org/d8/s3fs-public/connecting-the-dots.pdf (2018).

Bouvet, F., Porteaud, D. & Ramos, M. Delivering humanitarian water, sanitation and hygiene (WASH) at scale, anywhere and any time: road map for 2020–2025. UNICEF www.washroadmap.org/uploads/1/3/8/8/138810292/road_map_2025_english_1.pdf (2020).

Clean Air Fund. Joined-up action on air pollution and climate change. Clean Air Fund s40026.pcdn.co/wp-content/uploads/Joined-up_Action_on_Air_Pollution_and_Climate_Change-compressed-1.pdf (2021).

Blackshaw, J., Montel, S., King, S., Jarvis, A. & Valabhji, J. Report of the working group into: Joined up clinical pathways for obesity. NHS England www.england.nhs.uk/wp-content/uploads/2014/03/owg-join-clinc-path.pdf (2014).

Lawrence, S. E. et al. Family-based weight stigma and psychosocial health: a multinational comparison. Obesity 31 , 1666–1677 (2023).

Bentley, F., Swift, J. A., Cook, R. & Redsell, S. A. I would rather be told than not know” – a qualitative study exploring parental views on identifying the future risk of childhood overweight and obesity during infancy. BMC Public. Health 17 , 684 (2017).

Abdin, S., Heath, G. & Welch, R. K. Health professionals’ views and experiences of discussing weight with children and their families: a systematic review of qualitative research. Child. Care Health Dev. 47 , 562–574 (2021).

Auckburally, S., Davies, E. & Logue, J. The use of effective language and communication in the management of obesity: the challenge for healthcare professionals. Curr. Obes. Rep. 10 , 274–281 (2021).

Tandon, P. S. et al. The relationship between physical activity and diet and young children’s cognitive development: a systematic review. Prev. Med. Rep. 3 , 379–390 (2016).

Wassenaar, T. M. et al. A critical evaluation of systematic reviews assessing the effect of chronic physical activity on academic achievement, cognition and the brain in children and adolescents: a systematic review. Int. J. Behav. Nutr. Phys. Act. 17 , 79 (2020).

Penney, T. L. & Kirk, S. F. L. The health at every size paradigm and obesity: missing empirical evidence may help push the reframing obesity debate forward. Am. J. Public. Health 105 , e38–e42 (2015).

Cole, T. J., Bellizzi, M. C., Flegal, K. M. & Dietz, W. H. Establishing a standard definition for child overweight and obesity worldwide: international survey. BMJ 320 , 1240 (2000).

Download references

Acknowledgements

K.D.H. is supported by a Heart Foundation Future Leader Fellowship (105929). M.Z. is supported by a National Health Medical Research Council Early Career Fellowship (GNT1124283).

Author information

Authors and affiliations.

Institute for Physical Activity and Nutrition, Faculty of Health, Deakin University, Geelong, Victoria, Australia

Kylie D. Hesketh, Miaobing Zheng & Karen J. Campbell

You can also search for this author in PubMed   Google Scholar

Contributions

The authors contributed equally to all aspects of the article.

Corresponding author

Correspondence to Kylie D. Hesketh .

Ethics declarations

Competing interests.

The authors declare no competing interests.

Peer review

Peer review information.

Nature Reviews Endocrinology thanks Luis Moreno and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Related links

CDC’s Developmental Milestones: https://www.cdc.gov/ncbddd/actearly/milestones/index.html

Developmental Milestones: Birth to 5 years: https://med.stanford.edu/content/dam/sm/pediatricsclerkship/documents/5-Developmental-Milestones-MedU.pdf

WHO Child Growth Standards: Training Course on Child Growth Assessment: https://www.who.int/publications/i/item/9789241595070

WHO Global Health Observatory data repository, BMI anthropometry: https://apps.who.int/gho/data/node.main.BMIANTHROPOMETRY?lang = en

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Cite this article.

Hesketh, K.D., Zheng, M. & Campbell, K.J. Early life factors that affect obesity and the need for complex solutions. Nat Rev Endocrinol (2024). https://doi.org/10.1038/s41574-024-01035-2

Download citation

Accepted : 27 August 2024

Published : 23 September 2024

DOI : https://doi.org/10.1038/s41574-024-01035-2

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

Quick links

  • Explore articles by subject
  • Guide to authors
  • Editorial policies

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

childhood obesity research

  • Funding Opportunities

childhood obesity research

  • Create Thriving, Activity-Friendly Communities
  • Measures Registry Resource Suite
  • A Guide to Methods for Assessing Childhood Obesity
  • A Toolkit for Evaluating Childhood Healthy Weight Programs
  • Youth Compendium of Physical Activities
  • Catalogue of Surveillance Systems
  • Childhood Obesity Evidence Base (COEB): Test of a Novel Taxonomic Meta-Analytic Method

Never miss a newsletter

We are social.

Check us out on Facebook, LinkedIn, Twitter and YouTube

  • Download PDF
  • Share X Facebook Email LinkedIn
  • Permissions

Childhood Overweight and Obesity During and After the COVID-19 Pandemic

  • 1 Child and Health Parenting (CHAP), Department of Public Health and Caring Sciences, Uppsala University, Uppsala, Sweden
  • 2 Institute of Clinical Sciences, Department of Paediatrics, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden

Excessive childhood weight gain has been associated with the COVID-19 pandemic globally, attributed to its negative effects on diet and physical activity caused by social restrictions and reduced access to preschools. 1 Children from low socioeconomic backgrounds and with preexisting overweight were particularly affected. Childhood obesity increases the risk of obesity in adulthood, with greater risk of cardiovascular diseases, cancer, and lower quality of life. 2

Read More About

Fäldt A , Nejat S , Durbeej N , Holmgren A. Childhood Overweight and Obesity During and After the COVID-19 Pandemic. JAMA Pediatr. 2024;178(5):498–500. doi:10.1001/jamapediatrics.2024.0122

Manage citations:

© 2024

Artificial Intelligence Resource Center

Pediatrics in JAMA : Read the Latest

Browse and subscribe to JAMA Network podcasts!

Others Also Liked

Select your interests.

Customize your JAMA Network experience by selecting one or more topics from the list below.

  • Academic Medicine
  • Acid Base, Electrolytes, Fluids
  • Allergy and Clinical Immunology
  • American Indian or Alaska Natives
  • Anesthesiology
  • Anticoagulation
  • Art and Images in Psychiatry
  • Artificial Intelligence
  • Assisted Reproduction
  • Bleeding and Transfusion
  • Caring for the Critically Ill Patient
  • Challenges in Clinical Electrocardiography
  • Climate and Health
  • Climate Change
  • Clinical Challenge
  • Clinical Decision Support
  • Clinical Implications of Basic Neuroscience
  • Clinical Pharmacy and Pharmacology
  • Complementary and Alternative Medicine
  • Consensus Statements
  • Coronavirus (COVID-19)
  • Critical Care Medicine
  • Cultural Competency
  • Dental Medicine
  • Dermatology
  • Diabetes and Endocrinology
  • Diagnostic Test Interpretation
  • Drug Development
  • Electronic Health Records
  • Emergency Medicine
  • End of Life, Hospice, Palliative Care
  • Environmental Health
  • Equity, Diversity, and Inclusion
  • Facial Plastic Surgery
  • Gastroenterology and Hepatology
  • Genetics and Genomics
  • Genomics and Precision Health
  • Global Health
  • Guide to Statistics and Methods
  • Hair Disorders
  • Health Care Delivery Models
  • Health Care Economics, Insurance, Payment
  • Health Care Quality
  • Health Care Reform
  • Health Care Safety
  • Health Care Workforce
  • Health Disparities
  • Health Inequities
  • Health Policy
  • Health Systems Science
  • History of Medicine
  • Hypertension
  • Images in Neurology
  • Implementation Science
  • Infectious Diseases
  • Innovations in Health Care Delivery
  • JAMA Infographic
  • Law and Medicine
  • Leading Change
  • Less is More
  • LGBTQIA Medicine
  • Lifestyle Behaviors
  • Medical Coding
  • Medical Devices and Equipment
  • Medical Education
  • Medical Education and Training
  • Medical Journals and Publishing
  • Mobile Health and Telemedicine
  • Narrative Medicine
  • Neuroscience and Psychiatry
  • Notable Notes
  • Nutrition, Obesity, Exercise
  • Obstetrics and Gynecology
  • Occupational Health
  • Ophthalmology
  • Orthopedics
  • Otolaryngology
  • Pain Medicine
  • Palliative Care
  • Pathology and Laboratory Medicine
  • Patient Care
  • Patient Information
  • Performance Improvement
  • Performance Measures
  • Perioperative Care and Consultation
  • Pharmacoeconomics
  • Pharmacoepidemiology
  • Pharmacogenetics
  • Pharmacy and Clinical Pharmacology
  • Physical Medicine and Rehabilitation
  • Physical Therapy
  • Physician Leadership
  • Population Health
  • Primary Care
  • Professional Well-being
  • Professionalism
  • Psychiatry and Behavioral Health
  • Public Health
  • Pulmonary Medicine
  • Regulatory Agencies
  • Reproductive Health
  • Research, Methods, Statistics
  • Resuscitation
  • Rheumatology
  • Risk Management
  • Scientific Discovery and the Future of Medicine
  • Shared Decision Making and Communication
  • Sleep Medicine
  • Sports Medicine
  • Stem Cell Transplantation
  • Substance Use and Addiction Medicine
  • Surgical Innovation
  • Surgical Pearls
  • Teachable Moment
  • Technology and Finance
  • The Art of JAMA
  • The Arts and Medicine
  • The Rational Clinical Examination
  • Tobacco and e-Cigarettes
  • Translational Medicine
  • Trauma and Injury
  • Treatment Adherence
  • Ultrasonography
  • Users' Guide to the Medical Literature
  • Vaccination
  • Venous Thromboembolism
  • Veterans Health
  • Women's Health
  • Workflow and Process
  • Wound Care, Infection, Healing
  • Register for email alerts with links to free full-text articles
  • Access PDFs of free articles
  • Manage your interests
  • Save searches and receive search alerts

Stanford University

Childhood Research in Obesity Prevention - Assistant Program Director

🔍 school of medicine, stanford, california, united states.

The Department of Pediatrics, Division of Gastroenterology, Hepatology and Nutrition and The Childhood Research in Obesity Prevention (CROP) research program at Stanford University is seeking an Assistant Program Director (Academic Program Professional 2, hybrid) to work under the general direction of the program Principal Investigator (PI) to develop, implement, and administer the vision, strategy, and goals of the program. The CROP research program’s goal is to advance child health equity. To achieve this goal, the program seeks to translate clinical, community, and epidemiologic research findings into innovative population-level interventions during pregnancy, infancy, and early childhood to prevent and treat childhood obesity and chronic diseases particularly among health disparity populations. The culture of the program is one that values growth, teamwork, and inclusion. Current research projects are funded by NIH, PCORI, and Foundations amounting to over $20M total costs between 2024-2030 in addition to endowed program funding. These include the Food FARMacia randomized trial of an infant food security intervention; the LINC mixed methods study of social risk factors, navigation, and neighborhoods; and the PCORI-funded CHIME (Comparing Health Interventions for Maternal Equity) program. The CHIME program focused on maternal- infant health equity through a comparative effectiveness research study, broader partnership network, partner learning network, and research mentorship program. This position will also oversee the PCORI-funded CHIME research mentorship program for fellows and early-stage investigators in community based participatory research and implementation science focused on maternal-infant health equity, including development of the curriculum, coordinating meetings, and overseeing the application procedures.

The position will report to the research program PI and will oversee senior research program staff. The Assistant Program Director will participate in program strategy development, long-range planning, and partnership development by overseeing implementation of multiple multi-site research projects to promote food security, nutrition, and reduction of obesity and related chronic diseases starting early in life.

The Assistant Program Director will have documented expertise in nutrition and/or pediatric research, including clinical trials research experience. We are looking for someone who can collaborate with other researchers and external partners. The ability to manage multiple tasks and timelines and community clearly with collaborators will be central to success in this position. Strong analytic and writing skills, as well as the ability to take initiative and complete appropriate tasks independently, are required. Prior experience with managing large research grants and teams is required. Prior experience with assisting in the development and submission of extramural funding (e.g., NIH, CDC, AHRQ, PCORI)] applications is required.

Duties include:

·        Develop and manage research program including multi-site investigator grants and contracts, by conducting research activities, including outreach to varied stakeholders within the program, assigning resources and making program improvement recommendations that impact policies and programs, and completing quarterly, semi-annual, and annual reporting.

·        Collaborate with external projects PIs and stakeholders to ensure successful completion of projects, timely data sharing, and reporting.

·        Identify, recommend and implement opportunities for new research.

·        Source, collect and analyze data, create reports, review and explain trends; formulate and evaluate alternative solutions and/or recommendations to achieve the goals of the program or function. Oversee revisions and trainings on new program policies and procedures.

·        Teach and/or assist in the teaching and administration of research mentorship and career development programs, including oversight of the PCORI-funded CHIME Research Mentorship Program. Develop curriculum and application process. Develop curriculum-rating survey, detailed feedback on courses and make recommendations for preliminary overview and changes.

·        Write and/or edit complex content for proposals, research grants, peer-reviewed publications, and other program activities.

·        Contribute to and inform on strategic program/entity planning and related funding and financial sustainability.

·        . Write and/or edit complex content for proposals, research grants, peer-reviewed publications, and other program activities.

·        Develop or contribute to outreach strategy related to program communications, development, partnerships, and fundraising/funding.

·        Coach and mentor program staff. This includes development and implementation of our annual strategic and team-building retreat.

  • - Other duties may also be assigned

All members of the Department of Pediatrics are engaged in continuous learning and improvement to foster a culture where diversity, equity, inclusion, and justice are central to all aspects of our work. The Department collectively and publicly commits to continuously promoting anti-racism and equity through its policies, programs, and practices at all levels.

Stanford University provides pay ranges representing its good faith estimate of what the University reasonably expects to pay for a position. The pay offered to a selected candidate will be determined based on factors such as (but not limited to) the scope and responsibilities of the position, the qualifications of the selected candidate, departmental budget availability, internal equity, geographic location, and external market pay for comparable jobs. The pay range for this position working in the California Bay area is $95,000. to $139,000.

DESIRED QUALIFICATIONS:

Master’s or PhD degree and three or more years of relevant experience in nutrition and/or pediatrics. Experience with nutrition research, community partnered research, clinical trials research, mixed methods research, and ability to communicate well with community partners, researchers, funders, and philanthropists.

EDUCATION & EXPERIENCE (REQUIRED):

Bachelor's degree and three or more years of relevant experience or combination of education, training, and relevant experience. Advanced degree may be required for some programs. Experience managing a budget and developing financial plans.

KNOWLEDGE, SKILLS AND ABILITIES (REQUIRED):

·        Ability to develop program partnerships and funding sources.

·        Excellent oral, written, and analytical skills, exhibiting fluency in area of specialization.

·        Ability to oversee and direct staff.

·        Basic knowledge of managing budgets and developing financial plans.

CERTIFICATIONS & LICENSES:

PHYSICAL REQUIREMENTS*:

·        Frequently stand/walk, sitting, grasp lightly/fine manipulation, perform desk-based computer tasks.

·        Occasionally use a telephone, writing by hand, lift/carry/push/pull objects that weigh up to 40 pounds.

·        Rarely sort/file paperwork or parts, lift/carry/push/pull objects that weigh >40 pounds.

·        Ability to use voice to present information/communicate with others.

·        On-campus mobility.

* - Consistent with its obligations under the law, the University will provide reasonable accommodation to any employee with a disability who requires accommodation to perform the essential functions of his or her job.

WORKING CONDITIONS:

·        May work extended hours, evenings or weekends.

·        May travel locally.

Occasional overnight travel.

  • Schedule: Full-time
  • Job Code: 4112
  • Employee Status: Regular
  • Department URL: http://pediatrics.stanford.edu/
  • Requisition ID: 104651
  • Work Arrangement : Hybrid Eligible

My Submissions

Track your opportunities.

Similar Listings

 School of Medicine, Stanford, California, United States

📁 Administration

Post Date: Sep 11, 2024

Post Date: Sep 06, 2023

Post Date: Apr 22, 2024

Global Impact We believe in having a global impact

Climate and sustainability.

Stanford's deep commitment to sustainability practices has earned us a Platinum rating and inspired a new school aimed at tackling climate change.

Medical Innovations

Stanford's Innovative Medicines Accelerator is currently focused entirely on helping faculty generate and test new medicines that can slow the spread of COVID-19.

From Google and PayPal to Netflix and Snapchat, Stanford has housed some of the most celebrated innovations in Silicon Valley.

Advancing Education

Through rigorous research, model training programs and partnerships with educators worldwide, Stanford is pursuing equitable, accessible and effective learning for all.

Working Here We believe you matter as much as the work

Group Dance Class In A Gym

I love that Stanford is supportive of learning, and as an education institution, that pursuit of knowledge extends to staff members through professional development, wellness, financial planning and staff affinity groups.

School of Engineering

Students Working With A Robot Arm

I get to apply my real-world experiences in a setting that welcomes diversity in thinking and offers support in applying new methods. In my short time at Stanford, I've been able to streamline processes that provide better and faster information to our students.

Phillip Cheng

Office of the Vice Provost for Student Affairs

Students Working With A Robot Arm

Besides its contributions to science, health, and medicine, Stanford is also the home of pioneers across disciplines. Joining Stanford has been a great way to contribute to our society by supporting emerging leaders.

Denisha Clark

School of Medicine

Students Working With A Robot Arm

I like working in a place where ideas matter. Working at Stanford means being part of a vibrant, international culture in addition to getting to do meaningful work.

Office of the President and Provost

Getting Started We believe that you can love your job

Join Stanford in shaping a better tomorrow for your community, humanity and the planet we call home.

  • 4.2 Review Ratings
  • 81% Recommend to a Friend

View All Jobs

  • Alzheimer's disease & dementia
  • Arthritis & Rheumatism
  • Attention deficit disorders
  • Autism spectrum disorders
  • Biomedical technology
  • Diseases, Conditions, Syndromes
  • Endocrinology & Metabolism
  • Gastroenterology
  • Gerontology & Geriatrics
  • Health informatics
  • Inflammatory disorders
  • Medical economics
  • Medical research
  • Medications
  • Neuroscience
  • Obstetrics & gynaecology
  • Oncology & Cancer
  • Ophthalmology
  • Overweight & Obesity
  • Parkinson's & Movement disorders
  • Psychology & Psychiatry
  • Radiology & Imaging
  • Sleep disorders
  • Sports medicine & Kinesiology
  • Vaccination
  • Breast cancer
  • Cardiovascular disease
  • Chronic obstructive pulmonary disease
  • Colon cancer
  • Coronary artery disease
  • Heart attack
  • Heart disease
  • High blood pressure
  • Kidney disease
  • Lung cancer
  • Multiple sclerosis
  • Myocardial infarction
  • Ovarian cancer
  • Post traumatic stress disorder
  • Rheumatoid arthritis
  • Schizophrenia
  • Skin cancer
  • Type 2 diabetes
  • Full List »

share this!

September 24, 2024

This article has been reviewed according to Science X's editorial process and policies . Editors have highlighted the following attributes while ensuring the content's credibility:

fact-checked

peer-reviewed publication

trusted source

Research suggests obesity in moms doubles the risk of autism in babies

by University of South Australia

baby

Children born to mothers with obesity both before and during pregnancy have an increased risk of neuropsychiatric and behavioral conditions, including autism spectrum disorder (ASD), and attention deficit hyperactivity disorder (ADHD), according to new research from the University of South Australia.

The paper is published in the journal Psychiatry Research .

Conducted in partnership with Curtin University, Monash University, SAHMRI and a team of national institutions, the systematic review and meta-analysis of more than 3.6 million mother-child pairs across 42 epidemiological studies found that obesity during pregnancy:

  • increases the risk of ADHD in children by 32%
  • doubles the risk of developing ASD in children (by 2.23 times)
  • increases the risk of conduct disorders by 16%

The study also found that maternal pre-conception obesity or overweight was linked with an increased risk of ADHD, ASD, conduct disorder and psychotic disorder as well as a 30% increased risk in both externalizing symptoms, and peer relationship problems.

Lead researcher UniSA's Dr. Bereket Duko says the study provides new insights into the long-term impact of maternal body weight on child mental health.

"Maternal obesity has long been associated with a range of adverse perinatal outcomes, including preterm birth , low birthweight, stillbirth, and it is also linked with macrosomia, or high birthweight," Dr. Duko says.

"In this study, we examined maternal overweight and obesity before and during pregnancy, finding that both are significantly linked with psychiatric and behavioral problems in children later in life, specifically ASD, ADHD and peer relationship problems.

"Given the rising global obesity rates among women of reproductive age, and the growing numbers of children identified with neurodiverse conditions, it's important that we acknowledge the potential long-term consequences of maternal adiposity on child mental health."

In Australia, about one in 150 people have ASD with more than 8% of children aged 4–11 diagnosed with ADHD. Globally, one in eight people live with obesity .

Dr. Duko says the study's results underscore the need for interventions targeting maternal weight management before and during pregnancy.

"Public health efforts that target improving maternal health could help mitigate some of the risks of neuropsychiatric and behavioral disorders in children," Dr. Duko says.

"While further research is needed to explore the biological mechanisms underlying these associations, the findings do stress the need for health interventions that promote healthy living and weight among parents-to-be."

Explore further

Feedback to editors

childhood obesity research

How male hormones regulate skeletal muscle function

2 minutes ago

childhood obesity research

Psychedelic experience improves therapists' ability to deliver ketamine therapy, suggests study

8 minutes ago

childhood obesity research

Air pollution exposure during early life can have lasting effects on the brain's white matter

25 minutes ago

childhood obesity research

Baby chicks study sheds light on the brain's innate ability to recognize faces

36 minutes ago

childhood obesity research

Popular diabetes and weight-loss drug associated with lower opioid overdose risk

childhood obesity research

Higher doses of buprenorphine may improve treatment outcomes for people with opioid use disorder

childhood obesity research

Study reveals why children with Down syndrome have higher risk of leukemia

childhood obesity research

Encoding human experience: Study reveals how brain cells compute the flow of time

childhood obesity research

Soil and water pollution: An invisible threat to cardiovascular health

childhood obesity research

Researchers create mouse model to mimic Parkinson's disease

Related stories.

childhood obesity research

Smoking while pregnant risks academic achievement of unborn babies, says study

Aug 27, 2024

childhood obesity research

Pregnant women with obesity and diabetes may be more likely to have a child with ADHD

Sep 8, 2022

childhood obesity research

Prenatal ozone: A silent culprit in the battle against childhood obesity

Jul 10, 2024

childhood obesity research

Diet and exercise for obese mothers could lower cardiovascular risk in children

Jul 9, 2024

childhood obesity research

Women with obesity prior to conception are more likely to have children with obesity

Jun 11, 2019

childhood obesity research

Maternal obesity linked to ADHD and behavioral problems in children, study suggests

Feb 19, 2020

Recommended for you

childhood obesity research

Pandemic-era babies do not have higher autism risk, finds study

Sep 23, 2024

childhood obesity research

Why teens with autism struggle with non-verbal cues

Sep 16, 2024

childhood obesity research

Dyslexia and ADHD share genetic links, study shows

Sep 10, 2024

childhood obesity research

Study debunks theory linking autism to changes in brain's amygdala

Sep 4, 2024

childhood obesity research

Eating fish, not omega-3 supplements during pregnancy associated with lower likelihood of autism diagnosis

Sep 3, 2024

childhood obesity research

Collaborative research cracks the autism code, making the neurodivergent brain visible

Aug 28, 2024

Let us know if there is a problem with our content

Use this form if you have come across a typo, inaccuracy or would like to send an edit request for the content on this page. For general inquiries, please use our contact form . For general feedback, use the public comments section below (please adhere to guidelines ).

Please select the most appropriate category to facilitate processing of your request

Thank you for taking time to provide your feedback to the editors.

Your feedback is important to us. However, we do not guarantee individual replies due to the high volume of messages.

E-mail the story

Your email address is used only to let the recipient know who sent the email. Neither your address nor the recipient's address will be used for any other purpose. The information you enter will appear in your e-mail message and is not retained by Medical Xpress in any form.

Newsletter sign up

Get weekly and/or daily updates delivered to your inbox. You can unsubscribe at any time and we'll never share your details to third parties.

More information Privacy policy

Donate and enjoy an ad-free experience

We keep our content available to everyone. Consider supporting Science X's mission by getting a premium account.

E-mail newsletter

  • Allergy & Immunology
  • Dermatology
  • Flagship Journal
  • Gastroenterology
  • General Healthcare
  • Innovations
  • Interventional Cardiology
  • Microbiology & Infectious Diseases
  • Reproductive Health
  • Respiratory
  • Rheumatology
  • EMJ Media Pack
  • AMJ Media Pack
  • Editorial Enquiries
  • Contributors & Authors
  • Submit a Paper
  • Media Partners
  • Pharma Partners
  • Subscribe to EMJ GOLD
  • Subscribe to EMJ

Childhood Obesity’s Unexpected Impact on Skin

childhood obesity research

A STRONG link between childhood obesity and the development of immune-mediated skin diseases (IMSDs), such as alopecia areata, atopic dermatitis, and psoriasis, has been highlighted in new research.

Researchers found that obese children were significantly more likely to develop these common skin conditions compared to their normal-weight peers. Among the IMSDs studied, atopic dermatitis showed the most pronounced association with weight changes: children who gained weight (from normal to overweight) had a higher risk of developing the condition, while those who lost weight (from overweight to normal) had a reduced risk. The study analyzed data from 2.16 million Korean children from 2009 to 2020, making it one of the largest studies of its kind.

Co-lead investigator Seong Rae Kim from Seoul National University College of Medicine, South Korea, noted, “Many previous studies have examined the link between childhood obesity and IMSDs, but our long-term approach with a large sample size allows for a better understanding of how body weight changes over time affect the development of these diseases.”

The study underscores the importance of weight management in children, not only for overall health but also to reduce the risk of chronic skin conditions that impact quality of life. Despite advancements in biologic treatments, there are still limited options for managing these conditions in children, making prevention through weight maintenance and healthy lifestyle choices crucial.

Hyunsun Park, another co-lead investigator, emphasized the role of diet and lifestyle in influencing both gut health and skin conditions, suggesting a complex interplay between obesity and immune function. “Our findings suggest that preventing excessive weight gain and encouraging purposeful weight loss in children, especially before school age, can reduce the risk of developing atopic dermatitis and other IMSDs,” said Park. This research supports the need for targeted interventions to promote healthy weight and potentially prevent debilitating skin diseases in children.

Reference: Kim SR et al. Childhood obesity, weight change, and pediatric immune-mediated skin diseases. JID Innov. 2024;144(9):1984.e10.

Anaya Malik | AMJ

Rate this content's potential impact on patient outcomes

Please share some more information on the rating you have given

Related To This Subject

childhood obesity research

Skin Cancer Trends: Unravelling Melanoma Patterns

childhood obesity research

Psoriasis Linked to Increased Risk of Lung and Breast Cancer

More articles.

childhood obesity research

Clinical Practice Insights for Hyperpigmentation Treatment

childhood obesity research

Reviewing Non-Scarring Alopecia in Women

childhood obesity research

Dermatitis Artefacta Treatment

Featured journals.

childhood obesity research

AMJ Dermatology 1.1 2024

childhood obesity research

EMJ Dermatology 12 [Supplement 1] 2024

  • Skip to main menu
  • Skip to user menu

Childhood Research in Obesity Prevention - Assistant Program Director

Stanford University

Job Details

Organization.

Occasional overnight travel.

  • Schedule: Full-time
  • Job Code: 4112
  • Employee Status: Regular
  • Department URL: http://pediatrics.stanford.edu/
  • Requisition ID: 104651
  • Work Arrangement : Hybrid Eligible

Change the world. And yourself.

Stanford University has changed the world, over and over again.

We are one of Silicon Valley's largest employers - and also one of the most unique. Our mission is to educate future leaders and promote interdisciplinary, world-class research and teaching. This passion makes Stanford an intensely creative, rewarding, and challenging place to work. At the same time, our traditions of respect and collaboration sustain a humane, supportive environment in which to pursue your life and your career. 

At Stanford you'll work with bright, diverse, dedicated people. You'll find encouragement to learn and grow. You'll enjoy excellent benefits and an outstanding environment.

Stanford Facts at a Glance

Opened 1891

Student Enrollment

  • Undergraduates: 6,980
  • Graduates: 8,897
  • 8,180 contiguous acres in six governmental jurisdictions
  • Nearly 700 major buildings
  • 97% of undergraduates live on campus
  • 5,300 externally sponsored projects
  • $1.33 billion total budget
  • 2,043 faculty members
  • 21 Nobel laureates are currently members of the Stanford community
  • 5:1 student to faculty ratio

Stanford University is an Equal Employment Opportunity and Affirmative Action Employer and is committed to recruiting and hiring qualified women, minorities, protected veterans and persons with disabilities.

Share this job

Get job alerts

Create a job alert and receive personalized job recommendations straight to your inbox.

Before you apply - Turn on alerts for jobs like this!

We'll send them straight to your inbox :

When you create this job alert we will email you a selection of jobs matching your criteria. Our terms and conditions and privacy policy apply to this service and you can unsubscribe at any time.

By clicking to continue to apply below, your email address will be shared with the employer.

Extra nutrients during pregnancy may reduce childhood obesity risk

  • 31 January 2024

Taking a nutritional supplement before and during pregnancy could promote healthy weight in childhood, an NIHR-supported study has found.

The research is part of the international NiPPeR study . The study is a collaboration between the NIHR Southampton Biomedical Research Centre (BRC), the University of Southampton, the Liggins Institute at the University of Auckland, the National University of Singapore and the Agency for Science, Technology and Research (A*STAR) in Singapore.

How the study worked

Rates of childhood obesity are rising in many countries, particularly in less advantaged groups. Obesity increases the risk of many health diseases. These include type 2 diabetes, heart disease and some types of cancer.

Around 500 women from the UK, New Zealand and Singapore took part in this study. They were randomly allocated to two groups.

One group received an enriched supplement - including vitamins B2, B6, B12, D, probiotics and myoinositol - alongside a standard pregnancy supplement.

The other group received a standard pregnancy supplement alone. Neither the women nor their medical teams knew which group they were in.

The researchers checked in on the children when they were two years old. There were half as many obese children in the cohort whose mothers were in the enriched group (9% versus 18%). These children were almost 25% less likely to have experienced “rapid weight gain”, which often leads to obesity.

The new analysis by researchers in the UK, New Zealand and Singapore has been published in BMC Medicine .

A ‘special opportunity’

Professor Keith Godfrey from the University of Southampton (UoS) and the NIHR Southampton BRC is the study’s Chief Investigator. He said: “Preventing obesity is one of the most important things we can do, as treating obesity is much more difficult. The new findings suggest the period before and during pregnancy may provide a ‘special opportunity’. Supporting better nutritional status for the mother at this time could have lasting benefits for her child.”

Professor Wayne Cutfield is a professor of paediatric endocrinology at the Liggins Institute in Auckland, and one of the leaders of the research. He said: “In a world of obesity, our data suggests supplementing mums before and during pregnancy can have benefits way beyond the pregnancy and for the women involved. It can impact their baby into childhood and potentially beyond.”

Professor Marian Knight, NIHR Scientific Director for Infrastructure said: "These latest findings are a step towards beginning to understand and prevent childhood obesity. Pioneering nutrition, lifestyle and metabolism research is at the heart of our NIHR Southampton Biomedical Research Centre. Working closely with global partners, the aim of this ambitious study is to continue making discoveries that will help give every child the best start in life.”

Future research

The enhanced supplement contained seven additional micronutrients.

More research is needed to identify which of the nutrients in the supplement are most beneficial. Any of them - or a combination - could have impacted the metabolism and development of the children and the likelihood of obesity.

Professor Cutfield said: “We do not yet know the precise mechanism, but there’s evidence some of the micronutrients are associated with body metabolism in pregnancy. We have started analysing the data and we hope to be able to drill down into which component or components are most critical.”

Associate Professor Shiao Yng Chan from the National University of Singapore was a co-author on the paper. She says the effects of a mother's nutrition during pregnancy might not show in the baby right away.

“As the child grows, the things that happened in the baby's body while in the womb become apparent. These early events, sometimes called ‘foetal programming’, can influence how the child reacts to an unhealthy lifestyle, like eating lots of fatty foods and not getting enough exercise. This can make some children more likely to become overweight."

Read the full paper in BMC Medicine .

Share this page

Latest news.

childhood obesity research

NIHR takes on management of Better Methods for Better Research Programme

childhood obesity research

New findings on the use of molnupiravir to treat COVID-19

childhood obesity research

New funding opportunities for novel brain tumour research launched

Warning: The NCBI web site requires JavaScript to function. more...

U.S. flag

An official website of the United States government

The .gov means it's official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you're on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

  • Publications
  • Account settings
  • Browse Titles

NCBI Bookshelf. A service of the National Library of Medicine, National Institutes of Health.

StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2024 Jan-.

Cover of StatPearls

StatPearls [Internet].

Obesity effects on child health.

Palanikumar Balasundaram ; Sunil Krishna .

Affiliations

Last Update: April 10, 2023 .

  • Continuing Education Activity

Obesity in childhood is the most challenging public health issue in the twenty-first century. Childhood obesity is associated with increased morbidity and premature death. Prevention of obesity in children is a high priority in the current situation. This activity reviews the etiology, pathophysiology, and consequence of childhood obesity and also highlights the role of the interprofessional team in the prevention and management of childhood obesity.

  • Outline the definition of childhood obesity.
  • Describe the etiology and pathophysiology of childhood obesity.
  • Summarize the consequences of childhood obesity.
  • Explain how interprofessional teamwork can improve effective management interventions for childhood obesity.
  • Introduction

Obesity in childhood is the most challenging public health issue in the twenty-first century. It has emerged as a pandemic health problem worldwide. The children who are obese tend to stay obese in adulthood and prone to increased risk for diabetes and cardiac problems at a younger age. Childhood obesity is associated with increased morbidity and premature death. [1] Prevention of obesity in children is a high priority in the current situation.

Epidemiology

The prevalence of childhood obesity has alarmingly increased. The overall burden of obesity has almost tripled since 1975. However, an eightfold increase in obesity burden in the 5 to 19 years age group has been noted between 1975 and 2016. [2] Though childhood obesity is more prevalent in developed countries, the prevalence is increasing even in developing countries. [3] Currently, about 18.5% of US children present with obesity. Among boys, obesity is more prevalent in the school-age group (6 to 11 years), whereas in girls, it is more prevalent in adolescents (12 to 19 years). The prevalence of childhood obesity among boys and girls was not significantly different overall or by age groups. [4]

The word obesity infers the deposition of excessive fat in the body. Different methods can directly measure body fat like skinfold thickness, hydro densitometry, bioelectrical impedance, and air displacement plethysmography. [5] These methods are not readily available in the clinical setting and are expensive. Body mass index (BMI) provides an economical method to assess body fat indirectly. BMI is measured using a formula [BMI = weight (kg)/ height (m)^2]. [6] [7] As growth in children varies with age and sex, so do the norms for BMI. The following definitions are used to classify weight status based on BMI for children from 2 to 20 years of age. [8] [9]

  • Overweight – 85th to less than the 95th percentile.
  • Obese (class 1) – 95th percentile or greater
  • Severe (class II) obesity – ≥ 120% of 95th percentile (99th percentile) or ≥ 35 kg/m^2 (whichever is lower)
  • Class III obesity is a subcategory of severe obesity and is defined as BMI ≥140 % of 95th percentile or ≥ 40 kg/m^2. 

The World Health Organization (WHO) recommends using BMI Z-score cut-offs of >1, > 2, and > 3 to define at risk of overweight, overweight, and obesity, respectively. [7] Z-score is measured in terms of standard deviations from the mean.

  • Issues of Concern

Etiology and Pathophysiology

The complex interaction of individual and environmental factors plays a crucial role in developing obesity. The most important factors contributing to childhood obesity are summarized below. 

Environmental Factors

Changes in the environment in the past few decades in terms of easy access/ affordability of high-calorie fast food, increased portion size, increased intake of sugary beverages, and sedentary lifestyles are associated with increased incidence of obesity. [10] Increasing use of electronic devices [television, tablets, smartphone, videogames] by children has led to limited physical activity, disruption of the sleep-wake cycle, depression of metabolic rate, and poor eating patterns. [11]

Feeding patterns in infancy have a long-term effect on developing obesity later on in life. It has been shown that breastfeeding in the first year of life is inversely associated with weight gain and obesity. [12] This association was much more significant if the child was exclusively breastfed compared to having added formula or solid food. Despite concerns about the risk for obesity in preterm and SGA infants receiving calorie and protein supplementation, it has been shown to improve catch-up growth without increasing the risk of obesity. [13] High protein intake in the initial two years of life has also been postulated to increase weight gain later in childhood. 

Biological Factors

There is a complex interaction between the neural, hormonal, and gut-brain axis affecting hunger and satiety. Hypothalamus regulates appetite and is influenced by key hormones, ghrelin, and leptin. Ghrelin is released from the stomach and stimulates hunger (orexigenic), whereas leptin is mainly secreted from adipose tissue and suppresses appetite (anorexigenic). Several other hormones like neuropeptide Y and agouti-related peptide stimulate hunger, while pro-melanocortin and α-melanocyte-stimulating hormone suppress hunger. [14] These hormones control energy balance by stimulating the hunger and satiety centers in the arcuate nucleus of the hypothalamus through various signaling pathways. Stress-related psychiatric disorders with associated abnormal sleep-wake cycles can also lead to increased ghrelin levels and, in turn, increase appetite.

The gut microbiome includes the trillions of microorganisms that inhabit the human gut. Alterations in the gut microbiome can lead to weight gain through numerous pathways. [15] The dominant gut florae are Firmicutes and Bacteroidetes (90%), Proteobacteria , Actinobacteria , and Fusobacteria . These bacteria have a symbiotic relationship with their host. They can be affected by various factors, such as gestational age at birth, premature rupture of membranes, mode of delivery of the infant, type of feeding, feeding practices, and antibiotics usage. The maturation of gut flora occurs from birth to adulthood and is determined by various genetic factors, diet, lifestyle, and environment. Gut microbiota helps maintain the mucosal barrier, nutrient digestion (especially the synthesis of short-chain fatty acids), and immune response against pathogens. The imbalance of the gut microbiome (dysbiosis), leading to increased production of short-chain fatty acids, has been linked to developing obesity and other medical conditions, such as type 2 Diabetes Mellitus, Metabolic syndrome, anxiety, and depression. [16]

Genetic Factors

Obesity can be either monogenic, syndromic, or polygenic types. Monogenic obesity is uncommon, occurring in 3% to 5% of obese children. [17] Mutations in genes for leptin, leptin receptor, proopiomelanocortin, and melanocortin-4 receptor can lead to obesity. Monogenic type presents in early childhood with unusual feeding behaviors and severe obesity.

Genetic syndromes causing severe obesity include

  • Prader Willi syndrome:  Early growth faltering followed by hyperphagia and increased weight gain by 2 to 3 years. The mild or moderate cognitive deficit, microcephaly, short stature, hypotonia, almond-shaped eyes, high-arched palate, narrow hands/feet, delayed puberty are common features.
  • Alstrom syndrome:  Blindness, deafness, acanthosis nigricans, chronic nephropathy, type 2 diabetes, cirrhosis, primary hypogonadism in males, and normal cognition are common features in Alstrom syndrome.
  • Bardet Biedl syndrome: Intellectual disability, hypotonia, retinitis pigmentosa, polydactyly, hypogonadism, glucose intolerance, deafness, and renal disease are the features in Bardet Biedl syndrome.
  • Other syndromes include Beckwith-Weideman syndrome and Cohen syndrome.

Polygenic obesity is much more common and is caused by a complex interaction between multiple genetic variants and the environment known as gene-environment interaction (GEI). When a child with genotype variants conferring risk for obesity interacts with various environmental factors predisposing to obesity, there is a tendency for decreased physical activity, increased food intake, and body fat storage. Early life environment starting with maternal nutrition during the prenatal or early postnatal period and early childhood adverse environmental or psychosocial stressors can lead to epigenetic changes leading to obesity.

Endocrine Factors

Endocrine causes constitute less than 1% of cases of obesity in children. [18] It is usually associated with mild to moderate obesity, short stature, or hypogonadism. These include cortisol excess [steroid medications or Cushing syndrome], hypothyroidism, growth hormone deficiency, and pseudohypoparathyroidism.

Medications

Numerous medications can cause weight gain. These include antiepileptics, antidepressants, antipsychotics, diabetes medications [insulin, sulfonylureas, thiazolidinediones], glucocorticoids, progestins, antihistamines [cyproheptadine], alpha-blockers [terazosin], and beta-blockers [propranolol]. Close monitoring for excessive weight gain should be done when any of these medications are used in children.

Endocrine-disrupting chemicals, such as bisphenol A and dichlorodiphenyltrichloroethane, have been hypothesized to predispose to obesity by modulating estrogen receptors and possibly metabolic programming. [19]

Few studies in animal models have proven that obesity can be triggered by infection with adenovirus. However, human studies have found conflicting results.

  • Clinical Significance

Childhood obesity significantly impacts both physical and psychological health. Obesity can lead to severe health conditions, including non-insulin-dependent diabetes, cardiovascular problems, bronchial asthma, obstructive sleep apnea (OSA), hypertension, hepatic steatosis, gastroesophageal reflux (GER), and psychosocial issues. The preventive and therapeutic interventions in childhood obesity are crucial in decreasing the burden of comorbid health conditions.

Metabolic Syndrome

Metabolic syndrome, also named syndrome X, is a cluster of risk factors specific for cardiovascular diseases such as hypertension, glucose intolerance, dyslipidemia, and abdominal obesity that commonly occur in obese children or adolescents. Insulin resistance, hyperinsulinemia, and oxidative stress are the underlying factors contributing to metabolic syndrome. [20]  

Dyslipidemia

Atherogenic dyslipidemia is common in obese children and adolescents. A fasting lipoprotein level needs to be obtained in all children with obesity. Elevated triglycerides (TG) and Free fatty acid (FFA) levels, decreased HDL (high-density lipoprotein) cholesterol levels, and normal or mildly increased serum LDL (low-density lipoprotein) cholesterol levels are common findings in childhood obesity. [21] Hyperinsulinemia and insulin resistance in childhood obesity promotes hepatic delivery of FFA for triglyceride synthesis and sequestration into TG-rich lipoproteins. [22]  

Glucose Intolerance

Childhood obesity quadruples the risk of developing glucose intolerance and non-insulin-dependent diabetes mellitus (NIDDM or Type 2 diabetes). Over 85% of children with NIDDM are either overweight or obese at diagnosis. [23] Acanthosis nigricans is an increased pigmentation and thickness of the skin in intertriginous folds, and it is usually associated with glucose intolerance in children and adolescents. Fasting insulin and glucose should be included in the evaluation of childhood obesity. The risk factors for type 2 non-insulin-dependent diabetes and metabolic syndrome include, 

  • children with BMI 85th to 95th percentile along with,
  • immediate family history of type 2 diabetes 
  • signs of insulin resistance such as acanthosis nigricans, dyslipidemia, hypertension, and polycystic ovarian syndrome.
  • Children with BMI >95th percentile regardless of family history or associated features. [24]  

Hypertension

The most significant risk factor for pediatric hypertension is the high body mass index. One-fourth of obese children can have hypertension. Adipocyte is not only a storage depot for fat but is also an active endocrinological cell. The pro-inflammatory adipokines (leptin, resistin, and IL-6) lead to an increase in sympathetic nervous system (SNS) activation, which preferentially impacts the renal vascular beds. [25] Hypertension risk in childhood obesity can also be explained due to hyperinsulinemia. Hyperinsulinemia causes hypertension through secondary mechanisms such as increased renal sodium retention, increased intracellular free calcium, and increased SNS activity. [26] Dietary therapy, along with exercise, effectively decreases blood pressure. 

Hepatic Steatosis  

Pediatric liver disease is a severe complication of childhood obesity. Obesity-related non-alcoholic fatty liver disease (NAFLD) spectrum includes fatty liver, steatohepatitis, cirrhosis, and hepatocellular carcinoma. [27] Hyperinsulinemia in childhood obesity plays a significant role in contributing to hepatic steatosis. Gradual weight loss with regular exercise and diet with less refined carbohydrates and low-fat help normalize hepatic enzymes and resolve hepatic steatosis. [28]   

Cholelithiasis

The prevalence of cholelithiasis is high among adolescents with obesity, and the association is more robust in girls than in boys. Increased cholesterol synthesis and cholesterol saturation of bile contribute to cholelithiasis among adolescents with obesity. [29] [29]  Cholelithiasis occurs even more frequently with weight reduction. Almost half of the cases of cholecystitis in adolescents may be associated with obesity. 

Overweight or obese children have been observed to have a higher prevalence of asthma and asthma exacerbations. The link between asthma and obesity is mediated through abnormal inflammatory and oxidant stress, chest restriction with airway narrowing, and obesity-related comorbidities such as obstructive sleep apnea and gastroesophageal reflux. [30]  

Idiopathic Intracranial Hypertension 

Idiopathic intracranial hypertension (IIH) is an uncommon disease of childhood and adolescence characterized by increased intracranial pressure without any identifiable cause. Almost half of the children who present with this syndrome may be obese and also have more IIH symptoms at onset. [31]  The disease is characterized by elevated intracranial pressure. IIH presents with headaches and may lead to severe visual impairment or blindness. The potential for visual impairment indicates the need for aggressive treatment of obesity in patients with IIH.

Sleep Apnea

Obesity and overweight are crucial risk factors for obstructive sleep apnea (OSA). Neurocognitive deficits and excessive daytime sleepiness are common among obese children with sleep apnea. [32] Obesity hypoventilation syndrome may represent a long-term consequence of sleep apnea and is associated with a high mortality rate. Aggressive therapy is warranted for obese children with this syndrome. Obesity management such as increased physical activity and a healthy diet are recommended for OSA treatment, as well as surgical procedures, if appropriate. 

Orthopedic Complications

Fractures, musculoskeletal discomfort, and lower extremity malalignment such as Blount disease and slipped capital femoral epiphyses are more common in overweight than non-overweight children and adolescents. [33]  Blount disease is a disorder of the proximal tibial growth plate, which results in progressive bowing of the tibia. Although the prevalence of Blount disease is low, approximately two-thirds of Blount disease patients may be obese. Slipped capital femoral epiphysis occurs due to epiphyseal plate disruption. Between 30% and 50% of patients with slipped capital femoral epiphysis are overweight.  

Polycystic Ovary Disease 

Obesity is frequently associated with polycystic ovary disease (PCOD). Up to 30% of women with PCOD may be obese. Hyperandrogenism and hyperinsulinemia often accompany PCOD. Obesity increases the risk of PCOD through insulin resistance and compensatory hyperinsulinemia, which increases androgen production and decreases sex hormone-binding globulin, thereby increasing the bioavailability of androgen. Adolescents with PCOD are at increased risk for metabolic syndrome and glucose intolerance. Weight loss represents an important therapeutic target in obese adolescents with PCOD.  

Persistence of obesity into adulthood

About 15% to 30% of adults with obesity were also obese in their childhood or adolescence. [34]  The cardiovascular risk factors present in obese children or adolescents usually persist into adulthood. The change in body fat in obese adolescents can be a reasonable mediator contributing to the excess morbidity and mortality in later adulthood. 

Psychosocial impact 

Children with obesity or overweight are more likely to experience low self-esteem and depression during adolescence. Negative psychological experiences trigger emotional eating, leading to an ongoing obesity-depression cycle. Children who are overweight or obese face bullying at school and are excluded from competitive physical activities. Overall, children with obesity have less social interaction and spend more time in sedentary activities. Numerous studies have confirmed the association of childhood obesity with ADHD and anxiety disorders. [35]

Eating Disorders

Children with overweight or obesity have a high prevalence of disordered eating behaviors, increasing the risk of developing eating disorders. The majority of adolescents with restrictive eating disorders report a history of obesity in the past. Binge eating increases the risk of obesity and type 2 diabetes. [36]  Appropriate evaluation for eating disorders should be performed during the treatment planning of childhood obesity. 

Academic Performance 

Children who are obese and have comorbid health problems like diabetes, asthma, or sleep apnea miss school more frequently, thereby affecting their school performance negatively.

  • Enhancing Healthcare Team Outcomes

Prevention is the best intervention to decrease the prevalence of obesity. The pediatrician should explore the risk of obesity and overweight during every clinical visit for all children.  

  • Both bottle-fed and breastfed infants are at risk of overfeeding. However, overfeeding is more prevalent among bottle-fed infants. Exclusive breastfeeding and delayed initiation of solid foods may reduce the future risk of overweight. 
  • Skim milk is a safe replacement for whole milk after two years of age. Parents or caretakers should never use food like sweets for a reward. The entire family should have a balanced diet that comprises less than 30 percent of calories from fat. AAP recommends consuming a variety of vegetables and fruits, whole grains, proteins, low-fat dairies and decreasing the intake of sodium, saturated fats, and refined sugars beginning at the age of two years. [37]
  • An essential step in preventing obesity is reducing sedentary time. Limit the screen time, including television, video games, or mobile, not more than 2 hours per day for more than six-year-old children and not more than 1 hour per day for 2-6 years of age group. AAP strongly recommends not allowing kids less than two years to have screen time. [38]
  • Encourage physical activity for children. Children aged 3 to 5 years should be active throughout the day. Children and adolescents ages 6 to 17 years should be physically active for at least 60 minutes every day. [39]
  • As per CDC, 60% of middle school kids and 70% of high school kids do not meet the standard sleep recommendations. AAP recommends that children aged 1 to 2 years sleep 11 to 14 hours per day, children 3 to 5 years sleep 10 to 13 hours, children 6 to 12 years sleep 9 to 12 hours, and adolescents aged 13 to 18 years should regularly sleep 8 to 10 hours. [40]  Avoiding heavy meals close to bedtime, being physically active throughout the day, and removing electronic devices in the bedroom will help to get better sleep.  

The pediatrician should explore for associated morbidity in all obese children. The detailed assessment in obese children should include assessing cardiac comorbidities, orthopedic complications, and psycho-social complications.

  • Reasonable weight-loss goals should be initially 5 to 10 pounds (2 kg to 4.5 kg) or a rate of 1 to 4 pounds (0.5 to 2 kg) per month.
  • Dietary management:  Dieticians provide dietary prescriptions mentioning the total calories per day and recommended percentage of calories from carbohydrates, protein, and fat. The Traffic Light Plan is one method of providing dietary management. The Traffic Light Plan classifies foods as green (low energy density), yellow (moderate energy density), and red (high energy density). These categories help children in adopting healthier eating patterns.[41] The dietician plays a significant role in guiding the diet plan for the patients.
  • Physical activity:  As per the fitness level, begin the physical activity with the goal of 30 minutes/day in addition to any school activity. Treatment should target gradually increasing the activity to 60 minutes per day. An exercise physiologist, along with the physician, can help the patients to achieve their target physical activity.
  • Behavior modification:  Primary care-based behavioral interventions such as self-monitoring, nutritional education, improvement of eating habits, increasing physical activity, attitude change, and rewards help manage childhood obesity.
  • Family involvement:  Review overall family activity and television viewing patterns and always involve parents in nutrition counseling. Family-based behavioral treatment is the most robust intervention for childhood obesity. [41]
  • Psychotherapy:   Behavioral therapy and Cognitive therapy are commonly used by the psychologist in the management of obesity. Behavioral therapy trains patients to act differently around food, and cognitive therapy trains patients how to change their thoughts and emotions related to food.
  • None of the anorexiant medications are FDA approved for use in childhood obesity. Orlistat is the only FDA-approved medication for use in adolescents. 
  • Surgical procedures like gastric bypass have not been studied sufficiently in children to advise their use. 

An interprofessional team that provides a holistic and integrated approach can help achieve the best possible outcomes. Collaboration, shared decision making, and communication are key elements for a good outcome. Multidisciplinary teams include a primary physician, a dietician, a nurse or nurse practitioner, a clinical exercise physiologist, and a psychologist. The interprofessional team can provide a comprehensive weight loss program that benefits the patients.

  • Review Questions
  • Access free multiple choice questions on this topic.
  • Comment on this article.

Disclosure: Palanikumar Balasundaram declares no relevant financial relationships with ineligible companies.

Disclosure: Sunil Krishna declares no relevant financial relationships with ineligible companies.

This book is distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) ( http://creativecommons.org/licenses/by-nc-nd/4.0/ ), which permits others to distribute the work, provided that the article is not altered or used commercially. You are not required to obtain permission to distribute this article, provided that you credit the author and journal.

  • Cite this Page Balasundaram P, Krishna S. Obesity Effects on Child Health. [Updated 2023 Apr 10]. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2024 Jan-.

In this Page

Bulk download.

  • Bulk download StatPearls data from FTP

Related information

  • PMC PubMed Central citations
  • PubMed Links to PubMed

Similar articles in PubMed

  • The effectiveness of web-based programs on the reduction of childhood obesity in school-aged children: A systematic review. [JBI Libr Syst Rev. 2012] The effectiveness of web-based programs on the reduction of childhood obesity in school-aged children: A systematic review. Antwi F, Fazylova N, Garcon MC, Lopez L, Rubiano R, Slyer JT. JBI Libr Syst Rev. 2012; 10(42 Suppl):1-14.
  • Secular trends in overweight and obesity among Finnish adolescents in 1977-1999. [Int J Obes Relat Metab Disord....] Secular trends in overweight and obesity among Finnish adolescents in 1977-1999. Kautiainen S, Rimpelä A, Vikat A, Virtanen SM. Int J Obes Relat Metab Disord. 2002 Apr; 26(4):544-52.
  • Review Screening and Interventions for Childhood Overweight [ 2005] Review Screening and Interventions for Childhood Overweight Whitlock EP, Williams SB, Gold R, Smith P, Shipman S. 2005 Jul
  • Family Based Prevention of Cardiovascular Disease Risk Factors in Children by Lifestyle Change: The PEP Family Heart Study. [Adv Exp Med Biol. 2019] Family Based Prevention of Cardiovascular Disease Risk Factors in Children by Lifestyle Change: The PEP Family Heart Study. Schwandt P, Haas GM. Adv Exp Med Biol. 2019; 1121:41-55.
  • Review Screening and interventions for childhood overweight: a summary of evidence for the US Preventive Services Task Force. [Pediatrics. 2005] Review Screening and interventions for childhood overweight: a summary of evidence for the US Preventive Services Task Force. Whitlock EP, Williams SB, Gold R, Smith PR, Shipman SA. Pediatrics. 2005 Jul; 116(1):e125-44.

Recent Activity

  • Obesity Effects on Child Health - StatPearls Obesity Effects on Child Health - StatPearls

Your browsing activity is empty.

Activity recording is turned off.

Turn recording back on

Connect with NLM

National Library of Medicine 8600 Rockville Pike Bethesda, MD 20894

Web Policies FOIA HHS Vulnerability Disclosure

Help Accessibility Careers

statistics

COMMENTS

  1. National Collaborative on Childhood Obesity Research

    NCCOR is a network of researchers, funders, and partners who aim to reduce childhood obesity by providing tools, resources, and data for the field. Explore their products, such as the Catalogue of Surveillance Systems, the Measures Registry, and the Youth Compendium of Physical Activities.

  2. Childhood and Adolescent Obesity in the United States: A Public Health

    The association between obesity and other conditions makes it a public health concern for children and adolescents. Due to the increase in the prevalence of obesity among children, a variety of research studies have been conducted to discover what associations and risk factors increase the probability that a child will present with obesity.

  3. Childhood Obesity Facts

    Learn about the prevalence, causes, and consequences of obesity among U.S. children and adolescents. Find out how obesity affects different groups, such as age, race, ethnicity, and income, and how much it costs the health care system.

  4. Childhood obesity research at the NIH: Efforts, gaps, and opportunities

    The childhood obesity research that NIH supports includes studies in pregnancy, infancy, childhood, adolescence, and prevention and treatment approaches in families, schools, and other community settings, as well as in health care settings. The NIH also supports basic behavioral and social science research that is providing insights into ...

  5. Childhood Obesity: An Evidence-Based Approach to Family-Centered Advice

    Future childhood obesity research should evaluate the best methods for educating primary care providers in providing family-centered care and the optimal approaches to delivering this care. Acknowledgments. The authors would like to thank Dr Tom D. Thacher, Mayo Clinic Department of Family Medicine Research Chair, for support of our work. ...

  6. Childhood Obesity Evidence Base Project: A Systematic Review and Meta

    Introduction. Childhood obesity is a major public health challenge, with one in three US children between the ages of 2 and 5 meeting criteria for overweight or obesity. 1 The urgency to reverse the course of childhood obesity has led to significant growth in the scientific literature evaluating childhood obesity interventions. Extant reviews of this research have provided limited guidance ...

  7. Child and adolescent obesity

    The prevalence of child and adolescent obesity has plateaued at high levels in most high-income countries and is increasing in many low-income and middle-income countries. Obesity arises when a ...

  8. The global challenge of childhood obesity and its ...

    The article discusses the global challenge of childhood obesity and its health effects, and the need for prevention and management strategies. It mentions the role of social determinants, environmental factors, and intergenerational effects, but does not directly answer the query about the causes of obesity in kids.

  9. About

    NCCOR is a partnership of four federal agencies that fund and coordinate research to prevent and reduce childhood obesity in America. Learn about NCCOR's missions, goals, projects, accomplishments, and how to subscribe to its newsletter.

  10. Childhood obesity: A review of current and future management ...

    Despite the relative lack of widespread research in comparison to the adult population, newer therapies are being trialled, which should allow a greater availability of treatment options for childhood obesity in the future. This review summarizes the current evidence for the management of obesity in terms of medical and surgical options.

  11. Childhood obesity: a growing pandemic

    The editorial discusses the rising prevalence of obesity among children and adolescents worldwide, especially during the COVID-19 pandemic. It highlights the health consequences, risk factors, and interventions for childhood obesity, as well as the role of social and environmental determinants.

  12. Management for children and adolescents with overweight and obesity: a

    Childhood obesity has emerged as a critical global public health concern. For example, the obesity rate among children under the age of 6 is reported to be 3.6%, whereas for children and ...

  13. Duke Center for Childhood Obesity Research (DCCOR)

    In support of our overarching mission, the center's goals are to: Embrace innovative research strategies and support interdisciplinary collaboration by intentionally seeking out collaborators across different departments.; Discover and deliver effective obesity prevention and treatment to populations of children across the age spectrum from pre-conception through early adulthood by ...

  14. Interventions to prevent obesity in school-aged children 6-18 years: An

    This updated synthesis of obesity prevention interventions for children aged 6-18 years, found a small beneficial impact on child BMI for school-based obesity prevention interventions. A more comprehensive assessment of interventions is required to identify mechanisms of effective interventions to inform future obesity prevention public health policy, which may be particularly salient in for ...

  15. Global Prevalence of Overweight and Obesity in Children and Adolescents

    Early life is a pivotal period for childhood obesity development. 22 Prior analyses have linked preconception and prenatal environmental exposures to childhood obesity, including high maternal prepregnancy BMI, 23 gestational weight gain, 24 gestational diabetes, 25 and maternal smoking, 26 potentially through effects on the environment in ...

  16. Childhood and Adolescent Obesity: A Review

    Definition of Childhood Obesity. Body mass index (BMI) is an inexpensive method to assess body fat and is derived from a formula derived from height and weight in children over 2 years of age (1, 18, 19).Although more sophisticated methods exist that can determine body fat directly, they are costly and not readily available.

  17. PDF Taking Action on Childhood Obesity

    Taking Action on Childhood Obesity Childhood obesity is one of the most serious global public health challenges of the 21st century, affecting every country in the world. In just 40 years the number of school-age children and adolescents with obesity has risen more than 10-fold, from 11 million to 124 million (2016 estimates).1 In addition, an

  18. Early life factors that affect obesity and the need for complex

    Research also revealed that early nutrition and physical activity could influence childhood gut microbiota composition, diversity or function, which might in turn affect obesity development.

  19. Childhood obesity is on the rise, study finds

    Despite national school and community-based efforts to promote healthy behaviors at a young age, childhood obesity is becoming more common in the United States, a recent study found.. The research ...

  20. Tools

    Launched in 2009, the National Collaborative on Childhood Obesity Research (NCCOR) brings together four of the nation's leading research funders — the Centers for Disease Control and Prevention (CDC), the National Institutes of Health (NIH), the Robert Wood Johnson Foundation (RWJF), and the U.S. Department of Agriculture (USDA) — to accelerate progress in reducing childhood obesity in ...

  21. Childhood Obesity Clinical Trials

    Childhood obesity disproportionately affects specific racial and ethnic groups and households with low socioeconomic status and low parental education. The Alternative Learning Center (ALC) within Rochester School District 535 provides viable educational options for students who are experiencing difficulty in regular educational systems.

  22. Childhood Overweight and Obesity During and After COVID-19

    Excessive childhood weight gain has been associated with the COVID-19 pandemic globally, attributed to its negative effects on diet and physical activity caused by social restrictions and reduced access to preschools. 1 Children from low socioeconomic backgrounds and with preexisting overweight were particularly affected. Childhood obesity increases the risk of obesity in adulthood, with ...

  23. Obesity in children and adolescents: epidemiology, causes, assessment

    Introduction. Obesity in children and adolescents is a global health issue with increasing prevalence in low-income and middle-income countries (LMICs) as well as a high prevalence in many high-income countries. 1 Obesity during childhood is likely to continue into adulthood and is associated with cardiometabolic and psychosocial comorbidity as well as premature mortality.2, 3, 4 The provision ...

  24. Childhood Research in Obesity Prevention

    The CROP research program's goal is to advance child health equity. To achieve this goal, the program seeks to translate clinical, community, and epidemiologic research findings into innovative population-level interventions during pregnancy, infancy, and early childhood to prevent and treat childhood obesity and chronic diseases particularly ...

  25. Research suggests obesity in moms doubles the risk of autism in babies

    Children born to mothers with obesity both before and during pregnancy have an increased risk of neuropsychiatric and behavioral conditions, including autism spectrum disorder (ASD), and attention ...

  26. Childhood Obesity's Unexpected Impact on Skin

    A STRONG link between childhood obesity and the development of immune-mediated skin diseases (IMSDs), such as alopecia areata, atopic dermatitis, and psoriasis, has been highlighted in new research. Researchers found that obese children were significantly more likely to develop these common skin conditions compared to their normal-weight peers.

  27. Childhood Research in Obesity Prevention

    The Department of Pediatrics, Division of Gastroenterology, Hepatology and Nutrition and The Childhood Research in Obesity Prevention (CROP) research program at Stanford University is seeking an Assistant Program Director (Academic Program Professional 2, hybrid) to work under the general direction of the program Principal Investigator (PI) to ...

  28. Childhood obesity: causes and consequences

    Childhood obesity can profoundly affect children's physical health, social, and emotional well-being, and self esteem. It is also associated with poor academic performance and a lower quality of life experienced by the child. ... An Indian research study has defined overweight and obesity as overweight (between ≥85 th and <95 th percentile ...

  29. Extra nutrients during pregnancy may reduce childhood obesity risk

    Rates of childhood obesity are rising in many countries, particularly in less advantaged groups. Obesity increases the risk of many health diseases. These include type 2 diabetes, heart disease and some types of cancer. ... More research is needed to identify which of the nutrients in the supplement are most beneficial. Any of them - or a ...

  30. Obesity Effects on Child Health

    Obesity in childhood is the most challenging public health issue in the twenty-first century. It has emerged as a pandemic health problem worldwide. The children who are obese tend to stay obese in adulthood and prone to increased risk for diabetes and cardiac problems at a younger age. Childhood obesity is associated with increased morbidity and premature death.[1] Prevention of obesity in ...