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Childhood obesity: prevention is better than cure
1 Department of Pediatrics, SMGS Hospital Jammu, Jammu and Kashmir, India
2 Department of Pediatrics, Pt Bhagwat Dayal Sharma Post Graduate Institute of Medical Sciences, Rohtak, Haryana, India
3 Department of Microbiology Jammu University, Jammu, Jammu and Kashmir, India
4 Department of OBG Fernandez Hospital, Hyderabad,Telangana, India
5 Department of Orthopedics, Kokilaben Dhirubhai Ambani Hospital, Mumbai, India
6 Department of Surgery, Acharya Shri Chander College of Medical Sciences and Hospital, Jammu, Jammu and Kashmir, India
Obesity and its associated comorbidities have emerged as a major health problem garnering interests from both public health agencies and mainstream media consumers. With increasing awareness on its impact on health, finances, and community at large, it has come to the forefront for scientific research and development of health plans. The need for better strategies and novel interventions to manage obesity is now being recognized by the entire health care system. Obesity and overweight is now the fifth leading global risk factor for mortality. Strategic investment is thus urgently needed to implement population-based childhood obesity prevention programmes which are effective and also culturally appropriate. Population-based prevention is crucial to stem this rising tide of childhood obesity which is fast reaching epidemic proportions. Obesity has its onset very early in life; therefore, children constitute a major group of this disease. It is thus imperative to lay utmost importance on prevention of obesity in children and herald its progress, if present already. Furthermore, treatment is still in preliminary stage, so early prevention holds better than treatment at later stages. This article is an attempt to lay emphasis on childhood obesity as a problem that needs to be recognized early and measures for its prevention.
Obesity and its assessment.
The mechanisms involved in weight regulation and the development of obesity in children are varied and include genetic, environmental, and developmental factors. The relative importance of each of these mechanisms varies substantially between individuals and populations and is a subject of ongoing research. 1 IOTF (International Obesity Task Force) defines overweight and obesity in children 2–18 years of age using body mass index (BMI) cutoff points of 25 and 30 kg/m 2 , respectively. 2 As the child’s BMI varies with age, different age-specific cutoffs have been used to define overweight and obesity. Children are thus defined as being overweight or obese if they have a BMI above the cutoff for the given age and sex. 3 , 4 Accurate height and weight measurements are an integral part of general physical examination. Its role in early recognition of excessive weight gain makes it an important component of any visit to a primary health care center. 5 BMI is now recommended as the single best indicator of overweight and obesity in children and adolescents in clinical practice. 6 – 8
Why should we care about childhood obesity?
There are two main reasons to target childhood obesity. First, overweight and obese children and teens are much more likely to become obese as adults compared to normal BMI children, and second, it is more challenging for these adults to lose the excess weight once they become obese. Newer drugs and bariatric procedures for treating obesity-related health problems have emerged but these procedures are costly and have their own complications. Thus, prevention of childhood obesity with emphasis on increased physical activity is of prime importance. 9 – 11
The modern society and culture has managed to oust routine physical activity out of everyday life for most children and made energy dense, low nutrient food and beverages more affordable and accessible, making them far more appealing than their healthier counterparts. Behavioral changes and lifestyle modifications are the primary tools for reducing obesity. However, if the environment contributes to the unhealthy eating practices and sedentary lifestyle, strategies and interventions relying solely on individual “self-control” will not be very effective. Children are less equipped to make informed choices about what is healthy and what is not, making it all the more important to concentrate on modifying the environment. This will provide children with healthy food options and improve their physical activity level, thus reducing the risk of obesity. 12
Furthermore, obese children today are getting affected by diseases and health problems previously observed only in adults; many obese children today are developing health problems that once afflicted only adults. Chronic illnesses like diabetes mellitus and heart disease have an earlier onset and a prolonged course in these obese children, and even though the disease might remain undiagnosed until adulthood, the resulting complications are more severe leading to a shorter life. 13 Childhood obesity leads to many short- and long-term complications ( Table 1 ).
Complications associated with childhood obesity
Prevention of childhood obesity
Prevention is the key to success for obesity control as many, but not all, obese children will eventually become obese adults. “Tracking” or the likelihood of persistence of childhood obesity into adulthood is related to the age. The management of obesity in adults is a difficult and often unsuccessful feat especially in the absence of a known organic etiopathogenesis (eg, leptin deficiency, other hormonal abnormalities). Prevention of childhood obesity on the other hand can be more rewarding, providing better chances for reducing long-term complications. There are three levels of prevention in dealing with childhood obesity: 26 – 28
- Primordial prevention: deals with keeping a healthy weight and a normal BMI throughout childhood and into the teens.
- Primary prevention: aims to prevent overweight children from becoming obese.
- Secondary prevention: directed toward the treatment of obesity so as to reduce the comorbidities and reverse overweight and obesity if possible.
Inculcating healthy practices like plant-based foods and fruit consumption and inclusion of exercises and active lifestyle form the pillars of the prevention programme. 29 – 31
All the previously mentioned strategies when combined together can be put into practice sequentially from perinatal period to adolescence as follows:
- Perinatal: this includes adequate prenatal nutrition with optimal maternal weight gain, good blood sugar control in diabetics, postpartum weight loss with exercises and nutritional counseling. 32
- Infancy: early initiation of breastfeeding, exclusive breastfeeding for 6 months followed by inclusion of solid foods, providing a balanced diet with avoidance of unhealthy calorie-rich snacks and close monitoring of weight gain. 33 – 35
- Preschool: providing nutritional education to parents and children so as to develop healthy eating practices, offer healthy food preferences by giving early experience of different food and flavors, and following closely the rate of weight gain to prevent early adiposity rebound. 36
- Childhood: monitoring both the weight and height, preventing excessive prepubertal adiposity, provide nutritional counseling, and emphasis on daily physical activity. 37
- Adolescence: prevent the increase in weight after growth spurt, maintain healthy eating behavior, and reinforcing the need for daily exercises and workouts. 38 – 39
Furthermore, advocate nutritional goals, such as the traffic light diet:
- Green – GO: includes food which are low in calories and can be eaten without any restrictions.
- Yellow – CAUTION: food items with moderate high calorie content and can be eaten only in moderation.
- Red – STOP: high calorie food items which should be avoided or eaten rarely. 40 , 41
Physical activity and behavior therapy
Physical activity is the key component for prevention and management of obesity. 42 , 43 Preschool children require unstructured activities and thus will benefit from outdoor play and games. On the other hand, school going children and adolescents require at least 60 minutes of daily physical activity out of which 30 minutes should be structured activities like sports and supervised exercises. 44 – 46 This has also been recommended by American Academy of Pediatrics. 47 Simply providing education on obesity-related health risks, nutrition, and physical activity is insufficient to induce behavioral change. The best-established counseling techniques used for pediatric obesity treatment use a behavioral change model, which includes the following elements:
- Self-monitoring of target behaviors (logs of food, activity, or other behaviors recorded by patient or family).
This allows the child and family to recognize the behaviors contributing to their weight gain. Clinician feedback throughout the self-monitoring process is essential to monitor the behavior change. A patient’s food log may also identify other contributors to eating behaviors, such as the meal-time environment, boredom, and level of hunger, all of which can be valuable in the evaluation of stimulus control.
- Stimulus control to reduce environmental cues that contribute to unhealthy behaviors.
This includes reducing access to unhealthy behaviors (eg, removing some categories of food from the house or removing a television from the bedroom) and also efforts to establish new, healthier daily routines (such as making fruits and vegetables more accessible).
- Goal-setting for healthy behaviors rather than strict weight goals.
Goal-setting is widely used for inspiring behavioral change. However, the process can be detrimental if goals are not realistic and maintainable. Appropriate goals are Specific, Measurable, Attainable, Realistic, and Timely (“SMART”).
- Contracting for selected nutrition or activity goals.
Contracting is the explicit agreement to give a reward for the achievement of a specific goal. This helps children focus on specific behaviors and provides structure and incentive to their goal-setting process.
- Positive reinforcement of target behaviors.
Positive reinforcement can be in the form of praise for healthy behaviors or in the form of rewards for achieving specific goals. The reward should be negotiated by the parent and the child, ideally facilitated by the provider to ensure that the rewards are appropriate. Rewards should be small activities or privileges that the child can participate in frequently, rather than monetary incentives or toys; food should not be used as a reward. 48 – 53
Despite some discrepancy in study outcomes of increasing physical activity as a means to lower BMI, increasing the physical activity level of the child and family is a key focus in obesity treatment. 54 – 57 As with nutrition goals, strategies for increasing physical activity are individualized. Clinicians should take into account the developmental stage of the child, family schedule, and personal preferences for activity, while being mindful of sedentary activity. Clinicians can support the change process by consistently advising children and families to be physically active, suggesting options and encouraging goal-setting. In addition, community participation can be encouraged by forming partnerships with local fitness centers and schools. To increase physical activity in children, it is often helpful to consider a variety of options. Structured physical activity (organized sports or performance arts) may be team-based or individual and competitive or noncompetitive. Less structured activities include recreational sports with peers or family, self-directed physical training, and lifestyle activity. Although these categories overlap, they provide expanded and diverse options and increase the opportunities for physical activity for the child and family. For preschool-aged children, unstructured activity like outdoor play is simple and useful. 58 Providers can boost the level of activity in this age group by “prescribing” playground time and providing a list of local resources (playgrounds or other opportunities for active play), in addition to discouraging sedentary time (television use). The provider can also encourage parents to consider physical activity levels when they make choices regarding day care and after-school programs.
Substantial evidence supports the importance of reducing sedentary activity as a means of preventing and treating obesity in children. 59 , 60 – 63 Reducing sedentary activity has the secondary benefit of reducing the calorie intake and thus may prove to be more effective than increasing structured physical activity. 54 In developed countries, overindulgence in leisure activities and entertainments like television, computer and Internet, virtual gaming, and other media are the root cause of sedentary lifestyle. In fact, television viewing is the single best established environmental cause in the evolution of childhood obesity. Data on the role of other media in the development of obesity are lacking. It is recommended that television viewing and other “screen time” (other than homework) is restricted to less than 2 hours daily, and that children under age 2 years avoid television altogether. 64 Because many children initially will view television substantially more than this target, the first step should be in decreasing their present amount. School-wide campaigns and messages, and behavioral interventions using reinforcement and reward strategies have been effective in reducing television use. 60
Behavioral treatment strategies, detailed earlier, such as self-monitoring, can also be useful. Children and families should first monitor their present amount of media use and then set goals to reduce it. The following recommendations are made in keeping with the American Academy of Pediatrics policy statement. 64
- No television set in child’s bedroom
- No television viewing during meals
- Maximum time for television and media viewing of 2 hours or some strategy that approximates this limit
- No media viewing for children under 2 years of age
Substituting healthier behaviors and entertainment is helpful for accomplishment of these goals. For younger children, this is through the use of “active games” such as tag, hula hooping, and obstacle courses. Quiet, nonmedia activities such as reading aloud or playing board games are also acceptable substitutes, because they avoid television advertising and establish patterns of family interaction that may ultimately lead to active play. Taking activity breaks during television commercials both reduces exposure to advertising and establishes specific windows for activity; an average hour of television features ~20 minutes of commercials with half of them being food related. Strategies to reduce media use for older children are more variable and are best addressed through a combination of self-monitoring, establishment of family media limits, and negotiation to identify substitute activities. Because both media and homework are often accessed through the computer, it can be difficult for a parent to monitor a child’s actual media use. For these and other reasons, engagement of the child in the behavior-change process is essential, using the behavioral strategies outlined earlier.
Pediatric experience with drugs
Experience with pediatric use of weight loss drugs has surfaced and some of the findings are promising. However, anorectic drugs are not recommended for routine use for childhood obesity. The efficacy and safety of these drugs have to be established by controlled clinical trials before prescribing them in prepubertal children. In the case of post-pubertal adolescents who have failed to respond to behavioral therapy and diet modifications, use of anorectic drugs can be considered. All adolescents on medical therapy should be encouraged to engage in physical activity and should concurrently receive nutritional education and joint family counseling. 65 – 70
Many therapies that have been tried and are still in early phase or have met little success are “hunger training”, which aims to teach people to eat only when blood glucose is below a set target. Although it appears promising as a weight loss strategy, it is still to be proved so. 71 Based on the same principle, Biofeedback Enhanced Lifestyle Intervention has also been put to test in the recent past. 72 For this technique (also known as “hunger recognition”), participants are given a portable self-monitoring (blood glucose) device and instructed to eat only when physical hunger is confirmed (blood glucose in the target range of 60–85 mg/dL). Many people find these techniques as uncomfortable, embarrassing, and inconvenient. In addition to the previously mentioned techniques, there are certain biochemical markers that are markers of satiety like glucagon-like peptide and cholecystokinin. Leptin is another useful marker primarily stimulated by carbohydrates in diet that can be used for long-term appetite responses. 73 A lot needs to be investigated further to come to a complete understanding of this field.
Childhood obesity today constitutes one of the most serious health concerns, both in the developed and developing world. Obesity in childhood is causative for many chronic diseases, including type 2 diabetes, cardiovascular disease, hypertension, osteoporosis, and some carcinomas. It also has psychosocial consequences and may contribute to a delay in academic and social functioning as well as poor self-esteem and depression. The interventions for preventing and controlling obesity are mainly aimed at limiting the intake of sugar and high calorie snacks with higher consumption of vegetable- and fruit-based diet. This includes eating calcium-rich high-fiber diet with balanced micronutrients, daily healthy breakfasts and home cooked family meals, smaller portion size, and a curtailment in eating-out. Last but not least, decreasing the duration of “screen time”, especially television, and increasing the level of physical activity are vital for preventing childhood obesity. Over the last 30 years, the prevalence of childhood obesity has increased exponentially. Multifaceted strategies involving the public and private health sectors along with community participation are required to gradually reverse this trend.
No external funding was secured for this study.
All authors made substantial contributions to conception and design, acquisition of data, or analysis and interpretation of data; took part in either drafting the article or revising it critically for important intellectual content; gave final approval of the version to be published; and agree to be accountable for all aspects of the work.
The authors have no financial relationships relevant to this article to disclose. The authors report no conflicts of interest in this work.
Childhood Obesity: An Updated Review
- 1 Department of Pediatrics, The University of Calgary, The Alberta Children's Hospital, Calgary, Alberta, Canada.
- 2 Department of Family Medicine, The University of Calgary, Calgary, Alberta, Canada.
- 3 Department of Paediatrics, The Chinese University of Hong Kong, Hong Kong, China.
- 4 Department of Paediatrics and Adolescent Medicine, The Hong Kong Children's Hospital, Hong Kong, China.
- PMID: 35927921
- DOI: 10.2174/1573396318666220801093225
Background: Childhood obesity is an important and serious public health problem worldwide.
Objective: This article aims to familiarize physicians with the evaluation, management, and prevention of childhood.
Methods: A PubMed search was conducted in May, 2021, in Clinical Queries using the key terms "obesity" OR "obese". The search included clinical trials, randomized controlled trials, case-control studies, cohort studies, meta-analyses, observational studies, clinical guidelines, case reports, case series, and reviews. The search was restricted to English literature and children. The information retrieved from the above search was used in the compilation of the present article.
Results: Most obese children have exogenous obesity characterized by a growth rate for height above the 50th percentile, normal intelligence, normal genitalia, and lack of historical or physical evidence of an endocrine abnormality or a congenital syndrome. Obese children are at risk for dyslipidemia, hypertension, diabetes mellitus, non-alcoholic fatty liver disease, obstructive sleep apnea, psychosocial disturbances, impaired quality of life, and shorter life expectancy. The multitude of serious comorbidities necessitates effective treatment modalities. Dietary modification, therapeutic exercise, and behavioral modification are the fundamentals of treatment. Pharmacotherapy and/or bariatric surgery should be considered for obese individuals who do not respond to the above measures and suffer from a serious comorbid condition.
Conclusion: Childhood obesity, once established, is often refractory to treatment. Most treatment programs lead to a brief period of weight loss, followed by rapid re-accumulation of the lost weight after the termination of therapy. As such, preventive activity is the key to solving the problem of childhood obesity. Childhood obesity can be prevented by promoting a healthy diet, regular physical activity, and lifestyle modification. Parents should be encouraged to get involved in school and community programs that improve their children's nutritional status and physical activity.
Keywords: Diabetes mellitus; dyslipidemia; hypertension; non-alcoholic fatty liver disease; obesity; obstructive sleep apnea; overweight.
Copyright© Bentham Science Publishers; For any queries, please email at [email protected].
- Bariatric Surgery*
- Pediatric Obesity* / epidemiology
- Pediatric Obesity* / prevention & control
- Quality of Life
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- Published: 18 May 2023
Child and adolescent obesity
- Natalie B. Lister ORCID: orcid.org/0000-0002-9148-8632 1 , 2 ,
- Louise A. Baur ORCID: orcid.org/0000-0002-4521-9482 1 , 3 , 4 ,
- Janine F. Felix 5 , 6 ,
- Andrew J. Hill ORCID: orcid.org/0000-0003-3192-0427 7 ,
- Claude Marcus ORCID: orcid.org/0000-0003-0890-2650 8 ,
- Thomas Reinehr ORCID: orcid.org/0000-0002-4351-1834 9 ,
- Carolyn Summerbell 10 &
- Martin Wabitsch ORCID: orcid.org/0000-0001-6795-8430 11
Nature Reviews Disease Primers volume 9 , Article number: 24 ( 2023 ) Cite this article
- Paediatric research
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 mix of genetic and epigenetic factors, behavioural risk patterns and broader environmental and sociocultural influences affect the two body weight regulation systems: energy homeostasis, including leptin and gastrointestinal tract signals, operating predominantly at an unconscious level, and cognitive–emotional control that is regulated by higher brain centres, operating at a conscious level. Health-related quality of life is reduced in those with obesity. Comorbidities of obesity, including type 2 diabetes mellitus, fatty liver disease and depression, are more likely in adolescents and in those with severe obesity. Treatment incorporates a respectful, stigma-free and family-based approach involving multiple components, and addresses dietary, physical activity, sedentary and sleep behaviours. In adolescents in particular, adjunctive therapies can be valuable, such as more intensive dietary therapies, pharmacotherapy and bariatric surgery. Prevention of obesity requires a whole-system approach and joined-up policy initiatives across government departments. Development and implementation of interventions to prevent paediatric obesity in children should focus on interventions that are feasible, effective and likely to reduce gaps in health inequalities.
The prevalence of child and adolescent obesity remains high and continues to rise in low-income and middle-income countries (LMICs) at a time when these regions are also contending with under-nutrition in its various forms 1 , 2 . In addition, during the COVID-19 pandemic, children and adolescents with obesity have been more likely to have severe COVID-19 requiring hospitalization and mechanical ventilation 3 . At the same time, the pandemic was associated with rising levels of childhood obesity in many countries. These developments are concerning, considering that recognition is also growing that paediatric obesity is associated with a range of immediate and long-term negative health outcomes, a decreased quality of life 4 , 5 , an increased presentation to health services 6 and increased economic costs to individuals and society 7 .
Body weight is regulated by a range of energy homeostatic and cognitive–emotional processes and a multifactorial interplay of complex regulatory circuits 8 . Paediatric obesity arises when multiple environmental factors — covering preconception and prenatal exposures, as well as broader changes in the food and physical activity environments — disturb these regulatory processes; these influences are now widespread in most countries 9 .
The treatment of obesity includes management of obesity-associated complications, a developmentally sensitive approach, family engagement, and support for long-term behaviour changes in diet, physical activity, sedentary behaviours and sleep 10 . New evidence highlights the role, in adolescents with more severe obesity, of bariatric surgery 11 and pharmacotherapy, particularly the potential for glucagon-like peptide 1 (GLP1) receptor agonists 12 .
Obesity prevention requires a whole-system approach, with policies across all government and community sectors systematically taking health into account, avoiding harmful health impacts and decreasing inequity. Programmatic prevention interventions operating ‘downstream’ at the level of the child and family, as well as ‘upstream’ interventions at the level of the community and broader society, are required if a step change in tackling childhood obesity is to be realized 13 , 14 .
In this Primer, we provide an overview of the epidemiology, causes, pathophysiology and consequences of child and adolescent obesity. We discuss diagnostic considerations, as well as approaches to its prevention and management. Furthermore, we summarize effects of paediatric obesity on quality of life, and open research questions.
Definition and prevalence.
The World Health Organization (WHO) defines obesity as “abnormal or excessive fat accumulation that presents a risk to health” 15 . Paediatric obesity is defined epidemiologically using BMI, which is adjusted for age and sex because of the physiological changes in BMI during growth 16 . Global prevalence of paediatric obesity has risen markedly over the past four decades, initially in high-income countries (HICs), but now also in many LMICs 1 .
Despite attempts to standardize the epidemiological classification, several definitions of paediatric obesity are in use; hence, care is needed when comparing prevalence rates. The 2006 WHO Child Growth Standard, for children aged 0 to 5 years, is based on longitudinal observations of multiethnic populations of children with optimal infant feeding and child-rearing conditions 17 . The 2007 WHO Growth Reference is used for the age group 5–19 years 18 , and the 2000 US Centers for Disease Control and Prevention (CDC) Growth Charts for the age group 2–20 years 19 . The WHO and CDC definitions based on BMI-for-age charts are widely used, including in clinical practice. By contrast, the International Obesity Task Force (IOTF) definition, developed from nationally representative BMI data for the age group 2–18 years from six countries, is used exclusively for epidemiological studies 20 .
For the age group 5–19 years, between 1975 and 2016, the global prevalence of obesity (BMI >2 standard deviations (SD) above the median of the WHO growth reference) increased around eightfold to 5.6% in girls and 7.8% in boys 1 . Rates have plateaued at high levels in many HICs but have accelerated in other regions, particularly in parts of Asia. For the age group 2–4 years, between 1980 and 2015, obesity prevalence (IOTF definition, equivalent to an adult BMI of ≥30 kg/m 2 ) increased from 3.9% to 7.2% in boys and from 3.7% to 6.4% in girls 21 . Obesity prevalence is highest in Polynesia and Micronesia, the Middle East and North Africa, the Caribbean and the USA (Fig. 1 ). Variations in prevalence probably reflect different background levels of obesogenic environments, or the sum total of the physical, economic, policy, social and cultural factors that promote obesity 22 . Obesogenic environments include those with decreased active transport options, a ubiquity of food marketing directed towards children, and reduced costs and increased availability of nutrient-poor, energy-dense foods. Particularly in LMICs, the growth of urbanization, new forms of technology and global trade have led to reduced physical activity at work and leisure, a shift towards Western diets, and the expansion of transnational food and beverage companies to shape local food systems 23 .
Maps showing the proportions of children and adolescents living with overweight or obesity (part a , boys; part b , girls) according to latest available data from the Global Obesity Observatory . Data might not be comparable between countries owing to differences in survey methodology.
The reasons for varying sex differences in prevalence in different countries are unclear but may relate to cultural variations in parental feeding practices for boys and girls and societal ideals of body size 24 . In 2016, obesity in the age group 5–19 years was more prevalent in girls than in boys in sub-Saharan Africa, Oceania and some middle-income countries in other regions, whereas it was more prevalent in boys than in girls in all HICs, and in East and South-East Asia 21 . Ethnic and racial differences in obesity prevalence within countries are often assumed to mirror variations in social deprivation and other social determinants of obesity. However, an independent effect of ethnicity even after adjustment for socioeconomic status has been documented in the UK, with Black and Asian boys in primary school having higher prevalence of obesity than white boys 25 .
Among individuals with obesity, very high BMI values have become more common in the past 15 years. The prevalence of severe obesity (BMI ≥120% of the 95th percentile (CDC definition), or ≥35 kg/m 2 at any age 26 , 27 ) has increased in many HICs, accounting for one-quarter to one-third of those with obesity 28 , 29 . Future health risks of paediatric obesity in adulthood are well documented. For example, in a data linkage prospective study in Israel with 2.3 million participants who had BMI measured at age 17 years, those with obesity (≥95th percentile BMI for age) had a much higher risk of death from coronary heart disease (HR 4.9, 95% CI 3.9–6.1), stroke (HR 2.6, 95% CI 1.7–4.1) and sudden death (HR 2.1, 95% CI 1.5–2.9) compared with those whose BMI fell between the 5th and 24th percentiles 30 .
Causes and risk factors
Early life is a critical period for childhood obesity development 9 , 31 , 32 , 33 . According to the Developmental Origins of Health and Disease framework, the early life environment may affect organ structure and function and influence health in later life 34 , 35 . Meta-analyses have shown that preconception and prenatal environmental exposures, including high maternal pre-pregnancy BMI and, to a lesser extent, gestational weight gain, as well as gestational diabetes and maternal smoking, are associated with childhood obesity, potentially through effects on the in utero environment 33 , 36 , 37 , 38 . Paternal obesity is also associated with childhood obesity 33 . Birthweight, reflecting fetal growth, is a proxy for in utero exposures. Both low and high birthweights are associated with later adiposity, with high birthweight linked to increased BMI and low birthweight to central obesity 33 , 39 .
Growth trajectories in early life are important determinants of later adiposity. Rapid weight gain in early childhood is associated with obesity in adolescence 32 . Also, later age and higher BMI at adiposity peak (the usual peak in BMI around 9 months of age), as well as earlier age at adiposity rebound (the lowest BMI reached between 4 and 7 years of age), are associated with increased adolescent and adult BMI 40 , 41 . Specific early life nutritional factors, including a lower protein content in formula food, are consistently associated with a lower risk of childhood obesity 42 , 43 . These also include longer breastfeeding duration, which is generally associated with a lower risk of childhood obesity 42 . However, some controversy exists, as these effects are affected by multiple sociodemographic confounding factors and their underlying mechanisms remain uncertain 44 . Some studies comparing higher and lower infant formula protein content have reported that the higher protein group have a greater risk of subsequent obesity, especially in early childhood 41 , 42 ; however, one study with a follow-up period until age 11 years found no significant difference in the risk of obesity, but an increased risk of overweight in the high protein group was still observed 42 , 43 , 45 . A high intake of sugar-sweetened beverages is associated with childhood obesity 33 , 46 .
Many other behavioural factors are associated with an increased risk of childhood obesity, including increased screen time, short sleep duration and poor sleep quality 33 , 47 , reductions in physical activity 48 and increased intake of energy-dense micronutrient-poor foods 49 . These have been influenced by multiple changes in the past few decades in the broader social, economic, political and physical environments, including the widespread marketing of food and beverages to children, the loss of walkable green spaces in many urban environments, the rise in motorized transport, rapid changes in the use of technology, and the move away from traditional foods to ultraprocessed foods.
Obesity prevalence is inextricably linked to relative social inequality, with data suggesting a shift in prevalence over time towards those living with socioeconomic disadvantage, and thus contributes to social inequalities. In HICs, being in lower social strata is associated with a higher risk of obesity, even in infants and young children 50 , whereas the opposite relationship occurs in middle-income countries 51 . In low-income countries, the relationship is variable, and the obesity burden seems to be across socioeconomic groups 52 , 53 .
Overall, many environmental, lifestyle, behavioural and social factors in early life are associated with childhood obesity. These factors cannot be seen in isolation but are part of a complex interplay of exposures that jointly contribute to increased obesity risk. In addition to multiple prenatal and postnatal environmental factors, genetic variants also have a role in the development of childhood obesity (see section Mechanisms/pathophysiology).
Comorbidities and complications
Childhood obesity is associated with a wide range of short-term comorbidities (Fig. 2 ). In addition, childhood obesity tracks into adolescence and adulthood and is associated with complications across the life course 32 , 41 , 54 , 55 .
Obesity in children and adolescents can be accompanied by various other pathologies. In addition, childhood obesity is associated with complications and disorders that manifest in adulthood (red box).
Increased BMI, especially in adolescence, is linked to a higher risk of many health outcomes, including metabolic disorders, such as raised fasting glucose, impaired glucose tolerance, type 2 diabetes mellitus (T2DM), metabolic syndrome and fatty liver disease 56 , 57 , 58 , 59 . Other well-recognized obesity-associated complications include coronary heart disease, asthma, obstructive sleep apnoea syndrome (itself associated with metabolic dysfunction and inflammation) 60 , orthopaedic complications and a range of mental health outcomes including depression and low self-esteem 27 , 55 , 57 , 61 , 62 , 63 .
A 2019 systematic review showed that children and adolescents with obesity are 1.4 times more likely to have prediabetes, 1.7 times more likely to have asthma, 4.4 times more likely to have high blood pressure and 26.1 times more likely to have fatty liver disease than those with a healthy weight 64 . In 2016, it was estimated that, at a global level by 2025, childhood obesity would lead to 12 million children aged 5–17 years with glucose intolerance, 4 million with T2DM, 27 million with hypertension and 38 million with fatty liver disease 65 . These high prevalence rates have implications for both paediatric and adult health services.
Body weight regulation.
Body weight is regulated within narrow limits by homeostatic and cognitive–emotional processes and a multifactorial interplay of hormones and messenger substances in complex regulatory circuits (Fig. 3 ). When these regulatory circuits are disturbed, an imbalance between energy intake and expenditure leads to obesity or to poor weight gain. As weight loss is much harder to achieve than weight gain in the long term due to the regulation circuits discussed below, the development of obesity is encouraged by modern living conditions, which enable underlying predispositions for obesity to become manifest 8 , 66 .
Body weight is predominantly regulated by two systems: energy homeostasis and cognitive–emotional control. Both homeostatic and non-homeostatic signals are processed in the brain, involving multiple hormone and receptor cascades 217 , 218 , 219 . This overview depicts the best-known regulatory pathways. The homeostatic system, which is mainly regulated by brain centres in the hypothalamus and brainstem, operates on an unconscious level. Both long-term signals from the energy store in adipose tissue (for example, leptin) and short-term hunger and satiety signals from the gastrointestinal tract signal the current nutrient status. During gastric distension or after the release of gastrointestinal hormones (multiple receptors are involved) and insulin, a temporary feeling of fullness is induced. The non-homeostatic or hedonic system is regulated by higher-level brain centres and operates at the conscious level. After integration in the thalamus, homeostatic signals are combined with stimuli from the environment, experiences and emotions; emotional and cognitive impulses are then induced to control food intake. Regulation of energy homeostasis in the hypothalamus involves two neuron types of the arcuate nucleus: neurons producing neuropeptide Y (NPY) and agouti-related peptide (AgRP) and neurons producing pro-opiomelanocortin (POMC). Leptin stimulates these neurons via specific leptin receptors (LEPR) inducing anabolic effects in case of decreasing leptin levels and catabolic effects in case of increasing leptin levels. Leptin inhibits the production of NPY and AgRP, whereas low leptin levels stimulate AgRP and NPY production resulting in the feeling of hunger. Leptin directly stimulates POMC production in POMC neurons. POMC is cleaved into different hormone polypeptides including α-melanocyte-stimulating hormone which in turn activates melanocortin 4 receptors (MC4R) of cells in the nucleus paraventricularis of the hypothalamus, leading to the feeling of satiety. CART, cocaine and amphetamine responsive transcript; IR, insulin receptor.
In principle, there are two main systems in the brain which regulate body weight 8 , 66 (Fig. 3 ): energy homeostasis and cognitive–emotional control. Energy homeostasis is predominantly regulated by brain centres in the hypothalamus and brainstem and operates at an unconscious level. Both long-term signals from the adipose tissue energy stores and short-term hunger and satiety signals from the gastrointestinal tract signal the current nutrient status 8 , 66 . For example, negative energy balance leading to reduced fat mass results in reduced leptin levels, a permanently reduced urge to exercise and an increased feeling of hunger. During gastric distension or after the release of gastrointestinal hormones and insulin, a temporary feeling of fullness is induced 8 , 66 . Cognitive–emotional control is regulated by higher brain centres and operates at a conscious level. Here, the homeostatic signals are combined with stimuli from the environment (sight, smell and taste of food), experiences and emotions 8 , 66 . Disorders at the level of cognitive–emotional control mechanisms include emotional eating as well as eating disorders. For example, the reward areas in the brain of people with overweight are more strongly activated by high-calorie foods than those in the brain of people with normal weight 67 . Both systems interact with each other, and the cognitive–emotional system is strongly influenced by the homeostatic control circuits.
Disturbances in the regulatory circuits of energy homeostasis can be genetically determined, can result from disease or injury to the regulatory centres involved, or can be caused by prenatal programming 8 , 66 . If the target value of body weight has been shifted, the organism tries by all means (hunger, drive) to reach the desired higher weight. These disturbed signals of the homeostatic system can have an imperative, irresistible character, so that a conscious influence on food intake is no longer effectively possible 8 , 66 . The most important disturbances of energy homeostasis are listed in Table 1 .
The leptin pathway
The peptide hormone leptin is primarily produced by fat cells. Its production depends on the amount of adipose tissue and the energy balance. A negative energy balance during fasting results in a reduction of circulating leptin levels by 50% after 24 h (ref. 68 ). In a state of weight loss, leptin production is reduced 69 . In the brain, leptin stimulates two neuron types of the arcuate nucleus in the hypothalamus via specific leptin receptors: neurons producing neuropeptide Y (NPY) and agouti-related peptide (AgRP) and neurons producing pro-opiomelanocortin (POMC). High leptin levels inhibit the production of NPY and AgRP, whereas low leptin levels stimulate AgRP and NPY production. By contrast, leptin directly stimulates POMC production in POMC neurons (Fig. 3 ). POMC is a hormone precursor that is cleaved into different hormone polypeptides by specific enzymes, such as prohormone convertase 1 (PCSK1). This releases α-melanocyte-stimulating hormone (α-MSH) which in turn activates melanocortin 4 receptors (MC4R) of cells in the nucleus paraventricularis of the hypothalamus, leading to the feeling of satiety. Rare, functionally relevant mutations in the genes for leptin and leptin receptor, POMC , PCSK1/3 or MC4R lead to extreme obesity in early childhood. These forms of obesity are potential indications for specific pharmacological treatments, for example setmelanotide 70 , 71 . MC4R mutations are the most common cause of monogenic obesity, as heterozygous mutations can be symptomatic depending on the functional impairment and with variable penetrance and expression. Other genes have been identified, in which rare heterozygous pathological variants are also associated with early onset obesity (Table 1 ).
Pathological changes in adipose tissue
Adipose tissue can be classified into two types, white and brown adipose tissue. White adipose tissue comprises unilocular fat cells and brown adipose tissue contains multilocular fat cells, which are rich in mitochondria 72 . A third type of adipocyte, beige adipocytes, within the white adipose tissue are induced by prolonged exposure to cold or adrenergic signalling, and show a brown adipocyte-like morphology 72 . White adipose tissue has a large potential to change its volume to store energy and meet the metabolic demands of the body. The storage capacity and metabolic function of adipose tissue depend on the anatomical location of the adipose tissue depot. Predominant enlargement of white adipose tissue in the visceral, intra-abdominal area (central obesity) is associated with insulin resistance and an increased risk of metabolic disease development before puberty. Accumulation of adipose tissue in the hips and flanks has no adverse effect and may be protective against metabolic syndrome. In those with obesity, adipose tissue is characterized by an increased number of adipocytes (hyperplasia), which originate from tissue-resident mesenchymal stem cells, and by enlarged adipocytes (hypertrophy) 73 . Adipocytes with a very large diameter reach the limit of the maximal oxygen diffusion distance, resulting in hypoxia, the development of an inflammatory expression profile (characterized by, for example, leptin, TNF and IL-6) and adipocyte necrosis, triggering the recruitment of leukocytes. Resident macrophages switch from the anti-inflammatory M2 phenotype to a pro-inflammatory M1 phenotype, which is associated with insulin resistance, further promoting local sterile inflammation and the development of fibrotic adipose tissue. This process limits the expandability of the adipose tissue for further storage of triglycerides. In the patient, the increase in fat mass in obesity is associated with insulin resistance and systemic low-grade inflammation characterized by elevated serum levels of C-reactive protein and pro-inflammatory cytokines. The limitation of adipose tissue expandability results in storage of triglycerides in other organs, such as the liver, muscle and pancreas 74 .
Genetics and epigenetics in the general population
Twin studies have found heritability estimates for BMI of up to 70% 75 , 76 . In contrast to rare monogenic forms of obesity, which are often caused by a single genetic defect with a large effect, the genetic background of childhood obesity in the general population is shaped by the joint effects of many common genetic variants, each of which individually makes a small contribution to the phenotype. For adult BMI, genome-wide association studies, which examine associations of millions of such variants across the genome at the same time, have identified around 1,000 genetic loci 77 . The largest genome-wide association studies in children, which include much smaller sample sizes of up to 60,000 children, have identified 25 genetic loci for childhood BMI and 18 for childhood obesity, the majority of which overlap 78 , 79 . There is also a clear overlap with genetic loci identified in adults, for example for FTO , MC4R and TMEM18 , but this overlap is not complete, some loci are specific to early life BMI, or have a relatively larger contribution in childhood 78 , 79 , 80 . These findings suggest that biological mechanisms underlying obesity in childhood are mostly similar to those in adulthood, but the relative influence of these mechanisms may differ at different phases of life.
The role of epigenetic processes in childhood and adolescent obesity has gained increasing attention. In children, several studies found associations between DNA methylation and BMI 81 , 82 , 83 , 84 , but a meta-analysis including data from >4,000 children identified only minimal associations 85 . Most studies support the hypothesis that DNA methylation changes are predominantly a consequence rather than a cause of obesity, which may explain the lower number of identified (up to 12) associations in children, in whom duration of exposure to a higher BMI is shorter than in adults, in whom associations with DNA methylation at hundreds of sites have been identified 85 , 86 , 87 . In addition to DNA methylation, some specific circulating microRNAs have been found to be associated with obesity in childhood 84 .
The field of epigenetic studies in childhood obesity is relatively young and evolving quickly. Future studies will need to focus on defining robust associations in blood as well as other tissues and on identifying cause-and-effect relationships. In addition, other omics, such as metabolomics and proteomics, are promising areas that may contribute to an improved aetiological understanding or may provide biological signatures that can be used as predictive or prognostic markers of childhood obesity and its comorbidities.
Parental obesity and childhood obesity
There is an established link between increased parental BMI and increased childhood BMI 88 , 89 . This link may be due to shared genetics, shared environment, a direct intrauterine effect of maternal BMI or a combination of these factors. In the case of shared genetics, the child inherits BMI-increasing genetic variants from one or both parents. Shared environmental factors, such as diet or lifestyle, may also contribute to an increased BMI in both parents and child. In addition, maternal obesity might create an intrauterine environment that programmes metabolic processes in the fetus, which increases the risk of childhood obesity. Some studies show larger effects of maternal than paternal BMI, indicating a potential causal intrauterine mechanism of maternal obesity, but evidence showing similar maternal and paternal effects is increasing. The data may indicate that there is only a limited direct intrauterine effect of maternal obesity on childhood obesity; rather, genetic effects inherited from the mother or father, or both, and/or shared environmental factors may contribute to childhood obesity risk 90 , 91 , 92 , 93 , 94 , 95 .
Diagnosis, screening and prevention
The extent of overweight in clinical practice is estimated using BMI based on national charts 96 , 97 , 98 , 99 , 100 . Of note, the clinical classification of overweight or obesity differ depending on the BMI charts used and national recommendations; hence, local guidelines should be referred to. For example, the US CDC Growth Charts and several others use the 85th and 95th centile cut-points to denote overweight and obesity, respectively 19 . The WHO Growth Reference for children aged 5–19 years defines cut-points for overweight and obesity as a BMI-for-age greater than +1 and +2 SDs for BMI for age, respectively 18 . For children <5 years of age, overweight and obesity are defined as weight-for-height greater than +2 and +3 SDs, respectively, above the WHO Child Growth Standards median 17 . The IOTF and many countries in Europe use cut-points of 85th, 90th and 97th to define overweight, obesity and extreme obesity 26 .
BMI as an indirect measurement of body fat has some limitations; for example, pronounced muscle tissue leads to an increase in BMI, and BMI is not independent of height. In addition, people of different ethnicities may have different cut-points for obesity risk; for example, cardiometabolic risk occurs at lower BMI values in individuals with south Asian than in those with European ancestry 101 . Thus, BMI is best seen as a convenient screening tool that is supplemented by clinical assessment and investigations.
Other measures of body fat may help differentiate between fat mass and other tissues. Some of these tools are prone to low reliability, such as body impedance analyses (high day-to-day variation and dependent on level of fluid consumption) or skinfold thickness (high inter-observer variation), or are more expensive or invasive, such as MRI, CT or dual-energy X-ray absorptiometry, than simpler measures of body composition or BMI assessment.
Primary diseases rarely cause obesity in children and adolescents (<2%) 102 . However, treatable diseases should be excluded in those with obesity. A suggested diagnostic work-up is summarized in Fig. 4 . Routine measurement of thyroid-stimulating hormone (TSH) is not recommended 96 . Moderately elevated TSH levels (usually <10 IU/l) are frequently observed in obesity and are a consequence, and not a cause, of obesity 103 . In a growing child with normal height velocity, a normal BMI at the age of 2 years and normal cognitive development, no further diagnostic steps are necessary to exclude primary diseases 96 , 104 .
Concerning findings from a detailed medical history and physical examination will lead to further examinations. In individuals with early onset, extreme obesity (before age 3 years) and signs of hyperphagia, serum leptin level should be measured to rule out the extremely rare condition of congenital leptin deficiency. In individuals with normal or high leptin levels, genetic testing is indicated to search for monogenetic obesity. In individuals with intellectual disability, a syndromic disease may be present. Signs of impaired growth velocity or the history of central nervous system trauma or surgery will result in deeper endocrine evaluation and/or brain MRI. BDNF , brain-derived neurotropic factor; FT4, free thyroxin; KSR2 , kinase suppressor of ras 2; MC4R , melanocortin 4 receptor; POMC , pro-opiomelanocortin; SH2B1 , Src-homology 2 (SH2) B adapter protein 1; SIM1 , single-minded homologue 1; TSH, thyroid-stimulating hormone.
Clinical findings which need no further examination include pseudogynaecomastia (adipose tissue mimicking breast development; differentiated from breast tissue by ultrasonography), striae (caused by rapid weight increase) and a hidden penis in suprapubic adipose tissue (differentiated from micropenis by measurement of stretched penis length while pressing down on the suprapubic adipose tissue) 96 , 105 . Girls with obesity tend to have an earlier puberty onset (usually at around 8–9 years of age) and boys with severe obesity may have a delayed puberty onset (usually at around 13–14 years of age) 106 . Thus, if pubertal onset is slightly premature in girls or slightly delayed in boys, no further endocrine assessment is necessary.
Assessment of obesity-associated comorbidities
A waist to height ratio of >0.5 is a simple tool to identify central obesity 107 , 108 . Screening for cardiometabolic risk factors and fatty liver disease is recommended, especially in adolescents, and in those with more severe obesity or central adiposity, a strong family history of T2DM or premature heart disease, or relevant clinical symptoms, such as high blood pressure or acanthosis nigricans 96 , 97 , 98 , 99 , 109 . Investigations generally include fasting glucose levels, lipid profile, liver function and glycated haemoglobin, and might include an oral glucose tolerance test, polysomnography, and additional endocrine tests for polycystic ovary syndrome 96 , 97 , 98 , 99 .
T2DM in children and adolescents often occurs in the presence of a strong family history and may not be related to obesity severity 110 . T2DM onset usually occurs during puberty, a physiological state associated with increased insulin resistance 111 and, therefore, screening for T2DM should be considered in children and adolescents with obesity and at least one risk factor (family history of T2DM or features of metabolic syndrome) starting at pubertal onset 112 . As maturity-onset diabetes of the young (MODY) type II and type III are more frequent than T2DM in children and adolescents in many ethnicities, genetic screening for MODY may be appropriate 112 . Furthermore, type 1 diabetes mellitus (T1DM) should be excluded by measurement of autoantibodies in any individual with suspected diabetes with obesity. The differentiation of T2DM from MODY and T1DM is important as the diabetes treatment approaches differ 112 .
Several comorbidities of obesity should be considered if specific symptoms occur 96 , 109 . For polycystic ovary syndrome in hirsute adolescent girls with oligomenorrhoea or amenorrhoea, moderately increased testosterone levels and decreased sex hormone binding globulin levels are typical laboratory findings 113 . Obstructive sleep apnoea can occur in those with more severe obesity and who snore, have daytime somnolence or witnessed apnoeas. Diagnosis is made by polysomnography 114 . Minor orthopaedic disorders, such as flat feet and genu valgum, are frequent in children and adolescents with obesity and may cause pain. Major orthopaedic complications include slipped capital femoral epiphyses (acute and chronic), which manifest with hip and knee pain in young adolescents and are characterized by reduced range of hip rotation and waddling gait; and Blount disease (tibia vara), typically occurring in children aged 2–5 years 105 , 115 . In addition, children and adolescents with extreme obesity frequently have increased dyspnoea and decreased exercise capacity. A heightened demand for ventilation, elevated work of breathing, respiratory muscle inefficiency and diminished respiratory compliance are caused by increased truncal fat mass. This may result in a decreased functional residual capacity and expiratory reserve volume, ventilation to perfusion ratio abnormalities and hypoxaemia, especially when supine. However, conventional respiratory function tests are only mildly affected by obesity except in extreme cases 116 . Furthermore, gallstones should be suspected in the context of abdominal pain after rapid weight loss, which can be readily diagnosed via abdominal ultrasonography 105 . Finally, pseudotumor cerebri may present with chronic headache, and depression may present with flat affect, chronic fatigue and sleep problems 105 .
Obesity in adolescents can also be associated with disordered eating, eating disorders and other psychological disorders 117 , 118 . If suspected, assessment by a mental health professional is recommended.
A comprehensive approach
The 2016 report of the WHO Commission on Ending Childhood Obesity stated that progress in tackling childhood obesity has been slow and inconsistent, with obesity prevention requiring a whole-of-government approach in which policies across all sectors systematically take health into account, avoiding harmful health impacts and, therefore, improving population health and health equity 13 , 119 . The focus in developing and implementing interventions to prevent obesity in children should be on interventions that are feasible, effective and likely to reduce health inequalities 14 . Importantly, the voices of children and adolescents living with social disadvantage and those from minority groups must be heard if such interventions are to be effective and reduce inequalities 120 .
Figure 5 presents a system for the prevention of childhood obesity within different domains of the socioecological model 121 and highlights opportunities for interventions. These domains can be described on a continuum, from (most downstream) individual and interpersonal (including parents, peers and wider family) through to organizational (including health care and schools), community (including food, activity and environment), society (including media and finally cultural norms) and (most upstream) public policy (from local to national level). Interventions to prevent childhood obesity can be classified on the Nuffield intervention ladder 122 . This framework was proposed by the Nuffield Council on Bioethics in 2007 (ref. 122 ) and distributes interventions on the ladder steps depending on the degree of agency required by the individual to make the behavioural changes that are the aim of the intervention. The bottom step of the ladder includes interventions that provide information, which requires the highest agency and relies on a child, adolescent and/or family choosing (and their ability to choose) to act on that information and change behaviour. The next steps of the ladder are interventions that enable choice, guide choice through changing the default policy, guide choice through incentives, guide choice through disincentives, or restrict choice. On the top-most step of the ladder (lowest agency required) are interventions that eliminate choice.
This schematic integrates interventions that were included in a Cochrane review 127 of 153 randomized controlled trials of interventions to prevent obesity in children and are high on the Nuffield intervention ladder 122 . The Nuffield intervention ladder distributes interventions depending on the degree of agency required for the behavioural changes that are the aim of the intervention. The socioecological model 121 comprises different domains (or levels) from the individual up to public policy. Interventions targeting the individual and interpersonal domains can be described as downstream interventions, and interventions within public policy can be described as the highest level of upstream interventions. Within each of these domains, arrow symbols with colours corresponding to the Nuffield intervention ladder category are used to show interventions that were both included in the Cochrane review 127 and that guide, restrict or eliminate choice as defined by the Nuffield intervention ladder 122 . Upstream interventions, and interventions on the top steps of the Nuffield ladder, are more likely to reduce inequalities. NGO, non-governmental organization.
Downstream and high-agency interventions (on the bottom steps of the Nuffield ladder) are more likely to result in intervention-generated inequalities 123 . This has been elegantly described and evidenced, with examples from the obesity prevention literature 124 , 125 . A particularly strong example is a systematic review of 38 interventions to promote healthy eating that showed that food price (an upstream and low-agency intervention) seemed to decrease inequalities, all interventions that combined taxes and subsidies consistently decreased inequalities, and downstream high-agency interventions, especially dietary counselling, seemed to increase inequalities 126 .
Effectiveness of prevention interventions
A 2019 Cochrane review of interventions to prevent obesity in children 127 included 153 randomized controlled trials (RCTs), mainly in HICs (12% were from middle-income countries). Of these RCTs, 56% tested interventions in children aged 6–12 years, 24% in children aged 0–5 years, and 20% in adolescents aged 13–18 years. The review showed that diet-only interventions to prevent obesity in children were generally ineffective across all ages. Interventions combining diet and physical activity resulted in modest benefits in children aged 0–12 years but not in adolescents. However, physical activity-only interventions to prevent obesity were effective in school-age children (aged 5–18 years). Whether the interventions were likely to work equitably in all children was investigated in 13 RCTs. These RCTs did not indicate that the strategies increased inequalities, although most of the 13 RCTs included relatively homogeneous groups of children from disadvantaged backgrounds.
The potential for negative unintended consequences of obesity prevention interventions has received much attention 128 . The Cochrane review 127 investigated whether children were harmed by any of the strategies; for example, by having injuries, losing too much weight or developing damaging views about themselves and their weight. Of the few RCTs that did monitor these outcomes, none found any harms in participants.
Most interventions (58%) of RCTs in the Cochrane review aimed to change individual lifestyle factors via education-based approaches (that is, simply provide information) 129 . In relation to the socioecological model, only 11 RCTs were set in the food and physical activity environment domain, and child care, preschools and schools were the most common targets for interventions. Of note, no RCTs were conducted in a faith-based setting 130 . Table 2 highlights examples of upstream interventions that involve more than simply providing information and their classification on the Nuffield intervention ladder.
Different settings for interventions to prevent childhood obesity, including preschools and schools, primary health care, community settings and national policy, offer different opportunities for reach and effectiveness, and a reduction in inequalities.
Preschools and schools are key settings for public policy interventions for childhood obesity prevention, and mandatory and voluntary food standards and guidance on physical education are in place in many countries. Individual schools are tasked with translating and implementing these standards and guidance for their local context. Successful implementation of a whole-school approach, such as that used in the WHO Nutrition-Friendly Schools Initiative 131 , is a key factor in the effectiveness of interventions. Careful consideration should be given to how school culture can, and needs to, be shifted by working with schools to tailor the approach and manage possible staff capacity issues, and by building relationships within and outside the school gates to enhance sustainability 132 , 133 .
Primary health care offers opportunities for guidance for obesity prevention, especially from early childhood to puberty. Parent-targeted interventions conducted by clinicians in health-care or community settings have the strongest level of evidence for their effectiveness in reducing BMI z -score at age 2 years 134 . These interventions include group programmes, clinic nurse consultations, mobile phone text support or nurse home visiting, and focusing on healthy infant feeding, healthy childhood feeding behaviours and screen time.
A prospective individual participant data meta-analysis of four RCTs involving 2,196 mother–baby dyads, and involving nurse home visiting or group programmes, resulted in a small but significant reduction in BMI in infants in the intervention groups compared with control infants at age 18–24 months 134 . Improvements were also seen in television viewing time, breastfeeding duration and feeding practices. Interventions were more effective in settings with limited provision of maternal and child health services in the community. However, effectiveness diminished by age 5 years without further intervention, highlighting the need for ongoing interventions at each life stage 135 . Evidence exists that short-duration interventions targeting sleep in very early childhood may be more effective than nutrition-targeted interventions in influencing child BMI at age 5 years 136 .
Primary care clinicians can provide anticipatory guidance, as a form of primary prevention, to older children, adolescents and their families, aiming to support healthy weight and weight-related behaviours. Clinical guidelines recommend that clinicians monitor growth regularly, and provide guidance on healthy eating patterns, physical activity, sedentary behaviours and sleep patterns 97 , 100 . Very few paediatric trials have investigated whether this opportunistic screening and advice is effective in obesity prevention 100 . A 2021 review of registered RCTs for the prevention of obesity in infancy found 29 trials 137 , of which most were delivered, or were planned to be delivered, in community health-care settings, such as nurse-led clinics. At the time of publication, 11 trials had reported child weight-related outcomes, two of which showed a small but significant beneficial effect on BMI at age 2 years, and one found significant improvements in the prevalence of obesity but not BMI. Many of the trials showed improvements in practices, such as breastfeeding and screen time.
At the community level, local public policy should be mindful of the geography of the area (such as urban or rural) and population demographics. Adolescents usually have more freedom in food and beverage choices made outside the home than younger children. In addition, physical activity levels usually decline and sedentary behaviours rise during adolescence, particularly in girls 138 , 139 . These behavioural changes offer both opportunities and barriers for those developing community interventions. On a national societal level, public policies for interventions to prevent obesity in children include the control of advertising of foods and beverages high in fat, sugar and/or salt in some countries. Industry and the media, including social media, can have a considerable influence on the food and physical activity behaviours of children 13 , 119 .
Public policy may target interventions at all domains from the individual to the societal level. The main focus of interventions in most national public policies relies on the ability of individuals to make the behavioural changes that are the aim of the intervention (high-agency interventions) at the individual level (downstream interventions). An equal focus on low-agency and upstream interventions is required if a step change in tackling childhood obesity is to be realized 140 , 141 .
COVID-19 and obesity
Early indications in several countries show rising levels of childhood obesity, and an increase in inequalities in childhood obesity during the COVID-19 pandemic 142 . The substantial disruptions in nutrition and lifestyle habits of children during and since the pandemic include social isolation and addiction to screens 143 . Under-nutrition is expected to worsen in poor countries, but obesity rates could increase in middle-income countries and HICs, especially among vulnerable groups, widening the gap in health and social inequalities 143 . Public health approaches at national, regional and local levels should include strategies that not only prevent obesity and under-nutrition, but also reduce health inequalities.
In summary, although most trials of obesity prevention have occurred at the level of the individual, the immediate family, school or community, effective prevention of obesity will require greater investment in upstream, low-agency interventions.
Treatment should be centred on the individual and stigma-free (Box 1 ) and may aim for a reduction in overweight and improvement in associated comorbidities and health behaviours. Clinical considerations when determining a treatment approach should include age, severity of overweight and the presence of associated complications 144 , 145 .
Box 1 Strategies for minimizing weight stigma in health care 220 , 221 , 222
Minimizing weight bias in the education of health-care professionals
Improved education of health professionals:
pay attention to the implicit and explicit communication of social norms
include coverage of the broader determinants of obesity
include discussion of harms caused by social and cultural norms and messages concerning body weight
provide opportunities to practise non-stigmatizing care throughout education
Provide causal information focusing on the genetic and/or socioenvironmental determinants of weight.
Provide empathy-invoking interventions, emphasizing size acceptance, respect and human dignity.
Provide a weight-inclusive approach, by emphasizing that all individuals, regardless of size, have the right to equal health care.
Addressing health facility infrastructure and processes
Provide appropriately sized chairs, blood pressure cuffs, weight scales, beds, toilets, showers and gowns.
Use non-stigmatizing language in signage, descriptions of clinical services and other documentation.
Providing clinical leadership and using appropriate language within health-care settings
Senior clinicians and managers should role-model supportive and non-biased behaviours towards people with obesity and indicate that they do not tolerate weight-based discrimination in any form.
Staff should identify the language that individuals prefer in referring to obesity.
Use person-first language, for example a ‘person with obesity’ rather than ‘an obese person’.
Clinical guidelines advise that first-line management incorporates a family-based multicomponent approach that addresses dietary, physical activity, sedentary and sleep behaviours 97 , 99 , 109 , 146 . This approach is foundational, with adjunctive therapies, especially pharmacotherapy and bariatric surgery, indicated under specific circumstances, usually in adolescents with more severe obesity 144 , 145 . Guideline recommendations vary greatly among countries and are influenced by current evidence, and functionality and resourcing of local health systems. Hence, availability and feasibility of therapies differs internationally. In usual clinical practice, interventions may have poorer outcomes than is observed in original studies or anticipated in evidence-based guidelines 147 because implementation of guidelines is more challenging in resource-constrained environments 148 . In addition, clinical trials are less likely to include patients with specialized needs, such as children from culturally diverse populations, those living with social disadvantage, children with complex health problems, and those with severe obesity 149 , 150 .
There are marked differences in individual responses to behavioural interventions, and overall weight change outcomes are often modest. In children aged 6–11 years, a 2017 Cochrane review 150 found that mean BMI z -scores were reduced in those involved in behaviour-changing interventions compared with those receiving usual care or no treatment by only 0.06 units (37 trials; 4,019 participants; low-quality evidence) at the latest follow-up (median 10 months after the end of active intervention). In adolescents aged 12–17 years, another 2017 Cochrane review 149 found that multicomponent behavioural interventions resulted in a mean reduction in weight of 3.67 kg (20 trials; 1,993 participants) and reduction in BMI of 1.18 kg/m 2 (28 trials; 2,774 participants). These effects were maintained at the 24-month follow-up. A 2012 systematic review found significant improvements in LDL cholesterol triglycerides and blood pressure up to 1 year from baseline following lifestyle interventions in children and adolescents 151 .
Family-based behavioural interventions are recommended in national level clinical practice guidelines 97 , 100 , 146 , 152 . They are an important element of intensive health behaviour and lifestyle treatments (IHBLTs) 109 . Family-based approaches use behavioural techniques, such as goal setting, parental monitoring or modelling, taught in family sessions or in individual sessions separately to children and care givers, depending on the child’s developmental level. The priority is to encourage the whole family to engage in healthier behaviours that result in dietary improvement, greater physical activity, and less sedentariness. This includes making changes to the family food environment and requires parental monitoring.
Family-based interventions differ in philosophy and implementation from those based on family systems theory and therapy 153 . All are intensive interventions that require multiple contact hours (26 or more) with trained specialists delivered over an extended period of time (6–12 months) 10 . Changing family lifestyle habits is challenging and expensive, and the therapeutic expertise is not widely available. Moving interventions to primary care settings, delivered by trained health coaches, and supplemented by remote contact (for example by phone), will improve access and equity 154 .
Very few interventions use single psychological approaches. Most effective IHBLTs are multicomponent and intensive (many sessions), and include face-to-face contact. There has been interest in motivational interviewing as an approach to delivery 155 . As client-centred counselling, this places the young person at the centre of their behaviour change. Fundamental to motivational interviewing is the practitioner partnership that helps the young person and/or parents to explore ambivalence to change, consolidate commitment to change, and develop a plan based on their own insights and expertise. Evidence reviews generally support the view that motivational interviewing reduces BMI. Longer interventions (>4 months), those that assess and report on intervention fidelity, and those that target both diet and physical activity are most effective 155 , 156 .
More intensive dietary interventions
Some individuals benefit from more intensive interventions 98 , 144 , 157 , 158 , which include very low-energy diets, very low-carbohydrate diets and intermittent energy restriction 159 . These interventions usually aim for weight loss and are only recommended for adolescents who have reached their final height. These diets are not recommended for long periods of time due to challenges in achieving nutritional adequacy 158 , 160 , and lack of long-term safety data 158 , 161 . However, intensive dietary interventions may be considered when conventional treatment is unsuccessful, or when adolescents with comorbidities or severe obesity require rapid or substantial weight loss 98 . A 2019 systematic review of very low-energy diets in children and adolescents found a mean reduction in body weight of −5.3 kg (seven studies) at the latest follow‐up, ranging from 5 to 14.5 months from baseline 161 .
Until the early 2020s the only drug approved in many jurisdictions for the treatment of obesity in adolescents was orlistat, a gastrointestinal lipase inhibitor resulting in reduced uptake of lipids and, thereby, a reduced total energy intake 162 . However, the modest effect on weight in combination with gastrointestinal adverse effects limit its usefulness overall 163 .
A new generation of drugs has been developed for the treatment of both T2DM and obesity. These drugs are based on gastrointestinal peptides with effects both locally and in the central nervous system. GLP1 is an incretin that reduces appetite and slows gastric motility. The GLP1 receptor agonist liraglutide is approved for the treatment of obesity in those aged 12 years and older both in the USA and Europe 164 , 165 . Liraglutide, delivered subcutaneously daily at a higher dose than used for T2DM resulted in a 5% better BMI reduction than placebo after 12 months 166 . A 2022 trial of semaglutide, another GLP1 receptor agonist, delivered subcutaneously weekly in adolescents demonstrated 16% weight loss after 68 weeks of treatment, with modest adverse events and a low drop-out rate 12 . Tirzepatide, an agonist of both GLP1 and glucose-dependent insulinotropic polypeptide (GIP), is approved by the FDA for the treatment of T2DM in adults 167 . Subcutaneous tirzepatide weekly in adults with obesity resulted in ~20% weight loss over 72 weeks 168 . Of note, GIP alone increases appetite, but the complex receptor–agonist interaction results in downregulation of the GIP receptors 169 , illustrating why slightly modified agonists exert different effects. A study of the use of tirzepatide in adolescents with T2DM has been initiated but results are not expected before 2027 (ref. 170 ). No trials of tirzepatide are currently underway in adolescents with obesity but without T2DM.
Hypothalamic obesity is difficult to treat. Setmelanotide is a MC4R agonist that reduces weight and improves quality of life in most people with LEPR and POMC mutations 71 . In trials of setmelanotide, 8 of 10 participants with POMC deficiency and 5 of 11 with LEPR deficiency had weight loss of at least 10% at ~1 year. The mean percentage change in most hunger score from baseline was −27.1% and −43.7% in those with POMC deficiency and leptin receptor deficiency, respectively 71 .
In the near future, effective new drugs with, hopefully, an acceptable safety profile will be available that will change the way we treat and set goals for paediatric obesity treatment 171 .
Bariatric surgery is the most potent treatment for obesity in adolescents with severe obesity. The types of surgery most frequently used are sleeve gastrectomy and gastric bypass, both of which reduce appetite 172 . Mechanisms of action are complex, involving changes in gastrointestinal hormones, neural signalling, bile acid metabolism and gut microbiota 173 . Sleeve gastrectomy is a more straightforward procedure and the need for vitamin supplementation is lower than with gastric bypass. However, long-term weight loss may be greater after gastric bypass surgery 174 .
Prospective long-term studies demonstrate beneficial effects of both sleeve gastrectomy and gastric bypass on weight loss and comorbidities in adolescents with severe obesity 175 , 176 . In a 5-year follow-up period, in 161 participants in the US TEEN-LABS study who underwent gastric bypass, mean BMI declined from 50 to 37 kg/m 2 (ref. 11 ). In a Swedish prospective study in 81 adolescents who underwent gastric bypass, the mean decrease in BMI at 5 years was 13.1 kg/m 2 (baseline BMI 45.5 kg/m 2 ) compared with a BMI increase of 3.1 kg/m 2 in the control group 176 . Both studies showed marked inter-individual variations. Negative adverse effects, including gastrointestinal problems, vitamin deficits and reduction in lean body mass, are similar in adults and adolescents. Most surgical complications following bariatric surgery in the paediatric population are minor, occurring in the early postoperative time frame, but 8% of patients may have major perioperative complications 177 . Up to one-quarter of patients may require subsequent related procedures within 5 years 109 . However, many adolescents with severe obesity also have social and psychological problems, highlighting the need for routine and long-term monitoring 109 , 178 .
Recommendations for bariatric surgery in adolescents differ considerably among countries, with information on long-term outcomes emerging rapidly. In many countries, bariatric surgery is recommended only from Tanner pubertal stage 3–4 and beyond, and only in children with severe obesity and cardiometabolic comorbidities 177 . The 2023 American Academy of Pediatrics clinical practice guidelines recommend that bariatric surgery be considered in adolescents ≥13 years of age with a BMI of ≥35 kg/m 2 or 120% of the 95th percentile for age and sex, whichever is lower, as well as clinically significant disease, such as T2DM, non-alcoholic fatty liver disease, major orthopaedic complications, obstructive sleep apnoea, the presence of cardiometabolic risk, or depressed quality of life 109 . For those with a BMI of ≥40 kg/m 2 or 140% of the 95th percentile for age and sex, bariatric surgery is indicated regardless of the presence of comorbidities. Potential contraindications to surgery include correctable causes of obesity, pregnancy and ongoing substance use disorder. The guidelines comment that further evaluation, undertaken by multidisciplinary centres that offer bariatric surgery for adolescents, should determine the capacity of the patient and family to understand the risks and benefits of surgery and to adhere to the required lifestyle changes before and after surgery.
Long-term weight outcomes
Few paediatric studies have investigated long-term weight maintenance after the initial, more intensive, weight loss phase. A 2018 systematic review of 11 studies in children and adolescents showed that a diverse range of maintenance interventions, including support via face-to-face psychobehavioural therapies, individual physician consultations, or adjunctive therapeutic contact via newsletters, mobile phone text or e-mail, led to stabilization of BMI z -score compared with control participants, who had increases in BMI z -score 179 . Interventions that are web-based or use mobile devices may be particularly useful in young people 180 .
One concern is weight regain which occurs after bariatric surgery in general 181 but may be more prevalent in adolescents 176 . For example, in a Swedish prospective study, after 5 years, 25–30% of participants fulfilled the definitions of low surgical treatment effectiveness, which was associated with poorer metabolic outcomes 176 . As with adults, prevention of weight regain for most at-risk individuals might be possible with the combination of lifestyle support and pharmacological treatment 182 . Further weight maintenance strategies and long-term outcomes are discussed in the 2023 American Academy of Pediatrics clinical practice guidelines 109 . The appropriate role and timing of other therapies for long-term weight loss maintenance, such as anti-obesity medications, more intensive dietary interventions and bariatric surgery, are areas for future research.
In summary, management of obesity in childhood and adolescence requires intensive interventions. Emerging pharmacological therapies demonstrate greater short-term effectiveness than behavioural interventions; however, long-term outcomes at ≥2 years remain an important area for future research.
Quality of life
Weight bias describes the negative attitudes to, beliefs about and behaviour towards people with obesity 183 . It can lead to stigma causing exclusion, and discrimination in work, school and health care, and contributes to the inequities common in people with obesity 184 . Weight bias also affects social engagement and psychological well-being of children.
Children and adolescents with obesity score lower overall on health-related quality of life (HRQoL) 4 , 5 . In measures that assess domains of functioning, most score lower in physical functioning, physical/general health and psychosocial areas, such as appearance, and social acceptance and functioning. HRQoL is lowest in treatment-seeking children and in those with more extreme obesity 185 . Weight loss interventions generally increase HRQoL independent of the extent of weight loss 186 , especially in the domains most affected. However, changes in weight and HRQoL are often not strongly correlated. This may reflect a lag in the physical and/or psychosocial benefit from weight change, or the extent of change that is needed to drive change in a child’s self-perception.
Similar observations apply to the literature on self-esteem. Global self-worth is reduced in children and adolescents with obesity, as is satisfaction with physical appearance, athletic competence and social acceptance 187 . Data from intensive interventions suggest the psychological benefit of weight loss may be as dependent on some feature of the treatment environment or supportive social network as the weight loss itself 188 . This may include the daily company of others with obesity, making new friendships, and experienced improvements in newly prioritized competences.
There is a bidirectional relationship between HRQoL and obesity 189 , something also accepted in the relationship with mood disorder. Obesity increases the risk of depression and vice versa, albeit over a longer period of time and which may only become apparent in adulthood 190 . Obesity also presents an increased risk of anxiety 191 .
Structured and professionally delivered weight management interventions ameliorate mood disorder symptoms 192 and improve self-esteem 193 . Regular and extended support are important components beyond losing weight. Such interventions do not increase the risk of eating disorders 194 . This is despite a recognition that binge eating disorder is present in up to 5% of adolescents with overweight or obesity 195 . They are five times more likely to have binge eating symptoms than those with average weight. Importantly, adolescents who do not have access to professionally delivered weight management may be more likely to engage in self-directed dieting, which is implicated in eating disorder development 196 .
The literature linking childhood obesity with either attention deficit hyperactivity disorder or autism spectrum disorder is complex and the relationship is uncertain. The association seems to be clearer in adults but the mechanisms and their causal directions remain unclear 109 , 197 . Young children with obesity, especially boys, are more likely to be parent-rated as having behavioural problems 198 . This may be a response to the behaviour of others rather than reflect clinical diagnoses such as attention deficit hyperactivity disorder or autism spectrum disorder. Conduct and peer relationship problems co-occur in children, regardless of their weight.
Children with obesity experience more social rejection. They receive fewer friendship nominations and more peer rejections, most pronounced in those with severe obesity 199 . This continues through adolescence and beyond. Children with obesity are more likely to report being victimized 200 . Younger children may respond by being perpetrators themselves. While it is assumed that children are victimized because of their weight, very few studies have looked at the nature or reason behind victimization. A substantial proportion of children with obesity fail to identify themselves as being fat-teased 187 . Although the stigma associated with obesity should be anticipated in children, especially in those most overweight, it would be inappropriate to see all as victims. A better understanding of children’s resilience is needed.
Many gaps remain in basic, translational and clinical research in child and adolescent obesity. The mechanisms (genetic, epigenetic, environmental and social) behind the overwhelming association between parental obesity and child and adolescent obesity are still unclear given the paradoxically weak association in BMI between adopted children and their parents in combination with the modest effect size of known genetic loci associated with obesity 201 .
Early manifestation of extreme obesity in childhood suggests a strong biological basis for disturbances of homeostatic weight regulation. Deep genotyping (including next-generation sequencing) and epigenetic analyses in these patients will reveal new genetic causes and causal pathways as a basis for the development of mechanism-based treatments. Future work aiming to understand the mechanisms underlying the development of childhood obesity should consider the complex biopsychosocial interactions and take a systems approach to understanding causal pathways leading to childhood obesity to contribute to evidence-based prevention and treatment strategies.
Long-term outcome data to better determine the risks of eating disorders are required. Although symptoms improve during obesity treatment in most adolescents, screening and monitoring for disordered eating is recommended in those presenting for treatment 202 and effective tools for use in clinical practice are required. A limited number of tools are validated to identify binge eating disorder in youth with obesity 203 but further research is needed to screen appropriately for the full spectrum of eating disorder diagnoses in obesity treatment seeking youth 203 . Recent reviews provide additional detail regarding eating disorder risk in child and adolescent obesity 117 , 202 , 204 .
Most studies of paediatric obesity treatment have been undertaken in HICs and predominantly middle-class populations. However, research is needed to determine which strategies are best suited for those in LMICs and low-resource settings, for priority population groups including indigenous peoples, migrant populations and those living with social disadvantage, and for children with neurobehavioural and psychiatric disorders. We currently have a limited understanding of how best to target treatment pathways for different levels of genetic risk, age, developmental level, obesity severity, and cardiometabolic and psychological risk. Current outcomes for behavioural interventions are relatively modest and improved treatment outcomes are needed to address the potentially severe long-term health outcomes of paediatric obesity. Studies also need to include longer follow-up periods after an intervention, record all adverse events, incorporate cost-effectiveness analyses and have improved process evaluation.
Other areas in need of research include the role of new anti-obesity medications especially in adolescents, long-term outcomes following bariatric surgery and implementation of digital support systems to optimize outcomes and reduce costs of behavioural change interventions 205 . We must also better understand and tackle the barriers to implementation of treatment in real-life clinical settings, including the role of training of health professionals. Importantly, treatment studies of all kinds must engage people with lived experience — adolescents, parents and families — to understand what outcomes and elements of treatment are most valued.
Obesity prevention is challenging because it requires a multilevel, multisectoral approach that addresses inequity, involves many stakeholders and addresses both the upstream and the downstream factors influencing obesity risk. Some evidence exists of effectiveness of prevention interventions operating at the level of the child, family and school, but the very poor progress overall in modifying obesity prevalence globally highlights many areas in need of research and evidence implementation. Studies are needed especially in LMICs, particularly in the context of the nutrition transition and the double burden of malnutrition. A focus on intergenerational research, rather than the age-based focus of current work, is also needed. Systems research approaches should be used, addressing the broader food and physical activity environments, and links to climate change 206 . In all studies, strategies are needed that enable co-production with relevant communities, long-term follow-up, process evaluation and cost-effectiveness analyses. In the next few years, research and practice priorities must include a focus on intervention strategies in the earliest phases of life, including during pregnancy. The effects of COVID-19 and cost of living crises in many countries are leading to widening health inequalities 207 and this will further challenge obesity prevention interventions. Available resourcing for prevention interventions may become further constrained, requiring innovative solutions across agendas, with clear identification of co-benefits. For example, public health interventions for other diseases, such as dental caries or depression, or other societal concerns, such as urban congestion or climate change, may also act as obesity prevention strategies. Ultimately, to implement obesity prevention, societal changes are needed in terms of urban planning, social structures and health-care access.
Future high-quality paediatric obesity research can be enabled through strategies that support data sharing, which avoids research waste and bias, and enables new research questions to be addressed. Such approaches require leadership, careful engagement of multiple research teams, and resourcing. Four national or regional level paediatric weight registries exist 208 , 209 , 210 , 211 , which are all based in North America or Europe. Such registries should be established in other countries, especially in low-resource settings, even if challenging 208 . Another data-sharing approach is through individual participant data meta-analyses of intervention trials, which can include prospectively collected data 212 and are quite distinct from systematic reviews of aggregate data. Two recent examples are the Transforming Obesity Prevention in Childhood (TOPCHILD) Collaboration, which includes early interventions to prevent obesity in the first 2 years of life 213 , and the Eating Disorders in Weight-Related Therapy (EDIT) Collaboration, which aims to identify characteristics of individuals or trials that increase or protect against eating disorder risk following obesity treatment 214 . Formal data linkage studies, especially those joining up routine administrative datasets, enable longer-term and broader outcome measures to be assessed than is possible with standard clinical or public health intervention studies.
Collaborative research will also be enhanced through the use of agreed core outcome sets, supporting data harmonization. The Edmonton Obesity Staging System – Paediatric 215 is one option for paediatric obesity treatment. A core outcome set for early intervention trials to prevent obesity in childhood (COS-EPOCH) has been recently established 216 . These efforts incorporate a balance between wanting and needing to share data and adhering to privacy protection regulations. Objective end points are ideal, including directly measured physical activity and body composition.
Collaborative efforts and a systems approach are paramount to understand, prevent and manage child and adolescent obesity. Research funding and health policies should focus on feasible, effective and equitable interventions.
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 https://doi.org/10.1016/S0140-6736(17)32129-3 (2017).
Article Google Scholar
Popkin, B. M., Corvalan, C. & Grummer-Strawn, L. M. Dynamics of the double burden of malnutrition and the changing nutrition reality. Lancet 395 , 65–74 (2020).
Article PubMed Google Scholar
Kompaniyets, L. et al. Underlying medical conditions associated with severe COVID-19 illness among children. JAMA Netw. Open 4 , e2111182 (2021).
Article PubMed PubMed Central Google Scholar
Griffiths, L. J., Parsons, T. J. & Hill, A. J. Self‐esteem and quality of life in obese children and adolescents: a systematic review. Int. J. Pediatr. Obes. 5 , 282–304 (2010).
Buttitta, M., Iliescu, C., Rousseau, A. & Guerrien, A. Quality of life in overweight and obese children and adolescents: a literature review. Qual. Life Res. 23 , 1117–1139 (2014).
Hayes, A. et al. Early childhood obesity: association with healthcare expenditure in Australia. Obesity 24 , 1752–1758 (2016).
Marcus, C., Danielsson, P. & Hagman, E. Pediatric obesity – long-term consequences and effect of weight loss. J. Intern. Med. 292 , 870–891 (2022).
Berthoud, H. R., Morrison, C. D. & Münzberg, H. The obesity epidemic in the face of homeostatic body weight regulation: what went wrong and how can it be fixed? Physiol. Behav. 222 , 112959 (2020).
Article CAS PubMed PubMed Central Google Scholar
World Health Organization. Report of the commission on ending childhood obesity. WHO https://www.who.int/publications/i/item/9789241510066 (2016). This report from the WHO on approaches to childhood and adolescent obesity has six main recommendations for governments, covering food and physical activity, age-based settings and provision of weight management for those with obesity.
O’Connor, E. A. et al. Screening for obesity and intervention for weight management in children and adolescents: evidence report and systematic review for the US Preventive Services Task Force. JAMA 317 , 2427–2444 (2017).
Inge, T. H. et al. Five-year outcomes of gastric bypass in adolescents as compared with adults. N. Engl. J. Med. 380 , 2136–2145 (2019).
Weghuber, D. et al. Once-weekly semaglutide in adolescents with obesity. N. Engl. J. Med. https://doi.org/10.1056/NEJMoa2208601 (2022). To our knowledge, the first RCT of semaglutide 2.4 mg, administered weekly by subcutaneous injection, in adolescents with obesity.
World Health Organization. Report of the Commission on Ending Childhood Obesity: Implementation Plan: Executive Summary (WHO, 2017).
Hillier-Brown, F. C. et al. A systematic review of the effectiveness of individual, community and societal level interventions at reducing socioeconomic inequalities in obesity amongst children. BMC Public Health 14 , 834 (2014).
World Health Organization. Obesity. WHO https://www.who.int/health-topics/obesity#tab=tab_1 (2023).
Mei, Z. et al. Validity of body mass index compared with other body-composition screening indexes for the assessment of body fatness in children and adolescents. Am. J. Clin. Nutr. 75 , 978–985 (2002).
Article CAS PubMed Google Scholar
World Health Organization. Child growth standards. WHO https://www.who.int/tools/child-growth-standards/standards (2006).
World Health Organization. Growth reference data for 5–19 years. WHO https://www.who.int/tools/growth-reference-data-for-5to19-years (2007).
National Center for Health Statistics. CDC growth charts. Centers for Disease Control and Prevention http://www.cdc.gov/growthcharts/ (2022).
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).
Di Cesare, M. et al. The epidemiological burden of obesity in childhood: a worldwide epidemic requiring urgent action. BMC Med. 17 , 212 (2019).
Swinburn, B., Egger, G. & Raza, F. Dissecting obesogenic environments: the development and application of a framework for identifying and prioritizing environmental interventions for obesity. Prev. Med. 29 , 563–570 (1999).
Ford, N. D., Patel, S. A. & Narayan, K. V. Obesity in low-and middle-income countries: burden, drivers, and emerging challenges. Annu. Rev. Public Health 38 , 145–164 (2017).
Shah, B., Tombeau Cost, K., Fuller, A., Birken, C. S. & Anderson, L. N. Sex and gender differences in childhood obesity: contributing to the research agenda. BMJ Nutr. Prev. Health 3 , 387–390 (2020).
Public Health England. Research and analysis: differences in child obesity by ethnic group. GOV.UK https://www.gov.uk/government/publications/differences-in-child-obesity-by-ethnic-group/differences-in-child-obesity-by-ethnic-group#data (2019).
Cole, T. J. & Lobstein, T. Extended international (IOTF) body mass index cut‐offs for thinness, overweight and obesity. Pediatr. Obes. 7 , 284–294 (2012).
Kelly, A. S. et al. Severe obesity in children and adolescents: identification, associated health risks, and treatment approaches: a scientific statement from the American Heart Association. Circulation 128 , 1689–1712 (2013).
Garnett, S. P., Baur, L. A., Jones, A. M. & Hardy, L. L. Trends in the prevalence of morbid and severe obesity in Australian children aged 7–15 years, 1985-2012. PLoS ONE 11 , e0154879 (2016).
Spinelli, A. et al. Prevalence of severe obesity among primary school children in 21 European countries. Obes. Facts 12 , 244–258 (2019).
Twig, G. et al. Body-Mass Index in 2.3 million adolescents and cardiovascular death in adulthood. N. Engl. J. Med. 374 , 2430–2440 (2016).
González-Muniesa, P. et al. Obesity. Nat. Rev. Dis. Primers 3 , 17034 (2017).
Geserick, M. et al. Acceleration of BMI in early childhood and risk of sustained obesity. N. Engl. J. Med. 379 , 1303–1312 (2018).
Larqué, E. et al. From conception to infancy – early risk factors for childhood obesity. Nat. Rev. Endocrinol. 15 , 456–478 (2019).
Barker, D. J. Fetal origins of coronary heart disease. Br. Med. J. 311 , 171–174 (1995).
Article CAS Google Scholar
Gluckman, P. D., Hanson, M. A., Cooper, C. & Thornburg, K. L. Effect of in utero and early-life conditions on adult health and disease. N. Engl. J. Med. 359 , 61–73 (2008).
Philips, E. M. et al. Changes in parental smoking during pregnancy and risks of adverse birth outcomes and childhood overweight in Europe and North America: an individual participant data meta-analysis of 229,000 singleton births. PLoS Med. 17 , e1003182 (2020).
Voerman, E. et al. Maternal body mass index, gestational weight gain, and the risk of overweight and obesity across childhood: an individual participant data meta-analysis. PLoS Med. 16 , e1002744 (2019). Individual participant data meta-analysis of >160,000 mothers and their children on the associations of maternal BMI and gestational weight gain and childhood overweight or obesity.
McIntyre, H. D. et al. Gestational diabetes mellitus. Nat. Rev. Dis. Primers 5 , 47 (2019).
Oken, E. & Gillman, M. W. Fetal origins of obesity. Obes. Res. 11 , 496–506 (2003).
Hughes, A. R., Sherriff, A., Ness, A. R. & Reilly, J. J. Timing of adiposity rebound and adiposity in adolescence. Pediatrics 134 , e1354–e1361 (2014).
Rolland-Cachera, M. F. et al. Tracking the development of adiposity from one month of age to adulthood. Ann. Hum. Biol. 14 , 219–229 (1987).
Koletzko, B. et al. Prevention of childhood obesity: a position paper of the Global Federation of International Societies of Paediatric Gastroenterology, Hepatology and Nutrition (FISPGHAN). J. Pediatr. Gastroenterol. Nutr. 70 , 702–710 (2020).
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).
Cope, M. B. & Allison, D. B. Critical review of the World Health Organization’s (WHO) 2007 report on ‘evidence of the long‐term effects of breastfeeding: systematic reviews and meta‐analysis’ with respect to obesity. Obes. Rev. 9 , 594–605 (2008).
Totzauer, M. et al. Different protein intake in the first year and its effects on adiposity rebound and obesity throughout childhood: 11 years follow‐up of a randomized controlled trial. Pediatr. Obes. 17 , e12961 (2022).
Deren, K. et al. Consumption of sugar-sweetened beverages in paediatric age: a position paper of the European academy of paediatrics and the European Childhood Obesity Group. Ann. Nutr. Metab. 74 , 296–302 (2019).
Felső, R., Lohner, S., Hollódy, K., Erhardt, É. & Molnár, D. Relationship between sleep duration and childhood obesity: systematic review including the potential underlying mechanisms. Nutr. Metab. Cardiovasc. Dis. 27 , 751–761 (2017).
Farooq, A. et al. Longitudinal changes in moderate‐to‐vigorous‐intensity physical activity in children and adolescents: a systematic review and meta‐analysis. Obes. Rev. 21 , e12953 (2020).
Mahumud, R. A. et al. Association of dietary intake, physical activity, and sedentary behaviours with overweight and obesity among 282,213 adolescents in 89 low and middle income to high-income countries. Int. J. Obes. 45 , 2404–2418 (2021).
Ballon, M. et al. Socioeconomic inequalities in weight, height and body mass index from birth to 5 years. Int. J. Obes. 42 , 1671–1679 (2018).
Buoncristiano, M. et al. Socioeconomic inequalities in overweight and obesity among 6- to 9-year-old children in 24 countries from the World Health Organization European region. Obes. Rev. 22 , e13213 (2021).
Jiwani, S. S. et al. The shift of obesity burden by socioeconomic status between 1998 and 2017 in Latin America and the Caribbean: a cross-sectional series study. Lancet Glob. Health 7 , e1644–e1654 (2019).
Monteiro, C. A., Conde, W. L., Lu, B. & Popkin, B. M. Obesity and inequities in health in the developing world. Int. J. Obes. 28 , 1181–1186 (2004).
Guo, S. S. & Chumlea, W. C. Tracking of body mass index in children in relation to overweight in adulthood. Am. J. Clin. Nutr. 70 , 145S–148S (1999).
Aarestrup, J. et al. Birthweight, childhood overweight, height and growth and adult cancer risks: a review of studies using the Copenhagen School Health Records Register. Int. J. Obes. 44 , 1546–1560 (2020).
Eslam, M. et al. Defining paediatric metabolic (dysfunction)-associated fatty liver disease: an international expert consensus statement. Lancet Gastroenterol. Hepatol. 6 , 864–873 (2021).
Daniels, S. R. et al. Overweight in children and adolescents: pathophysiology, consequences, prevention, and treatment. Circulation 111 , 1999–2012 (2005).
Cioana, M. et al. The prevalence of obesity among children with type 2 diabetes: a systematic review and meta-analysis. JAMA Netw. Open 5 , e2247186 (2022).
Gepstein, V. & Weiss, R. Obesity as the main risk factor for metabolic syndrome in children. Front. Endocrinol. 10 , 568 (2019).
Kuvat, N., Tanriverdi, H. & Armutcu, F. The relationship between obstructive sleep apnea syndrome and obesity: a new perspective on the pathogenesis in terms of organ crosstalk. Clin. Respir. J. 14 , 595–604 (2020).
Baker, J. L., Olsen, L. W. & Sorensen, T. I. Childhood body-mass index and the risk of coronary heart disease in adulthood. N. Engl. J. Med. 357 , 2329–2337 (2007).
Bjerregaard, L. G. et al. Change in overweight from childhood to early adulthood and risk of type 2 diabetes. N. Engl. J. Med. 378 , 1302–1312 (2018).
Kelsey, M. M., Zaepfel, A., Bjornstad, P. & Nadeau, K. J. Age-related consequences of childhood obesity. Gerontology 60 , 222–228 (2014).
Sharma, V. et al. A systematic review and meta-analysis estimating the population prevalence of comorbidities in children and adolescents aged 5 to 18 years. Obes. Rev. 20 , 1341–1349 (2019).
Lobstein, T. & Jackson-Leach, R. Planning for the worst: estimates of obesity and comorbidities in school-age children in 2025. Pediatr. Obes. 11 , 321–325 (2016).
Berthoud, H. R., Münzberg, H. & Morrison, C. D. Blaming the brain for obesity: integration of hedonic and homeostatic mechanisms. Gastroenterology 152 , 1728–1738 (2017).
Devoto, F. et al. Hungry brains: a meta-analytical review of brain activation imaging studies on food perception and appetite in obese individuals. Neurosci. Biobehav. Rev. 94 , 271–285 (2018).
Blum, W. F., Englaro, P., Attanasio, A. M., Kiess, W. & Rascher, W. Human and clinical perspectives on leptin. Proc. Nutr. Soc. 57 , 477–485 (1998).
Friedman, J. M. Leptin and the endocrine control of energy balance. Nat. Metab. 1 , 754–764 (2019).
Kühnen, P. et al. Proopiomelanocortin deficiency treated with a melanocortin-4 receptor agonist. N. Engl. J. Med. 375 , 240–246 (2016).
Clément, K. et al. Efficacy and safety of setmelanotide, an MC4R agonist, in individuals with severe obesity due to LEPR or POMC deficiency: single-arm, open-label, multicentre, phase 3 trials. Lancet Diabetes Endocrinol. 8 , 960–970 (2020).
Rosen, E. D. & Spiegelman, B. M. What we talk about when we talk about fat. Cell 156 , 20–44 (2014).
Fischer-Posovszky, P., Roos, J., Zoller, V. & Wabitsch, M. in Pediatric Obesity: Etiology, Pathogenesis and Treatment (ed. Freemark, M. S.) 81–93 (Springer, 2018).
Hammarstedt, A., Gogg, S., Hedjazifar, S., Nerstedt, A. & Smith, U. Impaired adipogenesis and dysfunctional adipose tissue in human hypertrophic obesity. Physiol. Rev. 98 , 1911–1941 (2018).
Silventoinen, K. et al. Genetic and environmental effects on body mass index from infancy to the onset of adulthood: an individual-based pooled analysis of 45 twin cohorts participating in the collaborative project of development of anthropometrical measures in twins (CODATwins) study. Am. J. Clin. Nutr. 104 , 371–379 (2016).
Silventoinen, K. et al. Differences in genetic and environmental variation in adult BMI by sex, age, time period, and region: an individual-based pooled analysis of 40 twin cohorts. Am. J. Clin. Nutr. 106 , 457–466 (2017).
Yengo, L. et al. Meta-analysis of genome-wide association studies for height and body mass index in approximately 700000 individuals of European ancestry. Hum. Mol. Genet. 27 , 3641–3649 (2018).
Vogelezang, S. et al. Novel loci for childhood body mass index and shared heritability with adult cardiometabolic traits. PLoS Genet. 16 , e1008718 (2020).
Bradfield, J. P. et al. A trans-ancestral meta-analysis of genome-wide association studies reveals loci associated with childhood obesity. Hum. Mol. Genet. 28 , 3327–3338 (2019). To our knowledge, currently the largest genome-wide association study meta-analysis on childhood obesity in >13,000 individuals with obesity and >15,500 controls.
Couto Alves, A. et al. GWAS on longitudinal growth traits reveals different genetic factors influencing infant, child, and adult BMI. Sci. Adv. 5 , eaaw3095 (2019).
Ding, X. et al. Genome-wide screen of DNA methylation identifies novel markers in childhood obesity. Gene 566 , 74–83 (2015).
Huang, R. C. et al. Genome-wide methylation analysis identifies differentially methylated CpG loci associated with severe obesity in childhood. Epigenetics 10 , 995–1005 (2015).
Rzehak, P. et al. DNA-methylation and body composition in preschool children: epigenome-wide-analysis in the European Childhood Obesity Project (CHOP)-Study. Sci. Rep. 7 , 14349 (2017).
Alfano, R. et al. Perspectives and challenges of epigenetic determinants of childhood obesity: a systematic review. Obes. Rev. 23 , e13389 (2022).
Vehmeijer, F. O. L. et al. DNA methylation and body mass index from birth to adolescence: meta-analyses of epigenome-wide association studies. Genome Med. 12 , 105 (2020). Meta-analysis of epigenome-wide association studies of childhood BMI in >4,000 children.
Richmond, R. C. et al. DNA methylation and BMI: investigating identified methylation sites at HIF3A in a causal framework. Diabetes 65 , 1231–1244 (2016).
Wahl, S. et al. Epigenome-wide association study of body mass index, and the adverse outcomes of adiposity. Nature 541 , 81–86 (2017).
Kivimäki, M. et al. Substantial intergenerational increases in body mass index are not explained by the fetal overnutrition hypothesis: the Cardiovascular Risk in Young Finns Study. Am. J. Clin. Nutr. 86 , 1509–1514 (2007).
Whitaker, R. C., Wright, J. A., Pepe, M. S., Seidel, K. D. & Dietz, W. H. Predicting obesity in young adulthood from childhood and parental obesity. N. Engl. J. Med. 337 , 869–873 (1997).
Davey Smith, G., Steer, C., Leary, S. & Ness, A. Is there an intrauterine influence on obesity? Evidence from parent child associations in the Avon Longitudinal Study of Parents and Children (ALSPAC). Arch. Dis. Child. 92 , 876–880 (2007).
Fleten, C. et al. Parent-offspring body mass index associations in the Norwegian Mother and Child Cohort Study: a family-based approach to studying the role of the intrauterine environment in childhood adiposity. Am. J. Epidemiol. 176 , 83–92 (2012).
Gaillard, R. et al. Childhood cardiometabolic outcomes of maternal obesity during pregnancy: the Generation R Study. Hypertension 63 , 683–691 (2014).
Lawlor, D. A. et al. Exploring the developmental overnutrition hypothesis using parental-offspring associations and FTO as an instrumental variable. PLoS Med. 5 , e33 (2008).
Patro, B. et al. Maternal and paternal body mass index and offspring obesity: a systematic review. Ann. Nutr. Metab. 63 , 32–41 (2013).
Sorensen, T. et al. Comparison of associations of maternal peri-pregnancy and paternal anthropometrics with child anthropometrics from birth through age 7 y assessed in the Danish National Birth Cohort. Am. J. Clin. Nutr. 104 , 389–396 (2016).
Styne, D. M. et al. Pediatric obesity – assessment, treatment, and prevention: an Endocrine Society Clinical Practice guideline. J. Clin. Endocrinol. Metab. 102 , 709–757 (2017).
National Institute for Health and Care Excellence. Obesity: identification, assessment and managenent: clinical guideline [CG189]. NICE https://www.nice.org.uk/guidance/cg189 (2022). A high quality clinical practice guideline for obesity management.
Barlow, S. E. Expert Committee Expert committee recommendations regarding the prevention, assessment, and treatment of child and adolescent overweight and obesity: summary report. Pediatrics 120 (Suppl. 4), S164–S192 (2007).
Canadian Task Force on Preventive Health Care. Recommendations for growth monitoring, and prevention and management of overweight and obesity in children and youth in primary care. Can. Med. Assoc. J. 187 , 411–421 (2015).
US Preventive Services Task Force. Screening for obesity in children and adolescents: US Preventive Services Task Force recommendation statement. JAMA 317 , 2417–2426 (2017).
McConnell-Nzunga, J. et al. Classification of obesity varies between body mass index and direct measures of body fat in boys and girls of Asian and European ancestry. Meas. Phys. Educ. Exerc. Sci. 22 , 154–166 (2018).
Reinehr, T. et al. Definable somatic disorders in overweight children and adolescents. J. Pediatr. 150 , 618–622.e5 (2007).
Reinehr, T. Thyroid function in the nutritionally obese child and adolescent. Curr. Opin. Pediatr. 23 , 415–420 (2011).
Kohlsdorf, K. et al. Early childhood BMI trajectories in monogenic obesity due to leptin, leptin receptor, and melanocortin 4 receptor deficiency. Int. J. Obes. 42 , 1602–1609 (2018).
Armstrong, S. et al. Physical examination findings among children and adolescents with obesity: an evidence-based review. Pediatrics 137 , e20151766 (2016).
Reinehr, T. & Roth, C. L. Is there a causal relationship between obesity and puberty? Lancet Child Adolesc. Health 3 , 44–54 (2019).
Garnett, S. P., Baur, L. A. & Cowell, C. T. Waist-to-height ratio: a simple option for determining excess central adiposity in young people. Int. J. Obes. 32 , 1028–1030 (2008).
Maffeis, C., Banzato, C., Talamini, G. & Obesity Study Group of the Italian Society of Pediatric Endocrinology and Diabetology. Waist-to-height ratio, a useful index to identify high metabolic risk in overweight children. J. Pediatr. 152 , 207–213.e2 (2008).
Hampl, S. E. et al. Clinical practice guideline for the evaluation and treatment of children and adolescents with obesity. Pediatrics 151 , e2022060640 (2023). A new, comprehensive clinical practice guideline outlining current recommendations on assessment and treatment of children and adolescents with obesity.
Reinehr, T. et al. Comparison of cardiovascular risk factors between children and adolescents with classes III and IV obesity: findings from the APV cohort. Int. J. Obes. 45 , 1061–1073 (2021).
Reinehr, T. Metabolic syndrome in children and adolescents: a critical approach considering the interaction between pubertal stage and insulin resistance. Curr. Diabetes Rep. 16 , 8 (2016).
Zeitler, P. et al. ISPAD Clinical Practice Consensus Guidelines 2018: type 2 diabetes mellitus in youth. Pediatr. Diabetes 19 , 28–46 (2018).
Ibáñez, L. et al. An International Consortium update: pathophysiology, diagnosis, and treatment of polycystic ovarian syndrome in adolescence. Horm. Res. Paediatr. 88 , 371–395 (2017).
Brockmann, P. E., Schaefer, C., Poets, A., Poets, C. F. & Urschitz, M. S. Diagnosis of obstructive sleep apnea in children: a systematic review. Sleep Med. Rev. 17 , 331–340 (2013).
Taylor, E. D. et al. Orthopedic complications of overweight in children and adolescents. Pediatrics 117 , 2167–2174 (2006).
Winck, A. D. et al. Effects of obesity on lung volume and capacity in children and adolescents: a systematic review. Rev. Paul. Pediatr. 34 , 510–517 (2016).
PubMed PubMed Central Google Scholar
Jebeile, H., Lister, N., Baur, L., Garnett, S. & Paxton, S. J. Eating disorder risk in adolescents with obesity. Obes. Rev. 22 , e13173 (2021).
Quek, Y. H., Tam, W. W. S., Zhang, M. W. B. & Ho, R. C. M. Exploring the association between childhood and adolescent obesity and depression: a meta-analysis. Obes. Rev. 18 , 742–754 (2017).
World Health Organization. Consideration of the Evidence on Childhood Obesity for the Commission on Ending Childhood Obesity . Report of the Ad Hoc Working Group on Science and Evidence for Ending Childhood Obesity (WHO, 2016).
Pickett, K. et al. The Child of the North: building a fairer future after COVID-19. The Northern Health Science Alliance and N8 Research Partnership https://www.thenhsa.co.uk/app/uploads/2022/01/Child-of-the-North-Report-FINAL-1.pdf (2021).
Bronfenbrenner, U. Toward an experimental ecology of human development. Am. Psychol. 32 , 513–531 (1977).
Nuffield Council on Bioethics. Public Health: Ethical Issues (Nuffield Council on Bioethics, 2007).
Lorenc, T., Petticrew, M., Welch, V. & Tugwell, P. What types of interventions generate inequalities? Evidence from systematic reviews. J. Epidemiol. Community Health 67 , 190–193 (2013).
Adams, J., Mytton, O., White, M. & Monsivais, P. Why are some population interventions for diet and obesity more equitable and effective than others? The role of individual agency. PLoS Med. 13 , e1001990 (2016).
Backholer, K. et al. A framework for evaluating the impact of obesity prevention strategies on socioeconomic inequalities in weight. Am. J. Public Health 104 , e43–e50 (2014).
McGill, R. et al. Are interventions to promote healthy eating equally effective for all? Systematic review of socioeconomic inequalities in impact. BMC Public Health 15 , 457 (2015).
Brown, T. et al. Interventions for preventing obesity in children. Cochrane Database Syst. Rev. 7 , Cd001871 (2019). A Cochrane review involving 153 RCTs of diet and/or physical activity interventions to prevent obesity in children and adolescents, highlighting varying effectiveness of interventions in different age groups.
PubMed Google Scholar
Le, L. K.-D. et al. Prevention of high body mass index and eating disorders: a systematic review and meta-analysis. Eat. Weight Disord. 27 , 2989–3003 (2022).
Nobles, J., Summerbell, C., Brown, T., Jago, R. & Moore, T. A secondary analysis of the childhood obesity prevention Cochrane Review through a wider determinants of health lens: implications for research funders, researchers, policymakers and practitioners. Int. J. Behav. Nutr. Phys. Act. 18 , 22 (2021).
Rai, K. K., Dogra, S. A., Barber, S., Adab, P. & Summerbell, C. A scoping review and systematic mapping of health promotion interventions associated with obesity in Islamic religious settings in the UK. Obes. Rev. 20 , 1231–1261 (2019).
World Health Organization. Nutrition Action in Schools: A Review of Evidence Related to the Nutrition-Friendly Schools Initiative (WHO, 2021).
Daly-Smith, A. et al. Using a multi-stakeholder experience-based design process to co-develop the Creating Active Schools Framework. Int. J. Behav. Nutr. Phys. Act. 17 , 13 (2020).
Tibbitts, B. et al. Considerations for individual-level versus whole-school physical activity interventions: stakeholder perspectives. Int. J. Environ. Res. Public Health https://doi.org/10.3390/ijerph18147628 (2021).
Askie, L. M. et al. Interventions commenced by early infancy to prevent childhood obesity-The EPOCH Collaboration: an individual participant data prospective meta-analysis of four randomized controlled trials. Pediatr. Obes. 15 , e12618 (2020). To our knowledge, the first prospective individual participant data meta-analysis showing that interventions commencing in late pregnancy or very early childhood are associated with healthier BMI z -score at age 18–24 months.
Seidler, A. L. et al. Examining the sustainability of effects of early childhood obesity prevention interventions: follow-up of the EPOCH individual participant data prospective meta-analysis. Pediatr. Obes. 17 , e12919 (2022).
Taylor, R. W. et al. Sleep, nutrition, and physical activity interventions to prevent obesity in infancy: follow-up of the prevention of overweight in infancy (POI) randomized controlled trial at ages 3.5 and 5 y. Am. J. Clin. Nutr. 108 , 228–236 (2018).
Mihrshahi, S. et al. A review of registered randomized controlled trials for the prevention of obesity in infancy. Int. J. Environ. Res. Public Health 18 , 2444 (2021).
Farooq, M. A. et al. Timing of the decline in physical activity in childhood and adolescence: Gateshead Millennium Cohort Study. Br. J. Sports Med. 52 , 1002–1006 (2018).
van Sluijs, E. M. F. et al. Physical activity behaviours in adolescence: current evidence and opportunities for intervention. Lancet 398 , 429–442 (2021).
Griffin, N. et al. A critique of the English national policy from a social determinants of health perspective using a realist and problem representation approach: the ‘Childhood Obesity: a plan for action’ (2016, 2018, 2019). BMC Public Health 21 , 2284 (2021).
Knai, C., Lobstein, T., Petticrew, M., Rutter, H. & Savona, N. England’s childhood obesity action plan II. Br. Med. J. 362 , k3098 (2018).
World Health Organization. WHO European Regional Obesity Report 2022 (WHO, 2022).
Zemrani, B., Gehri, M., Masserey, E., Knob, C. & Pellaton, R. A hidden side of the COVID-19 pandemic in children: the double burden of undernutrition and overnutrition. Int. J. Equity Health 20 , 44 (2021).
Alman, K. L. et al. Dietetic management of obesity and severe obesity in children and adolescents: a scoping review of guidelines. Obes. Rev. https://doi.org/10.1111/obr.13132 (2020).
Pfeiffle, S. et al. Current recommendations for nutritional management of overweight and obesity in children and adolescents: a structured framework. Nutrients https://doi.org/10.3390/nu11020362 (2019).
Scottish Intercollegiate Guidelines Network. Management of obesity. A National Clinical Guideline . SIGN 115 (SIGN, 2010).
Reinehr, T. et al. Two-year follow-up in 21,784 overweight children and adolescents with lifestyle intervention. Obesity 17 , 1196–1199 (2009).
Ells, L. J. et al. Interventions for treating children and adolescents with overweight and obesity: an overview of Cochrane reviews. Int. J. Obes. 42 , 1823–1833 (2018).
Al‐Khudairy, L. et al. Diet, physical activity and behavioural interventions for the treatment of overweight or obese adolescents aged 12 to 17 years. Cochrane Database Syst. Rev. 6 , CD012691 (2017). One of three Cochrane reviews looking at lifestyle treatment of paediatric obesity, in this case in adolescents, which identified 44 completed trials, finding low quality evidence of improvements in BMI and moderate quality evidence of improvements in weight.
Mead, E. et al. Diet, physical activity and behavioural interventions for the treatment of overweight or obese children from the age of 6 to 11 years. Cochrane Database Syst. Rev. 6 , CD012651 (2017). A Cochrane Review, involving 70 RCTs, showing that multicomponent behavioural interventions can lead to small, short-term reductions in BMI and related measures in children aged 6–11 years with obesity.
Ho, M. et al. Effectiveness of lifestyle interventions in child obesity: systematic review with meta-analysis. Pediatrics 130 , e1647–e1671 (2012). To our knowledge, the first systematic review of lifestyle interventions in children and adolescents with obesity to show improvements in cardiometabolic outcomes (LDL cholesterol, triglycerides, fasting insulin and blood pressure), as well as weight.
Clinical Practice Guideline Panel. Clinical practice guideline for multicomponent behavioral treatment of obesity and overweight in children and adolescents: current state of the evidence and research needs. American Psychological Association https://www.apa.org/obesity-guideline/clinical-practice-guideline.pdf (2018).
Nowicka, P. & Flodmark, C. E. Family therapy as a model for treating childhood obesity: useful tools for clinicians. Clin. Child. Psychol. Psychiatry 16 , 129–145 (2011).
Wilfley, D. E. et al. Improving access and systems of care for evidence-based childhood obesity treatment: conference key findings and next steps. Obesity 25 , 16–29 (2017).
Amiri, P. et al. Does motivational interviewing improve the weight management process in adolescents? A systematic review and meta-analysis. Int. J. Behav. Med. 29 , 78–103 (2022).
Kao, T. A., Ling, J., Hawn, R. & Vu, C. The effects of motivational interviewing on children’s body mass index and fat distributions: a systematic review and meta-analysis. Obes. Rev. 22 , e13308 (2021).
Hassapidou, M. et al. European Association for the Study of Obesity (EASO) position statement on medical nutrition therapy for the management of overweight and obesity in children and adolescents developed in collaboration with the European Federation of the Associations of Dietitians (EFAD). Obes. Facts https://doi.org/10.1159/000527540 (2022).
Hoelscher, D. M., Kirk, S., Ritchie, L. & Cunningham-Sabo, L. Position of the Academy of Nutrition and Dietetics: interventions for the prevention and treatment of pediatric overweight and obesity. J. Acad. Nutr. Diet. 113 , 1375–1394 (2013).
Hoare, J. K., Jebeile, H., Garnett, S. P. & Lister, N. B. Novel dietary interventions for adolescents with obesity: a narrative review. Pediatr. Obes. 16 , e12798 (2021).
Lister, N. et al. Nutritional adequacy of diets for adolescents with overweight and obesity: considerations for dietetic practice. Eur. J. Clin. Nutr. 71 , 646–651 (2017).
Andela, S. et al. Efficacy of very low-energy diet programs for weight loss: a systematic review with meta-analysis of intervention studies in children and adolescents with obesity. Obes. Rev. 20 , 871–882 (2019).
Srivastava, G. & Apovian, C. M. Current pharmacotherapy for obesity. Nat. Rev. Endocrinol. 14 , 12–24 (2018).
Apperley, L. J. et al. Childhood obesity: a review of current and future management options. Clin. Endocrinol. 96 , 288–301 (2022).
European Medicines Agency. Saxenda. European Medicines Agency https://www.ema.europa.eu/en/medicines/human/EPAR/saxenda (2022).
US Food and Drug Administration. FDA approves weight management drug for patients aged 12 and older. FDA https://www.fda.gov/drugs/news-events-human-drugs/fda-approves-weight-management-drug-patients-aged-12-and-older (2021).
Kelly, A. S. et al. A randomized, controlled trial of liraglutide for adolescents with obesity. N. Engl. J. Med. 382 , 2117–2128 (2020). To our knowledge, the first RCT of liraglutide, administered daily via subcutaneous injection, in adolescents with obesity.
US Food and Drug Administration. FDA approves novel, dual-targeted treatment for type 2 iabetes. FDA https://www.fda.gov/news-events/press-announcements/fda-approves-novel-dual-targeted-treatment-type-2-diabetes (2022).
Jastreboff, A. M. et al. Tirzepatide once weekly for the treatment of obesity. N. Engl. J. Med. 387 , 205–216 (2022).
Holst, J. J. & Rosenkilde, M. M. GIP as a therapeutic target in diabetes and obesity: insight from incretin co-agonists. J. Clin. Endocrinol. Metab. https://doi.org/10.1210/clinem/dgaa327 (2020).
US National Library of Medicine. ClinicalTrials.gov https://clinicaltrials.gov/ct2/show/study/NCT05260021 (2023).
Müller, T. D., Blüher, M., Tschöp, M. H. & DiMarchi, R. D. Anti-obesity drug discovery: advances and challenges. Nat. Rev. Drug Discov. 21 , 201–223 (2022).
Chalklin, C. G., Ryan Harper, E. G. & Beamish, A. J. Metabolic and bariatric surgery in adolescents. Curr. Obes. Rep. 10 , 61–69 (2021).
Albaugh, V. L. et al. Regulation of body weight: lessons learned from bariatric surgery. Mol. Metab. https://doi.org/10.1016/j.molmet.2022.101517 (2022).
Uhe, I. et al. Roux-en-Y gastric bypass, sleeve gastrectomy, or one-anastomosis gastric bypass? A systematic review and meta-analysis of randomized-controlled trials. Obesity 30 , 614–627 (2022).
Inge, T. H. et al. Long-term outcomes of bariatric surgery in adolescents with severe obesity (FABS-5+): a prospective follow-up analysis. Lancet Diabetes Endocrinol. 5 , 165–173 (2017).
Olbers, T. et al. Laparoscopic Roux-en-Y gastric bypass in adolescents with severe obesity (AMOS): a prospective, 5-year, Swedish nationwide study. Lancet Diabetes Endocrinol. https://doi.org/10.1016/S2213-8587(16)30424-7 (2017).
Pratt, J. S. et al. ASMBS pediatric metabolic and bariatric surgery guidelines, 2018. Surg. Obes. Relat. Dis. 14 , 882–901 (2018).
Jarvholm, K. et al. 5-year mental health and eating pattern outcomes following bariatric surgery in adolescents: a prospective cohort study. Lancet Child Adolesc. Health 4 , 210–219 (2020).
Van Der Heijden, L., Feskens, E. & Janse, A. Maintenance interventions for overweight or obesity in children: a systematic review and meta‐analysis. Obes. Rev. 19 , 798–809 (2018).
Park, J., Park, M.-J. & Seo, Y.-G. Effectiveness of information and communication technology on obesity in childhood and adolescence: systematic review and meta-analysis. J. Med. Internet Res. 23 , e29003 (2021).
Brissman, M., Beamish, A. J., Olbers, T. & Marcus, C. Prevalence of insufficient weight loss 5 years after Roux-en-Y gastric bypass: metabolic consequences and prediction estimates: a prospective registry study. BMJ Open 11 , e046407 (2021).
El Ansari, W. & Elhag, W. Weight regain and insufficient weight loss after bariatric surgery: definitions, prevalence, mechanisms, predictors, prevention and management strategies, and knowledge gaps – a scoping review. Obes. Surg. 31 , 1755–1766 (2021).
World Health Organization Regional Office for Europe. Weight Bias and Obesity Stigma: Considerations for the WHO European Region (WHO, 2017).
Puhl, R. M. & Latner, J. D. Stigma, obesity, and the health of the nation’s children. Psychol. Bull. 133 , 557–580 (2007).
Black, W. R. et al. Health-related quality of life across recent pediatric obesity classification recommendations. Children 8 , 303 (2021).
Finne, E., Reinehr, T., Schaefer, A., Winkel, K. & Kolip, P. Changes in self-reported and parent-reported health-related quality of life in overweight children and adolescents participating in an outpatient training: findings from a 12-month follow-up study. Health Qual. Life Outcomes 11 , 1 (2013).
Hill, A. J. Obesity in children and the ‘myth of psychological maladjustment’: self-esteem in the spotlight. Curr. Obes. Rep. 6 , 63–70 (2017).
McGregor, S., McKenna, J., Gately, P. & Hill, A. J. Self‐esteem outcomes over a summer camp for obese youth. Pediatr. Obes. 11 , 500–505 (2016).
Jansen, P., Mensah, F., Clifford, S., Nicholson, J. & Wake, M. Bidirectional associations between overweight and health-related quality of life from 4–11 years: longitudinal study of Australian children. Int. J. Obes. 37 , 1307–1313 (2013).
Mannan, M., Mamun, A., Doi, S. & Clavarino, A. Is there a bi-directional relationship between depression and obesity among adult men and women? Systematic review and bias-adjusted meta analysis. Asian J. Psychiatr. 21 , 51–66 (2016).
Lindberg, L., Hagman, E., Danielsson, P., Marcus, C. & Persson, M. Anxiety and depression in children and adolescents with obesity: a nationwide study in Sweden. BMC Med. 18 , 30 (2020).
Jebeile, H. et al. Association of pediatric obesity treatment, including a dietary component, with change in depression and anxiety: a systematic review and meta-analysis. JAMA Pediatr. 173 , e192841 (2019).
Gow, M. L. et al. Pediatric obesity treatment, self‐esteem, and body image: a systematic review with meta‐analysis. Pediatr. Obes. 15 , e12600 (2020).
Jebeile, H. et al. Treatment of obesity, with a dietary component, and eating disorder risk in children and adolescents: a systematic review with meta-analysis. Obes. Rev. 20 , 1287–1298 (2019). To our knowledge, the first systematic review to show that structured and professionally led weight management interventions in children and adolescents with obesity are associated with reductions in eating disorder risk and symptoms.
Kjeldbjerg, M. L. & Clausen, L. Prevalence of binge-eating disorder among children and adolescents: a systematic review and meta-analysis. Eur. Child Adolesc. Psychiatry https://doi.org/10.1007/s00787-021-01850-2 (2021).
Patton, G. C., Selzer, R., Coffey, C., Carlin, J. B. & Wolfe, R. Onset of adolescent eating disorders: population based cohort study over 3 years. BMJ 318 , 765–768 (1999).
Cortese, S. The association between ADHD and obesity: intriguing, progressively more investigated, but still puzzling. Brain Sci. 9 , 256 (2019).
Griffiths, L. J., Dezateux, C. & Hill, A. Is obesity associated with emotional and behavioural problems in children? Findings from the Millennium Cohort Study. Int. J. Pediatr. Obes. 6 , e423–e432 (2011).
Harrist, A. W. et al. The social and emotional lives of overweight, obese, and severely obese children. Child. Dev. 87 , 1564–1580 (2016).
Van Geel, M., Vedder, P. & Tanilon, J. Are overweight and obese youths more often bullied by their peers? A meta-analysis on the relation between weight status and bullying. Int. J. Obes. 38 , 1263–1267 (2014).
Albuquerque, D., Nóbrega, C., Manco, L. & Padez, C. The contribution of genetics and environment to obesity. Br. Med. Bull. 123 , 159–173 (2017).
Rancourt, D. & McCullough, M. B. Overlap in eating disorders and obesity in adolescence. Curr. Diabetes Rep. 15 , 78 (2015).
House, E. T. et al. Identifying eating disorders in adolescents and adults with overweight or obesity: a systematic review of screening questionnaires. Int. J. Eat. Disord. 55 , 1171–1193 (2022).
Lister, N. B., Baur, L. A., Paxton, S. J. & Jebeile, H. Contextualising eating disorder concerns for paediatric obesity treatment. Curr. Obes. Rep. 10 , 322–331 (2021).
Hagman, E. et al. Effect of an interactive mobile health support system and daily weight measurements for pediatric obesity treatment, a 1-year pragmatical clinical trial. Int. J. Obes. 46 , 1527–1533 (2022).
Swinburn, B. A. et al. The global syndemic of obesity, undernutrition, and climate change: The Lancet commission report. Lancet 393 , 791–846 (2019).
Whitehead, M., Taylor-Robinson, D. & Barr, B. Poverty, health, and covid-19. Br. Med. J. 372 , n376 (2021).
Morrison, K. M. et al. The CANadian Pediatric Weight Management Registry (CANPWR): lessons learned from developing and initiating a national, multi-centre study embedded in pediatric clinical practice. BMC Pediatr. 18 , 237 (2018).
Kirk, S. et al. Establishment of the pediatric obesity weight evaluation registry: a national research collaborative for identifying the optimal assessment and treatment of pediatric obesity. Child. Obes. 13 , 9–17 (2017).
Hagman, E., Danielsson, P., Lindberg, L. & Marcus, C., BORIS Steering Committee. Paediatric obesity treatment during 14 years in Sweden: lessons from the Swedish Childhood Obesity Treatment Register – BORIS. Pediatr. Obes. 15 , e12626 (2020).
Bohn, B. et al. Changing characteristics of obese children and adolescents entering pediatric lifestyle intervention programs in Germany over the last 11 years: an adiposity patients registry multicenter analysis of 65,453 children and adolescents. Obes. Facts 10 , 517–530 (2017).
Seidler, A. L. et al. A guide to prospective meta-analysis. BMJ 367 , l5342 (2019).
Hunter, K. E. et al. Transforming obesity prevention for children (TOPCHILD) collaboration: protocol for a systematic review with individual participant data meta-analysis of behavioural interventions for the prevention of early childhood obesity. BMJ Open 12 , e048166 (2022).
Lister, N. B. et al. Eating disorders in weight-related therapy (EDIT) collaboration: rationale and study design. Nutr. Res. Rev. https://doi.org/10.1017/S0954422423000045 (2023).
Hadjiyannakis, S. et al. Obesity class versus the Edmonton Obesity Staging System for Pediatrics to define health risk in childhood obesity: results from the CANPWR cross-sectional study. Lancet Child Adolesc. Health 3 , 398–407 (2019).
Brown, V. et al. Core outcome set for early intervention trials to prevent obesity in childhood (COS-EPOCH): agreement on “what” to measure. Int. J. Obes. 46 , 1867–1874 (2022). A stakeholder-informed study that identified the minimum outcomes recommended for collecting and reporting in obesity prevention trials in early childhood.
Han, J. C., Lawlor, D. A. & Kimm, S. Y. Childhood obesity. Lancet 375 , 1737–1748 (2010).
Shin, A. C., Zheng, H. & Berthoud, H. R. An expanded view of energy homeostasis: neural integration of metabolic, cognitive, and emotional drives to eat. Physiol. Behav. 97 , 572–580 (2009).
Lennerz, B., Wabitsch, M. & Eser, K. Ätiologie und genese [German]. Berufl. Rehabil. 1 , 14 (2014).
Pont, S. J., Puhl, R., Cook, S. R. & Slusser, W. Stigma experienced by children and adolescents with obesity. Pediatrics 140 , e20173034 (2017).
Talumaa, B., Brown, A., Batterham, R. L. & Kalea, A. Z. Effective strategies in ending weight stigma in healthcare. Obes. Rev. 23 , e13494 (2022).
Rubino, F. et al. Joint international consensus statement for ending stigma of obesity. Nat. Med. 26 , 485–497 (2020).
Authors and affiliations.
Children’s Hospital Westmead Clinical School, Sydney Medical School, The University of Sydney, Sydney, New South Wales, Australia
Natalie B. Lister & Louise A. Baur
Institute of Endocrinology and Diabetes, The Children’s Hospital at Westmead, Sydney, New South Wales, Australia
Natalie B. Lister
Sydney School of Public Health, The University of Sydney, Sydney, New South Wales, Australia
Louise A. Baur
Weight Management Services, The Children’s Hospital at Westmead, Sydney, New South Wales, Australia
The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands
Janine F. Felix
Department of Paediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands
Institute of Health Sciences, School of Medicine, University of Leeds, Leeds, UK
Andrew J. Hill
Division of Paediatrics, Department of Clinical Science Intervention and Technology, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden
Vestische Hospital for Children and Adolescents Datteln, University of Witten/Herdecke, Datteln, Germany
Department of Sport and Exercise Sciences, Durham University, Durham, UK
Division of Paediatric Endocrinology and Diabetes, Department of Paediatrics and Adolescent Medicine, Ulm University Medical Centre, Ulm, Germany
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Introduction (L.A.B., J.F.F. and N.B.L.); Epidemiology (L.A.B. and J.F.F.); Mechanisms/pathophysiology (L.A.B., J.F.F., T.R. and M.W.); Diagnosis, screening and prevention (L.A.B., N.B.L., T.R., C.S. and M.W.); Management (L.A.B., N.B.L., A.J.H., C.M. and T.R.); Quality of life (L.A.B., N.B.L. and A.J.H.); Outlook (L.A.B., N.B.L., J.F.F., A.J.H., C.M., T.R., C.S. and M.W.); Overview of the Primer (L.A.B. and N.B.L.).
Correspondence to Louise A. Baur .
A.J.H. reports receiving payment for consultancy advice for Slimming World (UK). L.A.B. reports receiving honoraria for speaking in forums organized by Novo Nordisk in relation to management of adolescent obesity and the ACTION-Teens study, which is sponsored by Novo Nordisk. L.A.B. is the Australian lead of the study. T.R. received funding from the German Federal Ministry of Education and Research (BMBF; 01GI1120A/B) as part of the German Competence Network Obesity (Consortium ‘Youth with Extreme Obesity’). T.R. receives payment for consultancy advice related to pharmacological treatment of obesity from Novo Nordisk and Lilly, as well as honoraria for lectures in symposia organized by Novo Nordisk, Novartis and Merck. C.M. receives payments for consultancy advice and advisory board participation from Novo Nordisk, Oriflame Wellness, DeFaire AB and Itrim AB. C.M. also receives honoraria for speaking at meetings organized by Novo Nordisk and Astra Zeneca. C.M. is a shareholder and founder of Evira AB, a company that develops and sells systems for digital support for weight loss, and receives grants from Novo Nordisk for epidemiological studies of the effects of weight loss on future heath. M.W. received funding from the German Federal Ministry of Education and Research (BMBF; 01GI1120A/B) as part of the German Competence Network Obesity (Consortium ‘Youth with Extreme Obesity’). M.W. receives payment for consultancy advice related to pharmacological treatment of obesity from Novo Nordisk, Regeneron, Boehringer Ingelheim and LG Chem, as well as honoraria for speaking in symposia organized by Novo Nordisk, Rhythm Pharmaceuticals and Infectopharm. M.W. is principal investigator in phase II and phase III studies of setmelanotide sponsored by Rhythm Pharmaceuticals. N.B.L., J.F.F. and C.S. declare no competing interests.
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Lister, N.B., Baur, L.A., Felix, J.F. et al. Child and adolescent obesity. Nat Rev Dis Primers 9 , 24 (2023). https://doi.org/10.1038/s41572-023-00435-4
Accepted : 12 April 2023
Published : 18 May 2023
DOI : https://doi.org/10.1038/s41572-023-00435-4
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Overweight and Obesity Childhood Obesity
Childhood obesity is an increasingly serious problem in the United States. Nearly 1 in 5 children have obesity. Children with obesity are more likely to develop other serious health problems, including heart disease and type 2 diabetes. They are also more likely to suffer from anxiety, depression, and low self-esteem.
Obesity affects children from different backgrounds differently. About 1 in 4 Hispanic and non-Hispanic Black children have obesity. This is a challenge for parents, because addressing their child’s weight often means making lifestyle changes for the whole family.
All children should visit a healthcare provider every year for wellness check-ups that include monitoring of weight and calculation of body mass index (BMI) percentiles. Some of the best ways to prevent childhood obesity are to:
- Choose and prepare healthy foods that are lower in fat and have less calories. Use this guide (PDF, 136 KB) to help your family make smart food choices.
- Get regular physical activity. Your children should get at least 60 minutes of daily physical activity. Learn more about helping them get active every day.
- Reduce screen time. Try to limit screen time at home to 2 hours or less each day.
- Get enough good-quality sleep. NHLBI research has shown a relationship between lack of sleep and obesity that begins as early as infancy. See the recommended hours for children at every age.
The We Can! program offers a free, printable guide for parents, called Eat! Play! Grow! (PDF, 31.3 MB), on how to accomplish these goals.
Researchers agree that children inherit gene , the blueprints for our bodies, that make them more likely to have obesity. However, that genetic risk does not account for the increase in childhood obesity seen in recent years. A child’s community also has an impact on their weight, as the community can affect a family’s ability to make healthy choices. For example, fresh fruits and vegetables may be difficult to get, roads without sidewalks may make it unsafe to walk for exercise, or healthy meal choices in schools may be unavailable.
Most parents, however, do have some control over other risk factors that increase a child’s risk of having obesity. These include:
- Eating a high-calorie, low-nutrient diet
- Not getting enough good-quality sleep
- Too much screen time
- Too little physical activity
- Personal or family stress or trauma
BMI for children
BMI is used to determine whether your child’s weight fits the criteria for overweight or obesity. It is compared with growth charts for children who are the same age and sex as your child.
To learn your child’s percentile, use the Center for Disease Control and Prevention’s BMI percentile calculator for children and teens .
- Underweight is a BMI below the 5th percentile.
- Healthy weight is a BMI between the 5th to the 85th percentile.
- Overweight is a BMI between the 85th percentile and the 95th percentile.
- Obesity is a BMI in the 95th percentile or above.
Your child’s provider will monitor your child’s BMI and overall health during regular visits. They may talk to you about healthy lifestyle changes you can make as a family. If your child’s weight does not respond to those, your child’s provider may recommend medicine.
The good news for parents is that childhood obesity is reversible. Even small decreases in weight can have a positive impact on current health and future risk of health problems. The key is to learn the basics of maintaining a healthy weight, seek out resources in your community, and get both medical and mental health care for your child as needed.
Childhood Overweight & Obesity
Childhood obesity is a serious health problem in the United States where 1 in 5 children and adolescents are affected. Some groups of children are more affected than others, but all children are at risk of gaining weight that is higher than what is considered healthy.
Obesity is complex. Many factors can contribute to excess weight gain including behavior, genetics and taking certain medications. But societal and community factors also matter: child care and school environments, neighborhood design , access to healthy, affordable foods and beverages, and access to safe and convenient places for physical activity affect our ability to make healthy choices.
Every child deserves a healthy start in life. Learn what parents and caregivers can to do help prevent obesity at home , how healthcare systems can help families prevent and manage childhood obesity, and what strategies communities can use to support a healthy, active lifestyle for all.
Childhood Obesity Facts How many children in the United States have obesity?
Defining Childhood Overweight & Obesity How is childhood obesity measured?
Causes and Consequences What contributes to childhood obesity? What are the health risks?
Clinical Guidelines Resources for clinicians and healthcare providers on childhood obesity. Also see CDC’s Clinical Growth Charts .
Child and Teen BMI Calculator Use this calculator for children aged 2 through 19 years old.
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Childhood obesity is a serious medical condition that affects children and adolescents. It's particularly troubling because the extra pounds often start children on the path to health problems that were once considered adult problems — diabetes, high blood pressure and high cholesterol. Childhood obesity can also lead to poor self-esteem and depression.
One of the best strategies to reduce childhood obesity is to improve the eating and exercise habits of your entire family. Treating and preventing childhood obesity helps protect your child's health now and in the future.
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Not all children carrying extra pounds are overweight. Some children have larger than average body frames. And children normally carry different amounts of body fat at the various stages of development. So you might not know by how your child looks if weight is a health concern.
The body mass index (BMI), which provides a guideline of weight in relation to height, is the accepted measure of overweight and obesity. Your child's doctor can use growth charts, the BMI and, if necessary, other tests to help you figure out if your child's weight could pose health problems.
When to see a doctor
If you're worried that your child is putting on too much weight, talk to his or her doctor. The doctor will consider your child's history of growth and development, your family's weight-for-height history, and where your child lands on the growth charts. This can help determine if your child's weight is in an unhealthy range.
Lifestyle issues — too little activity and too many calories from food and drinks — are the main contributors to childhood obesity. But genetic and hormonal factors might play a role as well.
Many factors — usually working in combination — increase your child's risk of becoming overweight:
- Diet. Regularly eating high-calorie foods, such as fast foods, baked goods and vending machine snacks, can cause your child to gain weight. Candy and desserts also can cause weight gain, and more and more evidence points to sugary drinks, including fruit juices and sports drinks, as culprits in obesity in some people.
- Lack of exercise. Children who don't exercise much are more likely to gain weight because they don't burn as many calories. Too much time spent in sedentary activities, such as watching television or playing video games, also contributes to the problem. TV shows also often feature ads for unhealthy foods.
- Family factors. If your child comes from a family of overweight people, he or she may be more likely to put on weight. This is especially true in an environment where high-calorie foods are always available and physical activity isn't encouraged.
- Psychological factors. Personal, parental and family stress can increase a child's risk of obesity. Some children overeat to cope with problems or to deal with emotions, such as stress, or to fight boredom. Their parents might have similar tendencies.
- Socioeconomic factors. People in some communities have limited resources and limited access to supermarkets. As a result, they might buy convenience foods that don't spoil quickly, such as frozen meals, crackers and cookies. Also, people who live in lower income neighborhoods might not have access to a safe place to exercise.
- Certain medications. Some prescription drugs can increase the risk of developing obesity. They include prednisone, lithium, amitriptyline, paroxetine (Paxil), gabapentin (Neurontin, Gralise, Horizant) and propranolol (Inderal, Hemangeol).
Childhood obesity often causes complications in a child's physical, social and emotional well-being.
Physical complications of childhood obesity may include:
- Type 2 diabetes. This chronic condition affects the way your child's body uses sugar (glucose). Obesity and a sedentary lifestyle increase the risk of type 2 diabetes.
- High cholesterol and high blood pressure. A poor diet can cause your child to develop one or both of these conditions. These factors can contribute to the buildup of plaques in the arteries, which can cause arteries to narrow and harden, possibly leading to a heart attack or stroke later in life.
- Joint pain. Extra weight causes extra stress on hips and knees. Childhood obesity can cause pain and sometimes injuries in the hips, knees and back.
- Breathing problems. Asthma is more common in children who are overweight. These children are also more likely to develop obstructive sleep apnea, a potentially serious disorder in which a child's breathing repeatedly stops and starts during sleep.
- Nonalcoholic fatty liver disease (NAFLD). This disorder, which usually causes no symptoms, causes fatty deposits to build up in the liver. NAFLD can lead to scarring and liver damage.
Social and emotional complications
Children who have obesity may experience teasing or bullying by their peers. This can result in a loss of self-esteem and an increased risk of depression and anxiety.
To help prevent excess weight gain in your child, you can:
- Set a good example. Make healthy eating and regular physical activity a family affair. Everyone will benefit and no one will feel singled out.
- Have healthy snacks available. Options include air-popped popcorn without butter, fruits with low-fat yogurt, baby carrots with hummus, or whole-grain cereal with low-fat milk.
- Offer new foods multiple times. Don't be discouraged if your child doesn't immediately like a new food. It usually takes multiple exposures to a food to gain acceptance.
- Choose nonfood rewards. Promising candy for good behavior is a bad idea.
- Be sure your child gets enough sleep. Some studies indicate that too little sleep may increase the risk of obesity. Sleep deprivation can cause hormonal imbalances that lead to increased appetite.
Also, be sure your child sees the doctor for well-child checkups at least once a year. During this visit, the doctor measures your child's height and weight and calculates his or her BMI . A significant increase in your child's BMI percentile rank over one year may be a possible sign that your child is at risk of becoming overweight.
- Helping your child who is overweight. National Institute of Diabetes and Digestive and Kidney Diseases. https://www.niddk.nih.gov/health-information/weight-management/helping-your-child-who-is-overweight. Oct. 14, 2020.
- Childhood obesity causes and consequences. Centers for Disease Control and Prevention. https://www.cdc.gov/obesity/childhood/causes.html. Accessed Oct. 14, 2020.
- Kliegman RM, et al. Overweight and obesity. In: Nelson Textbook of Pediatrics. 21st ed. Elsevier; 2020. https://www.clinicalkey.com. Accessed Oct. 14, 2020.
- Hay WW, et al., eds. Normal childhood nutrition and its disorders. In: Current Diagnosis & Treatment: Pediatrics. 25th ed. McGraw Hill; 2020. https://accessmedicine.mhmedical.com. Accessed Oct. 20, 2020.
- Skelton JA. Management of childhood obesity in the primary care setting. https://www.uptodate.com/contents/search. Accessed Oct. 14, 2020.
- Klish WJ, et al. Definition, epidemiology and etiology of obesity in children and adolescents. https://www.uptodate.com/contents/search. Accessed Oct. 14, 2020.
- Polfuss ML, et al. Childhood obesity: Evidence-based guidelines for clinical practice — Part one. Journal of Pediatric Health Care. 2020; doi:10.1016/j.pedhc.2019.12.003.
- Davis RL, et al. Childhood obesity: Evidence-based guidelines for clinical practice — Part two. Journal of Pediatric Health Care. 2020; doi:10.1016/j.pedhc.2020.07.011.
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Comments on cbo blog post: “a call for new research in the area of obesity”.
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Editor’s note: The attached comment letter was submitted to the Congressional Budget Office on Nov. 2, 2023.
Schaeffer Center fellows commented on the Congressional Budget Office (CBO)’s October 5, 2023 blog post “ A Call for New Research in the Area of Obesity .” The researchers make the following points:
- There are serious limitations and biases of current real-world data on anti-obesity medications (AOMs), including the non-randomized and incomplete nature of the data set, the short-term use of the newest drugs in the insurance market, and unobservable variables that could impact outcomes.
- A simulation approach would be the best method for producing unbiased estimates of the value of current and future AOM treatments.
- Existing evidence on price trajectories, take-up and adherence could help address remaining analysis gaps.
They argue that while there are significant data and methodological challenges to be overcome, there are better alternatives to simplistically extrapolating from the real-world data on AOM use that is currently available.
Read the full comment letter here .
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Review article, childhood and adolescent obesity: a review.
- 1 Division of Endocrinology, Diabetes and Metabolism, Department of Pediatrics, Medical College of Wisconsin, Milwaukee, WI, United States
- 2 Division of Adolescent Medicine, Department of Pediatrics, Medical College of Wisconsin Affiliated Hospitals, Milwaukee, WI, United States
- 3 Division of Adolescent Medicine, Department of Pediatrics, Medical College of Wisconsin, Milwaukee, WI, United States
Obesity is a complex condition that interweaves biological, developmental, environmental, behavioral, and genetic factors; it is a significant public health problem. The most common cause of obesity throughout childhood and adolescence is an inequity in energy balance; that is, excess caloric intake without appropriate caloric expenditure. Adiposity rebound (AR) in early childhood is a risk factor for obesity in adolescence and adulthood. The increasing prevalence of childhood and adolescent obesity is associated with a rise in comorbidities previously identified in the adult population, such as Type 2 Diabetes Mellitus, Hypertension, Non-alcoholic Fatty Liver disease (NAFLD), Obstructive Sleep Apnea (OSA), and Dyslipidemia. Due to the lack of a single treatment option to address obesity, clinicians have generally relied on counseling dietary changes and exercise. Due to psychosocial issues that may accompany adolescence regarding body habitus, this approach can have negative results. Teens can develop unhealthy eating habits that result in Bulimia Nervosa (BN), Binge- Eating Disorder (BED), or Night eating syndrome (NES). Others can develop Anorexia Nervosa (AN) as they attempt to restrict their diet and overshoot their goal of “being healthy.” To date, lifestyle interventions have shown only modest effects on weight loss. Emerging findings from basic science as well as interventional drug trials utilizing GLP-1 agonists have demonstrated success in effective weight loss in obese adults, adolescents, and pediatric patients. However, there is limited data on the efficacy and safety of other weight-loss medications in children and adolescents. Nearly 6% of adolescents in the United States are severely obese and bariatric surgery as a treatment consideration will be discussed. In summary, this paper will overview the pathophysiology, clinical, and psychological implications, and treatment options available for obese pediatric and adolescent patients.
Obesity is a complex issue that affects children across all age groups ( 1 – 3 ). One-third of children and adolescents in the United States are classified as either overweight or obese. There is no single element causing this epidemic, but obesity is due to complex interactions between biological, developmental, behavioral, genetic, and environmental factors ( 4 ). The role of epigenetics and the gut microbiome, as well as intrauterine and intergenerational effects, have recently emerged as contributing factors to the obesity epidemic ( 5 , 6 ). Other factors including small for gestational age (SGA) status at birth, formula rather than breast feeding in infancy, and early introduction of protein in infant's dietary intake have been reportedly associated with weight gain that can persist later in life ( 6 – 8 ). The rising prevalence of childhood obesity poses a significant public health challenge by increasing the burden of chronic non-communicable diseases ( 1 , 9 ).
Obesity increases the risk of developing early puberty in children ( 10 ), menstrual irregularities in adolescent girls ( 1 , 11 ), sleep disorders such as obstructive sleep apnea (OSA) ( 1 , 12 ), cardiovascular risk factors that include Prediabetes, Type 2 Diabetes, High Cholesterol levels, Hypertension, NAFLD, and Metabolic syndrome ( 1 , 2 ). Additionally, obese children and adolescents can suffer from psychological issues such as depression, anxiety, poor self-esteem, body image and peer relationships, and eating disorders ( 13 , 14 ).
So far, interventions for overweight/obesity prevention have mainly focused on behavioral changes in an individual such as increasing daily physical exercise or improving quality of diet with restricting excess calorie intake ( 1 , 15 , 16 ). However, these efforts have had limited results. In addition to behavioral and dietary recommendations, changes in the community-based environment such as promotion of healthy food choices by taxing unhealthy foods ( 17 ), improving lunch food quality and increasing daily physical activity at school and childcare centers, are extra measures that are needed ( 16 ). These interventions may include a ban on unhealthy food advertisements aimed at children as well as access to playgrounds and green spaces where families can feel their children can safely recreate. Also, this will limit screen time for adolescents as well as younger children.
However, even with the above changes, pharmacotherapy and/or bariatric surgery will likely remain a necessary option for those youth with morbid obesity ( 1 ). This review summarizes our current understanding of the factors associated with obesity, the physiological and psychological effects of obesity on children and adolescents, and intervention strategies that may prevent future concomitant issues.
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. These methods include measuring skinfold thickness with a caliper, Bioelectrical impedance, Hydro densitometry, Dual-energy X-ray Absorptiometry (DEXA), and Air Displacement Plethysmography ( 2 ).
BMI provides a reasonable estimate of body fat indirectly in the healthy pediatric population and studies have shown that BMI correlates with body fat and future health risks ( 18 ). Unlike in adults, Z-scores or percentiles are used to represent BMI in children and vary with the age and sex of the child. BMI Z-score cut off points of >1.0, >2.0, and >3.0 are recommended by the World Health Organization (WHO) to define at risk of overweight, overweight and obesity, respectively ( 19 ). However, in terms of percentiles, overweight is applied when BMI is >85th percentile <95th percentile, whereas obesity is BMI > 95th percentile ( 20 – 22 ). Although BMI Z-scores can be converted to BMI percentiles, the percentiles need to be rounded and can misclassify some normal-weight children in the under or overweight category ( 19 ). Therefore, to prevent these inaccuracies and for easier understanding, it is recommended that the BMI Z-scores in children should be used in research whereas BMI percentiles are best used in the clinical settings ( 20 ).
As BMI does not directly measure body fat, it is an excellent screening method, but should not be used solely for diagnostic purposes ( 23 ). Using 85th percentile as a cut off point for healthy weight may miss an opportunity to obtain crucial information on diet, physical activity, and family history. Once this information is obtained, it may allow the provider an opportunity to offer appropriate anticipatory guidance to the families.
Pathophysiology of Obesity
The pathophysiology of obesity is complex that results from a combination of individual and societal factors. At the individual level, biological, and physiological factors in the presence of ones' own genetic risk influence eating behaviors and tendency to gain weight ( 1 ). Societal factors include influence of the family, community and socio-economic resources that further shape these behaviors ( Figure 1 ) ( 3 , 24 ).
Figure 1 . Multidimensional factors contributing to child and adolescent obesity.
There is a complex architecture of neural and hormonal regulatory control, the Gut-Brain axis, which plays a significant role in hunger and satiety ( Figure 2 ). Sensory stimulation (smell, sight, and taste), gastrointestinal signals (peptides, neural signals), and circulating hormones further contribute to food intake ( 25 – 27 ).
Figure 2 . Pictorial representation of the Hunger-Satiety pathway a and the various hormones b involved in the pathway. a, Y1/Y5R and MC3/4 are second order neuro receptors which are responsible in either the hunger or satiety pathway. Neurons in the ARC include: NPY, Neuropeptide Y; AgRP, Agouti-Related Peptide; POMC, Pro-Opiomelanocortin; CART, Cocaine-and Amphetamine-regulated Transcript; α-MSH, α-Melanocyte Stimulating Hormone. b, PYY, Peptide YY; PP, Pancreatic Polypeptide; GLP-1, Glucagon-Like Peptide- I; OMX, Oxyntomodulin.
The hypothalamus is the crucial region in the brain that regulates appetite and is controlled by key hormones. Ghrelin, a hunger-stimulating (orexigenic) hormone, is mainly released from the stomach. On the other hand, leptin is primarily secreted from adipose tissue and serves as a signal for the brain regarding the body's energy stores and functions as an appetite -suppressing (anorexigenic) hormone. Several other appetite-suppressing (anorexigenic) hormones are released from the pancreas and gut in response to food intake and reach the hypothalamus through the brain-blood barrier (BBB) ( 28 – 32 ). These anorexigenic and orexigenic hormones regulate energy balance by stimulating hunger and satiety by expression of various signaling pathways in the arcuate nucleus (ARC) of the hypothalamus ( Figure 2 ) ( 28 , 33 ). Dysregulation of appetite due to blunted suppression or loss of caloric sensing signals can result in obesity and its morbidities ( 34 ).
Emotional dysfunction due to psychiatric disorders can cause stress and an abnormal sleep-wake cycles. These modifications in biological rhythms can result in increased appetite, mainly due to ghrelin, and can contribute to emotional eating ( 35 ).
Recently, the role of changes in the gut microbiome with increased weight gain through several pathways has been described in literature ( 36 , 37 ). The human gut serves as a host to trillions of microorganisms, referred to as gut microbiota. The dominant gut microbial phyla are Firmicutes, Bacteroidetes, Actinobacteria, Proteobacteria, Fusobacteria, and Verrucomicrobia, with Firmicutes and Bacteroidetes representing 90% of human gut microbiota ( 5 , 38 ). The microbes in the gut have a symbiotic relationship within their human host and provide a nutrient-rich environment. Gut microbiota can be affected by various factors that include gestational age at birth, mode of infant delivery, type of neonatal and infant feeding, introduction of solid food, feeding practices and external factors like antibiotic use ( 5 , 38 ). Also, the maturation of the bacterial phyla that occurs from birth to adulthood ( 39 ), is influenced by genetics, environment, diet, lifestyle, and gut physiology and stabilizes in adulthood ( 5 , 39 , 40 ). Gut microbiota is unique to each individual and plays a specific role in maintaining structural integrity, and the mucosal barrier of the gut, nutrient metabolism, immune response, and protection against pathogens ( 5 , 37 , 38 ). In addition, the microbiota ferments the indigestible food and synthesizes other essential micronutrients as well as short chain fatty acids (SCFAs') ( 40 , 41 ). Dysbiosis or imbalance of the gut microbiota, in particularly the role of SCFA has been linked with the patho-physiology of obesity ( 36 , 38 , 41 , 42 ). SCFAs' are produced by anaerobic fermentation of dietary fiber and indigestible starch and play a role in mammalian energy metabolism by influencing gut-brain communication axis. Emerging evidence has shown that increased ratio of Firmicutes to Bacteroidetes causes increased energy extraction of calories from diets and is evidenced by increased production of short chain fatty acids (SCFAs') ( 43 – 45 ). However, this relationship is not affirmed yet, as a negative relationship between SCFA levels and obesity has also been reported ( 46 ). Due to the conflicting data, additional randomized control trials are needed to clarify the role of SCFA's in obese and non-obese individuals.
The gut microbiota also has a bidirectional interaction with the liver, and various additional factors such as diet, genetics, and the environment play a key role in this relationship. The Gut- Liver Axis is interconnected at various levels that include the mucus barrier, epithelial barrier, and gut microbiome and are essential to maintain normal homeostasis ( 47 ). Increased intestinal mucosal permeability can disrupt the gut-liver axis, which releases various inflammatory markers, activates an innate immune response in the liver, and results in a spectrum of liver diseases that include hepatic steatosis, non-alcoholic steatohepatitis (NASH), cirrhosis, and hepatocellular carcinoma (HCC) ( 48 , 49 ).
Other medical conditions, including type 2 Diabetes Mellitus, Metabolic Syndrome, eating disorders as well as psychological conditions such as anxiety and depression are associated with the gut microbiome ( 50 – 53 ).
Genetic causes of obesity can either be monogenic or polygenic types. Monogenic obesity is rare, mainly due to mutations in genes within the leptin/melanocortin pathway in the hypothalamus that is essential for the regulation of food intake/satiety, body weight, and energy metabolism ( 54 ). Leptin regulates eating behaviors, the onset of puberty, and T-cell immunity ( 55 ). About 3% of obese children have mutations in the leptin ( LEP ) gene and the leptin receptor (LEPR) and can also present with delayed puberty and immune dysfunction ( 55 , 56 ). Obesity caused by other genetic mutations in the leptin-melanocortin pathway include proopiomelanocortin (POMC) and melanocortin receptor 4 (MC4R), brain-derived neurotrophic factor (BDNF), and the tyrosine kinase receptor B (NTRK2) genes ( 57 , 58 ). Patients with monogenic forms generally present during early childhood (by 2 years old) with severe obesity and abnormal feeding behaviors ( 59 ). Other genetic causes of severe obesity are Prader Willi Syndrome (PWS), Alström syndrome, Bardet Biedl syndrome. Patients with these syndromes present with additional characteristics, including cognitive impairment, dysmorphic features, and organ-specific developmental abnormalities ( 60 ). Individuals who present with obesity, developmental delay, dysmorphic features, and organ dysfunction should receive a genetics referral for further evaluation.
Polygenic obesity is the more common form of obesity, caused by the combined effect of multiple genetic variants. It is the result of the interplay between genetic susceptibility and the environment, also known as the Gene-Environment Interaction (GEI) ( 61 – 64 ). Genome-wide association studies (GWAS) have identified gene variants [single nucleotide polymorphism (SNPs)] for body mass index (BMI) that likely act synergistically to affect body weight ( 65 ). Studies have identified genetic variants in several genes that may contribute to excessive weight gain by increasing hunger and food intake ( 66 – 68 ). When the genotype of an individual confers risk for obesity, exposure to an obesogenic environment may promote a state of energy imbalance due to behaviors that contribute to conserving rather than expending energy ( 69 , 70 ). Research studies have shown that obese individuals have a genetic variation that can influence their actions, such as increased food intake, lack of physical activity, a decreased metabolism, as well as an increased tendency to store body fat ( 63 , 66 , 67 , 69 , 70 ).
Recently the role of epigenetic factors in the development of obesity has emerged ( 71 ). The epigenetic phenomenon may alter gene expression without changing the underlying DNA sequence. In effect, epigenetic changes may result in the addition of chemical tags known as methyl groups, to the individual's chromosomes. This alteration can result in a phenomenon where critical genes are primed to on and off regulate. Complex physiological and psychological adjustment occur during infancy and can thereafter set the stage for health vs. disease. Developmental origins of health and disease (DOHaD) shows that early life environment can impact the risk of chronic diseases later in life due to fetal programming secondary to epigenetic changes ( 72 ). Maternal nutrition during the prenatal or early postnatal period may trigger these epigenetic changes and increase the risk for chronic conditions such as obesity, metabolic and cardiovascular disease due to epigenetic modifications that may persist and cause intergenerational effect on the health children and adults ( 58 , 73 , 74 ). Similarly, adverse childhood experiences (ACE) have been linked to a broad range of negative outcomes through epigenetic mechanisms ( 75 ) and promote unhealthy eating behaviors ( 76 , 77 ). Other factors such as diet, physical activity, environmental and psychosocial stressors can cause epigenetic changes and place an individual at risk for weight gain ( 78 ).
Eating behaviors evolve over the first few years of life. Young children learn to eat through their direct experience with food and observing others eating around them ( 79 ). During infancy, feeding defines the relationship of security and trust between a child and the parent. Early childhood eating behaviors shift to more self-directed control due to rapid physical, cognitive, communicative, and social development ( 80 ). Parents or caregivers determine the type of food that is made available to the infant and young child. However, due to economic limitations and parents having decreased time to prepare nutritious meals, consumption of processed and cheaper energy-dense foods have occurred in Western countries. Additionally, feeding practices often include providing large or super-sized portions of palatable foods and encouraging children to finish the complete meal (clean their plate even if they do not choose to), as seen across many cultures ( 81 , 82 ). Also, a segment of parents are overly concerned with dietary intake and may pressurize their child to eat what they perceive as a healthy diet, which can lead to unintended consequences ( 83 ). Parents' excessive restriction of food choices may result in poor self-regulation of energy intake by their child or adolescent. This action may inadvertently promote overconsumption of highly palatable restricted foods when available to the child or adolescent outside of parental control with resultant excessive weight gain ( 84 , 85 ).
During middle childhood, children start achieving greater independence, experience broader social networks, and expand their ability to develop more control over their food choices. Changes that occur in the setting of a new environment such as daycare or school allow exposure to different food options, limited physical activity, and often increased sedentary behaviors associated with school schedules ( 24 ). As the transition to adolescence occurs, physical and psychosocial development significantly affect food choices and eating patterns ( 25 ). During the teenage years, more independence and interaction with peers can impact the selection of fast foods that are calorically dense. Moreover, during the adolescent years, more sedentary behaviors such as video and computer use can limit physical exercise. Adolescence is also a period in development with an enhanced focus on appearance, body weight, and other psychological concerns ( 86 , 87 ).
Environmental changes within the past few decades, particularly easy access to high-calorie fast foods, increased consumption of sugary beverages, and sedentary lifestyles, are linked with rising obesity ( 88 ). The easy availability of high caloric fast foods, and super-sized portions, are increasingly common choices as individuals prefer these highly palatable and often less expensive foods over fruits and vegetables ( 89 ). The quality of lunches and snacks served in schools and childcare centers has been an area of debate and concern. Children and adolescents consume one-third to one-half of meals in the above settings. Despite policies in place at schools, encouraging foods, beverages, and snacks that are deemed healthier options, the effectiveness of these policies in improving children's dietary habits or change in obesity rate has not yet been seen ( 90 ). This is likely due to the fact that such policies primarily focus on improving dietary quality but not quantity which can impact the overweight or obese youth ( 91 ). Policies to implement taxes on sugary beverages are in effect in a few states in the US ( 92 ) as sugar and sugary beverages are associated with increased weight gain ( 2 , 3 ). This has resulted in reduction in sales of sugary drinks in these states, but the sales of these types of drinks has risen in neighboring states that did not implement the tax ( 93 ). Due to advancements in technology, children are spending increased time on electronic devices, limiting exercise options. Technology advancement is also disrupting the sleep-wake cycle, causing poor sleeping habits, and altered eating patterns ( 94 ). A study published on Canadian children showed that the access to and night-time use of electronic devices causes decreased sleep duration, resulting in excess body weight, inferior diet quality, and lower physical activity levels ( 95 ).
Infant nutrition has gained significant popularity in relation to causing overweight/obesity and other diseases later in life. Breast feeding is frequently discussed as providing protection against developing overweight/obesity in children ( 8 ). Considerable heterogeneity has been observed in studies and conducting randomized clinical trials between breast feeding vs. formula feeding is not feasible ( 8 ). Children fed with a low protein formula like breast milk are shown to have normal weight gain in early childhood as compared to those that are fed formulas with a high protein load ( 96 ). A recent Canadian childbirth cohort study showed that breast feeding within first year of life was inversely associated with weight gain and increased BMI ( 97 ). The effect was stronger if the child was exclusively breast fed directly vs. expressed breast milk or addition of formula or solid food ( 97 ). Also, due to the concern of poor growth in preterm or SGA infants, additional calories are often given for nutritional support in the form of macronutrient supplements. Most of these infants demonstrate “catch up growth.” In fact, there have been reports that in some children the extra nutritional support can increase the risk for overweight/obesity later in life. The association, however, is inconsistent. Recently a systemic review done on randomized controlled trials comparing the studies done in preterm and SGA infants with feeds with and without macronutrient supplements showed that macronutrient supplements may increase weight and length in toddlers but did not show a significant increase in the BMI during childhood ( 98 ). Increased growth velocity due to early introduction of formula milk and protein in infants' diet, may influence the obesity pathways, and can impact fetal programming for metabolic disease later in life ( 99 ).
General pediatricians caring for children with overweight/obesity, generally recommend endocrine testing as parents often believe that there may be an underlying cause for this condition and urge their primary providers to check for conditions such as thyroid abnormalities. Endocrine etiologies for obesity are rarely identified and patients with underlying endocrine disorders causing excessive weight gain usually are accompanied by attenuated growth patterns, such that a patient continues to gain weight with a decline in linear height ( 100 ). Various endocrine etiologies that one could consider in a patient with excessive weight gain in the setting of slow linear growth: severe hypothyroidism, growth hormone deficiency, and Cushing's disease/syndrome ( 58 , 100 ).
Clinical-Physiology of Pediatric Obesity
It is a well-known fact that early AR(increased BMI) before the age of 5 years is a risk factor for adult obesity, obesity-related comorbidities, and metabolic syndrome ( 101 – 103 ). Typically, body mass index (BMI) declines to a minimum in children before it starts increasing again into adulthood, also known as AR. Usually, AR happens between 5 and 7 years of age, but if it occurs before the age of 5 years is considered early AR. Early AR is a marker for higher risk for obesity-related comorbidities. These obesity-related health comorbidities include cardiovascular risk factors (hypertension, dyslipidemia, prediabetes, and type 2 diabetes), hormonal issues, orthopedic problems, sleep apnea, asthma, and fatty liver disease ( Figure 3 ) ( 9 ).
Figure 3 . Obesity related co-morbidities a in children and adolescents. a, NAFLD, Non-Alcoholic Fatty Liver Disease; SCFE, Slipped Capital Femoral Epiphysis; PCOS, Polycystic Ovary Syndrome; OSA, Obstructive Sleep Apnea.
Clinical Comorbidities of Obesity in Children
Growth and puberty.
Excess weight gain in children can influence growth and pubertal development ( 10 ). Childhood obesity can cause prepubertal acceleration of linear growth velocity and advanced bone age in boys and girls ( 104 ). Hyperinsulinemia is a normal physiological state during puberty, but children with obesity can have abnormally high insulin levels ( 105 ). Leptin resistance also occurs in obese individuals who have higher leptin levels produced by their adipose tissue ( 55 , 106 ). The insulin and leptin levels can act on receptors that impact the growth plates with a resultant bone age advancement ( 55 ).
Adequate nutrition is essential for the typical timing and tempo of pubertal onset. Excessive weight gain can initiate early puberty, due to altered hormonal parameters ( 10 ). Obese children may present with premature adrenarche, thelarche, or precocious puberty (PP) ( 107 ). The association of early pubertal changes with obesity is consistent in girls, and is well-reported; however, data is sparse in boys ( 108 ). One US study conducted in racially diverse boys showed obese boys had delayed puberty, whereas overweight boys had early puberty as compared to normal-weight boys ( 109 ). Obese girls with PP have high leptin levels ( 110 , 111 ). Healthy Lifestyle in Europe by Nutrition in Adolescence (HELENA) is a cross-sectional study and suggested an indirect relationship between elevated leptin levels, early puberty, and cardiometabolic and inflammatory markers in obese girls ( 112 ). Additionally, obese girls with premature adrenarche carry a higher risk for developing polycystic ovary syndrome (PCOS) in the future ( 113 , 114 ).
Obesity is an independent risk factor for obstructive sleep apnea (OSA) in children and adolescents ( 12 , 115 ). Children with OSA have less deleterious consequences in terms of cardiovascular stress of metabolic syndrome when compared to adolescents and adults ( 116 , 117 ). In children, abnormal behaviors and neurocognitive dysfunction are the most critical and frequent end-organ morbidities associated with OSA ( 12 ). However, in adolescents, obesity and OSA can independently cause oxidative systemic stress and inflammation ( 118 , 119 ), and when this occurs concurrently, it can result in more severe metabolic dysfunction and cardiovascular outcomes later in life ( 120 ).
Obesity is related to a clinical spectrum of liver abnormalities such as NAFLD ( 121 ); the most important cause of liver disease in children ( 122 – 124 ). NAFLD includes steatosis (increased liver fat without inflammation) and NASH (increased liver fat with inflammation and hepatic injury). While in some adults NAFLD can progress to an end-stage liver disease requiring liver transplant ( 125 , 126 ), the risk of progression during childhood is less well-defined ( 127 ). NAFLD is closely associated with metabolic syndrome including central obesity, insulin resistance, type 2 diabetes, dyslipidemia, and hypertension ( 128 ).
Obese children are also at risk for slipped capital femoral epiphysis (SCFE) ( 129 ), and sedentary lifestyle behaviors may have a negative influence on the brain structure and executive functioning, although the direction of causality is not clear ( 130 , 131 ).
Clinical Comorbidities of Obesity in Adolescents
Menstrual irregularities and pcos.
At the onset of puberty, physiologically, sex steroids can cause appropriate weight gain and body composition changes that should not affect normal menstruation ( 132 , 133 ). However, excessive weight gain in adolescent girls can result in irregular menstrual cycles and puts them at risk for PCOS due to increased androgen levels. Additionally, they can have excessive body hair (hirsutism), polycystic ovaries, and can suffer from distorted body images ( 134 , 135 ). Adolescent girls with PCOS also have an inherent risk for insulin resistance irrespective of their weight. However, weight gain further exacerbates their existing state of insulin resistance and increases the risk for obesity-related comorbidities such as metabolic syndrome, and type 2 diabetes. Although the diagnosis of PCOS can be challenging at this age due to an overlap with predictable pubertal changes, early intervention (appropriate weight loss and use of hormonal methods) can help restore menstrual cyclicity and future concerns related to childbearing ( 11 ).
Metabolic Syndrome and Sleep Disorders
Metabolic syndrome (MS) is a group of cardiovascular risk factors characterized by acanthosis nigricans, prediabetes, hypertension, dyslipidemia, and non-alcoholic steatohepatitis (NASH), that occurs from insulin resistance caused by obesity ( 136 ). Diagnosis of MS in adults requires at least three out of the five risk factors: increased central adiposity, hypertension, hyperglycemia, hypertriglyceridemia, or low HDL level. Definitions to diagnose MS are controversial in younger age groups, and many definitions have been proposed ( 136 ). This is due to the complex physiology of growth and development during puberty, which causes significant overlap between MS and features of normal growth. However, childhood obesity is associated with an inflammatory state even before puberty ( 137 ). In obese children and adolescents, hyperinsulinemia during puberty ( 138 , 139 ) and unhealthy sleep behaviors increase MS's risk and severity ( 140 ). Even though there is no consensus on diagnosis regarding MS in this age group, when dealing with obese children and adolescents, clinicians should screen them for MS risk factors and sleep behaviors and provide recommendations for weight management.
Social Psychology of Pediatric Obesity in Children and Adolescents
Obese children and adolescents may experience psychosocial sequelae, including depression, bullying, social isolation, diminished self-esteem, behavioral problems, dissatisfaction with body image, and reduced quality of life ( 13 , 141 ). Compared with normal-weight counterparts, overweight/obesity is one of the most common reasons children and adolescents are bullied at school ( 142 ). The consequence of stigma, bullying, and teasing related to childhood obesity are pervasive and can have severe implications for emotional and physical health and performance that can persist later in life ( 13 ).
In adolescents, psychological outcomes associated with obesity are multifactorial and have a bidirectional relationship ( Figure 4 ). Obese adolescents due to their physique may have a higher likelihood of psychosocial health issues, including depression, body image/dissatisfaction, lower self-esteem, peer victimization/bullying, and interpersonal relationship difficulties. They may also demonstrate reduced resilience to challenging situations compared to their non-obese/overweight counterparts ( 9 , 143 – 146 ). Body image dissatisfaction has been associated with further weight gain but can also be related to the development of a mental health disorder or an eating disorder (ED) or disorder eating habits (DEH). Mental health disorders such as depression are associated with poor eating habits, a sedentary lifestyle, and altered sleep patterns. ED or DEH that include anorexia nervosa (AN), bulimia nervosa (BN), binge-eating disorder (BED) or night eating syndrome (NES) may be related to an individual's overvaluation of their body shape and weight or can result during the treatment for obesity ( 147 – 150 ). The management of obesity can place a patient at risk of AN if there is a rigid focus on caloric intake or if a patient overcorrects and initiates obsessive self-directed dieting. Healthcare providers who primarily care for obese patients, usually give the advice to diet to lose weight and then maintain it. However, strict dieting (hypocaloric diet), which some patients may later engage in can lead to an eating disorder such as anorexia nervosa ( 151 ). This behavior leads to a poor relationship with food, and therefore, adolescents perseverate on their weight and numbers ( 152 ).
Figure 4 . Bidirectional relationship of different psychological outcomes of obesity.
Providers may not recognize DEHs when a morbidly obese patient loses the same weight as a healthy weight individual ( 149 ). It may appear as a positive result with families and others praising the individual without realizing that this youth may be engaging in destructive behaviors related to weight control. Therefore, it is essential to screen regarding the process of how weight loss was achieved ( 144 , 150 ).
Support and attention to underlying psychological concerns can positively affect treatment, overall well-being, and reduce the risk of adult obesity ( 150 ). The diagram above represents the complexity of the different psychological issues which can impact the clinical care of the obese adolescent.
Eating family meals together can improve overall dietary intake due to enhanced food choices mirrored by parents. It has also may serve as a support to individuals with DEHs if there is less attention to weight and a greater focus on appropriate, sustainable eating habits ( 148 ).
Prevention and Anticipatory Guidance
It is essential to recognize and provide preventive measures for obesity during early childhood and adolescence ( 100 , 153 , 154 ). It is well-established that early AR is a risk factor for adult obesity ( 66 – 68 ). Therefore, health care providers caring for the pediatric population need to focus on measures such as BMI but provide anticipatory guidance regarding nutritional counseling without stigmatizing or judging parents for their children's overweight/obesity ( 155 ). Although health care providers continue to pursue effective strategies to address the obesity epidemic; ironically, they frequently exhibit weight bias and stigmatizing behaviors. Research has demonstrated that the language that health care providers use when discussing a patient's body weight can reinforce stigma, reduce motivation for weight loss, and potentially cause avoidance of routine preventive care ( 155 ). In adolescents, rather than motivating positive changes, stigmatizing language regarding weight may negatively impact a teen and result in binge eating, decreased physical activity, social isolation, avoidance of health care services, and increased weight gain ( 156 , 157 ). Effective provider-patient communication using motivational interviewing techniques are useful to encourage positive behavior changes ( 155 , 158 ).
Anticipatory guidance includes educating the families on healthy eating habits and identifying unhealthy eating practices, encouraging increased activity, limiting sedentary activities such as screen time. Lifestyle behaviors in children and adolescents are influenced by many sectors of our society, including the family ( Figure 1 ) ( 3 , 24 ). Therefore, rather than treating obesity in isolation as an individual problem, it is crucial to approach this problem by focusing on the family unit. Family-based multi-component weight loss behavioral treatment is the gold standard for treating childhood obesity, and it is having been found useful in those between 2 and 6 years old ( 150 , 159 ). Additionally, empowering the parents to play an equal role in developing and implementing an intervention for weight management has shown promising results in improving the rate of obesity by decreasing screen time, promoting healthy eating, and increasing support for children's physical activity ( 160 , 161 ).
When dietary/lifestyle modifications have failed, the next option is a structured weight -management program with a multidisciplinary approach ( 15 ). The best outcomes are associated with an interdisciplinary team comprising a physician, dietician, and psychologist generally 1–2 times a week ( 15 , 162 ). However, this treatment approach is not effective in patients with severe obesity ( 122 ). Although healthier lifestyle recommendations for weight loss are the current cornerstone for obesity management, they often fail. As clinicians can attest, these behavioral and dietary changes are hard to achieve, and all too often is not effective in patients with severe obesity. Failure to maintain substantial weight loss over the long term is due to poor adherence to the prescribed lifestyle changes as well as physiological responses that resist weight loss ( 163 ). American TV hosts a reality show called “The Biggest Loser” that centers on overweight and obese contestants attempting to lose weight for a cash prize. Contestants from “The Biggest Loser” competition, had metabolic adaptation (MA) after drastic weight loss, regained more than they lost weight after 6 years due to a significant slow resting metabolic rate ( 164 ). MA is a physiological response which is a reduced basal metabolic rate seen in individuals who are losing or have lost weight. In MA, the body alters how efficient it is at turning the food eaten into energy; it is a natural defense mechanism against starvation and is a response to caloric restriction. Plasma leptin levels decrease substantially during caloric restriction, suggesting a role of this hormone in the drop of energy expenditure ( 165 ).
The role of pharmacological therapy in the treatment of obesity in children and adolescents is limited.
Orlistat is the only FDA approved medication for weight loss in 12-18-year-olds but has unpleasant side effects ( 166 ). Another medicine, Metformin, has been used in children with signs of insulin resistance, may have some impact on weight, but is not FDA approved ( 167 ). The combination of phentermine/topiramate (Qsymia) has been FDA approved for weight loss in obese individuals 18 years and older. In studies, there has been about 9–10% weight loss over 2 years. However, caution must be taken in females as it can lead to congenital disabilities, especially with use in the first trimester of pregnancy ( 167 ).
GLP-1 agonists have demonstrated great success in effective weight loss and are approved by the FDA for adult obesity ( 168 – 170 ). A randomized control clinical trial recently published showed a significant weight loss in those using liraglutide (3.0 mg)/day plus lifestyle therapy group compared to placebo plus lifestyle therapy in children between the ages of 12–18 years ( 171 ).
Recently during the EASL conference, academic researchers and industry partners presented novel interventions targeting different gut- liver axis levels that include intestinal content, intestinal microbiome, intestinal mucosa, and peritoneal cavity ( 47 ). The focus for these therapeutic interventions within the gut-liver axis was broad and ranged anywhere from newer drugs protecting the intestinal mucus lining, restoring the intestinal barriers and improvement in the gut microbiome. One of the treatment options was Hydrogel technology which was shown to be effective toward weight loss in patients with metabolic syndrome. Hydrogel technology include fibers and high viscosity polysaccharides that absorb water in the stomach and increasing the volume, thereby improving satiety ( 47 ). Also, a clinical trial done in obese pregnant mothers using Docosahexaenoic acid (DHA) showed that the mothers' who got DHA had children with lower adiposity at 2 and 4 years of age ( 172 ). Recently the role of probiotics in combating obesity has emerged. Probiotics are shown to alter the gut microbiome that improves intestinal digestive and absorptive functions of the nutrients. Intervention including probiotics may be a possible solution to manage pediatric obesity ( 173 , 174 ). Additionally, the role of Vitamin E for treating the comorbidities of obesity such as diabetes, hyperlipidemia, NASH, and cardiovascular risk, has been recently described ( 175 , 176 ). Vitamin E is a lipid- soluble compound and contains both tocopherols and tocotrienols. Tocopherols have lipid-soluble antioxidants properties that interact with cellular lipids and protects them from oxidation damage ( 177 ). In metabolic disease, certain crucial pathways are influenced by Vitamin E and some studies have summarized the role of Vitamin E regarding the treatment of obesity, metabolic, and cardiovascular disease ( 178 ). Hence, adequate supplementation of Vitamin E as an appropriate strategy to help in the treatment of the prevention of obesity and its associated comorbidities has been suggested. Nonetheless, some clinical trials have shown contradictory results with Vitamin E supplementation ( 177 ). Although Vitamin E has been recognized as an antioxidant that protects from oxidative damage, however, a full understanding of its mechanism of action is still lacking.
Bariatric surgery has gained popularity since the early 2000s in the management of severe obesity. If performed earlier, there are better outcomes for reducing weight and resolving obesity-related comorbidities in adults ( 179 – 182 ). Currently, the indication for bariatric in adolescents; those who have a BMI >35 with at least one severe comorbidity (Type 2 Diabetes, severe OSA, pseudotumor cerebri or severe steatohepatitis); or BMI of 40 or more with other comorbidities (hypertension, hyperlipidemia, mild OSA, insulin resistance or glucose intolerance or impaired quality of life due to weight). Before considering bariatric surgery, these patients must have completed most of their linear growth and participated in a structured weight-loss program for 6 months ( 159 , 181 , 183 ). The American Society for Metabolic and Bariatric Surgery (AMBS) outlines the multidisciplinary approach that must be taken before a patient undergoing bariatric surgery. In addition to a qualified bariatric surgeon, the patient must have a pediatrician or provider specialized in adolescent medicine, endocrinology, gastroenterology and nutrition, registered dietician, mental health provider, and exercise specialist ( 181 ). A mental health provider is essential as those with depression due to obesity or vice versa may have persistent mental health needs even after weight loss surgery ( 184 ).
Roux-en-Y Gastric Bypass (RYGB), laparoscopic Sleeve Gastrectomy (LSG), and Gastric Banding are the options available. RYGB and LSG currently approved for children under 18 years of age ( 166 , 181 , 185 ). At present, gastric banding is not an FDA recommended procedure in the US for those under 18y/o. One study showed some improvements in BMI and severity of comorbidities but had multiple repeat surgeries and did not believe a suitable option for obese adolescents ( 186 ).
Compared to LSG, RYGB has better outcomes for excess weight loss and resolution of obesity-related comorbidities as shown in studies and clinical trials ( 183 , 184 , 187 ). Overall, LSG is a safer choice and may be advocated for more often ( 179 – 181 ). The effect on the Gut-Brain axis after Bariatric surgery is still inconclusive, especially in adolescents, as the number of procedures performed is lower than in adults. Those who underwent RYGB had increased fasting and post-prandial PYY and GLP-1, which could have contributed to the rapid weight loss ( 185 ); this effect was seen less often in patients with gastric banding ( 185 ). Another study in adult patients showed higher bile acid (BA) subtype levels and suggested a possible BA's role in the surgical weight loss response after LSG ( 188 ). Adolescents have lower surgical complication rates than their adult counterparts, hence considering bariatric surgery earlier rather than waiting until adulthood has been entertained ( 180 ). Complications after surgery include nutritional imbalance in iron, calcium, Vitamin D, and B12 and should be monitored closely ( 180 , 181 , 185 ). Although 5-year data for gastric bypass in very obese teens is promising, lifetime outcome is still unknown, and the psychosocial factors associated with adolescent adherence post-surgery are also challenging and uncertain.
Obesity in childhood and adolescence is not amenable to a single easily modified factor. Biological, cultural, and environmental factors such as readily available high-density food choices impact youth eating behaviors. Media devices and associated screen time make physical activity a less optimal choice for children and adolescents. This review serves as a reminder that the time for action is now. The need for interventions to change the obesogenic environment by instituting policies around the food industry and in the schools needs to be clarified. In clinical trials GLP-1 agonists are shown to be effective in weight loss in children but are not yet FDA approved. Discovery of therapies to modify the gut microbiota as treatment for overweigh/obesity through use of probiotics or fecal transplantation would be revolutionary. For the present, ongoing clinical research efforts in concert with pharmacotherapeutic and multidisciplinary lifestyle programs hold promise.
AK, SL, and MJ contributed to the conception and design of the study. All authors contributed to the manuscript revision, read, and approved the submitted version.
Conflict of Interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
1. Gurnani M, Birken C, Hamilton. J. Childhood obesity: causes, consequences, and management. Pediatr Clin North Am. (2015) 62:821–40. doi: 10.1016/j.pcl.2015.04.001
PubMed Abstract | CrossRef Full Text | Google Scholar
2. Sahoo K, Sahoo B, Choudhury AK, Sofi NY, Kumar R, Bhadoria. AS. Childhood obesity: causes and consequences. J Family Med Prim Care. (2015) 4:187–92. doi: 10.4103/2249-4863.154628
3. Brown CL, Halvorson EE, Cohen GM, Lazorick S, Skelton JA. Addressing childhood obesity: opportunities for prevention. Pediatr Clin North Am. (2015) 62:1241–61. doi: 10.1016/j.pcl.2015.05.013
4. Qasim A, Turcotte M, de Souza RJ, Samaan MC, Champredon D, Dushoff J, et al. On the origin of obesity: identifying the biological, environmental, and cultural drivers of genetic risk among human populations. Obes Rev. (2018) 19:121–49. doi: 10.1111/obr.12625
5. Rinninella E, Raoul P, Cintoni M, Fransceschi F, Miggiano GAD, Gasbarrini A, et al. What is the healthy gut microbiota composition? a changing ecosystem across age, environment, diet, and diseases. Microorganisms. (2019) 7:14. doi: 10.3390/microorganisms7010014
6. Indrio F, Martini S, Francavilla R, Corvaglia L, Cristofori F, Mastrolia SA, et al. Epigenetic matters: the link between early nutrition, microbiome, and long-term health development. Front Pediatr. (2017) 5:178. doi: 10.3389/fped.2017.00178
7. Marcovecchio ML, Gorman S, Watson LPE, Dunger DB, Beardsall K. Catch-up growth in children born small for gestational age related to body composition and metabolic risk at six years of age in the UK. Horm Res Paediatr. (2020) 93:119–27. doi: 10.1159/000508974
8. Koletzko B, Fishbein M, Lee WS, Moreno L, Mouane N, Mouzaki M, et al. Prevention of childhood obesity: a position paper of the global federation of international societies of paediatric gastroenterology, hepatology nutrition (FISPGHAN). J Pediatr Gastroenterol Nutr. (2020) 70:702–10. doi: 10.1097/MPG.0000000000002708
9. Pulgarón ER. Childhood obesity: a review of increased risk for physical and psychological comorbidities. Clin Ther. (2013) 35:A18–32. doi: 10.1016/j.clinthera.2012.12.014
10. De Leonibus C, Marcovecchio ML, Chiarelli F. Update on statural growth and pubertal development in obese children. Pediatr Rep. (2012) 4:e35. doi: 10.4081/pr.2012.e35
11. Witchel SF, Burghard AC, Tao RH, Oberfield SE. The diagnosis and treatment of PCOS in adolescents. Curr Opin Pediatr . (2019) 31:562–9. doi: 10.1097/MOP.0000000000000778
12. Marcus CL, Brooks LJ, Draper KA, Gozal D, Halbower AC, Jones J, et al. Diagnosis and management of childhood obstructive sleep apnea syndrome. Pediatrics . (2012) 130:e714–55. doi: 10.1542/peds.2012-1672
CrossRef Full Text | Google Scholar
13. Rankin J, Matthews L, Cobley S, Han A, Sanders R, Wiltshire HD, et al. Psychological consequences of childhood obesity: psychiatric comorbidity and prevention. Adolesc Health Med Ther . (2016) 7:125–46. doi: 10.2147/AHMT.S101631
14. Topçu S, Orhon FS, Tayfun M, Uçaktürk SA, Demirel F. Anxiety, depression, and self-esteem levels in obese children: a case-control study. J Pediatr Endocrinol Metabol. (2016) 29:357–61. doi: 10.1515/jpem-2015-0254
15. Katzmarzyk PT, Barlow S, Bouchard C, Catalano PM, Hsia DS, Inge TH, et al. An evolving scientific basis for the prevention and treatment of pediatric obesity. Int J Obes. (2014) 38:887–905. doi: 10.1038/ijo.2014.49
16. Brown T, Moore TH, Hooper L, Gao Y, Zayegh A, Ijaz S, et al. Interventions for preventing obesity in children. Cochrane Database Syst Rev . (2019) 7:CD001871. doi: 10.1002/14651858.CD001871.pub4
17. Smith E, Scarborough P, Rayner M, Briggs ADM. Should we tax unhealthy food and drink? Proc Nutr Soc. (2019) 77:314–20. doi: 10.1017/S0029665117004165
18. Adab P, Pallan M, Whincup PH. Is BMI the best measure of obesity? BMJ. (2018) 360:k 1274. doi: 10.1136/bmj.k1274
19. Anderson LN, Carsley S, Lebovic G, Borkhoff CM, Maguire JL, Parkin PC, et al. Misclassification of child body mass index from cut-points defined by rounded percentiles instead of Z-scores. BMC Res Notes. (2017) 10:639. doi: 10.1186/s13104-017-2983-0
20. Must A, Anderson SE. Body mass index in children and adolescents: consideration for population-based applications. Int J Obes. (2006) 30:590–4. doi: 10.1038/sj.ijo.0803300
21. Flegal KM, Wei R, Ogden C. Weight-for-stature compared with body mass index-for-age growth charts for the United States from the centers for disease control and prevention. Am J Clin Nutr. (2002) 75:761–6.22. doi: 10.1093/ajcn/75.4.761
22. Himes JH, Dietz WH. Guidelines for overweight in adolescent preventive services: recommendations from an expert committee. The expert committee on clinical guidelines for overweight in adolescent preventive services. Am J Clin Nutr. (1994) 59:307–16. doi: 10.1093/ajcn/59.2.307
23. Lazarus R, Baur L, Webb K, Blyth F. Body mass index in screening for adiposity in children and adolescents: systematic evaluation using receiver operating characteristic curves. Am J Clin Nutr. (1996) 63:500–6. doi: 10.1093/ajcn/63.4.500
24. McGinnis JM, Gootman JA. Food Marketing to Children and Youth: Threat or Opportunity? Institute of Medicine of the National Academies. Washington, DC: The National Academies Press. (2006).
25. Chaudhri OB, Salem V, Murphy KG, Bloom SR. Gastrointestinal satiety signals. Annu Rev Physiol. (2008) 70:239–55. doi: 10.1146/annurev.physiol.70.113006.100506
26. Scaglioni S, De Cosmi V, Ciappolino V, Parazzini F, Brambilla P, Agostoni C. Factors influencing children's eating behaviours. Nutrients. (2018) 10:706. doi: 10.3390/nu10060706
27. Ahima RS, Antwi DA. Brain regulation of appetite and satiety. Endocrinol Metab Clin North Am. (2008) 37:811–23. doi: 10.1016/j.ecl.2008.08.005
28. Niswender KD, Baskin DG, Schwartz MW. Review insulin and its evolving partnership with leptin in the hypothalamic control of energy homeostasis. Trends Endocrinol Metab. (2004) 15:362–9. doi: 10.1016/j.tem.2004.07.009
29. Niswender KD, Schwartz MW. Review insulin and leptin revisited: adiposity signals with overlapping physiological and intracellular signaling capabilities. Front Neuroendocrinol. (2003) 24:1–10. doi: 10.1016/S0091-3022(02)00105-X
30. Amitani M, Asakawa A, Amitani H, Inui. A. The role of leptin in the control of insulin-glucose axis. Front Neurosci. (2013) 7:51. doi: 10.3389/fnins.2013.00051
31. Cowley MA, Smith RG, Diano S, Tschöp M, Pronchuk N, Grove KL, et al. The distribution and mechanism of action of ghrelin in the CNS demonstrates a novel hypothalamic circuit regulating energy homeostasis. Neuron. (2003) 37:649–61. doi: 10.1016/S0896-6273(03)00063-1
32. Buhmann H, le Roux CW, Bueter M. The gut–brain axis in obesity. Best Prac Res Clin Gastroenterol. (2014) 28:559–71. doi: 10.1016/j.bpg.2014.07.003
33. Cone RD. Review anatomy and regulation of the central melanocortin system. Nat Neurosci. (2005) 8:571–8. doi: 10.1038/nn1455
34. Timper K, Brüning JC. Hypothalamic circuits regulating appetite and energy homeostasis: pathways to obesity. Dis Model Mech. (2017) 10:679–89. doi: 10.1242/dmm.026609
35. Labarthe A, Fiquet O, Hassouna R, Zizzari P, Lanfumey L, Ramoz N, et al. Ghrelin-derived peptides: a link between appetite/reward, gh axis, and psychiatric disorders? Front Endocrinol. (2014) 5:163. doi: 10.3389/fendo.2014.00163
36. Hills R. D Jr, Pontefract BA, Mishcon HR, Black CA, Sutton SC, Theberge CR. Gut microbiome: profound implications for diet and disease. Nutrients. (2019) 11:1613. doi: 10.3390/nu11071613
37. Torres-Fuentes C, Schellekens H, Dinan TG, Cryan JF. The microbiota-gut-brain axis in obesity. Lancet Gastroenterol Hepatol. (2017) 2:747–56. doi: 10.1016/S2468-1253(17)30147-4
38. Gérard P. Gut microbiota and obesity. Cell Mol Life Sci. (2016) 73:147–62. doi: 10.1007/s00018-015-2061-5
39. Derrien M, Alvarez AS, de Vos WM. The gut microbiota in the first decade of life. Trends Microbiol. (2019) 27:997–1010.40. doi: 10.1016/j.tim.2019.08.001
40. Dao MC, Clément K. Gut microbiota and obesity: concepts relevant to clinical care. Eur J Intern Med . (2018) 48:18–24.41. doi: 10.1016/j.ejim.2017.10.005
41. Kim KN, Yao Y., Ju SY. Short chain fatty acids and fecal microbiota abundance in humans with obesity: a systematic review and meta-analysis. Nutrients. (2019) 11:2512. doi: 10.3390/nu11102512
42. Castaner O, Goday A, Park YM, Lee SH, Magkos F, Shiow STE, et al. The gut microbiome profile in obesity: a systematic review. Int J Endocrinol. (2018) 2018:4095789. doi: 10.1155/2018/4095789
43. Riva A, Borgo F, Lassandro C, Verduci E, Morace G, Borghi E, et al. Pediatric obesity is associated with an altered gut microbiota and discordant shifts in firmicutes populations. Enviroin Microbiol. (2017) 19:95–105. doi: 10.1111/1462-2920.13463
44. Fernandes J, Su W, Rahat-Rozenbloom S, Wolever TMS, Comelli EM. Adiposity, gut microbiota and faecal short chain fatty acids are linked in adult humans. Nutr Diabetes . (2014) 4:e121. doi: 10.1038/nutd.2014.23
45. Rahat-Rozenbloom S, Fernandes J, Gloor GB, Wolever TMS. Evidence for greater production of colonic short-chain fatty acids in overweight than lean humans. Int J Obes . (2014) 38:1525–31. doi: 10.1038/ijo.2014.46
46. Barczyńska R, Litwin M, Slizewska K, Szalecki M, Berdowska A, Bandurska K, et al. Bacterial microbiota fatty acids in the faeces of overweight obese children. Pol. J. Microbiol. (2018) 67:339–45. doi: 10.21307/pjm-2018-041
47. Albillos A, de Gottardi A, Rescigno M. The gut-liver axis in liver disease: Pathophysiological basis for therapy. J Hepatol. (2020) 72:558–77. doi: 10.1016/j.jhep.2019.10.003
48. Yu EL, Golshan S, Harlow KE, Angeles JE, Durelle J, Goyal NP, et al. Prevalence of nonalcoholic fatty liver disease in children with obesity. J Pediatr. (2019) 207:64–70. doi: 10.1016/j.jpeds.2018.11.021
49. Ranucci G, Spagnuolo MI, Iorio R. Obese children with fatty liver: Between reality and disease mongering. World J Gastroenterol. (2017) 23:8277–82. doi: 10.3748/wjg.v23.i47.8277
50. Cox AJ, West NP, Cripps A. W. Obesity, inflammation, and the gut microbiota. Lancet Diabet Endocrinol. (2015) 3:207–15. doi: 10.1016/S2213-8587(14)70134-2
51. Seitz J, Trinh S, Herpertz-Dahlmann B. The microbiome and eating disorders. Psychiatr Clin North Am. . (2019) 42:93–103. doi: 10.1016/j.psc.2018.10.004
52. Deans E. Microbiome and mental health in the modern environment. J Physiol Anthropol. (2016) 36:1. doi: 10.1186/s40101-016-0101-y
53. Peirce JM, Alviña K. The role of inflammation and the gut microbiome in depression and anxiety. J Neurosci Res . (2019) 97:1223–41. doi: 10.1002/jnr.24476
54. Ranadive SA, Vaisse C. Lessons from extreme human obesity: monogenic disorders. Endocrinol Metab Clin North Am. (2008) 37:733–51. doi: 10.1016/j.ecl.2008.07.003
55. Soliman AT, Yasin M, Kassem A. Leptin in pediatrics: a hormone from adipocyte that wheels several functions in children. Indian J Endocrinol Metab . (2012) 16(Suppl. 3):S577–87. doi: 10.4103/2230-8210.105575
56. Farooqi IS, Wangensteen T, Collins S, Kimber W, Matarese G, Keogh JM, et al. Clinical and molecular genetic spectrum of congenital deficiency of the leptin receptor. N Engl J Med. (2007) 356:237–47. doi: 10.1056/NEJMoa063988
57. Mutch DM, Clément K. Unraveling the genetics of human obesity. PLoS Genet. (2006) 2:e188. doi: 10.1371/journal.pgen.0020188
58. Crocker MK, Yanovski JA. Pediatric obesity: etiology and treatment. Endocrinol Metab Clin North Am. (2009) 38:525–48. doi: 10.1016/j.ecl.2009.06.007
59. Huvenne H, Dubern B, Clément K, Poitou C. Rare genetic forms of obesity: clinical approach and current treatments in 2016. Obes Facts. (2016) 9:158–73. doi: 10.1159/000445061
60. Stefan M, Nicholls RD. What have rare genetic syndromes taught us about the pathophysiology of the common forms of obesity? Curr Diab Rep. (2004) 4:143–50. doi: 10.1007/s11892-004-0070-0
61. Hetherington MM, Cecil JE. Gene-Environment interactions in obesity. Forum Nutr. (2009) 63:195–203. doi: 10.1159/000264407
62. Reddon H, Guéant JL, Meyre D. The importance of gene-environment interactions in human obesity. Clin Sci. (2016) 130:1571–97. doi: 10.1042/CS20160221
63. Castillo JJ, Orlando RA, Garver WS. Gene-nutrient interactions and susceptibility to human obesity. Genes Nutr. (2017) 12:29. doi: 10.1186/s12263-017-0581-3
64. Heianza Y, Qi L. Gene-Diet interaction and precision nutrition in obesity. Int J Mol Sci. (2017) 18:787. doi: 10.3390/ijms18040787
65. Goodarzi MO. Genetics of obesity: what genetic association studies have taught us about the biology of obesity and its complications. Lancet Diabetes Endocrinol. (2018) 6:223–36. . doi: 10.1016/S2213-8587(17)30200-0
66. Bouchard L, Drapeau V, Provencher V, Lemieux S, Chagnon Y, Rice T, et al. Neuromedin beta: a strong candidate gene linking eating behaviors and susceptibility to obesity. Am J Clin Nutr. (2004) 80:1478–86. . doi: 10.1093/ajcn/80.6.1478
67. Grimm ER, Steinle NI. Genetics of eating behavior: established and emerging concepts. Nutr Rev. (2011) 69:52–60. . doi: 10.1111/j.1753-4887.2010.00361.x
68. van der Klaauw AA, Farooqi IS. The hunger genes: pathways to obesity. Cell. (2015) 161:119–32. . doi: 10.1016/j.cell.2015.03.008
69. Martinez JA. Bodyweight regulation causes of obesity. Proc Nutr Soc. (2000) 59:337–45. Review. doi: 10.1017/S0029665100000380
70. Rask-Andersen M, Karlsson T, Ek WE, Johansson Å. Gene-environment interaction study for BMI reveals interactions between genetic factors and physical activity, alcohol consumption and socioeconomic status. PLoS Genet. (2017) 5:1. doi: 10.1371/journal.pgen.1006977
71. Xulong S, Pengzhou L, Xiangwu Y, Weizheng L, Xianjie Q, Shaihong Z, et al. From genetics and epigenetics to the future of precision treatment for obesity. Gastroenterol Rep. (2017) 5:266–70. doi: 10.1093/gastro/gox033
72. Bianco-Miotto T, Craig JM, Gasser YP, van dijk SJ, Ozanne SE. Epigenetics and DOHaD: from basics to birth and beyond. J Dev Orig Health Dis. (2017) 8:513–9. doi: 10.1017/S2040174417000733
73. van Dijk SJ, Molloy PL, Varinli H, Morrison JL, Muhlhausler BS, Members of EpiSCOPE. Epigenetics and human obesity. Int J Obes . (2015) 39:85–97. doi: 10.1038/ijo.2014.34
74. Li Y. Epigenetic mechanisms link maternal diets and gut microbiome to obesity in the offspring. Front Genet . (2018) 9:342. doi: 10.3389/fgene.2018.00342
75. Kaufman J, Montalvo-Ortiz JL, Holbrook H, O'Loughlin K, Orr C, Kearney C, et al. Adverse childhood experiences, epigenetic measures, and obesity in youth. J Pediatr. (2018) 202:150–6.76. doi: 10.1016/j.jpeds.2018.06.051
76. May Gardner R, Feely A, Layte R, Williams J, McGavock J. Adverse childhood experiences are associated with an increased risk of obesity in early adolescence: a population-based prospective cohort study. Pediatr Res. (2019) 86:522–28. doi: 10.1038/s41390-019-0414-8
77. Cheon BK„ Hong YY. Mere experience of low subjective socioeconomic status stimulates appetite food intake. Proc Natl Acad Sci USA . (2017) 114:72–7. doi: 10.1073/pnas.1607330114
78. Alegría-Torres JA, Baccarelli A, Bollati V. Epigenetics lifestyle. Epigenomics . (2011) 3:267-77. doi: 10.2217/epi.11.22
79. Birch LL, Fisher JO. Development of eating behaviors among children and adolescents. Pediatrics . (2011) 101:539–49.
PubMed Abstract | Google Scholar
80. Birch L, Savage JS, Ventura A. Influences on the development of children's eating behaviours: from infancy to adolescence. Can J Diet Pract Res. (2007) 68:s1–s56.
81. Nielsen SJ, Popkin BM. Patterns and trends in food portion sizes, 1977- 1998. JAMA. (2003) 289:450–53. . doi: 10.1001/jama.289.4.450
82. Munoz KA, Krebs-Smith SM, Ballard-Barbash R, Cleveland LE. Food intakes of US children and adolescents compared with recommendations. Pediatrics. (1997) 100:323–29. doi: 10.1542/peds.100.3.323
83. Fisher JO, Birch LL. Restricting access to palatable foods affects children's behavioral response, food selection, and intake. Am J Clin Nutr. (1999) 69:1264–72. doi: 10.1093/ajcn/69.6.1264
84. Faith MS, Scanlon KS, Birch LL, Francis LA, Sherry B. Parent-child feeding strategies and their relationships to child eating and weight status. Obes Res. (2004) 12:1711–22. . doi: 10.1038/oby.2004.212
85. Smith AD, Sanchez N, Reynolds C, Casamassima M, Verros M, Annameier SK, et al. Associations of parental feeding practices and food reward responsiveness with adolescent stress-eating. Appetite. (2020) 152:104715. doi: 10.1016/j.appet.2020.104715
86. Lowe CJ, Morton JB, Reichelt AC. Adolescent obesity and dietary decision making-a brain-health perspective. Lancet Child Adolesc Health. (2020) 4:388–96. doi: 10.1016/S2352-4642(19)30404-3
87. Goran MI, Treuth MS. Energy expenditure, physical activity, and obesity in children. Pediatr Clin North Am. (2001) 48:931–53. doi: 10.1016/S0031-3955(05)70349-7
88. Romieu I, Dossus L, Barquera S, Blottière HM, Franks PW, Gunter M, et al. Energy balance and obesity: what are the main drivers? Cancer Causes Control. (2017) 28:247–58. doi: 10.1007/s10552-017-0869-z
89. Mattes R, Foster GD. Food environment and obesity. Obesity. (2014) 22:2459–61. doi: 10.1002/oby.20922
90. Ickovics JR, O'Connor Duffany K, Shebl FM, Peters SM, Read MS, Gilstad-Hayden KR, et al. Implementing school-based policies to prevent obesity: cluster randomized trial. Am J Prev Med. (2019) 56:e1–11. doi: 10.1016/j.amepre.2018.08.026
91. Micha R, Karageorgou D, Bakogianni I, Trichia E, Whitsel LP, Story M, et al. Effectiveness of school food environment policies on children's dietary behaviors: A systematic review and meta-analysis. PLoS ONE. ( 2018 ) 13:e0194555. doi: 10.1371/journal.pone.0194555
92. Cawley J, Frisvold D, Hill A, Jones DJ. The impact of the philadelphia beverage tax on purchases and consumption by adults and children. Health Econ. (2019) 67:102225. doi: 10.1016/j.jhealeco.2019.102225
93. John Cawley J, Thow AM, Wen K, Frisvold D. The economics of taxes on sugar-sweetened beverages: a review of the effects on prices, sales, cross-border shopping, and consumption. Annu Rev Nutr. (2019) 39:317–38. doi: 10.1146/annurev-nutr-082018-124603
94. Fuller C, Lehman E, Hicks S, Novick MB. Bedtime use of technology and associated sleep problems in children. Glob Pediatr Health. (2017) 4:2333794X17736972. doi: 10.1177/2333794X17736972
95. Chahal H, Fung C, Kuhle S, Veugelers PJ. Availability and night-time use of electronic entertainment and communication devices are associated with short sleep duration and obesity among Canadian children. Pediatr Obes. (2012) 8:42–51. doi: 10.1111/j.2047-6310.2012.00085.x
96. Minghua T. Protein intake during the first two years of life and its association with growth and risk of overweight. Int J Environ Res Public Health. ( 2018 ) 15:1742. doi: 10.3390/ijerph15081742
97. Azad MB, Vehling L, Chan D, Klopp A, Nickel NC, McGavock JM, et al. Infant feeding and weight gain: separating breast milk from breastfeeding and formula from food. Pediatrics. (2018) 142:e20181092. doi: 10.1542/peds.2018-1092
98. Lin L, Amissah E, Gamble GD, Crowther CA, Harding JE. Impact of macronutrient supplements on later growth of children born preterm or small for gestational age: a systematic review and meta-analysis of randomised and quasirandomised controlled trials. PLoS Med. (2020) 17:e1003122. . doi: 10.1371/journal.pmed.1003122
99. Rzehak P, Oddy WH, Mearin ML, Grote V, Mori TA, Szajewska H, et al. Infant feeding and growth trajectory patterns in childhood and body composition in young adulthood. Am J Clin Nutr. (2017) 106:568–80. doi: 10.3945/ajcn.116.140962
100. Styne DM, Arslanian SA, Connor EL, Farooqi IS, Murad MH, Silverstein JH. Pediatric obesity-assessment, treatment, and prevention: an endocrine society clinical practice guideline. J Clin Endocrinol Metab. (2017) 102:709–57. doi: 10.1210/jc.2016-2573
101. Whitaker RC, Pepe MS, Wright JA, Seidel KD, Dietz WH. Early adiposity rebound and the risk of adult obesity. Pediatrics . (1998) 101:E5. doi: 10.1542/peds.101.3.e5
102. Geserick M, Vogel M, Gausche R, Lipek T, Spielau U, Keller E, et al. Acceleration of BMI in early childhood and risk of sustained obesity. N Engl J Med. (2018) 379:1303–12. doi: 10.1056/NEJMoa1803527
103. Jabakhanji SB, Boland F, Ward M, Biesma RJ. Body mass index changes in early childhood. Pediatrics. (2018) 202:106–14. doi: 10.1016/j.jpeds.2018.06.049
104. Chung S. Growth and puberty in obese children and implications of body composition. J Obes Metab Syndr. (2017) 26:243–50. doi: 10.7570/jomes.2017.26.4.243
105. Tagi VM, Giannini C, Chiarelli F. Insulin resistance in children. Front Endocrinol. (2019) 10:342. doi: 10.3389/fendo.2019.00342
106. Kelesidis I, Mantzoros CS. Leptin and its emerging role in children and adolescents. Clin Pediatr Endocrinol . (2006) 15:1–14. doi: 10.1297/cpe.15.1
107. Burt Solorzano CM, McCartney CR, Obesity and the pubertal transition in girls and boys. Reproduction . (2010) 140:399–410. doi: 10.1530/REP-10-0119
108. Li W, Liu Q, Deng X, Chen Y, Liu S, Story M. Association between obesity and puberty timing: a systematic review and meta-analysis. Int J Environ Res Public Health. (2017) 14:1266. doi: 10.3390/ijerph14101266
109. Lee JM, Wasserman R, Kaciroti N, Gebremariam A, Steffes J, Dowshen S, et al. Timing of puberty in overweight vs. obese boys. Pediatrics. (2016) 137:e20150164. doi: 10.1542/peds.2015-0164
110. He J, Kang Y, Zheng L. Serum levels of LH, IGF-1 and leptin in girls with idiopathic central precocious puberty (ICPP) and the correlations with the development of ICPP. Minerva Pediatr . (2018). doi: 10.23736/S0026-4946.18.05069-7
111. Kang MJ, Oh YJ, Shim YS, Baek JW, Yang S, Hwang IT. The usefulness of circulating levels of leptin, kisspeptin, and neurokinin B in obese girls with precocious puberty. Gynecol Endocrinol. (2018) 34:627–30. doi: 10.1080/09513590.2017.1423467
112. Rendo-Urteaga T, Ferreira de Moraes AC, Torres-Leal FL, Manios Y, Gottand F, Sjöström M, et al. Leptin and adiposity as mediators on the association between early puberty and several biomarkers in European adolescents: the helena study. J Pediatr Endocrinol Metab. (2018) 31:1221–29. doi: 10.1515/jpem-2018-0120
113. Franks S. Adult polycystic ovary syndrome begins in childhood. Best Pract Res Clin Endocrinol Metab. (2002) 16:263–72. doi: 10.1053/beem.2002.0203
114. Franks S. Polycystic ovary syndrome in adolescents. Int J Obes. (2008) 32:1035–41. doi: 10.1038/ijo.2008.61
115. Jehan S, Zizi F, Pandi-Perumal SR, Wall S, Auguste E, Myers K, et al. Obstructive sleep apnea and obesity: implications for public health. Sleep Med Disord. (2017) 1:00019.
116. Patinkin ZW, Feinn R, Santos M. Metabolic consequences of obstructive sleep apnea in adolescents with obesity: a systematic literature review and meta-analysis. Childhood Obes. (2017) 13:102–10. doi: 10.1089/chi.2016.0248
117. Kaditis A. From obstructive sleep apnea in childhood to cardiovascular disease in adulthood: what is the evidence? Sleep. (2010) 33:1279–80. doi: 10.1093/sleep/33.10.1279
118. Marseglia L, Manti S, D'Angelo G, Nicotera A, Parisi E, Di Rose G, et al. Oxidative stress in obesity: a critical component in human diseases. Int J Mol Sci . (2014) 16:378–400. doi: 10.3390/ijms16010378
119. Eisele HJ, Markart P, Schulz R. Obstructive sleep apnea, oxidative stress, and cardiovascular disease: evidence from human studies. Oxid Med Cell Longev . (2015) 2015:608438. doi: 10.1155/2015/608438
120. Hui W, Slorach C, Guerra V, Parekh RS, Hamilton J, Messiha S, et al. Effect of obstructive sleep apnea on cardiovascular function in obese youth. Am J Cardiol. (2019) 123:341–7. doi: 10.1016/j.amjcard.2018.09.038
121. Matteoni CA, Younossi Z .m., Gramlich T, Boparai N, Liu YC, et al. Nonalcoholic fatty liver disease: a spectrum of clinical and pathological severity. Gastroenterology. (1999) 1999:116:1413. doi: 10.1016/S0016-5085(99)70506-8
122. Lavine JE, Schwimmer JB. Nonalcoholic fatty liver disease in the pediatric population. Clin Liver Dis. ( 2004 ) 8:549. doi: 10.1016/j.cld.2004.04.010
123. Huang JS, Barlow SE, Quiros-Tejeira RE, Scheimann A, Skelton J, Suskind D, et al. Childhood obesity for pediatric gastroenterologists. J Pediatr Gastroenterol Nutr. (2013) 2013:56:99. doi: 10.1097/MPG.0b013e31826d3c62
124. Anderson EL, Howe LD, Jones HE, Higgins JPT, Lawlor DA, Fraser A. The prevalence of non-alcoholic fatty liver disease in children and adolescents: a systematic review and meta-analysis. PLoS ONE. ( 2015 ) 10:e0140908. doi: 10.1371/journal.pone.0140908
125. Nobili V, Alisi A, Newton KP, Schwimmer JB. Comparison of the phenotype and approach to pediatric vs adult patients with nonalcoholic fatty liver disease. Gastroenterology. (2016) 150:1798–810. doi: 10.1053/j.gastro.2016.03.009
126. Rafiq N, Bai C, Fang Y, Srishord M, McCullough A, Gramlich T, et al. Long-term follow-up of patients with nonalcoholic fatty liver. Clin Gastroenterol Hepatol. (2009) 7:234–38. doi: 10.1016/j.cgh.2008.11.005
127. Feldstein AE, Charatcharoenwitthaya P, Treeprasertsuk S, Benson JT, Enders FB, Angula P. The natural history of non-alcoholic fatty liver disease in children: a follow-up study for up to 20 years. Gut. (2009) 58:1538. doi: 10.1136/gut.2008.171280
128. Schwimmer JB, Pardee PE, Lavine JE, Blumkin AK, Cook S. Cardiovascular risk factors and the metabolic syndrome in pediatric nonalcoholic fatty liver disease. Circulation . (2008) 118:277. doi: 10.1161/CIRCULATIONAHA.107.739920
129. Perry DC, Metcalfe D, Lane S, Turner S. Childhood obesity and slipped capital femoral epiphysis. Pediatrics. (2018) 142:e20181067. doi: 10.1542/peds.2018-1067
130. Zavala-Crichton JP, Esteban-Cornejo I, Solis-Urra P, Mora-Gonzalez J, Cadenas-Sanchez C, Rodriguez-Ayllon M, et al. Association of sedentary behavior with brain structure and intelligence in children with overweight or obesity: Active Brains Project . (2020) 9:1101. doi: 10.3390/jcm9041101
131. Ronan L, Alexander-Bloch A, Fletcher PC. Childhood obesity, cortical structure, and executive function in healthy children. Cereb Cortex. (2019) 30:2519–28. doi: 10.1093/cercor/bhz257
132. Baker ER. Body weight and the initiation of puberty. Clin Obstetr Gynecol. (1985) 28:573–9. doi: 10.1097/00003081-198528030-00013
133. Siervogel RM, Demerath EW, Schubert C, Remsberg KE, Chumlea WM, Sun S, et al. Puberty and body composition. Horm Res. (2003) 60:36–45. doi: 10.1159/000071224
134. Sadeeqa S, Mustafa T, Latif S. Polycystic ovarian syndrome- related depression in adolescent girls. J Pharm Bioallied Sci. (2018) 10:55–9. doi: 10.4103/JPBS.JPBS_1_18
135. Himelein MJ, Thatcher SS. Depression and body image among women with polycystic ovary syndrome. J Health Psychol . (2006) 11:613–25. doi: 10.1177/1359105306065021
136. Magge SN, Goodman E, Armstrong SC. The metabolic syndrome in children and adolescents: shifting the focus to cardiometabolic risk factor clustering. Pediatrics. (2017) 140:e20171603. doi: 10.1542/peds.2017-1603
137. Mauras N, Delgiorno C, Kollman C, Bird K, Morgan M, Sweeten S, et al. Obesity without established comorbidities of the metabolic syndrome is associated with a proinflammatory and prothrombotic state, even before the onset of puberty in children. J Clin Endocrinol Metab. (2010) 95:1060–8. doi: 10.1210/jc.2009-1887
138. Weiss R, Dziura J, Burgert TS, Tamborlane WV, Taksali SE, Yeckel CW, et al. Obesity and the metabolic syndrome in children and adolescents. N Engl J Med. (2004) 350:2362–74. doi: 10.1056/NEJMoa031049
139. Erdmann J, Kallabis B, Oppel U, Sypchenko O, Wagenpfeil S, Schusdziarra V. Development of hyperinsulinemia and insulin resistance during the early stage of weight gain. Am J Physiol Endocrinol Metabol. (2008) 294:e568–75. . doi: 10.1152/ajpendo.00560.2007
140. Pulido-Arjona L, Correa-Bautista JE, Agostinis-Sobrinho C, Mota J, Santos R, Correa-Rodrigues M, et al. Role of sleep duration and sleep- related problems in the metabolic syndrome among children and adolescents. Ital J Pediatr. (2018) 44:9. doi: 10.1186/s13052-018-0451-7
141. Harriger JA, Thompson JK. Psychological consequences of obesity: weight bias and body image in overweight and obese youth. Int Rev Psychiatry. (2012) 24:247–53. . doi: 10.3109/09540261.2012.678817
142. Bacchini D, Licenziati MR, Garrasi A, Corciulo N, Driul D, Tanas R, et al. Bullying and victimization in overweight and obese outpatient children and adolescents: an italian multicentric study. PLoS ONE. (2015) 10:e0142715. doi: 10.1371/journal.pone.0142715
143. Loth KA, Watts AW, Berg PVD, Neumark-Sztainer D. Does body satisfaction help or harm overweight teens? A 10-year longitudinal study of the relationship between body satisfaction and body mass index. J Adolesc Health. (2015) 57:559–61. doi: 10.1016/j.jadohealth.2015.07.008
144. Gowey MA, Lim CS, Clifford LM, Janicke DM. Disordered eating and health-related quality of life in overweight and obese children. J Pediatr Psychol. (2014) 39:552–61. doi: 10.1093/jpepsy/jsu012
145. Mannan M, Mamun A, Doi S, Clavarino A. Prospective associations between depression and obesity for adolescent males and females- a systematic review and meta-analysis of longitudinal studies. PLoS ONE. (2016) 11:e0157240. doi: 10.1371/journal.pone.0157240
146. Ruiz LD, Zuelch ML, Dimitratos SM, Scherr RE. Adolescent obesity: diet quality, psychosocial health, and cardiometabolic risk factors. Nutrients. (2019) 12:43. doi: 10.3390/nu12010043
147. Goldschmidt AB, Aspen VP, Sinton MM, Tanofsky-Kraff M, Wilfley DE. Disordered eating attitudes and behaviors in overweight youth. Obesity. (2008) 16:257–64. doi: 10.1038/oby.2007.48
148. Golden NH, Schneider M, Wood C. Preventing obesity and eating disorders in adolescents. Pediatrics. (2016) 138:e1–e12. doi: 10.1542/peds.2016-1649
149. Rastogi R, Rome ES. Restrictive eating disorders in previously overweight adolescents and young adults. Cleve Clin J Med. (2020) 87:165–71. doi: 10.3949/ccjm.87a.19034
150. Hayes JF, Fitzsimmons-Craft EE, Karam AM, Jakubiak JL, Brown ME, Wilfley D. Disordered eating attitudes and behaviors in youth with overweight and obesity: implications for treatment. Curr Obes Rep. (2018) 7:235. doi: 10.1007/s13679-018-0316-9
151. Goldschmidt AB, Wall MM, Loth KA, Neumark-Sztainer D. Risk factors for disordered eating in overweight adolescents and young adults: Table I. J Pediatr Psychol. (2015) 40:1048–55. doi: 10.1093/jpepsy/jsv053
152. Follansbee-Junger K, Janicke DM, Sallinen BJ. The influence of a behavioral weight management program on disordered eating attitudes and behaviors in children with overweight. J Am Diet Assoc. (2010) 110:653–9. doi: 10.1016/j.jada.2010.08.005
153. Blake-Lamb TL, Locks LM, Perkins ME, Woo Baidal JA, Cheng ER, Taveras EM. Interventions for childhood obesity in the first 1,000 days a systematic review. Am J Prev Med. (2016) 50:780–9. doi: 10.1016/j.amepre.2015.11.010
154. McGuire S. Institute of Medicine (IOM). Early childhood obesity prevention policies. Washington, DC: The National Academies Press. Adv Nutr . (2011) 3:56–7. doi: 10.3945/an.111.001347
155. Pont SJ, Puhl R, Cook SR, Slusser W. Stigma experienced by children and adolescents with obesity. Pediatrics. (2017) 140:e20173034. doi: 10.1542/peds.2017-3034
156. Puhl R, Suh Y. Health consequences of weight stigma: implications for obesity prevention and treatment. Curr Obes Rep. (2015) 4:182–90. doi: 10.1007/s13679-015-0153-z
157. Schwimmer JB, Burwinkle TM, Varni JW. Health-related quality of life of severely obese children and adolescents. JAMA. (2003) 289:1813–9. doi: 10.1001/jama.289.14.1813
158. Carcone AI, Jacques-Tiura AJ, Brogan Hartlieb KE, Albrecht T, Martin T. Effective patient-provider communication in pediatric obesity. Pediatr Clin North Am. (2016) 63:525–38. doi: 10.1016/j.pcl.2016.02.002
159. Coppock JH, Ridolfi DR, Hayes JF, Paul MS, Wilfley DE. Current approaches to the management of pediatric overweight and obesity. Curr Treat Options Cardiovasc Med. (2014) 16:343. doi: 10.1007/s11936-014-0343-0
160. Davison KK, Jurkowski JM, Li K, Kranz S, Lawson HA. A childhood obesity intervention developed by families for families: results from a pilot study. Int J Behav Nutr Phys Act. (2013) 10:3. doi: 10.1186/1479-5868-10-3
161. Krystia O, Ambrose T, Darlington G, Ma DWL, Buchholz AC, Haines J. A randomized home- based childhood obesity prevention pilot intervention has favourable effects on parental body composition: preliminary evidence from the guelph family health study. BMC Obes. (2019) 6:10. doi: 10.1186/s40608-019-0231-y
162. Skjåkødegård HF, Danielsen YS, Morken M, Linde SRF, Kolko RP, Balantekin KN, et al. Study protocol: a randomized controlled trial evaluating the effect of family-based behavioral treatment of childhood and adolescent obesity–The FABO-study. BMC Public Health. (2016) 16:1106. doi: 10.1186/s12889-016-3755-9
163. Hall KD, Kahan S. Maintenance of lost weight and long-term management of obesity. Med Clin North Am. (2018) 102:183–97. doi: 10.1016/j.mcna.2017.08.012
164. Hall KD. Diet vs. exercise in “the biggest loser” weight loss competition. Obesity. (2013) 21:957–9. doi: 10.1002/oby.20065
165. Lecoultre V, Ravussin E, Redman LM. The fall in leptin concentration is a major determinant of the metabolic adaptation induced by caloric restriction independently of the changes in leptin circadian rhythms. J Clin Endocrinol Metabol. (2011) 96:E1512–E516. doi: 10.1210/jc.2011-1286
166. Kaur KK, Allahbadia G, Singh M. Childhood obesity: a comprehensive review of epidemiology, aetiopathogenesis and management of this global threat of the 21st century. Acta Sci Paediatr. (2019) 2:56–66. doi: 10.31080/ASPE.2019.02.0132
167. Crimmins NA, Xanthakos SA. Obesity. in Neinstein's Adolescent and Young Adult Health , Guide. Philadelphia, PA: Wolters Kluwer (2016). p. 295–300.
168. Astrup A, Rossner S, Van Gaal L, Rissanen A, Niskanen L, Al Hakim M, et al. Effects of liraglutide in the treatment of obesity: a randomized, double-blind, placebo-controlled study. Lancet. (2009) 374:1606–16. doi: 10.1016/S0140-6736(09)61375-1
169. Monami M, Dicembrini I, Marchionni N, Rotella CM, Mannucci E. Effects of glucagon-like peptide-1 receptor agonists on body weight: a meta-analysis. Exp Diabetes Res. (2012) 2012:672658. doi: 10.1155/2012/672658
170. Pi-Sunyer X, Astrup A, Fujioka K, Greenway F, Halpern A, Krempf, et al. A randomized, controlled trial of 3.0 mg of liraglutide in weight management. N Engl J Med. (2015) 373:11–22 . doi: 10.1056/NEJMoa1411892
171. Kelly AS, Auerbach P, Barrientos-Perez M, Gies I, Hale PM, Marcus C, et al. A randomized, controlled trial of liraglutide for adolescents with obesity. N Engl J Med. (2020) 382:2117–28. doi: 10.1056/NEJMoa1916038
172. Foster BA, Escaname E, Powell T, Larsen B, Siddiqui SK, Menchaca J, et al. Randomized controlled trial of DHA supplementation during pregnancy: child adiposity outcomes. Nutrients . (2017) 9:566. doi: 10.3390/nu9060566
173. Abenavoli L, Scarpellini E, Colica C, Boccuto L, Salehi B, Sharifi-Rad J, et al. Gut microbiota and obesity: a role for probiotics. Nutrients. (2019) 11:2690. doi: 10.3390/nu11112690
174. Vajro P, Mandato C, Veropalumbo C, De Micco I. Probiotics: a possible role in treatment of adult and pediatric nonalcoholic fatty liver disease. Ann Hepatol. (2013) 12:161–63. doi: 10.1016/S1665-2681(19)31401-2
175. Zhao L, Fang X, Marshall M, Chung S. Regulation of obesity and metabolic complications by gamma and delta tocotrienols. Molecules. (2016) 21:344. doi: 10.3390/molecules21030344
176. Wong SK, Chin K-Y, Suhaimi FH, Ahmad F, Ima-Nirwana S. Vitamin E as a potential interventional treatment for metabolic syndrome: evidence from animal and human studies. Front Pharmacol. (2017) 8:444. doi: 10.3389/fphar.2017.00444
177. Galli F, Azzi A, Birringer A, Cook-Mills JM, Eggersdorfer M, Frank J, et al. Vitamin E: Emerging aspects and new directions. Free Radic Biol Med. (2017) 102:16–36. doi: 10.1016/j.freeradbiomed.2016.09.017
178. Galmés S, Serra F, Palou A. Vitamin E metabolic effects and genetic variants: a challenge for precision nutrition in obesity and associated disturbances. Nutrients . (2018) 10:1919. doi: 10.3390/nu10121919
179. Ahn SM. Current issues in bariatric surgery for adolescents with severe obesity: durability, complications, and timing of intervention. J. Obes Metabol Syndrome. (2020) 29:4–11. doi: 10.7570/jomes19073
180. Lamoshi A, Chernoguz A, Harmon CM, Helmrath M. Complications of bariatric surgery in adolescents. Semin Pediatr Surg. (2020) 29:150888. doi: 10.1016/j.sempedsurg.2020.150888
181. Weiss AL, Mooney A, Gonzalvo JP. Bariatric surgery. Adv Pediatr. (2017) 6:269–83. doi: 10.1016/j.yapd.2017.03.005
182. Stanford FC, Mushannen T, Cortez P, Reyes KJC, Lee H, Gee DW, et al. Comparison of short and long-term outcomes of metabolic and bariatric surgery in adolescents and adults. Front Endocrinol. (2020) 11:157. doi: 10.3389/fendo.2020.00157
183. Inge TH, Zeller MH, Jenkins TM, Helmrath M, Brandt ML, Michalsky MP, et al. Perioperative outcomes of adolescents undergoing bariatric surgery: the teen-longitudinal assessment of bariatric surgery (Teen-LABS) study . JAMA Pediatr . (2014) 168:47–53. doi: 10.1001/jamapediatrics.2013.4296
184. Järvholm K, Bruze G, Peltonen M, Marcus C, Flodmark CE, Henfridsson P, et al. 5-year mental health and eating pattern outcomes following bariatric surgery in adolescents: a prospective cohort study. Lancet Child AdolescHealth . (2020) 4:210–9. doi: 10.1016/S2352-4642(20)30024-9
185. Xanthakos SA. Bariatric surgery for extreme adolescent obesity: indications, outcomes, and physiologic effects on the gut–brain axis. Pathophysiology. (2008) 15:135–46. doi: 10.1016/j.pathophys.2008.04.005
186. Zitsman JL, Digiorgi MF, Kopchinski JS, Sysko R, Lynch L, Devlin M, et al. Adolescent Gastric Banding: a five-year longitudinal study in 137 individuals. Surg Obes Relat Dis. (2018) 14. doi: 10.1016/j.soard.2018.09.030
187. Inge TH, Jenkins TM, Xanthakos SA, Dixon JB, Daniels SR, Zeller MH, et al. Long-term outcomes of bariatric surgery in adolescents with severe obesity (FABS-5+). A prospective follow-up analysis. Lancet Diabet Endocrinol . (2017) 5:165–73. doi: 10.1016/S2213-8587(16)30315-1
188. Kindel TL, Krause C, Helm MC, Mcbride CL, Oleynikov D, Thakare R, et al. Increased glycine-amidated hyocholic acid correlates to improved early weight loss after sleeve gastrectomy. Surg Endosc. (2017) 32:805–12. doi: 10.1007/s00464-017-5747-y
Keywords: obesity, childhood, review (article), behavior, adolescent
Citation: Kansra AR, Lakkunarajah S and Jay MS (2021) Childhood and Adolescent Obesity: A Review. Front. Pediatr. 8:581461. doi: 10.3389/fped.2020.581461
Received: 08 July 2020; Accepted: 23 November 2020; Published: 12 January 2021.
Copyright © 2021 Kansra, Lakkunarajah and Jay. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Alvina R. Kansra, email@example.com
This article is part of the Research Topic
Pediatric Obesity: From the Spectrum of Clinical-Physiology, Social-Psychology, and Translational Research