childhood obesity issues essay

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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.

Introduction

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.

Biological Factors

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 Factors

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 ).

Developmental Factors

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 Factors

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 ).

Sleep Disorders

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 ).

Other Comorbidities

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 ).

Pharmacological Management

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

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.

Author Contributions

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.

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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.

Reviewed by:

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, akansra@mcw.edu

This article is part of the Research Topic

Pediatric Obesity: From the Spectrum of Clinical-Physiology, Social-Psychology, and Translational Research

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• Published: 20 October 2015

Biological, environmental, and social influences on childhood obesity

• M. Karen Campbell 1 , 2 , 3 , 4  

Pediatric Research volume  79 ,  pages 205–211 ( 2016 ) Cite this article

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The prevalence of childhood obesity has increased globally over the past three decades, with evidence of recent leveling off in developed countries. Reduction in the, currently high, prevalence of obesity will require a full understanding of the biological and social pathways to obesity in order to develop appropriately targeted prevention strategies in early life. Determinants of childhood obesity include individual level factors, including biological, social, and behavioral risks, acting within the influence of the child’s family environment, which is, in turn, imbedded in the context of the community environment. These influences act across childhood, with suggestions of early critical periods of biological and behavioral plasticity. There is evidence of sex and gender differences in the responses of boys and girls to their environments. The evidence that determinants of childhood obesity act at many levels and at different stages of childhood is of policy relevance to those planning early health promotion and primary prevention programs as it suggests the need to address the individual, the family, the physical environment, the social environment, and social policy. The purpose of this narrative review is to summarize current, and emerging, literature in a multilevel, life course framework.

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Introduction.

The prevalence of childhood obesity has increased globally over the past three decades, with more rapid increases recently occurring in low-income countries ( 1 ). In the United States, more than 30% of children are now overweight or obese ( 1 ), with evidence that the prevalence has leveled off ( 2 ). Children and adolescents are exhibiting obesity-related conditions such as type 2 diabetes, elevated blood pressure, low-density lipoprotein cholesterol, and higher fasting insulin levels ( 3 , 4 , 5 , 6 ). In addition, childhood obesity predicts adulthood obesity and its known health consequences ( 7 , 8 ). Treatment of obesity is notoriously difficult, with weight loss rarely sustained in adults ( 9 ). Therapeutic interventions in childhood are somewhat more successful, particularly if the intervention occurs prior to onset of puberty ( 10 ). However, real and sustained progress in combating the obesity epidemic will require a full understanding of the biological and social pathways to obesity in order to develop appropriately targeted prevention strategies in early life.

Pathways to childhood obesity are complex. It is therefore helpful to discuss determinants of obesity within a conceptual framework. A multilevel conceptual model, Bronfenbrenner’s Bioecological Systems Theory ( 11 ), has previously been applied to the conceptualization of childhood obesity by Davison and Birch ( 12 ). This framework depicts individual-level factors, including biological, social, and behavioral risks, as acting within the influence of the child’s family environment, which is, in turn imbedded in the context of the community environment. It is also helpful to consider critical periods for obesity risk and, as will be further illustrated in a later section, there are likely critical periods of biological and behavioral plasticity beginning as early as fetal life ( 13 ) with risk factors accumulating, and interacting with each other, across the life course. This is consistent with a life course model of chronic disease epidemiology ( 14 ). Specific determinants of obesity will be discussed below within this multilevel framework and life course perspective.

This narrative review will discuss both biological and social determinants of childhood obesity at three levels (individual, family, and community) and across early childhood. The relationship between childhood stress and obesity will be explored in greater detail as this is an important pathway of active interest in current literature. In addition, the review will address recent attention to sex- and gender-based differences in obesity risk. A key purpose in undertaking this review was to summarize evidence regarding pathways to obesity in boys and girls by integrating established plus emerging perspectives in the literature. These include an overview of important factors at each level. Given the breadth of the literature, it was not the intention to cover all literature on each determinant but rather to provide these as key examples of the many dimensions of obesity risk.

Individual-, Family-, and Community-Level Determinants of Obesity

At the individual level, the most direct determinant of children’s obesity is the energy balance between nutritional intake and activity, the latter being influenced by both physical activity and sedentary behaviors ( 15 , 16 , 17 ). These behavioral factors are therefore frequent targets for both preventive and therapeutic interventions. However, nutrition and activity are “downstream” factors that can be influenced by many “upstream” causes. The energy balance required to maintain an appropriate fat mass varies among individuals due to differences in metabolism and in lipostatic set point, which will influence appetite and activity preferences ( 18 ). Metabolism and lipostatic set point, while to some degree influenced by genetic predisposition ( 18 ), can be altered by gene–environment interactions ( 19 , 20 , 21 ).

The family, physical, and social environment influence children’s obesity risk in two ways: through a direct influence on children’s nutrition and activity behaviors and through indirect influences via stress as will be discussed later in this paper. Higher parental education, parental nurturing, and higher self-esteem reduce obesity risk in girls ( 22 ). There is an abundance of evidence that the home food environment ( 23 , 24 , 25 ), shared family meals ( 26 , 27 ), and electronic media use influence children’s obesity ( 28 ) largely through behavioral pathways. Mothers primarily establish the home food environment and are role models for eating behaviors ( 29 ) with evidence of strong correlation between the eating patterns of mothers and children ( 25 , 29 ). Appetite control and food preferences are established early in life ( 30 ), and there is a high correlation between parental obesity and their children’s obesity ( 20 , 22 ).

The community environment is increasingly obesogenic, with increased use of convenience foods, automobiles, and electronic and televised forms of entertainment ( 31 , 32 , 33 ) leading to higher consumption of calorie-dense foods and more sedentary lifestyles. Food choices have been shown to be influenced by proximity to fast food outlets, supermarkets, and farmers markets ( 34 , 35 , 36 , 37 , 38 ). Physical activity levels are influenced by public recreation opportunities, transit availability, and neighborhood walkability ( 35 , 37 , 39 , 40 , 41 , 42 ). In addition, lower obesity levels are observed in areas where the natural environment has high recreational value ( 43 ). While evidence suggests that the above environmental factors affect risk behaviors and obesity, there is still a gap in understanding how children interface with the obesogenic environment ( 44 ).

Prenatal and Postnatal Influences

There is emerging interest in prenatal factors, postnatal factors, and their interactions. These are critical time periods of metabolic and endocrine plasticity and may condition later physiologic responses to environmental influences ( 13 ). This field of research has been labeled as the developmental origins of health and disease and is the subject of much attention in the biomedical and epidemiologic sciences.

For the past two decades, there has been intense interest in the possible effect of fetal undernutrition on later obesity. The interest in this proposed association was precipitated by seminal work by Barker ( 45 ). In humans, fetal undernutrition may be a consequence of maternal undernutrition, maternal smoking, or placental dysfunction from preeclampsia. Markers of fetal undernutrition, which include fetal growth restriction and its proxy indicator small birth weight for gestational age, have been shown to be associated with a modestly elevated risk of obesity. It has been suggested that this effect is due to an in utero adaptation that becomes a mismatch to a postnatal environment in which nutrition is abundant ( 46 , 47 ). Animal studies, often based on maternal dietary restriction, confirm evidence for such fetal metabolic adaptations to undernutrition ( 48 ). In both animal and human studies, there is evidence of the permanence of these adaptations. The greatest elevation in obesity risk is for those who were born small, but experienced rapid “catch up growth” postnatally ( 48 , 49 , 50 , 51 , 52 ).

Emerging literature is challenging the relationship of fetal undernutrition as a determinant of obesity. First, if the association does exist, is a genetic component partially responsible? Specific adult obesity gene loci have been implicated as associated both with fetal growth ( 53 ) and with growth velocity in infancy ( 54 ). In this genomic era, this will be an aspect of the literature to watch, although to date the predictive value of individual gene loci for obesity risk has been modest. There is emerging speculation as to whether this association indeed exists at all, despite the abundance of literature on the topic. Part of this speculation is based on a statistical argument that, in the zealous effort to control for the myriad of potential confounders, most studies looking at the relationship between fetal growth restriction or small birth weight for gestational age and later chronic conditions have controlled for variables along the causal pathway and thus introduced bias ( 55 , 56 ). Moreover, recent carefully analyzed studies have suggested the inverse; that small birth weight for gestational age is associated with a lower risk of obesity ( 57 ). This question remains an active topic of interest in the literature, despite the recognition that the association, if real, is a small magnitude association with no clear implications for prevention ( 58 ).

Fetal overnutrition, evidenced by large infant birth weight for gestational age, is a strong predictor of obesity in childhood and later life ( 59 , 60 , 61 ). A caveat is that, while large infant birth weight for gestational age is generally an indicator of excess fat mass, it may also reflect other growth parameters such that a subset of large infant birth weight for gestational age infants may have increased lean mass ( 62 , 63 ). Risk factors for large infant birth weight for gestational age include maternal obesity and maternal gestational diabetes ( 64 , 65 ) with African-American women exhibiting risk at lower maternal BMI thresholds ( 66 ). It is suggested that fetal hyperglycemia triggers fetal insulin production which in turn triggers fetal growth and adiposity ( 67 ). Animal studies demonstrate that fetal hyperinsulinemia may invoke permanent changes in the CNS mechanisms for regulating metabolism and body weight ( 67 ). Thus, fetal overnutrition may be a mechanism of intergenerational transmission of obesity and diabetes ( 67 , 68 ).

Early postnatal experiences are also important contributors to obesity risk. Breastfed infants are at lower risk for later obesity ( 69 , 70 , 71 , 72 , 73 ) for hypothesized reasons including that formula-fed infants develop greater reliance on external hunger cues ( 74 ) and have higher intake of protein ( 75 ), which may contribute to obesity risk through behavioral and physiologic mechanisms, respectively. The benefits of breastfeeding appear to be confined to exclusive breastfeeding; mixed infant feeding of breastmilk and formula do not reduce obesity risks associated with formula feeding ( 76 ). In addition, the timing and choice of complementary foods introduced into an infant’s diet may influence their food preferences in the long term ( 77 ). In general, obesity risk is elevated for those who experienced rapid early weight gain in infancy ( 78 , 79 , 80 ). Based on this knowledge, strategies for primary prevention in high-income countries may include support for long-term breastfeeding ( 81 ).

Psychosocial Vulnerabilities

There is evidence that psychosocial stress is associated with obesity in children. Measures of stress vary from study to study ( 82 ), but the findings are consistent. Whether this association is causal is not known, but there are theoretical frameworks that suggest causality. For example, the life course–stress process perspective introduced by Pearlin et al . ( 83 ) has been discussed by Wickrama et al . ( 84 ) in the context of body mass. A pathway from stress to obesity could include inflammatory mechanisms ( 85 ) including arousal of the hypothalamic–pituitary–adrenal axis leading to increased cortisol levels and subsequent metabolic disruption and increased hunger ( 84 , 86 , 87 , 88 ). If so, nutrition may mediate the relationship between stress and obesity, or lifestyle factors may be coexisting with environmental stressors ( 89 , 90 ). Some of the reported associations of environmental stressors with childhood overweight and obesity include negative life events ( 82 ), maltreatment ( 91 ), how well the family communicates ( 90 ), and parental stress ( 92 ).

Depression and obesity are often comorbid in both children and adults. This comorbidity may be due to common genetic and environmental etiologies ( 93 , 94 , 95 , 96 ) or common pathways via dysregulation of the hypothalamic–pituitary–adrenal system ( 93 , 95 , 96 ). Increased food intake and reduced physical activity are characteristic of both conditions ( 94 ). Bidirectional causation is also plausible, with suggestions that obesity may be a determinant of later depression in children ( 97 , 98 , 99 ) and conversely hypothesized mechanisms for depression causing obesity ( 93 , 95 , 98 , 99 , 100 ). Indeed, it has more recently been suggested that these two comorbid conditions may mutually reinforce a progressive downward spiral in each other ( 101 ) and that additional insight into their longitudinal interaction may be important for intervention strategies ( 102 ).

Mothers’ mental and emotional well-being has been shown to be associated with childhood obesity. Children of mothers with depressive symptoms are more likely to be obese or overweight in infancy ( 103 , 104 ), childhood ( 105 , 106 ), and adolescence ( 107 ). Prenatal exposure to maternal stress and distress has been shown to be associated with both children’s obesity and rapid postnatal growth ( 108 , 109 ). Proposed mechanisms for the association include infant feeding practices ( 110 ), mother–infant interaction ( 111 ), mother–infant feeding interactions ( 112 ), parenting style ( 113 ), and a direct effect of stressors leading to central adiposity via arousal of the child’s hypothalamic–pituitary–adrenal axis ( 86 ). It has also been suggested that, due to the comorbidity between maternal overweight and emotion regulation, these pathways may also play into the intergenerational transfer of overweight and obesity ( 112 ), as well as the roles of shared genes and environment ( 86 ). A recent systematic review noted the need for more prospective studies to confirm and explain these associations ( 114 ).

Consistently, in high-income countries, socioeconomic disadvantage has been shown to be associated with obesity risk in childhood and persistently throughout life ( 115 , 116 , 117 ). Socioeconomic disadvantage may exert its influence as early as the prenatal and postnatal period, through its association with maternal depression ( 106 , 118 ) and its consequences. Moreover, poverty may be associated with poorer individual diet ( 119 ), poorer retail food and recreational environment ( 34 , 120 , 121 ), suboptimal family food routines ( 118 , 122 ), and environmental stressors such as living in a higher crime neighborhood ( 121 ). The risks associated with socioeconomic disadvantage may accumulate and compound throughout childhood ( 123 ). Miller and Chen ( 124 ) present a theoretical model, with corresponding research evidence, linking poverty to the development of a proinflammatory phenotype and subsequent elevated risk for chronic conditions in childhood and beyond. Overall, it appears that poverty is associated with later obesity through its association with other obesity risk factors and through the stress process.

There is an increasing attention in the literature to the differences in vulnerabilities in boys and girls, suggesting different pathways to obesity. Much of the literature, to date, has looked at determinants of childhood obesity while statistically controlling for children’s sex. However, to truly understand the developmental processes leading to obesity, researchers may need to look at boys and girls separately in order to recognize both sex-specific (biological) and gender-specific (social and cultural) differences in the ways in which boys and girls interact with their physical and social environments. Some biological differences include body composition and growth patterns, with clear sex differences in the distribution of adiposity beginning as early as the neonatal period and continuing through adulthood ( 125 ). Energy requirements and the aptitude for specific physical activities exhibit sex differences, while specific gender differences include how boys and girls interact with their family and their food environment as well as their overall physical activity levels ( 126 ). There are also gender differences in metabolic responses to stress ( 87 ) and family disruption or conflict ( 127 ). Responses to the physical and social environment will influence, and be influenced by, pubertal development ( 47 , 48 , 125 ). Pubertal timing itself has significant influence on insulin resistance and metabolic syndrome, particularly in girls ( 128 , 129 ). The pubertal transition is also well established as a time when depression rates rise dramatically, particularly for females; indeed, this developmental stage is when the gender difference in depression emerges ( 130 , 131 ). Finally, pubertal timing and growth influence later adult cardiovascular risk in both males and females ( 128 ). Additional research focusing on the gendered dimensions of childhood obesity is needed.

Summary and Implications

In undertaking a review of this broad area of significant health promotion interest, I have used the narrative review method. It has been argued that narrative reviews have advantages when the scope and literature coverage is broad and covers a range of issues within a given topic ( 132 ). This broader coverage comes at the expense of the more explicit methods, reporting and reproducibility, that are associated with systematic reviews, which tend to focus on narrower topics using prescribed search methods ( 132 ). Given the methodological limitations of the narrative method, and the acknowledged potential for selection biases in study selection when a nonsystematic review is undertaken, the reader should turn to determinant-specific systematic reviews for exhaustive discussion of the specific determinants covered in this review. The main objective of this review was to summarize key early determinants of childhood obesity within the important framework of individual-, family-, and community-level biological and social influences acting across early life.

Consideration of determinants of obesity within this broader multilevel framework may imply that strategies for health promotion and primary prevention should include attention to determinants at all levels. The upstream influences on childhood obesity occur at many levels, including the family and the community, and begin very early in the life course. Health promotion activities typically target individual lifestyle factors, despite emerging evidence of the importance of broader environmental prevention targets ( 133 ). Family-based interventions to improve the home food environment ( 90 ) and parenting style ( 134 ) and policies to reduce the costs of healthy food choices ( 135 ) are needed. Prevention efforts should also include programs to reduce financial stress in families and programs aimed at teaching children on how to cope with stressors in their environment ( 86 ). It has been suggested that overweight and obesity reductions may accrue if the prevention focus is shifted, more broadly, to promoting healthy lifestyles and healthy environments and beyond the focus on individual children’s body weight as the outcome ( 136 ). The opportunities for early health promotion require attention simultaneously to many levels ( 30 ), suggesting the need to address the individual, family, and physical environment, the social environment, and social policy.

Statement of Financial Support

none; there are no conflicts of interest.

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M. Karen Campbell

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Campbell, M. Biological, environmental, and social influences on childhood obesity. Pediatr Res 79 , 205–211 (2016). https://doi.org/10.1038/pr.2015.208

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How To Write an Essay About Childhood Obesity

Understanding childhood obesity.

Writing an essay about childhood obesity requires a comprehensive understanding of the topic. Childhood obesity is a serious public health issue that has grown significantly in recent years. It's characterized by children having a body mass index (BMI) at or above the 95th percentile for children of the same age and sex. Start by exploring the causes of childhood obesity, which can include genetic factors, poor dietary habits, lack of physical activity, and environmental influences. Also, consider the short and long-term health implications, such as an increased risk of chronic diseases like diabetes and heart disease. This foundational knowledge sets the stage for a deeper analysis in your essay.

Developing a Focused Thesis Statement

Your essay should be guided by a clear, focused thesis statement. This statement should present a specific angle or argument about childhood obesity. For instance, you might argue the importance of early intervention programs, the role of schools in promoting healthy lifestyles, or the impact of advertising and media on children’s eating habits. Your thesis will determine the direction of your essay, guiding your analysis and ensuring a structured approach to the topic.

Gathering and Analyzing Data

An effective essay on childhood obesity should be supported by relevant data and research. This includes statistics on the prevalence of obesity, studies on its causes and effects, and evaluations of intervention programs. Use this information to support your thesis, incorporating both national and global perspectives. Analyze the data critically, acknowledging any limitations and considering different viewpoints. This approach adds depth to your essay and strengthens your arguments.

Discussing Solutions and Interventions

A significant portion of your essay should be dedicated to discussing potential solutions and interventions for childhood obesity. This can include public health policies, educational programs, changes in food industry practices, or community-based initiatives. Evaluate the effectiveness of these solutions, drawing on case studies or research findings. Discussing both the successes and challenges in tackling childhood obesity will provide a balanced view and demonstrate a comprehensive understanding of the topic.

Concluding the Essay

Conclude your essay by summarizing the main points of your discussion and restating your thesis in light of the evidence presented. Your conclusion should tie together your analysis and emphasize the significance of addressing childhood obesity. This is also an opportunity to reflect on potential future developments in the field or to suggest areas for further research.

Reviewing and Refining the Essay

After completing your essay, it's important to review and refine it. Check for coherence in your arguments and clarity in your writing. Ensure that your essay is well-organized and free from grammatical errors. Consider seeking feedback from peers, teachers, or health professionals to further improve your work. A well-crafted essay on childhood obesity should not only inform but also engage readers in considering the complexities of this public health issue and the collective efforts required to address it.

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Childhood Obesity Facts

• Prevalence of Childhood Obesity in the United States

Obesity and Socioeconomic Status

Women, infant, children (wic) data.

Childhood obesity is a serious problem in the United States, putting children and adolescents at risk for poor health. Obesity prevalence among children and adolescents is still too high.

For children and adolescents aged 2-19 years in 2017-2020 1 :

• The prevalence of obesity was 19.7% and affected about 14.7 million children and adolescents.
• Obesity prevalence was 12.7% among 2- to 5-year-olds, 20.7% among 6- to 11-year-olds, and 22.2% among 12- to 19-year-olds. Childhood obesity is also more common among certain populations.
• Obesity prevalence was 26.2% among Hispanic children, 24.8% among non-Hispanic Black children, 16.6% among non-Hispanic White children, and 9.0% among non-Hispanic Asian children.
• Obesity-related conditions include high blood pressure, high cholesterol, type 2 diabetes, breathing problems such as asthma and sleep apnea, and joint problems.

1 Read CDC National Center for Health Statistics (NCHS) data brief

Note:  Obesity is defined as a body mass index (BMI) at or above the 95th percentile of the CDC sex-specific BMI-for-age growth charts .

• Physical Activity
• Overweight & Obesity
• Healthy Weight, Nutrition, and Physical Activity
• Breastfeeding
• Micronutrient Malnutrition
• State and Local Programs
• Prevent Type 2 Diabetes
• Prevent Heart Disease
• Healthy Schools – Promoting Healthy Behaviors
• Obesity Among People with Disabilities

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Home — Essay Samples — Nursing & Health — Public Health Issues — Childhood Obesity

Essays on Childhood Obesity

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Dont Blame The Eater Analysis

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The Importance of Solving The Problem of Childhood Obesity

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Child Obesity and Its Effects on Population Health

The main causes of childhood obesity: child's environment, the problem of childhood obesity in america, actions needed to prevent childhood obesity in the usa, the roles of parents, schools, and the media in child obesity, a discussion of whether parents are responsible for childhood obesity, childhood obesity as a nutritional issue in new zealand, the influence of obesogenic environment on the rise of child obesity in the united states, the issue of consumer manipulation responsible for child obesity, childhood obesity outbreak: a challenge on parenting, problems, and inference, the nationwide epidemic of child obesity and its prevention, the factors contributing to child obesity in the united states, the contributions of the nature versus nurture theories in child obesity, research on lifestyle and diet of students, combatting child obesity, obesity in america, importance of a healthy lifestyle and adopting nutritious eating habits, the impact of childhood obesity: causes, consequences, and solutions, a comprehensive approach to physical activity at euclid middle school, importance of good health.

Childhood obesity is a condition where excess body fat negatively affects a child's health or well-being.

Childhood obesity can be brought on by a range of factors which often act in combination. "Obesogenic environment" is the medical term set aside for this mixture of elements. The greatest risk factor for child obesity is the obesity of both parents. This may be reflected by the family's environment and genetics. Other reasons may also be due to psychological factors and the child's body type.

The first problems to occur in obese children are usually emotional or psychological. However it can also lead to life-threatening conditions including diabetes, high blood pressure, heart disease, sleep problems, cancer, and other disorders. Some of the other disorders would include liver disease, early puberty or menarche, eating disorders such as anorexia and bulimia, skin infections, and asthma and other respiratory problems.

Black and Latino youths have substantially higher rates of overweight and obesity than do their White peers. An overweight adolescent has a 70 percent chance of becoming an overweight or obese adult. Since 1980, the obesity prevalence among children and adolescents has almost tripled. Children with obesity have three times more healthcare expenditures than children at healthy weights, costing an estimated $14 billion every year.

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• Eating Disorders
• Drug Addiction
• Teenage Pregnancy
• Vaccination
• Birth Control

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Prevention and Management of Childhood Obesity and its Psychological and Health Comorbidities

Justin d. smith.

1 Department of Psychiatry and Behavioral Sciences, Department of Preventive Medicine, and Department of Pediatrics, Northwestern University Feinberg School of Medicine, Chicago, 750 N. Lake Shore Drive, Illinois, 60611, USA

2 Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine, 750 N. Lake Shore Drive, Chicago, Illinois, 60611, USA

Marissa Kobayashi

3 Department of Public Health Sciences, University of Miami Miller School of Medicine, 1120 NW 14th Street, Suite 1009, Miami, FL 33136. Phone: (305) 972-9961

Childhood obesity has become a global pandemic in developed countries, leading to a host of medical conditions that contribute to increased morbidity and premature death. The causes of obesity in childhood and adolescence are complex and multifaceted, presenting researchers and clinicians with myriad challenges in preventing and managing the problem. This chapter reviews the state-of-the-science for understanding the etiology of childhood obesity, the preventive interventions and treatment options for overweight and obesity, and the medical complications and co-occurring psychological conditions that result from excess adiposity, such as hypertension, non-alcoholic fatty liver disease, and depression. Interventions across the developmental span, varying risk levels, and service contexts (e.g., community, school, home, and healthcare systems) are reviewed. Future directions for research are offered with an emphasis on translational issues for taking evidence-based interventions to scale in a manner that reduce the public health burden of the childhood obesity pandemic.

1.0. INTRODUCTION

Influenced by genetics, biology, psychosocial factors, and health behaviors, overweight and obesity (OW/OB) in childhood is a complex public health problem affecting the majority of developed countries worldwide. Additionally, the key contributors to obesity—poor diet and physical inactivity—are among the leading causes of preventable youth deaths, chronic disease, and economic health burden ( Friedemann et al 2012 , Hamilton et al 2018 ). Despite the remarkable need to prevent childhood obesity and to intervene earlier to prevent excess weight gain in later developmental periods, few interventions have demonstrated long-lasting effects or been implemented at such a scale to have an appreciable public health impact ( Hales et al 2018 ).

In this review, we describe the extent and nature of the childhood obesity pandemic, present conceptual and theoretical models for understanding its etiology, and take a translational-developmental perspective in reviewing intervention approaches within and across developmental stages and in the various contexts in which childhood OW/OB interventions are delivered. We pay particular attention to co-occurring psychological conditions intertwined with OW/OB for children, adolescents, and their families as they relate to both development/etiology and to intervention. For this reason, our review begins with interventions aimed at prevention and moves to management and treatment options for obesity and its psychological and medical comorbidities. Then, we discuss the state-of-the-science and expert recommendations for interventions to prevent and manage childhood OW/OB and what it would take to implement current evidence-based programs at scale. Last, we end by discussing identified gaps in the literature to inform future directions for research and the translation of research findings to real-world practice that can curb the pandemic. For readability, we use the term “interventions for the prevention and management of childhood OW/OB” to capture an array of approaches referred to by a variety of monikers in the literature, including primary prevention, prevention of excess weight gain, weight loss intervention, weight management, and treatment of obesity. More specific labels are used when needed.

2.0. EPIDEMIOLOGY OF CHILDHOOD OBESITY

Childhood OW/OB is determined by the child’s height and weight to calculate body mass index (BMI), which is adjusted according to norms based on the child’s age and gender. BMI between the 85th and 94th percentile is in the “overweight” range, whereas BMI ≥ 95 th percentile for age and gender is in the “obese” range ( Centers for Disease Control and Prevention [CDC] 2018 ). Rates of obesity among children and adolescents in developed countries worldwide, collected in 2013, were 12.9% for boys and 13.4% for girls ( Ng et al 2014 ). In the United States (US) from 1999–2016, 18.4% of children ages 2–19 years had obesity, and 5.2% had severe obesity, defined as BMI ≥120% of the 95th percentile for age and gender ( Skinner et al 2018 ). The prevalence of obesity has increased between 2011–2012 and 2015–2016 in children ages 2–5 and 16–19 years ( Hales et al 2018 ). Being in the obese range during childhood or adolescence makes the youth five times more likely to be obese in adulthood compared to peers who maintain a healthy weight ( Simmonds et al 2016 ). Compared to obesity, severe obesity is strongly linked with greater cardiometabolic risk, adult obesity, and premature death ( Skinner et al 2015 ).

OW/OB and its health consequences are disproportionately distributed across the US, with a higher prevalence among children of disadvantaged racial and socioeconomic backgrounds. Rates of OW/OB are significantly higher among Non-Hispanic black and Hispanic children compared to Non-Hispanic White children (e.g., Hales et al 2018 ). Such disparities are particularly pronounced among severe obesity, where 12.8% of African American children, and 12.4% of Hispanic children have severe obesity compared to 5.0% of Non-Hispanic White children ( Hales et al 2018 ). Youth in low socioeconomic households are more likely to develop OW/OB compared to their counterparts in high socioeconomic households. In 2011–2014, 18.9% of children ages 2–19 living in the lowest income group (≤130% of Federal Poverty Line) had obesity, whereas 10.9% of children in the highest income group (>350% Federal Poverty Line) had obesity ( Ogden et al 2018 ). Influences on multiple socioecological levels put racially diverse children of low socioeconomic status (SES) at higher risk of developing OW/OB, which is further exacerbated by limited access to health services that can prevent excess weight gain and its sequelae.

3.0. ETIOLOGY OF CHILDHOOD OBESITY

At the most basic level, childhood OW/OB emerges from consuming more calories than expended, resulting in excess weight gain and an excess body fat. Caloric imbalance is the result of, and can be further exacerbated by, a range of obesogenic behaviors. That is, behaviors that are highly correlated with excess weight gain. The most common obesogenic behaviors are high consumption of sugar sweetened beverages and low-nutrient, high saturated fat foods, low levels of physical activity and high levels of sedentary behaviors, and shortened sleep duration (e.g., Sisson et al 2016 ). Diet, physical activity, screen time, and sleep patterns are influenced by a myriad of factors and interactions involving genetics, interpersonal relationships, environment, and community (e.g., Russell & Russell 2019 , Smith et al 2018d ). Children living in the United States commonly consume the “Western Diet,” known as a diet high in calories, rich in sugars, trans and saturated fats, salt and food additives, and low in complex carbohydrates, and vitamins. Poor sleep patterns, defined as short duration and late timing, can contribute to obesity through changing levels of appetite-regulating hormones, and irregular eating patterns including late night snacking and eating ( Miller et al 2015 ). Children who experience shortened night time sleep from infancy to school age are at increased risk of developing OW/OB compared to same-aged children sleeping average, age-specific hours (e.g., Taveras et al 2014 ). Research indicates that children with higher rates of screen time also consume high levels of energy-dense snacks, beverages, and fast food, and fewer fruits and vegetables, and screen time is hypothesized to affect food and beverage consumption through distracted eating, reducing feelings of satiety or fullness, and exposure to advertisements for junk food (sweet and salty, calorically-dense foods) ( Robinson et al 2017 ). Screen time can also negatively affect children’s sleeping patterns, and is correlated with sedentary behaviors (e.g., watching television, playing video games) ( Hale & Guan 2015 ).

3.1. Conceptual Models for Understanding and Addressing Childhood OW/OB

Conceptualizing development of childhood OW/OB requires consideration of interplay of genetic, biological, psychological, behavioral, interpersonal, and environment factors ( Kumar & Kelly 2017 ). OW/OB interventions are typically designed to account for these multilevel factors to assist children in achieving expert recommendations for physical activity and fruit and vegetable consumption, while limiting sugar sweetened beverages intake and screen time, and regulating sleep patterns ( Kakinami et al 2019 ). Creating behavioral change requires understanding of the multi-level interactions to identify opportunities for intervention to prevent excess weight gain long-term. A variety of conceptual models exist to explain potential interactions and individual influences leading to obesogenic behaviors and development of childhood OW/OB, and targets for improving health behaviors and routines. Importantly, basic science and conceptual models can be translated to develop effective, targeted intervention programs for prevention of excess weight gain.

3.1.1. Biopsychosocial model

The biopsychosocial model combines biological foundations in child development with environmental and psychosocial influences to identify and address mechanisms and processes to prevent and manage development of childhood OW/OB ( Russell & Russell 2019 ). This model features biological factors, such as genetics, alongside environmental, psychosocial, and behavioral risk factors (e.g., family disorganization, parenting skills, feeding practices, child appetite, temperament), and the development of self-regulation. Such an approach can illustrate developmental processes interacting with biological underpinnings that can be targeted in prevention and management interventions for OW/OB. Intervening from a biopsychosocial model involves cognitive behavioral and behavioral therapy to reframe thoughts and replace unhealthy eating behaviors with new habits.

3.1.2. Ecological systems theory (EST)

EST embeds individual development and change within multiple proximal and distal contexts and emphasizes the need to understand how an “ecological niche” can contribute to the development of specific characteristics, and how such niches are embedded in more distal contexts ( Davison & Birch 2001 ). For example, a child’s ecological niche can be the family or school, which are embedded in larger social contexts, such as the community and society. Individual child characteristics, such as gender and age, interact within and between the family and community context levels, which all influence development of OW/OB. The EST model presents various predictors of childhood OW/OB through identifying risk factors moderated by intraindividual child characteristics. The structure of the EST is present in various studies examining influences of community exposures and children’s individual attributes on weight outcomes.

3.1.3. The Six C’s Model

The Six-C’s is a developmental ecological model that includes environmental (family, community, country, societal), personal, behavioral, and hereditary influences, and a system for categorizing environmental influences, all of which can be adapted to each stage of child development from infancy to adolescence ( Harrison et al 2011 ). The Six C’s stand for: cell, child, clan, community, country, and culture, which represent biology/genetics, personal behaviors, family characteristics, factors outside of the home including peers and school, state and national-level institutions, and culture-specific norms, respectively. Each C includes factors that contribute to child obesity that occur and interact simultaneously throughout child development. For example, among preschool age children, obesity-predisposing genes (cell), excessive media exposure (child), parent dietary intake (clan), unhealthful peer food choices (community), national economic recession, (country) and oversized portions (culture), are all factors associated with obesity that can occur simultaneously and interact during this developmental stage.

3.1.3. The developmental cascade model of pediatric obesity

The model described in the Smith et al. (2018b) article offers a longitudinal framework to elucidate the way cumulative consequences and spreading effects of multiple risk and protective factors, across and within biopsychosocial spheres and phases of development, can propel children towards OW/OB outcomes. The cascade model of pediatric obesity ( Figure 1 ) was developed using a theory-driven model-building approach and a search of the literature to identify paths and relationships in the model that were empirically based. The model allows for different pathways and interactions between different combinations of variables and constructs that contribute to pediatric obesity (equifinality), identifying multi-level risk and protective factors spanning from the prenatal stage to adolescence stage. The complete model can, but has yet to, be tested. The model focuses on intra- and inter-individual child processes and mechanisms (e.g., parenting practices), while acknowledging that individuals are embedded within the broader ecological systems. St. George et al (in press) then conducted a systematic review of the intervention literature to elucidate the ways in which the developmental cascade model of childhood obesity can inform and is informed by intervention approaches for childhood OW/OB.

Note. Bold text indicates strongest support based on our review of the literature. Reprinted with permission from Taylor and Francis Group: Originally published in Smith JD, Egan KN, Montaño Z, Dawson-McClure S, Jake-Schoffman DE, et al. 2018. A developmental cascade perspective of paediatric obesity: Conceptual model and scoping review. Health Psychology Review 12: 271–293.

3.2. Psychosocial Contributors

3.2.1. maternal mental and physical health.

An emerging body of literature has shown a significant relationship between higher levels of parental stress and youths’ higher weight status and unhealthy lifestyle behaviors ( Tate et al 2015 ). In a prospective study, Stout et al (2015) found that fetal exposure to stress, as evidenced by elevated maternal cortisol and corticotropin-releasing hormone, was related to patterns of increasing BMI over the first 24 months of life. Children of mothers experiencing psychological distress and anxiety during pregnancy had higher fat mass, BMI, subcutaneous and visceral fat indices, liver fat fraction, and risk of obesity at age 10 years compared to those whose mothers did not ( Vehmeijer et al 2019 ). Early stress can have long-lasting effects, and studies from a nationally-representative cohort study have shown that postnatal maternal stress during the first year has a positive longitudinal relationship with the child’s BMI up to age 5 ( Leppert et al 2018 ), and psychological distress at age 5 was associated with risk of obesity at age 11 in another nationally-representative cohort ( Hope et al 2019 ). Among Hispanic children and adolescents whose caregivers reported ≥ 3 chronic stressors, Isasi et al (2017) found an increased likelihood of childhood obesity when compared to those whose parents reported no chronic stressors. In a systematic review assessing the impact of maternal stress on children’s weight-related behaviors, O’Connor et al (2017) found mixed evidence for the relationship specific to dietary intake; however, researchers found consistent evidence for the detrimental impact on youths’ physical activity and sedentary behavior, which was often conceptualized as screen time. Understandably, highly stressed parents may have an increased reliance on convenient fast-food options versus grocery shopping and preparing fresh and healthy meals for their children and may not have the energy or wherewithal to support their youths’ physical activity, nor engage in limit-setting behaviors specific to their children’s screen time.

One of the few studies using a longitudinal design did not replicate the relationship between high parental stress and lower levels of youth physical activity, but the relationship held for high levels of parental stress and increased fast food consumption ( Baskind et al 2019 ). Interestingly, this study observed an interaction effect on the relationship of high parental stress and childhood obesity by only low-income households and among ethnic minority children, specifically non-Hispanic black children—explaining one of the factors that contributes to healthy disparities for childhood obesity rates in the US. In another study using a large, prospective cohort, Shankardass et al (2014) found a significant effect of parental stress on BMI. The researchers also observed a significantly larger effect among Hispanics versus the total sample population, further noting that the relationship was weaker and not statistically significant among non-Hispanic children. Due to the salient role of caregiver stress on child health behaviors, it seems that interventions for childhood OW/OB should incorporate stress reduction strategies for parents while simultaneously focusing efforts on reaching racial/ethnic minority families and the economically disadvantaged.

Maternal mental health, most commonly operationalized as depressive symptoms and diagnosis, relate to children’s risk for OW/OB. The longitudinal effects of postnatal maternal depressive symptoms predicted obesity risk in preschool-age children, and unhealthier lifestyle behaviors, such as high TV viewing time and low levels of physical activity ( Benton et al 2015 ). Children of mothers with severe depression were more likely to be obese compared to children of mothers with fewer symptoms ( Marshall et al 2018 ). Maternal mental health could negatively affect child feeding behaviors such that elevated depressive symptoms in low-income mothers have been associated with increased use of feeding to soothe children ( Savage & Birch 2017 ). Few interventions for childhood obesity to date specifically target caregiver depression, but some protocols provide guidance to engage caregivers in services to manage depression and related stressors ( Smith et al 2018c ).

3.2.2. Child mental health

Poor self-regulation and related constructs such as reactivity and impulsivity, are prospective obesogenic risk factors ( Bergmeier et al 2014 , Smith et al 2018d ). A child’s temperament describes behavioral tendencies in reactivity and self-regulation. Negative reactivity is characterized by a quick response with intense negative affect, and is difficult to soothe. Infants and children with negative reactivity are at high risk of excess weight gain, and developing obesity later on and toddlers with low self-regulation and inability to control impulses or behavior are at increased risk for obesity and rapid weight over the subsequent nine years compared to toddlers with higher self-regulation abilities ( Graziano et al 2013 ). Poorer emotional self-regulation at age 3 is an independent predictor of obesity at age 11 ( Anderson et al 2017 ). On the other hand, the ability to delay gratification at age 4 is associated with lower BMI 30 years later ( Schlam et al 2013 ). It is possible that parents of children with difficult temperament experience challenges effectively managing children’s behaviors and setting limits, leading to irregular health routines and increased obesity risk ( Bergmeier et al 2014 , Smith et al 2018d ). Further, parents could overuse food and feeding to soothe children ( Anzman-Frasca et al 2012 ). Throughout childhood, emotional regulation deficits and other mental health disorders continue to predict obesity and weight gain. Emotional regulation in conjunction with stress during childhood is highly linked to low physical activity, emotional eating, irregular and disrupted sleep, and later development of obesity ( Aparicio et al 2016 ). A longitudinal study examining emotional psychopathology in preadolescence saw that boys diagnosed with a social phobia, panic disorder or dysthymia (persistent depressive disorder) had higher waist circumference and/or BMI, and girls diagnosed with dysthymia had increased waist circumference at the three-year follow-up ( Aparicio et al 2013 ). In a prospective study, overweight children who reported binge eating at ages 6–12 years gained 15% more fat mass over a period of four years compared to overweight children with no binge eating ( Tanofsky-Kraff et al 2006 ). The predictive role of mental health on physical health conditions and subsequent comorbidities can be costly and burdensome. Children with obesity-related health conditions (e.g., type 2 diabetes, metabolic syndrome) and a comorbid psychiatric diagnosis (e.g., depressive mood disorder, bipolar disorder, attachment disorder) have higher healthcare utilization and costs per year compared to children without a comorbid psychiatric diagnosis ( Janicke et al 2009a )

There is an association between OW/OB and depression in childhood and adolescence, but there is mixed evidence of the directionality of this effect among children and adolescents. A review of high quality studies by Mühlig et al (2016) saw that among nine studies examining the influence of depression on weight status, six found no significant influence. Of the studies that reported significant associations, one study saw effects only among female adolescents, another only for male adolescents, and a third showed effects of adolescent depressive symptoms on adult obesity at age 53 years only in women. Conversely, OW/OB status can have significant influences on risk of low self-esteem and depressive symptoms/diagnosis in adolescence, as discussed later in this paper.

3.2.3. Stigma/bullying

Weight-related stigma, defined as subtly or overtly having discriminatory actions against individuals with obesity, toward children with obesity can impair quality of life, and contributes to unhealthy behaviors that can worsen obesity such as social isolation, decreased physical activity, and avoidance of health care services ( Pont et al 2017 ). Unfortunately, stigma is widespread and tolerated in society, furthering the reach of negative harm. Children with obesity face explicit weight bias and stigma from multiple environments including from parents, obesity researchers, clinical settings, and school. Parents not only demonstrate implicit bias against childhood obesity, but also implicit and explicit biases against children with obesity ( Lydecker et al 2018 ). Even among obesity researchers and health professionals, significant implicit and explicit anti-fat bias, and explicit anti-fat attitudes increased between 2001–2013 ( Tomiyama et al 2015 ). Exposure to stigma and weight bias can have damaging psychosocial effects on children, such that stigma can mediate the relationship between BMI, depression, and body dissatisfaction ( Stevens et al 2017 ).

Weight stigma can also initiate bullying and weight related teasing, which can have serious psychological consequences such as depression among children, further weight gain and lessen motivation to change. A nationally representative sample of children ages 10–17 years saw that OW/OB adolescents were at higher odds of being a victim of bullying, and also higher odds of perpetrating bullying and victimizing others ( Rupp & McCoy 2019 ). The children at higher odds of engaging in bullying, or being bullied were also at significantly higher odds of having depression, difficulty making friends, and conduct problems compared to OW/OB adolescents who were not bullies or victims of bullying. The relationship between obesity and bullying needs to be addressed through bullying engagement, and coping skills for victimization to prevent and manage associated behavioral and depressive symptoms.

3.2.4. Family functioning and home environment

Evidence suggests a link between general family functioning, parent–child relationships, communication, and use of positive behavior support strategies and childhood OW/OB (see Smith et al 2017a ). Influence of general parenting styles, as opposed to the more specific feeding styles, have been extensively studied and linked to children’s diet, physical activity, and weight ( Shloim et al 2015 ). Children raised with an authoritative (warm and demanding) parenting style had healthier diet, higher physical activity levels, and lower BMI’s than those raised with the other styles ( Sleddens et al 2011 ). Parents proactively structuring home environments to support and positively reinforce healthy dietary and physical activity behaviors also play a key role in children’s healthy lifestyles ( Smith et al 2017b ). Children exposed to less supportive environments consisting of family stress, father absence, maternal depression, confinement, and unclean home environments at 1 year of age has been associated with high BMI at age 21 ( Bates et al 2018 ). Taken together, family participation and building parenting skills can play a salient role in the prevention of childhood OW/OB ( Pratt & Skelton 2018 , Wen et al 2011 ).

4.0. PREVENTION AND MANAGEMENT OF OVERWEIGHT AND OBESITY

This section discusses the state-of-the-science in childhood OW/OB prevention and management along with salient factors related to their implementation in varied healthcare delivery systems. The current climate is being shaped by the position of the American Medical Association. In 2013, the Board voted to classify obesity as a disease that requires medical attention. This classification aimed to emphasize health risks of obesity, remove individual blame, and create new implications and opportunities for intervention. This classification can help to further: 1) a broader public understanding of the obesity condition and associated stigma; 2) prevention efforts; 3) research for treatment and management; 4) insurance reimbursement for intervention; and 5) medical education ( Kyle et al 2016 ). In primary healthcare settings specifically, the US Preventive Services Task Force (USPSTF) gave childhood obesity screening and family-based intervention a “B” grade for evidence of effectiveness ( US Preventive Services Task Force 2017 ), which is sufficient to open insurance reimbursement streams for activities related to the prevention and management of childhood OW/OB that did not exist before. Reimbursement has been a significant barrier to uptake of effective interventions and the impact of the USPSTF in removing this impediment is not yet fully known.

A number of high-quality systematic reviews and meta-analyses have been published in recent years, which provide the most contemporary perspective of the effectiveness of interventions for prevention and management, as well as revealing wide variability and inconsistent findings. For example, Peirson et al (2015a) saw that prevention interventions were associated with slightly improved weight outcomes compared to control groups in mixed-weight children and adolescents. However, intervention effects were not consistent among each intervention strategy tested, suggesting that specific characteristics of the interventions, such as setting, participants, dose, and tailoring, should be examined to determine what is and is not effective in achieving desired outcomes.

Intervention strategies for the prevention and management of child OW/OB occur in various contexts and within, and in coordination with, multiple service delivery systems. This is due in large part to the risk factors inherent to familial, school, and community/societal levels. Relatedly, for prevention in particular, there is some correspondence between the sample being targeted and the context, such that community and school-based interventions are far more likely to be universal (sample does not consider weight status) or selective (target sample is overweight or specifically targeted due to being at-risk for obesity; e.g., ethnic minority, low income) compared to the indicated (majority of target sample is in the obese range) models more commonly found in primary and specialty healthcare systems. Unsurprisingly, the specific intervention targets and behavior change strategies align with the context and approach ( St. George et al in press ).

4.1. Community Interventions

Community interventions are defined as incorporating policies and strategies aimed at reducing the population risk of obesity through legislation, modifications to the built environment, provision of accessible resources, and changes in economic/pricing/food subsidies ( Bleich et al 2013 ). Community interventions can involve the use of media, businesses (e.g., restaurants), community health services, community gardens, community or recreational centers, city planning, and the local governments ( Karacabeyli et al 2018 ). Interventions delivered in community settings have the ability to provide high degrees of access and exposure to strategies and programs to racially diverse, low-income children, who are at the highest risk of OW/OB. Interventions delivered in community settings can be effective, but the impact could be diminished through the lower likelihood of intervention completion due to living in lower socioeconomic circumstances and other obstacles ( Fagg et al 2015 ).

In comparison to other settings, such as the school and family level, there were fewer studies conducted at the community level in a recent review ( Bleich et al 2018 ). This may be due to the numerous challenges and complications involved in building community capacity and engaging community leaders, stakeholders, community agencies, and city organizations. Alternatively, it could reflect a greater focus to date on other contexts and intervention targets, which we discuss in the following sections. To address effectiveness and sustainability, a combined clinical and community intervention could hold promise, especially for racially diverse children living in a low-income community, who are most at-risk. A study by Hoffman et al (2018) showed that an integrated clinic-community model is feasible and improves physical activity and quality of life when compared to multidisciplinary treatment only in clinical care settings.

To summarize, there is promise in community-based interventions that involve either the health clinic and community partnerships or community and school partnerships. Interventions using a community-based participatory approach and a strong quasi-experimental design could achieve the long term goal of reducing both child BMI, the prevalence of OW/OB in childhood, and remission of obesity in children ( Economos & Hammond 2017 ).

4.2. School-Based Interventions

School-based interventions are defined as taking place during school hours or after-school hours for children in kindergarten through high school, and being focused exclusively in the school or delivered primarily in the school setting with secondary settings of family/home, primary care, or community ( Bleich et al 2018 ). Considering that the majority of children spend a significant amount of their day in school, many preventive interventions have leveraged schools as an entry point to improve the obesogenic environment by promoting more physical activity in physical education classes and recess, improving school playgrounds and nutritional options in school cafeterias, and providing healthy lifestyle education in classes or other school policies ( Ickes et al 2014 ). Previous reviews recommend using multi-component interventions targeting two or more health behaviors (i.e., physical activity, dietary outcomes, sedentary behavior) to improve adiposity outcomes when compared to single-component interventions (e.g., Wang et al 2015 ). Interestingly, well-designed school-based studies are effective in improving dietary behavior, but typically do not see statistically significant differences in child BMI between intervention and control schools, except for among children who are already in the obese range ( Bogart et al 2016 ). While increasing fruit, vegetable and water consumption are important, the health behavior modifications are not sufficient for significant long-term obesity management. A way this has been addressed is partnerships between schools and community-based interventions which also engage parents. In a review, Ickes et al (2014) found that less than half of childhood obesity interventions incorporated parents; of those studies involving parents, 75% demonstrated positive outcomes in reducing BMI or weight status. In a synthesis of systematic reviews and meta-analyses of school-based interventions, long-term interventions with a combination of diet and physical activity components and family or parental involvement significantly reduced weight among children ( Khambalia et al 2012 ). Aligned with previous research, Bleich et al (2018) found that school-based interventions that used a multi-component approach of both physical activity and nutrition with some intervention with families in the home had the largest effects. A systematic review and meta-analysis by Wang et al (2015) observed that strength of evidence of obesity prevention programs for children ages 2–18 years was dependent on intervention type, and delivery setting(s). Strength of evidence was high for physical activity-only interventions delivered in school settings with home involvement, or combined diet and physical activity interventions delivered in school settings with home and community involvement. They also found moderately strong evidence when delivering combined interventions in school-based settings alone, in schools with home or community component, or in community with a school component.

Bleich et al (2018) also reviewed a smaller number of pre-school interventions and found some promise in both single component interventions—focusing solely on physical activity—and multi-component interventions. In two other reviews evaluating early child care center-based interventions, both found promising evidence for multi-component interventions and multiple levels influencing the child, parent, teachers/staff, and class ( Sisson et al 2016 , Ward et al 2017 ). An exemplar study, Natale et al (2017) conducted an early childhood multi-level obesity intervention, which included menu modifications at the child care center, a nutrition and physical activity educational curriculum for preschoolers, and a healthy meal preparation and role modeling curriculum for parents. At two-years follow-up, the researchers observed significantly less increase in BMI percentile among the intervention group versus controls. Overall, strong obesity prevention interventions in early care and education settings were associated with healthy eating and anthropometric outcomes, which was further improved by parental engagement. In sum, the preschool and school contexts hold promise for improving weight-related behaviors and adiposity outcomes; however, evidence is clear that parents should be engaged in the process of supporting and reinforcing their children’s health behaviors for these programs to be maximally effective ( Ward et al 2017 ).

4.3. Family-Based Interventions

The home environment (e.g., family routines, limit setting, household chaos, crowding) has long been considered one of the most powerful influences on children’s healthy behaviors and OW/OB outcomes ( Bates et al 2018 ). Playing an integral role in physical activity, diet, screen time, and sleep, parents can exhibit positive parenting practices (e.g., limit-setting, role modeling) and provide a healthy, supportive environment (e.g., provisions of fresh fruits and vegetables), thereby shaping their children’s lifelong habits and preventing the onset of childhood obesity (for a review see Smith et al 2018d ). Family-based interventions are defined as involving either passive or active parental involvement, often with parents viewed as the primary or sole agents of change ( Sung-Chan et al 2013 ). Active parental involvement entails repeated engagement, such as participation in workshops, counseling, or educational sessions; passive involvement does not integrally involve the parent or guardian (e.g., brochures, newsletters).

In a review evaluating family-based interventions for OW/OB prevention, Ash et al (2017) found a significant increase in the number of family-based interventions with just six studies published in 2008 compared to 35 studies in 2013. The majority of studies employed rigorous RCT study designs (73%), but almost two thirds of the studies were short-term and implemented for less than a year. A fraction of studies occurred in multiple settings and over half targeted multiple components beyond diet and physical activity, such as screen time or sleep. Many preventive studies targeting young children (pre-natal to five years old) tend to use home or primary-care based settings with parental involvement, whereas interventions targeting older children tended to take place in community- and school-based settings. These findings are commensurate with the review of St. George et al (in press) , which showed a decrease in parental involvement and family-based intervention strategies with child age. This dovetails with the conclusions of Kothandan (2014) that family-based interventions demonstrated effectiveness for children younger than twelve, but for children twelve and up, school-based interventions were most effective in the short-term.

Regarding preventive interventions specifically, the majority of interventions have been tested among low SES families and predominantly white families ( Ash et al 2017 ). Hispanics/Latinx have been well-represented in US intervention studies in comparison to other ethnic minorities (i.e., African Americans, Asians, and indigenous groups). Latinx are particularly well-suited to participate in family-based interventions given their cultural emphasis on familial values; however, a recent meta-analysis noted diminishing intervention effects with a higher proportion of Hispanic children ( Ling et al 2016 ), which was attributed to a lack of culturally competent interventions to address language barriers and dietary preferences. In addition to incorporating other ethnic minorities and culturally appropriate interventions, Ash et al (2017) suggested that preventive family-based interventions should account for non-traditional families and their different needs and family dynamics.

In regard to family dynamics and interactions, poor family functioning has been linked with an increased risk of obesity, obesogenic behaviors, and adverse health outcomes (e.g., Pratt & Skelton 2018 ). Family-based care for childhood OW/OB involves targeting dietary and physical activity behaviors along with the rules of the family unit, family health routines, communication, and dynamics ( Pratt & Skelton 2018 ). Existing protocols involve family counseling for diet and physical activity change in the home environment, with some approaches also targeting more general parenting and family management skills that have been found to impact OW/OB status of the child ( Smith et al 2018a , Smith et al 2018b , Smith et al 2017b ). Interventions including both parents and children have shown more positive short and long-term effects on child weight when compared to parent-only interventions and controls in some studies ( Yackobovitch-Gavan et al 2018 ), whereas others have found comparable effects for parent-only and child-involved family-based approaches ( Boutelle et al 2017 ). Further, parent-only interventions have been shown to be more cost-effective ( Janicke et al 2009b ). In a meta-analysis evaluating comprehensive behavioral family lifestyle interventions treating pediatric obesity, Janicke et al (2014) found an overall standardized effect size of 0.47, which indicates a small-to-moderate effect on BMI. The dose of treatment (i.e., number of intervention sessions, minutes spent in treatment) was positively related to the treatment effect, which provides support for the notion that more intense and longer interventions are associated with better outcomes, a conclusion also made by ( Whitlock et al 2010 ). In addition, age was a significant moderator for weight outcomes indicating that older children had larger and more beneficial intervention effects than younger children.

Specifically, family-based interventions targeting positive behavior support have been used to address key mechanisms of change specific to promoting children’s healthy lifestyle behaviors ( Smith et al 2017b ). Positive behavior support has been identified as a way to reduce weight gain through improving the caregiver’s ability to support and work with the child toward a healthier diet and improved physical activity. Long-term prevention trials using family-based intervention to target positive behavior support found that children randomized to the intervention had lower BMI in the years following participation ( Smith et al 2015 ). This finding was particularly promising given that these trials did not explicitly focus on child weight in any way; thus, prevention of childhood OW/OB was a spillover effect.

Given the various ways individual, interpersonal, and family health behaviors contribute to child obesity, a tailored family-based intervention could be effective in identifying specific family needs and providing appropriate resources. In a family-based tailored intervention, Taylor et al (2015) saw that the children of families randomized to the tailored treatment had significantly lower BMI compared to families in the usual care group. Additionally, children in the tailored treatment had better dietary behaviors and were more physically active than children in the treatment as usual group. Smith, Berkel et al. (2018b) adapted the highly effective and well-known individually-tailored family-based prevention program called the Family Check-Up ® ( Dishion et al 2008 ) to specifically target obesogenic behaviors with the aim of preventing obesity and excess weight gain in children ages 2 to 12 years. This adaptation is referred to as the Family Check-Up ® 4 Health and is being tested in two large RCTs in coordination with pediatric primary care ( Smith et al 2018a ) and with community-based family resource centers and public schools ( Berkel et al 2019 ) in low-income neighborhoods with racially/ethnically-diverse families at highest risk for childhood OW/OB.

4.4. Primary Healthcare

Primary care interventions are defined as health promotion or weight management programs conducted within or in close coordination with the primary healthcare system. Primary care is viewed as an ideal, real world environment for weight management interventions because of accessibility and frequency of visits (i.e., routine well-child visits) ( Davis et al 2007 ). In a meta-analysis evaluating weight management interventions delivered in primary-care settings, Mitchell et al (2016) found an overall effect size of 0.26, indicating a small treatment effect, and a smaller effect than has been found in broader meta-analytic reviews (e.g., Janicke et al 2014 , Whitlock et al 2010 ). The dose-response relationship was significant, where the number of treatment contacts, length of treatment in months, and the number of visits with the pediatrician was associated with larger treatment effects.

A systematic review examining randomized control trials targeting obesity management in children ages 2–5 years saw five of six interventions, all in ambulatory healthcare settings, had significant decreases in child weight, with sustained intervention effects through follow-up ( Ling et al 2016 ). The effective interventions actively involved parents in health education, group meetings, physical activity sessions, or behavioral therapy.

4.5. Interventions by Developmental Period

In a review of interventions of OW/OB from birth to age 18, St. George et al (in press) identified 74 distinct interventions reported across the 141 included articles. They were categorized based on the child’s age at entry into the intervention: prenatal/infancy (< 2 years; n = 4), early childhood (2–5 years; n = 11), childhood (6–11 years; n = 38), early adolescence (12–15 years; n = 18), and late adolescence (16–18 years; n = 3). Developmental stage of the child has also been found to align with the strategy, such that interventions in the prenatal and infancy periods are nearly all universal, whereas during childhood and adolescence, as compared to early childhood, the burden of disease is larger and intervention strategies more often target selected and indicated samples with greater intensity ( St. George et al in press ).

5.0. EXPERT RECOMMENDATIONS

5.1. youth health behaviors.

It is recommended that children and adolescents aged 6–17 years should achieve ≥ 60 minutes of physical activity each day ( Piercy et al 2018 ). The 2015–2020 Dietary Guidelines for Americans recommend consuming a variety of fruits and vegetables, whole grains, proteins, low-fat dairy products, and limiting intake of sodium, solid fats and added sugars beginning at age 2 years ( DeSalvo et al 2016 ). Unfortunately, only 21.6% of children 6–19 years reach the recommended 60 minutes of physical activity at least five days per week ( Alliance 2016 ). Dietary quality impacts weight gain and OW/OB, and it is estimated that the obesity epidemic largely contributed to statistics showing a declining life expectancy, which occurred in 2015 for the first time in 30 years ( Ludwig 2016 ).

The American Academy of Pediatrics (AAP) recommends that children under 18 months should have no screen time aside from video-chatting, and children ages 2–5 years engage in one hour of screen time per day of high-quality programs with parents. Children ages 6 and above should have limited media exposure, ≤ 2 hours per day, which should not interfere with sleep, physical activity, or other health behaviors. The AAP recommends that families should have “media-free” time together, and “media-free” locations such as in the dining room or bedroom to avoid interfering with meals and sleep duration ( American Academy of Pediatrics Council on Communications and Media 2016 ). The World Health Organization asserts that screen time brings no benefit to children, and infants younger than one year should have no electronic screen exposure, and children age 2–4 years should not have more than one hour of daily “sedentary screen time.” In recent years, the portability of screen devices has led to an overall increase in screen time, with the majority of US youth exceeding screen time guidelines by a wide margin (averaging more than 7 hours daily) ( Barnett Tracie et al 2018 ).

The most recent AAP guidelines recommend that children ages 1–2 years sleep 11–14 hours per 24 hours, children 3–5 sleep 10–13 hours, children 6–12 sleep 9–12 hours, and teenagers ages 13–18 should regularly sleep 8–10 hours ( Paruthi et al 2016 ). Certain behaviors such as a regular routine, avoiding large meals close to bedtime, being physically active during the day time, and eliminating electronic devices in the bedroom are associated with better sleep ( Irish et al 2015 ). According to the CDC, 60% of middle schoolers and 70% of high schoolers do not meet regular sleep recommendations.

5.2. Behavioral Intervention

Family-based intervention is recommended by The National Academy of Medicine, the American Academy of Pediatrics, and the Endocrine Society, among others, as the preferred approach for the management of OW/OB from infancy to adolescence. Based on a systematic review, the USPSTF concluded that lifestyle-based weight loss interventions (not necessarily family-based) consisting of 26 or more hours of intervention engagement are likely to assist children and adolescents in weight management ( O’Connor et al 2017 ). Recommendations from a number of expert committees and task forces support targeting the following behaviors for prevention and management of childhood OW/OB: limiting consumption of sugar sweetened beverages, consuming daily recommended fruit and vegetables, limiting screen time, increasing physical activity, eating breakfast, limiting eating out at restaurants, encouraging family meals, and limiting portion sizes. The majority of existing interventions target multiple behaviors, but some have been designed for discrete behaviors.

5.3. Pharmacologic Intervention

Orlistat is the only FDA-approved medication for treating obesity for pediatric patients ages 12 years and older. Side effects in the gastrointestinal area are common in children, and further clinical trials are needed to evaluate medication risk and benefits among pediatric patients ( Chao et al 2018 ). Expert opinion states that Orlistat, in conjunction to lifestyle changes, leads to modest weight loss and could benefit children in the indicated age range with obesity but tolerability limits its use ( Kelly & Fox 2018 ). And results are not unequivocal. In a meta-analysis looking at primary-care based interventions, Peirson et al (2015b) found a medium effect (standardized effect size [ES] = −0.54) favoring behavioral interventions when compared to Orlistat plus behavioral intervention components (ES = −0.43). Additional research is needed on both effectiveness and tolerability in youth. Additionally, new pharmacologic options continue to be developed and tested and could reach the market in the next few years if approval is granted ( Kelly & Fox 2018 ).

5.4. Surgical Intervention

The American Society for Metabolic and Bariatric Surgery Pediatric Committee’s best practice guidelines selection criteria are based on systematic reviews of co-morbidities, risks and outcomes, important team members, and patient selection. They recommend that adolescents being considered for a bariatric procedure should have a BMI of ≥35 kg/m 2 with major co-morbidities such as type-2 diabetes mellitus, moderate to severe sleep apnea, or severe nonalcoholic steatohepatitis ( Michalsky et al 2012 ). Data show that bariatric surgery in morbidly obese adolescents can greatly impact weight loss, and attenuate or resolve associated chronic disease. However, adolescents undergoing bariatric surgery should be assessed for capability to adhere to follow-up care regimens to ensure proper nutrition intake and care. The committee also recommends a multidisciplinary team for adolescents undergoing bariatric surgery, which could include an experienced bariatric surgeon, pediatric specialist, registered dietitian, mental health specialist, care coordinator, and exercise physiologist.

6.0. CLINICAL IMPLICATIONS OF CO-OCCURRING MEDICAL AND PSYCHOLOGICAL CONDITIONS

6.1. co-occurring medical conditions.

The pro-inflammatory disease nature of obesity and contributing health behaviors affects normal physiology and metabolism, and can cause many associated diseases ( Gonzalez-Muniesa et al 2017 ). If left untreated, obesity can lead to serious health conditions including type-2 diabetes, cardiovascular disease, asthma, obstructive sleep apnea, high blood pressure/hypertension, non-alcoholic fatty liver disease, hepatocellular carcinoma, and psychosocial problems (e.g., Nobili et al 2015 ). Recent research indicates increased risk of cardiovascular disease incidence, morbidity (ischemic heart disease, stroke), and mortality in adulthood associated with being in the obese BMI range in childhood or adolescence ( Sommer & Twig 2018 ). Obesity prevention and management interventions in childhood are imperative for averting the burden of associated comorbidities.

6.1.1. Type-2 diabetes

Children with obesity are four times as likely to develop type-2 diabetes compared to children with a normal BMI ( Abbasi et al 2017 ). Ethnic minority children of low income are at increased risk, and have limited maintenance and glycemic control, furthering the probability of developing additional health complications down the line ( Pulgaron & Delamater 2014 ). Metformin is the main treatment of type-2 diabetes in youth and adults, though emerging evidence implicates a role in treating children with obesity and a family history of type-2 diabetes (e.g., Warnakulasuriya et al 2018 ). Exercise and lifestyle interventions have had significantly positive health effects in adults, however trials evaluating effects in youth with type-2 diabetes are limited. Given the data from adult trials, the American Diabetes Association recommends that youth with type-2 diabetes meet the 1-hour per day physical activity goal to manage symptoms and decrease health risks ( Colberg et al 2016 ).

6.1.2. Obstructive sleep apnea

Pediatric obstructive sleep apnea (OSA) involves a child having disrupted breathing due to partially or completely blocked upper airways during sleep ( Narang & Mathew 2012 ). Obesity confers the most significant risk for OSA. As many as 60% of children and adolescents with obesity have OSA, or some sort of disrupted breathing during sleep ( Narang & Mathew 2012 ). Obesity and OSA have additional comorbidities and impairments including excessive daytime sleepiness, neurocognitive function, reduced physical activity, cardiovascular burden, and hypertension, further complicating quality life of children with obesity ( Blechner & Williamson 2016 ). Obesity management such as increased physical activity and a healthy diet are recommended for OSA treatment, as well as surgical procedures, if appropriate.

6.1.3. Asthma

Asthma is one of the most common chronic diseases among children and adolescents: 10.1% of children ages 5–14 years had asthma in 2016 ( National Center for Health Statistics 2019 ). Although both obesity and asthma rates have been increasing, it does not appear that obesity has been contributing to the increased asthma prevalence rate ( Akinbami et al 2018 ). This does not discount the risks of obesity on asthma and its unique effects on asthma symptoms. OW/OB children have been observed to have higher prevalence of asthma, and exacerbation as early as preschool age compared to normal weight children ( Lang et al 2018 ). Additionally, OW/OB children have reported distinct asthma symptoms, such as greater shortness of breath, reduced airway hyperresponsiveness, and loss of asthma control, compared to normal weight children ( Lang et al 2015 ). The relationship between asthma and OW/OB should be further investigated.

6.1.4. Hypertension

Hypertension, like obesity, has been increasing among youth and is associated with increased cardiovascular disease risk throughout the lifetime ( May et al 2012 ). The greatest risk factor for pediatric hypertension is elevated BMI ( Falkner et al 2006 ). About 3% of children in the general population have hypertension, compared to about 25% of obese children ( Shatat & Brady 2018 ). In a meta-analysis examining cardiovascular risk factors, compared with normal weight children, systolic blood pressure was higher by 4.54 mm Hg (n=12169, 8 studies) in overweight children, and by 7.49 mm Hg (n=8074, 15 studies) in obese children ( Friedemann et al 2012 ). A study examining childhood hypertension and OW/OB in school children saw that 2.2% of the sample had hypertension, and 37% of those cases could be attributed to OW/OB status ( Chiolero et al 2007 ). A review shows that children with obesity-related hypertension are at increased risk of cardiovascular morbidity and mortality ( Wuhl 2019 ). About 3.8%–24.8% of children with OW/OB have hypertension, though these rates could be higher due to inconsistences and challenges with diagnoses ( Flynn et al 2017 ). The risks of hypertension on children’s lifetime health emphasize the importance of preventing obesity early on.

6.1.5. Nonalcoholic fatty liver disease (NAFLD)

NAFLD is the leading cause of liver disease, leading to a shorter life expectancy due to associated comorbidities; one of which, non-alcoholic steatohepatitis, is projected to be the leading indication for pediatric liver transplant by 2025 ( Charlton et al 2011 ). Epidemiological studies consistently show associations between NAFLD and adiposity, unhealthy diet, and sedentary behavior ( Dunn & Schwimmer 2008 ). Prevalence of NAFLD is especially high in young people who have obesity such that 22.5%–52.8% of children with obesity have NAFLD compared to 2.6% of all children ( Anderson et al 2015 ). Child obesity has the highest risk in the development of NAFLD during childhood ( Hays & McGinnis 2018 ). A longitudinal study of participants ages 3–18 years were followed for 31 years, and saw that child OW/OB was associated with increased risk for adult NAFLD ( Cuthbertson et al 2018 ). The associated risk was removed if participants obtained a normal range BMI by adulthood, emphasizing the salient role of weight management. The high prevalence of NAFLD among children with obesity, and effectiveness of weight change in treating this condition, emphasizes the need for prevention and management of obesity. Smith et al (2017a) found that among children who had NAFLD, poorer family functioning was significantly related to higher BMI, elevated levels of cholesterol, HbA1c, and glucose. Their study exposes the critical role of family functioning on child health, and the importance of using targeted intervention to prevent, and manage obesity and associated disease using a family-centered approach. Weight being the most modifiable factor, the mainstay of NAFLD treatment is lifestyle behavior modifications aimed at weight loss ( Marchesini et al 2015 ).

6.2. Co-Occurring Psychological Conditions

6.2.1. self-esteem/depression.

Children with OW/OB are more likely to experience low self-esteem, and develop depressive symptoms during adolescence compared to normal weight peers (e.g., Mühlig et al 2016 ). This relationship can be attributed to multi-level factors including health behaviors, parenting styles, and family functioning. A review by Hoare et al (2014) suggests that obesogenic risk factors, such as infrequent physical activity, sedentary behavior, poor diet quality, and adiposity were associated with depressive symptoms in adolescents. Conversely, healthier eating patterns were associated with decreased depressive symptoms. Child eating disorder pathology, emotionally-manipulative parenting style, and lower child social status have been associated with depressive symptomatology among children with OW/OB ( Sheinbein et al 2019 ). Children in poorly functioning families with low self-esteem participating in weight loss interventions have been observed to have poor 6-month outcomes, suggesting that multiple social-ecological factors need to be addressed when targeting depressive symptoms in children with OW/OB ( Taylor et al 2017 ). Further, negative psychological experiences more generally, such as trauma and stigma, trigger emotional eating, leading to an ongoing obesity-depression cycle ( Milaneschi et al 2019 ).

6.2.2. Eating disorders

Children with OW/OB have a high prevalence of disordered eating attitudes and behaviors, which can increase risk of developing eating disorders in adulthood. A high proportion of adolescents with restrictive eating disorders report a history of OW/OB ( Lebow et al 2015 ). Additionally, it is estimated that over a quarter of youth with OW/OB have binge and loss of control eating ( He et al 2017 ). Adolescent girls with OW/OB experiencing overvaluation of weight—so concerned with weight that self-evaluation is influenced—are at higher risk of starting to binge eat weekly 2 years later, have more severe depressive symptoms, and continuous overvaluation ( Sonneville et al 2015 ). The bidirectional relationship of obesity and eating disorders, including eating disorder psychopathology, should be properly evaluated during treatment planning.

7.0. IMPLEMENTATION AND RESEARCH TRANSLATION CHALLENGES

One of the abundant challenges for the field is the translation and implementation of effective interventions to the real-world service delivery systems that can reach those most in need. This so-called research-practice gap is pronounced in obesity prevention and management given the preponderance of untested, usual care approaches currently in use; the persistence of debunked myths about causes and effective intervention approaches (e.g., fad diets); and the incongruence between what is being developed by experts and what is acceptable, feasible, and sustainable in existing systems given the constraints of the workforce, space, and funding. This says nothing about the consumer of evidence-based interventions, who historically have had only cursory involvement in the design and deployment of interventions. This has contributed to low engagement rates and high attrition from more intensive OW/OB interventions ( Lydecker & Grilo 2016 ). Raising public and caregiver concern about the risks posed by OW/OB in childhood and adolescence would also facilitate engagement and retention. Currently, many parents with children with obesity underestimate their children’s weight ( Lydecker & Grilo 2016 ) and are thus unlikely to seek intervention or to follow through with a referral for intervention. Add the stigma in society surrounding obesity and the shame parents experience concerning their child’s weight, and traditional approaches to care will continue to be underutilized.

While many of the aforementioned conceptual models encapsulate the multiple levels contributing to childhood obesity, researchers are trying to elucidate which combination of levels and service contexts have greatest effectiveness, and which implementation strategies best address the complexity at levels of the community, school, family, and primary care. Implementation strategies are defined as the methods or techniques used to enhance the adoption, implementation, and sustainability of a clinical program or practice ( Proctor et al 2013 ). They are the actions taken on agents in the system of care itself, and rarely only on the patient or client that is the recipient of the clinical program or practice. The first iteration of the Childhood Obesity Research Demonstration Projects (CORD 1.0), a program of research administered by the CDC, examined multi-sector intervention implementation in schools, community centers, early care and health centers, and pediatric primary care practices. The three projects around the US, identified the facilitators and barriers of implementing multi-setting interventions targeting levels of the socioecologial model in racially diverse, lower-income communities ( Dooyema et al 2017 ). CORD 1.0 projects identified common implementation barriers in schools, rural communities and community centers, including staff turnover, limited resources, and competing needs for existing requirements (such as standardized testing in schools) ( Chuang et al 2016 , Ganter et al 2017 ). Interventions in rural communities and multiple settings benefited from engaging parents and obtaining support from organization members and leadership ( Chuang et al 2016 , Ganter et al 2017 ). Facilitators of school interventions included using the principal as a champion and using students to engage other students ( Blaine et al 2017 ). Low-income primary care settings showed that only about 27% of referred patients enrolled in the intervention ( Barlow et al 2017 ). Such knowledge assists in the design of future studies to develop effective, accessible, and acceptable interventions for those needing it most.

These implementation challenges are not unique to childhood obesity but the complexity of the problem will require more rapid translation of discoveries in research with bidirectional input from successes and failures in practice back to researchers. Last, improving the packaging of evidence-based programs can provide potential implementers with a “ready off the shelf” product that requires less involvement by the intervention developers, which is a primary contributor to the high cost of adopting a new program ( Jordan et al 2019 ), and can arguably aid implementers in delivering interventions with fidelity. This is the goal of the CDC’s Childhood Obesity Research Demonstration (CORD) 3.0 Project ( https://www.cdc.gov/obesity/strategies/healthcare/cord3.html ). However, the scale up penalty—reduced effects as interventions are widely disseminated and adopted—has been shown in the childhood obesity literature to be about 75% of efficacy studies ( McCrabb et al 2019 ), but implementation scientists have argued for dynamic adaptation that retains effectiveness while also increasing sustainability (e.g., Chambers et al 2013 ). This is an area in need of attention as interventions are taken to scale.

8.0. RECOMMENDATIONS FOR FUTURE RESEARCH

Reviews of interventions for childhood OW/OB show variability in effectiveness, often changing health behaviors but not weight, thus exposing the difficulties of addressing and managing this public health crisis. There are a number of directions for future research to improve outcomes and address the challenges of wide-scale implementation.

1) Interventions need to be integrated across systems.

Given the multifaceted, multilevel, and interrelated nature of OW/OB development, if interventions are to be maximally effective there needs to be an integration of multiple service systems (primary care, schools, communities, child care, the home) for the delivery of multicomponent interventions that utilize behavioral, structural, environmental, policy, and biomedical approaches.

2) There is no “one size fits all.”

More complex, individual child and family interventions need to be tailored both in terms of content and implementation strategy to best align with the personal needs of those involved. This means flexible, adaptive, or modularized intervention protocols addressing the cadre of potential health behaviors and related individual and familial risk factors of OW/OB present, and getting the intervention to families in a manner that is engaging, accessible, and has wide reach.

3) Consider implementation earlier.

Researchers developing interventions for childhood OW/OB ought to consider their implementability from the beginning using the framework of “designing for dissemination and implementation” ( Dearing et al 2013 ), which considers the capacities, needs, and preferences of the end users (service delivery systems, children/families, funding mechanisms) during design and testing. Another method for speeding translation is to adapt existing programs for new service contexts and new populations, rather than following the traditional pipeline of treating something different as “new” and having to establish efficacy and effectiveness before moving to implement. This concept has been referred to as “scaling out” ( Aarons et al 2017 ) and it has been applied in childhood OW/OB prevention and management ( Smith et al 2018b ). Scaling out is a critical method for implementation research to address the health inequities and disparities of childhood obesity ( McNulty et al 2019 ).

4) Engage the community to enhance scalability and sustainability.

Berkel et al (in press) engaged a diverse group of stakeholders, including payors, in the adaptation and delivery processes of a recent trial of the Family Check-Up ® 4 Health as a means of increasing the likelihood of sustained adoption beyond the funded trial. Economos and Hammond (2017) suggest that community-level research should employ novel techniques of systems mapping and causal loop diagramming, which can help stakeholders to visualize the interrelated processes and elements that are relevant to the intervention. They also suggest using agent-based modeling and other simulation methods to help encapsulate the complex dynamics involved in implementing successful community-based interventions. Tailoring strategies to local communities and deepening engagement holds promise in enhancing sustainability and scalability of community-based interventions.

5) Research rigor—scale up balance.

Future directions should address the shortcomings of less rigorous study designs, which inherently increases the risk of confounding and presents challenges in attributing changes in the outcome to intervention effects, but as research translation moves toward scaling up after establishing effectiveness, this tradeoff is both expected and encouraged to increase external validity. Additionally, research is needed to determine the appropriate length and dosage of interventions, along with clear reporting of outcomes, consistency of measures, and long-term follow ups ( Bleich et al 2018 , Ickes et al 2014 , St. George et al in press ). Echoing Karacabeyli et al (2018) , we also recommend collecting process evaluation and outcome data in order to understand the complex causal chain and to help bolster inferences in regard to the effectiveness and implementation of the intervention using hybrid designs .

6) Engagement and participation are critical challenges.

Large community trials in particular often suffer high attrition rates because of mobile populations who move to different residences, which can impact the ability to track and communicate with participants. And this relates to effectiveness. Children completing >75% of a community-based intervention program experienced beneficial change in BMI as well as associated health behaviors (physical activity, screen time, unhealthy food consumption) compared with children completing <75% of the program ( Hardy et al 2015 ). A way to attenuate attrition in research on community-level interventions could be through adjusting study intervention design. The majority of community-based interventions used a quasi-experimental design, which is often attributed to practicality and sustainability ( Bleich et al 2018 , Karacabeyli et al 2018 ). Interestingly, less rigorous study designs (e.g., quasi-experimental vs. RCTs) demonstrated significant reductions in child weight ( Karacabeyli et al 2018 ). By removing randomization, the authors reported that communities with the resources, engagement/buy-in, and capacity could be selected to participate, which optimized community support for the obesity intervention efforts through both sustainable partnerships and buy-in from the community and its champions. This participatory approach could potentially lead to lasting positive health changes that extend beyond the study period. In addition, Karacabeyli et al (2018) described the benefits of a quasi-experimental design which lends itself to selecting at-risk communities that could greatly benefit from intervention efforts. For example, using a stepped wedge or randomized rollout trial design where all at-risk communities selected would eventually receive the intervention at different time periods but none serve as “no intervention” controls (see Landsverk et al 2017 ).

9. CONCLUSIONS

There are signs that progress is being made in stemming the tide of childhood obesity and evidence-based interventions are available across development and for various contexts and systems that affected and at-risk children routinely encounter. Tremendous challenges remain in connecting the dots between etiology, development, and intervention targets, as well as when and where to intervene. There needs to be a push to scale up effective interventions as even small changes in weight can yield significant impact on multiple cardiometabolic indices ( Lloyd-Jones et al 2010 ) that can improve quality and length of life. Clinical health psychologists are ideally suited to conduct research on this complex problem but transdisciplinary teams will be needed to increasingly move the dial.

SUMMARY POINTS

• Childhood obesity is a complex, multidetermined, preventable chronic disease that increases risk for premature death and psychological problems.
• Evidence-based interventions for obesity are available for all stages of development from birth to 18 years.
• Specific interventions can be delivered in community, school, home, and healthcare settings depending on the type of strategy and risk level of the targeted population.
• Associated co-occurring medical and psychological conditions of childhood obesity present an opportunity for clinical and health psychology researchers and practitioners.

FUTURE ISSUES

• Future research ought to focus on translational considerations from the start and ways to scale up delivery of effective interventions.
• Research is needed on interventions and their implementation to more effectively reach minority and underserved populations at greatest risk for obesity.
• Increasing engagement and retention in childhood obesity interventions is a promising focus for future research.

ACKNOWLEDGEMENTS

The authors wish to thank Sara St. George for feedback on an earlier version of this review and to acknowledge support of this work from the Centers for Disease Control and Prevention (grant U18DP006255) and the United States Department of Agriculture (grant 2018-68001-27550), awarded to Justin Smith and Cady Berkel; and the National Institute on Drug Abuse (grant P30 DA027828), to C. Hendricks Brown, in support of Justin Smith.

DISCLOSURE STATEMENT

Justin D. Smith is co-developer of the Family Check-Up ® 4 Health intervention for childhood obesity. The authors are not aware of any other affiliations, memberships, funding, or financial holdings that might be perceived as affecting the objectivity of this review.

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