Prevalence and Intervention of Childhood Obesity: A Literature Review

Tiffany I. Atabansi1†

1Geisinger Commonwealth School of Medicine, Scranton, PA 18509 †Doctor of Medicine Program Correspondence: tatabansi@som.geisinger.edu

Abstract

Obesity is a prevailing epidemic that affects all demographics, including children and adolescents. The long-term effects of obesity, if left unmanaged, can be life-threatening. Obesity is a gateway condition to diseases associated with high morbidity and mortality rates, such as cardiovascular disease and Type 2 diabetes. Children and adolescents are currently experiencing earlier exposure to these diseases. Research has attributed this high rate to various factors including nutrient deficient diets, lack of physical activity, and lower socioeconomic status. This study aimed to critically analyze the leading causes of pediatric obesity and evaluate the efficacy of intervention strategies. A comprehensive understanding of these factors and strategies can facilitate the generation of more efficacious measures in reducing the prevalence and consequences of childhood obesity.

Introduction

Childhood obesity is one of the most serious public health challenges of the 21st century (1). For children and adolescents aged 2–19 years in 2017–2020, the prevalence of obesity was 19.7% and affected about 14.7 million children and adolescents in the United States (U.S.) (2). Overweight and obese children are likely to maintain their status into adulthood and are at higher risk for developing chronic diseases such as hypertension, dyslipidemia, Type 2 diabetes, cardiovascular disease, stroke, gallbladder diseases, osteoarthritis, sleep apnea and respiratory problems, and certain cancers (1). Obesity and the diseases listed above are considered diseases of affluence, also commonly referred to as lifestyle diseases. The included diseases are all chronic noncommunicable diseases that are thought to be a result of increasing wealth and ease of life in society (3). Many lifestyle diseases have a significant association with obesity, with children and adolescents being diagnosed earlier within their lifetime than previous generations. Type 2 diabetes mellitus was a rare occurrence in children and adolescents, but in the mid-1990s there was an observed increase of Type 2 diabetes worldwide in this young age group (4). This is the case particularly in the U.S. with the majority of the children being obese, and in some regions of the U.S., Type 2 diabetes mellitus is as frequent as Type 1 diabetes mellitus in adolescents (4). This exemplifies the correlation and gravity between obesity and lifestyle diseases. Recently, there has been a reported decline or plateau in childhood obesity (5, 6), but the youth generation still has a shorter life expectancy than the generations before. Obesity has been shown to have a substantial negative effect on longevity, reducing the length of life of people who are severely obese by an estimated 5 to 20 years (7). There is an increased correlation between low socioeconomic status (SES) and lifestyle diseases. Low socioeconomic families are more likely to be food insecure, resulting in the consumption of foods low in nutrient density and high in caloric value. Minority populations make up a significant amount of the low socioeconomic population in the U.S. Significant disparities in obesity prevalence persist among racial/ethnic groups and by SES, with more Hispanic and non-Hispanic Black youth being obese compared to their non-Hispanic white and non-Hispanic Asian counterparts (2, 5). Obesity can affect other areas of a child’s life beyond physical health. Psychological and intellectual development are at risk too. Obese children are a target for bullying. This affects their mental health, which creates space for the onset of depression, eating disorders, or suicide. The absence of a well-balanced diet alters the ability to learn. Due to these health consequences, early intervention is critical for this population. The purpose of this review is to critically examine the factors contributing to pediatric obesity and evaluate the efficacy of intervention strategies proposed to combat it.

Methods

A thorough review of the literature was conducted in search of childhood obesity prevalence and intervention. The initial search utilized Google Scholar, PubMed, ClinicalKey, and Elsevier databases. Research articles were deemed valid and credible for involvement as they were published in peer-reviewed journals and sourced from respectable databases. Articles’ publication dates range from 2012 to 2021. Additionally, The U.S. Department of Agriculture Dietary Guidelines for Americans 9th edition was referenced. Keywords phrases searched included childhood obesity, diet, socioeconomic status, nutritional requirements, diseases of affluence, physical activity, and intervention.

Discussion

Causes of obesity

Over the years, the cause of obesity has been simplified to total calorie intake surpassing calorie expenditure. Although this may be factual, it is more complex. Caloric imbalances have been exacerbated by obesogenic behaviors and environments, i.e., conditions that are highly correlated with excess weight gain (8, 9). 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, increased screen time, and shortened sleep duration (9). Larger portion sizes and increased frequency of meals and snacks also contribute to an obesogenic environment. These conditions are influenced by various factors, one notably being genetics. There is increasing research exploring genetic predisposition to obesity. Some studies have

found that body mass index (BMI) is 25–40% heritable (10). The monogenic model of obesity explains that obesity is mainly due to mutations within the leptin/melanocortin pathway (Figure 1) in the hypothalamus that is necessary for the regulation of food intake, satiety, body weight, and energy metabolism (11).

Figure 1. Leptin/melanocortin pathway. Adapted from (26).

This is rare in comparison to the polygenic model of obesity, which is a compilation of multiple genetic variants and is a result of the interplay between genetic susceptibility and the environment (11). In fewer cases, obesity is a secondary effect of diseases such as Prader-Willi Syndrome or hypothyroidism. Environmental factors such as school policies, demographics, and parents’ work-related demands further influence eating and activity behaviors (10). Alongside socioeconomic status, there are socio-cultural factors that influence the risk of obesity. Eating behaviors develop early on and young children learn to eat through their direct experience with food and observing others eating around them (11). This illustrates that obesity is multifaceted, and a simple equation does not sufficiently summarize its complexity.

Nutrition and lifestyle

The nutritional requirements of children differ greatly from those of adults. At ages critical for growth, it is important that children receive the necessary nutrients to develop, and this can be accomplished with diets balanced in protein, fats, and carbohydrates. These food groups contain vital components that assist in the prevention of acquiring obesity and other related lifestyle diseases; however, with the prevalence of fast-food industries, sugary beverages, and snacks, the diet of many children and adolescents has become calorie dense. The Dietary Guidelines for Americans recommend that children between 2–18 years of age consume 2 to 3 cups of fruits and vegetables per day, but most of the youth population does not meet this requirement, as the actual consumption rate is closer to 0.7 to 1.8 cups (12). This is a significant difference, suggesting that many children and adolescents do not consume even the recommended minimum of fruit and vegetables. Aune et al. analyzed 95 studies that evaluated fruit and vegetable intake in relation to cardiovascular disease, total cancer, and all-cause mortality. It was concluded that fruit and vegetable intakes were associated with a reduced risk of the aforementioned diseases; specifically, there was an 8–16% reduction in the relative risk (RR) of coronary heart disease, 13–18% reduction in the RR of stroke, 8–13% reduction in the RR of cardiovascular disease, 3–4% reduction in the RR of total cancer and 10–15% reduction in the RR of all-cause mortality for each 200 g/day increment in intake of fruits, vegetables, and fruits and vegetables combined (13). In the nonlinear models, there were 16%, 28%, 22%, 13%, and 27% reductions in the RR of coronary heart disease, stroke, cardiovascular disease, total cancer, and all-cause mortality, respectively, for an intake of 500 g of fruits and vegetables per day vs 0–40 g/day, whereas an intake of 800 g/day was associated with 24%, 33%, 28%, 14% and 31% reductions in the RR, respectively (13). Another study suggested vegetable intake alone is more important than fruit consumption, because vegetables have a greater protective effect than fruit; reducing death by 16% per each daily portion compared to 4% for fruit (14). Vegetable intake is low possibly due to their strong or bitter taste, unfamiliar texture, low energy density, and lack of availability/accessibility (14). Adequate fruit and vegetable consumption are essential components of a healthy diet with significant benefits and preventive power. Implementing these eating behaviors during childhood and adolescence can delay the onset and disrupt the progression of lifestyle diseases. However, there is increased consumption of fruit juices. Most juices are highly acidic, provide minimal roughage, and contain added sugar. There are contradicting recommendations for added sugar consumption, making it difficult to accurately assess the tolerable amount to consume. According to the 2015–2020 Dietary Guidelines, the total daily consumption of added sugars should be limited to less than 10% of calories per day from the age of 2 years (12). The Institute of Medicine recommends that added sugar is less than 25% of total calories, whereas the World Health Organization (WHO) recommends limiting added sugars to less than 100 calories for women and 150 calories daily for men (15). Studies have shown that individuals who consume higher amounts of added sugars, especially sugar-sweetened beverages, tend to gain more weight and have a higher risk of obesity (15). One 12-ounce can of Coke contains 120 calories from added sugar; there is even more sugar in energy drinks, and children and adolescents are the main consumers of these products. This illustrates that recommended sugar intake limits are easily reachable and likely surpassed daily due to added sugars. A major component of added sugar is fructose, and recent studies strongly suggest that excessive fructose intake and metabolism contribute to obesity. Fructose can be metabolized into fat. Glucose and fructose are dietary sugars with the same caloric value, but they differ in the way they are metabolized in the body (16). When ingested, glucose is used directly to provide energy to tissues such as the brain and muscles, and any residual glucose is converted to glycogen and stored in the liver. However, through the polyol pathway, glucose can also be converted to fructose (Figure 2).

This mechanism also takes place in the liver, and with the presence of the enzyme ketohexokinase, fructose is converted to fructose 1-phosphate. Fructose 1-phosphate can bypass a major regulatory step in glycolysis that generates fructose

ROS

Toxic aldehydes

Glucose

Aldose reductase

NADPH NADP+

GSSG GSH

NADPH

Oxidative stress Inactive alcohols

Sorbitol Sorbitol dehydrogenase

Glycative stress

Fructose

NAD+ NADH

Osmotic stress

NADH/NAD+

Reductive stress

Electrolyte imbalance & hydration and membrane damage

Figure 2. Polyol pathway and various pathogenic factors involved in diabetic complications arising from obesity. Adapted from (27).

1, 6-bisphosphate through the action of the energy-sensitive enzyme phosphofructokinase (16). In the absence of feedback inhibition, fructose is used to generate fat, unfettered by the cellular controls that prevent unrestrained lipid synthesis from glucose (16). Fructose can also be introduced directly into the diet and therefore, is not limited to an alternative pathway of glucose metabolism. The two major sources of fructose are sucrose (table sugar), which consists of 50% fructose and 50% glucose, and high-fructose corn syrup, which has varying fructose content, from 42% in pastries to 55–65% in fountain drinks (17). The combination of direct intake of fructose and glucose metabolism to fructose increases the total amount of fructose that can be converted to fatty acids. Diets high in fructose can cause excess fat accumulation in the liver, leading to liver disorders like fatty liver disease, steatohepatitis, and ultimately cirrhosis (16). Nonalcoholic fatty liver disease (NAFLD) is the most common liver disease in children and adults and is a hepatic manifestation of obesity and metabolic syndrome (17). This disease is strongly associated with fructose ingestion (17). Thus, total caloric intake is an important factor in obesity and its correlated consequences; however, where the calories are coming from may be even more significant.

In addition to nutrition, lifestyle patterns also contribute to the manifestation of obesity. Lifestyle patterns include physical activity, sedentary behaviors, and sociocultural influences. Physical activity has decreased with the increased use of cars, buses, and other labor-saving devices (8). People are experiencing prolonged periods of inactivity through jobs that require being stationary at a desk for extended periods of time. This applies to children too, as they are seated most of the day during school, and after-school extracurricular activities that do not include sports and even extend to their homes as they do their assignments. Sedentary behaviors are the behaviors we engage in once we are inactive. With the advancement of technology, leisure time is spent watching television, playing video games, and browsing the internet. Most of these activities are accompanied by eating. It is difficult to keep track of what is consumed when the attention is primarily elsewhere. To a lesser degree, in some households, food is used as a reward or punishment, which could also influence dietary patterns.

Socioeconomic status

Diseases of affluence are all chronic non-communicable diseases that are thought to be a result of increasing wealth and ease of life in society (3). Included in this category are obesity, cardiovascular disease, Type 2 diabetes, dyslipidemia, hypertension, certain cancers, and respiratory diseases. These diseases have a greater impact on poorer vulnerable populations. Vulnerable populations are those with a greaterthan-average risk of developing health problems by virtue of their marginalized socio-cultural status, their limited access to economic resources, or their personal characteristics (18). Based on this definition of a vulnerable population children in the United States belonging to minority/ethnic groups and low socioeconomic status are considered a vulnerable population (18). Obesity prevalence increased by 10% for all U.S. children, whereas obesity increased by 23–33% for children in low-education, low-income, and higher-unemployment households in 2003–2007 (19). This may seem contradictory because it is described as a result of the increasing wealth in society. However, increasing wealth in society brings about an abundance of food that is cheap and of low quality with minimal nutrition, and people of low SES are most susceptible to consuming these high-density foods. Low SES families typically

are food insecure and/or live in a food desert. They are also at risk because they have limited access to healthcare, are uneducated in matters related to lifestyle diseases, and usually have lower-income jobs that require more time to secure financial stability. Low-income families are less likely to realize that their child is overweight and/or intervene in the child's eating and activity behaviors (19).

Childhood obesity can start as early as infancy for children of disadvantaged backgrounds. Breastfed children have a lower risk for obesity. Various studies have found that breastfeeding provides a protective effect against excessive childhood weight gain (20), but mothers of low SES are less likely to breastfeed. A study was conducted with the aim of highlighting the primary maternal-related pathways through which socioeconomic disadvantage influences early childhood obesity (20). The maternal-related pathways included infant feeding practices and maternal characteristics. Observed infant feeding practices were breastfeeding, formula feeding, early solid food introduction, and infants put to bed with a bottle. The maternal characteristics were weight, mental health, and smoking. The sample consisted of 8,030 children based on the data from the Early Childhood Longitudinal Study of children from 9 months to kindergarten age. Family SES was measured by a composite scale consisting of household income, parental education, and occupational prestige created by the National Center for Educational Statistics, which served as a strong predictor of early childhood outcomes (20). The children were weighed at 9 months and 24 months. Their measurements were compared to the growth charts provided by the Centers for Disease Control and Prevention. A value marked within the 98th percentile at 24 months was an indication of childhood obesity. The other metric used was the child’s BMI at the 95th percentile. After 24 months, approximately 10% of the children were obese. Formula-fed infants had a higher percentage of obesity after 6 months (11.7% compared to 5.6%), being put to bed with a bottle (40% compared to 9%), and early introduction to solid foods (29% compared to 9%). Households with higher SES and breastfeeding were less likely to engage in these feeding practices and exhibited healthier feeding patterns. In conclusion, infants from socioeconomically disadvantaged backgrounds experienced several risk factors starting at birth that put them on a trajectory towards early childhood obesity (20). A follow-up of these children into adolescence could provide more information about these effects on childhood obesity and assist in designing effective interventions. Rogers et al. (19) studied the relationship between childhood obesity, low SES, and race/ethnicity. This study assessed whether race/ethnicity remained an independent predictor of childhood obesity when accounting for variations in SES (low-income) among communities in Massachusetts (19). The cohort included 111,799 students in grades 1, 4, 7, and 10 from 68 school districts. BMI was calculated for each student and the percentage of students who were overweight or obese was compared with the percentage of students in each district who were eligible for free/reduced-price lunch, received transitional aid, or were eligible for food stamps (19). Overweight or obese children ranged between 9.6% and 42%, with a mean prevalence of 32%, and low-income status among Massachusetts school districts varied from 2.4% to as high as 69.5%, with a mean prevalence of 27%. Multiple regression models demonstrated that districts’ low-income status was strongly associated with overweight/obese status (19). Race/ ethnicity was not statistically significant when community income was factored in. Therefore, in Massachusetts, race/ ethnicity was independent of low SES and childhood obesity manifestation. Studies conducted on a state-by-state basis, are important for formulating more targeted intervention strategies. Generalized strategies are useful, but more can be achieved when considering the characteristics of each community. Food security means access by all people at all times to quality food for an active, healthy life. In contrast, food insecurity implies a limited ability to secure adequate food due to insufficient household resources (21). In addition to consumption of a diet high in fat and energy value, children from food-insecure backgrounds may engage in binge eating as an adaptive response to episodic food shortages (22). A study was conducted to analyze the relationship between household food insecurity with and without hunger in infancy and childhood. It should be noted that currently, food insecurity with or without hunger is referred to low food insecurity or very low food insecurity, respectively. This study consisted of 28,335 children from diverse backgrounds with low SES. These children participated in the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) in Massachusetts between 2001 and 2006. WIC provides federal grants to states for supplemental foods, healthcare referrals, and nutrition education for low-income pregnant, breastfeeding, and nonbreastfeeding postpartum women, and to infants and children up to age 5 who are found to be at nutritional risk (22). The child’s anthropometrics were measured every 6 months by a WIC representative or by the child’s pediatrician who reported to the organization. These values were used to calculate BMI to assess the risk of obesity. Food security was measured based on the parent/caretaker responses to a four-question subscale of the 18-item Core Food Security Module. The four items on the subscale addressed the aspects of not having enough money to buy food for a balanced meal, adults cutting the size of or skipping meals, adult frequency of cutting or skipping meals, and adults not eating for a whole day (22). Based on those responses the families were categorized as food secure, food insecure with hunger, and food insecure without hunger. Other variants considered in this analysis were maternal weight, pre-pregnancy weight, age, and education. The data at the first infant visit was compared to the last child visit, which is between 2 and 5 years of age. About a quarter of the infants lived in households with some food insecurity, and 5.7% of that quarter were living in food insecure households with hunger. At their child visit, 23% of the children lived in households with some food insecurity, with 4.6% living in households with food insecurity with hunger (22). At the end of the study, about 17% of the children were obese. Households that had continuous food insecurity without hunger were associated with 22% greater odds of childhood obesity compared to households that are predominately food secure. Maternal pre-pregnancy weight was also a significant factor in the findings, as infants of overweight or obese mothers had a 65% greater risk for obesity. In conclusion, the results suggest that persistent household food insecurity without hunger is prospectively related to childhood obesity, but that the association depends on the maternal weight status (22).

Although many studies support the association between childhood obesity and food insecurity, a few studies have reported contradictory results. These studies add to the complexity of addressing pediatric obesity. For example, Gunderson et al. (23) found no association between childhood obesity and food insecurity. This study used multiple measures for the indication and assessment of childhood obesity compared to other studies that relied primarily on BMI. This approach was based upon our knowledge that excessive body fat is the pathology associated with obesity, and it cannot be measured directly using BMI since BMI does not distinguish between mass in the form of fat, lean tissue, or bone (23). This study included 2,516 children between the ages of 8 and 17 years from households below 200% of the poverty line, which suggests food insecurity according to the National Health and Nutrition Examination Survey (NHANES). The metrics used to classify obesity were BMI, waist circumference (WC), triceps skinfold thickness (TSF), trunk fat mass, and whole-body fat percentage. Food insecurity was measured using a method created by the U.S. Department of Agriculture (USDA). It consists of 18 questions from the Core Food Security module described in the study. The following results were attained: 18% of children were considered obese via BMI assessments, 21% via WC, 15% via TSF thickness, 30% via trunk fat mass, and 45% via body fat (23). Food insecurity status was cross-examined with these dimensions, and it was concluded that food-insecure children were no more likely to be obese than their food-secure counterparts (23). Additional research can be done to include these other measurements that indicate childhood obesity. In this same study, it was deemed significant to note that food insecurity and obesity often coexist in low-income children, because depending on the obesity measure and subsample assessed, 12–57% of food-insecure children were also obese (23).

Intervention

Due to the complexity of childhood obesity, intervention can be challenging. Effective solutions need to be easily applicable to the public, but also adaptable to populations based on their unique characteristics. This approach would produce results that address the high prevalence of child obesity. One study proposed federal policy as an agent of change. Federal policy can impact a broad scope of people, making it a powerful resource. This study aimed to assess the impact of three federal policies on childhood obesity prevalence in 2032, after 20 years of implementation (5). Microsimulation models based on demographic and behavioral variables were used to project the efficacy of the policies. The sample consisted of simulated school-aged children, 6 to 12 years of age, and adolescents, 13 to 18 years of age. BMI and overall changes in the percentage of overweight or obese children were used as the chief form of evaluation. The policies implemented were afterschool physical activity (PA) programs, sugar-sweetened beverage (SSB) excise tax, and a ban on fast food television targeting children. Through initial observation, it was found that over one-quarter of children get the recommended one hour of daily PA, whereas only 1 in 5 adolescents do, and approximately one-third of the simulated youth consume SSBs at least twice per day (32.3%) and fast food at least twice a week (35.4%) (5). The microsimulation predicted the following results—afterschool PA programs would increase the number of children and adolescents who met the daily PA recommendation by 7.7% and 7.4%, respectively; a $0.01/ounce SSB excise tax would reduce the number of children and adolescents consuming two or more SSBs per day by 11.4% and 16.6%, respectively; and the number of children eating two or more fast food meals per week would drop by almost 20% and for adolescents by 18% (5). In conclusion, these policies would be effective measures in reducing childhood obesity prevalence by 2032. Another intervention is through educational programs that enlighten parents or caretakers on childhood obesity. One study used motivational interviewing (MI) delivered by primary care providers (PCP) and dietary counseling by registered dieticians (RD) to reduce pediatric obesity. MI is a patient-centered communication style that uses specific techniques such as reflective listening, autonomy support, shared decision-making, and eliciting change talk (24). Forty-two practices from the Pediatric Research in Office Settings Network of the American Academy of Pediatrics were randomly assigned to one of three groups. Group 1 (usual care) measured BMI percentile at baseline and at 1- and 2-year follow-up and provided routine care by the PCP, as well as standard educational materials for parents (24). Group 2 consisted of only PCPs and had similar components to group 1 with the addition of training in motivational interviewing and behavior therapy. Group 3 consisted of both PCPs and RDs. It had similar components to the other groups with the addition of motivational interviewbased counseling from a trained RD linked to the practice. BMI was the primary metric used to evaluate the intervention. At a 2-year follow-up, the adjusted BMI percentile was 90.3, 88.1, and 87.1 for usual care (group 1), group 2, and group 3, respectively (24). The results indicated that overweight children whose parents received MI counseling from their PCPs supplemented by RD counseling showed a significant reduction in BMI percentile over 2 years compared with children whose parents received usual care (24). The net difference in BMI reduction between these two groups was 3.1 BMI percentile units, which is a significant difference. This strategy yielded outcomes that strongly suggest that MI and dietary counseling are effective intervention approaches. Media significantly influences the eating behaviors of children and adolescents and hence can be used to promote healthier eating habits. Many of the food products passively advertised in children’s media lack nutritional value and the consumption patterns shown can have potentially harmful effects on the eating behavior of children (25). Often in children’s movies and television shows, times of enjoyment, fun, or happiness are associated with eating “fun foods” such as pizza, ice cream, candy, hot dogs, etc. These foods are high in saturated fats, salt, and sugar (HFSS). Likewise, these same foods are also used when the mood of the child needs to be lifted, commonly following a scene where the child was noticeably sad at the dinner table avoidably pushing around their vegetables. This can create a dangerous association between food perception and eating behavior. In addition, food consumption on social media platforms, such as YouTube, is often portrayed in a rather extreme and distorted manner. For example, so called Mukbang videos (loosely based on the Korean translation for “eating broadcast”) typically showcase the overeating of large quantities of food (25). Media has been used to promote an obesogenic environment, but more cautious regulated

efforts can assist in its reversal. Folkvord et al. detail that most published studies focused on decreasing the reinforcing values of HFSS foods, but state it is also important to explore the potential of reinforcing healthier foods and assessing whether there is a long-term impact. A recent overarching theoretical model has been developed to explain and predict how the food promotion of fruits and vegetables works. It uses an eclectic synthesis of existing theoretical models from different disciplines and recent empirical evidence (25). The four basic assumptions of this model are that: 1) By increasing the reinforcing value of fruit and vegetables through effective food promotion techniques; 2) a reciprocal relation with eating behaviors occurs, that, in time; 3) leads to a normalization of the intake of fruits and vegetables, and lastly; 4) individual and contextual factors determine individual and contextual factors determine individual susceptibility to food promotion and food acceptance (25). This is a burgeoning area of research with great potential to alter pediatric consumption practices.

Conclusion

In the U.S. the increase in the incidence of childhood obesity has declined; however, prevalence is still high with a significant risk of lifestyle diseases and morbidity. A major attributing factor to childhood obesity prevalence is the inadequate consumption of fruits and vegetables and the increased intake of foods high in fat, salt, and sugar. Further, low physical activity, sedentary lifestyles, shortened sleep duration, and media have also contributed to an obesogenic environment. Other factors such as genetics, sociocultural factors, and socioeconomic status also influence childhood obesity. A promising area of research for intervention is in children’s media, being that we are in a more advanced technological era that will only progress further. Federal policy intervention is also a promising starting point because of the potentially large outreach that can be achieved. This would most notably assist vulnerable populations of low socioeconomic status and populations that are battling food insecurity. Educational programs should be at the foundation of all strategies. Awareness creates opportunities for children and adolescents to learn healthy habits that can be implemented long-term into adulthood. As more research and intervention strategies are conducted, the multifactorial characteristic of childhood obesity needs to be continually assessed. Strategies that target and address multiple factors may provide the most beneficial outcomes.

Acknowledgments

I am immensely grateful to Darina Lazarova, PhD, for her guidance on the earlier versions of the manuscript.

Disclosures

The author declares that she has no relevant or financial interests related to the research described in this paper.

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