The Surgeon General, the Institutes of Medicine, and the World Health Organization have classified childhood obesity as an epidemic in need of immediate and wide-reaching attention. The prevalence of childhood obesity has nearly tripled over the last 20 years, with 17% of children now considered obese. Pediatric health care providers have focused on prevention of the long-term sequelae of obesity, but now find themselves screening for and treating diseases previously found only in adults. Of children with newly diagnosed diabetes, nearly half have type 2. Childhood obesity is significantly associated with increasing health care costs, with an estimated $14 billion spent annually in caring for obese children and their weight-related comorbidities. This number is expected to rise as today’s obese children become tomorrow’s obese adults; recent projections estimate the future costs of care at $254 billion. Improvements in cardiovascular mortality in young adults are leveling off or worsening, and life expectancy may be shortened in this next generation. Although there is not a “one size fits all” approach, prevention and treatment modalities can be effective, and given the magnitude of the problem, they should be used and customized for individual children and families.
Definitions
Any definition of obesity must take into account two important criteria: diagnosis of increased body fat, and identification of an increased risk of adverse health outcomes. Currently there are no broadly accepted standards for body fatness for either adults or children. As a result, body mass index (BMI), which is calculated as weight (in kilograms) divided by the square of height (in meters), is used as a screening tool for both adult and childhood obesity. Although BMI cannot determine body fat content, it has been shown to accurately identify children with increased adiposity in a population, with fairly high specificity and moderate sensitivity. Alternative methods of determining body fat content, such as skin-fold thickness or waist circumference, are difficult to perform reliably in a clinical setting. Although skin-fold thickness measurement is predictive of total body fat in children, it is not recommended for routine use due to lack of readily available reference data, training involved in performing, and measurement error between operators. Waist circumference is increasingly correlated with excess weight in children and may be useful in predicting insulin resistance and other comorbidities. Although waist circumference is not as useful in predicting total adiposity, it has been found to be increasing over time, even with a stable BMI. This indicates that BMI may be less helpful in detecting central adiposity in children. As with skin-fold thickness, there is difficulty in performing waist circumference measurements reliably, especially in obese populations; there are no readily available standards in children, and therefore waist circumference measurement is not recommended for routine clinical use. Other more precise and sensitive methods for determining adiposity are too expensive (ultrasound, computed tomography, magnetic resonance imaging, dual energy X-ray absorptiometry, air displacement plethysmography), or are lacking normative data in children (bioelectric impedance analysis).
In adults, overweight is defined as a BMI ≥25 kg/m 2 , and obesity as a BMI ≥30. Additional higher levels are class 2 obesity, BMI ≥35, and class 3, BMI ≥40. These cut-off points were determined based on short-term and long-term health risks in adults. In children, such cut-offs have not been conclusively determined, yet statistically derived cut-off points define overweight in children as BMI ≥85th percentile for age and gender compared with nationally representative populations, and obesity as BMI ≥95th percentile. These cut-offs were originally created arbitrarily and for clinically practical reasons. However, more recent studies have found that for several short- and long-term outcomes, children with BMI percentiles above these levels have a higher risk of morbidity than their peers with lower BMI percentiles. Expert recommendations recognize that a BMI ≥95th percentile in older teens is higher than a BMI of 30 kg/m 2 . Therefore, the committee recommended that obesity be defined as a BMI of 95th percentile or of ≥30 kg/m 2 , whichever is lower. For children younger than 2 years of age, BMI is not used in the United States; instead, the use of weight-for-height is recommended (weight-for-height above the 95th percentile is considered overweight).
There is a need to establish nomenclature for higher levels of obesity for children under consideration for bariatric surgery or other aggressive forms of treatment. A BMI ≥40 kg/m 2 is class 3, or morbid obesity in adults, and has been proposed for children; however, it is not pertinent to younger children or even children in early adolescence, for whom a BMI ≥40 is extremely high. The 2000 Centers for Disease Control and Prevention (CDC) curves have a maximum BMI of 36. To aid in the clinical care of children who may not be included on the published curves, additions to these curves have been suggested, and newer expert recommendations have suggested the classification of severe obesity as a BMI greater than 120% of the 95th percentile for age and gender, or a BMI ≥35 kg/m 2 , whichever is lower. This is being used in place of an older classification of the 99th percentile BMI.
Despite the evident shortcomings in using BMI and BMI percentiles to screen for overweight and obesity in children, it is the current standard of care for all children. The American Academy of Pediatrics (AAP) recommends calculating BMI as the preferred measure for evaluation of childhood overweight and obesity. This recommendation includes the calculation and plotting of BMIs on a growth curve for all children older than age 2 years, at least annually. The tracking of BMI and weight status can be of use to identify early onset obesity. A child’s BMI reaches a natural nadir between 5 and 6 years of age and then rises again; this is referred to as the adiposity rebound. An early nadir and increase, occurring before 5 years of age, is associated with increased risk of hypertension and obesity in adulthood, primarily due to increased fat, rather than lean muscle deposition. However, it has not been clearly determined if intervening with early adiposity rebound prevents later obesity.
Epidemiology
The epidemiology of overweight and obesity in both children and adults in the United States has changed dramatically over the last several decades. In 1980, the prevalence of obesity among adults was 15%; in 2011, it was 34.9%. There is an indication that levels of obesity among adults may be leveling off, as no statistically significant increases in the prevalence were found between the periods of 2003 to 2004 and 2009 to 2010. Similar trends have been found for children and adolescents. During the period 1971 to 1974, the prevalence of overweight among children and adolescents ages 2 to 19 years was 15.3%, and the prevalence of obesity in the same group was 5.1%. For the period 2009 to 2010, the corresponding prevalence rates were 31.8% and 16.9%, respectively. These trends may be leveling off; no statistically significant changes were observed among overweight and obesity prevalence rates in children from the periods 2007 to 2008 to 2009 to 2010. In addition, a small downward trend in obesity prevalence among preschoolers was seen during the period 2008 to 2011 in 19 of 43 U.S. states and territories studied.
Each age group of children and adolescents has shown alarming trends. Similar increases were seen in both boys and girls, as well as among children of different racial/ethnic groups. During this period, there was increasing disparity between racial/ethnic groups, with Mexican Americans and African Americans showing marked increases in obesity prevalence, particularly Hispanic boys and African American teenaged girls. The early onset of obesity is important to address, as children who are overweight upon entering kindergarten are four times more likely to be obese by eighth grade, and therefore have a higher risk for obesity as an adult.
Etiology and Pathogenesis
At the most basic level, obesity is a result of an imbalance between energy intake and expenditure. The acute rise in obesity prevalence, cardiovascular disease, and other chronic illnesses suggests that changes in the human environment and lifestyles are behind this epidemic. Bouchard elegantly outlined a model of this epidemic and its main contributors, grouped into four areas: built environment, social environment, behavior, and biology. In this model, the built and social environments combine to create an “obesogenic” environment, leading to “obesogenic” behaviors. Biologic predisposition then has a profound influence on an individual’s energy balance, and therefore risk of obesity.
Obesogenic Environment
From the convenience of fast food to the increasing use of cars instead of walking, changes in the built and social environment over the last 50 years have contributed significantly to childhood obesity. Attempts are frequently made to isolate a small number of significant contributors to the obesity epidemic, but much like the biologic control of appetite (see subsequent text), this is a complex problem. Changes in the social environment are represented by the increase in energy-dense foods and drinks, easily available in large portions and at low prices. Changes in family structure, including single-parent households and dual-career couples, have led to increased use of high-calorie, high-fat convenience foods. Higher socioeconomic status is a risk factor for obesity in developing countries, and protective in already developed countries. In developing countries, the wealthy are able to afford higher calorie foods and mechanized transportation, and are less likely to have jobs that require manual labor. In developed or industrialized countries, much of the obesity epidemic is thought to result from food insecurity, where a person or family is at risk of being unable to provide food. This can lead to the purchase of bulk, energy-dense foods, which are often less expensive and engineered to be highly palatable, thereby increasing overall caloric intake and decreasing nutrient quality.
Systematic examinations of built environments reveal few consistent findings. Children are less susceptible to the decreased caloric expenditure of motorized travel and sedentary jobs, but electronic entertainment plays a large role. Video games, television, computers/Internet, and even cell phone use have led to increasing hours of sedentary activity in children (averaging more than 21 hours a week), which has been clearly associated with obesity. There is evidence that “screen time” use longer than the AAP’s recommended less than 2 hours a day increases childhood and later adult risk of obesity. Finally, investigation of the environment of children, including the safety of local roads, proximity of schools and playgrounds, hazards, walkability and safety of neighborhoods, and population density all influence a child’s weight status and risk of future obesity.
A recent literature review examining the association between childhood obesity and the built environment identified several areas of interest. Children in neighborhoods with perceived best access to shops, as well as those with more green open spaces and wider streets reported better eating habits, including increased consumption of fruits and vegetables, decreased consumption of fats, and lower incidence of overweight or obesity. This review also found that increased access to open green areas, in both urban and rural areas, was associated with increased physical activity in children. Active commuting to school and other activities was associated with traffic safety, pedestrian infrastructure, and lower crime threat. Although individual neighborhood walkability variables (including sidewalks, road safety, aesthetics, and residential density) were not associated with BMI, overall walkability of a neighborhood was associated with childhood overweight/obesity. Obesity was found to be associated with distance to fast food restaurants, presence and density of convenience stores, distance to playgrounds, and perceived access to gardens, playgrounds, parks, and shops. Perceived neighborhood safety was associated with some forms of physical activity; however, including screen time in the model negated this association.
In summary, obvious changes in the nutritional and activity (sedentary and physical) environments of children, possibly mediated by changes in families and socioeconomic status, have contributed significantly to this epidemic. The concept of biopsychosocial factors influencing a child’s weight status mirrors that of the ecological model. Nested layers of influence surround the child, all with direct or indirect effects on their lifestyle habits, and therefore their weight and health. Most proximal is the child’s own personal characteristics, including their behavior and susceptibility to weight gain. Next is the family, with influences of the parent being the most immediate, as well as issues of socioeconomic status and role modeling. Broader influences, such as the community and general culture, can have profound effects on obesity risk, even though they may be indirect and more difficult to determine.
Behavior
Much research has centered on various eating and activity behaviors and the potential impact of each on childhood obesity risk and prevalence. Little direct evidence exists for the importance of a single eating pattern on an individual’s weight status; rather it is more likely that several eating behaviors exist concurrently and interrelatedly, and that the impact of each is modified by the individual’s genetics, ethnicity, and gender. Eating behaviors such as those described in the following text are thought to contribute more to excess energy consumption than to absolute weight status.
Some of the specific eating behaviors that have been targeted as potential mediators of obesity include the following: restaurant food consumption; sugar-sweetened beverage consumption; fruit juice consumption; increasing portion sizes; energy-dense food consumption; decreased fruit and vegetable consumption; irregular or no breakfast consumption; and frequent snacking. Recent research has highlighted several of these behaviors and their relationship with childhood obesity. Consumption of sugar-sweetened beverages has been found to be correlated with BMI in both school- and preschool-aged children. Replacing sugar-sweetened beverages with sugar-free beverages in school-aged children was found to reduce weight gain, and an educational intervention to encourage adolescents to choose sugar-free beverages showed a smaller increase in BMI in the experimental group after a 1-year follow-up. Larger portion sizes have been associated with increased energy intake in children; however, an association of this behavior with overweight or obesity in children has not been described. Several international studies have found an inverse association between breakfast consumption and childhood BMI. In the United States, school breakfast appears to be protective against obesity. A recent large, nationally representative study found that American adolescents are increasing their daily physical activity, consumption of fruits and vegetables, and frequency of eating breakfast; despite these improvements, however, the same study also found an overall increase in BMI in the same group of adolescents. The apparent paradox of this evidence suggests other perhaps more important drivers of childhood obesity.
Various activities have been suggested as either attenuating or increasing BMI in children. Physical activity or exercise is thought to be beneficial for prevention of obesity as well as weight loss. A recent systematic review of the literature concluded that, although some of the more recent studies have found an inverse relationship between physical activity and weight status, many studies found no relationship between the two. In addition, sedentary activity, specifically television viewing, is associated with higher weight status; however, a dose–response relationship between the two has not been determined. Exergaming (active electronic media and video games) research found that active games can be used to increase physical activity among children. Despite the uncertainty around media use and weight, the AAP recommends no more than 2 hours of screen time per day for children older than 2 years of age.
Parenting and parenting style have become a new focus of intervention and prevention of obesity. A commonly used paradigm categorizes parenting styles by a parent’s expectations for child self-control and sensitivity toward the child. The application of this theory to parental feeding approaches has determined risks for childhood obesity, with overly controlling practices (authoritarian) having the highest risk ( Table 14-1 ). A summary of parenting and feeding styles and their relationship to childhood obesogenic behaviors and body weight found that the authoritative style appears to be the most protective parenting and feeding style. Although the mechanism of this relation has not been fully delineated, it does present opportunities for treatment and prevention at early ages. Including parents in any obesity intervention or treatment plan is critical; effective long-term obesity studies identify that intense parental involvement and parenting skills are key to their success.
| Parenting Style | Expectations for Self-Control | Sensitivity | Prevalence of Parenting Style in Study (N) | Prevalence of Obesity % |
|---|---|---|---|---|
| Authoritative | High | High | 20.5% (179) | 3.9% |
| Authoritarian | High | Low | 34.2% (298) | 17.1% |
| Permissive | Low | High | 15.1% (132) | 9.8% |
| Neglectful | Low | Low | 30.2% (263) | 9.9% |
Biology
There have been great strides in understanding the control of appetite, energy expenditure, and overall weight control in the last two decades, most notably in the discovery of the leptin gene in 1994. Although leptin did not turn out to be the “smoking gun,” it unveiled a complex regulatory system of energy intake and expenditure, using short-term and long-term feedback mechanisms to balance appetite and metabolism. Furthermore, a paradigm shift occurred in how adiposity, and more specifically the adipocyte, is viewed. No longer seen as a storage cell for excess calories, visceral adipose cells are categorized as independent endocrine cells with important roles in metabolism, inflammation, and cardiovascular disease ( Table 14-2 ).
| Name | Function/Effects | Effect |
|---|---|---|
| Adiponectin | Inhibits inflammatory and other metabolic processes | Increases insulin sensitivity, decreases atherosclerosis; independent risk factor of metabolic syndrome; linked to nonalcoholic fatty liver disease risk |
| Interleukin (IL)-6 | Stimulates hepatic production of C-reactive protein (pro-inflammatory) | Decreases insulin sensitivity; increases atherosclerosis |
| Tumor necrosis factor α (TNF-α) | Stimulates acute phase reactants | Decreases insulin sensitivity; increases atherosclerosis |
| Plasminogen activator inhibitor 1 (PAI-1) | Inhibits plasminogen and fibrinolysis | Increases risk of thromboembolic events |
| Leptin | Satiety signal via agouti-related peptide/neuropeptide Y (AgRP/NPY) neurons; multiple other effects in body | Leptin resistance linked to obesity |
| Resistin | Stimulates inflammatory cytokines; highest concentration in mononuclear cells, but found in adipocytes | Role in insulin resistance unclear |
| Visfatin | Inhibits apoptosis of neutrophils; promotes B-cell maturation | Decreases insulin resistance |
| Omentin | Function not clear | Levels decreased with obesity, increased with increases in high-density lipoprotein (HDL) cholesterol, and adiponectin |
Figure 14-1 and Table 14-3 summarize key hormones and signaling agents involved in the control of energy intake (usually manifested in appetite and meal initiation and termination) and energy expenditure (through physical activity and metabolism). The gastrointestinal, central nervous, and adipose/storage systems are the primary areas involved in the short- and long-term balance of energy and weight. Despite the elegance of this network, it is still influenced greatly by environmental stimuli. As an example, initiation of meals is influenced to a greater degree by environmental signals, whereas meal size and termination may be influenced to a greater degree by biologic signals. As of 2005, only 176 cases of human obesity have been identified as caused by a single-gene mutation, surprisingly low given the number of biologic determinants of appetite and weight. All chromosomes except Y have areas associated with obesity phenotypes, with 135 different candidate genes having been identified. In all, more than 600 genes have been associated with human and animal models of obesity.
| Short Name | Full Name | Origin | Function/Role in Weight Homeostasis |
|---|---|---|---|
| AgRP | Agouti-related peptide | Arcuate nucleus (hypothalamus) | Increases appetite; decreases metabolism |
| ARC | Arcuate nucleus | Hypothalamus | Area of energy regulation; location of CART, POMC, AgRP, NPY |
| CART | Cocaine-amphetamine–regulated transcript neurons | Arcuate nucleus (hypothalamus) | Reduces energy intake |
| CCK | Cholecystokinin | Intestines | Reduces appetite (short term); slows gastric emptying; stimulates gallbladder contractions |
| Ghr | Ghrelin | Stomach | Increases appetite (short term) |
| GLP-1 | Glucagon-like peptide 1 | Intestines, L cell | Stimulates insulin release; reduces appetite |
| In | Insulin | Pancreas | Reduces energy intake |
| Lep | Leptin | Adipose tissue | Reduces energy intake |
| α-MSH | Melanocyte-stimulating hormone α | POMC (ARC, hypothalamus) | Reduces energy intake |
| NPY | Neuropeptide Y | Arcuate nucleus | Increases appetite; decreases metabolism |
| OR | Orexin | Hypothalamus | Increases appetite |
| Oxm | Oxyntomodulin | Colon | Reduces appetite |
| POMC | Pro-opiomelanocortin | Arcuate nucleus (hypothalamus) | Releases α-MSH; reduces energy intake |
| PP | Pancreatic polypeptide | Pancreas | Reduces appetite |
| PVC | Periventricular Nucleus | Hypothalamus | Appetite and autonomic regulation |
| PYY 3-36 | Peptide YY | Ileum, colon | Reduces appetite; slows gastric emptying |
Leptin deficiency or leptin receptor abnormalities are exceedingly rare. Although described in two severely obese cousins with undetectable serum leptin levels, leptin deficiency has been identified in very few individuals. Within a high-risk group (individuals with hyperphagia, severe early onset obesity, and some from consanguineous families), only 3% had mutations in the leptin receptor gene. There have been six reported mutations of the leptin gene, affecting the production of leptin itself or the leptin receptor. In a population of individuals who were severely obese since childhood, nearly 6% had a mutation in the melanocortin 4 receptor gene (MC4R, the target of melanocyte-stimulating hormone α (α-MSH), a centrally released appetite-reducing signal), making it one of the most common monogenic forms of obesity. However, there are no available therapies for this mutation.
There are other exciting discoveries, aside from the neuroendocrine control of appetite, which present potential targets for intervention. Endocannabinoids are anabolic regulators of metabolism, increasing energy intake, promoting energy storage, and decreasing energy expenditure. Antagonists to this receptor have been shown to improve obesity as well as other aspects of the metabolic syndrome (insulin resistance and hyperlipidemia), but concerns about depression and other side effects have limited its use. There is increasing interest in gut microbiota and its possible regulation of obesity. Predominance of specific groups of bacteria (Bacteroidetes, Firmicutes) has been associated with obesity in mouse models, with increasing evidence of an association in humans. There appears to be bacterial control of metabolic process that could affect energy regulation, but clear pathways have not been fully determined. Even more interesting is the possible role of infection in adipogenesis. There are also genetic mutations associated with taste, meal size, and food selection that are tied to obesity. Animal models have demonstrated that adenoviral and other viral inoculations increased adipogenesis. Further studies demonstrated that a higher percentage of obese humans had adenovirus-36 antibodies than did nonobese subjects. Again, these findings are interesting, but far from conclusive.
The influence of genetics on obesity is unmistakable, with studies estimating the heritability of BMI to be between 20% and 60%. Twin studies have found that genes account for nearly 80% of variation in body fat and BMI. It is impossible to tease out the environmental influences of body weight when investigating its genetic origins. Although it appears that individuals may be predisposed to weight gain, it is within the context of an obesogenic environment, with many modifiers, both known (i.e., parenting style) and unknown (i.e., infections), which further complicates the dissection of human obesity.
Assessment of the Obese Child
The assessment of the obese child requires investigation of his or her personal history, including a dietary and physical activity assessment, a focused family history, a review of systems, and a physical examination. In addition, laboratory, radiographic, and/or subspecialty evaluation may be necessary. Each of these components will be discussed in subsequent text of this chapter.
Taking the medical history of an obese child should focus on three main goals: identification of modifiable risk factors; identification of risks for medical comorbidities; and assessment of the patient’s and family’s readiness to change their behavior.
Modifiable Risk Factors
Nutrition: Dietary assessment can take various forms and may be a difficult endeavor. A 24-hour recall, intake diary, or food frequency questionnaire can be helpful; each has its own advantages and disadvantages. For example, 24-hour dietary recall involves significant recall bias, and intake diaries require precise amounts and recipes for the information to be clinically useful. Although there are no standard in-office assessments of eating behaviors, attempts should be made to assess certain eating behaviors for which there are some data to support their roles in overconsumption of energy (fast food or other restaurants, sugar-sweetened beverages, portion sizes, energy-dense foods, few fruits and vegetables, skipping breakfast, frequent snacking). A recent review of brief nutrition assessments for young children found several that may be applicable for in-office use and screening for specific obesogenic behaviors, but also recognized the limited resources available for clinical use.
Physical activity: Because the development of obesity is invariably an imbalance in energy intake and expenditure, assessment of the child’s physical activity is also critical. As with dietary history, assessing physical activity is difficult. A self-report or self-administered checklist to determine frequency, amount of time, and intensity of activity is commonly used for older children and adolescents. Children younger than 10-years of age are generally not able to accurately report this type of history; in these cases, parental recall is substituted. Although adolescents have the ability to participate in activities similar to those of adults, younger children have very different patterns of activity. Asking questions about the amount of time spent outside, involvement in sports programs outside of school, and “fun” activities or hobbies can be a good proxy for activity in younger children.
Sedentary activity: The amount of time spent in sedentary activity, particularly television viewing, has been found to be associated with higher BMI percentiles. Specifically for school-aged children, the number of hours of screen time per day was found to be a significant predictor of obesity. This relationship was less pronounced for older children and adolescents. Although this relationship is not as strong for other sedentary behaviors, such as playing computer or video games, these pastimes can replace more active pursuits, and must be balanced. Two recent reviews of exergaming have found that this practice may not be as detrimental as other types of screen time, and may even be helpful in increasing physical activity levels in children and adults. A thorough activity history also includes time spent engaging in sedentary activity.
Medical Comorbidity Risk
Family History
The family history is crucial, both for assessment of the risk for persistence of obesity into adulthood, and the risk of current and future comorbidities. Family history should be assessed specifically for three important conditions among first- and second-degree relatives: obesity, type 2 diabetes mellitus (T2DM), and cardiovascular disease, including hyperlipidemia and hypertension.
Although weight status is generally determined by multifactorial influences, a child’s weight status is also strongly influenced by parental weight status. The risk of persistent obesity is higher if one or both parents are obese, regardless of the child’s current age or weight status. Both maternal and paternal weight status have been shown to independently and significantly influence the child’s BMI, even after adjusting for lifestyle, environment, and presence of comorbidities.
The development of T2DM has a strong genetic component. A positive family history for T2DM is a risk factor for insulin resistance in children. Certain racial/ethnic groups (Native American) are at particularly high risk given the high prevalence rates in both adults and children. Family history should also be assessed for cardiovascular disease; this should encompass myocardial infarction, stroke, hyperlipidemia, and recognized risk factors for cardiovascular disease, including obesity, hypertension, and diabetes. Obesity and family history of hypertension are independent risk factors for the development of hypertension in children.
Physical Examination
The physical examination should include all of the components of a standard pediatric examination, with particular attention paid to certain aspects. Anthropometry is crucial in this evaluation: height and weight should be measured at each clinic visit, and a BMI should be calculated. The BMI should then be plotted yearly on a standard growth chart to determine the BMI percentile for age and gender. Special attention should be paid to measurement of blood pressure. It should be measured manually using an appropriately sized cuff, and may require a longer, narrower cuff; blood pressure measurements can then be interpreted with the aid of reference tables. Repeated measurements are necessary to support a diagnosis of hypertension.
The fundi should be visualized, looking specifically for signs of increased intracranial pressure, especially if there is a history of headaches. This can be an indication of the presence of pseudotumor cerebri. The thyroid should be examined for goiter in the context of signs of hypothyroidism; the oropharynx should be examined thoroughly for redundant tissue or enlarged tonsils for concerns of sleep disturbances.
The skin examination is very important in the evaluation of obesity. Acanthosis nigricans, a hyperpigmented, hyperkeratotic velvety plaque most often found on the back of the neck, in the axillae, or other body folds and over joints, may be associated with insulin resistance. Keratosis pilaris, skin tags, intertrigo, and furunculosis are all potential findings; striae characteristic of Cushing syndrome are found less often; obese children often have abdominal striae, or “stretch marks,” but these are not violaceous.
Although cardiac, pulmonary, and abdominal exams may be difficult in the obese child, they remain important components of the evaluation. Irregular sounds, murmurs, wheezing, and organomegaly, specifically hepatomegaly, are all significant findings on exam. Secondary sexual development should also be assessed. Obesity is associated with premature pubarche and stigmata of polycystic ovary syndrome (PCOS), including hirsutism, in girls; it is also associated with gynecomastia in boys. The genitals of an obese male may appear small and be concerning for micropenis, but retraction of the pubic fat pad and palpation of the penis and testicles will most often reveal normal genitalia.
The lower extremities can be affected by obesity. Limitation of movement or pain can be signs of underlying disease, specifically slipped capital femoral epiphyses (hips) or Blount disease (knees). In addition, the lower back and the feet and ankles should be examined as sources of pain, with particular attention to fallen or flat arches (pes planus).
Syndromes or genetic abnormalities causing obesity may also be of concern. These are extremely rare and usually are identified through common presentations. Thus, a work-up for a genetic syndrome in an obese child is only indicated if other manifestations of the syndrome are present. Prader-Willi syndrome is typically identified at a young age, and is characterized by short stature, small hands and feet, almond-shaped eyes with round face, hypogonadism, and significant developmental delay. Pro-opiomelanocortin ( POMC ) mutations ( Figure 14-1 , Table 14-3 ) are associated with adrenal insufficiency and present with red hair and pale skin. Retinitis pigmentosa in the setting of obesity, polydactyly, short stature, and developmental delay should lead to consideration of Laurence-Moon or Bardet-Biedl syndromes. Fragile X syndrome should be considered with the presentation of hyperactive behavior, large forehead, prominent jaw, large ears, and mental retardation, but macroorchidism should raise suspicion for this condition in an obese child. Mutations in the melanocortin receptor of the hypothalamus (MC4R4) are involved with inhibiting appetite and associated with tall stature and advanced bone age. In summary, short stature (with the exception of MC4R4), developmental delay and cognitive impairment, polydactyly or syndactyly, visual impairment, deafness, hypotonia, and abnormal facies found in an obese child should prompt a consultation with a geneticist.
Comorbidities
As the obesity epidemic continues to worsen, pediatric care providers must transition from assessing for future risk of weight-related comorbidities to the detection and treatment of them. Although not comprehensive, Table 14-4a provides a focused review of systems, and Table 14-4b summarizes the comorbidities associated with pediatric obesity and testing to assist in their identification. The review of systems should focus on symptoms of potential comorbidities. The degree of obesity does not reliably predict the presence of comorbidities, and many of the symptoms may be unrecognized as related to weight status by the family. Some of the following problems are most commonly identified during the review of systems: disordered sleep and obstructive sleep apnea; menstrual disorders and PCOS; and abdominal pain, potentially signaling nonalcoholic fatty liver disease, gastroesophageal reflux, gallbladder disease, or constipation.
| System | Symptom | Explanation |
|---|---|---|
| Respiratory | Shortness of breath, exercise intolerance, wheezing, cough | Asthma, aerobic deconditioning |
| Gastrointestinal | Vague recurrent abdominal pain | Nonalcoholic fatty liver disease |
| Heartburn, dysphagia, regurgitation, chest or epigastric pain | Gastroesophageal reflux | |
| Abdominal pain or distension, flatulence, encopresis, anorexia, enuresis | Constipation | |
| Right upper quadrant or epigastric pain, vomiting, colicky pain | Gallbladder disease, gallstones | |
| Endocrine | Polyuria, polydipsia | Type 2 diabetes mellitus |
| Amenorrhea, oligomenorrhea, or menorrhagia | Polycystic ovary syndrome | |
| Orthopedic | Hip, knee, groin or thigh pain, painful gait | Slipped capital femoral epiphysis |
| Knee pain | Slipped capital femoral epiphysis or Blount disease | |
| Foot pain | Increased weight bearing, pes planus | |
| Sleep problems | Loud snoring, apnea, daytime sleepiness, restlessness, short attention span, behavioral problems | Obstructive sleep apnea, disordered sleep |
| Mental health | Flat affect, sad mood, loss of interest, worries | Depression, anxiety |
| Body dissatisfaction, school avoidance, poor self-esteem | Depression, anxiety | |
| Hyperphagia, binge eating, bulimia | Disordered eating | |
| Genitourinary | Nocturia, nocturnal enuresis | Disordered sleep |
| Dermatology | Rash, irritated skin | Intertrigo |
| Darkened skin around neck and axilla | Acanthosis nigricans |
| Condition | Tests | Reason | Note |
|---|---|---|---|
| Cardiac disease | Lipid profile | Hyperlipidemia, hypertriglyceridemia, heart disease risk | |
| Hypertension | 24-hour ambulatory blood pressure monitoring | Rule out “white coat hypertension” | Use appropriately sized cuffs and age-appropriate norms |
| Complete blood count (CBC), metabolic panel, renin assay, urinalysis, renal ultrasound | Determine if secondary hypertension | ||
| Fatty liver disease | Liver ultrasound; α1-antitrypsin, ceruloplasmin, anti-nuclear antibody (ANA), hepatitis antibodies | Determine cause of elevated transaminases | Persistent elevation of AST, ALT for >6 months warrants further investigation |
| Liver biopsy | Determine cause of elevated transaminases, assess degree of hepatitis | Imaging cannot accurately determine inflammation and fibrosis | |
| Type 2 Diabetes Mellitus | Fasting glucose, glucose tolerance test, urinary microalbumin, Hemoglobin (Hgb) A1c | Assess for insulin resistance, renal involvement | Fasting glucose >125 mg/dL, Hgb A1c ≥6.5% indicative of diabetes; 100-125 mg/dL; Hgb A1c 5.7% to 6.4% considered pre-diabetes |
| Sleep apnea | Polysomnogram | Evaluate sleep | Can also indicate disordered sleep pattern |
| Orthopedic disease | Hip radiographs | Evaluate for slipped capital femoral epiphysis (SCFE) | Frog-leg positioning |
| Knee radiographs | Evaluate for Blount disease | ||
| Polycystic ovary syndrome | 17-OH progesterone, DHEAS, androstenedione, testosterone, LH, FSH, possibly pelvic ultrasound | Determine biochemical evidence of hyperandrogenism, or other cause of menstrual irregularity | |
| Precocious puberty | LF, FSH, testosterone or estradiol, DHEAS | Early onset of obesity | Physical exam often sufficient to evaluate |
| Pseudotumor cerebri | Funduscopic exam, lumbar puncture | Papilledema indicative of increased intracranial pressure; elevated opening pressure on puncture |
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