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Can't remember the title or the author of a book? AAP policy stipulates that the evidence supporting each KAS be prospectively identified, appraised, and summarized, and an explicit link between quality levels and the grade of recommendation must be defined.

Level X: not an explicit level of evidence as outlined by the Centre for Evidence-Based Medicine. This level is reserved for interventions that are unethical or impossible to test in a controlled or scientific fashion and for which the preponderance of benefit or harm is overwhelming, precluding rigorous investigation.

When it was not possible to identify sufficient evidence, recommendations are based on the consensus opinion of the Subcommittee members. Obesity is a common, complex, and often persistent chronic disease associated with serious health and social consequences.

Obesity prevalence increases with increasing age. The COVID pandemic has significantly affected the lives and routines of children and adolescents. In 1 analysis, the pandemic period was associated with a doubling in the rate of BMI increase compared with the prepandemic period.

Disparities exist among children and youth with obesity, including, but not limited to, lower level of parental education, lower income, less access to healthier food options and safe and affordable physical activity opportunities, and higher incidence of ACEs. Disparities also exist in obesity prevalence across ethnic and racial groups.

In to , non-Hispanic Black children and Mexican American youth 6 to 11 years of age had a higher prevalence of obesity compared with non-Hispanic white children Among children 2 to 5 years of age from lower-income families enrolled in the Special Supplemental Nutrition Program for Women, Infants, and Children program, recent analyses indicate a modest but significant decline in obesity prevalence from In addition, children and youth with special health care needs CYSHCN have a higher prevalence of obesity and lower levels of physical activity compared with children having typical growth and development.

Children with obesity commonly become adolescents and adults with obesity; severe obesity during adolescence increases the risk for severe obesity during young adulthood.

Obesity puts children and adolescents at risk for serious short- and long-term adverse health outcomes later in life, including cardiovascular disease, including HTN; dyslipidemia; insulin resistance; T2DM; and nonalcoholic fatty liver disease NAFLD. In addition to physical and metabolic consequences, obesity in childhood and adolescence is associated with poor psychological and emotional health, increased stress, depressive symptoms, and low self-esteem.

Obesity in childhood and adolescence is associated with health care utilization and costs. For example, the most common primary conditions that cooccur with a secondary diagnosis of obesity and may increase costs and utilization include pregnancy, mood disorders, asthma, and diabetes.

Tracking obesity across the lifespan underscores the importance of primary and secondary prevention and treatment efforts early in life. These efforts include evaluating for obesity using BMI; identifying children at high risk and adolescents; providing or referring to evidence-based obesity treatments for children, youth, and their families; and addressing SDoHs.

Although KAS 1 was not explicitly studied and referenced by the TR, most of the TR studies implicitly included measurement of height and weight and calculation and plotting of BMI as part of the study procedures. Thus, the concept of appropriate measurement, calculation, charting, and tracking is implicit in research-based evidence included in the TR eg, references , , , The gold standard measurement of body composition—dual-energy x-ray absorptiometry—to identify, locate, and quantify body fat, and can be expensive and difficult to implement.

In clinical practice, BMI is frequently used as both a screening and diagnostic tool for detecting excess body fat because it is easy to use and inexpensive. BMI is a validated proxy measure of underlying adiposity that is replicable and can track weight status in children and adolescents.

The CDC BMI growth curves are frequently used to visualize BMI trajectory over time. Furthermore, BMI is often used to evaluate the success or impact of interventions to improve weight status.

For most individuals, BMI is generally well-correlated with direct measures of body fat, including skinfold thickness measurements, bioelectrical impedance, densitometry, and dual-energy x-ray absorptiometry. BMI has limitations, however, including high specificity and low sensitivity for detecting excess adiposity.

The CDC Growth Charts are recommended for clinically tracking BMI patterns among US children and adolescents aged 2 to 18 years; although the CDC Growth Charts can be used for adolescents aged 19 to 21 years, in practice, most pediatricians and other PHCPs transition to adult BMI calculation and categorization for patients older than 18 years.

The CDC Growth Charts were not intended to track growth of children with extremely high BMI values. Because of limited data on children and adolescents above the 97th percentile in the reference population, higher percentile curves could not be generated.

Caution was recommended in extrapolation of percentiles beyond the 97th percentile, as this may generate unusual or unexpected results. This method incorporates data on children and adolescents with obesity from more recent NHANES surveys to better characterize the BMI distribution above the 95th percentile while retaining the CDC Growth Chart BMI distribution below the 95th percentile.

These charts may, however, be limited, for example, by the small sample sizes used in developing them, which may not be representative of all children and youth with trisomy BMI is a useful evaluation measure to clinically identify children with overweight and obesity for appropriate treatment—such as family-based behavioral therapy—which can lead to improvements in BMI and related comorbidities.

Following comprehensive systematic reviews, the USPSTF issued a Grade B recommendation that pediatricians and other PHCPs screen children and adolescents aged 6 years or older annually for obesity—defined by BMI percentile—and offer, or refer children and adolescents to, a comprehensive, intensive, family-based behavioral treatment to improve weight status.

See Evaluation and Treatment sections. All 3 sources recommend annual screening for excess weight using BMI, with the USPSTF beginning at 6 years old and both Bright Futures and this CPG beginning at age 2 years.

Bright Futures also provides implementation tips and guidance for pediatricians and other PHCPs including, for example, providing counseling using motivational interviewing. Bright Futures offers guidance to states by offering a framework for meeting national performance standards under Title V.

Finally, Bright Futures suggests how communities and families can support healthier lifestyles and prevention. The practice of annual BMI measurement at well-child visits is recommended and central to the management and tracking of overweight and obesity in children.

Despite its limitations, BMI is currently the most appropriate clinical tool to screen for excess adiposity and make the clinical diagnosis of overweight or obesity. Thus, the BMI must be communicated to the patient and family, as it guides next steps for comprehensive evaluation and treatment of obesity and related comorbidities.

Weight-related discussions can be uncomfortable for clinicians who want to avoid stigmatizing children because of their shape or size. Avoiding this discussion may, however, cause delays or barriers to patients receiving evidence-based care.

In addition, obesity stigma can result in patient avoidance of health care and disruption of clinician-patient relationships. There is evidence that having conversations about obesity can facilitate effective treatment. Use words that are perceived as neutral by parents, adolescents, and children.

Recognize that discussing BMI with children, adolescents, and families, even when using nonstigmatizing language and preferred terms, can elicit strong emotional responses including sadness or anger.

Obesity is a chronic disease that has a multifactorial etiology. Risk factors for overweight and obesity—many of which are SDoHs—include broader policies and systems factors; institutional or organizational ie, school ; neighborhood and community; and family, socioeconomic, environmental, ecological, genetic, and biological factors Table 1.

Pediatricians and other PHCPs need to be aware of the risk factors for pediatric obesity to provide early anticipatory guidance for obesity prevention, monitor their patients closely, and intervene early when weight trajectory increases.

The CPG authors recommend pediatricians and other pediatric health care providers: perform initial and longitudinal assessment of individual, structural, and contextual risk factors to provide individualized and tailored treatment of the child or adolescent with overweight or obesity.

The larger macroenvironment—including societal attitudes and beliefs, government policies, food industry practices, and the educational and health care systems—can influence obesity risk. Marketing of unhealthy food and beverages directed at children tends to negatively impact their dietary choices and behaviors.

A systematic review and meta-analysis showed that even short exposure to unhealthy food and beverage marketing targeted to children resulted in in increased dietary intake and behavior during and after the exposure. Currently, marketing to children targets highly palatable relatively inexpensive energy-dense foods and beverages.

Underresourced communities are settings in which obesity risk factors can predominate over health-promoting factors. Children and families in these settings may be unable to access fresh fruits and vegetables and safe physical activity spaces and may suffer from food insecurity.

Understanding these contextual factors that impact each child and family is crucial in being able to provide compassionate and effective obesity treatment. Obesity has been shown to disproportionately affect children and adolescents who have low SES.

A longitudinal analysis of predominantly non-Hispanic white children in the United States found that low SES before 2 years of age was associated with higher obesity risk by adolescence in both boys and girls; this analysis also indicated that the effect of early poverty endures later in life.

In addition, poverty may limit access to healthy foods and opportunities for physical activity. For decades, researchers have believed that despite poverty and other negative SES factors, recently arrived immigrants are healthier than their US-born counterparts.

Recent studies, however, have examined large datasets in novel ways and now call this idea into question when it comes to children in families that have immigrated. As families who have immigrated try to adjust to a new culture, they may adopt Americanized foodways, which are high in fat, sugar, and salt.

Patterns of childhood overweight and obesity among families that have immigrated vary substantially by both ethnicity and generational status. Immigrants to the United States generally originate from countries that have a lower prevalence of obesity, but as families acculturate to US eating and activity patterns, rates of obesity may increase.

Several studies have indicated different patterns of developing obesity in Mexican-origin populations among adults and children. Obesity among adults of Mexican origin in the United States has been associated with longer stays in the United States and with being born in the United States versus Mexico, which are 2 proxies for acculturation.

In addition, in some cultures, larger body sizes may be preferred as an indication of health and wealth. For this and many other reasons, it is vital to ensure that children and families who have immigrated and who are native-born have access to culturally competent health care.

The literature positing an association between food insecurity and overweight and obesity in children has been inconsistent when looking at general child populations. Children living in households with food insecurity have been found, however, to have higher BMI z-scores and waist circumference measurement and a greater likelihood of having overweight or obesity.

Food insecurity is highly associated with poverty, and the cost of fruits and vegetables and fast food have been found to influence consumption in low-income families , and to be positively related to overweight in children. The Toolkit assists pediatricians and other PHCPs to: 1 better identify children living in households struggling with food insecurity; 2 sensitively address the topic; 3 connect patients and their families to federal nutrition programs and community resources; and 4 advocate for greater food security and improved overall health of children and their families.

Environmental factors play an important role in obesity prevalence. Children spend most of their time in school. Systematic reviews have shown an association between fast food outlets and convenience stores located near schools and obesity in children. Although the association was seen for all grade levels, the effect was larger in younger grades.

Although some studies have shown that a 1. Some of the differences were attributed to variations in assessment measures and lack of adjustment for confounding variables. Hence, it is not only the presence of supermarkets that is important, but also other factors that may impact dietary choices—such as the type of foods stocked, pricing, etc.

Some, but not all, studies have reported a positive association between neighborhood poverty and childhood and adolescent obesity. It has been suggested that lack of access to fresh fruits and vegetables may be a risk factor for childhood and adolescent obesity, as it may lead to an increased reliance on, and consumption of, unhealthy foods.

The data for this association have been inconsistent, however. A recent systematic review showed that, although there was a negative association between access to fresh fruits and vegetables and healthy eating behavior, the association between access to fresh fruits and vegetables and overweight and obesity was inconclusive.

Fast-food restaurants generally serve relatively low-priced and calorie-rich fast foods with high levels of saturated fat, simple carbohydrates, sugar, and sodium. Because of their easy availability, taste, and marketing strategies, fast foods tend to be popular with children and adolescents.

Fast-food consumption has been associated with weight gain. Greater exposure to green space has been shown to be associated with higher levels of physical activity and lower risk of obesity. A recent systematic review of the literature on the influence of the built environment and childhood obesity found significant association between childhood obesity and traffic air pollution and indicators of walkability which included intersection density and presence and amount of park area in the neighborhood.

A study of low-income preschool children in New York City reported an association of lower obesity risk in neighborhoods with trees alongside the streets and a positive association between obesity and higher homicide rates in the neighborhood. Exposure to environmental hazards during the prenatal period, infancy, and childhood can have impacts on the health and well-being of children.

Endocrine-disrupting chemicals EDC can cross the placental barrier and affect the fetus. In the postnatal and infancy period exposure may occur through breastfeeding, inhalation, ingestion, or absorption through the skin.

Children get exposed to chemicals that are used in household products including cleaning agents, food packaging, pesticides, fabrics, upholstery, etc. Leaching of chemical products eg, bisphenols, phthalates, parabens, and other EDCs has been reported in baby feeding bottles, clothing, diaper creams, etc.

Exposure to EDCs during early childhood can affect programming of several systems, including endocrine and metabolic systems, which may affect BMI, cardiovascular, and metabolic outcomes later in life.

Four types of parent feeding styles have been described: authoritative responsive and warm with high expectations ; authoritarian not responsive but with high expectations ; permissive or indulgent responsive and warm but lenient with few rules ; and negligent not responsive with few rules.

The 4 parenting styles discussed were initially defined by Baumrind and later expanded by Maccoby and Martin Children from authoritative parenting homes have been shown to eat more healthy foods, be more physically active, and have healthier BMI, compared with children raised in homes with authoritarian, permissive or indulgent, or negligent parenting styles.

A large cross-sectional study showed that, among preschool- and school-aged children, authoritarian or negligent parenting is associated with a higher risk of obesity, whereas authoritative parenting was associated with healthy BMI. A systematic review of associations between the organization of the family home environment and childhood obesity found that greater organization of the home environment, which included practices such as having family routines and setting limits, was inversely associated with obesity.

Most but not all of the 32 studies included in the review controlled for sociodemographic factors. A comprehensive review of this research reported that children who serve or are served larger portions of commonly liked energy-dense foods typically consume larger amounts but cautioned that long-term studies of the effects of larger portions over time on a number of variables, including body weight, are lacking.

A recent systematic review of body fat and consumption of ultra-processed foods defined as snacks, fast foods, junk foods, and convenience foods in children and adolescents found a positive association but noted that longer-term studies examining the association of these foods and obesity are needed.

Eating outside of the home has been shown to be associated with higher energy intake in both children and adults. In a systematic review of pediatric and adult studies, eating at fast-food establishments was associated with much higher weight gain, compared with eating at other types of restaurants.

Take-away food has also been associated with high BMI. Conversely, 2 meta-analyses found that increased frequency of eating family meals was associated with lower risk of childhood obesity.

Some, but not all, studies report an association between screen time duration, childhood adiposity, — and adult BMI. There is evidence to support the association between screen time and consumption of unhealthy diet and high energy intake.

A systematic review examining food choice and intake showed that food included in entertainment media affects eating behaviors of children. The association between sedentary behavior and adiposity has been shown to range from small to inconsistent. Teasing out the effects of sedentary behavior alone in treatment studies may be challenging, as this is often confounded with other behaviors such as physical activity, screen time, or increased intake of unhealthy foods.

Short sleep duration is associated with higher risk of obesity in children. Sleep restriction may be associated with increased calorie consumption. It is unclear whether the inverse association between sleep and adiposity is causal or a consequence of hormonal or metabolic disturbance.

Children exposed to environmental tobacco smoke ETS have been found to have higher BMI compared with their nonexposed counterparts, according to a systematic review of ETS exposure and growth outcomes in children up to 8 years of age.

A meta-analysis showed that prenatal psychological stress was associated with higher risk of childhood and adolescent obesity. Psychosocial and emotional issues may lead to weight gain through maladaptive coping mechanisms, including eating in the absence of hunger to suppress negative emotions, appetite up-regulation, low-grade inflammation, decrease in physical activity, increase in sedentary behavior, and sleep disturbance.

A number of studies have documented an association between ACEs and the development of overweight and obesity. A US study found that cumulative ACEs doubled the risk of children having overweight or obesity, compared with their counterparts with no history of ACEs.

Polygenetic causes of obesity are by far the most common, and single gene defects are rarer causes of obesity. The phenotypic effect manifests only in the presence of, or in combination with, other predisposing factors. Children with genetic causes of obesity may present with characteristic clinical features that have historically included findings such as short stature, dysmorphic features, developmental delay, skeletal defects, deafness, retinal changes, or intellectual disability.

It is important to note that more recently discovered genetic disorders associated with obesity are not necessarily characterized by these findings in childhood; for instance, short stature is not a hallmark of leptin deficiency in children.

Table 2 lists selected monogenetic causes and syndromes associated with obesity. Adapted from Pediatric Obesity-Assessment, Treatment, and Prevention: An Endocrine Society Clinical Practice Guideline.

Early onset of severe obesity and the presence of hyperphagia are the 2 clinical characteristics that distinguish genetic disorders of obesity. Epigenetic factors can result in alterations in gene expression without alteration in genetic code. These epigenetic factors may modify the interaction of environmental and individual factors in promoting weight gain.

The mechanisms by which the fetal environment predisposes to the development of obesity are complex and poorly understood. Preterm infants have a greater likelihood of developing childhood obesity. Parental weight is a strong predictor of pediatric obesity. Children are at greatest risk of developing obesity as an adult if at least 1 of their parents has obesity.

Maternal BMI is a stronger predictor of childhood and adolescent obesity, compared with paternal obesity. Paternal obesity has been associated with childhood and adolescent obesity and has an additive effect to maternal obesity.

Prepregnancy adiposity and weight gain during pregnancy are associated with neonatal, infancy, and childhood adiposity. Excess maternal adiposity has been suggested to affect fetal metabolic programing and make the offspring more vulnerable to the obesogenic environment and increase the risk of obesity.

The exact mechanism by which maternal obesity predisposes to adverse outcomes in the offspring is unclear. It has been suggested that the pathways that are affected control the central regulation of appetite and insulin sensitivity and cardiovascular regulation.

Infants and children of mothers with gestational diabetes mellitus GDM have higher fat mass and BMI than their counterparts whose mothers did not have GDM. Although the exact mechanisms of the effect of GDM are not fully understood, it has been postulated that the effect may be mediated through insulin.

Pregnant women with GDM have higher insulin resistance compared with pregnant women without GDM. Exposure to ETS has been shown to increase the prevalence of childhood and adolescent obesity. Children exposed to smoking in utero have a dose-dependent increased risk of developing overweight and obesity.

As with the prenatal environment, the postnatal environment is important to the later development of overweight and obesity. In addition to epigenetic mechanisms, behavioral habits begin to get set at an early age. Acceptance of foods, availability of high calorie foods, establishment of the microbiome, and early eating habits are only a few of the proposed mechanisms for postnatal factors to influence later weight status.

Several studies have shown a U-shaped or J-shaped distribution between birth weight and adult BMI. Some, but not all, studies have reported decreased risk of childhood and adolescent obesity in breastfed infants.

Breastfeeding has been found to be inversely associated with overweight risk in the first year of life, independent of maternal BMI and SES. Breastfeeding cessation before 6 months was associated with an increased risk of rapid weight gain and overweight by 12 months of age, compared with exclusive breastfeeding.

A systematic review of feeding practices associated with rapid infant weight gain found that certain practices such as overfeeding, inappropriately concentrating formula, placing infants in bed with a bottle, or adding cereal to a bottle may lead to rapid infant weight gain. In resource-abundant countries, rapid weight gain in infancy and during the first 2 years of life is associated with higher risk of obesity both in later childhood and in adulthood.

Therefore, rapid weight gain in infancy and early childhood can be viewed both as a risk factor for later excess weight gain and also as a signal, as mentioned previously, for pediatricians and other PHCPs to look for other underlying risk factors and causes for excess weight gain.

For instance, early introduction at younger than 4 months of age of complementary foods has been found to increase the risk of childhood obesity in several systematic reviews.

Various medical conditions that present in childhood and adolescence are associated with the development and progression of overweight and obesity. Similarly, certain behaviors established in childhood and adolescence can increase the risk of later development of overweight and obesity.

These disorders can be associated with endogenous or exogenous glucocorticoid excess eg, Cushing syndrome, use of corticosteroid medications. Short stature or growth failure and abnormally high BMI may result from pseudohypoparathyroidism type 1a, growth hormone deficiency, or hypothyroidism.

In addition to factors experienced by children without disabilities, factors that affect children with disabilities that have been implicated in their greater obesity risk are: more difficulty breastfeeding, disrupted appetite regulation, weight-gain promoting medications, , food selectivity and sensitivity issues, behavioral disorders, physical activity limitations, and use of food rewards.

Furthermore, it is important to consider that children with disabilities are at a disadvantage when it comes to obesity treatment strategies that are tailored to their needs. For example, most community or school weight management, nutrition or physical activity interventions are not readily adapted for children with disabilities.

Therefore, many children with disabilities do not have the support or strategies that they need to address excess weight.

Finally, children may face bullying or stigmatization and bias in school. They may also receive unhealthy incentives as rewards from caregivers increasing their risk for obesity. These systemic trends and biases make providing adequate care for children with disabilities extremely difficult.

Children and youth with autism spectrum disorder ASD have a higher risk of developing overweight or obesity. In the United States, children and adolescents 2 to 18 years of age with ASD have a Hence, the variable of race could be reflective of a negative SDoH.

Several etiological factors have been postulated to contribute to the association between ASD and obesity, including: genetic variants eg, 16p Several studies report increased rates of obesity of children with myelomeningocele, — with children having more severe disease tending to have higher BMIs.

Risk factors for obesity in this population include limited ambulation, sedentary lifestyle, decreased lean body mass, and reduced resting energy expenditure. This association is not affected by gender or by study setting, country, or quality.

Causality between ADHD and obesity could not be inferred from this meta-analysis, because the studies were cross-sectional; however, some prospective studies have shown that ADHD precedes the diagnosis of obesity.

Some of the known symptoms of ADHD may contribute to weight gain. For example, binge eating, which is a manifestation of impulsivity in individuals with ADHD, may result in increased energy intake. Inattentiveness, another symptom of ADHD, may lead to lack of planning, or of following through on a plan, resulting in missed meals or the consumption of unhealthy meals and snacks.

Dopamine plays an important role in some of the addictive behaviors of ADHD and obesity. Functional MRI studies have identified shared neuropsychiatric circuits that are associated with reward, response inhibition, and emotional regulation in obesity, ADHD, and abnormal eating behavior.

Parent feeding style, as discussed, has been shown to be of importance. Systematic review and meta-analysis of adult data showed a positive association between eating quickly and higher BMI, and in longitudinal studies, faster eating rate was associated with excess weight gain.

In addition to more rapid eating pace, these traits include eating in the absence of hunger, high enjoyment of food, low responsiveness to satiety, and low level of restrained eating. Medications within many categories have been associated with weight gain. The magnitude of risk associated with medication use is not fully known; therefore, there is an urgent need for more research in this area as well as mediating strategies.

Medications implicated include glucocorticoids, sulfonylureas, insulin, thiazolidinediones, antipsychotics, tricyclic antidepressants, and antiepileptic drugs. A recent review discusses the more commonly prescribed medications in children and adolescents with obesity and comorbidities, and offers suggestions on alternative therapeutic agents Table 3.

Selected Examples of Commonly Prescribed Medications and Weight Gain in Pediatric Practice This is not an exhaustive list; it is included as an example of medications that may result in weight gain and possible alternatives.

Children with obesity are more likely to have anxiety and depressive symptoms compared with their peers of healthy weight. It is not clear whether obesity is a risk factor for these symptoms.

Limitations of some of the studies included small samples; self-reported data on anthropometry; assessment of symptoms based on self-administered questionnaires; and not controlling for potential confounders, such as family history, neuropsychiatric disorders, and SES.

A more recent study showed that obesity was a risk factor for anxiety and depression among children and adolescent after adjusting for SES, neuropsychiatric disorders, and family history of anxiety or depression. The association between obesity and depression and anxiety may be attributable to interactions and shared pathophysiological mechanisms between these conditions.

Obesity is associated with subclinical inflammation and oxidative stress, which have been shown to be important etiological factors for depression, and this has been suggested as possible common link between obesity and depression.

This evaluation is an important part of COT see COT section in the Treatment section. As with all chronic diseases, a complete history, review of systems RoS , and physical examination are important for treatment.

Specific elements of both history and physical relating to obesity are of special importance. The early and accurate classification of overweight and obesity and identification of obesity-related comorbidities is fundamental to the provision of timely and appropriate treatment see the Comorbidities section, below.

The routine classification of weight status allows for early recognition of abnormal weight gain. This is particularly important because patients—including children and adolescents—often do not perceive overweight and obesity as a health problem.

Patients and caregivers identify pediatricians and other PHCPs as trusted and preferred sources of information about weight status, starting with discussions of feeding practice in infancy and continuing with evaluation of healthy nutrition and activity into adulthood.

Pediatricians and other PHCPs are also uniquely qualified to evaluate patients for overweight, obesity, and related comorbidities.

Routine well-child checks WCCs in the medical home are an opportune time for the evaluation of a child or adolescent with overweight and obesity, but this can occur during problem-focused visits as well. When the discussion of weight status is normalized and nonstigmatizing, the family and provider can exit a WCC or other visit with a clear and practical plan to improve health and quality of life.

Successfully and sensitively treating overweight and obesity can be highly rewarding for both the family and the pediatrician or other pediatric health care provider , because families suffering from overweight and obesity often have experienced previous shaming or negative experiences with treatment.

Overt or subtle and unintended bias in health care leads to adverse health, behavioral, and psychological outcomes. It is important, although challenging, for pediatricians and other PHCPs to communicate support and alliance with children, adolescents, and parents as they diagnose and guide obesity treatment.

In the AAP statement on obesity bias, steps to provide supportive and nonbiased behavior include recognition of the complex genetic and environmental influences on obesity.

Both a complete medical history and physical examination are necessary to evaluate any patient with a chronic disease. Obesity is no exception and, like other chronic diseases, requires comprehensive evaluation in certain areas of both the history and physical examination, which may require additional time to that which is allocated in a routine visit.

The medical history includes the chief complaint, history of the present illness, and family history. The chief complaint is notable for determining whether overweight and obesity is a concern for the patient and family. The history of the present illness provides a more comprehensive picture of the trajectory of overweight and obesity.

These prenatal and postnatal causes are described in detail in the Risk Factors section. Information about the onset of excess weight gain and consistency of weight status over time including a review of the growth curve and previous weight control attempts can provide an understanding of what weight status represents for the patient.

It can also offer clues as to root causes, necessary diagnostic evaluation, and potential therapeutic targets. The family history focuses on obesity-related comorbidities and potential genetic causes of obesity in addition to other family health problems.

A family history of obesity and obesity- related comorbidities may influence both evaluation and treatment. Although shared environment, SDoHs, and stress can contribute to obesity within the same family, a family history of obesity can also provide a clue to genetic susceptibility to obesity—especially if the family history includes severe obesity resulting in metabolic and bariatric surgery or severe obesity present in multiple family members and generations.

The medication history should be complete and should include medications associated with weight gain, such as antipsychotics, especially atypical antipsychotics; antidepressants including selective serotonin reuptake inhibitors; steroids; anticonvulsants; antihypertensives; birth control agents, including injected forms; and medications used in diabetes mellitus.

Table 4 summarizes the RoS and provides a valuable framework for investigating a variety of obesity-related conditions. Adapted from Krebs et al. A thorough social history is helpful in the evaluation of the child or adolescent with overweight and obesity. An understanding of family living arrangement will identify resources and barriers that are unique to the patient and their family.

Factors such as eating routines and schedules; eating at multiple households; and eating environments, such as family meals, eating at a table, eating with or without screens, are all important elements in assessing contributors to and potential treatment targets for excess weight gain.

How is food used in celebrations?

In a purely rational approach, the numbers and calculations involved work the same way regardless of whether the situation is one involving potential gain or potential loss. Prospect theory is a description of how people made actual decisions in experiments.

It is in the hands of decision makers to determine whether these tendencies are justifiable or if they should be overridden by a rational approach. Another theory that suggests a modification of pure rationality is known as bounded rationality. This concept revolves on a recognition that human knowledge and capabilities are limited and imperfect.

Three specific limitations are generally enumerated:. In light of these limitations, the theory of bounded rationality suggests that decision makers must be willing to adapt their rational approach. For example, they must determine how much information is reasonable to pursue during the information-gathering stage; they cannot reasonably expect to gather and analyze all possible information.

Similarly, decision makers must content themselves with a consideration of only a certain number of alternative solutions to the decision. Also, decision makers being far from perfect in their abilities to evaluate potential solutions must inevitably affect their approach.

They must be aware of the possibility that their analysis is wrong and be willing to accept evidence to this effect. Uncertainty and inaccuracy often arise in efforts to predict the future. What are decision makers to do when they are uncertain about potential results from their actions?

This makes a strictly rational approach difficult and less reliable. One of the approaches that might stem from a recognition of bounded rationality is the use of heuristics.

These are analytical and decision-making tools that help simplify the analysis process by relying on tried and tested rules of thumb. A heuristic simplifies a complex situation and allows the decision maker to focus only on the most important pieces of information.

For example, a business might use their proven experiences and that of many other companies to conclude that a new product line requires a certain amount of time to gain market share and become profitable. Though there are many complex factors involved in market analysis, the business might use this proven rule to guide its decision making.

When a proposed decision contradicts this rule, the company might discard it even if a complex and seemingly rational analysis might seem to support it. Of course, there are exceptions to most rules, and the use of heuristics might prevent a company from following courses of action that would be beneficial.

Likewise, heuristics that were once reliable rules might become obsolete because of changing markets and environments. Nonetheless, most analysts recognize heuristics as useful tools when used properly. Robust decisions revolve around the inability to predict the future with certainty.

It supposes that a number of situations are all possible and provides a solution pathway that will be successful if any of those situations should arise. This pathway could potentially be a single solution that works in any of the likely future scenarios, or it might provide separate responses to be enacted depending on how the future uncertainties unfold.

Answer the question s below to see how well you understand the topics covered in the previous section. This allows for more control over the shape of the curve without unduly raising the number of control points.

In particular, it adds conic sections like circles and ellipses to the set of curves that can be represented exactly. The term rational in NURBS refers to these weights.

The control points can have any dimensionality. One-dimensional points just define a scalar function of the parameter. These are typically used in image processing programs to tune the brightness and color curves. Three-dimensional control points are used abundantly in 3D modeling, where they are used in the everyday meaning of the word 'point', a location in 3D space.

Multi-dimensional points might be used to control sets of time-driven values, e. the different positional and rotational settings of a robot arm.

NURBS surfaces are just an application of this. Each control 'point' is actually a full vector of control points, defining a curve. These curves share their degree and the number of control points, and span one dimension of the parameter space.

By interpolating these control vectors over the other dimension of the parameter space, a continuous set of curves is obtained, defining the surface.

The knot vector is a sequence of parameter values that determines where and how the control points affect the NURBS curve. The number of knots is always equal to the number of control points plus curve degree plus one i. number of control points plus curve order. The knot vector divides the parametric space in the intervals mentioned before, usually referred to as knot spans.

Each time the parameter value enters a new knot span, a new control point becomes active, while an old control point is discarded. It follows that the values in the knot vector should be in nondecreasing order, so 0, 0, 1, 2, 3, 3 is valid while 0, 0, 2, 1, 3, 3 is not.

Consecutive knots can have the same value. This then defines a knot span of zero length, which implies that two control points are activated at the same time and of course two control points become deactivated.

This has impact on continuity of the resulting curve or its higher derivatives; for instance, it allows the creation of corners in an otherwise smooth NURBS curve. A number of coinciding knots is sometimes referred to as a knot with a certain multiplicity.

Knots with multiplicity two or three are known as double or triple knots. The multiplicity of a knot is limited to the degree of the curve; since a higher multiplicity would split the curve into disjoint parts and it would leave control points unused.

For first-degree NURBS, each knot is paired with a control point. The knot vector usually starts with a knot that has multiplicity equal to the order. This makes sense, since this activates the control points that have influence on the first knot span.

Similarly, the knot vector usually ends with a knot of that multiplicity. Curves with such knot vectors start and end in a control point. The values of the knots control the mapping between the input parameter and the corresponding NURBS value. For example, if a NURBS describes a path through space over time, the knots control the time that the function proceeds past the control points.

For the purposes of representing shapes, however, only the ratios of the difference between the knot values matter; in that case, the knot vectors 0, 0, 1, 2, 3, 3 and 0, 0, 2, 4, 6, 6 produce the same curve. The positions of the knot values influences the mapping of parameter space to curve space.

Rendering a NURBS curve is usually done by stepping with a fixed stride through the parameter range. By changing the knot span lengths, more sample points can be used in regions where the curvature is high.

Another use is in situations where the parameter value has some physical significance, for instance if the parameter is time and the curve describes the motion of a robot arm. The knot span lengths then translate into velocity and acceleration, which are essential to get right to prevent damage to the robot arm or its environment.

This flexibility in the mapping is what the phrase non uniform in NURBS refers to. Necessary only for internal calculations, knots are usually not helpful to the users of modeling software. Therefore, many modeling applications do not make the knots editable or even visible.

It's usually possible to establish reasonable knot vectors by looking at the variation in the control points. More recent versions of NURBS software e. They are one on the corresponding knot span and zero everywhere else.

Higher order basis functions are non-zero over corresponding more knot spans and have correspondingly higher degree. This makes the computation of the basis functions numerically stable. Again by induction, it can be proved that the sum of the basis functions for a particular value of the parameter is unity.

This is known as the partition of unity property of the basis functions. The figures show the linear and the quadratic basis functions for the knots { One knot span is considerably shorter than the others. On that knot span, the peak in the quadratic basis function is more distinct, reaching almost one.

Conversely, the adjoining basis functions fall to zero more quickly. In the geometrical interpretation, this means that the curve approaches the corresponding control point closely. In case of a double knot, the length of the knot span becomes zero and the peak reaches one exactly.

The basis function is no longer differentiable at that point. The curve will have a sharp corner if the neighbour control points are not collinear. The denominator is a normalizing factor that evaluates to one if all weights are one.

This can be seen from the partition of unity property of the basis functions. It is customary to write this as. A number of transformations can be applied to a NURBS object. In the process a number of control points change position and a knot is inserted in the knot vector.

This is not an exhaustive list; it is included as an example of medications that may result in weight gain and possible alternatives.

Children with obesity are more likely to have anxiety and depressive symptoms compared with their peers of healthy weight.

It is not clear whether obesity is a risk factor for these symptoms. Limitations of some of the studies included small samples; self-reported data on anthropometry; assessment of symptoms based on self-administered questionnaires; and not controlling for potential confounders, such as family history, neuropsychiatric disorders, and SES.

A more recent study showed that obesity was a risk factor for anxiety and depression among children and adolescent after adjusting for SES, neuropsychiatric disorders, and family history of anxiety or depression. The association between obesity and depression and anxiety may be attributable to interactions and shared pathophysiological mechanisms between these conditions.

Obesity is associated with subclinical inflammation and oxidative stress, which have been shown to be important etiological factors for depression, and this has been suggested as possible common link between obesity and depression.

This evaluation is an important part of COT see COT section in the Treatment section. As with all chronic diseases, a complete history, review of systems RoS , and physical examination are important for treatment. Specific elements of both history and physical relating to obesity are of special importance.

The early and accurate classification of overweight and obesity and identification of obesity-related comorbidities is fundamental to the provision of timely and appropriate treatment see the Comorbidities section, below.

The routine classification of weight status allows for early recognition of abnormal weight gain. This is particularly important because patients—including children and adolescents—often do not perceive overweight and obesity as a health problem.

Patients and caregivers identify pediatricians and other PHCPs as trusted and preferred sources of information about weight status, starting with discussions of feeding practice in infancy and continuing with evaluation of healthy nutrition and activity into adulthood.

Pediatricians and other PHCPs are also uniquely qualified to evaluate patients for overweight, obesity, and related comorbidities. Routine well-child checks WCCs in the medical home are an opportune time for the evaluation of a child or adolescent with overweight and obesity, but this can occur during problem-focused visits as well.

When the discussion of weight status is normalized and nonstigmatizing, the family and provider can exit a WCC or other visit with a clear and practical plan to improve health and quality of life.

Successfully and sensitively treating overweight and obesity can be highly rewarding for both the family and the pediatrician or other pediatric health care provider , because families suffering from overweight and obesity often have experienced previous shaming or negative experiences with treatment.

Overt or subtle and unintended bias in health care leads to adverse health, behavioral, and psychological outcomes. It is important, although challenging, for pediatricians and other PHCPs to communicate support and alliance with children, adolescents, and parents as they diagnose and guide obesity treatment.

In the AAP statement on obesity bias, steps to provide supportive and nonbiased behavior include recognition of the complex genetic and environmental influences on obesity. Both a complete medical history and physical examination are necessary to evaluate any patient with a chronic disease. Obesity is no exception and, like other chronic diseases, requires comprehensive evaluation in certain areas of both the history and physical examination, which may require additional time to that which is allocated in a routine visit.

The medical history includes the chief complaint, history of the present illness, and family history. The chief complaint is notable for determining whether overweight and obesity is a concern for the patient and family. The history of the present illness provides a more comprehensive picture of the trajectory of overweight and obesity.

These prenatal and postnatal causes are described in detail in the Risk Factors section. Information about the onset of excess weight gain and consistency of weight status over time including a review of the growth curve and previous weight control attempts can provide an understanding of what weight status represents for the patient.

It can also offer clues as to root causes, necessary diagnostic evaluation, and potential therapeutic targets. The family history focuses on obesity-related comorbidities and potential genetic causes of obesity in addition to other family health problems.

A family history of obesity and obesity- related comorbidities may influence both evaluation and treatment. Although shared environment, SDoHs, and stress can contribute to obesity within the same family, a family history of obesity can also provide a clue to genetic susceptibility to obesity—especially if the family history includes severe obesity resulting in metabolic and bariatric surgery or severe obesity present in multiple family members and generations.

The medication history should be complete and should include medications associated with weight gain, such as antipsychotics, especially atypical antipsychotics; antidepressants including selective serotonin reuptake inhibitors; steroids; anticonvulsants; antihypertensives; birth control agents, including injected forms; and medications used in diabetes mellitus.

Table 4 summarizes the RoS and provides a valuable framework for investigating a variety of obesity-related conditions. Adapted from Krebs et al. A thorough social history is helpful in the evaluation of the child or adolescent with overweight and obesity.

An understanding of family living arrangement will identify resources and barriers that are unique to the patient and their family. Factors such as eating routines and schedules; eating at multiple households; and eating environments, such as family meals, eating at a table, eating with or without screens, are all important elements in assessing contributors to and potential treatment targets for excess weight gain.

How is food used in celebrations? Is there pressure for the child to eat? Because overweight and obesity tends to cluster in social groups as well as families, discussions of neighborhood, school, and friend groups can guide pediatricians, other PHCPs, and families to productive areas for treatment.

Social history can heighten an awareness of, and provide insight into, patients who are most exposed to negative SDoHs. Given that inequities exist in obesity risk factors, an SDoH evaluation is important to increase awareness and provide insight in identifying patients who are more vulnerable to obesity.

Standardized tools for use in primary care exist and include the Safe Environment for Every Kid model and the Accountable Health Communities Health-Related Social Needs Screening Tool. Being alert to and recognizing SDoHs are the initial steps in trauma-informed care TIC. ACEs can have a profound impact on health over a lifetime and, as noted, include stressors as diverse as harsh parenting, food insecurity, and parental incarceration.

TIC is characterized by screening and recognition of these ACEs, responding to them, and working to prevent reexposure to trauma. Initial recognition of the importance of ACEs on health occurred in the field of adult obesity treatment. The importance of TIC and addressing ACEs in pediatric obesity management is ongoing.

Electronic health records, waiting room kiosks, and emailed previsit surveys can all be used to help gather this information. There are many additional tools to assess nutrition and physical activity. These include: hour recalls, electronic and written food diaries, telephone- and text-prompted diaries, and various smartphone applications that track food intake.

Pedometers and other wearable activity monitors can assist with physical activity assessment. Pediatricians and other PHCPs may find some of these applications and tools at their disposal. Cultural dietary habits, limited English proficiency, and limited literacy levels may influence the accuracy of the tool used.

In comparison with adults, physical activity assessment is challenging, because children and adolescents are less reliable in performing recall of performed activity. Sensitivity to cultural, economic, and literacy barriers is necessary with the nutrition history and physical activity history , as with other assessments.

Furthermore, the presence of eating disorders, obsessive-compulsive disorder, and other mental health conditions may preclude the use of certain tools that require intensive tracking.

Because rates of behavioral health illnesses are greater in patients with obesity than other patients, it is important for pediatricians and other PHCPs to evaluate the emotional health of children with overweight and obesity. gov to the child and parent as well as local counseling referral.

Various in-office tools can be used to address behavioral health disorders seen in greater prevalence in patients with obesity. These practices include skipping meals, using diet pills or laxatives, and inducing vomiting.

Therefore, it is important for pediatricians and other PHCPs to evaluate the adolescent with overweight or obesity for these and other related behaviors, and to examine the growth chart for evidence of more rapid than expected decline in BMI.

Pediatricians should evaluate patients for disordered eating and unhealthy weight-control behaviors at annual health supervision visits. Pediatricians should evaluate weight, height, and BMI by using age- and sex-appropriate charts, assess menstrual status in girls, and recognize the changes in vital signs that may signal the presence of an eating disorder.

The physical exam also requires focused attention to certain obesity-related findings related to physical evaluation Table 6. These include: Vital signs such as heart rate, pulse, and blood pressure should be taken; blood pressure should be measured accurately with an appropriately sized cuff.

Other important signs: short stature may be a sign of a genetic or endocrinologic cause for overweight and obesity. Flat affect may indicate depression, and anxious mood may indicate anxiety. Attention-seeking may be a signal for underlying distress over overweight and obesity.

Syndromic features may also offer indications of the presence of an underlying genetic cause for obesity. Skin examination should be performed to look for intertrigo and hidradenitis suppurativa associated with excess skin folds as well as acanthosis nigricans associated with insulin resistance.

The combination of purplish abdominal striae, slowed linear growth, cervicodorsal fat accumulation, proximal muscle wasting, full facies, and hypertension should prompt evaluation for Cushing syndrome.

Examination of the head, ears, eyes, nose, and throat should occur to look for papilledema associated with pseudotumor cerebri, tonsillar hypertrophy associated with sleep apnea and goiter associated with thyroid disease.

A cardiopulmonary examination should be performed to look for a spectrum of impairment that can be associated with overweight and obesity. Simple deconditioning may present with tachypnea, dyspnea, or tachycardia. Wheezing may be suggestive of intrinsic or exercise-induced asthma.

Tonsillar hypertrophy may be a sign that increases the likelihood of sleep apnea. In more severe obesity, congestive heart failure may present with basilar rales or other signs of more significant cardiac disease.

Liver size should be assessed by palpation and auscultation. If present, right upper quadrant tenderness should be noted. Genito-urinary examination should be performed to assess pubertal status and genital appearance looking for signs of endocrine or genetic abnormality. Hypogonadism may be present in certain syndromes associated with obesity or be a result of obesity.

Neurologic evaluation may reveal papilledema, as described above, as well as paresthesia. Obesity may also make detection of scoliosis more difficult. Neuromuscular evaluation of obesity, as with the orthopedic evaluation of obesity, includes assessment of bone structure, gait and pain, but also includes assessment for balance, coordination, lower limb muscle strength, flexibility and motor skill proficiency.

Patients with obesity frequently experience impairment in these areas. Such limitations can result in further reduction of ability to engage in physical activity.

Adapted from Table 4 and used with permission by Armstrong et al. et al. This evaluation is important when discussing healthy nutrition and activity with patients who have BMI in the healthy range; it assumes even greater importance with a patient and family who are struggling with overweight, obesity, or severe obesity where health concerns are elevated.

This evaluation of readiness to change is central to deciding how and when to embark on obesity treatment. Readiness to change, perceptions of weight status, health challenges, nutrition habits, and access to physical activity are influenced by familial, cultural, and socioeconomic factors.

For this reason, understanding these factors is beneficial in forging a productive relationship with children and their families. Caregivers should be reminded that the presence of overweight or obesity is NOT an indication of poor parenting.

Based on BMI classification—and augmented by findings in the history, physical examination, and patient readiness to change assessments—laboratory evaluation of the patient represents the next important step in evaluation. This laboratory evaluation and its connection to the delineation of more common comorbid illnesses is described in the Comorbidities section.

Other laboratory evaluations can be performed as clinically indicated. Children and adolescents with obesity have increased prevalence of comorbidities, and a greater risk for obesity in adulthood, morbidity, and premature death. Obesity and related comorbidities should be evaluated concurrently with an obesity-specific history and review of systems, family and social history, physical examination, and laboratory testing.

This evaluation provides pediatricians and other PHCPs with an opportunity to assess for both the etiology and complications of obesity see the Evaluation section. Pediatricians and other PHCPs need to take into consideration patient-specific factors that may increase the risk for comorbidities.

For example, prediabetes and diabetes occur more frequently among children who are 10 years and older, are in early pubertal stages, or have a family history of T2DM. There is compelling evidence that obesity increases the risk for comorbidities and that weight loss interventions can improve comorbidities.

To address when to begin evaluation, what tests to obtain, and frequency of testing, input from other clinical practice guidelines was also considered. Consensus recommendations are included to cover the breadth of relevant comorbidities associated with pediatric overweight and obesity and to provide context for implementation.

Each KAS or consensus recommendation is drawn from the technical reports, an extensive review of the literature, and clinical guidelines or position statements from premier organizations or professional societies in the field.

The inclusion criteria for the guidelines and position statements are in Table 7. When there was more than 1 guideline from the same organization or professional society, the most recent guideline was given precedence.

Other considerations for inclusion were guidelines supported by a technical report or endorsed by the AAP. The following section is divided into 3 sections: Overall KASs for Laboratory Evaluation of Obesity-Related Comorbidities for children with overweight and obesity KASs 3 — 3.

Concurrent Treatment of Obesity and Obesity-Related Comorbidities KAS 4 ; and. Specific Recommendations for Evaluation for Common Comorbidities KASs 5 — 8 and Guidelines for Other Comorbidities. Per KAS 3 and 3. Refer to evidence tables for KAS 3 and 3.

Pediatricians and other PHCPs should evaluate for NAFLD by obtaining an alanine transaminase ALT test. Recommendations for reevaluation and initial management of common comorbidities are in Appendix 3. The AAP Expert Committee on Child Obesity recommended laboratory evaluation for children with obesity for dyslipidemia, prediabetes, and NAFLD starting at 10 years by obtaining a fasting lipid panel, fasting glucose, alanine transaminase, and aspartate transaminase levels every 2 years.

To encourage a pragmatic and efficient evaluation strategy, KAS 3 and 3. The expectation is that pediatricians and other PHCPs will find it easier to adhere to recommendations when all tests are obtained at the same time. They may order fasting laboratory tests for the evaluation, because a fasting lipid panel is still the recommended test to evaluate for dyslipidemia for children and adolescents with overweight and obesity see the dyslipidemia section, below, for additional information.

For children 2 to 9 years of age with obesity, evaluation for lipid abnormalities may be considered KAS 3. This recommendation aligns with the National Heart Lung Blood Institute NHLBI Expert Panel on Integrated Guidelines for Cardiovascular Health and Risk Reduction in Children and Adolescents.

As the risk profile for NAFLD and diabetes mellitus in children younger than 10 years is lower especially in the absence of severe obesity , obtaining tests for abnormal glucose metabolism or liver function is not universally recommended for this population.

Detailed and specific recommendations are provided in the following sections on dyslipidemia, prediabetes and diabetes mellitus, and NAFLD. For children 10 years and older with overweight, evaluating for lipid abnormalities is recommended in the absence of additional risk factors KAS 3.

Adolescents with severe obesity—who have comparable BMI and metabolic profiles as adults—are more likely to present with advanced liver damage and severe systemic inflammation, suggesting that pediatric NAFLD may be more aggressive.

Concerns about overtesting and cost are warranted but are balanced by the significant impact of obesity and comorbidities on morbidity and mortality. Finally, although obesity prevalence rates continue to rise, the rate of evaluating for obesity or comorbidities in practice is low—suggesting that any concerns about overtesting are likely to be more theoretical than real.

See Appendix 3 for information on frequency of testing for comorbidities. There is substantial evidence to support concurrent treatment of obesity and comorbidities to achieve weight loss, avoid further weight gain, and improve obesity-related comorbidities.

Guidelines for dyslipidemia, T2DM, NAFLD, and HTN all recommend lifestyle treatment of the primary management of the comorbidity. Children are often seen at least once a year for WCCs, at which the pediatrician or other pediatric health care provider reviews the growth chart, provides anticipatory guidance on growth, feeding, nutrition, sedentary screen time, and participation in physical activity.

At a minimum, the WCC can include evaluation for comorbidities for children with overweight and obesity, and anticipatory guidance on risk for comorbidities with increasing BMI or obesity.

It may be helpful for pediatricians and other PHCPs to include the diagnosis of obesity to the problem list to heighten awareness and remind providers to address weight concerns at subsequent clinic encounters. There may also be a potential benefit for improved weight outcomes with comorbidity evaluation.

In adult studies, identifying obesity-related comorbidities has been shown to be a motivating factor to address weight concerns. Among those who had an HbA1c test, the decline in BMI-z slope per year was greater for youth with HbA1c in the prediabetes-range. The following sections provide specific recommendations on initial comorbidity evaluation.

Guidance on repeat evaluation and initial comorbidity management may be found in Appendix 3. Children and adolescents with overweight and obesity have increased prevalence of abnormal lipid levels. Children and adolescents with overweight and obesity can also have elevated total cholesterol and low-density lipoprotein LDL levels.

Studies indicate that cardiovascular risk factors track from childhood into adult life and that lifestyle treatments can improve outcomes with respect to these risk factors.

This KAS is supported by both the NHLBI Expert Panel on Integrated Guidelines for Cardiovascular Health and Risk Reduction in Children and Adolescents and American Heart Association and American College of Cardiology Guidelines, which recommend evaluation for early risk of atherosclerotic cardiovascular disease and counseling on risk-reduction behaviors in children and adolescents.

Additionally, awareness of an association of social factors, specifically ACEs, with cardiovascular risk factors is important. The NHLBI expert panel recommends a fasting lipid panel for evaluation of dyslipidemia for children with overweight and obesity.

For practical purposes, a nonfasting lipid panel using the non-HDL level may be easier to obtain for routine evaluation in the primary care setting. The non-HDL level is the total cholesterol minus the HDL cholesterol level. See the implementation guide for additional information.

The cut-off criteria for lipids in the NHLBI guidelines are the same across different age groups, except for triglycerides, as indicated in Table 8. Adapted from the Expert Panel on Integrated Guidelines for Cardiovascular Health.

See Appendix 3 for information on frequency of laboratory testing and information about initial management of dyslipidemia.

T2DM is now increasingly diagnosed in the pediatric population. Between and , the incidence of T2DM among to year-olds in the United States increased from 9. Because obesity is a strong predictor for developing prediabetes and T2DM, , , pediatricians and other PHCPs need to have an increased index of suspicion when caring for children with obesity, especially in the presence of other risk factors Table 9.

Other Risk Factors for Prediabetes and T2DM 90 , , , The pathogenesis of prediabetes and T2DM is a peripheral and hepatic resistance to insulin accompanied by progressive loss of islet cell function. Insulin resistance, when assessed by the homeostatic model assessment of insulin resistance test, varies across weight categories, with highest levels observed among children with severe obesity.

Testing for T2DM should always be performed if there is suspicion of hyperglycemia in a patient with symptoms and signs of hyperglycemia, such as new onset thirst polydipsia , frequent urination polyuria or new onset bedwetting, excessive hunger and eating polyphagia , blurred vision, unexplained or unexpected weight loss, or fatigue.

Diagnostic tests for prediabetes and T2DM are fasting plasma glucose FPG , 2-hour plasma glucose after oral glucose tolerance test OGTT , and HbA1c.

In addition, the concordance between all 3 tests is imperfect. This is a good reason to use the OGTT as a confirmation test if the initial test result is equivocal.

The HbA1c test is easy to obtain as fasting is not required. It provides a measure of chronic hyperglycemia, and use of the test has been shown to increase evaluation for T2DM in primary care settings.

Fasting insulin is not recommended for diagnosis of prediabetes or T2DM because the levels are highly variable and do not reliably correlate with the level of insulin resistance. The cut-off values are similar for pediatric and adult populations, as illustrated in Table 10 , above. If the results are unequivocally high and indicative of T2DM, obtaining a second or repeat confirmatory test is not recommended; instead, treatment should be initiated.

See the implementation guide for further discussion on use of OGTT or FBG tests. Criteria for Diagnosing Prediabetes and T2DM In the absence of unequivocal hyperglycemia, diagnosis is confirmed if 2 different tests are above threshold or a single test is above threshold on 2 separate occasions.

Oral glucose tolerance test OGTT using a load 1. In patients with hyperglycemic crises or classic symptoms of hyperglycemia eg, polyuria, polydipsia. Glycosylated hemoglobin HbA1c is the preferred test for monitoring prediabetes.

See Appendix 3 for more information on frequency of evaluation and on initial management of prediabetes and T2DM. NAFLD is a chronic liver disease marked by steatosis fat accumulation , inflammation, and fibrosis.

The underlying pathogenesis is insulin resistance, which alters the process of fat oxidation in the liver, increasing oxidative stress and inflammation—with resultant liver damage. Three diagnostic terms are used to describe the histology of the disease progression: NAFLD, nonalcoholic fatty liver NAFL , and nonalcoholic steatohepatitis NASH.

NAFLD refers to the whole spectrum of the disorder, from mild steatosis to cirrhosis of the liver. NAFLD is divided into steatosis NAFL and steatohepatitis NASH. In NASH, there is inflammation, steatosis, and fibrosis with ballooning injury to the hepatocytes.

The risk profile and natural history of the disorder in the pediatric population are still evolving, given that there are limited long-term studies in children. Pediatric NAFLD may reflect the early onset of a chronic disease with a more aggressive course, particularly once NASH has occurred. Among children with borderline or definite NASH, resolution occurred in about one-third.

Adolescents were more likely to develop worsening steatosis and less likely to experience any resolution of NASH or regression in fibrosis than younger children. Risk Factors for Diagnosis and Progression of NAFLD 88 , , The North American Society of Pediatric Gastroenterology, Hepatology and Nutrition NASPGHAN clinical practice guidelines recommend ALT as the preferred test for NAFLD.

Higher levels of ALT correlate with more advanced liver disease with steatosis and fibrosis; however, a normal ALT does not definitively exclude NAFLD. NAFLD is less common in children younger than 10 years. In an autopsy study of children, 3. See Appendix 3 for more information on the frequency of evaluation for NAFLD and on managing NAFLD.

One-third of children with obesity have a decreased nocturnal BP dip, increasing the potential risk for end-organ damage. Studies indicate that HTN during childhood and adolescence increases the risk for adult HTN and cardiovascular disease.

Obesity is the strongest risk factor for HTN in childhood. Obtaining a history of physical activity and inactivity levels is also recommended, because decreased activity levels are associated with childhood HTN.

For diagnosis, BP by auscultation should be repeated with confirmed elevated BP measurements on 3 separate clinic visits for elevated BP and stage 1 HTN, and on 2 separate visits for stage 2 HTN.

Used with permission and adapted from the AAP HTN CPG, 87 Fig 2 , and AAP Pediatric Obesity Clinical Decision Support Chart. Summary of KASs for Evaluation of Comorbidities Among Children and Adolescents With Overweight and Obesity. For children and adolescents with excess weight, a larger cuff size may be required to obtain accurate measurements.

For children and adolescents with severe obesity, a thigh cuff may be needed. Additionally, for children and adolescents with obesity, ambulatory blood pressure monitoring ABPM is recommended to assess HTN severity and identify possible abnormal circadian BP patterns, which increases risk for end-organ damage.

Improved identification of children at high risk and youth allows for a thorough evaluation, treatment, and follow-up, with the goal of decreasing long-term cardiovascular morbidity and mortality. See Appendix 3 for more information on repeat evaluation for HTN and on management of HTN.

Table 13 lists the KASs for the comorbidities covered in the TR. One study indicated that a 1-unit increase in the BMI SD score increased the odds of having OSA by a factor of 1.

Evaluation for OSA is based on history of symptoms and examination. Children with obesity, tonsillar hypertrophy, craniofacial anomalies, trisomy 21, and neuromuscular disorders are at higher risk for OSA.

Examination findings may include tonsillar hypertrophy, adenoidal facies, micro- or retrognathia, high-arched palate, and elevated BP. Diagnosis is made by obtaining a polysomnography, the gold standard test, with an apnea-hypopnea index of 1 or more episodes per hour in children.

The CPG authors recommend pediatricians and other PHCPs obtain: A sleep history, including symptoms of snoring, daytime somnolence, nocturnal enuresis, morning headaches, and inattention, among children and adolescents with obesity to evaluate for OSA.

A polysomnogram for children and adolescents with obesity and at least 1 symptom of disordered breathing.

See Appendix 3 for more information on the initial management of OSA. Polycystic ovarian syndrome PCOS is a heterogeneous disorder characterized by hyperandrogenism and disordered ovulatory function and is often associated with obesity and insulin resistance.

The condition increases risk for infertility, T2DM, cardiovascular disease, and cancer. Four different sets of criteria have been published for diagnosis of PCOS in adults as outlined by differing professional organizations Table All of the diagnostic criteria for PCOS require the exclusion of other disorders of adrenal excess, such as nonclassic or late-onset congenital adrenal hyperplasia, Cushing syndrome, hyperprolactinemia, hypothyroidism, acromegaly, premature ovarian failure, a virilizing adrenal or ovarian neoplasm, or a drug-related condition.

Additionally, for adolescents, evaluation should occur 2 years after menarche, because irregular menstrual cycles are not uncommon during this timeframe. Laboratory testing may include: hydroxyprogesterone, total testosterone, free testosterone, sex hormone-binding globulin, dehydroepiandrosterone sulfate, androstenedione, luteinizing hormone, follicle-stimulating hormone, estradiol, prolactin, free thyroxine, thyroid stimulating hormone, and insulin.

Interpretation of laboratory results should be made in the context of age-appropriate reference ranges; therefore, referral to a laboratory that can perform ultrasensitive pediatric assays is recommended. Routine ovarian imaging is not indicated for the diagnosis of PCOS in adolescents.

See Appendix 3 for more information on the initial management of PCOS. The CPG authors recommend pediatricians and other PHCPs: Evaluate for menstrual irregularities and signs of hyperandrogenism ie, hirsutism, acne among female adolescents with obesity to assess risk for PCOS.

The relationship between pediatric obesity and depression is less well understood than the physical comorbidities; however, identification of depression is an important component of the assessment and management of pediatric obesity, given its potential impact on treatment outcomes.

Studies are limited on the effect of treatment of pediatric obesity on depression. A recent meta-analysis of 36 studies found a small but significant reduction in depressive symptoms following structured pediatric obesity treatment. Notably, no adverse mental health outcomes were reported.

Evaluation for depression includes awareness of symptoms and risk factors. Symptoms include irritability, fatigue, insomnia, excessive sleeping, decline in academic performance, family conflict, and weight changes.

Risk factors include personal or family history of depression, substance use, trauma, frequent psychosomatic complaints, psychosocial stressors, and other mental health conditions. The AAP CPG for depression recommends evaluating adolescents 12 years and older for depression annually using a formal self-report tool, such as the Patient Health Questionnaire If initial evaluation for depression is positive, evaluation with a standardized depression tool should be conducted.

See Appendix 3 for more information on the initial management of depression. The CPG authors recommend pediatricians and other PHCPs: Monitor for symptoms of depression in children and adolescents with obesity and conduct annual evaluation for depression for adolescents 12 years and older with a formal self-report tool.

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Save EP - The Habit Of Words for later. Podcast episode 7 Amazing Benefits Of Mindfulness For Body And Brain: There are so many advantages to living in the present that writing a book about them would still be insufficient to explain them all. This article begins with an overview of distributional analysis.

It then examines the changes made in Circular A-4 , particularly with respect to income weighting. It also provides background on income weighting, examines potential legal and practical constraints on the use of income weighting, and explores certain critiques of income weighting.

I conclude that income weighting, if it can overcome the constraints, should lead to more rational and equitable regulation. Distributional analysis, which examines how effects of regulatory options vary across demographic categories, is crucial to ensure regulations do not perpetuate inequities for disadvantaged or marginalized groups through consistent, disproportionate allocation of costs and benefits in otherwise net beneficial regulations.

The Obama administration updated regulatory guidance with Executive Order 13,, but its guidance on distributional consequences of regulations was substantively the same as Executive Order 12, OIRA is charged with ensuring compliance with these executive orders, 18 Exec.

but has made little to no effort to force or even encourage agencies to measure or analyze distributional effects. As it now stands, agencies rarely engage in distributional analysis, and, even when they do, it is cursory, rarely quantitative, and often serves to simply affirm predetermined regulatory decisions.

A study of 24 major Obama-era regulations found none engaged in comprehensive quantitative distributional analysis. Robinson et al. Regulatory Analyses , 10 Rev. at With just three exceptions, the regulations only provided national-level estimates of health-related benefits.

More recently, an analysis of 15 proposed or final agency rules from the first 18 months of the Biden Administration found little improvement in the intervening decade. The study found agencies seldom consider distributional consequences of proposed rules and even more rarely consider distributional consequences of alternative rules.

When agencies did look at distributional consequences, they only performed baseline analyses of the pre-rule status quo and suggested the proposed rule would benefit disadvantaged communities.

The examination of alternatives is one of the foundational elements of analysis identified by Circular A-4 Without an analysis of alternatives, agencies cannot genuinely weigh better distributional consequences of one proposed regulation against the higher net benefits of another, making distributional analysis little more than a rubber stamp on the proposed regulation.

Disregarding distributional effects can lead not just to ineffective, but harmful regulation. Traditional CBA relies on monetary values to compare costs and benefits, regardless of how much utility or disutility recipients of benefits and burdens actually receive.

Melissa J. A little over two years later, following the confirmation of Richard Revesz as the new Administrator of OIRA, the office proposed the first revision to Circular A-4 in 20 years.

The proposed draft of Circular A-4 represents an overhaul of how regulatory analysis should treat distributional effects. A-4 dedicates five pages to explaining distributional analysis in detail. Perhaps the most significant change is the explicit endorsement of income weighting.

As the next section discusses, income weighting should bolster rationality and equity in regulatory decisions by directing more benefits and fewer burdens to low-income communities.

Regulatory analysis and CBA have always proceeded on the irrational assumption that a dollar of benefits or burdens is worth the same to everyone. at 65; Matthew D. Adler, Benefit—Cost Analysis and Distributional Weights: An Overview , 10 Rev.

A-4 rectifies this error, allowing agencies to use distributional weights to account for the diminishing marginal utility of income.

While this choice is not uncontroversial , income weighting should make regulatory analysis more rational by incorporating well-established economic principles on social welfare and more equitable by encouraging the deployment of regulatory benefits to low-income communities and individuals.

Berkman, L. Kahn, J. Livingston, Valuation as a Mechanism of Self-Control and Ego Depletion within Self-Regulation and Ego Control Academic Press , When applied to money, this means that identical increases in income for a poor person and a wealthy person provide less utility to the latter because the utility associated with marginal increases in income decrease as total income increases.

Mikkelson, Diversity and the Good , in Handbook of the Philosophy of Science , In contrast, that money would add very little, if any, utility to Jeff Bezos.

In the context of regulatory analysis, an additional dollar of benefit or burden to a poor person is worth more than the same benefit or burden to a wealthy person. This law of diminishing marginal utility can be functionalized through a social welfare function.

Social welfare functions are mathematical models that measure well-being based on the distribution of a utility such as income in response to policy interventions.

Income weighting is a social welfare function in which the value of costs and benefits factor in the income of those benefitted or burdened. Social welfare functions can also be applied to non-income utility measures, such as health or environmental quality, but those are more difficult to measure and operationalize.

A-4 draws on a strong pedigree of economics and social welfare research in recommending the use of an income-based social welfare function. Distributional weights have been described since at least the s, 48 Adler, supra note but have never been endorsed by U.

federal officials though they have been used by the World Bank and regulators in the United Kingdom. While prior CBAs have not explicitly engaged with income weighting, A-4 recognizes that all CBAs inherently include income weights.

Omitting an explicit income weight simply assumes benefits and burdens are worth the same to everyone, which is an income weight of 1.

However, for the reasons discussed above, a weight of 1 is an irrational weight. income, raised to the power of the elasticity of marginal utility times negative one. of Econ. The formula is as follows:. To illustrate what this means, we can use some simple numbers as an example. In this simplified example, the benefit to the lower income group is worth about 25 times more than the benefit to the higher income group.

Executive Orders 12, and 13, both command agencies to consider regulatory alternatives and choose the approach that maximizes net benefits. The use of income weighting will result in very different regulatory approaches maximizing net benefits.

Traditional CBA, by ignoring income weights, does not capture the actual utility of those burdened and benefitted and therefore cannot accurately determine whether total utility has increased. If agencies systematically use income weighting in CBAs, the design of regulation could shift substantially, increasing equity by directing more benefits to lower income groups.

However, the key question then becomes whether income weighting will be used as both a practical and legal matter. Circular A-4 does not require income weighting; it does not even seem to recommend it. Rather, it simply presents it to agencies as an option.

Thus, as a practical matter, it is possible that income weighting will simply never be used, much as distributional analysis writ large has gone largely unused despite its presence in Circular A-4 for 20 years.

Furthermore, as courts have become increasingly antagonistic to the regulatory state, a novel at least in the U. context mechanism such as income weighting could pose a legal liability that stymies its use.

While agencies have been reticent to engage in distributional analysis, in at least some circumstances, agencies may be incentivized to use income weighting without OIRA needing to recommend it more aggressively.

Any regulations in which benefits are distributed more to those with lower incomes and in which costs are distributed more to those with higher incomes should appear even more net beneficial when income weighting is used.

Given the command in A-4 and to maximize net benefits, agencies may have an easier time showing that benefits have been maximized by using income weighting. Thus, agencies should be drawn to use income weighting in at least some of their regulations on its own merits. However, OIRA may need to actively encourage the use of income weighting to analyze a wider range of regulatory proposals.

Beyond not mandating income weighting, OIRA appears to be hedging its bets further: if an agency does choose to use income weighting in its analysis, it must still present a CBA with the traditional income weight of 1. administrative law. In a legal environment in which courts appear increasingly averse to the regulatory state generally, income weighting could provide judges a reason to invalidate regulations.

Legal avenues of attack are magnified if a regulation only appears net beneficial when using income weights that incorporate the decreasing marginal utility of income i. EPA, U. If a regulation only appears beneficial when using income weights not equal to 1 e.

These are untested waters and innovation can often meet hostile responses from a judiciary predisposed to be skeptical or outright hostile to the regulatory state. Of even greater concern, should the Chevron doctrine be eliminated or curtailed in the forthcoming Supreme Court case Loper Bright Enterprises v.