Obesity, Metabolic Syndrome and Disorders of Energy Balance

Regulation of Food Intake

Human meal patterning is typically characterized by discrete bouts of food consumption interspersed with periods of fasting. The time-course of each meal follows a cycle, comprised of cephalic, gastric, and intestinal phases followed by a postabsorptive state. The cephalic phase consists of the physiologic responses to the thought, sight, smell, and taste of food in anticipation of ingestion. In the gastric phase, ingested food enters the stomach and digestion formally begins. As food leaves the stomach, the intestinal phase begins, where secreted pancreatic enzymes enhance digestion and nutrient absorption. Finally, in the postabsorptive state, nutrient absorption from the meal is complete and circulating glucose concentrations are maintained by glycogenolysis and gluconeogenesis until initiation of the next meal.

Short-term regulation of appetite determines satiety (time period between meals before hunger prompts meal initiation) and satiation (sensation of having eaten enough, leading to meal termination). Food intake is driven by a combination of hunger, social context, and sensory inputs. Hunger is mediated by a drop in anorexic (appetite-suppressing) signals in the postabsorptive state following the prior meal, and by a rise in ghrelin, an orexigenic (appetite-stimulating) peptide secreted by the enteroendocrine cells of the stomach during fasting. Nutrient ingestion leads to a rise in anorexic signals, including gastric wall stretch and mechanical contact with food, secretion of intestinal peptides (e.g., cholecystokinin [CCK], peptide YY, glucagon-like peptide 1 [GLP-1], etc.), and entry of digested nutrients into circulation. The vagal nerve is the primary neural connection between the gastrointestinal (GI) tract and the central nervous system (CNS). It is the longest cranial nerve and contains both sensory and motor fibers involved in the regulation of parasympathetic (“rest and digest”) homeostasis. Vagal sensory afferents from the gut terminate in the hindbrain where connections to cortical, forebrain, and midbrain regions are involved in vagal motor efferent regulation of GI motility and secretory functions for digestion. Importantly, the GI tract is also innervated by the spinal nerves, which convey sensory inputs from the intestinal tract to the homeostatic centers. Satiation is reached when ghrelin drops; gastric distension triggers anorexic vagal afferents to the hindbrain; and increases in glucose, insulin, and anorexic peptides lead to slowing of gastric motility and signaling of fullness to the CNS. Satiety, which determines the interval until the next meal, is influenced by the quantity and composition of the prior meal and additional physiologic contributors, such as gut microbiota, fermentation products, and bile acids.

Nonnutritive aspects of meal regulation include food palatability and neuropsychologic factors, such as mindfulness, stress, cognitive demands, and alertness. Food craving is linked to the hedonic aspects of eating because of activation of the mesocorticolimbic reward pathway. Opioid receptor activation mediates the reward sensation of food and the pleasure of eating, whereas dopaminergic activation mediates the reward value of food and the motivation to obtain food. Social context (gatherings and events where food consumption is expected) and sensory inputs (sight and smell of palatable food) can drive food intake in the absence of hunger, making environmental contingencies and stimulus control just as critical to address as physiologic cues for obesity management.

The Afferent System

Monitoring of metabolic status occurs in multiple regions of the body and assesses circulating forms of energy that are available for immediate use and fluctuate over the course of a meal cycle, as well as more constant stored forms of energy, namely fat. Direct detection of circulating forms of energy uses specific receptors for micronutrients or cellular detection systems, such as glycolytic flux generating varying amounts of adenosine triphosphate (ATP) depending on glucose availability. Indirect surveillance involves paracrine and endocrine hormones that reflect energy status and also stretch receptors in the GI tract that detect volume of material within the gut, nutritive or otherwise, rather than micronutrients specifically. The bloodstream and the autonomic nervous system, mainly the afferent vagus nerve, are the primary routes for transmission of metabolic information from the periphery to the CNS. The mediobasal hypothalamus (MBH, contains the ARC, ventromedial hypothalamic nucleus [VMH], and median eminence [ME]) and dorsal vagal complex (DVC, contains the nucleus of the solitary tract [NTS], the area postrema [AP], and dorsal motor nucleus of the vagus nerve [DMV]) of the brainstem medulla have a special fenestrated blood-brain barrier (BBB), allowing circulating hormones and micronutrients to diffuse into these brain regions for detection by specific receptors and sensing mechanisms. The DVC also receives sensory afferents from the vagal nerve, which innervates the GI tract from the esophagus to the colon and delivers information from chemical and mechanical sensors in the gut to the CNS.

Central Processing

The peripheral afferent signals outlined earlier reach the CNS and act primarily within the hypothalamus and brainstem, where they are integrated by a gated neural circuit, designed to promote net catabolic or anabolic effects (see Fig. 24.2 ).

The Efferent System

The MCRs in the PVN and LHA transduce the anorexigenic and orexigenic information coming from the VMH, to modulate activity of the SNS, and the efferent vagus, which promotes energy storage ( Fig. 24.4 ). In this way, peripheral energy balance can be modulated acutely to provide requisite energy for metabolic needs, and store the rest.

The Nucleus Accumbens and the Hedonic Pathway of Food Reward

The hedonic pathway comprises the ventral tegmental area (VTA) and the nucleus accumbens (NA), with inputs from various components of the limbic system, including the striatum, amygdala, hypothalamus, and hippocampus. These pathways also mediate the hedonic response to drugs of abuse, such as nicotine and morphine. In fact, administration of morphine to the NA increases food intake in a dose-dependent fashion. When functional, the hedonic pathway helps curtail food intake in situations where energy stores are replete; however, when dysfunctional, this pathway can increase food intake leading to obesity.

The VTA appears to mediate feeding on the basis of palatability rather than energy need. The dopaminergic projection from the VTA to the NA mediates the motivating, rewarding, and reinforcing properties of various stimuli, such as food and addictive drugs. Leptin and insulin receptors are expressed in the VTA, and both hormones have been implicated in modulating rewarding responses to food and other pleasurable stimuli. For instance, fasting and food restriction (when insulin and leptin levels are low) increase the addictive properties of drugs of abuse, whereas ICV leptin can reverse these effects. In rodent models of addiction, increased addictive behavior (and pleasurable response from a food reward), as measured by dopamine release and dopamine receptor signaling, is greater after food deprivation. In humans with leptin deficiency, alterations in activity in the NA can be seen using functional magnetic resonance imaging (MRI) scanning, and these changes subside with administration of exogenous leptin. Acutely, insulin increases expression and activity of the dopamine transporter, which clears and removes dopamine from the synapse; thus acute insulin exposure blunts the reward of food. Furthermore, insulin appears to inhibit the ability of VTA agonists (e.g., opioids) to increase intake of sucrose. Finally, insulin blocks the ability of rats to form a conditioned place preference association to a palatable food. However, insulin resistance of this pathway may lead to increased reward perception of food by way of reduced dopamine clearance from the synapse and prolongation of the postsynaptic hedonistic response.

One question that has garnered increasing interest is whether any macronutrient has addictive properties. In animal studies, sugar has been shown to induce the four criteria for addiction: (1) bingeing, (2) withdrawal, (3) craving, and (4) cross-sensitization with other drugs of abuse. Within fast food, sugar and caffeine satisfy the criteria presented in the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) for dependence in humans. However, the question of whether food addiction exists, and whether it can explain patients with obesity, remains contested, although a recent systematic review of the literature supports this notion of “highly-palatable food addiction” based on the criteria of impaired control, social impairment, risky use, and tolerance/withdrawal, at least as a paradigm for consideration in treatment strategies.

The Amygdala and the Stress Response

The VMH and VTA-NA mediate satiety when energy stores are replete, but they appear to be easily overridden by amygdala activation and resultant stress, a state of physiologic insulin resistance ( Fig. 24.5 ). Numerous lines of evidence suggest that the stress glucocorticoids corticosterone (in the rodent) or cortisol (in the human) are essential for the full expression of obesity, which helps to explain the disruptive role of stress in weight regulation.

Stress and glucocorticoids are integral in promoting adiposity and the metabolic syndrome. Adrenalectomized rats maintained pharmacologically with high levels of corticosterone demonstrate that exogenous fat intake is directly proportional to circulating corticosterone concentrations, whereas amygdala activation by stress is dampened by the ingestion of energy-dense food. In intact rats, corticosterone stimulates eating, particularly of high-fat food, and in humans, cortisol administration increases food intake. Human research shows increased caloric intake of “comfort foods” (i.e., those with high energy density) after acute stress, and that the stress response contributes to leptin resistance (discussed later). Several studies in children have observed relationships between stress and unhealthy dietary practices, including increased snacking, and an elevated risk for problems with weight during adolescence and adulthood. In a controlled study of 9-year-old children who scored high on dietary restraint and who felt more stressed by laboratory challenges tended to eat more comfort food. Adverse childhood experiences are also associated with later development of obesity and cardiometabolic risk factors suggesting a role of stress in longitudinal weight gain and metabolic health.

Leptin Resistance

Most children with obesity have high leptin levels but do not have receptor mutations, manifesting what is commonly referred to as functional leptin resistance . Leptin resistance prevents exogenous leptin administration from promoting weight loss. The response to most weight-loss regimens plateaus rapidly because of the rapid fall of peripheral leptin levels which induces a “starvation response” immediately, regardless of baseline values, and potentially because of reaching a personal “leptin threshold,” which is likely genetically determined. Leptin decline causes the VMH to sense a reduction in peripheral energy stores, which modulates a decrease in resting energy expenditure (REE) to conserve energy, analogous to a starvation response, but occurring at elevated leptin levels.

The cause of leptin resistance is unknown, but it may have several etiologies. Leptin crosses the BBB via a saturable transporter, which limits the amount of leptin reaching its receptor in the VMH ; this transporter operates more efficiently at lower levels of leptin, while preventing increased signaling at higher levels. Activation of the leptin receptor induces the intraneuronal expression of suppressor of cytokine signaling-3 (SOCS-3), which limits leptin signal transduction in an autoregulatory fashion. Because the presence of hyperleptinemia has been shown to be a prerequisite for development of leptin resistance, it has been postulated that leptin-induced expression of leptin signaling inhibitors may be an initial step in the process. Other studies suggest that obesity itself induces hypothalamic inflammation, gliosis, and endoplasmic reticulum (ER) stress that impair responsiveness to leptin.

The standard method for producing insulin resistance and obesity in rodents is a high-fat diet. Dietary fat promotes leptin resistance through its effects on hypertriglyceridemia, which limits access of peripheral leptin to the VMH, and also by interfering with leptin signal transduction upstream of STAT-3, its primary second messenger. One likely modulator of this pathway is the enzyme PI3K, which is the downstream effector of insulin action in POMC neurons and which appears to account for the effects of dietary fat on leptin resistance and obesity.

Two clinical paradigms have been shown to improve leptin sensitivity. After weight loss through caloric restriction, exogenous administration of leptin can then increase REE back to baseline and permit further weight loss, suggesting that the weight loss itself improves leptin sensitivity. Second, suppression of insulin correlates with improvement in leptin sensitivity and promotes weight loss, suggesting that hyperinsulinemia promotes leptin resistance by interfering with leptin signal transduction in the VMH and VTA. Indeed, insulin reduction strategies can effectively promote weight loss in children with hyperinsulinemia by improving leptin sensitivity.

Counterregulatory Mechanisms That Oppose Weight Loss

Because the homeostatic system for energy balance was developed to protect against starvation, body fat stores are avidly protected. Therefore dietary restriction, even before the onset of weight loss, triggers counterregulatory mechanisms to oppose the perceived threat of starvation, regardless of baseline adipose tissue stores. Gastric secretion of ghrelin acutely rises, which increases pituitary GH release, to stimulate lipolysis to provide energy substrate for catabolism. Ghrelin stimulates NPY/AgRP to antagonize α-MSH/CART. Decline of leptin reduces α-MSH/CART as well. This leads to decreased MC4R and MC3R occupancy leading to reduced anorexigenic and catabolic signaling with a net effect of increased feeding behavior and higher energy efficiency (with reduced fat oxidation). Appetite proportionally increases leading to food consumption above baseline by approximately 100 kCal/d per kilogram of lost weight. Meanwhile, total and resting energy expenditures decline in an attempt to conserve energy. Specifically, UCP1 levels within adipose tissue decline as a result of decreased SNS activity. In spite of decreased SNS tone at the adipocyte, there is clearly an obligate lipolysis (because of insulin suppression and upregulation of HSL), which is necessary to maintain energy delivery to the musculature and brain in the form of liver-derived ketone bodies. In addition, in the weight-reduced state, vagal tone is increased to slow the heart rate and myocardial oxygen consumption, increase β-cell insulin secretion in response to glucose, and increase adipose insulin sensitivity—all directed to increase energy storage. These counterregulatory mechanisms together serve to drive weight regain and can even persist for years after the initial onset of weight loss, therefore rendering maintenance of reduced body weight exceedingly challenging especially in light of the feed-forward mechanisms described later. In other words, the metabolic adaptations aimed at conserving energy and returning to the body weight before weight loss are maintained for years following the weight loss and achievement of weight plateau rendering the individual prone to weight gain. Upon comparison of two individuals with similar weight and body composition, a weight-stable patient and a patient who lost weight to achieve this measurement, to maintain the current body weight—the patient who lost weight will have to consume less energy and spend more energy in comparison with the weight-stable counterpart.

Feed-Forward Mechanism That Promote Weight Gain

Feed-forward signaling bridges homeostatic and hedonic mechanisms of appetite regulation, a concept developed based on the observation that a hungry mouse will have appropriately elevated AgRP neuronal firing in the fasted state but these AgRP neurons are then acutely suppressed when the mouse is presented with food, even before the onset of eating. In addition, gut signals are also released that anticipate the imminent arrival of ingested food, setting in motion, digestive processes before actual food intake. Because hunger is an aversive experience, rapid reduction in AgRP firing and the sudden removal of hunger sensations induce an acute reward experience, perhaps serving as a positive reinforcer of the environmental cue of food availability. For example, readily visible and appealing packaging of processed foods encourages hedonistic consumption and establishes a learned behavior that prompts subsequent return to the environment where such foods were available. Along the same lines, fast food restaurants and advertising targeting youth rely heavily on connecting images of food with other pleasurable stimuli (toys, games, fun, etc.), further compounding the reward effect of already highly palatable food. This feed-forward mechanism has potential implications as we consider the role of the built environment and its role in promoting food consumption.

Definition

The theoretical definition of obesity is a degree of somatic overweight that affords detrimental health consequences. Based on morbidity and mortality statistics, and with a desire to prevent future risk of morbidity, we practically define obesity as a statistical magnitude of overweight for a population, keeping in mind that morbidity and mortality vary with degree of overweight in different racial, ethnic, and socioeconomic groups.

The majority of obesity in adulthood has its origins in childhood, making obesity a pediatric concern and the prevention and treatment of obesity a pediatric goal. Body mass index (BMI) is also the accepted marker in children. In childhood, comparison of BMI with normal curves for age allows for categorization of BMI above the 85 ^th percentile as overweight, and above the 95 ^th percentile as obesity ( Fig. 24.6 A and B ). The World Health Organization (WHO) categorizes adult overweight into four subgroups based on BMI (weight [kg] ÷ height [m] ² ): BMI 25 to 30 (overweight); BMI 30 to 5, Grade 1 (moderate obesity); BMI 35 to 40, Grade 2 (severe obesity); and BMI over 40, Grade 3 (morbid obesity). A similar degree of obesity categorization can also be used in the pediatric population using BMI centiles where the 95 ^th centile for age and sex is used as a reference point and 100% to 120% of the 95 ^th percentile for age and sex is grade 1, 120% to 140% is grade 2, and over 140% is grade 3. Such categorization demonstrates that cardiometabolic risk increases with rising degrees of obesity.

Although BMI is the standard indicator of obesity for statistical purposes and within populations, it should be noted that BMI does not take into account body composition parameters such as total body fat, (as well as both subcutaneous and visceral fat), muscle, and bone. Furthermore, BMI in children is age, sex, and puberty dependent, thus BMI z-score is a more accurate assessment of childhood adiposity. Lastly, waist circumference (an indirect measure of intraabdominal visceral fat) has emerged as a more accurate indicator of metabolic disturbance in children. These limitations of BMI indicate that it is a useful index for population and epidemiologic studies yet should be used with caution when assessing an individual child in the clinical setting.

Prevalence and Epidemiology

The prevalence of childhood obesity in the United States has increased dramatically during the past 30 years, and continues to do so, although the comparison of longitudinal and cross-sectional data is difficult because of different definitions and measurement parameters between epidemiologic studies. The most recent estimates of obesity prevalence and trends in the United States are based on data from the 2011 to 2014 National Health and Nutrition Examination Survey (NHANES V). NHANES demonstrates that the epidemic of childhood obesity in the United States seems to have stabilized in some age groups but not in others. Overall, in 2013 to 2014, 9.4% (95% confidence interval [CI], 6.8–12.6) of infants and toddlers and 17% (95% CI, 15.5–18.6) of children and adolescents from 2 through 19 years of age had obesity. Of note, the prevalence of extreme obesity (> 120% of 95 ^th percentile for age and sex) was 5.8% (95% CI, 4.9– 6.8). Trend analyses over a 25-year period indicated a significant increase in obesity prevalence among children aged 2 to 5 years between 1988 and 1994 and 2003 and 2004 that slightly declined in 2013 to 2014 (7.2%, 13.9%, and 9.4%, respectively). Among children aged 6 to 11 years old, the prevalence of obesity increased from 1988 to 1994 to 2007 to 2008 and remained stable in 2013 to 2014 (11.3%, 19.6%, and 17.4%, respectively). Among adolescents 12 to 19 years of age, the prevalence of obesity significantly increased from 1988 to 1994 to 2013 to 2014 (10.5% and 20.6%, respectively, P < .001). Of note, the prevalence of extreme obesity increased among children 6 to 11 years old between 1988 and 1994 to 2013 and 2014 (3.6% and 4.3%, respectively, P = .02) and among adolescents aged 12 to 19 years (2.6% and 9.1%, respectively, P < .001). Importantly, no significant trends were observed between 2005 and 2006 and 2013 and 2014. The practical implication of these trends is for example in 1988 to 1994, the 95 ^th percentile of BMI among 17-year-old males was 31.5 kg/m ² (i.e., 5% of males had a BMI > 31.5), and in 2011 to 2014 the 95 ^th percentile was 36.2 kg/m ² (i.e., 5% of males had a BMI > 36.2). Thus between 1988 and 1994 and 2013 and 2014, the prevalence of obesity increased until 2003 to 2004 and then decreased in children aged 2 to 5 years, increased until 2007 to 2008 and then leveled off in children aged 6 to 11 years, and increased among adolescents aged 12 to 19 years. In 2013 to 2014, 17.4% of children met criteria for class I obesity, including 6.3% for class II and 2.4% for class III. A clear, statistically significant increase in all classes of obesity continued from 1999 through 2014. In the United States, obesity and severe obesity among children significantly increased with greater age and lower education of household head, and severe obesity increased with lower level of urbanization. Compared with non-Hispanic white youth, obesity and severe obesity prevalence were significantly higher among non-Hispanic black and Hispanic youth. Severe obesity, but not obesity, was significantly lower among non-Hispanic Asian youth than among non-Hispanic white youth. Lastly, projections argue that by 2030, 42% of American adults will have obesity.

Global Prevalence

Obesity has overtaken acquired immunodeficiency syndrome and malnutrition as the number one public health problem in the world. The global prevalence of childhood obesity has been increasing worldwide at an alarming rate during the past 20 years. Rates have increased 2.7 to 3.8-fold over 29 years in the United States, 2.0 to 2.8-fold over 10 years in England, 3.4 to 4.6-fold over 10 years in Australia, and 3.4 to 3.6-fold over 23 years in Brazil. European data, using slightly different obesity cutoff definitions (a childhood BMI corresponding to > 25 and 30 kg/m ² in adults signifying overweight and obesity, respectively), suggests that among European countries, prevalence of overweight/obesity combined ranges between 16% and 22% whereas that of obesity ranges between 4% and 6% (corresponding to 2.9–4.4 million children with obesity in the European continent). Rapid increases in the prevalence of overweight schoolchildren are being seen in all European countries for which data are available. The numbers indicate a lag of 10 to 15 years behind the United States. Using data from the mid-70s to 2016 in 200 countries, it was shown that trends in mean BMI have recently flattened in northwestern Europe and the high-income English-speaking and Asia-Pacific regions for both sexes, southwestern Europe for boys, and central and Andean Latin America for girls. In contrast, the rise in BMI has accelerated in east and south Asia for both sexes, and southeast Asia for boys. In developed countries, the urban poor are more susceptible for developing obesity, presumably because of poor dietary practices and limited opportunity for physical activity. In contrast, obesity is more frequent in upper socioeconomic class of developing countries, probably because of a nutrition transition to a more Western diet with more energy-dense items consisting of higher fats and sugar, which tend to be more palatable at a lower cost. This may be also caused by specific properties of processed food, which may promote leptin resistance.

Racial and Ethnic Considerations

The NHANES surveys only list prevalence among non-Hispanic whites, non-Hispanic blacks, and Asians, despite the fact that Native Americans, Pacific Islanders, and other racial/ethnic groups are experiencing rapid increases in obesity prevalence as well. Across racial groups, there is a marked dichotomy in the prevalence, and in the rate of increase of childhood obesity. For instance, the prevalence among African American (24.4%), Hispanic (21.7%) and Mexican American adolescents (22.2%) is significantly higher than among white adolescents (15.6%). Importantly, the prevalence of severe obesity (BMI > 97 ^th percentile) among African American (18.5%), Hispanic (15.2%) and Mexican American adolescents (15.2%) by far exceeds that of non-Hispanic white adolescents (10.5%). The rate of increase in the prevalence of obesity among African American and Hispanic adolescents almost doubled between 1988 and 1994 and 1999 and 2000, from 13.4% to 23.6% in African Americans, and from 13.8% to 23.4% in Hispanics. The 1994 Pediatric Nutrition Surveillance System (PedNSS) indicated that 12% of 2- to 4-year-old Native American children were overweight, which is similar to Hispanic children at the same age (12%) but much higher than white children (6%). The prevalence of overweight at 5 to 6 years in Native Americans is twice that in US youth in general, and the prevalence of obesity is even 3 times higher. Overall, both American Indian and Alaska Native children and adolescents have a greater prevalence of obesity compared with US children overall. Among infants and toddlers less than 2 years of age, the prevalence of obesity is highest in African Americans (18.5%), as compared with 10.1% in non-Hispanic whites and 13.7% in Hispanics. It is possible that different dietary practices may account for some of these differences. For instance, a study of 2-year-old Latino children in California correlated obesity with early consumption of sugar-sweetened beverages.

Within racial populations, ethnic variability in the prevalence of childhood obesity has also been noted. Only 25% of first-generation Hispanic adolescents were overweight based on BMI in the 85 ^th percentile or higher, as compared with 32% of second- and third-generation Hispanics. The prevalence of overweight in Asian American adolescents in this study was 20.6%, with comparable prevalence among Filipinos (18.5%) and Chinese (15.3%). Again, only 12% of first-generation Asian Americans were overweight, compared with 27% and 28%, of second and third generations, respectively. In Native Americans, there is great variation in the prevalence of obesity from 12% to 77%, based on tribes, age groups, measurement tools, and cut off values, among the studies performed between 1990 and 2000. These studies indicate that obesity in Native Americans begins very early in childhood.

Predictive Factors

The higher the BMI during childhood, the more likely adult obesity will manifest. In general, children with a BMI in the 95 ^th percentile or higher have a very high risk for adult obesity. Obesity in adolescence is a primary risk factor for obesity in adulthood, with an increased odds ratio from 1.3 for obesity at 1 to 2 years of age to 17.5 for obesity at 15 to 17 years of age. The strongest predictor of adolescent obesity is rapid weight gain between 2 and 6 years of age. The change of BMI during and after adolescence is the most important predictive variable for adult obesity. Children and adolescents with BMI in the 95 ^th percentile or higher have a 62% to 98% chance of having obesity at 35 years of age, with a 50% chance in males aged 13 years or older and 66% chance in girls age 13 years or older. Importantly, an elevated BMI in adolescence (even one that is considered well within the “normal” range) constitutes a substantial risk factor for obesity-related disorders in midlife. Although the risk of diabetes is mainly associated with increased BMI close to the time of diagnosis, the risk of coronary heart disease is associated with an elevated BMI both in adolescence and in adulthood.

The age of adiposity rebound, that is, the point of the BMI nadir before body fatness begins to rise (between 5 and 6 years of age), typically more pronounced in girls (see Fig. 24.6 A and B), is also an important predictor for adult obesity. Children with early adiposity rebound have a fivefold greater chance of having obesity as adults, compared with those with late adiposity rebound. At the age of adiposity rebound, children already overweight have a sixfold greater risk for adult obesity, as compared with lean children. Weight accumulation at an earlier age confers longer exposure to the obesity-related metabolic milieu and thus increases the risk for the development of obesity-related morbidity. Therefore the earlier the onset of childhood obesity, the greater is the risk for adult obesity.

Infant overnutrition plays an extremely important role in the future development of obesity. Numerous studies have implicated bottle feeding as a specific risk factor. The prevalence of obesity in children who were never breastfed was 4.5%, as compared with 2.8% in breastfed children, and a clear time-response effect was identified for the duration of breast-feeding on the decline in prevalence of obesity as well. Early overnutrition has been correlated with elevated leptin concentrations in later life. Differences in both volume and composition of commercial formula versus breast milk have been proposed as etiologic factors. An emerging paradigm posits that the gut microbiome plays a critical factor in the development of obesity in childhood as well as in adulthood. Early exposures to maternal factors including breast milk and to other dietary constituents in infancy (such as introduction of solids, exposure to artificial sweeteners etc.) may be key determinants of the profile of the microbiome impacting metabolism and weight balance during childhood and adulthood.

Parental obesity is also an important predictor of childhood obesity. Children with at least one overweight parent at the age of adiposity rebound have a fourfold to fivefold greater chance of becoming adults with obesity. Lean children aged 5 years or younger have a 13-fold risk of adult obesity if both parents have obesity. Excessive BMI gains of parents during childhood and adulthood are also associated with a higher BMI and risk of obesity in the offspring. Conversely, older children with obesity (10–14 years of age) have a 22.3-fold increased risk to become adult with obesity regardless of parental weight, suggesting that parental obesity is more important in early childhood weight gain. Upon studying associations of parental and child obesity status, stronger associations were shown in older children than in younger children , in both parents than in father or mother only, in parental obesity and child obesity compared with overweight status of both. Parental obesity is also related to early adiposity rebound, although it remains unclear whether the relation between parental and childhood obesity is genetic, epigenetic, or environmental.

Insulin Resistance

Insulin resistance is defined as the decreased tissue response to insulin-mediated cellular actions and is the inverse of insulin sensitivity. The term insulin resistance, as generally applied, refers to whole-body reduced glucose uptake in response to physiologic insulin levels and its consequent effects on glucose and insulin metabolism. However, it is now clear that not all insulin-responsive tissues are equally sensitive to insulin. Generalized insulin resistance would result in global metabolic dysfunction, such as leprechaunism or Rabson-Mendenhall syndrome. Thus the insulin resistance of obesity must of necessity affect different tissues quantitatively (see Chapter 3 and Chapter 21 on diabetes mellitus and insulin receptor mutations).

Hepatic Insulin Resistance . The liver plays a major role in substrate metabolism and is the primary target of insulin action. After insulin’s release from the β-cell following a glucose load, it travels directly to the liver via the portal vein, where it binds to the insulin receptor and elicits two key actions at the level of gene transcription. First, insulin stimulates the phosphorylation of FOXO1, which prevents it from entering the nucleus, and thus diminishes the expression of genes required for gluconeogenesis, mainly phosphoenolpyruvate carboxykinase (PEPCK) and glucose-6-phosphatase. The net effect is diminished hepatic glucose production. Second, insulin activates the transcription factor sterol regulatory element-binding protein (SREBP)-1c, which in turn increases the transcription of genes required for fatty acid and triglyceride (TG) biosynthesis, most notably ATP-citrate lyase, acetyl-coenzyme A carboxylase, and fatty acid synthase; which together constitute the process of de novo lipogenesis (DNL). TGs synthesized by DNL are then packaged with apolipoprotein B (apoB) into very low-density lipoproteins (VLDL) for export to the periphery for storage or utilization by reciprocal activation of lipoprotein lipase (LPL) on the surfaces of endothelial cells in adipose or muscle tissues.

For reasons that remain unclear, insulin-resistant subjects typically have “selective” or “dissociated” hepatic insulin resistance; that is, they have impaired glucose homeostasis (mediated by the FOXO1 pathway) but normal insulin-mediated hepatic DNL (mediated by the SREBP-1c pathway and the GCKR gene ). The increase in FFA flux within the liver, either by DNL or FFA delivery via the portal vein, impairs hepatic insulin action via fatty acyl-CoA intermediates within the hepatocyte, leading to increases in hepatic glucose output, the synthesis of proinflammatory cytokines, and excess TG secretion by the liver, low high-density lipoprotein (HDL) cholesterol levels, and an increase of relatively cholesterol-depleted LDL particles. Furthermore, the intrahepatic accumulation of FFA and lipid are also detrimental to liver insulin sensitivity as this leads to the generation of toxic lipid-derived metabolites, such as DAG, fatty acyl CoA, and ceramides. These in turn trigger activation of protein kinase C-ɛ (PKCɛ, and serine/threonine phosphorylation of insulin receptor substrate 1 (IRS-1), which attenuates hepatic insulin signal transduction. Intrahepatic insulin resistance results in greater first pass insulin clearance in the liver, resulting in lower amounts of insulin reaching the systemic circulation.

Adipose Tissue Insulin Resistance . The expanded adipose tissue mass that accompanies obesity often leads to increased lipolysis and FFA turnover. Normally, insulin inhibits adipose tissue lipolysis; however, in the insulin-resistant state, the lipolytic process is accelerated, leading to increased FFA release into the circulation. Moreover, visceral adipocytes are more sensitive to catecholamine-stimulated lipolysis than subcutaneous adipocytes, further increasing FFA flux. Macrophages also infiltrate into adipose tissue and contribute to both adipocyte hypertrophy and cytokine release. These circulating cytokines also affect insulin action in other tissues, such as liver and muscle. Within the normal glucose tolerance range, an increase in adipose insulin resistance is related to an increase in 2-h glucose levels. A tight relation exists between visceral fat (r = 0.34; P < .001) and the visceral/subcutaneous fat ratio and adipose tissue resistance to insulin. Greater FFA concentration following an oral glucose load is also evident with worsening glucose tolerance indicating reduced suppression of lipolysis and lower FFA clearance.

Muscle Insulin Resistance . Downstream of an insulin-resistant liver, increased plasma FFA flux into skeletal muscle results in fatty acyl-CoA derivates altering the insulin signal transduction pathway and resulting in reduced insulin-mediated glucose transport in skeletal muscle, facilitating the development of hyperglycemia. The ectopic deposition in skeletal muscle of fat as intramyocellular lipid may also play a direct role in the pathogenesis of whole-body insulin resistance and metabolic syndrome via lipid metabolite-induced activation of PKCɛ with subsequent impairment of insulin signaling. Greater intramyocellular lipid deposition is tightly associated with insulin resistance and is typically detected in children with obesity who have altered glucose metabolism. The manifestation of impaired insulin signal transduction in skeletal muscle is reduced translocation of GLUT4 to the cell membrane leading to reduced systemic glucose uptake.

Assessment of Insulin Resistance . The euglycemic hyperinsulinemic clamp is the gold standard for measuring insulin sensitivity; the frequently sampled intravenous glucose tolerance test (FSIVGTT) and steady-state plasma glucose (SSPG) methods are also valid measurements. The clamp is performed by infusing a body-surface-area–adjusted continuous insulin drip while maintaining fasting plasma glucose concentrations by modifying a glucose infusion. Greater glucose infusion rates needed to maintain euglycemia indicate greater insulin sensitivity. Euglycemic hyperinsulinemic clamp studies have shown that insulin resistance is determined primarily by the response of skeletal muscle, with over 75% of infused glucose taken up by muscle and only 2% to 3% by adipose tissue. All three methods are generally time consuming, require intravenous infusions and frequent blood sampling, are burdensome for participants, costly, and require a research setting. In an attempt to simplify the measurement of insulin sensitivity, a number of methods using single simultaneously obtained samples of fasting insulin and glucose have been developed, such as the homeostatic model for assessment of insulin resistance (HOMA-IR). Each of these uses a mathematical formula that adjusts for individual variability in insulin and glucose secretion and clearance. Although the goal for these methods was to improve the accuracy of fasting insulin alone by the addition of fasting glucose, it is now agreed that they yield similar results to fasting insulin. When correlated with gold standard methods in children, fasting insulin is a poor measure of whole-body insulin sensitivity in an individual child. Although the primary interest has been in insulin resistance, the adverse effects related to insulin resistance are more likely mediated via compensatory hyperinsulinemia. The fasting triglyceride to HDL-cholesterol ratio, a surrogate of insulin resistance that does not use insulin measurements, has been proposed and correlate quite well with clamp-derived insulin resistance, yet its utilization needs validation in ethnically diverse populations.

The two most important biologic conditions associated with insulin resistance in childhood are ethnicity and puberty. Studies show that African American, Hispanic, Pima Indian, and Asian children are less insulin sensitive compared with non-Hispanic white children with similar anthropometric measures. Insulin resistance in minority ethnic groups is manifested as lower insulin-stimulated glucose uptake, concomitant with hyperinsulinemia, evidence of increased insulin secretion from the β-cell, and decreased insulin clearance. During puberty there is around 25% to 50% decline in insulin sensitivity with recovery when pubertal development is complete. The compensatory increase in insulin secretion during puberty may be blunted in African American and Hispanic youth, thus increasing their risk for type 2 diabetes (T2DM) around the time of puberty. The development of T2DM is covered in depth in Chapter 21 , yet it is worth noting that impaired glucose tolerance (IGT), known as prediabetes, is a relatively common condition in children and adolescents with obesity. IGT in youth with obesity is typically characterized by obesity with an unfavorable pattern of lipid partitioning, with increased deposition of fat in the visceral, hepatic, and intramyocellular compartments.

Lipid Partitioning

The term lipid partitioning refers to the distribution of body fat in various organs and compartments. The majority of excess fat is stored in its conventional subcutaneous depot, yet other potential storage sites exist as well, such as the intraabdominal (visceral) fat compartment and insulin-responsive tissues, such as muscle and liver. One hypothesis to explain the relation between obesity and insulin resistance is the “portal-visceral” paradigm. This hypothesis claims that increased adiposity causes accumulation of fat in the visceral depot, leading to an increased portal and systemic FFA flux ( Fig. 24.7 ). Associations between visceral adiposity, insulin resistance, and comorbidities have been demonstrated across most age groups and ethnicities. Of note, studies of in vivo FFA fluxes from the visceral and the subcutaneous truncal and abdominal depots have failed to demonstrate a substantial difference in net fluxes between these depots.

Subcutaneous fat, which does not drain into the portal system, is strongly related to insulin resistance in healthy men with obesity and in men with diabetes. Similarly, truncal subcutaneous fat mass has been demonstrated to independently predict insulin resistance in women with obesity. Visceral and subcutaneous fat differ in their biologic responses because visceral fat is more resistant to insulin and has increased sensitivity to catecholamines. These observations emphasize that both visceral and subcutaneous abdominal fat can contribute to insulin resistance, possibly by different mechanisms. Studies performed in adolescents with obesity highlight the fact that the ratio of visceral to subcutaneous fat may be the determinant of their metabolic impact rather than their absolute quantity of fat. Indeed, adolescents with obesity who have a high visceral to subcutaneous fat ratio, despite having a comparable degree of obesity, demonstrate a markedly adverse metabolic phenotype of severe insulin resistance and alterations in glucose and lipid metabolism. Moreover, intrahepatic fat, although strongly associated with high levels of visceral fat, is also associated with the insulin-resistant state in adolescents with obesity, independent of all other fat depots.

A more unifying paradigm is the “adipose tissue expandability” hypothesis claiming that total body fat is not the culprit of adverse health in obesity rather the relative proportion of lipids in various fat depots is what determines the metabolic phenotype and its derived metabolic risk. This theory claims that as adipose tissue expands, “ectopic lipid deposition” in insulin-responsive tissues is the culprit of adverse effects on metabolism. This theory is based on the observations that lipid content in liver and/or muscle is increased in obesity and in T2DM and is a strong predictor of insulin resistance. Moreover, in conditions such as lipodystrophies, all fat is stored in liver and muscle because of lack of subcutaneous fat tissue, causing severe insulin resistance and diabetes. In adults with obesity (BMI > 30), muscle attenuation on computed tomography ([CT]; representing lipid content) is a stronger predictor of insulin resistance than is visceral fat. Studies performed in vivo using proton nuclear magnetic resonance ( ¹ H-NMR) spectroscopy demonstrated increased intramyocellular lipid (IMCL) content to be a strong determinant of insulin resistance in adults and in adolescents with obesity. Alternatively, lipid deposition in hepatocytes to produce intrahepatocellular lipid (IHCL) is highly predictive of insulin resistance, even more so than visceral fat. Thus obesity-driven morbidity may begin when the subcutaneous adipose tissue reaches its capacity to store excess fat and begins to shunt lipid to ectopic tissues, such as liver and muscle, leading to peripheral insulin resistance ; or possibly when liver or muscle accumulates lipid produced de novo in response to dietary manipulation (see later). Another postulated cause of IMCL and IHCL accumulation is a reduction of fat β-oxidation, related to low aerobic capacity, a reduced number or malfunction of mitochondria, or reduced SNS tone. The effect of IMCL or IHCL accumulation on peripheral sensitivity is postulated to be caused by an alteration of the insulin signal transduction pathway in muscle, caused by derivates of fat, such as long-chain fatty acyl-CoA and DAG within the hepatocyte or myocyte. These derivates activate the serine/threonine kinase cascade and cause serine phosphorylation of IRS-1, which inhibits insulin signaling. A comparable mechanism has been demonstrated in the liver, where accumulation of lipids, in particular DAG, activates the inflammatory cascade by inducing c-jun N-terminal kinase 1 (JNK-1), which causes serine rather than tyrosine phosphorylation of IRS-1, leading to inhibition of hepatic insulin signaling.

Vascular Changes

Early stages of the atherosclerotic process may be detected in children with obesity. In recent years, it has become clear that endothelial dysfunction represents a key early step in the development of atherosclerosis. The hallmark and cause of endothelial dysfunction is impairment in nitric oxide (NO)-mediated vasodilatation. This is caused by decreased NO production by endothelial nitric oxide synthase (eNOS), which has been postulated to result from high levels of FFAs and inflammatory cytokines (interleukin [IL]-6, tumor necrosis factor [TNF]-α) in insulin-resistant individuals with obesity, increased reactive oxygen species, or increased uric acid, which inhibit eNOS activity. Decreased NO bioavailability leads to an imbalance between vasodilating and vasoconstricting factors (such as endothelin), which leads to impaired vascular smooth muscle relaxation, increased adhesion of inflammatory cells to the endothelium, increased expression of plasminogen activator inhibitor–1 (PAI-1; a prothrombotic molecule) and increased vascular smooth muscle cell proliferation. Thus decreased NO bioavailability is thought to create a proinflammatory, prothrombotic environment which promotes atherosclerosis. Endothelial function represents an integrated index of the overall CV risk burden in any given individual. During the last decade, noninvasive techniques for the assessment of endothelial function, including high-resolution external vascular ultrasound to measure flow-mediated endothelium-dependent dilatation (FMD) of the brachial artery during hyperemia have been developed. Impaired FMD correlates with arterial wall stiffness, coronary dilatation, and endothelial dysfunction in children with obesity. Similarly, anatomic changes in peripheral arterial vessels, such as increased intimal medial thickness (IMT), have also been demonstrated in children and adolescents with obesity, which mimics early coronary pathology and predicts adverse CV outcomes.

There are no longitudinal studies that directly measure in vivo insulin sensitivity and its relationship to the development of atherosclerotic abnormalities in children. Very limited observations suggest a relationship between HOMA-IR and arterial stiffness and fasting insulin levels in youth. However, a role for insulin resistance in the early abnormalities of vascular smooth muscle is proposed based on the observation that circulating biomarkers of endothelial dysfunction (intercellular adhesion molecule and E-selectin) are highest, whereas adiponectin, the antiatherogenic adipocytokine, is lowest among the most insulin-resistant youth. The landmark Bogalusa heart study demonstrated that CV risk factors present in childhood are predictive of coronary artery disease in adulthood. Among these risk factors, LDL-cholesterol and BMI measured in childhood were found to predict IMT in young adults. There is now substantial evidence that the insulin resistance of childhood obesity creates the metabolic platform for adult CV disease. Obstructive sleep apnea (OSA), typically present in children with obesity, is also tightly associated with the presence of endothelial dysfunction. Moreover, the constellation of peripheral insulin resistance, an unfavorable adipocytokine profile, subacute inflammation, and endothelial dysfunction work in parallel to promote the pathologic processes of aging.

Adipocytokines

Leptin . The discovery of leptin in 1994 has dramatically changed the view of adipose tissue in the regulation of energy balance. Adipocytes secrete several proteins that act as regulators of glucose and lipid homeostasis. These proteins have been collectively referred to as adipocytokines because of their structural similarity with cytokines. Circulating leptin levels correlate with the degree of obesity. As stated earlier, the primary role of leptin is to serve as a long-term energy storage sensor to protect against starvation. Leptin probably has a permissive role in high-energy metabolic processes, such as puberty, ovulation, and pregnancy, but its role in states of energy excess is less known. In obesity, the development of leptin resistance may result in a breakdown of the normal partitioning of surplus lipids in the adipocyte compartment.

Adiponectin. The cytokine adiponectin is peculiar in obesity because, in contrast with the other adipocytokines, its level is reduced in individuals with obesity. The adiponectin gene is expressed exclusively in adipose tissue and codes a protein carboxyl terminal globular head domain and an amino terminal collagen domain, which is structurally reminiscent of the complement factor 1q. The gene is located on chromosome 3q27, a location previously linked to the development of type 2 diabetes and the metabolic syndrome. Several single nucleotide polymorphisms (SNPs) in the adiponectin gene have been reported to be associated with the development of type 2 diabetes in populations around the world, suggesting that adiponectin plays a major role in glucose metabolism. Adiponectin circulates in plasma in three major forms: a low-molecular-weight trimer, a middle-molecular-weight hexamer, and a high-molecular-weight 12- to 18-mer. Circulating plasma high-molecular-weight adiponectin concentrations demonstrate a sexual dimorphism (females have greater concentrations), suggesting a role for sex hormones in the regulation of adiponectin production or clearance. Dietary factors, such as linoleic acid or fish oil versus a high carbohydrate diet or increased oxidative stress, have been shown to increase or decrease adiponectin concentrations, respectively. These observations suggest that the circulating levels of adiponectin are regulated by complex interactions between genetic and environmental factors.

The receptors for adiponectin have been characterized in rodent models and cloned. Two receptors, named ADIPOR1 and ADIPOR2, have been characterized. ADIPOR1 is expressed in numerous tissues including muscle, whereas ADIPOR2 is mostly restricted to the liver. Both receptors are bound to the cell membrane, yet are unique in comparison to other G-protein–coupled receptors in the fact that the C-terminal is external, whereas the N-terminal is intracellular. Both ADIPOR1 and ADIPOR2 are receptors for the globular head of adiponectin and serve as initiators of signal transduction pathways that lead to increased PPARα and increased adenosine monophosphate (AMP) kinase activities, which promote glucose uptake and increased fatty acid oxidation. Adiponectin has been shown to have potent antiatherogenic functions, as it accumulates in the subendothelial space of injured vascular walls to reduce the expression of adhesion molecules and the recruitment of macrophages.

Studies in children and adolescents with obesity have shown that adiponectin is inversely related with the degree of obesity, insulin sensitivity visceral adiposity, IHCL, and IMCL, whereas weight loss increases adiponectin. In adolescents with obesity and type 2 diabetes, low baseline adiponectin and a reduced elevation in response to treatment have been shown to predict treatment failure. All of these observations along with human clinical data support a pivotal role for adiponectin in the prevention of the comorbidities of the metabolic syndrome.

Family studies using parent-offspring regressions revealed that most adipocytokines show evidence for significant inheritance. There are three main common axes of variation in the heritability of adipocytokines. The main axis, which explained 21% of the variation, was most strongly loaded on levels of leptin, TNF-α, insulin, and PAI-1, and inversely with adiponectin. This axis was significantly associated with BMI and phenotypically stronger in children, and showed a heritability of 50%, after adjustment for age, gender, and generational effects. Thus adipocytokines are highly heritable and their pattern of covariation is significantly correlated with BMI as early as the preteen years.

Myokines and Natriuretic Peptides. Skeletal and heart muscles may serve as an endocrine organ as well. Some of the effects of exercise on skeletal muscle are mediated by the transcriptional coactivator PPAR-γ coactivator 1α (PGC-1α). In the mouse, PGC-1α expression in muscle stimulates an increase in expression of FNDC5, a membrane protein that is cleaved and secreted as a newly identified hormone, named Irisin . Irisin acts on white adipose cells in culture and in vivo to stimulate UCP1 expression and induces “beiging” of white adipocytes into cells metabolically more active. Irisin is induced with exercise in mice and humans, and mildly increased irisin levels in the blood cause an increase in energy expenditure in mice with no changes in movement or food intake, resulting in improvements in obesity and glucose homeostasis. This novel myokine is actually the first hormonal link between exercise and the adipose tissue changes it may induce. Importantly, this molecule has a negative correlation with brain executive function and thus probably has multiple effects yet to be discovered. Atrial natriuretic peptides (ANP) also have been implicated in fat metabolism. These natriuretic peptides are produced with exercise, cardiac wall stress, weight loss, and cold exposure, and inhibited by obesity and insulin resistance. ANP binds to its natriuretic receptor, facilitating the formation of cyclic guanosine monophosphate (cGMP) from guanosine triphosphate (GTP). cGMP phosphorylates cGMP-dependent protein kinase, which activates lipolysis, and phosphorylates p38 mitogen-activated protein kinase to enhance mitochondrial biogenesis with increased energy expenditure and increased heat generation, as part of the brown-fat thermogenic program. Thus both skeletal and cardiac muscle may respond to exercise by inducing changes in fat metabolism to enhance caloric expenditure and limit obesity. These new findings are likely to open new avenues of clinical research to limit the consequences of the “obesity epidemic.”

Inflammatory Cytokines. Accumulating evidence indicates that obesity is associated with subclinical chronic inflammation. Adipose tissue serves not merely as a simple reservoir of energy stored as TGs, but also as an active secretory organ releasing many peptides, including inflammatory cytokines, into the circulation. This is probably because of infiltration of adipose tissue by cells of the immune system, mainly macrophages. In obesity, the balance between these numerous peptides is altered, such that larger adipocytes and macrophages embedded within them produce more inflammatory cytokines (i.e., TNF-α, IL-6) and less antiinflammatory peptides, such as adiponectin. One hypothesis posits that as energy accumulates in adipocytes, the perilipin border of the fat vacuole breaks down, causing the adipocyte death. Cell death recruits macrophages into the adipose tissue, especially within the visceral compartment, which in the process of clearing debris, also elaborate inflammatory cytokines, initiating a proinflammatory milieu that predates and possibly drives the development of systemic insulin resistance, diabetes, and endothelial dysfunction. Systemic concentrations of C-reactive protein (CRP) and IL-6, two major markers and participants of the inflammatory process, are increased in children and adolescents with obesity. CRP levels within the “high-normal” range have been shown to predict CV disease and development of T2DM in adults. Elevated levels of CRP correlate with other components of the metabolic syndrome in children with obesity. Thus inflammation may be one of the links between obesity and insulin resistance, potentially driving myocyte and hepatic resistance within the insulin signal transduction pathway.

Reactive Oxygen Species (ROS). The “Free Radical Theory” holds that imbalance between ROS generation and antioxidant defenses is a major factor in the determination of lipid peroxidation and protein misfolding, with resultant deoxyribonucleic acid (DNA) and cellular damage. Excessive intracellular ROS formation occurs via three pathways: (1) inflammatory cytokines derived from visceral fat accumulation, (2) dysfunctional mitochondrial energetics, and (3) glycation. Excessive nutrient processing by mitochondria can result in uncoupling of oxidative phosphorylation and increased generation of ROS; this, in turn, leads to altered mitochondrial function and further ROS generation. ROS accumulation can also impair ER function, causing ER stress and the compensatory unfolded protein response (UPR). The UPR can itself be overwhelmed by persistent excessive nutrient processing and ROS generation, leading to cellular shutdown, defective insulin secretion, and T2DM ( Fig. 24.8 ).

Because ROSs are inherent by-products of cellular metabolism, endogenous cellular antioxidants (e.g., catalase and glutathione) quench the ROS before they have a chance to promote peroxidation. These antioxidants are found primarily in peroxisomes, which collaborate with the mitochondria in ROS processing. Reduction in peroxisomal activity results in mitochondrial dysfunction and ER stress. Furthermore, cytokines, such as TNF-α, can reduce peroxisomal number and function, rendering cells even more vulnerable.

Comorbidities Related to Insulin Resistance