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Obesity

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Obesity
Author: Osama Hamdy, MD, PhD, FACE; Chief Editor: George T Griffing, MD more... Updated: Sep 24, 2012

Background
Obesity is a substantial public health crisis in the United States and in the rest of the industrialized world. The prevalence is increasing rapidly in numerous industrialized nations worldwide. This growing rate represents a pandemic that needs urgent attention if obesity’s potential toll on morbidity, mortality, and economics is to be avoided. Research into the complex physiology of obesity may aid in avoiding this impact (see the image below). (See Etiology and Epidemiology.)

Central nervous system neurocircuitry for satiety and feeding cycles.

The annual cost of managing obesity in the United States alone amounts to approximately $100 billion, of which approximately $52 billion are direct costs of health care. These costs amount to approximately 5.7% of all healthrelated expenditures in the United States. The cost of lost productivity due to obesity is approximately $3.9 billion, and another $33 billion is spent annually on weight-loss products and services. (See Treatment and Medication.)

Measurements of obesity
Obesity represents a state of excess storage of body fat. Although similar, the term overweight is puristically defined as an excess body weight for height. Normal healthy men have a body fat percentage of 15-20%, while normal healthy women have a percentage of approximately 25-30%.[1] Because differences in weight among individuals are only partly due to variations in body fat, body weight is a limited, although easily obtained, index of obesity. The body mass index (BMI), also known as the Quetelet index, is used far more commonly than body fat
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percentage to define obesity. In general, BMI is closely correlated with the degree of body fat in most settings; however, this correlation is weaker at low BMI. BMI = weight/height2, with weight being in kilograms and height being in meters (the weight in pounds X 0.703/height in inches2). The body fat percentage can be indirectly estimated by using the Deurenberg equation, as follows: body fat percentage = 1.2(BMI) + 0.23(age) - 10.8(sex) - 5.4, with age being in years and sex being designated as 1 for males and 0 for females. This equation has a standard error of 4% and accounts for approximately 80% of the variation in body fat. Although the BMI is typically closely correlated with percentage body fat in a curvilinear fashion, some important caveats to its interpretation apply. In mesomorphic (muscular) persons, BMIs that usually indicate overweight or mild obesity may be spurious, whereas in some persons with sarcopenia (as seen in elderly individuals and in persons of Asian descent, particularly from South Asia), a typically normal BMI may conceal underlying excess adiposity characterized by increased percentage fat mass and reduced muscle mass. In view of these limitations, some authorities advocate a definition of obesity based on percentage body fat. For men, a percentage of body fat greater than 25% defines obesity, with 21-25% being borderline. For women, over 33% defines obesity, with 31-33% being borderline. Other indices used to estimate the degree and distribution of obesity include the 4 standard skin thicknesses (ie, subscapular, triceps, biceps, suprailiac) and various anthropometric measures, of which waist and hip circumferences are the most important. Dual-energy X-ray absorptiometry (DEXA) scanning is mostly used by researchers to accurately measure body composition, particularly fat mass and fat-free mass. It has an additional advantage of measuring regional fat distribution. However, DEXA scanning cannot distinguish between subcutaneous and visceral abdominal fat deposits. The current criterion standard techniques for measuring visceral fat volume are abdominal CT scanning (at L4-L5) and MRI techniques. These methods are limited to clinical research.

Classification of obesity
Although several classifications and definitions for degrees of obesity are accepted, the most widely accepted classifications are those from the World Health Organization (WHO), based on BMI. The WHO designations include the following: Grade 1 overweight (commonly and simply called overweight) - BMI of 25-29.9 kg/m2 Grade 2 overweight (commonly called obesity) - BMI of 30-39.9 kg/m2 Grade 3 overweight (commonly called severe or morbid obesity) - BMI greater than or equal to 40 kg/m2 The surgical literature often uses a different classification to recognize particularly severe obesity. The categories are as follows: Severe obesity - BMI greater than 40 kg/m2 Morbid obesity - BMI of 40-50 kg/m2 Super obese - BMI greater than 50 kg/m2 The definition of obesity in children involves BMIs greater than the 85th (commonly used to define overweight) or the 95th (commonly used to define obesity) percentile, respectively, for age-matched and sex-matched control subjects. The BMI cutoff for observed risk in different Asian populations varies from 22-25 kg/m2; for high risk, it varies from 26-31 kg/m2.[2]

Comorbidities associated with obesity
Obesity is associated with a host of potential comorbidities that significantly increase the potential morbidity and mortality associated with the condition. Although no cause-and-effect relationship is exhaustively demonstrated for all of these comorbidities, amelioration of these conditions after substantial weight loss suggests that obesity probably plays an important role in their development. (See Presentation.) Overweight and obese individuals are at increased risk for the following health conditions:

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Cardiometabolic syndrome Type 2 diabetes Hypertension Dyslipidemia Coronary heart disease Osteoarthritis Stroke Gall bladder disease Obstructive sleep apnea Gastroesophageal reflux disease (GERD) Some cancers (endometrial, breast, and colon) Apart from total body fat mass, accumulating data suggest that regional fat distribution also substantially affects the incidence of comorbidities associated with obesity.[3] High abdominal fat content (including visceral and, to a lesser extent, subcutaneous abdominal fat) is strongly correlated with worsened metabolic and clinical consequences of obesity. As a result, android obesity, which is predominantly abdominal, is more predictive of adipose-related comorbidities than gynecoid obesity, which has a relatively peripheral (gluteal) distribution. Waist circumferences greater than 94 cm (37 in) in men and greater than 80 cm (31.5 in) in women and waist-tohip ratios greater than 0.95 in men and greater than 0.8 in women are the thresholds for significantly increased potential cardiovascular risk. Circumferences of 102 cm (40 in) in men and 88 cm (35 in) in women indicate a markedly increased potential risk requiring urgent therapeutic intervention; these are the thresholds used in the Adult Treatment Panel III (ATPIII) definition of the metabolic syndrome. These thresholds are much lower in European and Asian populations. An elevated BMI during adolescence (within the range currently considered normal) strongly associates with the risk of developing obesity-related disorders later in life.[4] Changes in BMI during early adulthood (age 25-40 y) are associated with a worse biomarker profile related to obesity than changes in BMI during later adulthood.[5] This is consistent with most emerging data regarding timing of changes in BMI and later health consequences. Apart from the metabolic complications associated with obesity, a paradigm of increased intra-abdominal pressure has been recognized. This pressure effect is most apparent in the setting of marked obesity (BMI ≤50) and is espoused by bariatric surgeons.[6] Given findings from bariatric surgery and animal models, this change in pressure may play a (potentially major) role in the pathogenesis of comorbidities of obesity, such as pseudotumor cerebri, lower-limb stasis, ulcers, dermatitis, thrombophlebitis, reflux esophagitis, abdominal hernias, and possibly hypertension and nephrotic syndrome. A study by Losina et al exploring the association of obesity with knee osteoarthritis found that a substantial number of quality-adjusted life years among persons in the study were lost due to knee osteoarthritis and obesity, most notably among black and Hispanic women.[7] Some reports, including those by Adelman and colleagues and by Kasiske and Jennette, suggest an association between severe obesity and focal glomerulosclerosis.[8, 9, 10] These complications, in particular, improve substantially or resolve early after bariatric surgery, well before clinically significant weight loss is achieved. The so-called Pickwickian syndrome, named after the boy who was obese in Charles Dickens’s novel The Pickwick Papers, is a combined syndrome of obesity-related hypoventilation (associated with severe mechanical respiratory limitations to chest excursion, caused by severe obesity) and sleep apnea (which may be from obstructive and/or central mechanisms). Obstructive sleep apnea is common among men with collar size greater than 17 in (43 cm) and women with collar size greater than 16 in (41 cm). There is evidence linking obesity to psoriasis although data is sparse. One study of 89049 obese women found an association between high BMI and an increased risk of psoriatic arthritis.[11]

Anatomy
The adipocyte, which is the cellular basis for obesity, is increasingly found to be a complex and metabolically active cell. At present, the adipocyte is being perceived as an endocrine gland with several peptides and metabolites that may be relevant to the control of body weight, and these are being studied intensively.[12]
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Among the products of the adipocyte involved in complex intermediary metabolism are cytokines, tumor necrosis factor-alpha, interleukin 6, lipotransin, monocyte chemo-attracting protein-1 (MCP-1), plasminogen activator inhibitor-1 (PAI-1), adipocyte lipid-binding protein, acyl-stimulation protein, prostaglandins, adipsin, perilipins, lactate, leptin, adiponectin, monobutyrin, and phospholipid transfer protein.[13] Among critical enzymes involved in adipocyte metabolism are endothelial-derived lipoprotein lipase (lipid storage), hormone-sensitive lipase (lipid elaboration and release from adipocyte depots), acyl-coenzyme A (acyl-CoA) synthetases (fatty acid synthesis), and a cascade of enzymes (beta-oxidation and fatty acid metabolism). The ongoing flurry of investigation into the intricacies of adipocyte metabolism has not only improved our understanding of the pathogenesis of obesity but has also offered several potential targets for therapy. Another area of active research is investigation of the cues for the differentiation of preadipocytes to adipocytes. With the recognition that this process occurs in white and brown adipose tissue, even in adults, its potential role in the development of obesity and the relapse to obesity after weight loss has become more important than before. Among the identified factors in this process are transcription factors peroxisome proliferator-activated receptorsgamma (PPAR-gamma), retinoid-X receptor ligands, perilipin, adipocyte differentiation-related protein (ADRP), and CCAAT enhancer-binding proteins (C/EBP) alpha, beta, and delta. One study showed that an elevated level of plasma procalcitonin within the normal range is associated with obesity, although it appears that this is not an independent variable, since it reflects a state of distress or inflammation.[14]

Etiology
The etiology of obesity is far more complex than the simple paradigm of an imbalance between energy intake and energy output. Although this concept allows easy conceptualization of the various mechanisms involved in the development of obesity, obesity is far more than simply the result of too much eating and/or too little exercise. (See energy-balance equation below.)

Energy balance equation.

However, the prevalence of inactivity in industrialized countries is considerable and relevant. In the United States, only approximately 22% of adults and 25% of adolescents report notable regular physical activity. Approximately 25% of adults in the United States report no remarkable physical activity during leisure, while approximately 14% of adolescents have similar reports of inactivity. Two major groups of factors with a balance that variably intertwines in the development of obesity are genetics, which is presumed to explain 40-70% of the variance in obesity, and environmental factors. From genetic point of view, obesity may be caused by a single gene or by multiple genes defects. The exact gene or genes that contribute to common forms of human obesity have not been clearly identified. Several genetic studies suggest polymorphisms in several genes, including those for the melanocortin-4 receptor, the beta-3adrenergic receptor, and the peroxisome-proliferator-activated receptor (PPAR)-gamma 2. Polymorphism of these genes is clearly associated with obesity. Obesity also has strong heritability genetic factors. This has been made clear in several twin and adoptee studies, in which obese individuals who were reared separately followed the same weight pattern of their biological parents and of their identical twins. Metabolic rate, spontaneous physical activity, and thermic response to food seem to be heritable to a variable extent.

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On the other hand, many hormones, neurotransmitters, and neurogenic signals affect appetite and food intake. Endocannabinoids, through their effects on endocannabinoid receptors, increase appetite, enhance nutrient absorption, and stimulate lipogenesis. Melanocortin hormone, through its effects on various melanocortin receptors, modifies appetite. Several gut hormones play significant roles in inducing satiety, including glucagonlike peptide-1 (GLP-1), neuropeptide YY (PYY), and cholecystokinin. Leptin and pancreatic amylin are other potent satiety hormones. On the other hand, ghrelin, which is secreted from the stomach fundus, is a major hunger hormone. A study by Freeman et al found that having an overweight or obese father and healthy weight mother significantly increased the odds of childhood obesity; however, the reverse scenario, having an obese mother and healthy weight father, was not associated with an increased risk of obesity in childhood.[15] Although the high prevalence of obesity in the children of parents who are obese and the high concordance of obesity in identical twins suggest a substantial genetic component to the pathogenesis of obesity, the secular trends of the last few decades, which have been coincident with changes in dietary habits and activity, also suggest an important role for environmental factors. Smell plays an important role in feeding behavior.[16] The olfactory threshold was measured in 8 lean individuals before and during 2-hour hyperinsulinemic euglycemia insulin clamp and was compared with the threshold in lean, fasted subjects. Increased insulin led to reduced smelling capacity, potentially reducing the pleasantness of eating. Therefore, insulin action in the olfactory bulb may be involved in the process of satiety and may be of interest in the pathogenesis of obesity for clinicians.

Leptin
Friedman and colleagues discovered leptin (from the Greek word leptos, meaning thin) in 1994 and ushered in an explosion of research and a great increase in knowledge about regulation of the human feeding and satiation cycle. Since this discovery, neuromodulation of satiety and hunger with feeding has been found to be far more complex than the old, simplistic model of the ventromedial hypothalamic nucleus and limbic centers of satiety and the feeding centers of the lateral hypothalamus. (The potential for possible leptin sensitizers may assist in changing feeding habits.) Leptin is a 16-kd protein produced predominantly in white subcutaneous adipose tissue and, to a lesser extent, in the placenta, skeletal muscle, and stomach fundus in rats. Leptin has myriad functions in carbohydrate, bone, and reproductive metabolism that are still being unraveled, but its role in body-weight regulation is the main reason it came to prominence. The major role of leptin in body-weight regulation is to signal satiety to the hypothalamus and, thus, reduce dietary intake and fat storage while modulating energy expenditure and carbohydrate metabolism to prevent further weight gain. Unlike the Ob/Ob mouse model in which this peptide was first characterized, most humans who are obese are not leptin deficient but rather leptin resistant. Therefore, they have elevated levels of circulating leptin. A study by Lieb et al indicated that higher circulating leptin levels are associated with a greater risk of congestive heart failure and cardiovascular disease but that leptin does not offer incremental prognostic information beyond BMI. The authors assayed plasma leptin in 818 elderly participants in the Framingham Heart Study.[17] Leptin levels, which were higher in women, were strongly correlated with BMI. On follow-up (mean, 8 y), it was found that congestive heart failure had developed in 129 participants (out of 775 individuals who had been free of congestive heart failure), a first cardiovascular disease event had occurred in 187 participants (out of 532 individuals who had been free of cardiovascular disease), and 391 persons had died. Murray et al first reported on a sequence variant within the leptin gene that enhances the intrinsic bioactivity of leptin, leading to reduced weight rather than obesity.[18] This sequence variant within the leptin gene is associated with delayed puberty as well.

Monogenic models for obesity in humans and experimental animals
Although more than 90% of human cases of obesity are polygenic, the recognition of monogenic variants has greatly enhanced our knowledge of the etiopathogenesis of obesity.[19] Proopiomelanocortin (POMC) and alpha–melanocyte-stimulating hormone (alpha-MSH) act centrally on the melanocortin receptor 4 (MC 4) to reduce dietary intake.[20] Genetic defects in POMC production and mutations in
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the MC4 gene are described as monogenic causes of obesity in humans.[21] Of particular interest is the fact that patients with POMC mutations tend to have red hair because of the resultant deficiency in MSH production. Also, because of their diminished levels of adrenocorticotropic hormone (ACTH), they tend to have central adrenal insufficiency. Data suggest that as many as 5% of children who are obese have MC4 or POMC mutations. If confirmed, these would be the most common identifiable genetic defects associated with obesity in humans (band 2p23 for POMC and band 18q21.3 for MC4). Ob/Ob mice were the prototypical mice that enabled the discovery of leptin. These mice lack the leptin gene and are overweight and hyperphagic. A few humans with a similar genetic defect and similar phenotypic consequences have been identified. This variant of obesity, although minor in the grand scheme of human obesity, is exquisitely sensitive to leptin injection, with reduced dietary intake and profound weight loss. (The involved band is at 7q31.) Db/Db mice have mutations of the leptin receptor in the hypothalamus. Fa/Fa mice also have leptin-receptor mutations. Like the Ob/Ob mice, these mice have early onset obesity and hyperphagia, but they also have normal or elevated leptin levels. Human counterparts of this model are rare; their conditions are associated with hyperphagia, hypogonadotropic hypogonadism, and defective thyrotropin secretion but are not associated with hypercortisolism, hyperglycemia, and hypothermia, as occurs in Db/Db mice (involvement at band 1p31). The leptin receptor belongs to the cytokine receptor families and is activated through the Janus kinases/signal transducers and activators of transcription (JAK/STAT) mechanisms. Prohormone convertase, an enzyme that is critical in protein processing, appears to be involved in the conversion of POMC to alpha-MSH. Rare patients that have been identified as having alterations in this enzyme have had clinically significant obesity, hypogonadotropic hypogonadism, and central adrenal insufficiency. This is one of the few models of obesity not associated with insulin resistance. (The involved band is 5q15-21.) PPAR-gamma is a transcription factor that is involved in adipocyte differentiation. All humans described so far with mutations of the receptor (at band 3p25) have had severe obesity.

Additional factors in obesity
In addition to the monogenic models of obesity mentioned above, genome-wide linkage analyses and microarray technology have revealed a rapidly growing list of potential obesity-susceptibility genes. Among those that are being actively studied are genes on chromosome arms 2p, 10p, 5p, 11q, and 20q. Just as Helicobacter pylori was found to be the cause of peptic ulcer disease, evolving data suggest that a notable inflammatory, and possibly infective, etiology may exist for obesity. Adipose tissue is known to be a repository of various cytokines, especially interleukin 6 and tumor necrosis factor alpha. Data have shown that adenovirus-36 infection is associated with obesity in chickens and mice. Other data suggest that, although humans who are not obese have a 5% prevalence of adenovirus-36 infection, humans who are obese have an adenovirus-36 prevalence of 20-30%. Factors to be considered in the development of obesity include the following: Metabolic factors Genetic factors level of activity Behavior Endocrine factors Race, sex, and age factors Ethnic and cultural factors Socioeconomic status Dietary habits Smoking cessation Pregnancy and menopause Psychologic factors History of gestational diabetes Lactation history in mothers

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Epidemiology
Occurrence in the United States
Approximately 100 million adults in the United States are at least overweight or obese, including approximately 35% of women and 31% of men older than age 19 years. The numbers among children are even more imposing than these figures, although the 2009-2010 NHANES updates on the US obesity prevalence rates surprisingly show a leveling-off of obesity in children.[22] Although the prevalence of obesity has steadily increased over the years, updated data indicate a potential stabilization of obesity trends in the United States.[22, 23] During the past 20 years, the prevalence of obesity and being overweight has increased sharply for adults in the United States. Data from 2 National Health and Nutrition Examination Surveys (NHANES) show that among adults aged 20-74 years, the prevalence of obesity increased from 15% (in the 1976-1980 survey) to 32.9% (in the 20032004 survey). According to the US Center for Disease Control and Prevention (CDC), after a quarter century of increases, obesity prevalence has not measurably increased in the past few years but levels are still high—in 2007, at 34% of US adults aged 20 and older.[24] The prevalence of obesity in children in the United States increased markedly between the time of the NHANES 2 and 3 trials. Approximately 20-25% of children are either overweight or obese, and the prevalence is even greater than this in some minority groups, including Pima Indians, Mexican Americans, and African Americans.[24] A study by Ludwig et al found that neighborhoods with high levels of poverty are associated with increases in the incidence of extreme obesity and diabetes. Although the mechanisms behind this association is unclear, further investigation is warranted.[25]

International occurrence
The prevalence of obesity worldwide is increasing, particularly in the industrialized nations of the Northern hemisphere, such as the United States, Canada, and most countries of Europe. Available data from the Multinational Monitoring of Trends and Determinants in Cardiovascular Disease (MONICA) project suggest that at least 15% of men and 22% of women in Europe are obese.[26, 27] Similar data now are being reported in other parts of the world, including from many developing nations. Reports from countries such as Malaysia, Japan, Australia, New Zealand, and China detail an epidemic of obesity in the past 2-3 decades. Data from the Middle Eastern countries of Bahrain, Saudi Arabia, Egypt, Jordan, Tunisia, and Lebanon, among others, indicate this same disturbing trend, with levels of obesity often exceeding 40% and being particularly worse in women than in men. Information from the Caribbean and from South America highlights similar trends. Although data from Africa on this issue are scant, a clear and distinct secular trend of profoundly increased BMIs is observed when people from Africa immigrate to the northwestern regions of the world. Comparisons of these indices among Nigerians and Ghanaians residing in their native countries with indices in recent immigrants to the United States show this trend poignantly. Conservative estimates suggest that as many as 250 million people (approximately 7% of the estimated current world population) are obese. Two to 3 times more people than this are probably overweight. Although socioeconomic class and the prevalence of obesity are negatively correlated in most industrialized countries, including the United States, this correlation is distinctly reversed in many relatively undeveloped areas, including China, Malaysia, parts of South America, and sub-Saharan Africa. Finucane et al conducted a comprehensive, constructive study that revealed growing global trends in BMI. This study may serve as wake-up call and initiate large-scale interventions in an effort to combat increasing body weight and associated adverse health consequences.[28]

Race-related demographics
Obesity is a cosmopolitan disease that affects all races worldwide. However, certain ethnic and racial groups appear to be particularly predisposed. The Pima Indians of Arizona and other ethnic groups native to North America have a particularly high prevalence of obesity. In addition, Polynesians, Micronesians, Anurans, Maoris of
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the West and East Indies, African Americans, and Hispanic populations (either Mexican or Puerto Rican in origin) in North America also have particularly high predispositions to the development of obesity. Secular trends clearly emphasize the importance of environmental factors (particularly dietary issues) in the development of obesity. In many genetically similar cohorts of the high-risk ethnic and racial groups mentioned above, the prevalence of obesity in their countries of origin is low, but this rate changes considerably when members of these groups emigrate to the affluent countries of the Northern Hemisphere, where they alter their dietary and activity habits. These findings form the core concept of the thrifty gene hypothesis that Neal and colleagues espoused.

Age-related demographics
In the United States, as previously stated, approximately 35% of women and 31% of men older than age 19 years are overweight or obese, as are approximately 20-25% of children. As evidenced in secular trends, children, and particularly adolescents, who are obese have a high probability of growing to be adults who are obese; hence, the bimodal distribution of obesity portends a large-scale obesity epidemic in the next few decades. Taller children generally tend to be more obese than shorter peers, are more insulin-resistant, and have increased leptin levels.[29] Adolescent obesity poses a serious risk for severe obesity during early adulthood, particularly in non-Hispanic black women. This would call for stronger emphasis on reduction during early adolescence specifically targeting groups with greater risk.[30]

Prognosis
The association between obesity and morbidity is not in doubt. However, the previous notion that the increased mortality and morbidity in patients who are obese was not entirely due to comorbidities was controversial. Results from several observational studies detailed by the Expert Panel on the Identification, Evaluation, and Treatment of Overweight Adults, as well as results from reports by Allison, Bray, and others, exhaustively show that obesity on its own is associated with increased cardiovascular morbidity and mortality and greater all-cause mortality.[31, 32, 33] For a person with a BMI of 25-28.9 kg/m2, the relative risk for coronary heart disease is 1.72. This risk progressively increases with an increasing BMI. Therefore, with BMIs greater than 33 kg/m2, the relative risk is 3.44. Similar trends were demonstrated in the relationship between obesity and stroke or congestive heart failure. Overall, obesity is estimated to increase the cardiovascular mortality rate 4-fold and the cancer-related mortality rate 2-fold.[34] As a group, people who are severely obese have a 6- to 12-fold increase in the all-cause mortality rate.

Morbidity and mortality
Data from insurance databases and large, prospective cohorts, such as findings from the Framingham and NHANES studies, clearly indicate that obesity is associated with a substantial increase in morbidity and mortality rates. Although the exact magnitude of the attributable excess in mortality associated with obesity (about 112,000365,000 excess deaths annually) has been disputed, obesity is indisputably the greatest preventable healthrelated cause of mortality after cigarette smoking.[31] Some evidence suggests that, if unchecked, trends in obesity in the United States may be associated with overall reduced longevity of the population in the next few years. Data also show that obesity is associated with an increased risk and duration of lifetime disability. Furthermore, obesity in middle age is associated with poor indices of quality of life at old age. The mortality data appear to have a U - or J -shaped conformation in relation to weight distribution.[35] However, the degree of obesity (generally indicated by the BMI) at which mortality discernibly increases in African Americans and Hispanic Americans is greater than in white Americans; this observation suggests a notable racial spectrum and difference in this effect Underweight was associated with substantially high risk of death in a study of Asian populations. A high BMI is also associated with an increased risk of death, except in Indians and Bangladeshis.[36]
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A study by Boggs et al found that the risk of death from any cause among black women increased with a BMI of 25 or higher, which is similar to the pattern observed among whites. Waist circumference appeared to be associated with an increased risk of death only among women who were not obese.[37] The optimal BMI in terms of life expectancy is about 23-25 for whites and 23-30 for blacks. Emerging data suggest that the ideal BMI for Asians is substantially lower than that for whites.[2] For persons with severe obesity (BMI ≥40), life expectancy is reduced by as much as 20 years in men and by about 5 years in women. Coexisting obesity and smoking are associated with even greater risks than these for premature mortality. A study by Berrington de Gonzalez et al confirmed health advantages of normal BMI (20-24.9) and reinforced that overweight and underweight lead to an increased death risk.[38] Factors that modulate the morbidity and mortality associated with obesity include the following: Age of onset and duration of obesity Severity of obesity Amount of central adiposity Other comorbidities Gender level of cardiorespiratory fitness Race

Morbidity in elderly persons
A longitudinal study by Stessman et al of more than 1000 individuals indicated that a normal BMI, rather than obesity, is associated with a higher mortality rate in elderly people. The investigators determined that a unit increase in BMI in female members of the cohort could be linked to hazard ratios (HRs) of 0.94 at age 70 years, 0.95 at age 78 years, and 0.91 at age 85 years. In men, a unit increase in BMI was associated with HRs of 0.99 at age 70 years, 0.94 at age 78 years, and 0.91 at age 85 years. According to a time-dependent analysis of 450 cohort members followed from age 70 to age 88 years, a unit increase in BMI produced an HR of 0.93 in women and in men.[39] Similar results to those in the Stessman study were found in a Japanese investigation of 26,747 older persons (aged 65-79 years at baseline). Tamakoshi et al found no elevation in all-cause mortality risk in overweight (measured as BMI 25.0-29.9 in this study) or obese (BMI ≥30.0) males; slightly elevated hazard ratios were found in women in the obese group, but not in the overweight group, in comparison with women in the mid–normal-range group. In contrast, an association was found between a low BMI and an increased risk of all-cause mortality, even among persons in the lower-normal BMI range.[40]

Patient Education
In studies among low-income families, adults and adolescents noted caloric information when reading labels.[41] However, this information did not affect food selection by adolescents or parental food selections for children. The National Health and Nutrition Examination Survey (NHANES) found that patients who received a formal diagnosis of overweight/obese from a healthcare provider demonstrated a higher rate of dietary change and/or physical activity than did persons whose overweight/obese condition remained undiagnosed. These findings are important for any clinician caring for overweight/obese patients.[24] A meta-analysis by Waters et al of 55 studies assessing educational, behavioral, and health promotion interventions in children aged 0-18 years found that these interventions reduced BMI (standardized mean difference in adiposity, 0.15 kg/m2).[42] The study concluded that child obesity prevention programs have beneficial effects. For patient education information, see the Diabetes Center, as well as Obesity, Weight Loss and Control, High Cholesterol, Cholesterol levels (Cholesterol Charts - What the Numbers Mean), and Lifestyle Cholesterol Management.

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Contributor Information and Disclosures
Author Osama Hamdy, MD, PhD, FACE Medical Director, Obesity Clinical Program, Director of Inpatient Diabetes Management, Joslin Diabetes Center; Assistant Professor of Medicine, Harvard Medical School Osama Hamdy, MD, PhD, FACE is a member of the following medical societies: American Association of Clinical Endocrinologists and American Diabetes Association Disclosure: Merck Inc Honoraria Speaking and teaching Coauthor(s) Elena Citkowitz, MD, PhD, FACP Clinical Professor of Medicine, Yale University School of Medicine; Director, Cholesterol Management Center, Director, Cardiac Rehabilitation, Department of Medicine, Hospital of St Raphael Elena Citkowitz, MD, PhD, FACP is a member of the following medical societies: American College of Physicians, American Heart Association, National Lipid Association, and Sigma Xi Disclosure: Nothing to disclose. Gabriel I Uwaifo, MD Associate Professor, Section of Endocrinology, Diabetes and Metabolism, Louisiana State University School of Medicine in New Orleans; Adjunct Professor, Joint Program on Diabetes, Endocrinology and Metabolism, Pennington Biomedical Research Center in Baton Rouge Gabriel I Uwaifo, MD is a member of the following medical societies: American Association of Clinical Endocrinologists, American College of Physicians-American Society of Internal Medicine, American Diabetes Association, American Medical Association, American Society of Hypertension, and Endocrine Society Disclosure: Nothing to disclose. Elif Arioglu, MD Assistant Professor of Medicine, Division of Endocrinology and Metabolism, University of Michigan Medical School Elif Arioglu, MD is a member of the following medical societies: American College of Physicians-American Society of Internal Medicine, American Diabetes Association, American Medical Association, and Endocrine Society Disclosure: Nothing to disclose. Chief Editor George T Griffing, MD Professor of Medicine, St Louis University School of Medicine George T Griffing, MD is a member of the following medical societies: American Association for the Advancement of Science, American College of Medical Practice Executives, American College of Physician Executives, American College of Physicians, American Diabetes Association, American Federation for Medical Research, American Heart Association, Central Society for Clinical Research, Endocrine Society, International Society for Clinical Densitometry, and Southern Society for Clinical Investigation Disclosure: Nothing to disclose. Additional Contributors Romesh Khardori, MD, PhD, FACP Former Professor, Department of Medicine, Former Chief, Division of Endocrinology, Metabolism, and Molecular Medicine, Southern Illinois University School of Medicine Romesh Khardori, MD, PhD, FACP is a member of the following medical societies: American Association of Clinical Endocrinologists, American College of Physicians, American Diabetes Association, and Endocrine Society Disclosure: Nothing to disclose. Francisco Talavera, PharmD, PhD Adjunct Assistant Professor, University of Nebraska Medical Center College of Pharmacy; Editor-in-Chief, Medscape Drug Reference
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Disclosure: Medscape Salary Employment Additional Contributors Romesh Khardori, MD, PhD, FACP Former Professor, Department of Medicine, Former Chief, Division of Endocrinology, Metabolism, and Molecular Medicine, Southern Illinois University School of Medicine Romesh Khardori, MD, PhD, FACP is a member of the following medical societies: American Association of Clinical Endocrinologists, American College of Physicians, American Diabetes Association, and Endocrine Society Disclosure: Nothing to disclose. Francisco Talavera, PharmD, PhD Adjunct Assistant Professor, University of Nebraska Medical Center College of Pharmacy; Editor-in-Chief, Medscape Drug Reference Disclosure: Medscape Salary Employment

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