- Author: Osama Hamdy, MD, PhD; Chief Editor: Romesh Khardori, MD, PhD, FACP more...
Obesity is a substantial public health crisis in the United States, and internationally, with the prevalence increasing rapidly in numerous industrialized nations. In 2009-2010, the prevalence of obesity among American men and women was almost 36%.
The image below details the comorbidities of obesity.
Signs and symptoms
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 body mass index (BMI). The WHO designations are as follows:
Grade 1 overweight (commonly and simply called overweight) - BMI of 25-29.9 kg/m 2
Grade 2 overweight (commonly called obesity) - BMI of 30-39.9 kg/m 2
Grade 3 overweight (commonly called severe or morbid obesity) - BMI ≥40 kg/m 2
Some authorities advocate a definition of obesity based on percentage of body fat, as follows:
Men - Percentage of body fat greater than 25%, with 21-25% being borderline
Women - Percentage of body fat great than 33%, with 31-33% being borderline
The clinician should also determine whether the patient has had any of the comorbidities related to obesity, including the following :
Respiratory - Obstructive sleep apnea,  greater predisposition to respiratory infections, increased incidence of bronchial asthma, and Pickwickian syndrome (obesity hypoventilation syndrome)
Malignant - Association with endometrial, prostate, colon, breast, gall bladder, and possibly lung cancer 
Psychological - Social stigmatization and depression
Cardiovascular - Coronary artery disease,  essential hypertension, left ventricular hypertrophy, cor pulmonale, obesity-associated cardiomyopathy, accelerated atherosclerosis, and pulmonary hypertension of obesity
Central nervous system (CNS) - Stroke, idiopathic intracranial hypertension, and meralgia paresthetica
Obstetric and perinatal - Pregnancy-related hypertension, fetal macrosomia, and pelvic dystocia 
Surgical - Increased surgical risk and postoperative complications, including wound infection, postoperative pneumonia, deep venous thrombosis, and pulmonary embolism
Pelvic - Stress incontinence
Gastrointestinal (GI) - Gall bladder disease (cholecystitis, cholelithiasis), nonalcoholic steatohepatitis (NASH), fatty liver infiltration, and reflux esophagitis
Orthopedic - Osteoarthritis, coxa vera, slipped capital femoral epiphyses, Blount disease and Legg-Calvé-Perthes disease, and chronic lumbago
Metabolic - Type 2 diabetes mellitus, prediabetes, metabolic syndrome, and dyslipidemia
Reproductive (in women) - Anovulation, early puberty, infertility, hyperandrogenism, and polycystic ovaries
Reproductive (in men) - Hypogonadotropic hypogonadism
Cutaneous - Intertrigo (bacterial and/or fungal), acanthosis nigricans, hirsutism, and increased risk for cellulitis and carbuncles
Extremity - Venous varicosities, lower extremity venous and/or lymphatic edema
Miscellaneous - Reduced mobility and difficulty maintaining personal hygiene
See Clinical Presentation for more detail.
Fasting lipid panel
Liver function studies
Thyroid function tests
Fasting glucose and hemoglobin A1c (HbA1c)
Evaluation of degree of body fat
BMI calculation, waist circumference, and waist/hip ratio are the common measures of the degree of body fat used in routine clinical practice. Other procedures that are used in few clinical centers include the following:
Caliper-derived measurements of skin-fold thickness
Dual-energy radiographic absorptiometry (DEXA)
Bioelectrical impedance analysis
Ultrasonography to determine fat thickness
See Workup for more detail.
Treatment of obesity starts with comprehensive lifestyle management (ie, diet, physical activity, behavior modification). The 3 major phases of any successful weight-loss program are as follows:
Preinclusion screening phase
Maintenance phase - This can conceivably last for the rest of the patient's life but ideally lasts for at least 1 year after the weight-loss program has been completed
Currently, the 3 major groups of drugs used to manage obesity are as follows:
Centrally acting medications that impair dietary intake
Medications that act peripherally to impair dietary absorption
Medications that increase energy expenditure
Among the standard bariatric procedures are the following:
Roux-en-Y gastric bypass
Adjustable gastric banding
Gastric sleeve surgery
Vertical sleeve gastrectomy
See Treatment and Medication for more detail.
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 Pathophysiology and Etiology.)
The annual cost of managing obesity in the United States alone amounts to approximately $190.2 billion per year, or 20.6% of national health expenditures, according to a recent study. Compared with a nonobese person, an obese person incurs $2741 more in medical costs (in 2005 dollars) annually. In addition, the annual cost of lost productivity due to obesity is approximately $73.1 billion, and almost $121 billion is spent annually on weight-loss products and services. (See Treatment and Medication.)
For information on pediatric obesity, see Obesity in Children.
Measurements of obesity
Obesity represents a state of excess storage of body fat. Although similar, the term overweight is puristically defined as an excess of 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%. However, because differences in weight among individuals are only partly the result of 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 percentage to define obesity. In general, BMI correlates closely with the degree of body fat in most settings; however, this correlation is weaker at low BMIs.
An individual’s BMI is calculated as weight/height2, with weight being in kilograms and height being in meters (otherwise, the equation is weight in pounds ´ 0.703/height in inches2). Online BMI calculators are available.
A person’s 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 typically correlates closely with percentage body fat in a curvilinear fashion, some important caveats apply to its interpretation. In mesomorphic (muscular) persons, BMIs that usually indicate overweight or mild obesity may be spurious, whereas in some persons with sarcopenia (eg, elderly individuals and persons of Asian descent, particularly from South Asia), a typically normal BMI may conceal underlying excess adiposity characterized by an increased percentage of fat mass and reduced muscle mass.
In view of these limitations, some authorities advocate a definition of obesity based on percentage of 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. Skinfold measurements are the least accurate means by which to assess obesity.
Dual-energy radiographic absorptiometry (DXA) scanning is used primarily by researchers to accurately measure body composition, particularly fat mass and fat-free mass. It has the additional advantage of measuring regional fat distribution. However, DXA scans cannot be used to distinguish between subcutaneous and visceral abdominal fat deposits.
The current standard techniques for measuring visceral fat volume are abdominal computed tomography (CT) scanning (at L4-L5) and magnetic resonance imaging (MRI) techniques. A simpler technique, using bioelectrical impedance, was recently introduced. However, 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/m 2
Grade 2 overweight (commonly called obesity) - BMI of 30-39.9 kg/m 2
Grade 3 overweight (commonly called severe or morbid obesity) - BMI greater than or equal to 40 kg/m 2
The cut-off for each grade varies according to an individual’s ethnic background. For example, a BMI of 23 kg/m2 or higher may define grade 1 overweight and 27.5 kg/m2 or higher may define grade 2 overweight (obesity) in many Asian populations, in which the risk was shown to be high and extremely high for grade 1 and 2 overweight at these levels, respectively. Other BMI cutoffs identified as potential public health action points in these populations are 32.5 and 37.5 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/m 2
Morbid obesity - BMI of 40-50 kg/m 2
Super obese - BMI greater than 50 kg/m 2
In children, a BMI above the 85th percentile (for age-matched and sex-matched control subjects) is commonly used to define overweight, and a BMI above the 95th percentile is commonly used to define obesity.
Comorbidities associated with obesity
Obesity is associated with a host of potential comorbidities that significantly increase the risk of morbidity and mortality in obese individuals. Although no cause-and-effect relationship has been clearly 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.)
Apart from total body fat mass, the following aspects of obesity have been associated with comorbidity:
Age of obesity onset
Accumulating data suggest that regional fat distribution substantially affects the incidence of comorbidities associated with obesity. Android obesity, in which adiposity is predominantly abdominal (including visceral and, to a lesser extent, subcutaneous), is strongly correlated with worsened metabolic and clinical consequences of obesity.
The thresholds used in the National Cholesterol Education Program Adult Treatment Panel III definition of metabolic syndrome state that significantly increased cardiovascular risk (metabolic central obesity) exists in men with waist circumferences of greater than 94 cm (37 in) and in women with waist circumferences of greater than 80 cm (31.5 in), as well as waist-to-hip ratios of greater than 0.95 in men and of greater than 0.8 in women. Circumferences of 102 cm (40 in) in men and 88 cm (35 in) in women indicate a markedly increased risk requiring urgent therapeutic intervention.
These thresholds are much lower in Asian populations. After analyzing survey results of Chinese, Malay, and Asian-Indian cohorts, Tan and colleagues concluded that a waist circumference of greater than 90 cm in men and of more than 80 cm in women were more appropriate criteria for metabolic central obesity in these ethnic groups.
Age of obesity onset
An elevated BMI during adolescence (starting within the range currently considered normal) is strongly associated with the risk of developing obesity-related disorders later in life, independent of adult BMI. Increases in BMI during early adulthood (age 25-40 y) are associated with a worse profile of biomarkers related to obesity than are BMI increases during later adulthood. 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 kg/m2) and is espoused by bariatric surgeons.
Findings from bariatric surgery and animal models suggest that this pressure elevation may play a role (potentially a major one) in the pathogenesis of comorbidities of obesity, such as the following :
Lower-limb circulatory stasis
Possibly, hypertension and nephrotic syndrome
Overweight and obese individuals are at increased risk for the following health conditions:
Type 2 diabetes
Coronary heart disease
Non-alcoholic fatty liver disease (NAFLD)
Infertility (women) and erectile dysfunction (men)
Risk of stillbirth [21, 22]
Gall bladder disease
Obstructive sleep apnea
Gastroesophageal reflux disease (GERD)
Some cancers (endometrial, breast, and colon)
A study by Abdullah et al indicated that not only the severity of a patient’s obesity but its duration as well is associated with the individual’s risk of developing type 2 diabetes mellitus. Based on a more than four decade follow-up of 5132 participants in the Framingham Offspring Study, the investigators found a significant rise in type 2 diabetes risk as obese-years increased.
A study by Losina et al found that obesity with knee osteoarthritis resulted in the loss of a substantial number of quality-adjusted life years. The association was most notable among black and Hispanic women.
Some reports, including those by Adelman and colleagues and by Kasiske and Jennette, suggest an association between severe obesity and focal glomerulosclerosis.[25, 26, 27] This complication, in particular, improves substantially or resolves soon after bariatric surgery, well before clinically significant weight loss is achieved.
The so-called Pickwickian syndrome is a combined syndrome of obesity-related hypoventilation and sleep apnea. It is named after Charles Dickens’s novel The Pickwick Papers, which contains an obese character who falls asleep constantly during the day.
The hypoventilation in Pickwickian syndrome results from severe mechanical respiratory limitations to chest excursion, caused by severe obesity. The sleep apnea 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).
Increased and decreased sleep duration
Sleep duration of less than 5 hours or more than 8 hours was associated with increased visceral and subcutaneous body fat, in a study of young African Americans and Hispanic Americans. This association relates mostly to decreased leptin hormone and increased ghrelin hormone levels.
Hypertrophic versus hypercellular obesity
The adipocyte, which is the cellular basis for obesity, may be increased in size or number in obese persons. Hypertrophic obesity, characterized by enlarged fat cells, is typical of android abdominal obesity. Hypercellular obesity is more variable than hypertrophic obesity; it typically occurs in persons who develop obesity in childhood or adolescence, but it is also invariably found in subjects with severe obesity.
Hypertrophic obesity usually starts in adulthood, is associated with increased cardiovascular risk, and responds quickly to weight reduction measures. In contrast, patients with hypercellular obesity may find it difficult to lose weight through nonsurgical interventions.
The adipocyte is increasingly found to be a complex and metabolically active cell. At present, the adipocyte is perceived as an active endocrine gland producing several peptides and metabolites that may be relevant to the control of body weight; these are being studied intensively.
Many of the adipocytokines secreted by adipocytes are proinflammatory or play a role in blood coagulation. Others are involved in insulin sensitivity and appetite regulation. However, the function of many of these identified cytokines remains unknown or unclear.
Proinflammatory products of the adipocyte include the following :
Tumor necrosis factor–alpha
Monocyte chemoattractant protein–1 (MCP-1)
Other adipocyte products include the following :
Plasminogen activator inhibitor-1 (PAI-1) - Associated with cardiovascular risk
Adipocyte lipid-binding protein
Prostaglandins - Coagulation role
Leptin - Appetite regulator
Adiponectin - Major role in insulin sensitivity
Phospholipid transfer protein
Metabolism and function
Critical enzymes involved in adipocyte metabolism and function include the following:
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
In addition, a cascade of enzymes is involved in 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. The recognition that this process occurs in white and brown adipose tissue, even in adults, has increased its potential importance in the development of obesity and the relapse to obesity after weight loss.
Among the identified elements in this process are the following transcription factors:
Peroxisome proliferator-activated receptor–gamma (PPAR-gamma)
Retinoid-X receptor ligands
Adipocyte differentiation–related protein (ADRP)
CCAAT/enhancer-binding proteins (C/EBP) alpha, beta, and delta
PPAR-gamma agonists increase the recruitment, proliferation, and differentiation of preadipocytes (healthy fat) and cause apoptosis of hypertrophic and dysfunctional adipocytes (including visceral fat). This results in improved fat function and improved metabolic parameters associated with excessive fat–related metabolic diseases (EFRMD), including type 2 diabetes mellitus, hypertension, and dyslipidemia.
Hormonal influences on appetite
In addition to neurotransmitters and neurogenic signals, many hormones 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.
Odor detection threshold
Smell plays an important role in feeding behavior. Differences in the odor detection threshold (ie, the lowest concentration of a substance detectable by the human olfactory sense) were found in a study that measured thresholds in 8 lean, fasted individuals before and during a 2-hour hyperinsulinemic euglycemic insulin clamp.
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 clinical interest as a possible factor in the pathogenesis of obesity.
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. 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.
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. Potentially, leptin sensitizers may assist in changing feeding habits.
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, preventing 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 are instead leptin resistant. Therefore, they have elevated levels of circulating leptin. Leptin levels are higher in women than in men and are strongly correlated with BMI.
Patients with night-eating syndrome have attenuation of the nocturnal rise in plasma melatonin and leptin levels and higher circadian levels of plasma cortisol. These individuals have morning anorexia, evening hyperphagia, and insomnia. In one study, patients with night-eating syndrome averaged 3.6 awakenings per night; 52% of these awakenings were associated with food intake, with a mean intake per ingestion of 1134 kcal.
Mutations resulting in defects of the leptin receptor in the hypothalamus may occur. These mutations result in early onset obesity and hyperphagia despite normal or elevated leptin levels, along with hypogonadotropic hypogonadism, and defective thyrotropin secretion.
Murray et al first reported on a sequence variant within the leptin gene that enhances the intrinsic bioactivity of leptin, but which was associated with reduced weight rather than obesity. This sequence variant within the leptin gene is also associated with delayed puberty.
The etiology of obesity is far more complex than simply an imbalance between energy intake and energy output. Although this view allows easy conceptualization of the various mechanisms involved in the development of obesity, obesity is far more than simply the result of eating too much and/or exercising too little (see the energy-balance equation, below). Possible factors in the development of obesity include the following:
Level of activity
Race, sex, and age factors
Ethnic and cultural factors
Pregnancy and menopause
History of gestational diabetes
Nevertheless, the prevalence of inactivity in industrialized countries is considerable and relevant to the rise in obesity. In the United States, less than half of all adults meet the federal 2008 Physical Activity Guidelines, and fewer than 3 in 10 high school students get at least 60 minutes of physical activity every day.
A study by Maripuu et al indicated that hypercortisolism associated with recurrent affective disorders increases the risk for metabolic disorders and cardiovascular risk factors such as obesity, overweight, large waist, high low-density lipoprotein (LDL) levels, and low high-density lipoprotein (HDL) levels. The study included 245 patients with recurrent depression or bipolar disorder and 258 controls.
Two major groups of factors, genetic and environmental, have a balance that variably intertwines in the development of obesity. Genetic factors are presumed to explain 40-70% of the variance in obesity, within a limited range of BMI (18-30 kg/m2).
A study in which monozygotic twins were overfed by 1000 kcal per day, 6 days a week, over a 100-day period found that the amount of weight gain varied significantly between pairs (4.3 to 13.3 kg). However, the similarity within each pair was significant with respect to body weight, percentage of fat, fat mass, and estimated subcutaneous fat, with about 3 times more variance among pairs than within them. This observation indicates that genetic factors are significantly involved and may govern the tendency to store energy.
The strong heritability of obesity has been demonstrated in several twin and adoptee studies, in which obese individuals who were reared separately followed the same weight pattern as that of their biological parents and their identical twin. Metabolic rate, spontaneous physical activity, and thermic response to food seem to be heritable to a variable extent.
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, having an obese mother and a healthy-weight father was not associated with an increased risk of obesity in childhood. This discrepancy suggests a role for epigenetic factors in hereditary risk.
Genetic susceptibility loci
Rarely, obesity may be caused by a single gene, but much more commonly it is a complex interplay of susceptibility loci and environmental factors. Genome-wide association studies (GWAS) have found a robust number of genetic susceptibility loci associated with obesity. A single-nucleotide polymorphism (SNP) in the FTO (fat mass and obesity associated) gene and SNPs near the MC4R (melanocortin 4 receptor) gene have been highly associated with BMI.[41, 42, 43, 44]
Although many genetic susceptibility loci have been discovered, the effect sizes of the established loci are small, and combined they explain only a fraction of the variation in BMI between individuals. Their low predictive value means that they have limited value in clinical medicine. Moreover, the fact that increases in the rate of obesity over the last few decades have coincided with changes in dietary habits and activity suggests an important role for environmental factors.
Monogenic models for obesity in humans and experimental animals
More than 90% of human cases of obesity are thought to be multifactorial. Nevertheless, the recognition of monogenic variants has greatly enhanced knowledge of the etiopathogenesis of obesity. As previously mentioned, 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.
POMC and MC4
Proopiomelanocortin (POMC) is converted into alpha–melanocyte-stimulating hormone (alpha-MSH), which acts centrally on the melanocortin receptor 4 (MC 4) to reduce dietary intake. Genetic defects in POMC production and mutations in the MC4 gene are described as monogenic causes of obesity in humans.
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 up to 5% of children who are morbidly 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).
Rare cases of humans with congenital leptin deficiency caused by mutations in the leptin gene have been identified. (The involved band is at 7q31.) The disorder is autosomal recessive and manifested by severe obesity and hyperphagia accompanied by metabolic, neuroendocrine, and immune dysfunction. It is exquisitely sensitive to leptin injection, with reduced dietary intake and profound weight loss.
Prohormone convertase, an enzyme that is critical in protein processing, appears to be involved in the conversion of POMC to alpha-MSH. Rare patients with 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.
PPAR-gamma is a transcription factor that is involved in adipocyte differentiation. All humans with mutations of the receptor (at band 3p25) described so far have had severe obesity.
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. One study showed an association between obesity and a high-normal level of plasma procalcitonin, a dependent variable that reflects a state of distress or inflammation.
Data have shown that adenovirus-36 infection is associated with obesity in chickens and mice. In human studies, the prevalence of adenovirus-36 infection is 20-30% in people who are obese, versus 5% in people who are not obese. Despite these provocative findings, the roles of infection and inflammation in the pathogenesis of obesity remain unclear.
United States statistics
Approximately 78 million adults above age 20 (37.5 million men and 40.6 million women) and 12.5 million children and adolescents (5.5 million boys and 7 million girls) in the United States are obese. In 2009-2010, the prevalence of obesity among men and women was almost 36%. The prevalence in children and adolescents was 16.9%. Approximately 20-25% of children are either overweight or obese, and the prevalence is even greater in some minority groups, including Pima Indians, Mexican Americans, and African Americans.
During the past several decades, the prevalence of obesity and 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 2003-2004 survey. Data from the past few years, however, indicate a potential stabilization of obesity trends in adults and children.[2, 52, 53]
Overweight and obesity were associated with nearly 1 in 5 deaths (18.2%) among adults in the United States from 1986 through 2006, according to a study published in the American Journal of Public Health.[54, 55] Previous research has likely underestimated obesity’s impact on US mortality.
Obesity appeared to have a particularly strong effect among black women, with 26.8% of deaths associated with a BMI of 25 kg/m2 or higher.[54, 55] In white women, 21.7% of deaths were associated with overweight or obesity. Among black men, 5.0% of deaths were associated with overweight or obesity, and among white men, 15.6% were. Data also show the more recent the birth year, the greater effect obesity has on mortality rates.[54, 55]
The researchers used data from 19 consecutive waves of the National Health Interview Survey covering 1986 through 2004 and linked those data with mortality information in the National Death Index through 2006.[54, 55] This study is the first to account for differences in age, birth cohort, sex, and race in analyzing Americans’ risk for death from obesity.
A randomized trial by Ludwig et al found that low-income persons who were assigned to live in higher-income neighborhoods gained less weight over time and had a lower risk of diabetes than did low-income persons who remained in predominantly low-income neighborhoods. The mechanisms behind this association are unclear, and further investigation is warranted.
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.[57, 58]
Similar data 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 have detailed 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%.
Internationally, rates of obesity are higher in women than in men. A somewhat higher rate would be expected, given the biologically higher percentage of body fat in women.
Information from the Caribbean and from South America highlights similar trends. Although data from Africa are scant, a clear and distinct secular trend of profoundly increased BMIs is observed when people from Africa emigrate 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.
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, Pacific islanders (eg, Polynesians, Micronesians, Maoris), 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 high-risk ethnic and racial groups, the prevalence of obesity in their countries of origin is low but rises considerably when members of these groups emigrate to the affluent countries of the Northern Hemisphere, where they alter their dietary habits and activities. These findings form the core concept of the thrifty gene hypothesis espoused by Neel and colleagues.
The thrifty gene hypothesis posits that human evolution favored individuals who were more efficient at storing energy during times of food shortage and that this historic evolutionary advantage is now a disadvantage during a time of abundant food availability.
Children, particularly adolescents, who are obese have a high probability of becoming 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.
Adolescent obesity poses a serious risk for severe obesity during early adulthood, particularly in non-Hispanic black women. This calls for a stronger emphasis on weight reduction during early adolescence, specifically targeting groups at greater risk.
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.
The adverse consequences of obesity may be attributed in part to comorbidities, but 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.[63, 64, 65]
For a person with a BMI of 25-28.9 kg/m2, the relative risk for coronary heart disease is 1.72. The risk progressively increases with an increasing BMI; with BMIs greater than 33 kg/m2, the relative risk is 3.44. Similar trends have been demonstrated in the relationship between obesity and stroke or chronic heart failure.
Overall, obesity is estimated to increase the cardiovascular mortality rate 4-fold and the cancer-related mortality rate 2-fold. As a group, people who are severely obese have a 6- to 12-fold increase in the all-cause mortality rate. Although the exact magnitude of the attributable excess in mortality associated with obesity (about 112,000-365,000 excess deaths annually) has been disputed, obesity is indisputably the greatest preventable health-related cause of mortality after cigarette smoking.
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. The greater reduction in life expectancy for men is consistent with the higher prevalence of android (ie, predominantly abdominal) obesity and the biologically higher percent body fat in women. The risk of premature mortality is even greater in obese persons who smoke.
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 near future. 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 in old age.
The mortality data appear to have a U - or J -shaped conformation in relation to weight distribution. Underweight was associated with substantially high risk of death in a study of Asian populations, and a high BMI is also associated with an increased risk of death, except in Indians and Bangladeshis. A study in whites found that all-cause mortality is generally lowest with a BMI of 20-24.9 and reinforced that overweight and underweight lead to an increased risk of death.
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. 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.
On the other hand, 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 in nonobese women.
Stated another way, individuals who have abdominal obesity (elevated waist circumference) are at risk for obesity-related health complications. Most individuals with a BMI of over 25 and essentially all persons with a BMI of more than 30 have abdominal obesity.
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
level of cardiorespiratory fitness
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.
Similar results were found in a Japanese study of 26,747 older persons (aged 65-79 years at baseline). Tamakoshi et al found no elevation in all-cause mortality risk in overweight (BMI 25.0-29.9) or obese (BMI ≥30.0) men; slightly elevated hazard ratios were found in women in the obese group, but not in the overweight group, compared 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.
Most individuals are able to attain weight loss in the short term, but weight regain is unfortunately a common pattern. On average, participants in nonsurgical weight-management programs lose approximately 10% of their initial body weight over 12-24 weeks, but the majority regain two thirds of the weight lost within a year.
Old data indicated that 90-95% of the weight lost is regained in 5 years. Recent data show that more intensive and structured nonsurgical weight management may help a significant number of patients to maintain most of the weight lost for up to 4 years.
In the Look AHEAD study, 887 of 2570 participants (34.5%) in the intensive lifestyle group lost at least 10% of their weight at year 1. Of these, 374 (42.2%) maintained this loss at year 4 and another 17% maintained 7-10% weight loss at 4 years. More than 45% of all intensive lifestyle participants had achieved and maintained a clinically significant weight loss (≥ 5%) at 4 years.
In studies among low-income families, adults and adolescents noted caloric information when reading labels. However, this information did not affect food selection by adolescents or parental food selections for children.
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.
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). The study concluded that child obesity prevention programs have beneficial effects.
For patient education information, see the Diabetes Health Center and Metabolic Syndrome Health Center, as well as Obesity, Weight Loss and Control, High Cholesterol, Cholesterol Charts (What the Numbers Mean), and Lifestyle Cholesterol Management.
Roundtable on Obesity Solutions, Food and Nutrition Board, Health and Medicine Division, National Academies of Sciences, Engineering, and Medicine. Obesity in the Early Childhood Years: State of the Science and Implementation of Promising Solutions: Workshop Summary. 2016 May 23. Available at http://www.ncbi.nlm.nih.gov/books/NBK368372/.
Flegal KM, Carroll MD, Kit BK, Ogden CL. Prevalence of obesity and trends in the distribution of body mass index among US adults, 1999-2010. JAMA. 2012 Feb 1. 307(5):491-7. [Medline].
Wijga AH, Scholtens S, Bemelmans WJ, de Jongste JC, Kerkhof M, Schipper M, et al. Comorbidities of obesity in school children: a cross-sectional study in the PIAMA birth cohort. BMC Public Health. 2010 Apr 9. 10:184. [Medline]. [Full Text].
Li C, Ford ES, Zhao G, Croft JB, Balluz LS, Mokdad AH. Prevalence of self-reported clinically diagnosed sleep apnea according to obesity status in men and women: National Health and Nutrition Examination Survey, 2005-2006. Prev Med. 2010 Jul. 51(1):18-23. [Medline].
Jiao L, Berrington de Gonzalez A, Hartge P, Pfeiffer RM, Park Y, Freedman DM, et al. Body mass index, effect modifiers, and risk of pancreatic cancer: a pooled study of seven prospective cohorts. Cancer Causes Control. 2010 Aug. 21(8):1305-14. [Medline]. [Full Text].
Oreopoulos A, Padwal R, McAlister FA, Ezekowitz J, Sharma AM, Kalantar-Zadeh K, et al. Association between obesity and health-related quality of life in patients with coronary artery disease. Int J Obes (Lond). 2010 Sep. 34(9):1434-41. [Medline].
Galtier-Dereure F, Boegner C, Bringer J. Obesity and pregnancy: complications and cost. Am J Clin Nutr. 2000 May. 71(5 Suppl):1242S-8S. [Medline].
Wadden TA, Webb VL, Moran CH, Bailer BA. Lifestyle modification for obesity: new developments in diet, physical activity, and behavior therapy. Circulation. 2012 Mar 6. 125(9):1157-70. [Medline]. [Full Text].
Cawley J, Meyerhoefer C. The medical care costs of obesity: an instrumental variables approach. J Health Econ. 2012 Jan. 31(1):219-30. [Medline].
Finkelstein EA, DiBonaventura Md, Burgess SM, Hale BC. The costs of obesity in the workplace. J Occup Environ Med. 2010 Oct. 52(10):971-6. [Medline].
Weight Loss Markets for Products and Services. BCC Research. Available at http://www.bccresearch.com/report/weight-loss-markets-products-services-fod027c.html. Accessed: April 23, 2012.
Gallagher D, Heymsfield SB, Heo M, Jebb SA, Murgatroyd PR, Sakamoto Y. Healthy percentage body fat ranges: an approach for developing guidelines based on body mass index. Am J Clin Nutr. 2000 Sep. 72(3):694-701. [Medline].
Ward LC. Segmental bioelectrical impedance analysis: an update. Curr Opin Clin Nutr Metab Care. 2012 Sep. 15(5):424-9. [Medline].
Shiwaku K, Anuurad E, Enkhmaa B, Kitajima K, Yamane Y. Appropriate BMI for Asian populations. Lancet. 2004 Mar 27. 363(9414):1077. [Medline].
Grundy SM, Brewer HB Jr, Cleeman JI, Smith SC Jr, Lenfant C. Definition of metabolic syndrome: Report of the National Heart, Lung, and Blood Institute/American Heart Association conference on scientific issues related to definition. Circulation. 2004 Jan 27. 109(3):433-8. [Medline]. [Full Text].
Tan CE, Ma S, Wai D, Chew SK, Tai ES. Can we apply the National Cholesterol Education Program Adult Treatment Panel definition of the metabolic syndrome to Asians?. Diabetes Care. 2004 May. 27(5):1182-6. [Medline]. [Full Text].
Tirosh A, Shai I, Afek A, Dubnov-Raz G, Ayalon N, Gordon B, et al. Adolescent BMI trajectory and risk of diabetes versus coronary disease. N Engl J Med. 2011 Apr 7. 364(14):1315-25. [Medline].
Montonen J, Boeing H, Schleicher E, Fritsche A, Pischon T. Association of changes in body mass index during earlier adulthood and later adulthood with circulating obesity biomarker concentrations in middle-aged men and women. Diabetologia. 2011 Jul. 54(7):1676-83. [Medline].
Sugerman HJ, Kellum JM, Engle KM, Wolfe L, Starkey JV, Birkenhauer R, et al. Gastric bypass for treating severe obesity. Am J Clin Nutr. 1992 Feb. 55(2 Suppl):560S-566S. [Medline].
Sugerman HJ. Effects of increased intra-abdominal pressure in severe obesity. Surg Clin North Am. 2001 Oct. 81(5):1063-75, vi. [Medline].
Yao R, Ananth CV, Park BY, Pereira L, Plante LA, for the Perinatal Research Consortium. Obesity and the risk of stillbirth: a population-based cohort study [abstract]. Presented at: The 2014 SMFM Annual Meeting; February 3-8, 2014; New Orleans, LA. Am J Obstet Gynecol. 2014. 210:[Full Text].
Hackethal V. Obese women may have 25% increased risk for stillbirth. Medscape Medical News. March 27, 2014. [Full Text].
Abdullah A, Amin FA, Hanum F, et al. Estimating the risk of type-2 diabetes using obese-years in a contemporary population of the Framingham Study. Glob Health Action. 2016. 9:30421. [Medline].
Losina E, Walensky RP, Reichmann WM, Holt HL, Gerlovin H, Solomon DH, et al. Impact of obesity and knee osteoarthritis on morbidity and mortality in older Americans. Ann Intern Med. 2011 Feb 15. 154(4):217-26. [Medline].
Adelman RD, Restaino IG, Alon US, Blowey DL. Proteinuria and focal segmental glomerulosclerosis in severely obese adolescents. J Pediatr. 2001 Apr. 138(4):481-5. [Medline].
Kasiske BL, Napier J. Glomerular sclerosis in patients with massive obesity. Am J Nephrol. 1985. 5(1):45-50. [Medline].
Jennette JC, Charles L, Grubb W. Glomerulomegaly and focal segmental glomerulosclerosis associated with obesity and sleep-apnea syndrome. Am J Kidney Dis. 1987 Dec. 10(6):470-2. [Medline].
Hairston KG, Bryer-Ash M, Norris JM, Haffner S, Bowden DW, Wagenknecht LE. Sleep duration and five-year abdominal fat accumulation in a minority cohort: the IRAS family study. Sleep. 2010 Mar. 33(3):289-95. [Medline]. [Full Text].
Spiegel K, Tasali E, Penev P, Van Cauter E. Brief communication: Sleep curtailment in healthy young men is associated with decreased leptin levels, elevated ghrelin levels, and increased hunger and appetite. Ann Intern Med. 2004 Dec 7. 141(11):846-50. [Medline].
Martinelli CE, Keogh JM, Greenfield JR, Henning E, van der Klaauw AA, Blackwood A, et al. Obesity due to melanocortin 4 receptor (MC4R) deficiency is associated with increased linear growth and final height, fasting hyperinsulinemia, and incompletely suppressed growth hormone secretion. J Clin Endocrinol Metab. 2011 Jan. 96(1):E181-8. [Medline].
Hamdy O. The role of adipose tissue as an endocrine gland. Curr Diab Rep. 2005 Oct. 5(5):317-9. [Medline].
Bays H, Blonde L, Rosenson R. Adiposopathy: how do diet, exercise and weight loss drug therapies improve metabolic disease in overweight patients?. Expert Rev Cardiovasc Ther. 2006 Nov. 4(6):871-95. [Medline].
Ketterer C, Heni M, Thamer C, Herzberg-Schäfer SA, Häring HU, Fritsche A. Acute, short-term hyperinsulinemia increases olfactory threshold in healthy subjects. Int J Obes (Lond). 2011 Aug. 35(8):1135-8. [Medline].
Lieb W, Sullivan LM, Harris TB, Roubenoff R, Benjamin EJ, Levy D, et al. Plasma leptin levels and incidence of heart failure, cardiovascular disease, and total mortality in elderly individuals. Diabetes Care. 2009 Apr. 32(4):612-6. [Medline]. [Full Text].
Birketvedt GS, Florholmen J, Sundsfjord J, Osterud B, Dinges D, Bilker W, et al. Behavioral and neuroendocrine characteristics of the night-eating syndrome. JAMA. 1999 Aug 18. 282(7):657-63. [Medline].
Murray PG, Read A, Banerjee I, Whatmore AJ, Pritchard LE, Davies RA, et al. Reduced appetite and body mass index with delayed puberty in a mother and son: association with a rare novel sequence variant in the leptin gene. Eur J Endocrinol. 2011 Apr. 164(4):521-7. [Medline].
Physical Activity: Facts about Physical Activity. Centers for Disease Control and Prevention. Available at http://www.cdc.gov/physicalactivity/data/facts.html. Accessed: January 9, 2013.
Maripuu M, Wikgren M, Karling P, Adolfsson R, Norrback KF. Relative hypocortisolism is associated with obesity and the metabolic syndrome in recurrent affective disorders. J Affect Disord. 2016 Jun 21. 204:187-196. [Medline].
Bouchard C, Tremblay A, Després JP, Nadeau A, Lupien PJ, Thériault G, et al. The response to long-term overfeeding in identical twins. N Engl J Med. 1990 May 24. 322(21):1477-82. [Medline].
Freeman E, Fletcher R, Collins CE, et al. Preventing and treating childhood obesity: time to target fathers. Int J Obes (Lond). 2012 Jan. 36(1):12-5. [Medline].
Chambers JC, Elliott P, Zabaneh D, Zhang W, Li Y, Froguel P, et al. Common genetic variation near MC4R is associated with waist circumference and insulin resistance. Nat Genet. 2008 Jun. 40(6):716-8. [Medline].
Frayling TM, Ong K. Piecing together the FTO jigsaw. Genome Biol. 2011. 12(2):104. [Medline]. [Full Text].
Loos RJ, Lindgren CM, Li S, Wheeler E, Zhao JH, Prokopenko I, et al. Common variants near MC4R are associated with fat mass, weight and risk of obesity. Nat Genet. 2008 Jun. 40(6):768-75. [Medline]. [Full Text].
Scuteri A, Sanna S, Chen WM, Uda M, Albai G, Strait J, et al. Genome-wide association scan shows genetic variants in the FTO gene are associated with obesity-related traits. PLoS Genet. 2007 Jul. 3(7):e115. [Medline]. [Full Text].
Day FR, Loos RJ. Developments in obesity genetics in the era of genome-wide association studies. J Nutrigenet Nutrigenomics. 2011. 4(4):222-38. [Medline].
Reinehr T, Kleber M, de Sousa G, et al. Leptin concentrations are a predictor of overweight reduction in a lifestyle intervention. Int J Pediatr Obes. May 13 2009;1-9:[Medline].
Cummings DE, Schwartz MW. Melanocortins and body weight: a tale of two receptors. Nat Genet. 2000 Sep. 26(1):8-9. [Medline].
Vaisse C, Clement K, Durand E, Hercberg S, Guy-Grand B, Froguel P. Melanocortin-4 receptor mutations are a frequent and heterogeneous cause of morbid obesity. J Clin Invest. 2000 Jul. 106(2):253-62. [Medline]. [Full Text].
Wardlaw SL. Clinical review 127: Obesity as a neuroendocrine disease: lessons to be learned from proopiomelanocortin and melanocortin receptor mutations in mice and men. J Clin Endocrinol Metab. 2001 Apr. 86(4):1442-6. [Medline].
Gibson WT, Farooqi IS, Moreau M, DePaoli AM, Lawrence E, O'Rahilly S, et al. Congenital leptin deficiency due to homozygosity for the Delta133G mutation: report of another case and evaluation of response to four years of leptin therapy. J Clin Endocrinol Metab. 2004 Oct. 89(10):4821-6. [Medline].
Abbasi A, Corpeleijn E, Postmus D, Gansevoort RT, de Jong PE, Gans RO, et al. Plasma procalcitonin is associated with obesity, insulin resistance, and the metabolic syndrome. J Clin Endocrinol Metab. 2010 Sep. 95(9):E26-31. [Medline].
Yaemsiri S, Slining MM, Agarwal SK. Perceived weight status, overweight diagnosis, and weight control among US adults: the NHANES 2003-2008 Study. Int J Obes (Lond). 2011 Aug. 35(8):1063-70. [Medline].
Ogden CL, Carroll MD, Kit BK, Flegal KM. Prevalence of obesity and trends in body mass index among US children and adolescents, 1999-2010. JAMA. 2012 Feb 1. 307(5):483-90. [Medline].
Laidman J. Obesity's Toll: 1 in 5 Deaths Linked to Excess Weight. Medscape Medical News. Available at http://www.medscape.com/viewarticle/809516. Accessed: August 21, 2013.
Masters RK, Reither EN, Powers DA, Yang YC, Burger AE, Link BG. The Impact of Obesity on US Mortality Levels: The Importance of Age and Cohort Factors in Population Estimates. Am J Public Health. 2013 Aug 15.
Ludwig J, Sanbonmatsu L, Gennetian L, et al. Neighborhoods, obesity, and diabetes--a randomized social experiment. N Engl J Med. 2011 Oct 20. 365(16):1509-19. [Medline].
Molarius A, Seidell JC, Sans S, Tuomilehto J, Kuulasmaa K. Varying sensitivity of waist action levels to identify subjects with overweight or obesity in 19 populations of the WHO MONICA Project. J Clin Epidemiol. 1999 Dec. 52(12):1213-24. [Medline].
Molarius A, Seidell JC, Sans S, Tuomilehto J, Kuulasmaa K. Waist and hip circumferences, and waist-hip ratio in 19 populations of the WHO MONICA Project. Int J Obes Relat Metab Disord. 1999 Feb. 23(2):116-25. [Medline].
Finucane MM, Stevens GA, Cowan MJ, Danaei G, Lin JK, Paciorek CJ, et al. National, regional, and global trends in body-mass index since 1980: systematic analysis of health examination surveys and epidemiological studies with 960 country-years and 9·1 million participants. Lancet. 2011 Feb 12. 377(9765):557-67. [Medline].
Neel JV. The "thrifty genotype" in 1998. Nutr Rev. 1999 May. 57(5 Pt 2):S2-9. [Medline].
Metcalf BS, Hosking J, Frémeaux AE, Jeffery AN, Voss LD, Wilkin TJ. BMI was right all along: taller children really are fatter (implications of making childhood BMI independent of height) EarlyBird 48. Int J Obes (Lond). 2011 Apr. 35(4):541-7. [Medline].
The NS, Suchindran C, North KE, Popkin BM, Gordon-Larsen P. Association of adolescent obesity with risk of severe obesity in adulthood. JAMA. 2010 Nov 10. 304(18):2042-7. [Medline]. [Full Text].
Allison DB, Fontaine KR, Manson JE, Stevens J, VanItallie TB. Annual deaths attributable to obesity in the United States. JAMA. 1999 Oct 27. 282(16):1530-8. [Medline].
[Guideline] Expert Panel on the Identification, Evaluation, and Treatment of Overweight Adults. Clinical guidelines on the identification, evaluation, and treatment of overweight and obesity in adults: executive summary. Expert Panel on the Identification, Evaluation, and Treatment of Overweight in Adults. Am J Clin Nutr. 1998 Oct. 68(4):899-917. [Medline].
Bray GA. Health hazards of obesity. Endocrinol Metab Clin North Am. 1996 Dec. 25(4):907-19. [Medline].
Flegal KM, Graubard BI, Williamson DF, Gail MH. Excess deaths associated with underweight, overweight, and obesity. JAMA. 2005 Apr 20. 293(15):1861-7. [Medline].
Zheng W, McLerran DF, Rolland B, Zhang X, Inoue M, Matsuo K, et al. Association between body-mass index and risk of death in more than 1 million Asians. N Engl J Med. 2011 Feb 24. 364(8):719-29. [Medline].
Berrington de Gonzalez A, Hartge P, Cerhan JR, Flint AJ, Hannan L, MacInnis RJ, et al. Body-mass index and mortality among 1.46 million white adults. N Engl J Med. 2010 Dec 2. 363(23):2211-9. [Medline]. [Full Text].
Boggs DA, Rosenberg L, Cozier YC, Wise LA, Coogan PF, Ruiz-Narvaez EA, et al. General and abdominal obesity and risk of death among black women. N Engl J Med. 2011 Sep 8. 365(10):901-8. [Medline].
Stessman J, Jacobs JM, Ein-Mor E, Bursztyn M. Normal body mass index rather than obesity predicts greater mortality in elderly people: the Jerusalem longitudinal study. J Am Geriatr Soc. 2009 Dec. 57(12):2232-8. [Medline].
Tamakoshi A, Yatsuya H, Lin Y, Tamakoshi K, Kondo T, Suzuki S, et al. BMI and all-cause mortality among Japanese older adults: findings from the Japan collaborative cohort study. Obesity (Silver Spring). 2010 Feb. 18(2):362-9. [Medline].
Wadden TA, Neiberg RH, Wing RR, Clark JM, Delahanty LM, Hill JO, et al. Four-year weight losses in the Look AHEAD study: factors associated with long-term success. Obesity (Silver Spring). 2011 Oct. 19(10):1987-98. [Medline]. [Full Text].
Elbel B, Gyamfi J, Kersh R. Child and adolescent fast-food choice and the influence of calorie labeling: a natural experiment. Int J Obes (Lond). 2011 Apr. 35(4):493-500. [Medline].
Waters E, de Silva-Sanigorski A, Hall BJ, et al. Interventions for preventing obesity in children. Cochrane Database Syst Rev. 2011 Dec 7. 12:CD001871. [Medline].
American Association of Clinical Endocrinologists Statement on the Use of A1C for the Diagnosis of Diabetes. Available at http://emedicine.medscape.com/article/117853-workup. Accessed: August 6 2012.
[Guideline] Diagnosis and classification of diabetes mellitus. Diabetes Care. 2010 Jan. 33 Suppl 1:S62-9. [Medline]. [Full Text].
[Guideline] Jensen MD, Ryan DH, Apovian CM, et al. 2013 AHA/ACC/TOS guideline for the management of overweight and obesity in adults: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines and The Obesity Society. J Am Coll Cardiol. 2013. [Medline]. [Full Text].
Nainggolan L. New obesity guidelines: authoritative 'roadmap' to treatment. Medscape Medical News. November 12, 2013. [Full Text].
Tucker ME. New US obesity guidelines. Treat the weight first. Medscape Medical News. Available at http://www.medscape.com/viewarticle/838285.
Apovian CM, Aronne LJ, Bessesen DH, et al. Pharmacological management of obesity: an endocrine society clinical practice guideline. J Clin Endocrinol Metab. 2015 Feb. 100(2):342-62. [Medline].
Jolly K, Lewis A, Beach J, et al. Comparison of range of commercial or primary care led weight reduction programmes with minimal intervention control for weight loss in obesity: Lighten Up randomised controlled trial. BMJ. 2011 Nov 3. 343:d6500. [Medline]. [Full Text].
Bray GA. Medications for weight reduction. Med Clin North Am. 2011 Sep. 95(5):989-1008. [Medline].
Wing RR, Lang W, Wadden TA, Safford M, Knowler WC, Bertoni AG, et al. Benefits of modest weight loss in improving cardiovascular risk factors in overweight and obese individuals with type 2 diabetes. Diabetes Care. 2011 Jul. 34(7):1481-6. [Medline]. [Full Text].
Stolley MR, Fitzgibbon ML, Schiffer L, Sharp LK, Singh V, Van Horn L, et al. Obesity reduction black intervention trial (ORBIT): six-month results. Obesity (Silver Spring). 2009 Jan. 17(1):100-6. [Medline].
Blüher M, Rudich A, Kloting N, et al. Two patterns of adipokine and other biomarker dynamics in a long-term weight loss intervention. Diabetes Care. 2012 Feb. 35(2):342-9. [Medline]. [Full Text].
Sumithran P, Prendergast LA, Delbridge E, et al. Long-term persistence of hormonal adaptations to weight loss. N Engl J Med. 2011 Oct 27. 365(17):1597-604. [Medline].
Maffeis C. Childhood obesity: the genetic-environmental interface. Baillieres Best Pract Res Clin Endocrinol Metab. 1999 Apr. 13(1):31-46. [Medline].
Proimos J, Sawyer S. Obesity in childhood and adolescence. Aust Fam Physician. 2000 Apr. 29(4):321-7. [Medline].
Harsha DW, Bray GA. Body composition and childhood obesity. Endocrinol Metab Clin North Am. 1996 Dec. 25(4):871-85. [Medline].
Older Adults and the Elderly. In: Human Energy Requirements: Report of a Joint FAO/WHO/UNU Expert Consultation. Rome, 17-24 October 2001. Food and Agriculture Organization of the UN. Available at http://www.fao.org/docrep/007/y5686e/y5686e09.htm#bm9.
Brooks M. Standard '1-MET' Value Invalid in Overweight/Obese. Medscape Medical News. Available at http://www.medscape.com/viewarticle/821375. Accessed: March 10, 2014.
Wilms B, Ernst B, Thurnheer M, Weisser B, Schultes B. Correction factors for the calculation of metabolic equivalents (MET) in overweight to extremely obese subjects. Int J Obes (Lond). 2014 Feb 7. [Medline].
Foster GD, Wyatt HR, Hill JO, Makris AP, Rosenbaum DL, Brill C, et al. Weight and metabolic outcomes after 2 years on a low-carbohydrate versus low-fat diet: a randomized trial. Ann Intern Med. 2010 Aug 3. 153(3):147-57. [Medline]. [Full Text].
Shai I, Schwarzfuchs D, Henkin Y, Shahar DR, Witkow S, Greenberg I, et al. Weight loss with a low-carbohydrate, Mediterranean, or low-fat diet. N Engl J Med. 2008 Jul 17. 359(3):229-41.
Larsen TM, Dalskov SM, van Baak M, Jebb SA, Papadaki A, Pfeiffer AF, et al. Diets with high or low protein content and glycemic index for weight-loss maintenance. N Engl J Med. 2010 Nov 25. 363(22):2102-13. [Medline].
Dansinger ML, Gleason JA, Griffith JL, Selker HP, Schaefer EJ. Comparison of the Atkins, Ornish, Weight Watchers, and Zone diets for weight loss and heart disease risk reduction: a randomized trial. JAMA. 2005 Jan 5. 293(1):43-53. [Medline].
Very low calorie diets. Drug Ther Bull. 2012 May. 50(5):54-7. [Medline].
Van Nieuwenhove Y, Dambrauskas Z, Campillo-Soto A, van Dielen F, Wiezer R, Janssen I, et al. Preoperative very low-calorie diet and operative outcome after laparoscopic gastric bypass: a randomized multicenter study. Arch Surg. 2011 Nov. 146(11):1300-5. [Medline].
Dennis EA, Dengo AL, Comber DL, Flack KD, Savla J, Davy KP, et al. Water consumption increases weight loss during a hypocaloric diet intervention in middle-aged and older adults. Obesity (Silver Spring). 2010 Feb. 18(2):300-7. [Medline]. [Full Text].
Dubnov-Raz G, Constantini NW, Yariv H, Nice S, Shapira N. Influence of water drinking on resting energy expenditure in overweight children. Int J Obes (Lond). 2011 Oct. 35(10):1295-300. [Medline].
Wiesner S, Haufe S, Engeli S, Mutschler H, Haas U, Luft FC, et al. Influences of normobaric hypoxia training on physical fitness and metabolic risk markers in overweight to obese subjects. Obesity (Silver Spring). 2010 Jan. 18(1):116-20. [Medline].
Jakicic JM, Marcus BH, Lang W, Janney C. Effect of exercise on 24-month weight loss maintenance in overweight women. Arch Intern Med. 2008 Jul 28. 168(14):1550-9; discussion 1559-60. [Medline]. [Full Text].
Ballor DL, Poehlman ET. Exercise-training enhances fat-free mass preservation during diet-induced weight loss: a meta-analytical finding. Int J Obes Relat Metab Disord. 1994 Jan. 18(1):35-40. [Medline].
Villareal DT, Chode S, Parimi N, Sinacore DR, Hilton T, Armamento-Villareal R, et al. Weight loss, exercise, or both and physical function in obese older adults. N Engl J Med. 2011 Mar 31. 364(13):1218-29. [Medline]. [Full Text].
Goodpaster BH, Delany JP, Otto AD, Kuller L, Vockley J, South-Paul JE, et al. Effects of diet and physical activity interventions on weight loss and cardiometabolic risk factors in severely obese adults: a randomized trial. JAMA. 2010 Oct 27. 304(16):1795-802. [Medline]. [Full Text].
Hankinson AL, Daviglus ML, Bouchard C, Carnethon M, Lewis CE, Schreiner PJ, et al. Maintaining a high physical activity level over 20 years and weight gain. JAMA. 2010 Dec 15. 304(23):2603-10. [Medline].
Rejeski WJ, Brubaker PH, Goff DC Jr, Bearon LB, McClelland JW, Perri MG, et al. Translating weight loss and physical activity programs into the community to preserve mobility in older, obese adults in poor cardiovascular health. Arch Intern Med. 2011 May 23. 171(10):880-6. [Medline].
Van Dorsten B, Lindley EM. Cognitive and behavioral approaches in the treatment of obesity. Med Clin North Am. 2011 Sep. 95(5):971-88. [Medline].
Morgan PJ, Lubans DR, Callister R, Okely AD, Burrows TL, Fletcher R, et al. The 'Healthy Dads, Healthy Kids' randomized controlled trial: efficacy of a healthy lifestyle program for overweight fathers and their children. Int J Obes (Lond). 2011 Mar. 35(3):436-47. [Medline].
Mozaffarian D, Hao T, Rimm EB, Willett WC, Hu FB. Changes in diet and lifestyle and long-term weight gain in women and men. N Engl J Med. 2011 Jun 23. 364(25):2392-404. [Medline]. [Full Text].
Nedeltcheva AV, Kilkus JM, Imperial J, Schoeller DA, Penev PD. Insufficient sleep undermines dietary efforts to reduce adiposity. Ann Intern Med. 2010 Oct 5. 153(7):435-41. [Medline]. [Full Text].
FDA Expands Warning to Consumers About Tainted Weight Loss Pills. US Food and Drug Administration. January 8, 2009. Available at http://www.fda.gov/newsevents/newsroom/pressannouncements/2008/ucm116998.htm. Accessed: January, 2013.
United States Food and Drug Administration. BMPEA in Dietary Supplements. Available at http://www.fda.gov/Food/DietarySupplements/QADietarySupplements/ucm443790.htm. Accessed: 2015 April 27.
Heck AM, Yanovski JA, Calis KA. Orlistat, a new lipase inhibitor for the management of obesity. Pharmacotherapy. 2000 Mar. 20(3):270-9. [Medline].
US Food and Drug Administration. FDA approves Belviq to treat some overweight or obese adults. June 27, 2012. Available at http://www.fda.gov/NewsEvents/Newsroom/PressAnnouncements/ucm309993.htm. Accessed: July 12, 2012.
Schedules of Controlled Substances: Placement of Lorcaserin Into Schedule IV. Drug Enforcement Administration. Available at http://www.deadiversion.usdoj.gov/fed_regs/rules/2012/fr1219.htm. Accessed: December 28, 2012.
Smith SR, Weissman NJ, Anderson CM, Sanchez M, Chuang E, Stubbe S, et al. Multicenter, placebo-controlled trial of lorcaserin for weight management. N Engl J Med. 2010 Jul 15. 363(3):245-56. [Medline]. [Full Text].
Fidler MC, Sanchez M, Raether B, Weissman NJ, Smith SR, Shanahan WR, et al. A one-year randomized trial of lorcaserin for weight loss in obese and overweight adults: the BLOSSOM trial. J Clin Endocrinol Metab. 2011 Oct. 96(10):3067-77. [Medline].
O'Neil PM, Smith SR, Weissman NJ, Fidler MC, Sanchez M, Zhang J, et al. Randomized placebo-controlled clinical trial of lorcaserin for weight loss in type 2 diabetes mellitus: the BLOOM-DM study. Obesity (Silver Spring). 2012 Jul. 20(7):1426-36. [Medline].
FDA News Release. FDA approves weight-management drug Saxenda. Available at http://www.fda.gov/NewsEvents/Newsroom/PressAnnouncements/ucm427913.htm. Accessed: December 23, 2014.
Serretti A, Mandelli L. Antidepressants and body weight: a comprehensive review and meta-analysis. J Clin Psychiatry. 2010 Oct. 71(10):1259-72. [Medline].
Goldfield GS, Lorello C, Doucet E. Methylphenidate reduces energy intake and dietary fat intake in adults: a mechanism of reduced reinforcing value of food?. Am J Clin Nutr. 2007 Aug. 86(2):308-15. [Medline].
Gadde KM, Franciscy DM, Wagner HR 2nd, Krishnan KR. Zonisamide for weight loss in obese adults: a randomized controlled trial. JAMA. 2003 Apr 9. 289(14):1820-5. [Medline].
Lustig RH, Hinds PS, Ringwald-Smith K, Christensen RK, Kaste SC, Schreiber RE, et al. Octreotide therapy of pediatric hypothalamic obesity: a double-blind, placebo-controlled trial. J Clin Endocrinol Metab. 2003 Jun. 88(6):2586-92. [Medline].
Desilets AR, Dhakal-Karki S, Dunican KC. Role of metformin for weight management in patients without type 2 diabetes. Ann Pharmacother. 2008 Jun. 42(6):817-26. [Medline].
Vilsbøll T, Christensen M, Junker AE, Knop FK, Gluud LL. Effects of glucagon-like peptide-1 receptor agonists on weight loss: systematic review and meta-analyses of randomised controlled trials. BMJ. 2012 Jan 10. 344:d7771. [Medline]. [Full Text].
Gadde KM, Xiong GL. Bupropion for weight reduction. Expert Rev Neurother. 2007 Jan. 7(1):17-24. [Medline].
Black SC. Cannabinoid receptor antagonists and obesity. Curr Opin Investig Drugs. 2004 Apr. 5(4):389-94. [Medline].
Van Gaal LF, Rissanen AM, Scheen AJ, et al. Effects of the cannabinoid-1 receptor blocker rimonabant on weight reduction and cardiovascular risk factors in overweight patients: 1-year experience from the RIO-Europe study. Lancet. Apr 16-22 2005. 365(9468):1389-97.
Cox SL. Rimonabant hydrochloride: an investigational agent for the management of cardiovascular risk factors. Drugs Today (Barc). 2005 Aug. 41(8):499-508. [Medline].
Fernandez JR, Allison DB. Rimonabant Sanofi-Synthélabo. Curr Opin Investig Drugs. 2004 Apr. 5(4):430-5. [Medline].
Nagao T, Meguro S, Hase T, Otsuka K, Komikado M, Tokimitsu I, et al. A catechin-rich beverage improves obesity and blood glucose control in patients with type 2 diabetes. Obesity (Silver Spring). 2009 Feb. 17(2):310-7. [Medline].
Dunican KC, Adams NM, Desilets AR. The role of pramlintide for weight loss. Ann Pharmacother. 2010 Mar. 44(3):538-45. [Medline].
Batterham RL, Cohen MA, Ellis SM, Le Roux CW, Withers DJ, Frost GS, et al. Inhibition of food intake in obese subjects by peptide YY3-36. N Engl J Med. 2003 Sep 4. 349(10):941-8. [Medline].
Boggiano MM, Chandler PC, Oswald KD, Rodgers RJ, Blundell JE, Ishii Y. PYY3-36 as an anti-obesity drug target. Obes Rev. 2005 Nov. 6(4):307-22. [Medline].
Roth CL, Enriori PJ, Harz K, Woelfle J, Cowley MA, Reinehr T. Peptide YY is a regulator of energy homeostasis in obese children before and after weight loss. J Clin Endocrinol Metab. 2005 Dec. 90(12):6386-91. [Medline].
Moon HS, Matarese G, Brennan AM, Chamberland JP, Liu X, Fiorenza CG, et al. Efficacy of metreleptin in obese patients with type 2 diabetes: cellular and molecular pathways underlying leptin tolerance. Diabetes. 2011 Jun. 60(6):1647-56. [Medline]. [Full Text].
Ravussin E, Smith SR, Mitchell JA, Shringarpure R, Shan K, Maier H, et al. Enhanced weight loss with pramlintide/metreleptin: an integrated neurohormonal approach to obesity pharmacotherapy. Obesity (Silver Spring). 2009 Sep. 17(9):1736-43. [Medline]. [Full Text].
Tam CS, Lecoultre V, Ravussin E. Novel strategy for the use of leptin for obesity therapy. Expert Opin Biol Ther. 2011 Dec. 11(12):1677-85. [Medline].
Sjöström L, Peltonen M, Jacobson P, Sjöström CD, Karason K, Wedel H, et al. Bariatric surgery and long-term cardiovascular events. JAMA. 2012 Jan 4. 307(1):56-65. [Medline].
Flum DR, Belle SH, King WC, Wahed AS, Berk P, Chapman W, et al. Perioperative safety in the longitudinal assessment of bariatric surgery. N Engl J Med. 2009 Jul 30. 361(5):445-54. [Medline]. [Full Text].
Maggard MA, Shugarman LR, Suttorp M, Maglione M, Sugerman HJ, Livingston EH, et al. Meta-analysis: surgical treatment of obesity. Ann Intern Med. 2005 Apr 5. 142(7):547-59. [Medline].
Tucker ME. New Bariatric Surgery Guidelines Reflect Rapidly Evolving Field. Medscape Medical News. Mar 28 2013. Available at http://www.medscape.com/viewarticle/781619. Accessed: Apr 3 2013.
Fiore K. New Guidelines for Weight-Loss Surgery Upgrade Sleeve Procedure. MedPage Today. Available at http://www.medpagetoday.com/Endocrinology/Obesity/38112?utm_content=&utm_medium=email&utm_campaign=DailyHeadlines&utm_source=WC&xid=NL_DHE_2013email@example.com&mu_id=5780408. Accessed: Apr 3 2013.
Mechanick JI, Youdim A, Jones DB, Garvey WT, Hurley DL, McMahon MM, et al. Clinical Practice Guidelines for the Perioperative Nutritional, Metabolic, and Nonsurgical Support of the Bariatric Surgery Patient - 2013 Update: Cosponsored by American Association of Clinical Endocrinologists, The Obesity Society, and American Society for Metabolic & Bariatric Surgery. Endocr Pract. 2013 Mar 25. e1-e36. [Medline].
Ashley S, Bird DL, Sugden G, Royston CM. Vertical banded gastroplasty for the treatment of morbid obesity. Br J Surg. 1993 Nov. 80(11):1421-3. [Medline].
Flickinger EG, Pories WJ, Meelheim HD, Sinar DR, Blose IL, Thomas FT. The Greenville gastric bypass. Progress report at 3 years. Ann Surg. 1984 May. 199(5):555-62. [Medline]. [Full Text].
Plecka Östlund M, Marsk R, Rasmussen F, Lagergren J, Näslund E. Morbidity and mortality before and after bariatric surgery for morbid obesity compared with the general population. Br J Surg. 2011 Jun. 98(6):811-6. [Medline].
Mingrone G, Panunzi S, De Gaetano A, Guidone C, Iaconelli A, Leccesi L, et al. Bariatric surgery versus conventional medical therapy for type 2 diabetes. N Engl J Med. 2012 Apr 26. 366(17):1577-85. [Medline]. [Full Text].
Søvik TT, Aasheim ET, Taha O, Engström M, Fagerland MW, Björkman S, et al. Weight loss, cardiovascular risk factors, and quality of life after gastric bypass and duodenal switch: a randomized trial. Ann Intern Med. 2011 Sep 6. 155(5):281-91. [Medline].
Hedberg J, Sundbom M. Superior weight loss and lower HbA1c 3 years after duodenal switch compared with Roux-en-Y gastric bypass--a randomized controlled trial. Surg Obes Relat Dis. 2012 May-Jun. 8(3):338-43. [Medline].
Cigaina V. Gastric pacing as therapy for morbid obesity: preliminary results. Obes Surg. 2002 Apr. 12 Suppl 1:12S-16S. [Medline].
Klein S, Fontana L, Young VL, et al. Absence of an effect of liposuction on insulin action and risk factors for coronary heart disease. N Engl J Med. Jun 17 2004. 350(25):2549-57.
Koch TR, Finelli FC. Postoperative metabolic and nutritional complications of bariatric surgery. Gastroenterol Clin North Am. 2010 Mar. 39(1):109-24. [Medline].
Abbott Laboratories agrees to withdraw its obesity drug Meridia. FDA, U.S. Food and Drug Administration. Available at http://www.fda.gov/NewsEvents/Newsroom/PressAnnouncements/ucm228812.htm. Accessed: October 8, 2010.
Anderson JW, Jhaveri MA. Reductions in medications with substantial weight loss with behavioral intervention. Curr Clin Pharmacol. 2010 Nov. 5(4):232-8. [Medline].
Food and Drug Administration. FDA approves weight-management drug Qsymia. Available at http://www.fda.gov/NewsEvents/Newsroom/PressAnnouncements/ucm312468.htm. Accessed: August 7, 2012.
Grudell AB, Sweetser S, Camilleri M, Eckert DJ, Vazquez-Roque MI, Carlson PJ, et al. A controlled pharmacogenetic trial of sibutramine on weight loss and body composition in obese or overweight adults. Gastroenterology. 2008 Oct. 135(4):1142-54. [Medline]. [Full Text].
James WP, Caterson ID, Coutinho W, Finer N, Van Gaal LF, Maggioni AP, et al. Effect of sibutramine on cardiovascular outcomes in overweight and obese subjects. N Engl J Med. 2010 Sep 2. 363(10):905-17. [Medline].
Laidman J. Obesity Thresholds Accurately Predict Adolescent Health Risk. Medscape Medical News. Jan 29 2014. [Full Text].
Laurson KR, Welk GJ, Eisenmann JC. Diagnostic performance of BMI percentiles to identify adolescents with metabolic syndrome. Pediatrics. 2014 Feb. 133(2):e330-8. [Medline].
Makowski CT, Gwinn KM, Hurren KM. Naltrexone/bupropion: an investigational combination for weight loss and maintenance. Obes Facts. 2011. 4(6):489-94. [Medline].
Nainggolan L. Gastric band is first step surgery for morbidly obese teens. Medscape Medical News. May 29, 2014. [Full Text].
Nainggolan L. FDA Approves Bupropion/Naltrexone (Contrave) for Obesity. Medscape Medical News. Available at http://www.staging.medscape.com/viewarticle/831513. Accessed: September 14, 2014.
Schauer PR, Kashyap SR, Wolski K, Brethauer SA, Kirwan JP, Pothier CE, et al. Bariatric surgery versus intensive medical therapy in obese patients with diabetes. N Engl J Med. 2012 Apr 26. 366(17):1567-76. [Medline]. [Full Text].
Sjöström L, Narbro K, Sjöström CD, Karason K, Larsson B, Wedel H, et al. Effects of bariatric surgery on mortality in Swedish obese subjects. N Engl J Med. 2007 Aug 23. 357(8):741-52. [Medline].