Continuing Education Activity

Obesity is a significant health concern worldwide because it is a risk factor for many diseases like diabetes, hypertension, cardiovascular disease, and cancers. A complex interplay of genetic changes, environmental influence, biological and behavioral factors precede obesity. Therefore, the management involves a multidisciplinary approach in which lifestyle modification plays a considerable role. This activity reviews the evaluation and management of obesity and highlights the role of the interprofessional team in improving the care of patients with this condition.

Objectives:

• Review the risk factors for developing obesity.
• Explain the common physical exam findings associated with obesity.
• Describe the pathophysiology of hypertension in obesity.
• Identify the indications for bariatric surgery.

Introduction

The current recommendation to identify obesity is in terms of Body Mass Index (BMI). A person with a BMI of 30 kg/m^2 or more is defined as an obese individual. The rising prevalence of obesity is a significant health concern worldwide because excess weight is a risk factor for many diseases, such as cardiovascular disease, diabetes, hypertension, and certain cancers.[1] Obesity results from a complex interaction between environmental, cultural, and genetic factors.[2] 

Poor dietary intake, decreased physical activity and a sedentary lifestyle contribute as the risk factors for obesity. The World Health Organization in 2005 maintained that about 1.6 billion adults of age 15 or greater were overweight, 400 million were obese, and more than 20 million children less than five years of age were overweight.[3] The numbers rose in 2015, and it was concluded that overweight adults make up approximately 2.3 billion of the world population, and over 700 million people are obese.

The heritability of obesity in various twin and family-based genetic studies is between 40 and 70%.[4] The severe forms and majority of the early-onset monogenic forms of obesity have aroused from gene mutations in the leptin-melanocortin axis, particularly LEPR encoding for the leptin receptor, POMC (pro-opiomelanocortin), MC4R (melanocortin-4 receptor), NTRK2 (tropomyosin receptor kinase B receptor), and SIM1 (single-minded 1 transcription factor).[5][6] 

The opioid pathway has recently been implicated in obesity causation, and there is evidence of the association of mu-opioid receptor (MOR) OPRM1 with dietary fat intake. A prominent landmark study was done in 2015 through genome-wide association studies (GWASs), and meta-analysis identified 97 BMI-associated loci and other obesity-related traits.[7]

The new approaches employed for modulating the central melanocortin system include AgRP (agouti-related protein) antagonists, MC4R PAMs (positive allosteric modulators), and MC4R or LepRb (leptin receptor) chaperones.[8]

Function

BMI is calculated by weight (kg)/height (m^2). Another way to calculate BMI is weight (lbs)/height (in^2) x 703. It should be noted that BMI is a poor indicator of obesity. A flexible tape measures the Waist Circumference (WC) around the iliac crests in a horizontal plane. WC varies with ethnic background. A high WC for BMI value of 25 TO 35 indicates an increased risk of cardiovascular disease and diabetes mellitus type II.

Weight is classified based on BMI as underweight, normal, overweight, obesity class I, obesity class II, and obesity class III. The classes of obesity with their corresponding BMI values are enlisted in Table 1.

Table

 Obesity Class BMI (kg/m^2)

Table 1: Obesity classes and their corresponding BMI values

The disease risks in adults increase with increasing waist circumference and the obesity class. For instance, men with WC > 102 cm (40 in) and women with WC > 88 cm (35 in) who are overweight have a high risk to develop the obesity-associated disease, compared to an extremely high risk in adults who fall under the obesity class III.

Limitations of BMI

There are some limitations to the use of BMI for the diagnosis of obesity. Firstly, an anthropometric value co-relates height and weight and does not directly estimate adipose tissue mass. Lean body mass and water contribute to body weight, so BMI has poor approximation for individual-specific fat mass. BMI overestimates adipose mass in edematous patients and athletes with increased muscle mass and underestimates adiposity in old age patients with sarcopenia. Therefore, BMI alone cannot accurately identify excess adiposity and diagnose overweight or obese patients in all cases.[9][10] 

Due to these reasons, BMI is only used as a screening tool. BMI values are clinically evaluated based on history and physical examination to determine excess adipose tissue mass for an actual diagnosis. Patients should be evaluated for certain factors that can affect the relationship between BMI and adiposity. The quantification of adipose fat mass and body composition is useful in diagnosing and responding to therapy in some patients and is done through clinically available tools such as plethysmography techniques (bioelectric impedance, air displacement) or dual-energy x-ray absorptiometry (DEXA). A poor reflection of the distribution of body fat is the second limitation of BMI. There is a non-uniform distribution of fat depots all around the body, indicating the difference in disease risk.[11][12][13] 

The visceral adipose tissue that surrounds vital organs contributes significantly to the pathophysiology of cardiometabolic disease. Similarly, abnormal fat accumulation in muscle and hepatocytes cause a worsening of insulin resistance and non-alcoholic fatty liver disease, respectively. Cardiometabolic disease is the underlying pathophysiological process in both metabolic and vascular diseases. The most crucial initial event is insulin resistance which progresses to metabolic syndrome or pre-diabetes, and finally to diabetes mellitus type 2 or cardiovascular disease, depending upon patient characteristics. Hence, the distribution of fat and overall adipose tissue mass has a role in disease outcomes in patients with obesity. It signifies the importance of waist circumference in the measurement of abdominal fat accumulation.[14] 

Finally, BMI does not estimate the degree to which excess adipose tissue adversely affects the health of individual patients in terms of morbidity and mortality. The presence and severity of complications show how the degree of excess adiposity affects individual patients' health. In contrast, if we want to improve patients' health with obesity, the goal of therapy in obesity is to halt and treat complications resulting from obesity. This approach is followed by the complications-centric approach of obesity management exercised by the American Association of Clinical Endocrinologists (AACE). AACE evidence-based guidelines stress weight loss with the primary objective of preventing and treating complications to improve health compared to the single focus of degree of weight loss alone. Table 2 outlines the limitations of BMI in diagnosing and evaluating obesity.

Table

Table 2. Limitations of BMI in diagnosis and evaluation of obesity 1. BMI caters for height and weight but does not measure adiposity directly. BMI requires individual interpretation with attention to the following characteristics

Issues of Concern

Obesity is associated with several adverse medical consequences. The most noteworthy diseases are Type 2 diabetes mellitus, cardiovascular diseases such as coronary artery disease, unexplained congestive heart failure, and hypertension, metabolic syndrome, stroke, gallbladder disease, non-alcoholic steatohepatitis, dyslipidemia, certain types of cancers like colon, prostate, endometrial, and breast cancer, infertility, osteoarthritis, low back pain, psychological problems, and increased total morbidity and mortality.[15][16]

Researchers propose that the stable increase in life expectancy over the past two decades may halt due to the rising prevalence of obesity.[17] Cardiovascular disease is the biggest cause of mortality worldwide, and obesity is a major underlying risk factor.

Clinical Significance

The current screening recommendation is to use CANRISK (Canadian Diabetes Risk Score) or FINDRISK (Finnish Diabetic Risk Score) scores to evaluate for the risk of prediabetes and diabetes mellitus type 2 in people of age 45-74 years of age, although it may be in high-risk younger age individuals. CANRISK is adapted from a similar tool called FINDRISK, a part of Finland's national diabetes prevention program. The CANRISK is specifically modified to suit the Canadian population and includes additional ethnicity, education, and gestational diabetes questions. The CANRISK scores utilize a questionnaire that consists of 12 questions, each with points for patient characteristics. The points are then added and compared with threshold scores for three risk categories, i.e., low (<21), moderate (21 to 32), and high (>32) risk. The BMI risk assessment is also recommended every 3 to 5 years in individuals at high risk of developing diabetes mellitus in 10 years.

If BMI is more than 25 kg/m^2 or WC is above the cutoff point, advise regular clinical visits to conduct clinical examinations and laboratory investigations to assess for comorbidities. 

In the initial visit, the clinician needs to pay attention to aspects of history and examination in detail, conduct an obesity-focused review of systems looking for potential symptoms of obesity-related complications, and perform laboratory testing. It is also essential to involve a psychiatrist or psychologist and screen for depression and other mood disorders and psychological problems.[18] Finally, ask about medications that could iatrogenically lead to weight gain and substitute them with other alternative drugs.[19] The clinical data that is important to be obtained during the initial evaluation are summarized in Table 3. General guidelines to follow during an initial visit are as follows:

• Check blood pressure, heart rate, fasting glucose, lipid profile that includes total cholesterol, triglycerides, LDL (low-density cholesterol), HDL (high-density cholesterol), and the ratio of total cholesterol to HDL cholesterol.
• Examine for hyperlipidemia signs such as xanthelasmata (cholesterol deposit underneath the skin or around eyelid), tendinous xanthoma (lipid deposit in tendon), eruptive xanthoma (painful reddish yellow and pruritic rash), lipemia retinalis (atheromata in retinal blood vessels), and corneal arcus (lipid deposit in the cornea).
• Screen and evaluate for psychiatric illnesses like depression, binge eating and other eating disorders, and mood disorders.
• Manage associated comorbidities to reduce health risk factors.
• Assess for personal habits and barriers to weight loss.
• Counsel the patient and evaluate readiness for weight loss.

Table

Table 3: Key clinical data to be obtained at initial evaluation.

Disease Staging

Both the anthropometric and clinical component of diagnosis leads to the staging of the disease that acts as a guide to management to target aggressive interventions to those patients who would benefit from weight loss therapy the most. Out of many staging systems, the AACE obesity guidelines advocate a clinically helpful tool. Every complication is assessed for its severity and impact on the patient's health. The disease is classified as stage 0, with no complications, Stage 1, when complications are mild-moderate, and stage 2, when at least one of the complications is moderate-severe using specific criteria.

In stage 0 (uncomplicated overweight/obesity), secondary prevention strategies to prevent further weight gain and emergence of complications are executed. Structured lifestyle intervention is appropriate at this stage. Once complications arise, it becomes evident that the excess adipose tissue mass is adversely affecting the patient's health regardless of the BMI class, and a more rigorous management plan is warranted. Tertiary prevention is then needed to lose enough weight to treat the complications. For patients categorized as Stage 1 (mild-moderate complications), combined lifestyle change and anti-obesity medications are employed, and in cases of moderate-severe complications (stage 2), additional pharmacological therapy is appropriate. Bariatric surgery is considered in only selected patients.

The Edmonton protocol proposes five stages ranging from no effect to severe impairment. It evaluates the medical, psychological, and functional impact of obesity.[20] Another staging device, cardiometabolic disease staging (CMDS), quantifies diabetes and cardiovascular disease risk in a large pool of at-risk patients with prediabetes or metabolic syndrome, approximated as 40 percent of the United States population in the National Health and Nutrition Examination (NHANES) survey.[21][22] 

CMDS uses quantitative clinical values to stratify the risk of progression to type 2 diabetes mellitus in cardiometabolic disease patients on weight loss therapy and formulates that the risk is 40 times more in overweight/obese patients. For high-risk patients, weight loss effectively prevents progression to diabetes and has a lower 'number-needed-to-treat' but a superior benefit/risk ratio.[23][24][25]

Other Issues

The relationship between obesity and hypertension is well established in adults and children, but the mechanism by which obesity causes hypertension is not yet clearly understood.[26] The combined effects of the autonomic nervous system, abdominal fat, intra-vascular fat, increased renal sodium absorption, and the renin-angiotensin-aldosterone system plays a vital role in the pathogenesis of hypertension related to obesity. Hypertension is a chronic medical condition in which blood pressure is more than 140/90 mm Hg. Fats in blood circulation can have detrimental local actions through the formation of atherosclerosis. Atherosclerosis is defined as the accumulation of fat inside the medium and large arterial vessel walls. Many other factors such as smoking, physical inactivity, carbohydrate-rich diet, alcohol consumption, certain bacteria, and stress also promote atherosclerosis of the vessel walls.[27] 

This build-up of fat creates a plaque that grows bigger until it causes critical obstruction of the arterial lumen leading to downstream local disturbances in the organs it supplies, eventually increasing morbidity and even sudden death rates.[28][29] 

High dietary fat and carbohydrate also directly stimulate peripheral alpha-1 and beta-adrenergic receptors, resulting in hypertension.  In addition, blockade of both alpha and beta-adrenergic receptors causes a more prominent decrease in blood pressure in obese hypertensive patients than non-obese hypertensive patients. However, increased heart rate results from decreased parasympathetic activity.

Obesity affects all major body organs such as the heart, liver, kidney, lungs, colon, skin, blood vessels, and brain. The kidney appears to be the most affected by obesity, and dietary fat restriction significantly reverses renal damage. At first, obesity causes renal vasodilatation and glomerular hyperfiltration, maintaining sodium balance despite higher tubular sodium reabsorption. The increased tubular reabsorption combined with raised blood pressure in arteries, metabolic abnormalities, inflammatory causes, oxidative stress, and lipotoxicity contributes to exacerbating renal damage by following a vicious cycle. The most directly dependent on body weight appears to be renal injury, and dietary fat restriction significantly reverses renal damage. At first, obesity causes renal vasodilatation and glomerular hyperfiltration, which functions to maintain sodium balance despite higher tubular sodium reabsorption. The increased tubular reabsorption combined with raised blood pressure in arteries, metabolic abnormalities, inflammatory causes, oxidative stress, and lipotoxicity contributes to the exacerbation of renal damage by following a vicious cycle.[30]

Clinically, this damage is evident as proteinuria, followed by a decrease in the glomerular filtration rate several years later. Adipose tissue, particularly abdominal fat, is also linked with generalized effects on various body systems through the secretion of hormones and cytokines, causing a type of glomerular damage called obese-associated glomerulopathy.[31]

Abdominal fat serves to be a prime component among the characteristic features of metabolic syndrome. It is expected that the incidence of metabolic syndrome will increase up to 53% in 2035. Other factors leading to metabolic syndrome include nuclear peroxisome proliferator-activated (PPAR) modulation, insulin resistance, dyslipidemia, high blood pressure, and certain proinflammatory states. Higher body fat mass also results in increased adipocyte size of subcutaneous and omentum fat. Hyperplasia occurs predominantly in subcutaneous fats, whereas hypertrophy is found in both mental and subcutaneous fat tissue. Eventually, fat accumulation progressively increased in the subcutaneous compartment as compared to visceral fat tissue. WC and BMI are significant indicators of visceral adiposity in adults and strongly predict the presence of hepatic steatosis.

Enhancing Healthcare Team Outcomes

The management of obesity involves a multidisciplinary approach that starts with behavioral/lifestyle modification, pharmacological therapy, and surgical methods if all of the above fails. In addition, physicians, nurses, nutritionists, and other allied health care professional services are required to achieve realistic goals.

Behavioural/Lifestyle Changes

• Weight loss of >5% significantly reduces cardiovascular risk factors, e.g., elevated blood pressure, blood glucose, and lipids. Aim for 5 to 10% of weight loss or 0.5 to 1 kg (1 to 2 lb) per week for six months
• Engage healthcare team for advising lifestyle modification, and arrange group as well as individual sessions
• Reduce energy intake by 500 to 1000 kcal/day
• Moderate intensity exercises initially for 30 min 3 to 5 times/week, eventually >60 min on most days of the week. Clinical evaluation is essential before beginning an activity program.
• Cognitive-behavioral therapy also plays a part.
• Regular monitoring with advice on weight maintenance, reinforcing healthy eating habits, and promoting physical activity
• Weight monitoring every three months.
• Calculate BMI and WC every 1 to 2 years.

Pharmacological Interventions

Consider pharmacologic intervention if the patient has not lost 0.5 to 1 kg (1 to 2 lb) per week for 3 to 6 months after lifestyle modifications. Medications are used as an adjunct to lifestyle changes. Although the recommendations are against using medications for weight loss, some patients prefer them and can be good candidates for pharmacologic management. There is better evidence of benefit from behavioral modification alone, and NNH (number needed to harm) is as low as 10 with drugs, primarily due to gastrointestinal (GI) side effects.

Pharmacotherapy options for weight loss have considerably evolved over the last ten years.[32] Rimonabant, a cannabinoid receptor type 1 (CB1R) antagonist, was initially approved by European Medicines Agency (EMEA) but not by the FDA and was withdrawn due to concerns about the high risk of suicidal ideation. Sibutramine, a neurotransmitter reuptake inhibitor and anorectic agent, was withdrawn in 2012 due to cardiovascular side effects, especially at increased risk of stroke.[33] 

By 2012, only two weight loss drugs were approved to be used in the US, phentermine, and orlistat. In contrast, only orlistat is approved for use in Europe. Four new drugs showed good efficacies and responder success rates in clinical trials and were approved by FDA after 2012. Lorcaserin and liraglutide are single therapy agents that act on 5-HT2c receptors and glucagon-like peptide-1 receptor (GLP-1R), respectively. Fixed-dose combinations include extended-release phentermine HCl/topiramate and naltrexone HCl/bupropion, and they have complex polypharmacology.[32][34] 

Only two of them, liraglutide and naltrexone/bupropion, are approved for weight loss by the EMEA. Interestingly, the placebo-adjusted weight loss of drug combinations such as phentermine/topiramate is remarkably greater than other approved drugs and provided a basis for new combination approaches in treating obesity.[35][36] Such new agents act on molecular targets in the central nervous system to decrease appetite. Most of the drugs above are orally active except for liraglutide which requires daily subcutaneous administration.

Start drug therapy if BMI > 27 kg/m^2 with risk factors or BMI ≥ 30 kg/m^2 alone. Orlistat is a favored drug, and it decreases fat absorption by inhibiting gastrointestinal lipase, particularly pancreatic lipase. However, this medication is associated with several adverse effects and is not approved to use for more than two years. It is also avoided in patients with GI diseases such as inflammatory bowel disease or chronic bowel disorders.

Surgical Treatment

Consider when lifestyle, medications, and other weight loss attempts fail to obtain desired goals. Bariatric surgery is a term used collectively for various procedures that change the digestive tract and help lose weight. The main procedures are biliopancreatic diversion with duodenal switch (BPD/DS), gastric bypass (Roux-en-Y), and sleeve gastrectomy. Bariatric surgery is not without risks. It has the potential for post-operative and long-term complications and requires lifelong monitoring.  The candidates for surgery are those having BMI ≥ 40 kg/m^2 or BMI ≥ 35 kg/m^2 and at least one or more comorbidities like type 2 diabetes mellitus, hypertension, sleep apnea, non-alcoholic fatty liver disease, osteoarthritis, lipid metabolism disorders, gastrointestinal diseases, and heart diseases.

Review Questions

• Access free multiple choice questions on this topic.
• Comment on this article.

References

1.

Wang YC, McPherson K, Marsh T, Gortmaker SL, Brown M. Health and economic burden of the projected obesity trends in the USA and the UK. Lancet. 2011 Aug 27;378(9793):815-25. [PubMed: 21872750]

2.

Apovian CM. Obesity: definition, comorbidities, causes, and burden. Am J Manag Care. 2016 Jun;22(7 Suppl):s176-85. [PubMed: 27356115]

3.

Gill T, King L, Caterson I. Obesity prevention: necessary and possible. A structured approach for effective planning. Proc Nutr Soc. 2005 May;64(2):255-61. [PubMed: 15960870]

4.

Barsh GS, Farooqi IS, O'Rahilly S. Genetics of body-weight regulation. Nature. 2000 Apr 06;404(6778):644-51. [PubMed: 10766251]

5.

Farooqi S. Genetic strategies to understand physiological pathways regulating body weight. Mamm Genome. 2014 Oct;25(9-10):377-83. [PMC free article: PMC4164839] [PubMed: 25154910]

6.

Farooqi IS, O'Rahilly S. Monogenic obesity in humans. Annu Rev Med. 2005;56:443-58. [PubMed: 15660521]

7.

Locke AE, Kahali B, Berndt SI, Justice AE, Pers TH, Day FR, Powell C, Vedantam S, Buchkovich ML, Yang J, Croteau-Chonka DC, Esko T, Fall T, Ferreira T, Gustafsson S, Kutalik Z, Luan J, Mägi R, Randall JC, Winkler TW, Wood AR, Workalemahu T, Faul JD, Smith JA, Zhao JH, Zhao W, Chen J, Fehrmann R, Hedman ÅK, Karjalainen J, Schmidt EM, Absher D, Amin N, Anderson D, Beekman M, Bolton JL, Bragg-Gresham JL, Buyske S, Demirkan A, Deng G, Ehret GB, Feenstra B, Feitosa MF, Fischer K, Goel A, Gong J, Jackson AU, Kanoni S, Kleber ME, Kristiansson K, Lim U, Lotay V, Mangino M, Leach IM, Medina-Gomez C, Medland SE, Nalls MA, Palmer CD, Pasko D, Pechlivanis S, Peters MJ, Prokopenko I, Shungin D, Stančáková A, Strawbridge RJ, Sung YJ, Tanaka T, Teumer A, Trompet S, van der Laan SW, van Setten J, Van Vliet-Ostaptchouk JV, Wang Z, Yengo L, Zhang W, Isaacs A, Albrecht E, Ärnlöv J, Arscott GM, Attwood AP, Bandinelli S, Barrett A, Bas IN, Bellis C, Bennett AJ, Berne C, Blagieva R, Blüher M, Böhringer S, Bonnycastle LL, Böttcher Y, Boyd HA, Bruinenberg M, Caspersen IH, Chen YI, Clarke R, Daw EW, de Craen AJM, Delgado G, Dimitriou M, Doney ASF, Eklund N, Estrada K, Eury E, Folkersen L, Fraser RM, Garcia ME, Geller F, Giedraitis V, Gigante B, Go AS, Golay A, Goodall AH, Gordon SD, Gorski M, Grabe HJ, Grallert H, Grammer TB, Gräßler J, Grönberg H, Groves CJ, Gusto G, Haessler J, Hall P, Haller T, Hallmans G, Hartman CA, Hassinen M, Hayward C, Heard-Costa NL, Helmer Q, Hengstenberg C, Holmen O, Hottenga JJ, James AL, Jeff JM, Johansson Å, Jolley J, Juliusdottir T, Kinnunen L, Koenig W, Koskenvuo M, Kratzer W, Laitinen J, Lamina C, Leander K, Lee NR, Lichtner P, Lind L, Lindström J, Lo KS, Lobbens S, Lorbeer R, Lu Y, Mach F, Magnusson PKE, Mahajan A, McArdle WL, McLachlan S, Menni C, Merger S, Mihailov E, Milani L, Moayyeri A, Monda KL, Morken MA, Mulas A, Müller G, Müller-Nurasyid M, Musk AW, Nagaraja R, Nöthen MM, Nolte IM, Pilz S, Rayner NW, Renstrom F, Rettig R, Ried JS, Ripke S, Robertson NR, Rose LM, Sanna S, Scharnagl H, Scholtens S, Schumacher FR, Scott WR, Seufferlein T, Shi J, Smith AV, Smolonska J, Stanton AV, Steinthorsdottir V, Stirrups K, Stringham HM, Sundström J, Swertz MA, Swift AJ, Syvänen AC, Tan ST, Tayo BO, Thorand B, Thorleifsson G, Tyrer JP, Uh HW, Vandenput L, Verhulst FC, Vermeulen SH, Verweij N, Vonk JM, Waite LL, Warren HR, Waterworth D, Weedon MN, Wilkens LR, Willenborg C, Wilsgaard T, Wojczynski MK, Wong A, Wright AF, Zhang Q, LifeLines Cohort Study. Brennan EP, Choi M, Dastani Z, Drong AW, Eriksson P, Franco-Cereceda A, Gådin JR, Gharavi AG, Goddard ME, Handsaker RE, Huang J, Karpe F, Kathiresan S, Keildson S, Kiryluk K, Kubo M, Lee JY, Liang L, Lifton RP, Ma B, McCarroll SA, McKnight AJ, Min JL, Moffatt MF, Montgomery GW, Murabito JM, Nicholson G, Nyholt DR, Okada Y, Perry JRB, Dorajoo R, Reinmaa E, Salem RM, Sandholm N, Scott RA, Stolk L, Takahashi A, Tanaka T, van 't Hooft FM, Vinkhuyzen AAE, Westra HJ, Zheng W, Zondervan KT, ADIPOGen Consortium. AGEN-BMI Working Group. CARDIOGRAMplusC4D Consortium. CKDGen Consortium. GLGC. ICBP. MAGIC Investigators. MuTHER Consortium. MIGen Consortium. PAGE Consortium. ReproGen Consortium. GENIE Consortium. International Endogene Consortium. Heath AC, Arveiler D, Bakker SJL, Beilby J, Bergman RN, Blangero J, Bovet P, Campbell H, Caulfield MJ, Cesana G, Chakravarti A, Chasman DI, Chines PS, Collins FS, Crawford DC, Cupples LA, Cusi D, Danesh J, de Faire U, den Ruijter HM, Dominiczak AF, Erbel R, Erdmann J, Eriksson JG, Farrall M, Felix SB, Ferrannini E, Ferrières J, Ford I, Forouhi NG, Forrester T, Franco OH, Gansevoort RT, Gejman PV, Gieger C, Gottesman O, Gudnason V, Gyllensten U, Hall AS, Harris TB, Hattersley AT, Hicks AA, Hindorff LA, Hingorani AD, Hofman A, Homuth G, Hovingh GK, Humphries SE, Hunt SC, Hyppönen E, Illig T, Jacobs KB, Jarvelin MR, Jöckel KH, Johansen B, Jousilahti P, Jukema JW, Jula AM, Kaprio J, Kastelein JJP, Keinanen-Kiukaanniemi SM, Kiemeney LA, Knekt P, Kooner JS, Kooperberg C, Kovacs P, Kraja AT, Kumari M, Kuusisto J, Lakka TA, Langenberg C, Marchand LL, Lehtimäki T, Lyssenko V, Männistö S, Marette A, Matise TC, McKenzie CA, McKnight B, Moll FL, Morris AD, Morris AP, Murray JC, Nelis M, Ohlsson C, Oldehinkel AJ, Ong KK, Madden PAF, Pasterkamp G, Peden JF, Peters A, Postma DS, Pramstaller PP, Price JF, Qi L, Raitakari OT, Rankinen T, Rao DC, Rice TK, Ridker PM, Rioux JD, Ritchie MD, Rudan I, Salomaa V, Samani NJ, Saramies J, Sarzynski MA, Schunkert H, Schwarz PEH, Sever P, Shuldiner AR, Sinisalo J, Stolk RP, Strauch K, Tönjes A, Trégouët DA, Tremblay A, Tremoli E, Virtamo J, Vohl MC, Völker U, Waeber G, Willemsen G, Witteman JC, Zillikens MC, Adair LS, Amouyel P, Asselbergs FW, Assimes TL, Bochud M, Boehm BO, Boerwinkle E, Bornstein SR, Bottinger EP, Bouchard C, Cauchi S, Chambers JC, Chanock SJ, Cooper RS, de Bakker PIW, Dedoussis G, Ferrucci L, Franks PW, Froguel P, Groop LC, Haiman CA, Hamsten A, Hui J, Hunter DJ, Hveem K, Kaplan RC, Kivimaki M, Kuh D, Laakso M, Liu Y, Martin NG, März W, Melbye M, Metspalu A, Moebus S, Munroe PB, Njølstad I, Oostra BA, Palmer CNA, Pedersen NL, Perola M, Pérusse L, Peters U, Power C, Quertermous T, Rauramaa R, Rivadeneira F, Saaristo TE, Saleheen D, Sattar N, Schadt EE, Schlessinger D, Slagboom PE, Snieder H, Spector TD, Thorsteinsdottir U, Stumvoll M, Tuomilehto J, Uitterlinden AG, Uusitupa M, van der Harst P, Walker M, Wallaschofski H, Wareham NJ, Watkins H, Weir DR, Wichmann HE, Wilson JF, Zanen P, Borecki IB, Deloukas P, Fox CS, Heid IM, O'Connell JR, Strachan DP, Stefansson K, van Duijn CM, Abecasis GR, Franke L, Frayling TM, McCarthy MI, Visscher PM, Scherag A, Willer CJ, Boehnke M, Mohlke KL, Lindgren CM, Beckmann JS, Barroso I, North KE, Ingelsson E, Hirschhorn JN, Loos RJF, Speliotes EK. Genetic studies of body mass index yield new insights for obesity biology. Nature. 2015 Feb 12;518(7538):197-206. [PMC free article: PMC4382211] [PubMed: 25673413]

8.

Jackson VM, Breen DM, Fortin JP, Liou A, Kuzmiski JB, Loomis AK, Rives ML, Shah B, Carpino PA. Latest approaches for the treatment of obesity. Expert Opin Drug Discov. 2015;10(8):825-39. [PubMed: 25967138]

9.

Neeland IJ, de Lemos JA. Time to Retire the BMI?: Evaluating Abdominal Adipose Tissue Imaging as Novel Cardiovascular Risk Biomarker. J Am Coll Cardiol. 2016 Oct 04;68(14):1522-4. [PubMed: 27687193]

10.

Bray GA, Heisel WE, Afshin A, Jensen MD, Dietz WH, Long M, Kushner RF, Daniels SR, Wadden TA, Tsai AG, Hu FB, Jakicic JM, Ryan DH, Wolfe BM, Inge TH. The Science of Obesity Management: An Endocrine Society Scientific Statement. Endocr Rev. 2018 Apr 01;39(2):79-132. [PMC free article: PMC5888222] [PubMed: 29518206]

11.

Cefalu WT, Bray GA, Home PD, Garvey WT, Klein S, Pi-Sunyer FX, Hu FB, Raz I, Van Gaal L, Wolfe BM, Ryan DH. Advances in the Science, Treatment, and Prevention of the Disease of Obesity: Reflections From a Diabetes Care Editors' Expert Forum. Diabetes Care. 2015 Aug;38(8):1567-82. [PMC free article: PMC4831905] [PubMed: 26421334]

12.

Van Gaal LF, Mertens IL, De Block CE. Mechanisms linking obesity with cardiovascular disease. Nature. 2006 Dec 14;444(7121):875-80. [PubMed: 17167476]

13.

Després JP, Lemieux I. Abdominal obesity and metabolic syndrome. Nature. 2006 Dec 14;444(7121):881-7. [PubMed: 17167477]

14.

Heymsfield SB, Wadden TA. Mechanisms, Pathophysiology, and Management of Obesity. N Engl J Med. 2017 Jan 19;376(3):254-266. [PubMed: 28099824]

15.

Bloomgarden ZT. Third Annual World Congress on the Insulin Resistance Syndrome: associated conditions. Diabetes Care. 2006 Sep;29(9):2165-74. [PubMed: 16936171]

16.

Strumpf E. The obesity epidemic in the United States: causes and extent, risks and solutions. Issue Brief (Commonw Fund). 2004 Nov;(713):1-6. [PubMed: 15597518]

17.

Walls HL, Backholer K, Proietto J, McNeil JJ. Obesity and trends in life expectancy. J Obes. 2012;2012:107989. [PMC free article: PMC3359718] [PubMed: 22655173]

18.

Succurro E, Segura-Garcia C, Ruffo M, Caroleo M, Rania M, Aloi M, De Fazio P, Sesti G, Arturi F. Obese Patients With a Binge Eating Disorder Have an Unfavorable Metabolic and Inflammatory Profile. Medicine (Baltimore). 2015 Dec;94(52):e2098. [PMC free article: PMC5291597] [PubMed: 26717356]

19.

Apovian CM, Aronne LJ, Bessesen DH, McDonnell ME, Murad MH, Pagotto U, Ryan DH, Still CD., Endocrine Society. Pharmacological management of obesity: an endocrine Society clinical practice guideline. J Clin Endocrinol Metab. 2015 Feb;100(2):342-62. [PubMed: 25590212]

20.

Sharma AM, Kushner RF. A proposed clinical staging system for obesity. Int J Obes (Lond). 2009 Mar;33(3):289-95. [PubMed: 19188927]

21.

Guo F, Moellering DR, Garvey WT. The progression of cardiometabolic disease: validation of a new cardiometabolic disease staging system applicable to obesity. Obesity (Silver Spring). 2014 Jan;22(1):110-8. [PMC free article: PMC3866217] [PubMed: 23894121]

22.

Guo F, Garvey WT. Development of a Weighted Cardiometabolic Disease Staging (CMDS) System for the Prediction of Future Diabetes. J Clin Endocrinol Metab. 2015 Oct;100(10):3871-7. [PMC free article: PMC4596035] [PubMed: 26241327]

23.

Moore JX, Chaudhary N, Akinyemiju T. Metabolic Syndrome Prevalence by Race/Ethnicity and Sex in the United States, National Health and Nutrition Examination Survey, 1988-2012. Prev Chronic Dis. 2017 Mar 16;14:E24. [PMC free article: PMC5364735] [PubMed: 28301314]

24.

Menke A, Casagrande S, Geiss L, Cowie CC. Prevalence of and Trends in Diabetes Among Adults in the United States, 1988-2012. JAMA. 2015 Sep 08;314(10):1021-9. [PubMed: 26348752]

25.

Guo F, Garvey WT. Cardiometabolic Disease Staging Predicts Effectiveness of Weight-Loss Therapy to Prevent Type 2 Diabetes: Pooled Results From Phase III Clinical Trials Assessing Phentermine/Topiramate Extended Release. Diabetes Care. 2017 Jul;40(7):856-862. [PMC free article: PMC5481985] [PubMed: 28455281]

26.

Kotsis V, Stabouli S, Bouldin M, Low A, Toumanidis S, Zakopoulos N. Impact of obesity on 24-hour ambulatory blood pressure and hypertension. Hypertension. 2005 Apr;45(4):602-7. [PubMed: 15723966]

27.

Ross R. Atherosclerosis--an inflammatory disease. N Engl J Med. 1999 Jan 14;340(2):115-26. [PubMed: 9887164]

28.

Ledwozyw A, Michalak J, Stepień A, Kadziołka A. The relationship between plasma triglycerides, cholesterol, total lipids and lipid peroxidation products during human atherosclerosis. Clin Chim Acta. 1986 Mar 28;155(3):275-83. [PubMed: 3708856]

29.

Taylor WC, Landau WM. Atherosclerosis and stroke. Ann Neurol. 1990 Jul;28(1):108-9. [PubMed: 2375626]

30.

Kincaid-Smith P. Hypothesis: obesity and the insulin resistance syndrome play a major role in end-stage renal failure attributed to hypertension and labelled 'hypertensive nephrosclerosis'. J Hypertens. 2004 Jun;22(6):1051-5. [PubMed: 15167435]

31.

Kambham N, Markowitz GS, Valeri AM, Lin J, D'Agati VD. Obesity-related glomerulopathy: an emerging epidemic. Kidney Int. 2001 Apr;59(4):1498-509. [PubMed: 11260414]

32.

Jackson VM, Price DA, Carpino PA. Investigational drugs in Phase II clinical trials for the treatment of obesity: implications for future development of novel therapies. Expert Opin Investig Drugs. 2014 Aug;23(8):1055-66. [PubMed: 25000213]

33.

Scheen AJ. Cardiovascular risk-benefit profile of sibutramine. Am J Cardiovasc Drugs. 2010;10(5):321-34. [PubMed: 20860415]

34.

Aronne LJ, Wadden TA, Peterson C, Winslow D, Odeh S, Gadde KM. Evaluation of phentermine and topiramate versus phentermine/topiramate extended-release in obese adults. Obesity (Silver Spring). 2013 Nov;21(11):2163-71. [PubMed: 24136928]

35.

Shin JH, Gadde KM. Clinical utility of phentermine/topiramate (Qsymia™) combination for the treatment of obesity. Diabetes Metab Syndr Obes. 2013;6:131-9. [PMC free article: PMC3626409] [PubMed: 23630428]

36.

Apovian CM, Aronne L, Rubino D, Still C, Wyatt H, Burns C, Kim D, Dunayevich E., COR-II Study Group. A randomized, phase 3 trial of naltrexone SR/bupropion SR on weight and obesity-related risk factors (COR-II). Obesity (Silver Spring). 2013 May;21(5):935-43. [PMC free article: PMC3739931] [PubMed: 23408728]

Disclosure: Zoia Khattak declares no relevant financial relationships with ineligible companies.

Disclosure: Farah Zahra declares no relevant financial relationships with ineligible companies.