Diabetes and Obesity

Living reference work entry
Part of the Endocrinology book series (ENDOCR)


The prevalence of obesity and diabetes has reached epidemic proportions worldwide and contributes to premature mortality. Obesity describes an abnormal or excessive fat accumulation and is defined by a body mass index ≥30 kg/m2. Obesity increases the risk for metabolic and cardiovascular diseases, musculoskeletal disorders, some types of cancer, pulmonary, and psychological diseases. A doubling of the obesity prevalence since the 1980s may be caused by a globally increased intake of energy-dense foods with a parallel decrease in daily physical activity due to the increasingly sedentary nature of many forms of work, changing modes of transportation, and increasing urbanization. Obesity represents the strongest modifiable risk factor for type 2 diabetes (T2D). Obesity and T2D may develop on a common genetic risk background. Mechanisms linking obesity to T2D include abdominal fat distribution, adipose tissue dysfunction, or inflammation characterized by the secretion of a diabetogenic adipokine pattern which contributes to impaired insulin action in skeletal muscle, liver, brain, and other organs. In patients with obesity and T2D, therapeutic weight reduction leads to improvements of all metabolic disturbances including beneficial effects on insulin sensitivity, lipid metabolism, liver fat, and chronic inflammation. Weight loss could be achieved by caloric restriction combined with increased physical activity and behavior training in the context of multimodal interventions. Pharmacotherapies may support additional weight loss, and for patients with overweight or obesity-associated T2D antihyperglycemic treatment strategies which promote weight loss should be preferred. However, bariatric surgery is the approach with the best long-term efficacy to treat morbid obesity and may lead to significant improvements on obesity-comorbidities including a high remission rate of T2D.


Obesity Diabetes Adipose tissue Insulin resistance Adipokines Beta cell function Fat distribution Genetics Weight loss Diet Pharmacotherapy Bariatric surgery 


Obesity is characterized by an excess of body fat mass and is defined by a body mass index equal to or greater than 30 kg/m2. Its prevalence has increased considerably over the past decades in all parts of the world and currently affects 15–30% of the adult populations in Western countries. This worldwide obesity epidemic has become a major health concern, because it contributes to higher mortality due to an increased risk for noncommunicable diseases including type 2 diabetes, cardiovascular diseases, musculoskeletal disorders, and some cancers including endometrial, breast, ovarian, prostate, liver, gallbladder, kidney, and colon. Obesity represents by far the most important modifiable risk factor for type 2 diabetes mellitus. An abdominal type of body fat distribution is closely associated with type 2 diabetes, particularly in the lower body mass index categories. Insulin resistance may link accumulation of adipose tissue in obesity to type 2 diabetes although the underlying mechanisms are not completely understood.

The fundamental cause of obesity is an energy imbalance between calories consumed and calories expended. Both obesity and type 2 diabetes have a strong genetic background. The known susceptibility genes for obesity mainly affect central pathways of food intake, whereas most risk genes for type 2 diabetes compromise β-cell function. In addition, environmental factors contribute to obesity. Such factors include permanent availability of foods, energy-dense diets, lack of physical activity, and low socioeconomic status.

At least theoretically, obesity is largely preventable. Obesity could be reduced by supportive environments and communities shaping people’s choices, by making the choice of healthier foods and regular physical activity the most accessible, available, and affordable choice. At the individual level, obesity could be prevented and treated by limiting energy intake from total fats and sugars; increasing consumption of fruit, vegetables and legumes, whole grains and nuts; and engaging in regular physical activity (60 min a day for children and 150 min spread through the week for adults) (WHO).

Weight loss improves – in part as a function of the extent of reducing body weight and fat mass – all noncommunicable obesity-related diseases. Weight management including weight loss and maintaining a healthier body weight can be achieved by dietary therapy, physical activity, behavior modification, pharmacotherapy, and weight loss surgery. Surgical obesity treatment is the most powerful approach to treat morbid obesity and may lead to a marked improvement of the metabolic disturbances if not the resolution of type 2 diabetes.

Definition of Obesity

Obesity is defined as abnormal or excessive fat accumulation that may impair health (National Institute for Health and Clinical Excellence 2014). Body mass index (BMI) is a simple index of weight-for-height that is commonly used to classify overweight and obesity in adults. It is defined as a person’s weight in kilograms divided by the square of his height in meters (kg/m2). According to the World Health Organization (WHO) (WHO fact sheet 2016), a BMI greater than 30 kg/m2 is the central formal criterion for the definition of obesity (Table 1). For individuals with a BMI greater than 30 kg/m2, obesity is further subdivided into three classes depending on the severity of excessive body fat (Table 1). The BMI range of 25–29.9 kg/m2 represents the category of overweight or preobesity which requires additional criteria to assess the concomitant health risks.
Table 1

Classification of human obesity based on body mass index (BMI). (Reproduced from World Health Organization 2016)


BMI (kg/m2)



Normal weight





 Grade I


 Grade II


 Grade III


Definition and Classification of Diabetes

Diabetes may be diagnosed based on HbA1C criteria or plasma glucose criteria, either the fasting plasma glucose (FPG) or the 2-h plasma glucose (2-h PG) value after a 75-g oral glucose tolerance test (OGTT) (Table 2). Diabetes is a group of metabolic diseases characterized by hyperglycemia resulting from defects in insulin secretion, insulin action, or both (ADA 2015). The chronic hyperglycemia of diabetes is associated with long-term damage, dysfunction, and failure of different organs, especially the eyes, kidneys, nerves, heart, and blood vessels. Diabetes can be classified into four general categories (Table 3). Type 1 diabetes is caused by (autoimmune) β-cell destruction, usually leading to absolute insulin deficiency. Type 2 diabetes accounts for ∼90–95% of diabetes cases and encompasses individuals who have insulin resistance combined with relative insulin deficiency (ADA 2010). Most likely, pathogenetic factors including obesity-associated diabetes are more heterogeneous. Another category of diabetes is gestational diabetes mellitus (GDM), which is diagnosed in the second or third trimester of pregnancy, but is not considered clearly overt diabetes. Under a fourth category, specific types of diabetes are summarized, which are due to other causes, e.g., monogenic diabetes syndromes, including neonatal diabetes and maturity-onset diabetes of the young (MODY), diseases of the exocrine pancreas, and drug- or chemical-induced diabetes (Table 3).
Table 2

Diagnostic criteria for diabetes according to the American Diabetes Association (ADA 2015)

HbA1C ≥6.5%. The test should be performed in a laboratory using a method that is NGSP certified and standardized to the DCCT assaya


FPG ≥126 mg/dL (7.0 mmol/L). Fasting is defined as no caloric intake for at least 8 ha


2-h PG ≥200 mg/dL (11.1 mmol/L) during an OGTT. The test should be performed as described by the WHO, using a glucose load containing the equivalent of 75 g anhydrous glucose dissolved in watera


In a patient with classic symptoms of hyperglycemia or hyperglycemic crisis, a random plasma glucose ≥200 mg/dL (11.1 mmol/L)

aIn the absence of unequivocal hyperglycemia, results should be confirmed by repeat testing

Table 3

Etiologic classification of diabetes mellitus (ADA 2010)

I. Type 1 diabetes (β-cell destruction, usually leading to absolute insulin deficiency)

 A. Immune mediated

 B. Idiopathic

II. Type 2 diabetes (may range from predominantly insulin resistance with relative insulin deficiency to a predominantly secretory defect with insulin resistance)

III. Other specific types

 A. Genetic defects of β-cell function

  1. Chromosome 12, HNF-1α (MODY3)

  2. Chromosome 7, glucokinase (MODY2)

  3. Chromosome 20, HNF-4α (MODY1)

  4. Chromosome 13, insulin promoter factor-1 (IPF-1; MODY4)

  5. Chromosome 17, HNF-1β (MODY5)

  6. Chromosome 2, NeuroD1 (MODY6)

  7. Mitochondrial DNA

  8. Others

 B. Genetic defects in insulin action

  1. Type A insulin resistance

  2. Leprechaunism

  3. Rabson-Mendenhall syndrome

  4. Lipoatrophic diabetes

  5. Others

 C. Diseases of the exocrine pancreas

  1. Pancreatitis

  2. Trauma/pancreatectomy

  3. Neoplasia

  4. Cystic fibrosis

  5. Hemochromatosis

  6. Fibrocalculous pancreatopathy

  7. Others

 D. Endocrinopathies

  1. Acromegaly

  2. Cushing’s syndrome

  3. Glucagonoma

  4. Pheochromocytoma

  5. Hyperthyroidism

  6. Somatostatinoma

  7. Aldosteronoma

  8. Others

 E. Drug or chemical induced

  1. Vacor

  2. Pentamidine

  3. Nicotinic acid

  4. Glucocorticoids

  5. Thyroid hormone

  6. Diazoxide

  7. β-adrenergic agonists

  8. Thiazides

  9. Dilantin

  10. γ-Interferon

  11. Others

 F. Infections

  1. Congenital rubella

  2. Cytomegalovirus

  3. Others

 G. Uncommon forms of immune-mediated diabetes

  1. “Stiff-man” syndrome

  2. Anti-insulin receptor antibodies

  3. Others

 H. Other genetic syndromes sometimes associated with diabetes

  1. Down syndrome

  2. Klinefelter syndrome

  3. Turner syndrome

  4. Wolfram syndrome

  5. Friedreich ataxia

  6. Huntington chorea

  7. Laurence-Moon-Biedl syndrome

  8. Myotonic dystrophy

  9. Porphyria

  10. Prader-Willi syndrome

  11. Others

 IV. Gestational diabetes mellitus

Epidemiology of Obesity and Diabetes

Obesity has reached epidemic proportions globally with a prevalence which has more than doubled since 1980. According to the WHO, more than 1.9 billion adults were overweight and of these, over 600 million were obese (WHO 2016) in 2014. Overall, about 13% of the world’s adult population (11% of men and 15% of women) were obese in 2014. Overweight and obesity are linked to more deaths worldwide than underweight. Globally there are more people who are obese than underweight – this occurs in every region except parts of sub-Saharan Africa and Asia. Forty-one million children under the age of 5 were overweight or obese in 2014. Once considered a high-income country problem, obesity prevalence is now increasing in low- and middle-income countries, particularly in urban settings. In Africa, the number of children who are overweight or obese has nearly doubled from 5.4 million in 1990 to 10.6 million in 2014 (WHO). In the context of the Global Burden of Disease Study (GBD) (Ng et al. 2014), estimates of the prevalence of overweight and obesity were reported for men and women in different age groups separately from 188 countries and 21 regions (Fig. 1).
Fig. 1

Age-standardized prevalence of obesity (BMI ≥ 30kg/m2), age >20 years in man and women 2013. (Taken from GBD 2013 Mortality and Causes of Death Collaborators 2015)

From 1980 to 2013, combined prevalence of overweight and obesity increased by 27.5% (from 921 million to 2.1 billion) for adults and by 47.1% for children (Ng et al. 2014). This trend in age-standardized global obesity prevalence was observed in developing and developed countries (Fig. 1; Ng et al. 2014). The proportion of adults with a BMI of ≥25 increased from 28.8% (28.4–29.3) in 1980 to 36.9% (36.3–37.4) in 2013 for men and from 29.8% (29.3–30.2) to 38.0% (37.5–38.5) for women (Ng et al. 2014). In developed countries, men have higher rates of obesity, while in developing countries, women exhibit higher rates and this relationship persists over time. The rate of increase of obesity was most pronounced between 1992 and 2002, but has slowed down over the last decade, particularly in developed countries (Ng et al. 2014).

In parallel to the significant increase in obesity prevalence since 1980, age-standardized diabetes prevalence in adults has almost quadrupled with a faster increase in low/middle-income compared to high-income countries (Zhou et al. 2016). In the NCD Risk Factor Collaboration, data from 751 studies including more than 4 million adults from 146 countries were used to estimate global age-standardized diabetes prevalence, which increased from 4.3% in 1980 to 9.0% in 2014 in men and from 5.0% to 7.9% in women (Zhou et al. 2016). The number of adults with diabetes in the world increased from 108 million in 1980 to 422 million in 2014 (Table 2). Age-standardized adult diabetes prevalence in 2014 was lowest in northwestern Europe and highest in Polynesia and Micronesia, at nearly 25%, followed by Melanesia and the Middle East and north Africa (Table 4).
Table 4

Estimated prevalence of people with diabetes (age >18 years). (Modified from NCD Risk Factor Collaboration. Worldwide diabetes prevalence data from 1980 and 2014 from a pooled analysis of 751 population-based studies with more than 4 million participants. Modified from Zhou et al. 2016)

WHO region

Prevalence (%)

Number (millions)






The Americas





Eastern Mediterranean










South-East Asia





Western Pacific










Pathophysiology of Obesity and Diabetes

The fundamental cause of obesity is an energy imbalance between calories consumed and calories expended. Globally, there has been an increased intake of energy-dense foods that are high in fat and a decrease in physical activity due to the modern sedentary nature of many forms of work, changing modes of transportation, and increasing urbanization (WHO 2016). In addition, genetic factors may underlie heterogeneous susceptibility for the extent of weight gain upon overeating, physical activity, and our adipogenic environment (Hauner 2010).

Changes in dietary and physical activity patterns are often the result of environmental and societal changes associated with development and lack of supportive policies in sectors such as health, agriculture, transport, urban planning, environment, food processing, distribution, marketing, communication, and education (Swinburn et al. 2011). Most likely a complex gene–environment interaction determines the individual risk to develop obesity.

In humans, energy homeostasis is under tight control and a stable body weight is very well defended across challenges including times of hunger and overeating. The tight defense of body weight (loss) suggests the existence of a setpoint for body weight, which can vary substantially among individuals and may also vary across lifetime (Hauner 2010). Appetite and satiety a regulated by a complex system which controls energy homeostasis. This system integrates central pathways and signals from peripheral organs (e.g., leptin from adipose tissue, gut hormone secretion in response to meals, signals from the gastrointestinal nervous system, nutrients). These signals induce a complex response in the central nervous system specifically in the anorexigenic leptin–melanocortin and the orexigenic NPY–AgRP pathway according to dietary intake and nutrient requirements of the organism (Hauner 2010). Other factors such as insulin may modify these signaling processes and thereby influence energy balance (Schwartz et al. 2000). A complex homeostatic system serves to defend body weight against critical energy deficits or chronic overnutrition. Several adaptive systems are known to restore the initial body weight under such fluctuations of energy intake and expenditure. This may explain why obese humans exhibit a strong tendency to regain weight after intentional dietary weight reduction. The same tendency to return to initial body weight is observed after experimental overfeeding. The role of energy homeostasis in the development of obesity has been elaborated by previous studies using indirect calorimetry to investigate the contribution of the resting metabolic rate to the risk of obesity. Importantly, reduced resting energy expenditure predicts body weight gain in Pima Indians (Ravussin et al. 1988).

Environmental factors that may contribute to both the development of obesity and type 2 diabetes include almost unlimited availability and high palatability of food, high energy density and relatively low cost of foods, high consumption of sugar-sweetened beverages, aggressive commercial food promotion, culture of fast food, and low physical activity (Hauner 2010). Importantly, the socioeconomic status is a strong determinant of obesity and of T2D. In most countries, there is a gradient between education and household income and the prevalence of obesity. A low socioeconomic status is associated with an unfavorable lifestyle including poor nutrition, low leisure-time physical activity, and low health consciousness. Thus, the association between low household income and obesity may be mediated by the low costs of energy-dense foods, whereas prudent healthy diets based on lean meats, fish, vegetables, and fruit may be less affordable for those of lower socioeconomic status (Hauner 2010). The enormous complexity of the causal relations and determinants of obesity (Fig. 2), and their inter-relations may explain why strategies to prevent or treat obesity have widely failed. In addition, the mechanisms causing obesity are not understood well enough to offer an effective prevention and etiology-based individualized treatment.
Fig. 2

Pathogenesis of obesity. Obesity is caused by a chronic positive energy balance characterized by overeating, low energy expenditure, and low physical activity. The complex individual, socio-cultural, and environmental pathogenic factors are not understood well enough to offer an etiology-based obesity treatment. Changes in dietary and physical activity patterns are often the result of environmental and societal changes associated with development and lack of supportive policies in sectors such as health, agriculture, transport, urban planning, environment, food processing, distribution, marketing, communication, and education. As a consequence of obesity, the risk of metabolic and vascular diseases such as type 2 diabetes, fatty liver disease, hypertension, coronary heart disease, and peripheral artery disease, but also pulmonary diseases, osteoarthritis, psychological disorders, and several types of cancer increases

In the context of the relationship between obesity and impaired glucose metabolism, this chapter focuses on type 2 diabetes. T2D is characterized by an impaired insulin action or a defective secretion of insulin or a combination of both (Fig. 3). Both defects are thought to be required for the manifestation of the disease, and both are present many years before the clinical onset of the disease. Whereas insulin resistance is an early phenomenon partly related to obesity, pancreas β-cell function declines gradually over time already before the onset of clinical hyperglycemia (Stumvoll et al. 2005). In the pathogenesis of T2D, several mechanisms have been proposed, including increased nonesterified fatty acids, inflammatory cytokines, adipokines, and mitochondrial dysfunction for insulin resistance, and glucotoxicity, lipotoxicity, and amyloid formation for β-cell dysfunction. To understand the cellular and molecular mechanisms causing T2D, it is necessary to conceptualize the framework within which glycemia is controlled. Insulin is the key hormone for regulating blood glucose and, generally, normoglycemia is maintained by the balanced interplay between insulin action and insulin secretion. It is important to note that the normal pancreatic cell is capable of adapting to changes in insulin action, i.e., a decrease in insulin action is accompanied by upregulation of insulin secretion (and vice versa), and there is a curvilinear relationship between normal beta cell function and insulin sensitivity (Stumvoll et al. 2005) (Fig. 3). Deviation from this “hyperbola” such as in individuals with IGT and T2D occurs when beta cell function is inadequately low for a given degree on insulin sensitivity (Fig. 3). Thus, beta cell dysfunction is a critical component in the pathogenesis of type 2 diabetes. This concept has been verified by longitudinal studies in Pima Indians progressing from normal to impaired glucose tolerance to type 2 diabetes (Stumvoll et al. 2005). On the other hand, when insulin action decreases such as in response to weight gain, the system normally compensates by increasing beta cell function. However, at the same time, fasting and 2-h glucose concentrations will increase significantly. This increase may well be small but over time and due to glucose toxicity becomes damaging and in itself a cause for beta cell dysfunction. Thus, even with (theoretically) unlimited beta cell reserve insulin resistance sets the path to hyperglycemia and type 2 diabetes (Stumvoll et al. 2005). Importantly, the capacity of the organism to compensate for various challenges on glucose homeostasis may have a strong genetic component, however only a few “T2D-genes” have been identified so far.
Fig. 3

Hyperbolic relation between β-cell function and insulin sensitivity. IGT impaired glucose tolerance, NGT normal glucose tolerance, T2DM type 2 diabetes mellitus. (Reproduced from Stumvoll et al. 2005)

Genetics of Obesity and Diabetes

Family, adoption, and twin studies have provided strong evidence that obesity and T2D are heritable traits (Hauner 2010; Franks and McCarthy 2016). As an example, an adoption study demonstrated that there was no resemblance between the adult BMI of adopted Danish children and the BMI of the adopting parents, but a significant correlation to the BMI of the biologic parents, especially to the BMI class of the biologic mother (Stunkard et al. 1986b). In a twin study of obesity, concordance rates for different degrees of overweight were twice as high for monozygotic twins as for dizygotic twins. This high heritability for BMI was seen at the age of 20 years and to a similar extent at a 25-year follow-up, suggesting that body fatness is under substantial genetic control (Stunkard et al. 1986a). There is also a very close correlation in monozygotic twins who were reared apart, also indicating a high heritability of the BMI trait. In a systematic study among 5092 twins investigated in the UK, the estimated heritability of BMI and waist circumference was 0.77, further supporting the strong effect of the genetic components irrespective of the environment (Wardle et al. 2008).

Our understanding of the genetic causes of obesity has been improved during recent years by discoveries of monogenic disorders that result in excessive fat accumulation. Although monogenic obesity only occurs in very rare cases, characterization of the causative variants led to novel concepts in the pathophysiology and potentially the future treatment of obesity.

Monogenic obesity is typically diagnosed in childhood as early onset obesity due to extreme alterations of appetite and satiety. Following the discovery that a lack of the adipose tissue hormone leptin causes the extremely obese phenotype of the ob/ob mouse model (Zhang et al. 1994), rare cases of monogenetically inherited leptin deficiency have been also found in humans (Farooqi et al. 1999). Importantly, for individuals with a loss-of-function mutation in the leptin gene, a truly etiology-based obesity treatment is available through compassionate use of recombinant leptin (Farooqi et al. 1999). As another example, patients with rare defects in the gene encoding proopiomelanocortin (POMC) have extreme early-onset obesity, hyperphagia, hypopigmentation, and hypocortisolism, resulting from the lack of the proopiomelanocortin-derived peptides melanocyte-stimulating hormone and corticotropin (Kühnen et al. 2016). In these individuals, treatment with the melanocortin-4 receptor agonist setmelanotide leads to sustainable reduction in hunger and substantial weight loss (Kühnen et al. 2016). Until now, several homozygous and compound heterozygous mutations have been described in genes that are involved in the central control of food intake, some of them with functional consequences resulting in human obesity (Franks and McCarthy 2016). Functional mutations in the melanocortin-4-receptor gene are considered to be the most frequent cause of monogenic obesity in children with a frequency of 2–4% of all obese cases (Hauner 2010).

Supporting the hypothesis that central mechanisms of food intake regulation are the main pathogenetic factors in obesity development and that obesity represents a heritable neurobehavioral disorder that is highly sensitive to environmental conditions, genome-wide association studies (GWAS) in large cohorts reported common genetic variants associated with BMI mainly related to central pathways of food intake (Frayling et al. 2007). Despite these remarkable advances in our understanding of the genetic factors related to obesity, the effect size of most of the BMI-related gene variants is rather modest. For example, homozygous carriers of the obesity-related variant with the strongest effect size in the FTO gene identified in GWAS have only 3 kg higher body weight compared to carriers of the two low-risk alleles (Frayling et al. 2007). Importantly, FTO is mainly expressed in the brain and in the arcuate nucleus of the hypothalamus and may thus play a role in regulation of food intake (Hauner 2010). All other recently discovered gene polymorphisms, including variants in the MC4R gene influence body weight by far less than 1 kg (Hauner 2010). Thus, obesity represents a rather heterogeneous disorder in terms of genetic background and susceptibility to etiologic environmental factors. In addition, the risk for developing co-morbidities including T2D may strongly depend on the individual genetic predisposition towards such diseases. In the case of T2D, the lifetime risk of developing this disease is about 30% in the white North American population and similar in other ethnic groups (Narayan et al. 2003). Importantly, the genetic risk for T2D may additionally be determined by genetic factors related to beta cell function (Scott et al. 2017) and the interaction between genes and macronutrient intake (Li et al. 2017).

In the search for genetic risk factors for the development of T2D, the candidate gene approach, i.e., identifying a causative factor among the obvious biological candidates for insulin resistance and insulin secretion defects, has not provided significant advances to the field (Stumvoll et al. 2005). Variants in many candidate genes were extensively studied over the past 2 decades, such as the Gly972Arg polymorphism in IRS-1, the Gly1057Asp polymorphism in IRS-2, the Trp64Arg polymorphism in the beta-3 adrenergic receptor, the –308 G/A promoter variant in tumor necrosis factor α or variants in the adiponectin gene. In most instances, the initial association was not replicated in subsequent analyses and, currently, the most robust single candidate variant is the highly prevalent Pro12Ala polymorphism in peroxisome proliferator-activated receptor (PPAR)γ (reviewed in Stumvoll et al. 2005). The Gly972Arg polymorphism in IRS-1, an intuitive variant to be associated with insulin resistance, may have a weak association with type 2 diabetes, although possibly through beta cell dysfunction rather than insulin resistance (Porzio et al. 1999). Among the many candidate genes for insulin secretory dysfunction, those encoding the sulphonylurea receptor-1 (SUR1) and the potassium inward rectifier (KIR) 6.2, a potassium channel, have been most extensively studied. The two genes (ABCC8 and KCNJ11, respectively) are adjacent to one another on chromosome 11. There is insufficient evidence for association of two widely studied SUR1 polymorphisms (exon 16-3t/c, exon 18 T759T) with type 2 diabetes (Gloyn et al. 2003). Meta-analyses on the E23K variant in the KIR6.2 gene are more robust, suggesting a ~15 % increased risk of type 2 diabetes for the K allele (Gloyn et al. 2003) most likely through decreased insulin secretion. A recent haplotype analysis using an independent dataset not only confirmed the association with the KIR6.2 variant but further substantiated the notion that genetic variation in the SUR1/KIR6.2 region is associated with type 2 diabetes.

Interestingly, analyses from the European Prospective Investigation into Cancer (EPIC) study, significant interactions between macronutrients and genetic variants in or near transcription factor 7-like 2 (TCF7L2), gastric inhibitory polypeptide receptor (GIPR), caveolin 2 (CAV2), and peptidase D (PEPD) have been described (Li et al. 2017). For the majority of the newly identified obesity and T2D genes, the main challenge remains to elicit their function and main targets. Understanding the mode of action for these candidate genes may facilitate their future clinical use as pharmacotherapies, drug targets, or predictors of obesity and T2D.

Obesity: A Major Risk Factor for Type 2 Diabetes

The mechanisms by which obesity increases the risk of developing T2D are only partly understood and the evolving picture is getting more and more complex. The main adverse effect of obesity is on the action of insulin, particularly in liver, muscle, and adipose tissue, but obesity also affects insulin secretion. Substantial advances have been made over recent years in our understanding how an excessive fat mass, but also chronic over-nutrition, may cause metabolic disturbances resulting in overt T2D in those with a genetic predisposition for the disease.

There are several mechanisms mediating the link and interaction between obesity and T2D (Fig. 4). Obesity (i.e., excessive fat accumulation), adverse fat distribution, and impaired adipose tissue function may cause impaired insulin signaling and insulin secretion defects via increased nonesterified (free) fatty acids (NEFA) from lipolysis, glucose toxicity in response to reduced peripheral glucose uptake and secretion of adipokines (e.g., leptin, adiponectin), and pro-inflammatory cytokines (e.g., IL-6, TNF-alpha, MCP-1) (Fig. 4). As an example, increased mass, especially in visceral or deep subcutaneous adipose depots, leads to adipocyte hypertrophy which are themselves resistant to the ability of insulin to suppress lipolysis. This results in elevated release and circulating levels of NEFA and glycerol, both of which aggravate insulin resistance in skeletal muscle and liver (Stumvoll et al. 2005).
Fig. 4

Model of factors linking obesity (including adipose tissue dysfunction), systemic insulin resistance and impaired insulin secretion as potential mechanisms how obesity increases the risk for type 2 diabetes. Several mechanisms including increased lipolysis, higher free fatty acid (FFA) release from adipose tissue, reduced glucose uptake, and the increased secretion of diabetogenic, atherogenic, and pro-inflammatory signals may cause impaired insulin sensitivity. Altered adipokine (e.g., adiponectin, leptin, chemerin, progranulin) and pro-inflammatory cytokine (e.g., IL-6, TNF-α, MCP-1, PAI-1) secretion from adipose tissue may directly impair insulin signaling (e.g., liver, skeletal muscle) or activate pro-inflammatory pathways in target tissues which causes local and subsequently systemic insulin resistance. IL interleukin, TNF-α tumor necrosis factor α, MCP-1 monocyte-chemotactic-protein-1, PAI-1 plasminogen activator inhibitor-1. (Modified from Blüher 2016)

Role of Glucose Toxicity

Because hyperglycemia itself can decrease insulin secretion, the concept of glucose toxicity has been developed and may represent a mechanistic link between obesity and T2D (Fig. 4). Glucose toxicity may initially cause reversible, but in the context of chronic hyperglycemia sustained damage to cellular components of insulin production over time (Stumvoll et al. 2005, DeFronzo 2010). Even short-term hyperglycemia induced by prolonged hyperglycemic clamp studies in individuals with normal glucose metabolism causes significant deterioration of insulin sensitivity and insulin secretion (Brunzell et al. 1976). In beta cells, oxidative glucose metabolism will lead to production of reactive oxygen species (ROS), normally detoxified by catalase and superoxide dismutase. Beta cells are equipped with a low amount of these proteins and also of the redox-regulating enzyme glutathione peroxidase (Robertson et al. 2003). Hyperglycemia has been proposed to lead to large amounts of ROS in beta cells, with subsequent damage to cellular components. Loss of pancreas duodenum homeobox-1 (PDX-1), a critical regulator of insulin promoter activity, has also been proposed as an important mechanism leading to beta cell dysfunction (Robertson et al. 2003). In addition, ROS are known to enhance NF-κB activity, which may induce apoptosis of beta cells.

Role of Lipotoxicity

Increased levels of NEFA released by expanded (predominantly visceral) adipose tissue adversely influence the insulin signaling cascade (Stumvoll et al. 2005). NEFA inhibit insulin-stimulated glucose metabolism in skeletal muscle and suppress glycogenolysis in liver (Boden and Shulman 2002). Fatty acids lead to enhanced insulin secretion in acute studies, but after 24 h they actually inhibit insulin secretion. In the presence of glucose, fatty acid oxidation in beta cells is inhibited and accumulation of long-chain acyl CoA (LC-CoA) occurs (Stumvoll et al. 2005). This has been proposed to be an integral part of the normal insulin secretory process. However, long-chain acyl CoA itself can also diminish the insulin secretory process by opening beta cell potassium channels. A second mechanism possibly involved in the negative effect of fatty acids on insulin secretion may be increased expression of uncoupling protein-2 (UCP-2), which would lead to less ATP formation and, hence, less insulin secretion. A third mechanism may involve apoptosis of beta cells possibly via fatty acid or triglyceride-induced ceramide synthesis or generation of reactive oxygen species and/or nitric oxide (Stumvoll et al. 2005). NEFA activate cellular kinases, including atypical protein kinase C isoforms by increasing cellular diacylglycerol levels, which can activate the inflammatory kinases inhibitor κB kinase (IKK) and c-jun N-terminal kinase (JNK), increasing serine/threonine phosphorylation of IRS-1, and reducing downstream IRS-1 signaling (Stumvoll et al. 2005, Boden and Shulman 2002). Adipose tissue secreted cytokines including TNFα enhance adipocyte lipolysis and contribute further to increased NEFA plasmaconcentrations, which may subsequently deteriorate beta cell function and glucose-stimulated insulin secretion (Stumvoll et al. 2005; Blüher 2013). Experimental NEFA elevation to reproduce levels in type 2 diabetes causes severe muscle/liver insulin resistance and inhibits insulin secretion (reviewed in: DeFronzo 2010). Elevated plasma NEFA impair glucose oxidation/glycogen synthesis and decrease glucose transport/phosphorylation (reviewed in: DeFronzo 2010). Most importantly, lipid infusion to increase plasma NEFA levels in participants with normal glucose tolerance caused a dose–response inhibition of insulin receptor/IRS-1 tyrosine phosphorylation and PI-kinase activity, which correlate closely with reduced insulin-stimulated glucose disposal (Belfort et al. 2005).

Role of Insulin Resistance

Insulin resistance is defined as the inability of a known quantity of exogenous or endogenous insulin to increase glucose uptake and utilization in an individual as much as it does in a normal population (Lebovitz 2001). Insulin action is the consequence of insulin binding and activating of its specific plasma membrane receptor with tyrosine kinase activity and is transmitted through the cell by a series of protein-protein interactions. Two major cascades of protein-protein interactions mediate intracellular insulin action: one pathway is involved in regulating intermediary metabolism and the other plays a role in controlling growth processes and mitoses (Lebovitz 2001). The regulation of these two distinct pathways can be dissociated. Indeed, some data suggest that the pathway regulating intermediary metabolism is diminished in type 2 diabetes while that regulating growth processes and mitoses is normal. Genetic abnormalities of one or more proteins of the insulin action cascade, fetal malnutrition, adipose tissue dysfunction, and increased visceral adiposity have been suggested as major causes of insulin resistance (Lebovitz 2001; DeFronzo 2010). In the fasting state, skeletal muscle accounts for only a small proportion of glucose disposal (less than 20%), while endogenous glucose production from the liver is responsible for all of the glucose appearing in plasma (Stumvoll et al. 2005).

Cellular mechanisms of insulin resistance may contribute to tissue-related und systemic insulin resistance. Substrates of the insulin receptor kinase, most prominently the insulin receptor substrate (IRS) proteins, are phosphorylated on multiple sites, which serve as binding scaffolds for a variety of adaptor proteins and lead to the downstream signaling cascade (White 2002). Insulin activates a series of lipid and protein kinase enzymes linked to the translocation of glucose transporters to the cell surface, synthesis of glycogen, protein, mRNAs, and nuclear DNA that influences cell survival and proliferation (White 2002). In states of insulin resistance, one or more of the following molecular mechanisms to block insulin signaling are likely to be involved. The positive effects on downstream responses exerted by tyrosine phosphorylation of the receptor and the IRS proteins are opposed by dephosphorylation of these tyrosine side-chains by cellular protein-tyrosine phosphatases (PTPs) and by protein phosphorylation on serine and threonine residues (which often occur together) (Goldstein 2003). PTP1B is a widely expressed PTP which has been shown to play an important role in the negative regulation of insulin signaling (Goldstein 2003).

Serine/threonine phosphorylation of IRS-1 reduces its ability to act as a substrate for the tyrosine kinase activity of the insulin receptor and inhibits its coupling to its major downstream effector systems. Multiple IRS serine kinases have been identified, including various mitogen-activated protein kinases (MAPK/ERK), c-Jun NH2-terminal kinase (JNK), atypical protein kinase C, phosphatidylinositol 3′-kinase, among others (White 2002). Signal down-regulation can also occur via internalization and loss of the insulin receptor from the cell surface and degradation of IRS proteins (Stumvoll et al. 2005).

Body Fat Distribution and Risk for Type 2 Diabetes

Approximately 70% of individuals with obesity do not develop T2D, suggesting that fat accumulation alone does not explain the higher risk of T2D upon body weight gain. In this context, it has been consistently demonstrated that fat distribution rather than total body fat mass determines the individual obesity-associated risk for T2D (Schleinitz et al. 2014; Bjorntorp 1991). Fat stored in visceral adipose depots makes obese individuals more prone to T2D than fat distributed subcutaneously (Despres et al. 1989). Moreover, it has been demonstrated that reducing subcutaneous fat mass by liposuction does not ameliorate risk factors od T2D and cardiovascular diseases (Klein et al. 2004). On the other hand, visceral fat mass reduction by omentectomy combined with gastric banding resulted in long-term beneficial effects on glucose metabolism and insulin sensitivity (Thorne et al. 2002). The relationship of ectopic visceral fat deposition with T2D may be at least partially explained by intrinsic properties of visceral as opposed to subcutaneous adipose tissue with regard to decreased insulin sensitivity, lower angiogenic potential, increased lipolytic activity, different cellular composition, and the expression of genes regulating adipocyte function (Blüher 2009). In addition, the visceral fat depot drains into the portal vein, thus exposing the liver to undiluted metabolites, cytokines, and adipokines released from visceral fat, which could further contribute to an increased cardiometabolic risk (Schleinitz et al. 2014). Dysfunction of adipose tissue including ectopic fat deposition seems to play an important role in the individual risk of developing obesity-associated T2D. However, it is noteworthy that recent imaging studies, including the Framingham Heart Study, have highlighted not only the importance of visceral adipose tissue, but also other ectopic fat depots such as liver or renal fat (Speliotes et al. 2010, Foster et al. 2011).

Role of Adipose Tissue Dysfunction: A Mechanistic Link Between Obesity and Type 2 Diabetes

Adipose tissue represents the major organ for energy storage under conditions of caloric surplus. During periods of fasting and prolonged starvation, adipose tissue releases lipids to serve the energy demand of the body. In addition, adipose tissue contributes to insulation of the body, thermoregulation, and mechanical organ protection (Blüher 2013). With higher adipose tissue mass and fat accumulation, the risk to develop insulin resistance and type 2 diabetes increases (Colditz et al. 1995). On the other hand, deficiency or a complete lack of adipose tissue also causes insulin resistance, diabetes, fatty liver, and other metabolic alterations both in transgenic animals and in human lipodystrophies (Moitra et al. 1998; Robbins and Savage 2015). The association of lipodystrophy with metabolic diseases suggests that impaired lipid storage capacity of adipose tissue may underlie the link to insulin resistance and metabolic diseases, a hypothesis which is further supported by adipose tissue transplantation experiments in animal models demonstrating that increasing functional adipose tissue mass may have beneficial effects on glucose and lipid metabolism (Konrad et al. 2007; Tran et al. 2008).

Typically, there is a curvilinear relationship between insulin sensitivity and BMI (Fig. 5). With increasing BMI, insulin sensitivity decreases; however, there are subgroups of individuals with an either inadequately high insulin sensitivity despite BMI >40 kg/m2 which have been described as insulin sensitive patients with obesity (Klöting et al. 2010) or patients with lipodystrophy who are characterized by extreme insulin resistance at a BMI <25 kg/m2 (Fig. 5). Some of these phenotype characteristics of both excessive and lack of adipose tissue could be explained by altered adipocyte storage capacity, i.e., impaired expandability of subcutaneous adipose tissue, the release of diabetogenic metabolites, cytokines or adipokines or impaired lipogenesis and lipolysis (Blüher 2009).
Fig. 5

Relationship between insulin sensitivity and BMI in individuals with a wide range of insulin sensitivity and BMI. Despite the hyperbolic relationship between decreasing insulin sensitivity with increasing BMI, there are individuals with low BMI, but pronounced insulin resistance (e.g., lipodystophy) or with BMI> 40kg/m2, but insulin sensitivity similar to a person with a BMI <25 kg/m2. The dotted hyperbolic line is a regression curve of glucose infusion rate (GIR) during the steady state of an euglycemic-hyperinsulinemic clamp over BMI based on subjects at the University Hospital Leipzig outpatients clinics who underwent euglycemic clamps between 1996–2005. (Modified from Klöting et al. 2010)

These complex alterations of adipose tissue function may develop under conditions of a chronically positive energy balance due to continued overeating and low physical activity. Under these circumstances which describe the modern lifestyle in many parts of the world, adipose tissue mass increases (Fig. 6). Whereas a subgroup of individuals may respond to caloric access by expanding “healthy” subcutaneous fat depots through adipocyte hyperplasia and hypertrophy, the majority of patients with obesity exhibit an impaired expandability of subcutaneous adipose tissue. This inability to store energy in safe places may initiate a sequence of pathogenic factors including adipocyte hypertrophy, ectopic fat deposition (liver, visceral fat, skeletal muscle), hypoxia, adipocyte insulin resistance, increased stress response, autophagy, apoptosis causing impaired adipose tissue function which subsequently leads to end organ damage through adverse signals from adipose tissue (Fig. 6) (Blüher 2009).
Fig. 6

Potential mechanisms for the development of adipose tissue dysfunction. With a chronic excessive energy intake and low physical activity, a positive energy balance causes body weight gain and higher nutrient flux into adipose tissue. Adipocytes primarily respond to the higher demand for energy storage by increasing their size (adipocyte hypertrophy). Adipocyte hypertrophy is typically associated with increased hypoxia, cellular, and tissue stress (reflected by activation of JNK, NF-κB, and other stress kinases), increased production of pro-inflammatory cytokines (including TNF-α, IL-1β, monocyte chemoattractant protein-1, chemerin, progranulin, PAI-1), but also activation of autophagy and apoptosis (mainly in visceral depots) and increased release of cell-free DNA. Chemoattractant and endothelial adhesion molecules bind integrins and chemokine receptors on monocytes which subsequently recruits them into adipose tissue. As a result, adipose tissue inflammation may develop

With the discovery that adipose tissue produces and secretes hundreds of factors (e.g., leptin, adiponectin, TNF-α, sex steroids, adipsin) (Table 5, Fig. 7), it became clear that altered adipose tissue function could cause secondary changes in target organs of these adipokines (reviewed in Blüher 2016). Distinct cell types within adipose tissue produce pro-inflammatory cytokines/ adipokines including TNFα, transforming growth factor β (TGFβ) and interferon-γ, C-reactive protein (CRP), interleukins (IL) -1, -6, -8, -10, plasminogen activator inhibitor-1 (PAI-1), retinol binding protein-4 (RBP4), vaspin, endocannabinoids, fetuin-A, omentin, bone morphogenetic proteins (BMPs), clusterin, fractalkine, orosomucoid, fatty acid binding protein 4 (FABP4), fibrinogen, haptoglobin, angiopoietin-related proteins, metallothionein, complement factor 3, serum amyloid A (SAA) protein, anandamide and 2-AG as well as chemoattractant cytokines, such as monocyte chemotactic protein-1 (MCP-1), progranulin, and macrophage inflammatory protein-1α and others (Fig. 7, Table 5) (Blüher 2013). The majority of these adipokines are elevated in obese states and correlate with measures of fat mass, fat distribution and insulin sensitivity.
Table 5

Adipokines contribute to the regulation of biological processes. (Modified from Fasshauer and Blüher 2015)


Main actions


Satiety signal, regulation of appetite, food intake, locomotor activity, energy expenditure, fertility, and other processes


Improves insulin sensitivity, antidiabetic, anti-atherogenic, anti-inflammatory


Chemoattractant protein, regulation of adipogenesis

Tumor necrosis factor (TNF) α


Interleukin (IL)-6




Fatty acid binding protein-4 (FABP-4)

Associated with increased type 2 diabetes risk and impaired myocardial contractility

Fibroblast growth factor 21 (FGF21)

Stimulates glucose uptake into adipocytes, increases thermogenesis, energy expenditure, fat utilization, improves glucose and lipid metabolism

Retinol binding protein-4 (RBP4)

Related to insulin resistance, visceral fat distribution, dyslipidemia


Serine protease inhibitor, decreases food intake, improves hyperglycemia


inhibits insulin secretion


direct glucose-dependent insulinotropic effect on β-cells


Nampt-mediated systemic NAD biosynthesis is critical for β cell function

Monocyte chemotactic protein-1 (MCP-1)

Chemoattractant protein, adipose tissue inflammation


Chemoattractant protein, neurodegenerative diseases, adipose tissue inflammation


Reflects liver fat content, associated with lipid-induced inflammation, insulin resistance, promotes cancer progression


Anti-inflammatory, insulin sensitizing

Dipeptidyl peptidase-4 (DPP-4)

degrades GIP and GLP-1

Inhibitors in clinical use for type 2 diabetes


Promotes, tumor progression and angiogenesis

Bone morphogenetic protein-4 (BMP-4)

Regulates adipogenic precursor cell commitment and differentiation

Bone morphogenetic protein-7 (BMP-7)

Stimulates brown adipogenesis, reduces food intake, increases energy expenditure

Cathepsins S, L, K

Regulation of glucose metabolism and adipose tissue mass

Angiopoietin-like protein 8 (Angptl8)

Promotes pancreatic β-cell proliferation and improves glucose tolerance

Tissue inhibitor of matrix metalloproteinase-1 (TIMP-1)

decreases adipogenesis, impairs glucose tolerance


Related to obesity, insulin resistance, inflammation

Lipocalin 2

Related to insulin resistance and inflammation

Wnt1 inducible signaling pathway protein 1 (Wisp1)

Regulation of adipogenesis and adipose tissue inflammation


Activation of the alternative complement pathway

Transforming growth factor β (TGFβ)

Regulation of cell proliferation, differentiation and apoptosis

Vascular endothelial growth factor (VEGF)

Stimulates angiogenesis in adipose tissue

Fig. 7

Factors released or secreted by adipose tissue. Adipocytes, immune cells, fibroblasts, endothelial cells, and others contribute to the release of metabolites, lipids, and adipokines. Examples for adipose tissue derived molecules. 2-AG 2-arachidonoylglycerol, ASP acylating simulation protein, BMPs bone morphogenetic proteins, CTRPs C1q/TNF-related proteins, FGF21 fibroblast growth factor 21, MCP-1 monocyte chemotactic protein-1, PAI-1 plasminogen activator inhibitor-1, RAS renin angiotensin system, RBP-4 retinol binding protein-4. (Modified from Fasshauer and Blüher 2015)

Adipose tissue released factors contribute to the regulation of multiple important biological processes including the regulation of appetite and satiety control, fat distribution, insulin sensitivity and insulin secretion, energy expenditure, inflammation, blood pressure, hemostasis, and endothelial function, modulation of adipogenesis, immune cell migration into adipose tissue, adipocyte metabolism and function in an autocrine, paracrine manner as well as in an endocrine manner on target organs including the brain, liver, muscle, endothelium, heart, skin, and pancreatic β-cells (Fig. 8).
Fig. 8

Signals from adipose tissue modulate important biologic processes via autocrine, paracrine and endocrine mode of actions. Adipokines regulate adipogenesis, adipocyte metabolism, immune cell migration into adipose tissue via autocrine and paracrine signaling. In addition, adipokines have endocrine/systemic effects on appetite and satiety control, regulation of energy expenditure and activity, influence insulin sensitivity and energy metabolism in insulin-sensitive tissues, such as liver, muscle, and fat as well as insulin secretion in pancreatic β-cells. IL interleukin, TNFα tumor necrosis factor alpha, MCP-1 monocyte-chemotactic-protein-1, FABP4 fatty acid binding protein 4, RBP4 retinol-binding-protein-4. (Modified from Blüher 2013)

Although adipocytes represent the main parenchymal cell, adipose tissue is composed of several different cell types including preadipocytes, fibroblasts, endothelial, and other cells. Adipocytes can be categorized into white, brown, and the more recently described beige or brite adipocytes (Cinti 2012; Cohen and Spiegelman 2015; Waldén et al. 2012). Importantly, the distinction of these adipocyte subtypes was originally based on rodent adipose tissue only, but recently evidence for brown adipose tissue in adult humans could finally proof that heterogeneity in adipose tissue cellular composition can be translated into the human situation (van Marken Lichtenbelt et al. 2009; Cypess et al. 2009). The “adipose organ” has a remarkable plasticity displaying adipocyte transdifferentiation from white into brown phenotypes during chronic cold exposure, physical exercise, lactation, and obesity (Cinti 2012).

As an example for the plasticity of adipose tissue to respond to increased demands for fat storage, adipocytes may hypertrophy to volumes larger than 1000 pL or significantly increase their generation rate (hyperplasia) (Waldén et al. 2012). Data demonstrating that adipocyte number is tightly regulated at a constant level and determined during childhood suggest that increasing adipocyte size represents the main plasticity mechanism in response to a chronic positive energy balance (Spalding et al. 2008). In contrast to children, late-onset obesity in adults who gain body weight more slowly over years may initially respond to excess energy by adipocyte hypertrophy up to a certain threshold before recruiting precursor cells or mesenchymal stem cells to additionally increase adipocyte number (Spalding et al. 2008).

In an attempt to systemically characterize the changes that occur in adipose tissue from a variety of mouse models of obesity, Weisberg et al. (2003) found that with increasing adiposity, the number of macrophages in adipose tissue increases both in rodent models and humans. In subsequent studies, it was shown that macrophages in adipose tissue cluster around necrotic-like adipocyte death in crown-like structures, suggesting that scavenging of adipocyte debris is an important function of infiltrating macrophages in obese individuals (Cinti et al. 2005). In patients with obesity, macrophage infiltration has been shown to be significantly higher in visceral compared to subcutaneous adipose tissue (reviewed in Blüher 2016). Interestingly, adipose tissue macrophage number can be reduced by significant weight loss after bariatric surgery (Cancello et al. 2005). In addition to the number of macrophages in adipose tissue, it is important to note that switching the phenotype of macrophages belongs to the alterations associated with adipose tissue inflammation. Changes in the macrophage phenotypes are most likely regulated by cells of the adaptive immune system, i.e., with increasing fat mass upon high caloric intake, recruitment of B cells and T cells may precede macrophage infiltration into adipose tissue (Sell et al. 2012).

Infiltration of adipose tissue with immune cells may be considered a symptom of obesity and immune cells proliferating in adipose tissue and emigrating to other tissues could link increased adiposity to obesity-related metabolic diseases (Haase et al. 2014).

Prevention of Obesity and Type 2 Diabetes

Obesity and T2D are at least theoretically preventable, and therefore, the most important goal of ultimately reducing the population burden of obesity and diabetes is to prevent the diseases (WHO 2016). Several studies have demonstrated that diabetes can be delayed or prevented in individuals at high risk undergoing an intensive diet and exercise program or pharmacological interventions with metformin, acarbose, thiazolidinediones, or GLP-1 receptor agonists (reviewed in Stumvoll et al. 2005). The observation that improvement in one or more major pathogenic factors offsets or delays the progression from prediabetic states to diabetes underscores the contribution of each of these factors to the development of the disease, including insulin sensitivity, beta-cell function, and glucose excursions. Lifestyle modification has been difficult to maintain over a long term and has costs associated with regular visits to various health care professionals and lifestyle coaches. However, the WHO declared that: “supportive environments and communities are fundamental in shaping people’s choices, by making the choice of healthier foods and regular physical activity the easiest choice and therefore preventing overweight and obesity.” At the individual level, people at risk for obesity and T2D may limit energy intake from total fats and sugars, increase consumption of fruit and vegetables, as well as legumes, whole grains and nuts, and engage in regular physical activity (60 min a day for children and 150 min spread through the week for adults) (WHO 2016). A critical prerequisite for these individual opportunities seems to be the access to a healthy lifestyle provided at the societal level. An individual behavior change, which may prevent obesity and T2D, needs to be facilitated by sustained implementation of evidence-based and population-based policies that make regular physical activity and healthier dietary choices available, affordable, and easily accessible to everyone (WHO 2016). In addition, the food industry can play a significant role in promoting healthy diets by reducing the fat, sugar, and salt content of processed foods, ensuring that healthy and nutritious choices are available and affordable to all consumers, restricting marketing of foods high in sugars, salt, and fats, especially those foods aimed at children and teenagers and ensuring the availability of healthy food choices and supporting regular physical activity practice in the workplace (WHO 2016).

Management of Obesity

Modern treatment strategies of obesity need to be based on the diagnosis of the multifactorial and individually variable determinants of weight gain and the health benefits to be derived from weight loss. The basis for any weight loss intervention is lifestyle change, diet, and increased physical activity. The approach should be a high quality diet to which patients will adhere accompanied by an exercise prescription describing frequency, intensity, type, and time with a minimum of 150 min moderate weekly activity (Bray et al. 2016). For patients who do not achieve individual health benefit goals from weight loss, management of medications that are contributing to weight gain, and use of approved medications for chronic weight management along with lifestyle changes are appropriate. Medications approved in the USA and European Union are orlistat, naltrexone/bupropion, and liraglutide 3.0 mg (Bray et al. 2016). In addition, lorcaserin and phentermine/topiramate are approved weight management medications in the USA. Bariatric surgery including gastric banding, sleeve gastrectomy, Roux-en Y gastric bypass, and other procedures can produce remarkable health improvement and reduce mortality for patients with severe obesity (Bray et al. 2016). In principle, obesity treatment can be escalated when individual treatment goals are not achieved by a stepwise approach (Fig. 9).
Fig. 9

Stepwise escalating weight loss strategies in patients with obesity (and type 2 diabetes). The Endocrine Society Clinical Practice Guidelines recommend that diet, exercise, and behavioral modification be included in all overweight and obesity management approaches for BMI ≥25 kg/m2 and that other tools such as pharmacotherapy (BMI ≥27 kg/m2 with comorbidity or BMI over 30 kg/m2) and bariatric surgery (BMI ≥ 35 kg/m2 with comorbidity or BMI over 40 kg/m2) be used as adjuncts to behavioral modification to reduce food intake and increase physical activity when this is possible

Lifestyle and behavioral interventions aimed at reducing calorie intake and increasing energy expenditure have limited long-term success due to complex and persistent hormonal, metabolic, and neurochemical adaptations that defend against weight loss and promote weight regain. On the other hand, more effective surgical treatments are unavailable or unsuitable for the majority of individuals with obesity; therefore, effective and safe pharmacotherapies are urgently needed (Table 6).
Table 6

The Edmonton obesity staging system. (From Padwal et al. 2011)


No apparent risk factors (e.g., blood pressure, serum lipid and fasting glucose levels within normal range), physical symptoms, psychopathology, functional limitations and/or impairment of well-being related to obesity


Presence of obesity-related subclinical risk factors (e.g., borderline hypertension, impaired fasting glucose levels, elevated levels of liver enzymes), mild physical symptoms (e.g., dyspnea on moderate exertion, occasional aches and pains, fatigue), mild psychopathology, mild functional limitations, and/or mild impairment of well-being


Presence of established obesity-related chronic disease (e.g., hypertension, type 2 diabetes, sleep apnea, osteoarthritis), moderate limitations in activities of daily living and/or well-being


Established end-organ damage such as myocardial infarction, heart failure, stroke, significant psychopathology, significant functional limitations and/or impairment of well-being


Severe (potentially end-stage) disabilities from obesity-related chronic diseases, severe disabling psychopathology, severe functional limitations and/or severe impairment of well-being

The increase in the prevalence of obesity represents a challenging task for health care systems. Since the obesity associated risk to develop comorbid disorders and the individual response to weight reducing therapies are heterogeneous, a stratification of the severity of obesity should be assessed prior to the initiation of weight loss interventions (Sharma and Kushner 2009). Bariatric surgery is so far the only long-term effective evidence-based treatment strategy to significantly reduce body weight in patients with obesity. Also in the light of limited resources in health care systems, it will become important to identify those individuals with obesity who may benefit the most from an intervention aiming at body weight reduction. The Edmonton Obesity Staging System (EOSS) has been demonstrated to be a valuable diagnostic tool to stratify and prioritize patients for different treatment strategies including bariatric surgery (Table 7) (Padwal et al. 2011). The EOSS is a risk-stratification system that classifies individuals with obesity into 5 graded categories, based on their morbidity and health-risk profile. All patients can be provided weight-management advice; however, patients in the first 2 stages (EOSS stages 0 and 1) may not necessarily require weight loss, as they represent an obese phenotype with relatively minor health problems (Sharma and Kushner 2009). This is in contrast to the typical obese phenotype that is associated with several clinical metabolic, mental, and physiological aberrations (EOSS stages 2–4) (Sharma and Kushner 2009).
Table 7

Pharmacotherapy of obesity in the United States (2014). (Modified from Apovian et al. 2015)

Drug (generic)


Mechanism of action

Mean weight loss

(% or kg)


Common side effects


Phentermine resin

37.5 mg/d

Norepinephrine-releasing agent

3.6 kg

Approved in 1960s for short-term use (3 months)

Headache, elevated BP, elevated HR, insomnia, dry mouth, constipation, anxiety Cardiovascular: palpitation, tachycardia, elevated BP, ischemic events

Central nervous system: overstimulation, restlessness, dizziness, insomnia, euphoria, dysphoria, tremor, headache, psychosis Gastrointestinal: dryness of the mouth, unpleasant taste, diarrhea, constipation, other gastrointestinal disturbances Allergic: urticaria Endocrine: impotence, changes in libido

Anxiety disorders (agitated states), history of heart disease, uncontrolled hypertension, seizure, MAO inhibitors, pregnancy and breastfeeding, hyperthyroidism, glaucoma, history of drug abuse, sympathomimetic amines


75 mg/d

Norepinephrine-releasing agents

3.0 kg

FDA approved in 1960s for short-term use (3 months)

See phentermine resin

See phentermine resin


120 mg TID

Pancreatic and gastric lipase inhibitor

2.9–3.4 kg

FDA approved in 1999 for chronic weight management

Decreased absorption of fat-soluble vitamins, steatorrhrea, oily spotting, flatulence with discharge, fecal urgency, oily evacuation, increased defecation, fecal incontinence

Cyclosporine (taken 2 h before or after orlistat dose), chronic malabsorption syndrome, pregnancy and breastfeeding, cholestasis, levothyroxine, warfarin, antiepileptic drugs


10 mg BID

5HT2c receptor agonist

3.6 kg

FDA approved in 2012 for chronic weight management

Headache, nausea, dry mouth, dizziness, fatigue, constipation

Pregnancy and breastfeeding Use with caution: SSRI, SNRI/MAOI, St John’s wort, triptans, buproprion, dextromethorphan

Phentermine (P)/topiramate (T)

3.75 mg P/23 mg T ER QD (starting dose) 7.5 mg P/46 mg T ER daily (recommended dose) 15 mg P/92 mg P/T ER daily (high dose)

GABA receptor modulation (T) plus norepinephrinereleasing agent (P)

6.6 kg (recommended dose), 8.6 kg (high dose)

FDA approved in 2012 for chronic weight management

Insomnia, dry mouth, constipation, paraesthesia, dizziness, dysgeusia

Pregnancy and breastfeeding, hyperthyroidism, glaucoma, MAO inhibitor, sympathomimetic amines


32 mg/360 mg 2 tablets QID (high dose)

Reuptake inhibitor of dopamine and norepinephrine (bupropion) and opioid antagonist (naltrexone)


FDA approved in 2014 for chronic weight management

Nausea, constipation, headache, vomiting, dizziness

Uncontrolled hypertension, seizure disorders, anorexia nervosa or bulimia, drug or alcohol withdrawal, MAO inhibitors


3.0 mg injectable

GLP-1 agonist

5.8 kg

FDA approved in 2014 for chronic weight management

Nausea, vomiting, pancreatitis

Medullary thyroid cancer history, multiple endocrine neoplasia type 2 history

Noteworthy, studies including real-world observations are required to validate the EOSS in clinical practice and whether obesity treatment could be optimized using this systematic approach. In analyses of data from the National Health and Human Nutrition Examination Surveys (NHANES) III (1988–1994) and the NHANES 1999–2004, with mortality follow-up through to the end of 2006, it has been shown that EOSS independently predicted increased mortality even after adjustment for contemporary methods of classifying adiposity (Fig. 10) (Padwal et al. 2011). Before the initiation of individual weight management plans, assessment of the obesity-related risk using the EOSS may therefore help to prioritize treatment of patients at highest risk for obesity-related premature mortality (Padwal et al. 2011). To structure the treatment of a patient with obesity, several guidelines have been developed in different countries of the world (reviewed in Bray et al. 2016).
Fig. 10

The Edmonton Obesity Staging System predicts all-cause mortality among people with normal weight, overweight and obesity. NHANES = National Health and Human Nutrition Examination Surveys. (Reproduced and modified from Padwal et al. 2011)

Treatment of Obesity in Patients with Type 2 Diabetes

For patients with obesity related T2D, achieving a healthier body weight is a central component in the treatment strategy (Hauner 2010). In the LOOK AHEAD study, patients with T2D could achieve clinically significant weight loss with an average 8.6% weight loss in the intensive lifestyle intervention group after 1 year of treatment (LOOK AHEAD Research Group 2013). Weight loss was accompanied by substantial improvements of all weight-associated risk factors including improvements in HbA1c (from 7.3% (56 mmol/mol) at baseline to 6.2% (44 mmol/mol) after 1 year) (LOOK AHEAD Research Group 2013). In general, treatment of patients with obesity and T2D is usually considered to be more difficult than treating obese subjects without diabetes. This may apply as early as at prediabetes states. For example, in the SCALE obesity and prediabetes trial, reducing body weight by liraglutide 3.0 mg was more pronounced in those individuals with normal glucose metabolism compared to the prediabetes patients (Pi-Sunyer et al. 2015). There are several reasons for the less effective weight reducing programs in patients with T2D compared to those with obesity and normoglycemia. T2D patients are usually older than obese subjects without diabetes, which may mean a smaller weight loss as energy expenditure decreases with age (Hauner 2010). Another reason is that T2D patients may focus more on blood glucose control, which could result in neglecting other health problems (Hauner 2010). Finally, the effect of various antidiabetic agents to increase weight or prevent weight loss has to be considered (Hauner 2010).

Behavior Modifications

Obesity develops in genetically predisposed people because of chronically increased intake of energy-dense foods that are high in fat and carbohydrates in parallel with a low physical activity due to the modern sedentary nature of the work, facilitated modes of transportation, and increasing urbanization. These components characterize a “modern lifestyle” in many societies, and therefore interventions aiming at changing this lifestyle are considered as cornerstone of weight-reducing treatment. On the other hand, the term lifestyle intervention is misleading, because it would require an intervention at both the individual and societal level, which goes far beyond the medical perspective of an individualized obesity treatment. Therefore, here the term behavior modification will be used instead of “lifestyle intervention” as basis for any more specific obesity treatment. International guidelines for treatment of obesity recommend a multicomponent behavior intervention, which includes three major strategies: lifestyle or behavioral training, dietary approaches to reduce energy intake, and an increase in physical activity (Bray et al. 2016). Patients with obesity following the goal to reduce their body weight and maintain a healthier body weight should ideally follow the behavior intervention lifelong. However, the efficacy and adherence rates to multimodal behavior interventions are generally very low. Therefore, the effectiveness of treatments aiming at behavior changes is considered relatively low. On the other hand there is increasing evidence supporting the efficacy of lifestyle intervention or behavioral modification from large randomized and controlled trials. The Look AHEAD study (Look AHEAD Research Group et al. 2013) and the Diabetes Prevention Program (Knowler et al. 2009) are prominent examples to support the notion that behavior intervention could be successfully used – even in the long term – to reduce body weight and improve measures of obesity related disorders. In the LOOK AHEAD trial, number of attended face-to-face behavioral sessions, number of meal replacements, and accumulative weekly physical activity were predictors of weight after 1, 4, and 8 years (Look AHEAD Research Group et al. 2013). If these components could be delivered in at least 14 group or individual sessions over 6 months with treatment continuing to 1 year, the average reported weight loss would be 8 kg (Bray et al. 2016). Although the extent of weight may seem small, this weight loss was associated with clinically significant improvements in obesity-related traits including lowering of systolic and diastolic blood pressure, triglycerides, parameters of glycemic control, increasing HDL-cholesterol, and reduction in risk for progression to type 2 diabetes (Ryan and Heaner 2014, Bray et al. 2016).

Based on the results of the LOOK AHEAD trial and other supportive evidence, the US Preventive Services Task Force (LeFevre and U.S. Preventive Services Task Force 2014) has recommended that individuals with obesity and cardiovascular disease risk factors should be referred for lifestyle treatment, and the US Center for Medicare and Medicaid Services promote policies to reimburse providers for intensive behavioral therapy for the patient with obesity (Bray et al. 2016). In the UK, the National Institute for Health and Care Excellence recommends progressively intensive interventions on the basis of the degree of overweight and obesity and presence of comorbidities (Bray et al. 2016). Importantly, initial rates of weight loss predicted long-term weight loss in the LOOK AHEAD trial – an observation which could also be attributed to other weight loss interventions including dietary approaches (Greenberg et al. 2009; Shai et al. 2008) and pharmacotherapy (Pi-Sunyer et al. 2015). In the LOOK AHEAD trial, individuals losing less than 3% of their body weight at 2 months were 2.5% below the average baseline weight at 8 years, whereas those losing 3–6% of their body weight were about 4.5% below baseline at 8 years, and those losing more than 6% were ~7% below baseline on average at 8 years, suggesting that larger early weight losses are beneficial (Bray et al. 2016; Unick et al. 2015). There are many commercial programs that can provide tools to facilitate individual behavior changes and support weight loss (Gudzune et al. 2015). On average, commercial behavior change-based weight loss programs lead to a weight loss of ~3% in the first year – however, long-term adherence to such programs is generally poor (Gudzune et al. 2015). Despite several claims regarding the superiority of one program or another for inducing weight loss, a recent meta-analysis comparing 48 unique randomized trials (including 7286 individuals) found that significant weight loss was observed with any low-carbohydrate or low-fat diet (Johnston et al. 2014). These analyses support the practice of recommending any multimodal behavior program or diet that a patient will adhere to in order to lose weight (Johnston et al. 2014).

Diets for Weight Loss

Patients and health care professional are frequently facing the belief that there is a magic weight loss diet (Bray et al. 2016). This belief has stimulated many studies that have compared low-fat, low-carbohydrate or high-protein, low glycemic index, balanced deficit diets. However, meta-analyses of these studies demonstrated that reduced-calorie diets result in clinically meaningful weight loss regardless of which macronutrients or diet-composition they emphasize (Sacks et al. 2009).

On the other hand, dietary approaches for weight loss represent the most important nonpharmacological, nonsurgical treatment strategy for patients with obesity including patients with obesity and T2D. The basic principle of a weight reduction program includes a moderately hypocaloric diet, an increase in physical activity, and behavior modification (Hauner 2010). The gold standard in the dietary treatment of obese patients with or without T2D is a balanced moderately energy-restricted diet with an energy deficit of at least 500 kcal/day below energy requirements (Hauner 2010). Alternatively, patients may use a dietary plan that has 1200–1500 kcal/day for women or 1500–1800 kcal/day for men (increased by a further 300 kcal/day for each sex if weight exceeds 150 kg) (Bray et al. 2016).

In a large study of 811 participants with overweight and obesity, the effects of diets with 20% or 40% fat and 15% or 25% protein were compared and reported no difference in weight loss at 6 months or 2 years attributable to any specific diet composition (Sacks et al. 2009). Additional meta-analyses of low-carbohydrate versus low fat diets support the notion that low-carbohydrate diets are at least as effective as low-fat diets at reducing weight and improving metabolic risk factors (Hu et al. 2012). Following the results from these trials and meta-analyses, the best advice to patients aiming at weight loss to improve their health is to provide low energy diets that are likely to be adhered to by the patient and provide health benefits. In patients with nephropathy, however, protein intake remains a critical issue and should be limited in accordance with current recommendations (Hauner 2010).

From the DIRECT study, a 2-year trial, in which 322 moderately obese subjects have been randomly assigned to one of three diets – low-fat, restricted-calorie; Mediterranean, restricted-calorie; or low-carbohydrate, nonrestricted-calorie – it has been suggested that a Mediterranean style diet had favorable effects particularly with regard to adherence rates and practicability (Shai et al. 2008). Moreover, in a meta-analysis of nine studies with 1178 patients, Mediterranean style diets were associated with a significant decrease in body weight and BMI and reductions in HbA1c, fasting plasma glucose, fasting insulin reduce, and cardiovascular disease risk (Huo et al. 2014).

From a practical point of view, it is important to assess the habitual diet of patients with T2D and to focus counseling on changes of their eating habits in order to approach current dietary recommendations (Hauner 2010). All possible efforts for dietary changes should be made as simple as possible for patients as they may also be burdened by many requirements to manage their diabetes (Hauner 2010). For obese subjects with T2D, the frequent recommendation to distribute their restricted calorie intake over five to six meals is difficult to meet and may even hinder weight loss without being of any advantage for metabolic control (Hauner 2010). Therefore, in T2D patients without insulin treatment, three meals a day may be more appropriate and advantageous to reach the individual dietary and weight goals.

It is still debated whether low-glycemic index or low glycemic load diets are superior in the dietary treatment of patients with T2D (Bray et al. 2016). Study data comparing such strategies are inconclusive (Bray et al. 2016).

In the model of a step-wise escalating weight loss therapy (Fig. 10), the use of a very low calorie diet (VLCD) could be recommended for initial (short term) weight loss.

VLCDs or very low-energy diets are defined as having 200 and 800 kcal/day and provide a lower energy intake that might result in more rapid loss of body fat and weight (Bray et al. 2016). It could be shown that VLCDs can rapidly normalize blood glucose and other risk factors in people with type 2 diabetes. Therefore, this option may be particularly valuable for patients with poor metabolic control (Hauner 2010). Dietary restriction in the context of short periods of VLCD leads to a rapid improvement of insulin sensitivity and glycemic control. VLCDs can only be applied for a limited period of time and require intensive medical surveillance. The long-term results of VLCD are moderately better than those of conventional diets, although there is considerable weight regain after VLCD short-term interventions (Anderson et al. 2001). Therefore, there is need for new sophisticated solutions such as intermittent VLCD in combination with conventional hypocaloric diets to obtain better long-term results (Hauner 2010). In an analysis of commercial programs, it could be demonstrated that medically monitored VLCDs programs (e.g., Health Management Resources, Medifast, OPTIFAST) resulted in at least 4.0% greater short-term weight loss than counseling (Gudzune et al. 2015).

Increasing Physical Activity

Increased physical activity is an essential and integral component of behavior modification programs (Bray et al. 2016). Different guidelines recommend typically a gradually increasing aerobic physical activity (e.g., walking, cycling) to reach a goal of more than 150 min/week (equal to >30 min/day, for at least 5 days each week) (Jakicic et al. 2013; National Clinical Guideline Centre (UK); Bray et al. 2016). Increased physical activity may not be effective in weight loss without a parallel diet intervention. However, weight maintenance after losing weight as well as significant benefits for general health and even reduced mortality (Paffenbarger et al. 1986) that are independent of weight loss could be achieved by increased physical activity (Wu et al. 2009). Importantly, low cardiorespiratory fitness is a strong and independent predictor of cardiovascular disease (CVD)-related and all-cause mortality and of comparable importance with that of diabetes mellitus and other CVD risk factors in patients with obesity (Wei et al. 1999). There is evidence that a greater amount physical activity (30–45 min/day) is needed to prevent obesity and that for long-term weight maintenance in those who have lost weight, 60–90 min/day is required, but this is likely to require close supervision as part of an intensive program, which might not be practical or sustainable in many clinical settings (Bray et al. 2016). As an example from the LOOK AHEAD trial, although physical activity is effective in the short term, the activities and their benefits are not always sustained (Look AHEAD Research Group et al. 2013). The type of physical activity including strength versus endurance, aerobic versus resistance, or high intensity versus low intensity training does not seem to be related to overall weight loss (Bray et al. 2016). With regard to practicability, more intensive exercise programs may produce similar weight loss with a reduced time commitment and could therefore be preferred by patients with obesity. In general and in analogy to behavior programs and diet approaches, long-term adherence to increased physical activity is the most important goal.

Antidiabetic Medications and Body Weight

It has long been recognized that some glucose lowering medications can promote weight gain in patients with T2D. The strongest weight-promoting effect is exerted by insulin. In the Diabetes Control and Complications Trial (DCCT), intensified insulin treatment was associated with substantial weight gain that resulted in unfavorable changes of lipid levels and blood pressure similar to those seen in the insulin resistance syndrome (Purnell et al. 1998). In the UK Prospective Diabetes Study (UKPDS), insulin treatment caused a mean weight gain of approximately 7 kg over 12 years of treatment in newly diagnosed subjects with T2DM (UKPDS study group 1998). In addition, sulfonylureas and glinides are known to promote weight gain because of their action to promote insulin secretion. In the UKPDS, the average weight gain under glibenclamide treatment amounted to about 5 kg (UKPDS study group 1998).

Glitazones lead to substantial weight gain of 4–5 kg on average, mainly in subcutaneous depots and by enhanced fluid retention (Hauner 2010). In contrast, metformin and α-glucosidase inhibitors have a modest weight lowering potential (Hauner 2010). DPP-4 inhibitors (e.g., alogliptin, sitagliptin, linagliptin, saxagliptin, vildagliptin) have been shown to be weight neutral, whereas the administration of sodium glucose cotransporter-2 (SGLT-2) inhibitors (e.g., canagliflozin, dapagliflozin, empagliflozin) and GLP-1 receptor agonists (e.g., exenatide, liraglutide, dulaglutide, lixisenatide) results in a substantial weight loss, and liraglutide in a dose of 3.0 mg daily is an approved weight management pharmacotherapy in the US, Canada and Europe (Drucker and Nauck 2006).

Pharmacotherapy of Obesity

In the stepwise escalating weight loss treatment algorithm (Fig. 10), the adjunct administration of weight lowering drugs represents another component in the treatment of obesity (Hauner 2010). As the efficacy of currently approved drugs is limited, drug treatment is only recommended if the nonpharmacologic treatment program is not sufficiently successful and if the benefit to risk ratio justifies drug administration (National Task Force on the Prevention and Treatment of Obesity 1996). This means if patients do not achieve individual health benefit goals (typically <5% weight loss), the use of approved weight loss medications for chronic weight management along with lifestyle changes is appropriate (Bray et al. 2016). There are differences in the approval status of different medications for weight loss in different countries and regions of the world (Table 5). In the USA and the European Union, orlistat, naltrexone/bupropion, and liraglutide 3.0 mg are approved (Bray et al. 2016). Only in the USA, lorcaserin and phentermine/topiramate are approved for weight management. Most of the approved drugs are working centrally where stimulation of the POMC/CART pathway has anorexigenic effects, whereas the NPY/AGRP pathway exerts orexigenic effects. The interaction with the several receptors present in neurones of the hypothalamus determines the balance between orexigenic and anorexigenic effects (Schwartz et al. 2000).

Independently of the approved weight loss drugs, patients with obesity (and T2D) should be guided with regard to avoid wherever possible medications for other indications, which may induce weight gain interfere with weight loss goals. A clinical guidance statement from the Endocrine Society promotes the concept that for patients with obesity, medicating for chronic diseases should be with a weight centric focus (Bray et al. 2016). Many medications in use for common chronic diseases produce weight gain, and others are associated with weight loss, albeit those medications do not have an obesity indication (summarized in Bray et al. 2016).

The indications for adding pharmacotherapy to a basic multimodal weight loss program are a failure to achieve clinically meaningful weight loss (>5% of total body weight) and to sustain lost weight, for patients who meet regulatory prescribing guidelines (BMI ≥27 kg/m2 with one or more comorbidities or a BMI >30 kg/m2 with or without associated cardiometabolic disorders). When prescribing the approved five medications in the USA and three in the EU (Table 5), some guiding principles need to be followed. Most importantly, in parallel with the weight loss medication, an effective behavior support for weight loss should be provided. Medications work to reinforce the patient’s attempts to change eating behaviors and produce an energy deficit. In addition, the potential pharmacotherapy related risks and side effects should be known and explained in detail to the patient to make informed choices. If clinically meaningful weight loss cannot be achieved with the pharmacotherapy within the first three months, medications should be discontinued and a new treatment plan needs to be implemented (Bray et al. 2016). Meaningful weight could be defined as loss of more than 5% of body weight in patients without diabetes or loss of >3% of body weight in patients with obesity and T2D (Bray et al. 2016). Noteworthy, the responder rate to any antiobesity pharmacotherapy is not 100%, but patients who may not respond to one medication could achieve relevant weight loss with another medication.

Before the approval of a weight loss medication by the medical regulatory agencies in the USA and EU, data for more than 2500 patients have to be provided and weight loss needs to be approximate to or exceed 5% greater weight loss than lifestyle intervention (placebo). In addition, positive effects on various risk factors and disease markers need to be shown (Bray et al. 2016). All drugs must show evidence of no increase in cardiovascular risk, which is likely to require a cardiovascular outcome trial either before or after marketing. Furthermore, all of the drugs (Table 5) were studied with a suicidality rating scale. These medications have an indication for chronic weight management, indicating long-term usage, along with diet and physical activity in individuals with BMI of 30 kg/m2 or greater or a BMI 27 kg/m2 or greater with one or more comorbidities. They are to be used in the long term not only to produce weight loss but also to sustain weight loss.

Orlistat is a gastric and pancreatic lipase inhibitor that impairs the intestinal absorption of 30% of ingested fat when eating a 30% fat diet. It is available in most countries worldwide and belongs to the safest drugs in this category. Therefore, orlistat has been approved for use in adolescents (Bray et al. 2016). In a recent systematic review of clinical studies over at least 12 weeks in obese subjects with T2DM, orlistat treatment produced a greater weight loss than placebo treatment by 2.0 kg on average, associated with a small improvement in HbA1c compared with controls (Norris et al. 2005). Furthermore, orlistat moderately decreases low density lipoprotein (LDL) cholesterol concentrations. The XENDOS study could demonstrate over four years orlistat’s safety and efficacy as well as that it reduces the development of T2D in a high risk population of individuals with prediabetes (Torgerson et al. 2004). However, the drug’s gastrointestinal side effects limit its popularity with patients (Bray et al. 2016).

Phentermine is a sympathomimetic drug with cardiostimulatory properties. It has only been studied in short-term trials and is a controlled substance in the United States (Bray et al. 2016). It has misuse potential (albeit small) and small risk of primary pulmonary hypertension (Bray et al. 2016).

Lorcaserin is a specific serotonin 2c receptor agonist with a favorable tolerability and low rate of adverse events profile (Smith et al. 2010). Lorcaserin should not be used with monoamine oxidase inhibitors because of the risk of serotonin syndrome (Bray et al. 2016).

The combination of phentermine and topiramate as an extended release (ER) formulation uses lower doses of both drugs (7.5 mg of phentermine and 46 mg of topiramate at the recommended dose) than are usually prescribed when either drug is used as alone for other indications (Gadde et al. 2011). Topiramate is associated with fetal toxic effects (oral clefts); therefore, a pregnancy test before initiation of therapy, and monthly thereafter, is recommended. The most common side effects include paraesthesias, dizziness, dysgeusia, insomnia, constipation, and dry mouth (Bray et al. 2016). A rare side effect of topiramate is acute myopia with glaucoma and the drug is contraindicated in glaucoma. The combination of phentermine and topiramate is also contraindicated in hyperthyroidism and within 14 days of treatment with monoamine oxidase inhibitors. Other rare potential adverse risks include kidney stones (associated with topiramate) and increased heart rate (associated with phentermine) in patients susceptible to sympathomimetic drugs (Bray et al. 2016).

The combination of naltrexone/bupropion has been approved in the USA in 2012 and in the EU in 2015. Bupropion is a mild reuptake inhibitor of dopamine and norepinephrine. Naltrexone, an opioid antagonist has minimum effect on weight loss on its own, but it is likely to block the inhibitory effects of opioid receptors activated by the β-endorphin released in the hypothalamus that stimulates feeding (Bray et al. 2016). The latter mechanism may support the inhibitory effects of α-melanocyte stimulating hormone to reduce food intake. Regarding side effects, naltrexone/bupropion can increase blood pressure, and therefore the combination should only be prescribed to patients with controlled hypertension and the patient’s blood pressure should be monitored after initiation of the treatment (Bray et al. 2016). Tolerability issues, especially nausea, on initiating the drug require a dose escalation over four weeks. All antidepressants in the USA are required to carry a black box warning of suicidality, and the combination’s label includes this despite the fact that there was no signal for suicidality in phase 3 studies of naltrexone/bupropion (Bray et al. 2016).

Liraglutide is an injectable GLP-1 agonist which has been used for the management of diabetes at doses of up to 1.8 mg (Pi-Sunyer et al. 2015). For chronic weight management, it is approved in the USA and EU at a dose of 3.0 mg. Nausea has been one of the most prominent side effects; thus, a slow dose escalation over 5 weeks is recommended. In clinical trials, a small, but significant increase in heart rate has been observed, whereas blood pressure tends to fall (Bray et al. 2016). Liraglutide should not be prescribed in patients with family or personal history of medullary thyroid cancer or multiple endocrine neoplasia. Other rare side effects include acute pancreatitis, gall bladder disease, and hypoglycemia in patients with T2D particularly if they are co-treated with medication who cause hypoglycemia (insulin, sulfonureas).

Bariatric and Metabolic Surgery

As the most invasive option to treat obesity (Fig. 10), bariatric surgery has become an established method to reduce body weight in patients with extreme obesity (>40 kg/m2) (Hauner 2010). In addition, there is growing consensus that this method can also be applied in patients with T2D at a BMI ≥35 kg/m2. In patients fulfilling these criteria, bariatric surgery is the most effective treatment with excellent long-term results compared to all other methods (Hauner et al. 2010). Several bariatric surgery procedures including gastric banding, sleeve gastrectomy, Roux-en-Y gastric bypass, biliopancreatic diversion, and others are now well established and result in varying degrees of weight loss ranging from ~11.4% (gastric banding) to ~21.9% (Roux-e-Y gastric bypass) weight loss (Bray et al. 2016). Each surgical procedure has its own risks and benefits which need to be considered carefully with each patient.

In the Swedish Obese Subjects (SOS) study, a large prospective trial comparing bariatric surgery with conventional (dietary) obesity treatment, sustained (>15 years) weight loss of more than 20 kg was achieved in the surgically treated subjects (Sjöström et al. 2007). In the context, the SOS study bariatric surgery reduced the incidence of T2D and significantly reduced total mortality by ~24% mainly due to reduced cardiovascular mortality and cancer mortality in women (Sjöström et al. 2012). In a metaanalysis of bariatric surgery studies among patients with obesity and T2D, a 78% complete remission of diabetes has been shown at least in the short term (Buchwald et al. 2009). Fifteen years data from the SOS study demonstrate that the diabetes remission rates decreased to 30.4% for bariatric surgery patients (controls: 6.5%). Compared to medical treatment alone, bariatric surgery has been shown to be more effective in improving hyperglycemia, hypertension, and dyslipidemia in randomized clinical trials among patients with obesity and type 2 diabetes (Bray et al. 2016). On the other hand, surgery has the risk for acute perioperative complications, long-term micronutrient deficiencies, and psychological problems. Weighing these risks against the benefits of significant weight loss and improved glycemic control, bariatric surgery seems to be a promising treatment option for obesity-associated T2D (Table 8).
Table 8

Comparisons between medical and surgical treatment of type 2 diabetes in patients with obesity. Selected studies with a duration between 1 and 3 years in which medical and surgical treatment were directly compared. For studies including different surgical procedures, only data for Roux-en-Y-gastric bypass (RYGB) surgery were included *, significant differences (p<0.05) between medical and surgical treatment. (Modified from Tham et al. 2014)

Clinical trial

Schauer et al. 2012

Mingrone et al. 2012

Schauer et al. 2014


1 year

2 years

3 years



Surgery (RYMB)


Surgery (RYMB)


Surgery (RYMB)



Body weight (kg)

−5.4 ± 8.0

−29.4 ± 8.9*

−4.7 ± 6.4

−33.3 ± 7.9*

−4.3 ± 8.8

−26.2 ± 10.6*

HbA1c (%)





−0.6 ± 2.5

−2.5 ± 1.9*

Diabetes medications







Despite growing evidence that bariatric/metabolic surgery powerfully improves T2D, existing diabetes treatment algorithms do not include surgical options (Rubino et al. 2016). To overcome the neglection of data from bariatric surgery trials, an international consensus conference (2nd Diabetes Surgery Summit) developed global guidelines to inform clinicians and policymakers about benefits and limitations of metabolic surgery for T2D. Although additional studies are needed to further demonstrate long-term benefits, there is sufficient clinical and mechanistic evidence to support inclusion of metabolic surgery among antidiabetes interventions for people with T2D and obesity (Rubino et al. 2016).

Numerous randomized clinical trials (Table 6), albeit mostly short/midterm, demonstrate that metabolic surgery achieves very good glycemic control and reduces cardiovascular risk factors. On the basis of such evidence, metabolic surgery should be recommended to treat T2D in patients with BMI ≥40 kg/m2 and in those with BMI 35.0–39.9 kg/m2 when hyperglycemia is inadequately controlled by lifestyle and optimal medical therapy (Fig. 11). According to the Joint Statement by International Diabetes Organizations (Rubino et al. 2016), surgery may also be considered for patients with T2D and BMI 30.0–34.9 kg/m2 if hyperglycemia is inadequately controlled despite optimal treatment with either oral or injectable medications (Fig. 11).
Fig. 11

Metabolic Surgery in the treatment of patients with type 2 diabetes. Algorithm as recommended by the 2nd Diabetes Surgery Summit voting delegates (Modified from Rubino et al. 2016). Patient selection for metabolic surgery should be based on balancing surgical and other long-term risks with potential long-term benefits to individual patients

These encouraging data from randomized clinical trials comparing bariatric/metabolic surgery with the best medical treatment of T2D patients (Schauer et al. 2012; Mingrone et al. 2012; Schauer et al. 2014) need to be put into the context of potential risks and side effects of surgery, which for some patients can be distressing or disabling. Although mortality is low for modern laparoscopic surgery (~0.1–0.3% perioperative mortality), re-operation rates for surgical complications are high, particularly for gastric banding (Chang et al. 2014).

Patients require a lifelong replacement therapy and monitoring is required for nutritional vitamin and mineral deficiencies, particularly after malabsorptive surgery (Bray et al. 2016).

In addition to the acute surgery associated risks (Birkmeyer et al. 2013), long-term risks including osteoporosis, malnutrition, vitamin deficiencies, dumping syndrome, gastro-esophageal reflux, and hypoglycemia can be distressing and a challenging to treat (Tack and Deloose 2014). Weight regain can also be a substantial issue, and revisional surgery carries greater risks and no guarantee of success (Bray et al. 2016). From a clinical perspective, patients and clinicians considering referral for bariatric surgery should be made fully aware of the risks and benefits, good practice might include provision of a detailed education session, attendance at patient support groups, and detailed lifestyle advice and psychological support both before and after surgery (Bray et al. 2016).


Obesity increases the risk to develop T2D, and in recent years several potential mechanistic links have been elucidated. Not only excess body fat, but also adverse (ectopic) fat distribution and dysfunction of adipose tissue promote through the release of metabolites, adipokines, and cytokines impaired insulin sensitivity and deteriorate insulin secretion. Body weight management is the central component in the treatment of patients with obesity and T2D, because weight loss has been shown to provide a marked improvement in metabolic control and may reduce the obesity-associated risk for T2D, but also several other diseases. Weight management includes an escalating approach which consists of behavioral treatment with the aim to reduce hypercaloric nutrition and to increase physical activity as basic strategy, pharmacotherapy, and bariatric surgery. Recently, bariatric surgery has been shown to be effective in the treatment of patients with T2D.


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Authors and Affiliations

  1. 1.Department of MedicineUniversity of LeipzigLeipzigGermany

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