Metabolic syndrome

Last updated
Metabolic syndrome
Other namesDysmetabolic syndrome X
Obesity6.JPG
A man with marked central obesity, a hallmark of metabolic syndrome. His weight is 182 kg (400 lbs), height 185 cm (6 ft 1 in), and body mass index (BMI) 53 (normal 18.5 to 25).
Specialty Endocrinology
Symptoms Obesity
Differential diagnosis Insulin resistance, prediabetes, hyperuricemia, obesity, nonalcoholic fatty liver disease, polycystic ovarian syndrome, erectile dysfunction, acanthosis nigricans

Metabolic syndrome is a clustering of at least three of the following five medical conditions: abdominal obesity, high blood pressure, high blood sugar, high serum triglycerides, and low serum high-density lipoprotein (HDL).

Contents

Metabolic syndrome is associated with the risk of developing cardiovascular disease and type 2 diabetes. [1] In the U.S., about 25% of the adult population has metabolic syndrome, a proportion increasing with age, particularly among racial and ethnic minorities. [2] [3]

Insulin resistance, metabolic syndrome, and prediabetes are closely related to one another and have overlapping aspects. The syndrome is thought to be caused by an underlying disorder of energy utilization and storage, but the cause of the syndrome is an area of ongoing medical research. Researchers debate whether a diagnosis of metabolic syndrome implies differential treatment or increases risk of cardiovascular disease beyond what is suggested by the sum of its individual components. [4]

Signs and symptoms

The key sign of metabolic syndrome is central obesity, also known as visceral, male-pattern or apple-shaped adiposity. It is characterized by adipose tissue accumulation predominantly around the waist and trunk. [5] Other signs of metabolic syndrome include high blood pressure, decreased fasting serum HDL cholesterol, elevated fasting serum triglyceride level, impaired fasting glucose, insulin resistance, or prediabetes. Associated conditions include hyperuricemia; fatty liver (especially in concurrent obesity) progressing to nonalcoholic fatty liver disease; polycystic ovarian syndrome in women and erectile dysfunction in men; and acanthosis nigricans. [6]

Neck circumference

Neck circumference has been used as a surrogate simple and reliable index to indicate upper-body subcutaneous fat accumulation. Neck circumference of more than 40.25 cm (15.85 in) for men and more than 35.75 cm (14.07 in) for women are considered high-risk for metabolic syndrome. Persons with large neck circumferences have a more-than-double risk of metabolic syndrome. [7] In adults with overweight/obesity, clinically significant weight loss may protect against COVID-19 [8] and neck circumference has been associated with the risk of being mechanically ventilated in COVID-19 patients, with a 26% increased risk for each centimeter increase in neck circumference. [9] Moreover, hospitalized COVID-19 patients with a "large neck phenotype" on admission had a more than double risk of death. [10]

Complications

Metabolic syndrome can lead to several serious and chronic complications, including type-2 diabetes, cardiovascular diseases, stroke, kidney disease and nonalcoholic fatty liver disease. [11]

Furthermore, metabolic syndrome is associated with a significantly increased risk of surgical complications across most types of surgery in a 2023 systematic review and meta-analysis of over 13 million individuals. [12]

Causes

The mechanisms of the complex pathways of metabolic syndrome are under investigation. The pathophysiology is very complex and has been only partially elucidated. Most people affected by the condition are older, obese, sedentary, and have a degree of insulin resistance. Stress can also be a contributing factor. The most important risk factors are diet (particularly sugar-sweetened beverage consumption), [13] genetics, [14] [15] [16] [17] aging, sedentary behavior [18] or low physical activity, [19] [20] disrupted chronobiology/sleep, [21] mood disorders/psychotropic medication use, [22] [23] and excessive alcohol use. [24] The pathogenic role played in the syndrome by the excessive expansion of adipose tissue occurring under sustained overeating, and its resulting lipotoxicity was reviewed by Vidal-Puig. [25]

Recent studies have highlighted the global prevalence of metabolic syndrome, driven by the rise in obesity and type 2 diabetes. The World Health Organization (WHO) and other major health organizations define metabolic syndrome with criteria that include central obesity, insulin resistance, hypertension, and dyslipidemia. As of 2015, metabolic syndrome affects approximately 25% of the global population, with rates significantly higher in urban areas due to increased consumption of high-calorie, low-nutrient diets and decreased physical activity. This condition is associated with a threefold increase in the risk of type 2 diabetes and cardiovascular disease, accounting for a substantial burden of non-communicable diseases globally (Saklayen, 2018). [26]

There is debate regarding whether obesity or insulin resistance is the cause of the metabolic syndrome or if they are consequences of a more far-reaching metabolic derangement. Markers of systemic inflammation, including C-reactive protein, are often increased, as are fibrinogen, interleukin 6, tumor necrosis factor-alpha  (TNF-α), and others. Some have pointed to a variety of causes, including increased uric acid levels caused by dietary fructose. [27] [28] [29]

Research shows that Western diet habits are a factor in the development of metabolic syndrome, with high consumption of food that is not biochemically suited to humans. [30] [ page needed ] Weight gain is associated with metabolic syndrome. Rather than total adiposity, the core clinical component of the syndrome is visceral and/or ectopic fat (i.e., fat in organs not designed for fat storage) whereas the principal metabolic abnormality is insulin resistance. [31] The continuous provision of energy via dietary carbohydrate, lipid, and protein fuels, unmatched by physical activity/energy demand, creates a backlog of the products of mitochondrial oxidation, a process associated with progressive mitochondrial dysfunction and insulin resistance.[ citation needed ]

Stress

Recent research indicates prolonged chronic stress can contribute to metabolic syndrome by disrupting the hormonal balance of the hypothalamic-pituitary-adrenal axis (HPA-axis). [32] A dysfunctional HPA-axis causes high cortisol levels to circulate, which results in raising glucose and insulin levels, which in turn cause insulin-mediated effects on adipose tissue, ultimately promoting visceral adiposity, insulin resistance, dyslipidemia and hypertension, with direct effects on the bone, causing "low turnover" osteoporosis. [33] HPA-axis dysfunction may explain the reported risk indication of abdominal obesity to cardiovascular disease (CVD), type 2 diabetes and stroke. [34] Psychosocial stress is also linked to heart disease. [35]

Obesity

Central obesity is a key feature of the syndrome, as both a sign and a cause, in that the increasing adiposity often reflected in high waist circumference may both result from and contribute to insulin resistance. However, despite the importance of obesity, affected people who are of normal weight may also be insulin-resistant and have the syndrome. [36]

Sedentary lifestyle

Physical inactivity is a predictor of CVD events and related mortality. Many components of metabolic syndrome are associated with a sedentary lifestyle, including increased adipose tissue (predominantly central); reduced HDL cholesterol; and a trend toward increased triglycerides, blood pressure, and glucose in the genetically susceptible. Compared with individuals who watched television or videos or used their computers for less than one hour daily, those who carried out these behaviors for greater than four hours daily have a twofold increased risk of metabolic syndrome. [36]

Aging

Metabolic syndrome affects 60% of the U.S. population older than age 50. With respect to that demographic, the percentage of women having the syndrome is higher than that of men. The age dependency of the syndrome's prevalence is seen in most populations around the world. [36]

Diabetes mellitus type 2

The metabolic syndrome quintuples the risk of type 2 diabetes mellitus. Type 2 diabetes is considered a complication of metabolic syndrome. [1] In people with impaired glucose tolerance or impaired fasting glucose, presence of metabolic syndrome doubles the risk of developing type 2 diabetes. [37] It is likely that prediabetes and metabolic syndrome denote the same disorder, defining it by the different sets of biological markers.[ citation needed ]

The presence of metabolic syndrome is associated with a higher prevalence of CVD than found in people with type 2 diabetes or impaired glucose tolerance without the syndrome. [36] Hypoadiponectinemia has been shown to increase insulin resistance [38] and is considered to be a risk factor for developing metabolic syndrome. [39]

Coronary heart disease

The approximate prevalence of the metabolic syndrome in people with coronary artery disease (CAD) is 50%, with a prevalence of 37% in people with premature coronary artery disease (age 45), particularly in women. With appropriate cardiac rehabilitation and changes in lifestyle (e.g., nutrition, physical activity, weight reduction, and, in some cases, drugs), the prevalence of the syndrome can be reduced. [36]

Lipodystrophy

Lipodystrophic disorders in general are associated with metabolic syndrome. Both genetic (e.g., Berardinelli-Seip congenital lipodystrophy, Dunnigan familial partial lipodystrophy) and acquired (e.g., HIV-related lipodystrophy in people treated with highly active antiretroviral therapy) forms of lipodystrophy may give rise to severe insulin resistance and many of metabolic syndrome's components. [36]

Rheumatic diseases

There is research that associates comorbidity with rheumatic diseases. Both psoriasis and psoriatic arthritis have been found to be associated with metabolic syndrome. [40]

Chronic obstructive pulmonary disease

Metabolic syndrome is seen to be a comorbidity in up to 50 percent of those with chronic obstructive pulmonary disease (COPD). It may pre-exist or may be a consequence of the lung pathology of COPD. [41]

Pathophysiology

It is common for there to be a development of visceral fat, after which the adipocytes (fat cells) of the visceral fat increase plasma levels of TNF-α and alter levels of other substances (e.g., adiponectin, resistin, and PAI-1). TNF-α has been shown to cause the production of inflammatory cytokines and also possibly trigger cell signaling by interaction with a TNF-α receptor that may lead to insulin resistance. [42] An experiment with rats fed a diet with 33% sucrose has been proposed as a model for the development of metabolic syndrome. The sucrose first elevated blood levels of triglycerides, which induced visceral fat and ultimately resulted in insulin resistance. The progression from visceral fat to increased TNF-α to insulin resistance has some parallels to human development of metabolic syndrome. The increase in adipose tissue also increases the number of immune cells, which play a role in inflammation. Chronic inflammation contributes to an increased risk of hypertension, atherosclerosis and diabetes. [43]

The involvement of the endocannabinoid system in the development of metabolic syndrome is indisputable. [44] [45] [46] Endocannabinoid overproduction may induce reward system dysfunction [45] and cause executive dysfunctions (e.g., impaired delay discounting), in turn perpetuating unhealthy behaviors.[ medical citation needed ] The brain is crucial in development of metabolic syndrome, modulating peripheral carbohydrate and lipid metabolism. [44] [45]

Metabolic syndrome can be induced by overfeeding with sucrose or fructose, particularly concomitantly with high-fat diet. [47] The resulting oversupply of omega-6 fatty acids, particularly arachidonic acid (AA), is an important factor in the pathogenesis of metabolic syndrome.[ medical citation needed ] Arachidonic acid (with its precursor – linoleic acid) serves as a substrate to the production of inflammatory mediators known as eicosanoids, whereas the arachidonic acid-containing compound diacylglycerol (DAG) is a precursor to the endocannabinoid 2-arachidonoylglycerol (2-AG) while fatty acid amide hydrolase (FAAH) mediates the metabolism of anandamide into arachidonic acid. [48] [46] Anandamide can also be produced from N-acylphosphatidylethanolamine via several pathways. [46] Anandamide and 2-AG can also be hydrolized into arachidonic acid, potentially leading to increased eicosanoid synthesis. [46]

Diagnosis

NCEP

As of 2023, the U.S. National Cholesterol Education Program Adult Treatment Panel III (2001) continues to be the most widely-used clinical definition. [4] It requires at least three of the following: [49]

2009 Interim Joint Statement

The International Diabetes Federation Task Force on Epidemiology and Prevention; the National Heart, Lung, and Blood Institute; the American Heart Association; the World Heart Federation; the International Atherosclerosis Society; and the International Association for the Study of Obesity published an interim joint statement to harmonize the definition of the metabolic syndrome in 2009. [50] According to this statement, the criteria for clinical diagnosis of the metabolic syndrome are three or more of the following:

This definition recognizes that the risk associated with a particular waist measurement will differ in different populations. However, for international comparisons and to facilitate the etiology, the organizations agree that it is critical that a commonly agreed-upon set of criteria be used worldwide, with agreed-upon cut points for different ethnic groups and sexes. There are many people in the world of mixed ethnicity, and in those cases, pragmatic decisions will have to be made. Therefore, an international criterion of overweight may be more appropriate than ethnic specific criteria of abdominal obesity for an anthropometric component of this syndrome which results from an excess lipid storage in adipose tissue, skeletal muscle and liver. [50]

The report notes that previous definitions of the metabolic syndrome by the International Diabetes Federation [51] (IDF) and the revised National Cholesterol Education Program (NCEP) are very similar, and they identify individuals with a given set of symptoms as having metabolic syndrome. There are two differences, however: the IDF definition states that if body mass index (BMI) is greater than 30 kg/m2, central obesity can be assumed, and waist circumference does not need to be measured. However, this potentially excludes any subject without increased waist circumference if BMI is less than 30. Conversely, the NCEP definition indicates that metabolic syndrome can be diagnosed based on other criteria. Also, the IDF uses geography-specific cut points for waist circumference, while NCEP uses only one set of cut points for waist circumference regardless of geography.[ citation needed ]

WHO

The World Health Organization (1999) [52] requires the presence of any one of diabetes mellitus, impaired glucose tolerance, impaired fasting glucose or insulin resistance, AND two of the following:

EGIR

The European Group for the Study of Insulin Resistance (1999) requires that subjects have insulin resistance (defined for purposes of clinical practivality as the top 25% of the fasting insulin values among nondiabetic individuals) AND two or more of the following: [53]

Cardiometabolic index

The Cardiometabolic index (CMI) is a tool used to calculate risk of type 2 diabetes, non-alcoholic fatty liver disease, [54] and metabolic issues. It is based on calculations from waist-to-height ratio and triglycerides-to-HDL cholesterol ratio. [55]

CMI can also be used for finding connections between cardiovascular disease and erectile dysfunction. [56] When following an anti inflammatory diet (low-glycemic carbohydrates, fruits, vegetables, fish, less red meat and processed foods) the markers may drop resulting in a significant reduction in body weight and adipose tissue. [57]

Other

High-sensitivity C-reactive protein has been developed and used as a marker to predict coronary vascular diseases in metabolic syndrome, and it was recently used as a predictor for nonalcoholic fatty liver disease (steatohepatitis) in correlation with serum markers that indicated lipid and glucose metabolism. [58] Fatty liver disease and steatohepatitis can be considered manifestations of metabolic syndrome, indicative of abnormal energy storage as fat in ectopic distribution. Reproductive disorders (such as polycystic ovary syndrome in women of reproductive age), and erectile dysfunction or decreased total testosterone (low testosterone-binding globulin) in men can be attributed to metabolic syndrome. [59]

Prevention

Various strategies have been proposed to prevent the development of metabolic syndrome. These include increased physical activity (such as walking 30 minutes every day), [60] and a healthy, reduced calorie diet. [61] Many studies support the value of a healthy lifestyle as above. However, one study stated these potentially beneficial measures are effective in only a minority of people, primarily because of a lack of compliance with lifestyle and diet changes. [19] The International Obesity Taskforce states that interventions on a sociopolitical level are required to reduce development of the metabolic syndrome in populations. [62]

The Caerphilly Heart Disease Study followed 2,375 male subjects over 20 years and suggested the daily intake of an Imperial pint (~568 mL) of milk or equivalent dairy products more than halved the risk of metabolic syndrome. [63] Some subsequent studies support the authors' findings, while others dispute them. [64] A systematic review of four randomized controlled trials said that, in the short term, a paleolithic nutritional pattern improved three of five measurable components of the metabolic syndrome in participants with at least one of the components. [65]

Management

Diet

Dietary carbohydrate restriction reduces blood glucose levels, contributes to weight loss, and reduces the use of several medications that may be prescribed for metabolic syndrome. [66] Studies suggest that meal timing and frequency can significantly impact the risk of developing metabolic syndrome. Research indicates that individuals who maintain regular meal timings and avoid eating late at night have a reduced risk of developing this condition (Alkhulaifi & Darkoh, 2022). [67]

Medications

Generally, the individual disorders that compose the metabolic syndrome are treated separately. [68] Diuretics and ACE inhibitors may be used to treat hypertension. Various cholesterol medications may be useful if LDL cholesterol, triglycerides, and/or HDL cholesterol is abnormal.[ citation needed ]

Epidemiology

Approximately 20–25 percent of the world's adult population has the cluster of risk factors that is metabolic syndrome. [51] In 2000, approximately 32% of U.S. adults had metabolic syndrome. [69] [70] In more recent years that figure has climbed to 34%. [70] [71]

In young children, there is no consensus on how to measure metabolic syndrome since age-specific cut points and reference values that would indicate "high risk" have not been well established. [72] A continuous cardiometabolic risk summary score is often used for children instead of a dichotomous measure of metabolic syndrome. [73]

Other conditions [74] and specific microbiome diversity [75] seems to be associated with metabolic syndrome, with certain-degree of gender-specificity. [76]

History

In 1921, Joslin first reported the association of diabetes with hypertension and hyperuricemia. [77] In 1923, Kylin reported additional studies on the above triad. [78] In 1947, Vague observed that upper body obesity appeared to predispose to diabetes, atherosclerosis, gout and calculi. [79] In the late 1950s, the term metabolic syndrome was first used.

In 1967, Avogadro, Crepaldi and coworkers described six moderately obese people with diabetes, hypercholesterolemia, and marked hypertriglyceridemia, all of which improved when the affected people were put on a hypocaloric, low-carbohydrate diet. [80] In 1977, Haller used the term metabolic syndrome for associations of obesity, diabetes mellitus, hyperlipoproteinemia, hyperuricemia, and hepatic steatosis when describing the additive effects of risk factors on atherosclerosis. [81] The same year, Singer used the term for associations of obesity, gout, diabetes mellitus, and hypertension with hyperlipoproteinemia. [82] In 1977 and 1978, Gerald B. Phillips developed the concept that risk factors for myocardial infarction concur to form a "constellation of abnormalities" (i.e., glucose intolerance, hyperinsulinemia, hypercholesterolemia, hypertriglyceridemia, and hypertension) associated not only with heart disease, but also with aging, obesity and other clinical states. He suggested there must be an underlying linking factor, the identification of which could lead to the prevention of cardiovascular disease; he hypothesized that this factor was sex hormones. [83] [84] In 1988, in his Banting lecture, Gerald M. Reaven proposed insulin resistance as the underlying factor and named the constellation of abnormalities syndrome X. Reaven did not include abdominal obesity, which has also been hypothesized as the underlying factor, as part of the condition. [85]

See also

Related Research Articles

Insulin resistance (IR) is a pathological condition in which cells in insulin-sensitive tissues in the body fail to respond normally to the hormone insulin or downregulate insulin receptors in response to hyperinsulinemia.

<span class="mw-page-title-main">Abdominal obesity</span> Excess fat around the stomach and abdomen

Abdominal obesity, also known as central obesity and truncal obesity, is the human condition of an excessive concentration of visceral fat around the stomach and abdomen to such an extent that it is likely to harm its bearer's health. Abdominal obesity has been strongly linked to cardiovascular disease, Alzheimer's disease, and other metabolic and vascular diseases.

<span class="mw-page-title-main">Glucose tolerance test</span> Medical test of how quickly glucose is cleared from the blood

The glucose tolerance test is a medical test in which glucose is given and blood samples taken afterward to determine how quickly it is cleared from the blood. The test is usually used to test for diabetes, insulin resistance, impaired beta cell function, and sometimes reactive hypoglycemia and acromegaly, or rarer disorders of carbohydrate metabolism. In the most commonly performed version of the test, an oral glucose tolerance test (OGTT), a standard dose of glucose is ingested by mouth and blood levels are checked two hours later. Many variations of the GTT have been devised over the years for various purposes, with different standard doses of glucose, different routes of administration, different intervals and durations of sampling, and various substances measured in addition to blood glucose.

<span class="mw-page-title-main">Hyperglycemia</span> Too much blood sugar, usually because of diabetes

Hyperglycemia or hyperglycaemia is the situation in which blood glucose level is higher than in a healthy subject. A fasting healthy human shows blood glucose level up to 5.6 mmol/L (100 mg/dL). After a meal (postprandial) containing carbohydrates, healthy subjects show postpandrial euglycemic peaks of less than 140 mg/dL (7.8 mmol/L). Therefore, fasting hyperglycemia are values of blood glucose higher than 5.6 mmol/L (100 mg/dL) whereas postprandial hyperglycemia are values higher than 140 mg/dL (7.8 mmol/L). Postprandial hyperglycemic levels as high as 155 mg/dL (8.6 mmol/L) at 1-h are associated with T2DM-related complications, which worsen as the degree of hyperglycemia increases. Patients with diabetes are oriented to avoid exceeding the recommended postprandial threshold of 160 mg/dL (8.89 mmol/L) for optimal glycemic control. Values of blood glucose higher than 160 mg/dL are classified as ‘very high’ hyperglycemia, a condition in which an excessive amount of glucose (glucotoxicity) circulates in the blood plasma. These values are higher than the renal threshold of 180 mg/dL (10 mmol/L) up to which glucose reabsorption is preserved at physiological rates and insulin therapy is not necessary. Blood glucose values higher than the cutoff level of 200 mg/dL (11.1 mmol/L) are used to diagnose T2DM and strongly associated with metabolic disturbances, although symptoms may not start to become noticeable until even higher values such as 13.9–16.7 mmol/L (~250–300 mg/dL). A subject with a consistent fasting blood glucose range between ~5.6 and ~7 mmol/L is considered slightly hyperglycemic, and above 7 mmol/L is generally held to have diabetes. For diabetics, glucose levels that are considered to be too hyperglycemic can vary from person to person, mainly due to the person's renal threshold of glucose and overall glucose tolerance. On average, however, chronic levels above 10–12 mmol/L (180–216 mg/dL) can produce noticeable organ damage over time.

<span class="mw-page-title-main">Type 2 diabetes</span> Form of diabetes mellitus

Type 2 diabetes (T2D), formerly known as adult-onset diabetes, is a form of diabetes mellitus that is characterized by high blood sugar, insulin resistance, and relative lack of insulin. Common symptoms include increased thirst, frequent urination, fatigue and unexplained weight loss. Other symptoms include increased hunger, having a sensation of pins and needles, and sores (wounds) that heal slowly. Symptoms often develop slowly. Long-term complications from high blood sugar include heart disease, stroke, diabetic retinopathy, which can result in blindness, kidney failure, and poor blood flow in the lower-limbs, which may lead to amputations. The sudden onset of hyperosmolar hyperglycemic state may occur; however, ketoacidosis is uncommon.

<span class="mw-page-title-main">Fibrate</span> Class of chemical compounds

In pharmacology, the fibrates are a class of amphipathic carboxylic acids and esters. They are derivatives of fibric acid. They are used for a range of metabolic disorders, mainly hypercholesterolemia, and are therefore hypolipidemic agents.

<span class="mw-page-title-main">Hypertriglyceridemia</span> High triglyceride blood levels

Hypertriglyceridemia is the presence of high amounts of triglycerides in the blood. Triglycerides are the most abundant fatty molecule in most organisms. Hypertriglyceridemia occurs in various physiologic conditions and in various diseases, and high triglyceride levels are associated with atherosclerosis, even in the absence of hypercholesterolemia and predispose to cardiovascular disease.

<span class="mw-page-title-main">Adiponectin</span> Mammalian protein found in Homo sapiens

Adiponectin is a protein hormone and adipokine, which is involved in regulating glucose levels and fatty acid breakdown. In humans, it is encoded by the ADIPOQ gene and is produced primarily in adipose tissue, but also in muscle and even in the brain.

<span class="mw-page-title-main">Hyperinsulinemia</span> Abnormal increase in insulin in the bloodstream relative to glucose

Hyperinsulinemia is a condition in which there are excess levels of insulin circulating in the blood relative to the level of glucose. While it is often mistaken for diabetes or hyperglycaemia, hyperinsulinemia can result from a variety of metabolic diseases and conditions, as well as non-nutritive sugars in the diet. While hyperinsulinemia is often seen in people with early stage type 2 diabetes mellitus, it is not the cause of the condition and is only one symptom of the disease. Type 1 diabetes only occurs when pancreatic beta-cell function is impaired. Hyperinsulinemia can be seen in a variety of conditions including diabetes mellitus type 2, in neonates and in drug-induced hyperinsulinemia. It can also occur in congenital hyperinsulinism, including nesidioblastosis.

The main goal of diabetes management is to keep blood glucose (BG) levels as normal as possible. If diabetes is not well controlled, further challenges to health may occur. People with diabetes can measure blood sugar by various methods, such as with a BG meter or a continuous glucose monitor, which monitors over several days. Glucose can also be measured by analysis of a routine blood sample. Usually, people are recommended to control diet, exercise, and maintain a healthy weight, although some people may need medications to control their blood sugar levels. Other goals of diabetes management are to prevent or treat complications that can result from the disease itself and from its treatment.

Metabolic imprinting refers to the long-term physiological and metabolic effects that an offspring's prenatal and postnatal environments have on them. Perinatal nutrition has been identified as a significant factor in determining an offspring's likelihood of it being predisposed to developing cardiovascular disease, obesity, and type 2 diabetes amongst other conditions.

<span class="mw-page-title-main">Prediabetes</span> Predisease state of hyperglycemia with high risk for diabetes

Prediabetes is a component of metabolic syndrome and is characterized by elevated blood sugar levels that fall below the threshold to diagnose diabetes mellitus. It usually does not cause symptoms but people with prediabetes often have obesity, dyslipidemia with high triglycerides and/or low HDL cholesterol, and hypertension. It is also associated with increased risk for cardiovascular disease (CVD). Prediabetes is more accurately considered an early stage of diabetes as health complications associated with type 2 diabetes often occur before the diagnosis of diabetes.

<span class="mw-page-title-main">Android fat distribution</span> Distribution of human adipose tissue mainly around the trunk and upper body

Android fat distribution describes the distribution of human adipose tissue mainly around the trunk and upper body, in areas such as the abdomen, chest, shoulder and nape of the neck. This pattern may lead to an "triangle"-shaped body or central obesity, and is more common in males than in females. Thus, the android fat distribution of men is about 48.6%, which is 10.3% higher than that of premenopausal women. In other cases, an ovoid shape forms, which does not differentiate between men and women. Generally, during early adulthood, females tend to have a more peripheral fat distribution such that their fat is evenly distributed over their body. However, it has been found that as females age, bear children and approach menopause, this distribution shifts towards the android pattern of fat distribution, resulting in a 42.1% increase in android body fat distribution in postmenopausal women. This could potentially provide evolutionary advantages such as lowering a woman's center of gravity making her more stable when carrying offspring.

The waist-to-height ratio is the waist circumference divided by body height, both measured in the same units.

A number of lifestyle factors are known to be important to the development of type 2 diabetes including: obesity, physical activity, diet, stress, and urbanization. Excess body fat underlies 64% of cases of diabetes in men and 77% of cases in women. A number of dietary factors such as sugar sweetened drinks and the type of fat in the diet appear to play a role.

This article provides a global overview of the current trends and distribution of metabolic syndrome. Metabolic syndrome refers to a cluster of related risk factors for cardiovascular disease that includes abdominal obesity, diabetes, hypertension, and elevated cholesterol.

<span class="mw-page-title-main">Diabetes</span> Group of endocrine diseases characterized by high blood sugar levels

Diabetes mellitus, often known simply as diabetes, is a group of common endocrine diseases characterized by sustained high blood sugar levels. Diabetes is due to either the pancreas not producing enough insulin, or the cells of the body becoming unresponsive to the hormone's effects. Classic symptoms include polydipsia, polyuria, weight loss, and blurred vision. If left untreated, the disease can lead to various health complications, including disorders of the cardiovascular system, eye, kidney, and nerves. Diabetes accounts for approximately 4.2 million deaths every year, with an estimated 1.5 million caused by either untreated or poorly treated diabetes.

Normal weight obesity is the condition of having normal body weight, but with a high body fat percentage, leading to some of the same health risks as obesity.

Diabetes mellitus (DM) is a type of metabolic disease characterized by hyperglycemia. It is caused by either defected insulin secretion or damaged biological function, or both. The high-level blood glucose for a long time will lead to dysfunction of a variety of tissues.

The Metabolic Score for Insulin Resistance (METS-IR) is a metabolic index developed with the aim to quantify peripheral insulin sensitivity in humans; it was first described under the name METS-IR by Bello-Chavolla et al. in 2018. It was developed by the Metabolic Research Disease Unit at the Instituto Nacional de Ciencias Médicas Salvador Zubirán and validated against the euglycemic hyperinsulinemic clamp and the frequently-sampled intravenous glucose tolerance test in Mexican population. It is a non-insulin-based alternative to insulin-based methods to quantify peripheral insulin sensitivity and an alternative to SPINA Carb, the Homeostatic Model Assessment (HOMA-IR) and the quantitative insulin sensitivity check index (QUICKI). METS-IR is currently validated for its use to assess cardio-metabolic risk in Latino population.

References

  1. 1 2 "Metabolic syndrome". Mayo Clinic. Retrieved 10 Sep 2020.
  2. Falkner B, Cossrow ND (July 2014). "Prevalence of metabolic syndrome and obesity-associated hypertension in the racial ethnic minorities of the United States". Current Hypertension Reports. 16 (7): 449. doi:10.1007/s11906-014-0449-5. PMC   4083846 . PMID   24819559.
  3. Beltrán-Sánchez H, Harhay MO, Harhay MM, McElligott S (August 2013). "Prevalence and trends of metabolic syndrome in the adult U.S. population, 1999–2010". Journal of the American College of Cardiology. 62 (8): 697–703. doi:10.1016/j.jacc.2013.05.064. PMC   3756561 . PMID   23810877.
  4. 1 2 Anagnostis, Panagiotis (November 30, 2023). "Metabolic Syndrome". BMJ Best Practice. Retrieved 30 December 2023.
  5. "Metabolic Syndrome". Diabetes.co.uk. 15 January 2019.
  6. Mendrick DL, Diehl AM, Topor LS, Dietert RR, Will Y, La Merrill MA, et al. (March 2018). "Metabolic Syndrome and Associated Diseases: From the Bench to the Clinic". Toxicological Sciences. 162 (1): 36–42. doi:10.1093/toxsci/kfx233. PMC   6256950 . PMID   29106690.
  7. Mohseni-Takalloo, Sahar; Mozaffari-Khosravi, Hassan; Mohseni, Hadis; Mirzaei, Masoud; Hosseinzadeh, Mahdieh (2023-06-13). "Evaluating Neck Circumference as an Independent Predictor of Metabolic Syndrome and Its Components Among Adults: A Population-Based Study". Cureus. 15 (6): e40379. doi: 10.7759/cureus.40379 . ISSN   2168-8184. PMC   10344419 . PMID   37456431.
  8. Shyam, Sangeetha; García-Gavilán, Jesús Francisco; Paz-Graniel, Indira; Gaforio, José J.; Martínez-González, Miguel Ángel; Corella, Dolores; Martínez, J. Alfredo; Alonso-Gómez, Ángel M.; Wärnberg, Julia; Vioque, Jesús; Romaguera, Dora; López-Miranda, José; Estruch, Ramon; Tinahones, Francisco J.; Lapetra, José (2023-10-13). "Association of adiposity and its changes over time with COVID-19 risk in older adults with overweight/obesity and metabolic syndrome: a longitudinal evaluation in the PREDIMED-Plus cohort". BMC Medicine. 21 (1): 390. doi: 10.1186/s12916-023-03079-z . ISSN   1741-7015. PMC   10576302 . PMID   37833678.
  9. Di Bella, Stefano; Cesareo, Roberto; De Cristofaro, Paolo; Palermo, Andrea; Sanson, Gianfranco; Roman-Pognuz, Erik; Zerbato, Verena; Manfrini, Silvia; Giacomazzi, Donatella; Dal Bo, Eugenia; Sambataro, Gianluca; Macchini, Elisabetta; Quintavalle, Francesco; Campagna, Giuseppe; Masala, Renato (2021). "Neck circumference as reliable predictor of mechanical ventilation support in adult inpatients with COVID-19: A multicentric prospective evaluation". Diabetes/Metabolism Research and Reviews. 37 (1): e3354. doi:10.1002/dmrr.3354. ISSN   1520-7552. PMC   7300447 . PMID   32484298.
  10. Di Bella, Stefano; Zerbato, Verena; Sanson, Gianfranco; Roman-Pognuz, Erik; De Cristofaro, Paolo; Palermo, Andrea; Valentini, Michael; Gobbo, Ylenia; Jaracz, Anna Wladyslawa; Bozic Hrzica, Elizabeta; Bresani-Salvi, Cristiane Campello; Galindo, Alexandre Bezerra; Crovella, Sergio; Luzzati, Roberto (2021-12-10). "Neck Circumference Predicts Mortality in Hospitalized COVID-19 Patients". Infectious Disease Reports. 13 (4): 1053–60. doi: 10.3390/idr13040096 . ISSN   2036-7449. PMC   8700782 . PMID   34940406.
  11. "Metabolic syndrome – Symptoms and causes". Mayo Clinic. Retrieved 2022-03-31.
  12. Norris, Philip; Gow, Jeff; Arthur, Thomas; Conway, Aaron; Fleming, Fergal J; Ralph, Nicholas (2 November 2023). "Metabolic syndrome and surgical complications: A systematic review and meta-analysis of 13 million individuals". International Journal of Surgery. 110 (1): 541–53. doi: 10.1097/JS9.0000000000000834 . PMC   10793842 . PMID   37916943.
  13. Malik VS, Popkin BM, Bray GA, Després JP, Willett WC, Hu FB (November 2010). "Sugar-sweetened beverages and risk of metabolic syndrome and type 2 diabetes: a meta-analysis". Diabetes Care. 33 (11): 2477–83. doi:10.2337/dc10-1079. PMC   2963518 . PMID   20693348.
  14. Pollex RL, Hegele RA (September 2006). "Genetic determinants of the metabolic syndrome". Nature Clinical Practice Cardiovascular Medicine. 3 (9): 482–89. doi:10.1038/ncpcardio0638. PMID   16932765. S2CID   24558150.
  15. Poulsen P, Vaag A, Kyvik K, Beck-Nielsen H (May 2001). "Genetic versus environmental aetiology of the metabolic syndrome among male and female twins". Diabetologia. 44 (5): 537–43. doi: 10.1007/s001250051659 . PMID   11380071. S2CID   26582450.
  16. Groop L (March 2000). "Genetics of the metabolic syndrome". The British Journal of Nutrition. 83 (Suppl 1): S39–S48. doi: 10.1017/S0007114500000945 . PMID   10889791. S2CID   8974554.
  17. Bouchard C (May 1995). "Genetics and the metabolic syndrome". International Journal of Obesity and Related Metabolic Disorders. 19 (Suppl 1): S52–59. PMID   7550538.
  18. Edwardson CL, Gorely T, Davies MJ, Gray LJ, Khunti K, Wilmot EG, Yates T, Biddle SJ (2012). "Association of sedentary behaviour with metabolic syndrome: a meta-analysis". PLOS ONE. 7 (4): e34916. Bibcode:2012PLoSO...734916E. doi: 10.1371/journal.pone.0034916 . PMC   3325927 . PMID   22514690.
  19. 1 2 Katzmarzyk PT, Leon AS, Wilmore JH, Skinner JS, Rao DC, Rankinen T, Bouchard C (October 2003). "Targeting the metabolic syndrome with exercise: evidence from the HERITAGE Family Study". Medicine and Science in Sports and Exercise. 35 (10): 1703–09. doi: 10.1249/01.MSS.0000089337.73244.9B . PMID   14523308. S2CID   25598917.
  20. He D, Xi B, Xue J, Huai P, Zhang M, Li J (June 2014). "Association between leisure time physical activity and metabolic syndrome: a meta-analysis of prospective cohort studies". Endocrine. 46 (2): 231–40. doi:10.1007/s12020-013-0110-0. PMID   24287790. S2CID   5271746.
  21. Xi B, He D, Zhang M, Xue J, Zhou D (August 2014). "Short sleep duration predicts risk of metabolic syndrome: a systematic review and meta-analysis". Sleep Medicine Reviews. 18 (4): 293–97. doi:10.1016/j.smrv.2013.06.001. PMID   23890470.
  22. Vancampfort D, Correll CU, Wampers M, Sienaert P, Mitchell AJ, De Herdt A, Probst M, Scheewe TW, De Hert M (July 2014). "Metabolic syndrome and metabolic abnormalities in patients with major depressive disorder: a meta-analysis of prevalences and moderating variables". Psychological Medicine. 44 (10): 2017–28. doi:10.1017/S0033291713002778. PMID   24262678. S2CID   206253750.
  23. Vancampfort D, Vansteelandt K, Correll CU, Mitchell AJ, De Herdt A, Sienaert P, Probst M, De Hert M (March 2013). "Metabolic syndrome and metabolic abnormalities in bipolar disorder: a meta-analysis of prevalence rates and moderators". The American Journal of Psychiatry. 170 (3): 265–74. doi:10.1176/appi.ajp.2012.12050620. PMID   23361837.
  24. Sun K, Ren M, Liu D, Wang C, Yang C, Yan L (August 2014). "Alcohol consumption and risk of metabolic syndrome: a meta-analysis of prospective studies". Clinical Nutrition. 33 (4): 596–602. doi:10.1016/j.clnu.2013.10.003. PMID   24315622.
  25. Vidal-Puig A (2013). "Adipose tissue expandability, lipotoxicity and the metabolic syndrome". Endocrinologia y Nutricion. 60 (Suppl 1): 39–43. doi:10.1016/s1575-0922(13)70026-3. PMID   24490226.
  26. Saklayen, M.G. (2018). "The Global Epidemic of the Metabolic Syndrome". Current Hypertension Reports. 20 (2): 12. doi:10.1007/s11906-018-0812-z. PMC   5866840 . PMID   29480368.
  27. Nakagawa T, Hu H, Zharikov S, Tuttle KR, Short RA, Glushakova O, Ouyang X, Feig DI, Block ER, Herrera-Acosta J, Patel JM, Johnson RJ (March 2006). "A causal role for uric acid in fructose-induced metabolic syndrome". American Journal of Physiology. Renal Physiology. 290 (3): F625–31. doi:10.1152/ajprenal.00140.2005. PMID   16234313.
  28. Hallfrisch J (June 1990). "Metabolic effects of dietary fructose". FASEB Journal. 4 (9): 2652–60. doi: 10.1096/fasebj.4.9.2189777 . PMID   2189777. S2CID   23659634.
  29. Reiser S, Powell AS, Scholfield DJ, Panda P, Ellwood KC, Canary JJ (May 1989). "Blood lipids, lipoproteins, apoproteins, and uric acid in men fed diets containing fructose or high-amylose cornstarch". The American Journal of Clinical Nutrition. 49 (5): 832–39. doi: 10.1093/ajcn/49.5.832 . PMID   2497634.
  30. Bremer AA, Mietus-Snyder M, Lustig RH (March 2012). "Toward a unifying hypothesis of metabolic syndrome". Pediatrics. 129 (3): 557–70. doi:10.1542/peds.2011-2912. PMC   3289531 . PMID   22351884.
  31. Ali ES, Hua J, Wilson CH, Tallis GA, Zhou FH, Rychkov GY, Barritt GJ (September 2016). "The glucagon-like peptide-1 analogue exendin-4 reverses impaired intracellular Ca(2+) signalling in steatotic hepatocytes". Biochimica et Biophysica Acta (BBA) - Molecular Cell Research. 1863 (9): 2135–46. doi:10.1016/j.bbamcr.2016.05.006. PMID   27178543.
  32. Gohil BC, Rosenblum LA, Coplan JD, Kral JG (July 2001). "Hypothalamic-pituitary-adrenal axis function and the metabolic syndrome X of obesity". CNS Spectrums. 6 (7): 581–86, 589. doi:10.1017/s1092852900002121. PMID   15573024. S2CID   22734016.
  33. Tsigos C, Chrousos GP (October 2002). "Hypothalamic-pituitary-adrenal axis, neuroendocrine factors and stress". Journal of Psychosomatic Research. 53 (4): 865–71. doi:10.1016/S0022-3999(02)00429-4. PMID   12377295.
  34. Rosmond R, Björntorp P (February 2000). "The hypothalamic-pituitary-adrenal axis activity as a predictor of cardiovascular disease, type 2 diabetes and stroke". Journal of Internal Medicine. 247 (2): 188–97. doi: 10.1046/j.1365-2796.2000.00603.x . PMID   10692081. S2CID   20336259.
  35. Brunner EJ, Hemingway H, Walker BR, Page M, Clarke P, Juneja M, Shipley MJ, Kumari M, Andrew R, Seckl JR, Papadopoulos A, Checkley S, Rumley A, Lowe GD, Stansfeld SA, Marmot MG (November 2002). "Adrenocortical, autonomic, and inflammatory causes of the metabolic syndrome: nested case-control study". Circulation. 106 (21): 2659–65. doi: 10.1161/01.cir.0000038364.26310.bd . PMID   12438290. S2CID   5992769.
  36. 1 2 3 4 5 6 Fauci, Anthony S. (2008). Harrison's principles of internal medicine. McGraw-Hill Medical. ISBN   978-0-07-147692-8.[ page needed ]
  37. Goldberg RB, Mather K (September 2012). "Targeting the consequences of the metabolic syndrome in the Diabetes Prevention Program". Arteriosclerosis, Thrombosis, and Vascular Biology. 32 (9): 2077–90. doi:10.1161/ATVBAHA.111.241893. PMC   3901161 . PMID   22895669.
  38. Lara-Castro C, Fu Y, Chung BH, Garvey WT (June 2007). "Adiponectin and the metabolic syndrome: mechanisms mediating risk for metabolic and cardiovascular disease". Current Opinion in Lipidology. 18 (3): 263–70. doi:10.1097/MOL.0b013e32814a645f. PMID   17495599. S2CID   20799218.
  39. Renaldi O, Pramono B, Sinorita H, Purnomo LB, Asdie RH, Asdie AH (January 2009). "Hypoadiponectinemia: a risk factor for metabolic syndrome". Acta Medica Indonesiana. 41 (1): 20–24. PMID   19258676.
  40. Quilon III A, Brent L (2010). "The primary care physician's guide to inflammatory arthritis: diagnosis". The Journal of Musculoskeletal Medicine. 27: 223–31.
  41. Chan SM, Selemidis S, Bozinovski S, Vlahos R (June 2019). "Pathobiological mechanisms underlying metabolic syndrome (MetS) in chronic obstructive pulmonary disease (COPD): clinical significance and therapeutic strategies". Pharmacol Ther. 198: 160–88. doi:10.1016/j.pharmthera.2019.02.013. PMC   7112632 . PMID   30822464.
  42. Hotamisligil GS (June 1999). "The role of TNFalpha and TNF receptors in obesity and insulin resistance". Journal of Internal Medicine. 245 (6): 621–25. doi: 10.1046/j.1365-2796.1999.00490.x . PMID   10395191. S2CID   58332116.
  43. Whitney, Ellie and Ralfes, R. Sharon. 2011. Understanding Nutrition. Wadsworth Cengage Learning: Belmont, CA
  44. 1 2 Gatta-Cherifi B, Cota D (2015). "Endocannabinoids and Metabolic Disorders". Endocannabinoids. Handbook of Experimental Pharmacology. Vol. 231. pp. 367–91. doi:10.1007/978-3-319-20825-1_13. ISBN   978-3-319-20824-4. PMID   26408168. The endocannabinoid system (ECS) is known to exert regulatory control on essentially every aspect related to the search for, and the intake, metabolism and storage of calories, and consequently it represents a potential pharmacotherapeutic target for obesity, diabetes and eating disorders. ... recent research in animals and humans has provided new knowledge on the mechanisms of actions of the ECS in the regulation of eating behavior, energy balance, and metabolism. In this review, we discuss these recent advances and how they may allow targeting the ECS in a more specific and selective manner for the future development of therapies against obesity, metabolic syndrome, and eating disorders.
  45. 1 2 3 Vemuri VK, Janero DR, Makriyannis A (March 2008). "Pharmacotherapeutic targeting of the endocannabinoid signaling system: drugs for obesity and the metabolic syndrome". Physiology & Behavior. 93 (4–5): 671–86. doi:10.1016/j.physbeh.2007.11.012. PMC   3681125 . PMID   18155257. The etiology of many appetitive disorders is characterized by a pathogenic component of reward-supported craving, be it for substances of abuse (including alcohol and nicotine) or food. Such maladies affect large numbers of people as prevalent socioeconomic and healthcare burdens. Yet in most instances drugs for their safe and effective pharmacotherapeutic management are lacking despite the attendant medical needs, collateral adverse physical and psychological effects, and enormous global market potential. The endocannabinoid signaling system plays a critical role in motivational homeostasis as a conduit for reward stimuli and a positive modulator of brain reward circuits. Endocannabinoid-system hyperactivity through CB1 receptor transmission is considered contributory to a range of appetitive disorders and, hence, is a major focus of contemporary pharmaceutical research.
  46. 1 2 3 4 Turcotte C, Chouinard F, Lefebvre JS, Flamand N (June 2015). "Regulation of inflammation by cannabinoids, the endocannabinoids 2-arachidonoyl-glycerol and arachidonoyl-ethanolamide, and their metabolites". Journal of Leukocyte Biology. 97 (6): 1049–70. doi:10.1189/jlb.3RU0115-021R. PMID   25877930. S2CID   206999921.
  47. Fukuchi S, Hamaguchi K, Seike M, Himeno K, Sakata T, Yoshimatsu H (June 2004). "Role of fatty acid composition in the development of metabolic disorders in sucrose-induced obese rats". Experimental Biology and Medicine. 229 (6): 486–93. doi:10.1177/153537020422900606. PMID   15169967. S2CID   20966659.
  48. Di Marzo V, Fontana A, Cadas H, et al. (Dec 1994). "Formation and inactivation of endogenous cannabinoid anandamide in central neurons". Nature (Submitted manuscript). 372 (6507): 686–91. Bibcode:1994Natur.372..686D. doi:10.1038/372686a0. PMID   7990962. S2CID   4341716.
  49. Expert Panel On Detection, Evaluation (May 2001). "Executive Summary of The Third Report of The National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, And Treatment of High Blood Cholesterol In Adults". JAMA. 285 (19): 2486–97. doi:10.1001/jama.285.19.2486. PMID   11368702.
  50. 1 2 3 Alberti KG, Eckel RH, Grundy SM, Zimmet PZ, Cleeman JI, Donato KA, Fruchart JC, James WP, Loria CM, Smith SC (October 2009). "Harmonizing the metabolic syndrome: a joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity" (PDF). Circulation. 120 (16): 1640–45. doi:10.1161/CIRCULATIONAHA.109.192644. PMID   19805654.
  51. 1 2 Alberti G, Zimmet P, Shaw J (2006). Grundy SM (ed.). IDF Consensus Worldwide Definition of the Metabolic Syndrome (PDF) (Report). Brussels, Belgium: International Diabetes Federation. Archived from the original on 2012-09-16.
  52. Alberti KG, et al. (1999). "Definition, Diagnosis, and Classification of Diabetes Mellitus and its Complications" (PDF). World Health Organization. pp. 32–33. Archived from the original (PDF) on 21 August 2014. Retrieved 25 March 2013.
  53. Balkau B, Charles MA (May 1999). "Comment on the provisional report from the WHO consultation. European Group for the Study of Insulin Resistance (EGIR)". Diabet Med. 16 (5): 442–43. doi:10.1046/j.1464-5491.1999.00059.x. PMID   10342346.
  54. Khanmohammadi, Shaghayegh; Tavolinejad, Hamed; Aminorroaya, Arya; Rezaie, Yasaman; Ashraf, Haleh; Vasheghani-Farahani, Ali (2022-08-30). "Association of lipid accumulation product with type 2 diabetes mellitus, hypertension, and mortality: a systematic review and meta-analysis". Journal of Diabetes & Metabolic Disorders. 21 (2). Springer Science and Business Media LLC: 1943–73. doi:10.1007/s40200-022-01114-z. ISSN   2251-6581. PMC   9672205 . PMID   36404835. S2CID   251912707.
  55. Pluta, Waldemar; Dudzińska, Wioleta; Lubkowska, Anna (2022-01-06). "Metabolic Obesity in People with Normal Body Weight (MONW) – Review of Diagnostic Criteria". International Journal of Environmental Research and Public Health. 19 (2). MDPI AG: 624. doi: 10.3390/ijerph19020624 . ISSN   1660-4601. PMC   8776153 . PMID   35055447.
  56. Chen, Lei; Shi, Guang-rui; Huang, Dan-dan; Li, Yang; Ma, Chen-chao; Shi, Min; Su, Bin-xiao; Shi, Guang-jiang (2019). "Male sexual dysfunction: A review of literature on its pathological mechanisms, potential risk factors, and herbal drug intervention". Biomedicine & Pharmacotherapy. 112. Elsevier BV: 108585. doi: 10.1016/j.biopha.2019.01.046 . ISSN   0753-3322. PMID   30798136.
  57. Bagheri, Soghra; Zolghadri, Samaneh; Stanek, Agata (2022-09-26). "Beneficial Effects of Anti-Inflammatory Diet in Modulating Gut Microbiota and Controlling Obesity". Nutrients. 14 (19). MDPI AG: 3985. doi: 10.3390/nu14193985 . ISSN   2072-6643. PMC   9572805 . PMID   36235638.
  58. Kogiso T, Moriyoshi Y, Shimizu S, Nagahara H, Shiratori K (2009). "High-sensitivity C-reactive protein as a serum predictor of nonalcoholic fatty liver disease based on the Akaike Information Criterion scoring system in the general Japanese population". Journal of Gastroenterology. 44 (4): 313–21. doi:10.1007/s00535-009-0002-5. PMID   19271113. S2CID   1193178.
  59. Brand JS, van der Tweel I, Grobbee DE, Emmelot-Vonk MH, van der Schouw YT (February 2011). "Testosterone, sex hormone-binding globulin and the metabolic syndrome: a systematic review and meta-analysis of observational studies". International Journal of Epidemiology. 40 (1): 189–207. doi: 10.1093/ije/dyq158 . PMID   20870782.
  60. Lakka TA, Laaksonen DE (February 2007). "Physical activity in prevention and treatment of the metabolic syndrome". Applied Physiology, Nutrition, and Metabolism. 32 (1): 76–88. doi:10.1139/h06-113. PMID   17332786.
  61. Feldeisen SE, Tucker KL (February 2007). "Nutritional strategies in the prevention and treatment of metabolic syndrome". Applied Physiology, Nutrition, and Metabolism. 32 (1): 46–60. doi:10.1139/h06-101. PMID   17332784.
  62. James PT, Rigby N, Leach R (February 2004). "The obesity epidemic, metabolic syndrome and future prevention strategies". European Journal of Cardiovascular Prevention and Rehabilitation. 11 (1): 3–8. doi:10.1097/01.hjr.0000114707.27531.48. PMID   15167200. S2CID   36797932.
  63. Elwood PC, Pickering JE, Fehily AM (August 2007). "Milk and dairy consumption, diabetes and the metabolic syndrome: the Caerphilly prospective study". Journal of Epidemiology and Community Health. 61 (8): 695–98. doi:10.1136/jech.2006.053157. PMC   2652996 . PMID   17630368.
  64. Snijder MB, van der Heijden AA, van Dam RM, Stehouwer CD, Hiddink GJ, Nijpels G, Heine RJ, Bouter LM, Dekker JM (April 2007). "Is higher dairy consumption associated with lower body weight and fewer metabolic disturbances? The Hoorn Study". The American Journal of Clinical Nutrition. 85 (4): 989–95. doi: 10.1093/ajcn/85.4.989 . PMID   17413097.
  65. Manheimer EW, van Zuuren EJ, Fedorowicz Z, Pijl H (October 2015). "Paleolithic nutrition for metabolic syndrome: systematic review and meta-analysis". The American Journal of Clinical Nutrition. 102 (4): 922–32. doi:10.3945/ajcn.115.113613. PMC   4588744 . PMID   26269362.
  66. Feinman RD, Pogozelski WK, Astrup A, Bernstein RK, Fine EJ, Westman EC, et al. (January 2015). "Dietary carbohydrate restriction as the first approach in diabetes management: critical review and evidence base". Nutrition. 31 (1): 1–13. doi: 10.1016/j.nut.2014.06.011 . PMID   25287761.
  67. Alkhulaifi, F. (2022). "Meal Timing, Meal Frequency and Metabolic Syndrome". Nutrients. 14 (1719): 1719. doi: 10.3390/nu14091719 . PMC   9102985 . PMID   35565686.
  68. Srikanthan K, Feyh A, Visweshwar H, Shapiro JI, Sodhi K (2016). "Systematic Review of Metabolic Syndrome Biomarkers: A Panel for Early Detection, Management, and Risk Stratification in the West Virginian Population". International Journal of Medical Sciences. 13 (1): 25–38. doi:10.7150/ijms.13800. PMC   4716817 . PMID   26816492.
  69. Ford ES, Li C, Zhao G (September 2010). "Prevalence and correlates of metabolic syndrome based on a harmonious definition among adults in the US". Journal of Diabetes. 2 (3): 180–93. doi: 10.1111/j.1753-0407.2010.00078.x . PMID   20923483. S2CID   5145131.
  70. 1 2 Ford ES, Giles WH, Mokdad AH (October 2004). "Increasing prevalence of the metabolic syndrome among u.s. Adults". Diabetes Care. 27 (10): 2444–49. doi: 10.2337/diacare.27.10.2444 . PMID   15451914.
  71. Mozumdar A, Liguori G (January 2011). "Persistent increase of prevalence of metabolic syndrome among U.S. adults: NHANES III to NHANES 1999–2006". Diabetes Care. 34 (1): 216–19. doi:10.2337/dc10-0879. PMC   3005489 . PMID   20889854.
  72. Kamel M, Smith BT, Wahi G, Carsley S, Birken CS, Anderson LN (December 2018). "Continuous cardiometabolic risk score definitions in early childhood: a scoping review". Obesity Reviews. 19 (12): 1688–99. doi:10.1111/obr.12748. PMID   30223304. S2CID   52291692.
  73. Chiarelli F, Mohn A (October 2017). "Early diagnosis of metabolic syndrome in children". The Lancet. Child & Adolescent Health. 1 (2): 86–88. doi:10.1016/S2352-4642(17)30043-3. PMID   30169210.
  74. Mendrick, Donna L; Diehl, Anna Mae; Topor, Lisa S; Dietert, Rodney R; Will, Yvonne; La Merrill, Michele A; Bouret, Sebastien; Varma, Vijayalaskshmi; Hastings, Kenneth L; Schug, Thaddeus T; Emeigh Hart, Susan G; Burleson, Florence G (2018-03-01). "Metabolic Syndrome and Associated Diseases: From the Bench to the Clinic". Toxicological Sciences. 162 (1): 36–42. doi:10.1093/toxsci/kfx233. ISSN   1096-6080. PMC   6256950 . PMID   29106690.
  75. Fan, Yong; Pedersen, Oluf (January 2021). "Gut microbiota in human metabolic health and disease". Nature Reviews Microbiology. 19 (1): 55–71. doi:10.1038/s41579-020-0433-9. ISSN   1740-1526. PMID   32887946. S2CID   256744684.
  76. Pietropaoli, Davide; Altamura, Serena; Ortu, Eleonora; Guerrini, Luca; Pizarro, Theresa T.; Ferri, Claudio; Del Pinto, Rita (2023-04-10). "Association between metabolic syndrome components and gingival bleeding is women-specific: a nested cross-sectional study". Journal of Translational Medicine. 21 (1): 252. doi: 10.1186/s12967-023-04072-z . ISSN   1479-5876. PMC   10088168 . PMID   37038173.
  77. Joslin E (1921). "The Prevention of Diabetes Mellitus". JAMA. 76 (2): 79–84. doi:10.1001/jama.1921.02630020001001.
  78. Kylin E (1923). "[Studies of the hypertension-hyperglycemia-hyperuricemia syndrome]". Zentralbl Inn Med (in German). 44: 105–27.
  79. Vague J (1947). "La diffférenciacion sexuelle, facteur déterminant des formes de l'obésité". Presse Med. 30: 339–40.
  80. Avogaro P, Crepaldi G, Enzi G, Tiengo A (1967). "Associazione di iperlipemia, diabete mellito e obesita' di medio grado" [Association of hyperlipemia, diabetes mellitus and middle-degree obesity]. Acta Diabetologica Latina (in Italian). 4 (4): 572–90. doi:10.1007/BF01544100. S2CID   25839940.
  81. Haller H (April 1977). "[Epidermiology and associated risk factors of hyperlipoproteinemia]". Zeitschrift für Sie Gesamte Innere Medizin und Ihre Grenzgebiete. 32 (8): 124–28. PMID   883354.
  82. Singer P (May 1977). "[Diagnosis of primary hyperlipoproteinemias]". Zeitschrift für die Gesamte Innere Medizin und Ihre Grenzgebiete. 32 (9): 129–33. PMID   906591.
  83. Phillips GB (July 1978). "Sex hormones, risk factors and cardiovascular disease". The American Journal of Medicine. 65 (1): 7–11. doi:10.1016/0002-9343(78)90685-X. PMID   356599.
  84. Phillips GB (April 1977). "Relationship between serum sex hormones and glucose, insulin and lipid abnormalities in men with myocardial infarction". Proceedings of the National Academy of Sciences of the United States of America. 74 (4): 1729–33. Bibcode:1977PNAS...74.1729P. doi: 10.1073/pnas.74.4.1729 . PMC   430867 . PMID   193114.
  85. Reaven GM (December 1988). "Banting lecture 1989. Role of insulin resistance in human disease". Diabetes. 37 (12): 1595–607. doi:10.2337/diabetes.37.12.1595. PMID   3056758.