The Effects of Metabolic Syndrome on Psychiatric Disorders

Elif Şentürk1, Hadi Sasani2, Berzah Güneş3, Oytun Erbaş3

1St Helens and Knowsley Teaching Hospitals NHS Foundation Trust, Department of Psychiatry, North West, United Kingdom
2Tekirdağ Namık Kemal University, Faculty of Medicine, Department of Radiology, Tekirdağ, Turkey
3ERBAS Institute of Experimental Medicine, Illinois, USA & Gebze, Turkey

Keywords: Cardiovascular diseases, metabolic syndrome, neurodegenerative disorders, radiology

Abstract

The metabolic syndrome (MetS) is characterized by the presence of five parameters including dyslipidemia, abdominal (centripetal) obesity, impaired glucose tolerance, insulin resistance and hypertension. The likelihood of a patient having cardiovascular disease (CVD) is increased by all of these factors. Worldwide, its prevalence is higher among people with severe mental illness, possibly as a result of the harmful lifestyles defined by inactivity, heavy drinking, smoking, unhealthful foods, and psychotropic prescription use. Patients in psychiatric facilities run a higher risk of dying too soon, mostly from CVD. There is some proof that mental illnesses and MetS have a bidirectional longitudinal influence and that there is a dose-response relationship between the intensity and duration of symptoms. In general, associations with dyslipidemia dysregulations and abdominal obesity seem greater than those with hypertension. Unhealthy lifestyle choices and poor adherence to prescribed medications, which are common among people with mental health conditions, are contributing factors. The development of MetS and mental disorders is influenced by pleiotropy in genetic susceptibility and pathophysiological processes, such as those causing greater central and peripheral activation of immuno-metabolic or endocrine systems. Imaging is crucial for assessing abdominal obesity as well as for identifying fatty liver or consequences from MetS. In this article, we aimed to review the link between MetS and psychiatric disorders.

The metabolic syndrome (MetS), also known as syndrome X, is a collection of five conditions that together raise a patient’s risk of cardiovascular disease (CVD). These conditions include dyslipidemia, abdominal obesity, impaired glucose tolerance, insulin resistance, and hypertension.[1,2]

The cardiovascular system, pancreas, and liver are major areas that are vulnerable to injury.[3–5] There are some reported conditions associated with MetS including CVD, neurological disorders (cognitive impairment, vascular dementia, Alzheimer’s disease, stroke), endocrinological disorders (polycystic ovary syndrome, nonalcoholic steatohepatitis, type 2 diabetes), psychiatric conditions (major depressive disorder, bipolar disorder, schizophrenia, anxiety disorder, attention-deficit hyperactivity disorder, and posttraumatic stress disorder) and cancer.[6-11]

The purpose of this article was to examine the relationship between MetS and psychiatric disorders.

About 20-25% of people worldwide suffer from metabolic syndrome. In comparison to the general population, it is more prevalent (by about 1.5-2 times) and triples the risk of heart attack or stroke in people with severe mental illness.[12,13]

Studies conducted in developed countries, such as the United States, have shown prevalence rates reaching nearly 35% in adults,[14] while a mean prevalence of approximately 25% has been found in Latin America.[15] According to a recent systematic review, rates for Brazilian adults ranged from 14.9% to 65.3%.[16]

ETIOLOGY

In order to create preventive and/or therapeutic strategies, it is crucial to comprehend potential shared mechanisms underlying metabolic syndrome and the diseases that it is associated with. Several factors have been mentioned in the literature, including:

Mitochondrial dysfunction: As the disease progresses from insulin resistance to type 2 diabetes and from nonalcoholic fatty liver disease to nonalcoholic steatohepatitis, mitochondrial dysfunction appears to play a role in metabolic syndrome and increases.[17] Insulin resistance has been associated with mitochondrial DNA (mt-DNA) mutations and haplotypes, however, there are differences between ethnic groups that may be explained by varying nuclear genetic origins or environmental variables.[18]

Inflammation: Derived from data of elevated serum levels of several proinflammatory cytokines (e.g., tumor necrosis factor-alpha and interleukin-1 beta) and inflammation biomarkers (e.g., C-reactive protein), metabolic syndrome triggers chronic inflammation at key sites including the liver, the intestine, and adipose tissue. Inflammatory mediators are released, causing broad tissue malfunction and exacerbating chronic inflammation.[19–23]

Microbiome: Due to the fact that meals and calorie intake can modify the gut microbiota, this might result in a faulty barrier function where bacterial metabolites enter the bloodstream and inflame the liver. Normalizing the gut microbiota is possible using prebiotics, probiotics, and fecal transplants. As human cells include receptors that permit cross-talk between the host and the bacterium, microbial metabolites can have an effect on human health. Fecal microbiota and the occurrence of obesity and type 2 diabetes are linked by metagenome-wide association studies.[24,25] The hepatic enzyme flavin mono-oxygenase 3 transforms the trimethylamine (TMA) that intestinal bacteria make into the trimethylamine N-oxide (TMAO). Circulating TMAO is associated with type 2 diabetes, obesity, and atherosclerosis because it improves forward cholesterol transport while lowering reverse cholesterol transport and encouraging atherosclerosis. In mice and people, TMAO has been found to promote atherosclerosis.[26,27]

Effects on the environment and medications: Studies have shown a connection between the chemicals dichlorodiphenyltrichloroethane (DDT) and dichlorodiphenyldichloroethylene (DDE) and the risk of obesity, type 2 diabetes, and hypertension.[28,29] The risk of metabolic syndrome in adult female babies is increased by DDT exposure during pregnancy, which reduces heat generation and alters lipid and carbohydrate metabolism.[30] Exposure to some medications such as protease inhibitors[31] may exacerbate nonalcoholic fatty liver disease or medications like tamoxifen, irinotecan, and corticosteroids may cause metabolic syndrome.[32]

DIAGNOSTIC CRITERIA

Measures of abdominal obesity, atherogenic dyslipidemia, hypertension, and glucose intolerance are used to diagnose metabolic syndrome clinically. The measurement of fasting insulin or its substitutes and the presence of evidence of insulin resistance are required elements of the World Health Organization’s diagnosis of metabolic syndrome. However, a more straightforward definition, created for therapeutic usage and without any calculation of insulin resistance, was put forth by the Adult Treatment Panel III of the National Cholesterol Education Program (NCEP).[33,34]

Metabolic syndrome is defined as meeting the following three requirements[1]:

•High blood pressure (>130/85 mm Hg)

•Low high-density lipoprotein cholesterol (HDL-C) levels (1.04 mmol/l in men and 1.29 mmol/l in women)

•High triglyceride levels (>1.69 mmol/l)

•High fasting plasma glucose levels (>6.1 mmol/l), and abdominal obesity (waist circumference >102 cm in men and >88 cm in women) are all risk factors for heart disease.

The International Diabetes Federation has proposed a new definition with a range of cut-offs for waist circumference for people from different ethnic groups that includes central obesity as a key requirement.

Among the metabolic characteristics of the MetS, abdominal obesity and insulin resistance are particularly important. Incidence of MetS, as well as an elevated risk for additional MetS components and cardiometabolic disease, are all strongly correlated with the duration and severity of obesity. Increased mortality and increased morbidity are both consequences of obesity. An imbalance between adipokines and insulin is recognized to be a primary contributor to visceral obesity, which is also strongly linked to the other four MetS characteristics.[35–37]

Factors Affecting Metabolic Syndrome

Age: MetS is more common as people get older, and as people get older, physiological and environmental changes affect how they eat and how they use their energy, which can contribute to cardiovascular diseases.[38,39]

Gender: There is no discernible difference in the prevalence of MetS between males and females.[15,40]

Ethnicity: Research findings have demonstrated that populations in Asia, China, and Africa have higher rates of MetS and cardiometabolic risk factors than Caucasians. Higher visceral fat, which frequently has nothing to do with high body mass index (BMI) values, is correlated with MetS in these groups. For instance, Asians have a higher body fat index compared to Caucasians.[41–44]

Modalities for Radiological Diagnosis

The evaluation of visceral abdominal adipose tissue (VAT), which is the best predictor of MetS in women and a good predictor in men, using ultrasound (US), computed tomography (CT), and magnetic resonance imaging (MRI) is a useful application of these imaging modalities.[45]

• The use of the US to assess VAT and subcutaneous adipose tissue (SAT) is safe, noninvasive, practical, quick, and reasonably priced.[46] When compared to computed tomography and MRI, VAT measurements in obese people and the elderly taken using the US have better correlations, while SAT has a lesser connection.[47] Independent of body mass index, larger VAT was linked to increased hepatic insulin resistance, triglycerides, and lower levels of HDL-C regardless of ethnic group or gender. These findings imply that the US may be helpful in assessing intra-abdominal adipose tissue. In other words, even after adjusting for clinical risk variables and BMI, there is a substantial link between VAT and cardiovascular disease, although SAT did not.[46,48] However, it has been demonstrated in a study that SAT and VAT assessed by the US are both independently related to MetS.[49]

• Computed tomography and MRI are the guideline procedures for the evaluation of VAT and SAT since they are cross-sectional modalities.[50,51] Although it has the highest temporal and spatial resolution, CT is a quick and efficient diagnostic method that exposes users to radiation.[52] The range of adipose tissue density in CT is between -30 and -190 Hounsfield unit (HU). One slice of a CT scan can be used to quantify VAT at the L4 level, which has a strong correlation with the total abdominal VAT measurement.[53] Compared to waist circumference, CT-measured VAT is more significantly linked with MetS.[54] Although the VAT and SAT measurements rely on a person’s race and gender, the values fluctuate depending on the degree of measurement. Total VAT volume was more correctly reflected at L2-3, as opposed to L4-5, in the research of an obese white European population. Nevertheless, several studies used L4 level measurements (in Japanese, Europeans, South Asians, and African Caribbeans)[53,55] and in other studies at L4-L5, where they assert that it is most connected with the overall volume of VAT, and scans at this level best enable VAT and SAT distinction.[56] For the purpose of determining the risk of obesity-related problems, a visceral fat area cut-off value of 100 cm2 is employed.[53]

Increased morbidity and death are consequences of metabolic syndrome. Consequently, the diagnosis, as well as treatment, is crucial. Non-invasive imaging techniques are useful for stratifying risk variables, such as abdominal obesity and insulin resistance, and assessing the damages to the target organs in specific MetS patients. The research has documented the use of imaging techniques like the US or cross-sectional modalities (CT, MRI) in identifying MetS markers like VAT and SAT. Although there are various stated levels of measurement in the literature, a single slice CT scan at the L4 level in late expiration can serve as the standard for measuring SAT and VAT due to its accuracy, reproducibility, repeatability, and convenience. High triglycerides, high ALT, high GGT, and the combination of both VAT and SAT have the highest associations with visceral adipose tissue, and they also have the strongest associations with MetS.[49,53,56]

PSYCHIATRIC CONDITIONS LINKED TO METABOLIC SYNDROME

Cardiovascular diseases increase the risk of premature death in psychiatric patients. Evidence suggests that metabolic syndrome risk factors such as hyperglycemia, dyslipidemia, obesity, and hypertension are more common in those with mental illnesses. Compared to the general population, individuals with psychiatric conditions are more likely to develop MetS. Mental illnesses, such as major depressive disorder[57], anxiety disorder[58], schizophrenia[59], and bipolar disorder, are considerably more likely to have linked to comorbidities such as diabetes, stroke, and obesity.[60] For instance, 47.5% of study participants with bipolar disorder and 39% of participants with major depressive disorder had MetS, and MetS, with a prevalence of 38.4%, was significantly associated with the presence of any anxiety disorder.[8,61,62] Research indicates that those with severe psychiatric problems have life expectancies that are seven to 24 years shorter.[63] Poor adherence to medical therapy and an unhealthy lifestyle are contributing factors.

Major Depressive Disorder

A depressed mood or a loss of interest that lasts more than two weeks are symptoms of major depressive disorder. Depressed mood or irritability, significant changes in weight and appetite, decreased interest in most activities, changes in sleep, feelings of worthlessness, psychomotor agitation or retardation, fatigue, poor concentration, and suicidal thoughts are five of the nine symptoms that must be present almost every day.[64] Numerous investigations have been conducted to determine the connection between depression and metabolic syndrome; the majority of these studies have discovered a favorable correlation.[65-69] Data show a correlation between depression and the beginning of MetS and depression and the onset of MetS.[70] A combination of metabolic dysregulations, according to studies conducted on depressed individuals, is a factor in the persistent chronicity of depression.[71,72] Common molecular processes may contribute to the link between depression and obesity. These illnesses’ correlation may result from aberrant neurological or inflammatory networks.[73] The hypothalamic-pituitary-adrenal axis (HPA) abnormalities, hormones and signaling molecules originating from adipose tissue, dysfunctional brain-derived neurotrophic factor signaling, insulin signaling, the activity of inflammatory cytokines, and oxidative stress pathways are some of the hypotheses.[74]

Anxiety

Excessive concern in several areas, together with physical symptoms that have been persistent for at least six months, are signs of generalized anxiety disorder, which can cause clinically substantial discomfort or functional impairment.[75] Unhealthy habits including smoking, binge drinking, being sedentary, and eating poorly have all been linked to anxiety.[76] The cortisol awakening response is less apparent in people who experience high levels of anxiety symptoms, according to research correlating anxiety to altered cortisol activity.[77] Stress and the production of cortisol are two mechanisms through which anxiety may be linked to poor metabolic outcomes. This links metabolic syndrome with anxiety. Additionally, the long-term development of MetS may be influenced by hypothalamic-pituitary-adrenocortical system dysregulation linked to affective disorders, such as anxiety.[67]

Schizophrenia

Schizophrenia is a serious mental illness with high rates of morbidity and permanent impairment. Antipsychotics, prolonged hospitalization, poor lifestyle choices, and eating disorders have all contributed to the development of a metabolic syndrome in schizophrenia patients, which includes obesity, impaired glucose metabolism, dyslipidemia, and hypertension.[59,78,79] In people with schizophrenia, the estimated frequency of metabolic syndrome ranges from 37 to 67%, which represents a 2- to 3-fold greater risk compared to the general population.[80,81] Currently, the mechanism of risk factors for MetS is not well known. According to some research, the pathogenesis of schizophrenia may be influenced by changes in the levels of gene expression as well as alterations in the dopamine and serotonin neurotransmitters and receptors brought on by psychotropic medications or schizophrenia.[82] Additionally, first-episode psychosis patients have changes in their immune system, cardiometabolic system, brain anatomy, neurophysiology, and characteristics related to the HPA. This shows that among those experiencing their first episode of psychosis, malfunction is prevalent throughout several organ systems.[83]

MANAGEMENT AND TREATMENT

Reducing the risk for clinical cardiovascular events such as atherosclerotic disease is the main objective of clinical care in people with metabolic syndrome. First-line treatment is focused on addressing the main risk factors such as high low-density lipoprotein cholesterol (LDL-C), hypertension, and preventing type 2 diabetes mellitus, even in those with metabolic syndrome. The main goal of managing metabolic syndrome is to minimize all of the metabolic risk factors (obesity, physical inactivity, and atherogenic diet) by modifying the modifiable underlying risk factors through lifestyle modifications. Drug therapy can be administered when the absolute risk is great. Additionally, efforts should be made to help cigarette smokers stop smoking. The presence of additional metabolic syndrome risk factors in diabetics indicates a higher likelihood of developing atherosclerotic cardiovascular disease (ASCVD) in the future.[84,85]

Physical exercise: Increasing physical activity helps people lose weight, has positive impacts on metabolic risk factors, and, most significantly, lowers their risk of developing ASCVD overall. A moderate-intensity workout lasting more than 30 minutes, like brisk walking, provides greater advantages.[86,87]

Diet: Saturated and trans fats, cholesterol, salt, and simple carbohydrates should all be consumed in moderation. fruits, veggies, whole grains, and fish should all be consumed in sufficient amounts. Diets high in protein and low in carbohydrates will help you lose weight.[88–91] After achieving the LDL-C goal in patients with atherogenic dyslipidemia whose serum triglyceride levels are 200 mg/dL, non-HDL-C is the next treatment goal. While non-HDL-C targets are similar to LDL-C targets, the former is 30 mg/ dL higher. Triglyceride-lowering medications ought to be taken into consideration to stop the onset of acute pancreatitis when blood levels are below 500 mg/dL. Fibrinolytic acid and fibrates both increase HDL-C and lower triglycerides and small LDL particles. Fenofibrate can be chosen if a statin is being used to lower LDL-C.[34,85,92]

Controlling high blood pressure: According to the Dietary Approaches to Stop Hypertension (DASH) diet, it can be successfully managed with lifestyle therapies like weight management, increased physical activity, moderate alcohol consumption, sodium reduction, and increased consumption of fresh produce and low-fat dairy products. Medications like angiotensin-converting enzyme (ACE) inhibitors or angiotensin receptor blockers (ARBs) may be used if blood pressure is not controlled by lifestyle changes. First-line treatment for hypertension in metabolic syndrome should include ACE inhibitors, particularly in cases of type 2 diabetes or chronic renal disease. ARBs may be used in patients with left ventricular dysfunction or in those who cannot tolerate ACE inhibitors.[88,93,94]

Control of high fasting blood sugar: Impaired fasting glucose and type 2 diabetes mellitus are both considered to have high fasting glucose (100 mg/dL). To reduce the risk of type 2 diabetes mellitus in persons with impaired fasting glucose or impaired glucose intolerance, drugs including metformin, thiazolidinediones, and acarbose can be used if lifestyle treatments are unsuccessful. Metformin reduces the risk of metabolic syndrome in individuals with increased fasting plasma glucose levels, however, lifestyle changes were more effective and altered the intestinal flora.[95–98]

Antipsychotics are used in the long-term therapeutic strategy for the treatment of schizophrenia, which has the potential side effect of increasing the risk of metabolic syndrome and cardiovascular events.[99] Hyperprolactinemia is most frequently caused by antipsychotics.[100] Antipsychotics can all result in hyperprolactinemia since they all block D2 receptors, which also eliminates dopamine’s inhibitory influence on prolactin release.[101] Tricyclic antidepressants, regardless of how they affect weight, can increase blood lipids and produce insulin resistance. With regard to weight gain, second-generation antipsychotics clozapine and olanzapine pose the biggest risk. Risperidone, paliperidone, and quetiapine have a moderate risk of making patients gain weight. Asenapine, amisulpride, ziprasidone, and aripiprazole have less of an impact on body weight. A total mean weight gain of 12.1 kg was recorded three years following the start of treatment in a cohort trial involving 170 patients with psychosis.[102]

Antipsychotics and other psychiatric medications are linked to weight gain. A reduction in basal metabolic rate, as well as an increase in hunger and a yearning for carbohydrates, are possible side effects of treatment. The use of antidepressants was linked to high levels of fasting plasma glucose, low HDL cholesterol, and hypertension.[103]

In conclusion, although metabolic syndrome poses a high risk, especially in terms of cardiovascular system diseases, it can also accompany psychiatric disorders such as major depressive disorder, anxiety disorder, schizophrenia, and bipolar disorder. Therefore, metabolic diseases should be considered in the differential diagnosis of psychiatric disorders in the evaluation and especially in the treatment phase of high-risk patients.

Cite this article as: Şentürk E, Sasani H, Güneş B, Erbaş O. The Effects of Metabolic Syndrome on Psychiatric Disorders. JEB Med Sci. 2022;3(2):125-133.

Conflict of Interest

The authors declared no conflicts of interest with respect to the authorship and/or publication of this article.

Financial Disclosure

The authors received no financial support for the research and/or authorship of this article.

References

  1. Alberti KGMM, Zimmet P, Shaw J, IDF Epidemiology Task Force Consensus Group. The metabolic syndrome--a new worldwide definition. Lancet 2005;366:1059–62.
  2. Khunti K, Davies M. Metabolic syndrome. BMJ 2005;331:1153-4.
  3. Tariq H, Nayudu S, Akella S, Glandt M, Chilimuri S. Non-Alcoholic Fatty Pancreatic Disease: A Review of Literature. Gastroenterology Res 2016;9:87-91.
  4. Aksoy D, Solmaz V, Taşkıran D, Erbaş O. The association between seizure predisposition and inflammation in a rat model of fatty liver disease. Neurol Sci 2014;35:1441-6.
  5. Erbaş O, Altuntaş I, Çağlar O, Özyilmaz E, Sari E, Üzümcü I, et al. Experimental Model of Cardiotoxicity. IntechOpen; 2022.
  6. Gomez G, Beason-Held LL, Bilgel M, An Y, Wong DF, Studenski S, et al. Metabolic Syndrome and Amyloid Accumulation in the Aging Brain. J Alzheimers Dis 2018;65:629-39.
  7. Mendrick DL, Diehl AM, Topor LS, Dietert RR, Will Y, La Merrill MA, et al. Metabolic Syndrome and Associated Diseases: From the Bench to the Clinic. Toxicol Sci 2018;162:36-42.
  8. Moreira FP, Jansen K, Cardoso T de A, Mondin TC, Magalhães PV, Kapczinski F, et al. Metabolic syndrome and psychiatric disorders: a population-based study. Braz J Psychiatry 2019;41:38-43.
  9. Penninx BWJH, Lange SMM. Metabolic syndrome in psychiatric patients: overview, mechanisms, and implications. Dialogues Clin Neurosci 2018;20:63-73.
  10. Erbaş O, Solmaz V, Taşkıran D. Granulocyte colony-stimulating factor provides protection against cardiovascular autonomic neuropathy in streptozotocin-induced diabetes in rats. Diabetes Res Clin Pract 2015;107:377-83.
  11. Savcı D, Karadeniz S, Erbaş O. Neuregulin 1 and Its Roles in Schizophrenia: A Systematic Review. JEBMS 2021;2:406-13.
  12. Agaba DC, Migisha R, Namayanja R, Katamba G, Lugobe HM, Aheisibwe H, et al. Prevalence and Associated Factors of Metabolic Syndrome among Patients with Severe Mental Illness Attending a Tertiary Hospital in Southwest Uganda. Biomed Res Int 2019;2019:1096201.
  13. Ho CSH, Zhang MWB, Mak A, Ho RCM. Metabolic syndrome in psychiatry: advances in understanding and management. Advances in Psychiatric Treatment 2014;20:101-12.
  14. Aguilar M, Bhuket T, Torres S, Liu B, Wong RJ. Prevalence of the metabolic syndrome in the United States, 2003-2012. JAMA 2015;313:1973-4.
  15. Márquez-Sandoval F, Macedo-Ojeda G, Viramontes-Hörner D, Fernández Ballart JD, Salas Salvadó J, Vizmanos B. The prevalence of metabolic syndrome in Latin America: a systematic review. Public Health Nutr 2011;14:1702-13.
  16. de Carvalho Vidigal F, Bressan J, Babio N, Salas-Salvadó J. Prevalence of metabolic syndrome in Brazilian adults: a systematic review. BMC Public Health 2013;13:1198.
  17. Montgomery MK, Turner N. Mitochondrial dysfunction and insulin resistance: an update. Endocr Connect 2015;4:R1-15.
  18. Park KS, Chan JC, Chuang L-M, Suzuki S, Araki E, Nanjo K, et al. A mitochondrial DNA variant at position 16189 is associated with type 2 diabetes mellitus in Asians. Diabetologia 2008;51:602-8.
  19. Henao-Mejia J, Elinav E, Jin C, Hao L, Mehal WZ, Strowig T, et al. Inflammasome-mediated dysbiosis regulates progression of NAFLD and obesity. Nature 2012;482:179-85.
  20. Lumeng CN. Innate immune activation in obesity. Mol Aspects Med 2013;34:12-29.
  21. Malagón MM, Díaz-Ruiz A, Guzmán-Ruiz R, Jiménez-Gómez Y, Moreno NR, García-Navarro S, et al. Adipobiology for novel therapeutic approaches in metabolic syndrome. Curr Vasc Pharmacol 2013;11:954-67.
  22. Tilg H, Kaser A. Gut microbiome, obesity, and metabolic dysfunction. J Clin Invest 2011;121:2126-32.
  23. Tornatore L, Thotakura AK, Bennett J, Moretti M, Franzoso G. The nuclear factor kappa B signaling pathway: integrating metabolism with inflammation. Trends Cell Biol 2012;22:557-66.
  24. Brown JM, Hazen SL. The gut microbial endocrine organ: bacterially derived signals driving cardiometabolic diseases. Annu Rev Med 2015;66:343-59.
  25. Korem T, Zeevi D, Suez J, Weinberger A, Avnit-Sagi T, Pompan-Lotan M, et al. Growth dynamics of gut microbiota in health and disease inferred from single metagenomic samples. Science 2015;349:1101-6.
  26. Bennett BJ, de Aguiar Vallim TQ, Wang Z, Shih DM, Meng Y, Gregory J, et al. Trimethylamine-N-oxide, a metabolite associated with atherosclerosis, exhibits complex genetic and dietary regulation. Cell Metab 2013;17:49-60.
  27. Koeth RA, Wang Z, Levison BS, Buffa JA, Org E, Sheehy BT, et al. Intestinal microbiota metabolism of L-carnitine, a nutrient in red meat, promotes atherosclerosis. Nat Med 2013;19:576-85.
  28. Cohn BA, Wolff MS, Cirillo PM, Sholtz RI. DDT and breast cancer in young women: new data on the significance of age at exposure. Environ Health Perspect 2007;115:1406-14.
  29. Narayan KMV, Boyle JP, Thompson TJ, Sorensen SW, Williamson DF. Lifetime risk for diabetes mellitus in the United States. JAMA 2003;290:1884-90.
  30. Cano-Sancho G, Salmon AG, La Merrill MA. Association between Exposure to p,p’-DDT and Its Metabolite p,p’-DDE with Obesity: Integrated Systematic Review and Meta-Analysis. Environ Health Perspect 2017;125:096002.
  31. Anuurad E, Semrad A, Berglund L. Human immunodeficiency virus and highly active antiretroviral therapy-associated metabolic disorders and risk factors for cardiovascular disease. Metab Syndr Relat Disord 2009;7:401-10.
  32. Fromenty B. Drug-induced liver injury in obesity. J Hepatol 2013;58:824-6.
  33. Alberti KG, Zimmet PZ. Definition, diagnosis and classification of diabetes mellitus and its complications. Part 1: diagnosis and classification of diabetes mellitus provisional report of a WHO consultation. Diabet Med 1998;15:539-53.
  34. Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults. 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 (Adult Treatment Panel III). JAMA 2001;285:2486-97.
  35. Carr DB, Utzschneider KM, Hull RL, Kodama K, Retzlaff BM, Brunzell JD, et al. Intra-abdominal fat is a major determinant of the National Cholesterol Education Program Adult Treatment Panel III criteria for the metabolic syndrome. Diabetes 2004;53:2087-94.
  36. McKenney RL, Short DK. Tipping the balance: the pathophysiology of obesity and type 2 diabetes mellitus. Surg Clin North Am 2011;91:1139-48.
  37. Tsukiyama H, Nagai Y, Matsubara F, Shimizu H, Iwamoto T, Yamanouchi E, et al. Proposed cut-off values of the waist circumference for metabolic syndrome based on visceral fat volume in a Japanese population. J Diabetes Investig 2016;7:587-93.
  38. Dutra ES, de Carvalho KM, Miyazaki E, Hamann EM-, Ito MK. Metabolic syndrome in central Brazil: prevalence and correlates in the adult population. Diabetol Metab Syndr 2012;4:20.
  39. Hildrum B, Mykletun A, Hole T, Midthjell K, Dahl AA. Age-specific prevalence of the metabolic syndrome defined by the International Diabetes Federation and the National Cholesterol Education Program: the Norwegian HUNT 2 study. BMC Public Health 2007;7:220.
  40. Marquezine GF, Oliveira CM, Pereira AC, Krieger JE, Mill JG. Metabolic syndrome determinants in an urban population from Brazil: social class and gender-specific interaction. Int J Cardiol 2008;129:259-65.
  41. Anuurad E, Shiwaku K, Nogi A, Kitajima K, Enkhmaa B, Shimono K, et al. The new BMI criteria for asians by the regional office for the western pacific region of WHO are suitable for screening of overweight to prevent metabolic syndrome in elder Japanese workers. J Occup Health 2003;45:335-43.
  42. Deurenberg-Yap M, Schmidt G, van Staveren WA, Deurenberg P. The paradox of low body mass index and high body fat percentage among Chinese, Malays and Indians in Singapore. Int J Obes Relat Metab Disord 2000;24:1011-7.
  43. Liu M, He Y, Jiang B, Wu L, Wang J, Yang S, et al. Association between reproductive variables and metabolic syndrome in chinese community elderly women. Arch Gerontol Geriatr 2016;63:78-84.
  44. Malayala SV, Raza A. Health behavior and perceptions among African American women with metabolic syndrome. J Community Hosp Intern Med Perspect 2016;6:30559.
  45. Pickhardt PJ, Jee Y, O’Connor SD, del Rio AM. Visceral adiposity and hepatic steatosis at abdominal CT: association with the metabolic syndrome. AJR Am J Roentgenol 2012;198:1100-7.
  46. Rønn PF, Andersen GS, Lauritzen T, Christensen DL, Aadahl M, Carstensen B, et al. Abdominal visceral and subcutaneous adipose tissue and associations with cardiometabolic risk in Inuit, Africans and Europeans: a cross-sectional study. BMJ Open 2020;10:e038071.
  47. Stolk RP, Wink O, Zelissen PM, Meijer R, van Gils AP, Grobbee DE. Validity and reproducibility of ultrasonography for the measurement of intra-abdominal adipose tissue. Int J Obes Relat Metab Disord 2001;25:1346-51.
  48. Britton KA, Massaro JM, Murabito JM, Kreger BE, Hoffmann U, Fox CS. Body fat distribution, incident cardiovascular disease, cancer, and all-cause mortality. J Am Coll Cardiol 2013;62:921-5.
  49. Bertoli S, Leone A, Vignati L, Spadafranca A, Bedogni G, Vanzulli A, et al. Metabolic correlates of subcutaneous and visceral abdominal fat measured by ultrasonography: a comparison with waist circumference. Nutr J 2016;15:2.
  50. Vlachos IS, Hatziioannou A, Perelas A, Perrea DN. Sonographic assessment of regional adiposity. AJR Am J Roentgenol 2007;189:1545-53.
  51. Wajchenberg BL. Subcutaneous and visceral adipose tissue: their relation to the metabolic syndrome. Endocr Rev 2000;21:697-738.
  52. Lin E, Alessio A. What are the basic concepts of temporal, contrast, and spatial resolution in cardiac CT? J Cardiovasc Comput Tomogr 2009;3:403-8.
  53. Ryo M, Kishida K, Nakamura T, Yoshizumi T, Funahashi T, Shimomura I. Clinical significance of visceral adiposity assessed by computed tomography: A Japanese perspective. World J Radiol 2014;6:409-16.
  54. Fox CS, Massaro JM, Hoffmann U, Pou KM, Maurovich-Horvat P, Liu C-Y, et al. Abdominal visceral and subcutaneous adipose tissue compartments: association with metabolic risk factors in the Framingham Heart Study. Circulation 2007;116:39-48.
  55. Eastwood SV, Tillin T, Wright A, Heasman J, Willis J, Godsland IF, et al. Estimation of CT-derived abdominal visceral and subcutaneous adipose tissue depots from anthropometry in Europeans, South Asians and African Caribbeans. PLoS One 2013;8:e75085.
  56. Borkan GA, Gerzof SG, Robbins AH, Hults DE, Silbert CK, Silbert JE. Assessment of abdominal fat content by computed tomography. Am J Clin Nutr 1982;36:172–7.
  57. Penninx BWJH, Milaneschi Y, Lamers F, Vogelzangs N. Understanding the somatic consequences of depression: biological mechanisms and the role of depression symptom profile. BMC Med 2013;11:129.
  58. Batelaan NM, Seldenrijk A, Bot M, van Balkom AJLM, Penninx BWJH. Anxiety and new onset of cardiovascular disease: critical review and meta-analysis. Br J Psychiatry 2016;208:223-31.
  59. Mitchell AJ, Vancampfort D, Sweers K, van Winkel R, Yu W, De Hert M. Prevalence of metabolic syndrome and metabolic abnormalities in schizophrenia and related disorders--a systematic review and meta-analysis. Schizophr Bull 2013;39:306-18.
  60. McIntyre RS, Soczynska JK, Beyer JL, Woldeyohannes HO, Law CWY, Miranda A, et al. Medical comorbidity in bipolar disorder: re-prioritizing unmet needs. Curr Opin Psychiatry 2007;20:406-16.
  61. Crichton GE, Elias MF, Robbins MA. Association between depressive symptoms, use of antidepressant medication and the metabolic syndrome: the Maine-Syracuse Study. BMC Public Health 2016;16:502.
  62. Moreira FP, Jansen K, Mondin TC, Cardoso T de A, Magalhães PV da S, Kapczinski F, et al. Biological rhythms, metabolic syndrome and current depressive episode in a community sample. Psychoneuroendocrinology 2016;72:34-9.
  63. Chesney E, Goodwin GM, Fazel S. Risks of all-cause and suicide mortality in mental disorders: a meta-review. World Psychiatry 2014;13:153-60.
  64. Asken MJ, Grossman D, Christensen LW. American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders. Arlington, VA: American Psychiatric Pub-lishing, 2013. Archibald, Herbert C., and Read D. Tuddenham.“Persistent Stress Reac-tion after Combat: A 20-Year Follow-Up.” Archives of General Psy. Therapy 2007;45:2317-25.
  65. Goldbacher EM, Bromberger J, Matthews KA. Lifetime history of major depression predicts the development of the metabolic syndrome in middle-aged women. Psychosom Med 2009;71:266-72.
  66. Pulkki-Råback L, Elovainio M, Kivimäki M, Mattsson N, Raitakari OT, Puttonen S, et al. Depressive Symptoms and the Metabolic Syndrome in Childhood and Adulthood. Health Psychol 2009;28:108-16.
  67. Räikkönen K, Matthews KA, Kuller LH. The relationship between psychological risk attributes and the metabolic syndrome in healthy women: antecedent or consequence? Metabolism 2002;51:1573-7.
  68. Roriz-Cruz M, Rosset I, Wada T, Sakagami T, Ishine M, Roriz-Filho JS, et al. Stroke-independent association between metabolic syndrome and functional dependence, depression, and low quality of life in elderly community-dwelling Brazilian people. J Am Geriatr Soc 2007;55:374-82.
  69. Vanhala M, Jokelainen J, Keinänen-Kiukaanniemi S, Kumpusalo E, Koponen H. Depressive symptoms predispose females to metabolic syndrome: a 7-year follow-up study. Acta Psychiatr Scand 2009;119:137-42.
  70. Pan A, Keum N, Okereke OI, Sun Q, Kivimaki M, Rubin RR, et al. Bidirectional association between depression and metabolic syndrome: a systematic review and meta-analysis of epidemiological studies. Diabetes Care 2012;35:1171-80.
  71. Marijnissen RM, Vogelzangs N, Mulder ME, van den Brink RHS, Comijs HC, Oude Voshaar RC. Metabolic dysregulation and late-life depression: a prospective study. Psychol Med 2017;47:1041-52.
  72. Vogelzangs N, Beekman ATF, Boelhouwer IG, Bandinelli S, Milaneschi Y, Ferrucci L, et al. Metabolic depression: a chronic depressive subtype? Findings from the InCHIANTI study of older persons. J Clin Psychiatry 2011;72:598-604.
  73. Soczynska JK, Kennedy SH, Woldeyohannes HO, Liauw SS, Alsuwaidan M, Yim CY, et al. Mood disorders and obesity: understanding inflammation as a pathophysiological nexus. Neuromolecular Med 2011;13:93-116.
  74. Liu CS, Carvalho AF, McIntyre RS. Towards a “metabolic” subtype of major depressive disorder: shared pathophysiological mechanisms may contribute to cognitive dysfunction. CNS Neurol Disord Drug Targets 2014;13:1693-707.
  75. Gale CK, Millichamp J. Generalised anxiety disorder. BMJ Clin Evid 2011;2011:1002.
  76. Strine TW, Mokdad AH, Dube SR, Balluz LS, Gonzalez O, Berry JT, et al. The association of depression and anxiety with obesity and unhealthy behaviors among community-dwelling US adults. Gen Hosp Psychiatry 2008;30:127-37.
  77. Therrien F, Drapeau V, Lupien SJ, Beaulieu S, Doré J, Tremblay A, et al. Awakening cortisol response in relation to psychosocial profiles and eating behaviors. Physiol Behav 2008;93:282-8.
  78. Ijaz S, Bolea B, Davies S, Savović J, Richards A, Sullivan S, et al. Antipsychotic polypharmacy and metabolic syndrome in schizophrenia: a review of systematic reviews. BMC Psychiatry 2018;18:275.
  79. Erbaş O, Akseki HS, Aktuğ H, Taşkıran D. Low-grade chronic inflammation induces behavioral stereotypy in rats. Metab Brain Dis 2015;30:739-46.
  80. DE Hert M, Schreurs V, Vancampfort D, VAN Winkel R. Metabolic syndrome in people with schizophrenia: a review. World Psychiatry 2009;8:15-22.
  81. Vancampfort D, Wampers M, Mitchell AJ, Correll CU, De Herdt A, Probst M, et al. A meta-analysis of cardiometabolic abnormalities in drug naïve, first-episode and multi-episode patients with schizophrenia versus general population controls. World Psychiatry 2013;12:240-50.
  82. Sugawara N, Yasui-Furukori N, Yamazaki M, Shimoda K, Mori T, Sugai T, et al. Predictive Utility of Body Mass Index for Metabolic Syndrome Among Patients with Schizophrenia in Japan. Neuropsychiatr Dis Treat 2020;16:2229-36.
  83. Pillinger T, D’Ambrosio E, McCutcheon R, Howes OD. Is psychosis a multisystem disorder? A meta-review of central nervous system, immune, cardiometabolic, and endocrine alterations in first-episode psychosis and perspective on potential models. Mol Psychiatry 2019;24:776-94.
  84. Alexander CM, Landsman PB, Teutsch SM, Haffner SM, Third National Health and Nutrition Examination Survey (NHANES III), National Cholesterol Education Program (NCEP). NCEP-defined metabolic syndrome, diabetes, and prevalence of coronary heart disease among NHANES III participants age 50 years and older. Diabetes 2003;52:1210-4.
  85. Grundy SM, Cleeman JI, Daniels SR, Donato KA, Eckel RH, Franklin BA, et al. Diagnosis and management of the metabolic syndrome: an American Heart Association/ National Heart, Lung, and Blood Institute Scientific Statement. Circulation 2005;112:2735-52.
  86. Franklin BA, Kahn JK, Gordon NF, Bonow RO. A cardioprotective “polypill”? Independent and additive benefits of lifestyle modification. Am J Cardiol 2004;94:162-6.
  87. Thompson PD, Buchner D, Pina IL, Balady GJ, Williams MA, Marcus BH, et al. Exercise and physical activity in the prevention and treatment of atherosclerotic cardiovascular disease: a statement from the Council on Clinical Cardiology (Subcommittee on Exercise, Rehabilitation, and Prevention) and the Council on Nutrition, Physical Activity, and Metabolism (Subcommittee on Physical Activity). Circulation 2003;107:3109-16.
  88. Chobanian AV, Bakris GL, Black HR, Cushman WC, Green LA, Izzo JL, et al. The Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure: the JNC 7 report. JAMA 2003;289:2560-72.
  89. Foster GD, Wyatt HR, Hill JO, McGuckin BG, Brill C, Mohammed BS, et al. A randomized trial of a low-carbohydrate diet for obesity. N Engl J Med 2003;348:2082-90.
  90. Krauss RM, Eckel RH, Howard B, Appel LJ, Daniels SR, Deckelbaum RJ, et al. AHA Dietary Guidelines: revision 2000: A statement for healthcare professionals from the Nutrition Committee of the American Heart Association. Circulation 2000;102:2284-99.
  91. Kris-Etherton PM, Harris WS, Appel LJ, American Heart Association. Nutrition Committee. Fish consumption, fish oil, omega-3 fatty acids, and cardiovascular disease. Circulation 2002;106:2747-57.
  92. Jones PH, Davidson MH. Reporting rate of rhabdomyolysis with fenofibrate + statin versus gemfibrozil + any statin. Am J Cardiol 2005;95:120-2.
  93. Ball SG, White WB. Debate: angiotensin-converting enzyme inhibitors versus angiotensin II receptor blockers--a gap in evidence-based medicine. Am J Cardiol 2003;91:15G-21G.
  94. Barnett AH, Bain SC, Bouter P, Karlberg B, Madsbad S, Jervell J, et al. Angiotensin-receptor blockade versus converting-enzyme inhibition in type 2 diabetes and nephropathy. N Engl J Med 2004;351:1952-61.
  95. Buchanan TA, Xiang AH, Peters RK, Kjos SL, Marroquin A, Goico J, et al. Preservation of pancreatic betacell function and prevention of type 2 diabetes by pharmacological treatment of insulin resistance in high-risk hispanic women. Diabetes 2002;51:2796-803.
  96. Chiasson J-L, Josse RG, Gomis R, Hanefeld M, Karasik A, Laakso M, et al. Acarbose for prevention of type 2 diabetes mellitus: the STOP-NIDDM randomised trial. Lancet 2002;359:2072-7.
  97. Forslund K, Hildebrand F, Nielsen T, Falony G, Le Chatelier E, Sunagawa S, et al. Disentangling type 2 diabetes and metformin treatment signatures in the human gut microbiota. Nature 2015;528:262-6.
  98. Knowler WC, Barrett-Connor E, Fowler SE, Hamman RF, Lachin JM, Walker EA, et al. Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. N Engl J Med 2002;346:393-403.
  99. Siafis S, Tzachanis D, Samara M, Papazisis G. Antipsychotic Drugs: From Receptor-binding Profiles to Metabolic Side Effects. Curr Neuropharmacol 2018;16:1210-23.
  100. Grigg J, Worsley R, Thew C, Gurvich C, Thomas N, Kulkarni J. Antipsychotic-induced hyperprolactinemia: synthesis of world-wide guidelines and integrated recommendations for assessment, management and future research. Psychopharmacology (Berl) 2017;234:3279-97.
  101. Besnard I, Auclair V, Callery G, Gabriel-Bordenave C, Roberge C. [Antipsychotic-drug-induced hyperprolactinemia: physiopathology, clinical features and guidance]. Encephale 2014;40:86-94.
  102. Pérez-Iglesias R, Martínez-García O, Pardo-Garcia G, Amado JA, Garcia-Unzueta MT, Tabares-Seisdedos R, et al. Course of weight gain and metabolic abnormalities in first treated episode of psychosis: the first year is a critical period for development of cardiovascular risk factors. Int J Neuropsychopharmacol 2014;17:41-51.
  103. DE Hert M, Correll CU, Bobes J, Cetkovich-Bakmas M, Cohen D, Asai I, et al. Physical illness in patients with severe mental disorders. I. Prevalence, impact of medications and disparities in health care. World Psychiatry 2011;10:52-77.