Hanife Kocakaya1, Sedat Batmaz2, Osman Demir3, Emrah Songur4, Zekiye Celikbas1
1 Tokat Dr. Cevdet Aykan Mental Health Hospital, Tokat, Turkey.
2 Gaziosmanpasa University School of Medicine, Department of Psychiatry, Tokat, Turkey.
3 Gaziosmanpasa University School of Medicine, Department of Statistics, Tokat, Turkey.
4 Ankara Kecioren Training and Research Hospital, Ankara, Turkey.
Received: 03/20/2018 – Accepted: 10/21/2018
Address for correspondence: Hanife Kocakaya. Tokat Dr. Cevdet Aykan Menthal Health Hospital – Adult Psychiatry Tokat Gop Bulvar Tokat 60200, Turkey. Telephone: +905063435242. E-mail: [email protected]
Background: The metabolic syndrome is a growing global public health problem and highly prevalent in patiens with bipolar disorder. There are a few studies about relationship between metabolic syndrome and bipolar disorder subtypes. Objective: The aim of this study was to investigate the prevalence of metabolic syndrome (MS) and its individual components in subjects with bipolar I (BD I) and bipolar II (BD II) disorder compared with non-psychiatric controls, and to determine the variables affecting MS. Methods: A total of 210 individuals (mean age 42.5 ± 11.87, 58.1% female) of whom 70 had BD I, 70 BD II, and 70 controls, were included in this study. MS was diagnosed according to the National Cholesterol Education Program Adult Treatment Panel III (NCEP ATP III), the adapted ATP III (ATP III-A) and the International Diabetes Federation (IDF) criteria. Results: Participants with BD I had a significantly higher prevalence of MS when compared to individuals BD II and non-psychiatric controls according to the NCEP-ATP III, ATP III-A, and IDF criteria (ps < 0.01). In individuals with MS, increased waist circumference was the most common abnormality. Logistic regression analysis revealed that the presence of physical illness, age and number of cigarettes smoked significantly predicted the presence of MS. Discussion: This study showed that MS was more prevalent among BD I individuals compared to BD II and controls, and highlighted the importance of regular screening for MS in individuals with BD.
Kocakaya H et al. / Arch Clin Psychiatry. 2018;45(6):143-9
Keywords: Bipolar disorder I and II, metabolic syndrome, prevalence.
Bipolar disorder (BD) is a chronic disorder that usually starts in adolescence and early adulthood, and is characterized by significant changes in the affective state and by impaired social and/or neuropsychological development1. According to the epidemiological field study in the United States of America (USA), the lifetime prevalence rate is 0.8% for bipolar I disorder (BD I), and 0.5% for bipolar II disorder (BD II)2. The World Health Organization (WHO) estimates that BD is currently the sixth leading cause of disability worldwide among adults. Depending on unhealthy lifestyle models such as high calorie diet, cholesterol intake, smoking and physical inactivity, 38% of individuals with BD suffer from cardiovascular disease (CVD). Life expectancy compared to the general population is 13.6 years shorter for male patients, and 12.1 years shorter for female patients3. In addition, the long-term use of some antipsychotics (AP) or mood stabilizers for treatment may be associated with an increased risk of developing obesity, dyslipidemia, diabetes mellitus, and metabolic syndrome (MS)4.
MS leads to an increase in central obesity, fasting blood glucose (FBG), blood pressure (BP), and arteriosclerosis associated with deteriorating lipid profiles. Insulin resistance (IR) plays a role in its pathogenesis. It is becoming increasingly common all over the world. The risk of MS increases with age5,6. The prevalence of MS varies between 6% and 70%7. According to the results of the Metabolic Syndrome Research (METSAR) conducted across Turkey, the prevalence of MS was 35% among adults 20 years of age and over8.
In studies conducted in different countries, it has been reported that the prevalence of MS in patients with BD varies between 22.4% and 67%9-11. Although there are not many studies undertaken on MS in Turkey, the prevalence of MS ranges from 24.7% to 36.7%12,13. It has been shown that unhealthy lifestyle habits (smoking, alcohol use, malnutrition, and lack of exercise) are frequently present in individuals with BD, and that these variables increase the risk for the development of MS. The relationship between BD and MS remained unchanged even after adjustments for age, race, smoking, physical inactivity, carbohydrate intake, and alcohol use4. Obesity is frequently associated with MS, and it is common among individuals with BD. In these patients, obesity has been associated with bad eating habits, lack of exercise, and the use of some psychotropic drugs leading to weight gain14. In obese people, the hypothalamic pituitary adrenal (HPA) axis may be disrupted due to increased leptin and other hormones released from the adipose tissue, which affects normal mood regulation, and consequently leads to significant and/or rapid mood fluctuations such as depression, mania, or the mixture of both mood states15. In individuals with BD, the presence of MS has also been found to be associated with a decrease in treatment response, a more adverse course of illness, increased frequency of manic and depressive episodes, and increased suicide tendency16.
Therefore, in the current study, our first aim was to investigate the prevalence of MS in individuals with BD I, BD II, and non-psychiatric controls, and to compare patients with BD with the control subjects in terms of their demographics and clinical variables. The second aim of the study was to determine which of the individual MS components were associated with BD. We also aimed to identify the clinical correlates of MS in BD.
This study was carried out between 01.03.2016 and 01.07.2016 in the Department of Psychiatry at Tokat Gaziosmanpasa University Faculty of Medicine (Tokat, Turkey). A total of 210 subjects (age range: 18-65 years) consisting of 140 euthymic patients diagnosed with either BD I or BD II according to the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5)17 and 70 non-psychiatric control subjects were enrolled in the study. The control group consisted of healthy volunteers who did not have any psychiatric diagnoses, and who presented to the outpatient clinic of the physical therapy department. Participants who suffered from comorbid alcohol- and drug-related disorders (except for smoking) were not included in the study (because of the low number of alcohol and substance users among the participants with BD during their remission period), and participants who had mental retardation (MR) and/or pervasive developmental disorders were excluded from the study.
Instruments of assessment
A demographic and clinical data form, which was prepared to assess the demographic and clinical features of the participants, was completed by the interviewer. Additionally, the Young Mania Rating Scale (YMRS)18,19, the Bipolar Depression Rating Scale (BDRS)20,21, the Beck Depression Inventory (BDI)22,23 were used to assess the severity of the mood episodes of the participants. To calculate the amount of cigarettes smoked, we asked the participants how many packs of cigarettes they smoked daily and how many years they were smoking and the number of packs/year was recorded, the International Physical Activity Questionnaire Short Form (IPAQ-SF)24 was used to assess the level of their physical activity. The Turkish versions of all these scales were used in the study25.
Face to face interviews were held with all of the participants. The questionnaires and scales used in the study were filled out by the interviewer, and the participants during these interviews. These questionnaires and scales were later rated by the interviewer. The groups (BD I, BD II, BD I+BD II, total participants) were divided into two groups: a) current cigarette smokers (yes = 1) and b) non-smokers (no = 0). Firstly the relationship between cigarettes smoking and the duration of illness was assessed. Secondly it was assessed whether there is a relationship between the amount of cigarettes and the duration of illness. Body weight, height, and waist circumference (WC) were measured to investigate the diagnostic criteria for MS in the participants and healthy controls. The participants also underwent blood tests to identify MS parameters. Biochemical findings [FBG, high density lipoprotein (HDL), low density lipoprotein (LDL), triglyceride (TG)], and BP measurements, which are examined routinely for MS, were recorded for all three groups. MS was diagnosed according to the criteria of the National Cholesterol Education Program Adult Treatment Panel III (NCEP ATP III), the adapted ATP III (ATP III-A)26,27, and the International Diabetes Federation (IDF)28.
Independent samples’ t-test, Pearson’s chi-square and one-way analysis of variance (ANOVA) were used to determine whether there was a statistically significant difference between the means of the variables in the different groups. For group comparisions involving ANOVA, post-hoc Tukey analyses were performed to identify where the group differences were. Binary logistic regression analyses were used to assess the proposed relationship between the demographic and clinical variables and the presence of MS. A value of p < 0.05 was considered statistically significant. All statistical analyses were performed using a statistical software package (IBM SPSS Statistics 19, SPSS inc., an IBM Co., Somers, NY).
The study was approved by the Clinical Trials Ethics Committee of Tokat Gaziosmanpasa University Faculty of Medicine. The participants were also informed about the study. Then, written informed consent was obtained from the participants who voluntarily agreed to participate.
Group comparisons according to demographic and clinical characteristics
A total of 210 participants (18-65 years) including 70 participants with BD I, 70 participants with BD II, and 70 non-psychiatric controls were enrolled in the study. The mean age was 43.51 (±11.75) years for the BD I group, 43.17 (±12.97) years for the BD II group, and 40.83 (±10.78) years for the control group. There was a significant difference among non-psychiatric controls and the other groups in terms of age (p < 0.001). The number of female participants in the BD II group was higher and there was a significant difference compared to the other groups (p = 0.003). Non-psychiatric controls were more successful in terms of work status than participants with BD (p < 0.001). The demographic characteristics of the participants are presented in Table 1.
The groups were compared with each other in terms of their clinical characteristics. In the BD I group YMRS score (± standard deviation (SD) was 0.26 (±0.97), BDRS score (±SD) was 3.1 (±3.05), BDI score (±SD) was 4.9 (±4.7), in the BD II group YMRS score (±SD) was 0.04 (± 0.36), BDRS score (±SD) was 3.5 (±3.03), BDI score (±SD) was 6.66 (±4.78), in the control group BDI score (±SD) was 4.9 (±4.7), and there was no significant difference between the groups in terms of these scale scores. The mean number of depressive episodes [± standard deviation (SD)], and the mean total number of mood episodes (±SD) were 4.94 (±2.48), and 8.66 (±3.69), respectively. In the BD II group, the mean number of depressive episodes (±SD), and the mean total number of mood episodes (±SD) were 5.49 (±2.67), and 8.67 (±4.27), respectively. There was a significant difference between the BD I group and the BD II group in terms of the mean number of depressive episodes, and mean total number of mood episodes (both p values 0.024). In the BD I group, the mean number of manic episodes (± SD), and the mean hypomanic episodes (± SD) were 3.0 (± 1.77), and 0.78 (± 1.48), in the BD II group, the mean hypomanic episodes 3.21 (±2.19 SD), respectively. The groups did not differ from each other on the mean number of manic/hypomanic episodes (p = 0.804). The cigarette smokers were twenty-one (30.%) participants for the BD I group, nineteen (27.1%) participants for the BD II group, and fourteen (20.%) participants for the control group. According to the results of statistical analysis, there was not found a significant relationship between smoking and duration of illness between groups (BD I (χ2 = 0.258, df = 66, p = 0.79), BD II (χ2 = 0.073, df = 68, p = 0.472), BD I+BD II (χ2 = 0.320, df = 136, p = 0.50), total participants (χ2 = 0.001, df = 208, p = 0.30 ). The mean amount of cigarettes (±SD) were 5.75 (±9.85) packs/year in the BD I group, 3.94 (±8.23) packs/year for the BD II group, and 3.53 (±8.05) packs/year for the control group, respectively. Additionaly, there was not a significant correlation between the amount of cigarettes and the duration of illness for BD I (correlation coefficient) r = 0.202, p = 0.094) and BD II (r = 0.151, p = 0.212). Mood stabilizers and combination therapies were significantly more frequently offered in the BD I group. There was a significant difference in the use of mood stabilizers and combination therapy (AP + mood stabilizers) between the BD I group and the BD II group (p = 0.002, p < 001).
Prevalence of metabolic syndrome and the presence of metabolic syndrome components according to the groups
In participants with BD who met the diagnostic criteria for MS, the prevalence of the individual diagnostic components was as follows: 93.4% for abnormal WC, 82.4% for low HDL, 74.7% for hypertriglyceridemia, 50.5% for high systolic BP, 48.4% for high FBG, 29.7% for high diastolic BP.
There was a statistically significant difference between the BD I group, and the BD II and control groups in terms of body mass index (BMI), WC, diastolic BP, triglycerides, and FGB (all p values < 0.001). On all these parameters, the BD I group had higher levels than the other two groups. On the same parameteres, there were no statistically significant differences between the BD II group and the non-psychiatric controls. Systolic BP was statistically significantly different between the BD I group and the non-psychiatric controls, and the BD I group had higher levels. There was a statistically significant difference in the HDL-cholesterol levels between the BD II group, and the non-psychiatric controls and the BD I group (p < 0.001), and the BD II group had higher levels than the other groups.
There was a statistically significant difference between the groups in terms of the prevalence of metabolic syndrome according to different diagnostic criteria (all p values < 0.01). According to the diagnostic criteria of the NCEP-ATP-III, the ATP-III-A, and the IDF, the prevalence of MS was higher in the BD I group than the BD II group and the non-psychiatric controls. The prevalence of MS did not differ from each other in the BD II group and the control group. Mean scores of the MS components and the prevalence of MS according to the groups are presented in Table 2.
Factors associated with metabolic syndrome
The effect of the independent variables sex (coded as female = 0/male = 2), age, duration of psychiatric illness, presence of comorbid physical illness (coded as yes = 1/no = 2), total number of mood episodes, total number of hospitalizations, number of cigarette smoking (packs/year), total BDRS scores, and exercise status (MET (min/week (1 MET = 3,5 mL/kg/dk) on the presence of MS according to the IDF criteria was assessed by a binary logistic regression model. Because it was the most recent among other MS diagnostic criteria. There was a significant relationship between the presence of MS and the presence of comorbid physical illness, age, and the number of cigarettes smoked (p = 0.001, p = 0.037, p = 0.044, respectively).
MS has also been known as Syndrome X, insulin resistance syndrome, Reaven syndrome, and the metabolic cardiovasculer syndrome29. MS was associated with a poor course of illness and prognosis in individuals with BD, suggesting that MS still is an important issue in clinical psychiatric practice30,31.
In the present study, participants were assessed for MS according to the NCEP-ATP III, ATP III-A, and IDF criteria. According to the NCEP-ATP III criteria, the prevalence of MS was 57.1% for the BD I group, 30% for the BD II group, 35.7% for the non-psychiatric controls, according to the ATP III-A criteria 57.1% for the BD I group, 34.3% for the BD II group, 35.7% for the non-psychiatric controls and according to the IDF criteria 58.6% for the BD I group, 34.3% for the BD II group, 37.1% for the non-psychiatric controls. According results of previous MS prevalence in participants with BD studies, MS prevalence ranged from 17% to 53%27,32-34. MS prevalence has been reported to be 18-26% in European countries10,35,36, and 30-49% in the USA4,36-38. The lower prevalence rate in European countries has been attributed to differing eating habits, ethnicity, and lifestyle4. The studies we use in relation to MS prevalence are presented in Table 4.
Focusing specifically on studies of MS in BD, in a study conducted in Taiwan where the participants with BD I (n = 15), BD II (n = 16), major depressive disorder (MDD) (n = 141), and anxiety disorders (n = 36) were compared in terms of the prevalence of MS, it was reported that 46.7% BD I, 25% BD II, 22% MDD, and 18.4% anxiety disorder participants suffered from MS34. In another study, which was conducted in New Zealand, the prevalence of MS was reported to be 50% for participants with BD, and 32% for healthy controls16. In a study in which participants with BD II without treatment (valproate acid and fluoxetine were used if needed) were monitored for 12 weeks in terms of their MS parameters, it was reported that only the BMI increased during the observation period. Therefore, the authors concluded that BD II was more moderate in terms of metabolic dysregulation, and that the prevalence of MS in BD II was similar to the general population35. In our study, the prevalence of MS was lower in the BD II group and the non-psychiatric controls than in the BD I group.
Not many studies were conducted in Turkey in this area of research, and in one of these studies, which consisted of 125 participants, the prevalence of MS was reported 32%8. In another study, evaluating the efficacy of agents used for MS treatment in BD, 60 participants were reported to have MS, with a prevalence rate of 36.7%13. We obtained a higher MS prevalence for BD I participants in our study. Previous studies have reported that the use of lithium, valproic acid and atypical antipsychotics (e.g. olanzapine, clozapine) contributed to obesity and MS in the BD group, mainly due to their effects on appetite and glucose and lipid metabolism32,39. The higher prevalence of MS in BD I group in our study may be related to the higher use of AP and mood stabilizers in this group. It also differs from other studies since BD II participants and non-psychiatric controls were also included. Although this finding may have been somewhat affected by the geographic differences, these differences might also indicate that additional factors, including genetic vulnerability and environmental (lifestyle) effects, may have played a role in modifying MS prevalence rates in patients with BD33. At this point, it should be emphasized that abdominal obesity is one of the main causes for the occurence of all the components of MS, because adipose tissue plays an important role in lipid and glucose metabolism, and because it is responsible for the production of various cytokines influencing the development of the syndrome40. In studies evaluating the prevalence of obesity in Turkey, the prevalence was reported 25 % in Trabzon41, 28% in Ankara42 and Kocaeli43, and 29% in Mersin44. The prevalence of obesity in Tokat was higher than these cities, and it was reported 33.6 % for women, and 12.9 % for men45. Therefore, the difference of MS prevalence reported in these studies may be due to the differences in the prevalence of obesity, which is the major component of MS in the general population.
According to the IDF criteria, the prevalence of MS was 58.6% for the BD I group, 43.3% for the BD II group, and 37.1% for the non-psychiatric controls. In a study that investigated the prevalence of MS with different diagnostic criteria in participants with BD, it was determined that the prevalence of MS was 25.3% according to the ATP-III criteria, and 30% according to the IDF criteria4. Similarly, a higher prevalence of MS was detected with the IDF diagnostic criteria in our study.
The mean values for WC, BMI, systolic BP, diastolic BP, FBG, and TG levels were found to be higher in the BD I group compared to the BD II group and the control group. These values were similar in the BD II group and the control group, there was no significant difference between these two groups. In a recent study that compared participants with BD with participants with MDD and non-psychiatric controls in terms of MS parameters, it was reported that the mean values of WC, triglycerides, systolic BP, diastolic BP, and FBG levels were higher in participants with BD than in participants with MDD and in non-psychiatric controls, and there were also differences between the MDD group and the control subjects, where the levels were higher in the MDD patients than in the non-psychiatric controls46. Our study compared euthymic participants with BD I and BD II with non-psychiatric controls, which differs from other studies. Hence, these results are a novel addition to the literature.
In our study, the mean HDL-cholesterol levels were found to be the highest for the BD II group, and the lowest for the BD I group. These findings were in line with the prevalence of MS in our study. In a study that compared participants with BD with participants with MDD and non-psychiatric controls in terms of their HDL-cholesterol levels, the mean HDL-cholesterol levels were significantly the highest in non-psychiatric controls and was the lowest in BD I. In this study, an inverse relationship was found between the HDL-cholesterol levels and MS prevalence, which was similar to our findings46. Therefore it may be hypothesized that in patients with BD, HDL-cholesterol levels are a predictor for MS frequency, but surely there is a need for further studies to confirm this finding.
When analysing the prevalence of each of the components of MS in our population, we found that increased WC was the most common abnormality (93.4%), followed by abnormalities in low HDL-cholesterol levels (82.4%), increased triglyceride levels (74.7%), increased systolic BP measurements (50.5%), increased FBG (48.4%) levels, and increased diastolic BP measurements (29.7%). The majority of studies undertaken in participants with BD indicate that increased WC was the most9,10,38,47-49, and increased FBG was the least frequently encountered abnormality4,10,38,47,49-52, and our findings are also, to a great extent, in line with these previous reports.
Daily exercise time was found to be lower in the BD I group compared to the BD II group and the control group. In a study that examined the relationship between eating and lifestyle habits and metabolic disorders in participants with BD, unhealthy eating habits and lack of exercise were found to be higher in participants with BD than in healthy participants. In the same study, it was reported that unhealthy eating habits and lack of exercise were associated with weight gain and obesity53.
Additionaly, relationship between participants smoking behavior and duration of illness was examined; there was not found a significant relationship between smoking and duration of illness and there was not a significant correlation between the amount of cigarettes and the duration of illness in our study. However, Medeiros et al., found a significant relationship between smoking and duration of illness, severity of manic symptoms in bipolar subjects54. Our study results were different, this discrepancy can be related to the fact that participants were in clinical remission.
The participants were assessed in terms of variables affecting MS, and there was a significant relationship between MS and the presence of comorbid physical illness, age and number of cigarettes smoked. The diagnostic categories of BD I or BD II were not associated with the presence of MS. In a study involving participants with BD I and BD II in which factors affecting the development of MS were assessed, it was reported that there was a relationship between the development of MS and age, BD I diagnosis, use of AP or mood stabilizers55. Our results are very similar to those reported by Van Winkel et al., in which patients with BD and MS were older than those without36. Aging is commonly accompanied by a loss of muscle mass and by an increase in body fat, especially in the abdomen, and both of these changes can increase IR and finally lead to MS28. Additionally, the meta-analysis by Sun, Liu and Ning56, based on data from prospective studies concluded that active smoking was associated with the development of MS. In another study that examined the relationship between smoking and metabolic disorders, it was reported that smoking was higher in patients diagnosed with MS57. On the other hand, another study reported that there was no relationship between MS and smoking4. The results of our study add to the literature that there might be a significant relationship between MS and smoking.
The findings of the current study suggest that active and early screening of metabolic parameters, including triglycerides, and HDL-C levels, WC measurements, and lifestyle interventions, including dietary changes and physical activity are absolutely essential to managing MS among patients with BD and the general population. The Mediterranean diet (MD) is a dietary pattern first presented by Ancel Keys in the 1960s58, and it is characterized by a high intake of fruits, vegetables, legumes, fish, whole grains, nuts, and olive oil; moderate consumption of dairy products and wine; and low intake of red and processed meats and foods that contain high amounts of added sugars59. The beneficial role of the MD with regard to mortality from all causes, cardiovascular disease (CVD) and cancer, as well as obesity and type 2 diabetes60,61 has already been reported from the results of many epidemiological studies and clinical trials. Similar recommendations should proactively be pursued for the physical health status of patients with BD, and a closer follow-up regarding the metabolic parameters should be part of their routine clinical management program.
When the results of the current study are evaluated, it is necessary to consider the limitations of the study. The fact that participants were evaluated cross-sectionally, and that they were not followed up longitudinally, and that all of the patients were in an euthymic period might limit the generalizability of the results. Other limitations of the study are (i) there was no definitive causal relationship in the outcomes, (ii) the study results could not be compared, or were only suboptimally compared, with other studies in the literature due to lack of similarly designed studies in similar clinical populations, (iii) it was not possible to compare the groups which were offered psychopharmacological treatment with those who were not, which might be a contributing factor for the development of MS, and (iv) did not evaluate the role of comorbid alcohol and substance use.
In light of the high rates of MS observed in all settings, we propose that minimum monitoring for all individuals, even those with normal baseline tests, should include WC or BMI at these time points. Optimal monitoring should also include assessments of FBG, triglycerides, HDL-c and BP. Patients treated with drugs with potential for weight gain and metabolic side effects should be evaluated more frequently in terms of weight and metabolic parameters. For the medical treatment of MS, lifestyle changes such as weight loss, regular exercise, smoking cessation, healty eating are also important. The MD is one of the healthiest dietary patterns, and it may help with the prevention and treatment of cardiovascular disase, diabetes, hypertension and MS.
In conclusion, this article aimed to draw attention to MS, which not only affects patients with BD, but also increases in frequency in healthy individuals all over the world, and to emphasize the importance of necassary measures to be taken. BD is relatively highly comorbid with MS, and appropriate interventions should be prioritized against the development of MS in BD.
1. Ferrari AJ, Baxter AJ, Whiteford HA. A systematic review of the global distribution and availability of prevalence data for bipolar disorder. J Affect Disord. 2011;134(1):1-13.
2. Rihmer Z, Angst J. Mood Disorders: epidemiology: In Aydın H, Bozkurt A (Translation editors). Kaplan & Sadocks Comprehensive Textbook of Psychiatry Eighth Ed Ankara: Gunes Kitabevi. 2007:1575-82.
3. Laursen TM. Life expectancy among persons with schizophrenia or bipolar affective disorder. Schizophr Res. 2011;131(1):101-4.
4. Salvi V, Albert U, Chiarle A, Soreca I, Bogetto F, Maina G. Metabolic syndrome in Italian patients with bipolar disorder. Gen Hosp Psychiatry. 2008;30(4):318-23.
5. Haffner SM, Valdez RA, Hazuda HP, Mitchell BD, Morales PA, Stern MP. Prospective analysis of the insulin-resistance syndrome (syndrome X). Diabetes. 1992;41(6):715-22.
6. Toalson P, Ahmed S, Hardy T, Kabinoff G. The metabolic syndrome in patients with severe mental illnesses. Prim Care Companion J Clin Psychiatry. 2004;6(4):152-8.
7. Eberly LE, Prineas R, Cohen JD, Vazquez G, Zhi X, Neaton JD, et al. Metabolic syndrome risk factor distribution and 18-year mortality in the Multiple Risk Factor Intervention Trial. Diabetes Care. 2006;29(1):123-30.
8. Yumru M, Savas HA, Kurt E, Kaya MC, Selek S, Savas E, et al. Atypical antipsychotics related metabolic syndrome in bipolar patients. J Affect Disord. 2007;98(3):247-52.
9. McIntyre RS, Danilewitz M, Liauw SS, Kemp DE, Nguyen HT, Kahn LS, et al. Bipolar disorder and metabolic syndrome: an international perspective. J Affect Disord. 2010;126(3):366-87.
10. Garcia-Portilla MP, Saiz PA, Benabarre A, Sierra P, Perez J, Rodriguez A, et al. The prevalence of metabolic syndrome in patients with bipolar disorder. J Affect Disord. 2008;106(1):197-201.
11. John AP, Koloth R, Dragovic M, Lim S. Prevalence of metabolic syndrome among Australians with severe mental illness. Med J Aust. 2009;190(4):176-9.
12. Altınbaş K, Darçın AE, Gülöksüz S, Oral TE. İki uçlu bozuklukta metabolik sendrom yaygınlığının mevsimsel değişimi. J Mood Disord. 2012;2(2):51-7.
13. Yumru M, Savaş E, Gergerlioğlu HS, Başaralı K, Kalenderoğlu A, Savaş HA, et al. Ikiuçlu Bozuklukta Metabolik Sendrom, Serum Leptin Düzeyleri ve Tedavi iliş lkisi. Klinik Psikofarmakoloji Bulteni. 2008;18(2).
14. Evans-Lacko SE, Zeber JE, Gonzalez JM, Olvera RL. Medical comorbidity among youth diagnosed with bipolar disorder in the United States. J Clin Psychiatry. 2009;70(10):1461-6.
15. Gálvez JF, Sanches M, Bauer IE, Sharma AN, Hamilton J, Mwangi B, et al. Premorbid obesity and metabolic disturbances as promising clinical targets for the prevention and early screening of bipolar disorder. Med Hypotheses. 2015;84(4):285-93.
16. McIntyre RS, Woldeyohannes HO, Soczynska JK, Miranda A, Lachowski A, Liauw SS, et al. The rate of metabolic syndrome in euthymic Canadian individuals with bipolar I/II disorder. Adv Ther. 2010;27(11):828-36.
17. Association AP. American Psychiatric Association. DSM-5. APA DSM. 2013;5.
18. Young R, Biggs J, Ziegler V, Meyer D. A rating scale for mania: reliability, validity and sensitivity. Br J Psychiatry. 1978;133(5):429-35.
19. Karadağ F, Oral ET, Aran Yalçın F, Erten E. Young Mani Derecelendirme Ölçeğinin Türkiye’de Geçerlik ve Güvenilirliği. Türk Psikiyatri Dergisi. 2001;13(2):107-14.
20. Berk M, Malhi GS, Cahill C, Carman AC, Hadzi‐Pavlovic D, Hawkins MT, et al. The Bipolar Depression Rating Scale (BDRS): its development, validation and utility. Bipolar Disord. 2007;9(6):571-9.
21. Batmaz S, Ozdel K, Kocbiyik S, Karadag H. The validity and reliability of the Turkish version of the bipolar depression rating scale. Compr Psychiatry. 2014;55(6):1448-54.
22. Beck AT. A systematic investigation of depression. Compr Psychiatry. 1961;2(3):163-70.
23. Hisli N. A study on the validity of Beck Depression Inventory. Turkish Journal of Psychology. 1988;6(22):118-23.
24. Saglam M, Arikan H, Savci S, Inal-Ince D, Bosnak-Guclu M, Karabulut E, et al. International Physical Activity Questionnaire: Reliability and Validity of The Turkish Version 1. Percept Mot Skills. 2010;111(1):278-84.
25. Saglam M, Arikan H, Savci S, Inal-Ince D, Bosnak-Guclu M, Karabulut E, et al. International physical activity questionnaire: reliability and validity of the Turkish version. Percept Mot Skills. 2010;111(1):278-84.
26. Expert Panel on Detection E. 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(19):2486.
27. 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(17):2735-52.
28. Alberti KGMM, Zimmet P, Shaw J. Metabolic syndrome – A new world‐wide definition. A consensus statement from the international diabetes federation. Diabet Med. 2006;23(5):469-80.
29. Hjermann I. The metabolic cardiovascular syndrome: syndrome X, Reaven’s syndrome, insulin resistance syndrome, atherothrombogenic syndrome. J Cardiovasc Pharmacol. 1992;20 Suppl 8:S5-10.
30. Czepielewski L, Daruy Filho L, Brietzke E, Grassi-Oliveira R. Bipolar disorder and metabolic syndrome: a systematic review. Rev Bras Psiquiatr. 2013;35(1):88-93.
31. Taylor V, MacQueen G. Associations between bipolar disorder and metabolic syndrome: A review. J Clin Psychiatry. 2006;67(7):1034-41.
32. de Almeida KM, Moreira CL, Lafer B. Metabolic syndrome and bipolar disorder: what should psychiatrists know? CNS Neurosci Ther. 2012;18(2):160-6.
33. Vancampfort D, Vansteelandt K, Correll CU, Mitchell AJ, De Herdt A, Sienaert P, et al. Metabolic syndrome and metabolic abnormalities in bipolar disorder: a meta-analysis of prevalence rates and moderators. Am J Psychiatry. 2013;170(3):265-74.
34. Murray DP, Weiner M, Prabhakar M, Fiedorowicz JG. Mania and mortality: why the excess cardiovascular risk in bipolar disorder? Curr Psychiatry Rep. 2009;11(6):475-80.
35. Birkenaes AB, Opjordsmoen S, Brunborg C, Engh JA, Jonsdottir H, Ringen PA, et al. The level of cardiovascular risk factors in bipolar disorder equals that of schizophrenia: a comparative study. J Clin Psychiatry. 2007;68(6):917-23.
36. Van Winkel R, De Hert M, Van Eyck D, Hanssens L, Wampers M, Scheen A, et al. Prevalence of diabetes and the metabolic syndrome in a sample of patients with bipolar disorder. Bipolar Disord. 2008;10(2):342-8.
37. Cardenas J, Frye MA, Marusak SL, Levander EM, Chirichigno JW, Lewis S, et al. Modal subcomponents of metabolic syndrome in patients with bipolar disorder. J Affect Disord. 2008;106(1):91-7.
38. Fagiolini A, Frank E, Scott JA, Turkin S, Kupfer DJ. Metabolic syndrome in bipolar disorder: findings from the Bipolar Disorder Center for Pennsylvanians. Bipolar Disord. 2005;7(5):424-30.
39. Kupfer DJ. The increasing medical burden in bipolar disorder. JAMA. 2005;293(20):2528-30.
40. Hajer GR, van Haeften TW, Visseren FL. Adipose tissue dysfunction in obesity, diabetes, and vascular diseases. Eur Heart J. 2008;29(24):2959-71.
41. Erem C, Yildiz R, Kavgaci H, Karahan C, Deger O, Çan G, et al. Prevalence of diabetes, obesity and hypertension in a Turkish population (Trabzon city). Diabetes Res Clin Pract. 2001;54(3):203-8.
42. Çayir A, Nazlı A, Köse SK. Beslenme ve diyet kliniğine başvuranlarda obezite durumu ve etkili faktörlerin belirlenmesi. Ankara Üniversitesi Tıp Fakültesi Mecmuası. 2011;64(01):013-9.
43. Aladağ N, Ciğerli Ö, Topsever P, Topallı R, Görpelioğlu S, Filiz TM. Değirmendere Aile hekimliği polikliniğine başvuran erişkin hastalarda obezite sıklığı ve eşlik eden hastalıklarla ilişkisi: bir olgu kontrol çalışması. Türkiye Aile Hekimliği Dergisi. 2007;7(3):117-21.
44. Akbay E, Bugdayci R, Tezcan H, Konca K, Yazar A, Pata C. The prevalence of obesity in adult population in a city on the Mediterranean coast of Turkey. Turkish Journal of Endocrinology and Metabolism. 2003;1:31-5.
45. Kutlutürk F, Öztürk B, Yildirim B, Özuğurlu F, Çetin İ, Etikan İ, et al. Obezite prevalansı ve metabolik risk faktörleri ile ilişkisi: Tokat ili prevalans çalışması. Turkiye Klinikleri J Med Sci. 2011;31(1):
46. Silarova B, Giltay EJ, Dortland AVR, Van Rossum EF, Hoencamp E, Penninx BW, et al. Metabolic syndrome in patients with bipolar disorder: Comparison with major depressive disorder and non-psychiatric controls. J Psychosom Res. 2015;78(4):391-8.
47. Chang HH, Chou CH, Chen PS, Gean PW, Huang HC, Lin CY, et al. High prevalence of metabolic disturbances in patients with bipolar disorder in Taiwan. J Affect Disord. 2009;117(1):124-9.
48. Elmslie JL, Porter RJ, Joyce PR, Hunt PJ, Shand BI, Scott RS. Comparison of insulin resistance, metabolic syndrome and adiponectin in overweight bipolar patients taking sodium valproate and controls. Aust N Z J Psychiatry. 2009;43(1):53-60.
49. Khatana SAM, Kane J, Taveira TH, Bauer MS, Wu W-C. Monitoring and prevalence rates of metabolic syndrome in military veterans with serious mental illness. PLoS One. 2011;6(4):e19298.
50. Elmslie JL, Porter RJ, Joyce PR, Hunt PJ, Shand BI, Scott RS. Comparison of insulin resistance, metabolic syndrome and adiponectin in overweight bipolar patients taking sodium valproate and controls. Aust N Z J Psychiatry. 2009;43(1):53-60.
51. Sicras A, Rejas J, Navarro R, Serrat J, Blanca M. Metabolic syndrome in bipolar disorder: a cross‐sectional assessment of a Health Management Organization database. Bipolar Disord. 2008;10(5):607-16.
52. Teixeira PJR, Rocha FL. The prevalence of metabolic syndrome among psychiatric inpatients in Brazil. Rev Bras Psiquiatr. 2007;29(4):330-6.
53. Taylor V, MacQueen G. Associations between bipolar disorder and metabolic syndrome: a review. J Clin Psychiatry. 2006;67(7):1034-41.
54. Medeiros GC, Lafer B, Kapczinski F, Miranda-Scippa A, Almeida KM. Bipolar disorder and tobacco smoking: Categorical and dimensional clinical correlates in subjects from the Brazilian bipolar research network. Compr Psychiatry. 2018;82:14-21.
55. Xiang YT, Li LJ, Zhou JJ, Wang CY, Dixon LB, Dickerson F, et al. Quality of life of patients with euthymic bipolar disorder and its associations with demographic and clinical characteristics, psychopathology, and cognitive deficits. Perspect Psychiatr Care. 2014;50(1):44-50.
56. Sun K, Liu J, Ning G. Active smoking and risk of metabolic syndrome: a meta-analysis of prospective studies. PLoS One. 2012;7(10):e47791.
Fagiolini A, Chengappa KR, Soreca I, Chang J. Bipolar disorder and the metabolic syndrome. CNS drugs. 2008;22(8):655-69.
57. Keys A, Mienotti A, Karvonen MJ, Aravanis C, Blackburn H, Buzina R, et al. The diet and 15-year death rate in the seven countries study. Am J Epidemiol. 1986;124(6):903-15.
58. Trichopoulou A, Costacou T, Bamia C, Trichopoulos D. Adherence to a Mediterranean diet and survival in a Greek population. N Engl J Med. 2003;348(26):2599-608.
59. Giugliano D, Esposito K. Mediterranean diet and metabolic diseases. Curr Opin Lipidol. 2008;19(1):63-8.
60. Buckland G, Bach A, Serra‐Majem L. Obesity and the Mediterranean diet: a systematic review of observational and intervention studies. Obes Rev. 2008;9(6):582-93.