|Year : 2018 | Volume
| Issue : 6 | Page : 476-484
Association of antipsychotic and antidepressant treatment with metabolic syndrome and 10 years' coronary heart disease risk
Vivek Pratap Singh, Archana Javadekar, Suprakash Chaudhury, Daniel Saldanha
Department of Psychiatry, Dr. D. Y. Patil Medical College, Hospital and Research Center, Dr. D. Y. Patil Vidyapeeth, Pune, Maharashtra, India
|Date of Submission||01-Feb-2018|
|Date of Acceptance||15-May-2018|
|Date of Web Publication||15-Nov-2018|
Department of Psychiatry, Dr. D. Y. Patil Medical College, Pimpri, Pune - 411 018, Maharashtra
Source of Support: None, Conflict of Interest: None
Background: Cardiovascular risk is becoming a growing concern in patients receiving psychotropic medications. An increased Framingham risk score (FRS) and 10-year coronary artery disease risk has been reported in patients suffering from mental diseases. Aim: This study aims to evaluate the cardiometabolic risk profile in patients suffering from psychiatric disorders being treated with antipsychotics and antidepressants. Materials and Methods: This cross-sectional study was conducted on 68 patients diagnosed with psychiatric disorders according to International Statistical Classification of Diseases-10 at a tertiary health-care center. Patient's demographic details, family history, level of education, duration of disease, use of alcohol and or nicotine, use of concomitant medications, psychotropic drug history, history of treatment of diabetes, dyslipidemia, hypertension, or any other medical conditions were also recorded. Waist circumference, blood pressure, fasting blood sugar, triglyceride, and high-density lipoprotein values were estimated by taking fasting venous samples under aseptic measures. Metabolic syndrome was diagnosed using the International Diabetes Federation Criteria. Ten-year cardiovascular risk was assessed using the FRS. Statistical evaluation was done using appropriate parametric and nonparametric statistical methods. Results: A total of 49 patients were being treated with antipsychotic drugs and 19 were receiving antidepressants. The mean age of patient receiving antipsychotics were 37.51, and those receiving antidepressant were 34.15. The metabolic syndrome was 36.76% in patients taking antipsychotics as compared to 11.76% in patients on antidepressant. The mean FRS score in antipsychotic group was 7.48, and those receiving antidepressants were 4.7. The 10-year coronary heart disease (CHD) risk score was significantly higher in patients receiving antipsychotics as compared to patients on antidepressants. Conclusion: Treatment with antipsychotics is associated with significantly higher 10-year CHD risk scores as compared to treatment with antidepressants.
Keywords: Antidepressants, antipsychotics, coronary heart disease risk, Framingham risk score, hypertension, lipid profile, side effects, waist circumference
|How to cite this article:|
Singh VP, Javadekar A, Chaudhury S, Saldanha D. Association of antipsychotic and antidepressant treatment with metabolic syndrome and 10 years' coronary heart disease risk. Med J DY Patil Vidyapeeth 2018;11:476-84
|How to cite this URL:|
Singh VP, Javadekar A, Chaudhury S, Saldanha D. Association of antipsychotic and antidepressant treatment with metabolic syndrome and 10 years' coronary heart disease risk. Med J DY Patil Vidyapeeth [serial online] 2018 [cited 2019 Mar 24];11:476-84. Available from: http://www.mjdrdypv.org/text.asp?2018/11/6/476/245422
| Introduction|| |
Metabolic syndrome and obesity are the major comorbidity associated with psychiatric disorders, and it is found in more than 40% of the cases. Individuals diagnosed with depression and psychotic disorders were noted to have a higher prevalence of both metabolic syndrome and obesity when compared to the general population, and due to similar underlying mechanism, the probability of developing affective and psychotic disorder increases with metabolic syndrome.,
Antipsychotics are considered to be the cornerstone in the management of schizophrenia, and there is a strong evidence to suggest that they reduce suicide, morbidity, and hospital admissions. The occurrence of metabolic syndrome in patients suffering from schizophrenia was reported in the range of 3.3%–68%. The prevalence was also compared in between those who did not receive antipsychotics and those who received antipsychotics, and it was seen to be between 3.3% and 26% in the former and 32%–68% in the latter group; the trend was also found to be more in female patients, younger patients and Hispanics, whereas it was on the lower side amongst orientals and African-Americans. The occurrence of metabolic abnormalities was on the higher side in the patient receiving second-generation antipsychotics, more with clozapine, olanzapine, quetiapine, and risperidone when compared to the first-generation antipsychotics. Both typical and atypical antipsychotics and antidepressants have been implicated in causing dyslipidemia, weight gain, and glucose dysregulation.
Among the patients suffering from depression, the use of antidepressant was associated with increased risk of metabolic syndrome. Insulin resistance and hypertriglyceridemia was associated with the use of tricyclic antidepressants. In addition, patients treated with tricyclic antidepressant experience considerable weight gain. However, the use of selective serotonin reuptake inhibitor (SSRI) was linked to the reduction of weight in the beginning, though long-term use resulted in weight gain. In patients with depression, the risk of development of metabolic syndrome is exacerbated by a decrease in body metabolism. SSRIs may provide short-term benefits in glucose regulation, but on the other hand, tricyclic and noradrenergic antidepressant may worsen the metabolic state. Exceptionally, females taking antidepressant have increased risk of developing type 2 diabetes mellitus than nonmedicated patients.
The relationship between psychiatric disorders and metabolic syndrome is complex. The onset of psychiatric disorders and metabolic syndrome in childhood and adolescents suggest a strong biological linkage. Stress can increase leptin resistance, levels of neuropeptide Y, and inflammatory cytokines which causes an increase in appetite and obesity. The environmental factors also pose a risk of metabolic syndrome to specific population with high risk of mental illness. It has been noted that increase sugar and saturated fat intake in women with depression and obesity may increase the probability of weight gain and metabolic syndrome. Moreover, depression and emotional dysregulation commonly lead to increase predilection for sweet and fatty food, higher caloric consumption, and sedentary lifestyle. Therefore, psychiatric disorders can promote and maintain an obese state and may also increase resistance to treatment.,,
Very few Indian studies have evaluated metabolic syndrome in patients taking antipsychotics drugs, and no study has assessed patients on antidepressants for the presence of metabolic syndrome. In view of the above, the present study was undertaken to assess the influence of antipsychotics and antidepressants on the physical health of individuals suffering from psychiatric disorders.
| Materials and Methods|| |
This cross-sectional, hospital-based study was carried out in the Psychiatry Department of Dr. D. Y. Patil Medical College, Hospital and Research Center during July 2015 to September 2017. The project was submitted to and approved by the institutional ethical committee. All patients admitted for psychiatric treatment and being treated with antipsychotic drugs or antidepressants were included in the study after obtaining their written informed consent.
The sample for the study was selected by purposive sampling method. Consecutive patients presenting for psychiatric management and treated with antipsychotic drugs or antidepressants were included in the study with their written informed consent.
- Patients presenting with psychiatric disorders at a tertiary care center
- Patients taking antipsychotic or antidepressant drugs only
- Adults between 18 years to 65 years of age.
- Patients who refused to give consent
- Pregnant women with psychiatric illness
- All those who have delivered a child in the past 1 year.
International Diabetes Federation criteria
Metabolic syndrome was diagnosed with the definition given by the International Diabetes Federation (IDF), which consists of abdominal obesity (abdominal circumference of ≥90 cm and ≥80 cm for men and women, respectively), triglyceride levels of >150 mg/dl, a systolic blood pressure (BP) ≥130 mmHg or a diastolic BP ≥85 mmHg, fasting plasma glucose level (FBS) of ≥100 mg/dl, high-density lipoproteins (HDL) of <40 mg/dl, and 50 mg/dl for men and women, respectively. The IDF criteria require central obesity plus any other two or more out of five criteria.
Framingham cardiovascular risk score
The Framingham Risk Score (FRS) is calculated using age, sex, total cholesterol, HDL, diabetes mellitus, smoking habits, and systolic arterial pressure. The FRS Score was used to calculate 10-year coronary heart disease (CHD) risk in patients.
Patients were diagnosed with psychiatric disorders with the help of International Statistical Classification of Diseases-10. Sociodemographic and illness-related details were recorded in a specially designed pro forma. Body weight and height in kilograms and centimeters, respectively, were recorded. Waist circumference was measured and BP in supine position was noted by using manometer. Blood was sent for estimation of fasting blood glucose, cholesterol, triglyceride, and HDL levels. After obtaining the biochemical values, the presence of metabolic syndrome was diagnosed using IDF and then 10-year CHD risk was calculated.
The data obtained were processed using Statistical Package of Social Sciences – version 20.0 (SPSS-20, IBM, USA). Descriptive statistics was used to calculate mean, percentage, and standard deviation of the sample. Chi-square, Fisher's exact test, t-test, and Mann–Whitney U tests were used for statistical analysis as appropriate.
| Results|| |
During the study, 88 patients attending the psychiatric outpatient department were treated only with antipsychotics or antidepressants. Among them, 7 were children, 9 were pregnant, and 4 patients did not give consent. Therefore, a total of 68 patients were included in the study. The sociodemographic and clinical characteristics of the patients are shown in [Table 1] and [Table 2], respectively. The metabolic profile, FRS, and 10-year coronary risk score (CRS) are given in [Table 3]. Frequency of abnormal metabolic parameters and CRS of psychiatric patients on antipsychotics and antidepressants is given in [Table 4]. Comparison of patients on antipsychotics and antidepressants who developed metabolic syndrome is shown in [Table 5].
|Table 1: Demographic characteristics of patients on antipsychotics (n=49) and on antidepressants (n=19)|
Click here to view
|Table 2: Clinical details of psychiatric patients on antipsychotics and antidepressants|
Click here to view
|Table 3: Metabolic profile, Framingham Risk Score, and 10-year Coronary Risk score of psychiatric patients on antipsychotics (n=49) and antidepressants (n=19)|
Click here to view
|Table 4: Frequency of abnormal metabolic parameters and 10-year Coronary Risk Score of psychiatric patients on antipsychotics (n=49) and antidepressants (n=19)|
Click here to view
|Table 5: Comparison of patients on antipsychotics (n=25) and antidepressants (n=8) who developed metabolic syndrome|
Click here to view
| Discussion|| |
The study was carried out in a teaching medical college hospital located in close proximity to urban area and catchment area of rural population who avail the facilities of the institute. The present population is estimated to be approximately 2,000,000, and this hospital caters to a large number of people suffering from mental health issues. The primary aim of the study was to study the cardiometabolic risk factors in patients with psychiatric disorders.
In the present study, the majority of patients (n = 39; 57.35%) were in the age group of <40 years and 30 (42.64%) cases were aged more than 40 years. This finding was consistent with an earlier study which showed that age is an important predictor of mental illness in the population irrespective of the residential settings. The majority of patients were females (n = 37; 54.41%) and 32 (45.58%) males. This is in accordance to a study which found that gender differences occur in mental disorder, but women predominate. The female preponderance can be attributed to many factors such as hormonal disturbances, alcohol use, sexual and physical violence by husband, having low autonomy in decision-making, and low level of support from family., The majority of patients (n = 62; 84.21%) were Hindu, while 6 cases (15.78%) belonged to Muslim community. This is not surprising as the population of this area is mostly Hindu who outnumbers other minority groups such as Christians and Muslims. Hence, no conclusions can be drawn about this demographic factor.
The majority of patients (n = 48; 70.58%) were illiterates or studied up to primary level, 16 (23.52%) were educated up to higher secondary level, and 4 (5.9%) were graduates. This was consistent with a study done where maximum number of individual suffering from mental disorders had completed their studies only till their secondary education. Another possible explanation would be that poor education can decrease people skills and could lead to faulty coping mechanism making them prone to mental health illnesses. The majority of patients (n = 43; 63.23) had a family income of less than 1 lakh, while 26 (36.76%) patients had a family income of more than 1 lakh. This was in accordance to an earlier study which showed that low socioeconomic status and illiterates were found to be more affected by mental illnesses and it can be due to low socioeconomic status which can lead to adverse economic stress leading to mental illnesses.
The majority of patients (n = 36) belonged to rural areas and 33 patients were from urban area.
This was in accordance with an earlier study done in India where the prevalence of mental illness was found to be higher in rural settings. Considering the fact that large proportion of rural population lives in poverty, it can be a significant determinant of mental illness. The majority of patients (n = 44; 64.70%) were married while 25 (35.29%) cases were unmarried. In India, 95% of women are married by age 25, whereas the same percentage of men are married by age 32, whereas in Maharashtra, the mean age of marriage was found to be 18.05. Even in comparison with other developing countries, India has one of the lowest ages at marriage.
The majority of patients, 40 (58.82%) cases, were unskilled and unemployed and 29 (41.17%) were skilled, homemaker, and students. The above two finding was in accordance to a study by Khattri et al. which showed that maximum number of cases were unskilled and married. In general, persons suffering from mental illness also have neurocognitive impairment and maladaptive social functioning which hinders them to continue their higher education, which tends to affect entry into the skilled job market.,,
Psychiatric illness-wise distribution showed that 40 (58.82%) cases had psychosis, 14 (20.58%) had unipolar depression, 9 (13.23%) were from others group, and 5 (7.35%) had BAD and mania. This was in accordance to a study performed at a tertiary care hospital which showed that maximum patients presenting to a tertiary care were from Psychosis group.
There were 17 (68%) patients on antipsychotics having a history of substance use while 3 (37.5%) of patients on antidepressants. A significant association between substance use and antipsychotic drugs was found. This was in accordance to a study which found that the prevalence of smoking was higher in patients with psychosis. In another study, it was found that comorbid alcohol use disorder was common in patients suffering from psychiatric disorders and that alcohol and nicotine were used as self-medication by psychiatric patients.,,
The majority of patients (n = 54; 79.41%) were doing mild or moderate physical activity while 15 (22.05%) were doing vigorous physical activity. This was in accordance to a study where physical activity pattern was studied in patients suffering from mental health illnesses, and it was found that they were overall less physically active. It has also been reported that that anomalous bodily experiences and negative symptoms were significantly responsible for low physical activity.,
The majority of patients were having reduced HDL (n = 49;72.05%), high triglyceride (n = 47; 69.11%), and high BMI (n = 51;75%). This was in accordance to a study where almost 40% cases were having altered BMI, HDL, and triglycerides. Several reasons have been proposed for high level of obesity and deranged laboratory and metabolic parameters which includes shared biological vulnerability between mental health illnesses and abnormal metabolic processes along with unhealthy lifestyles and emerging evidences also support the use of psychotropic medicines as a risk factor.
In the present study, 33 (48.52%) of patients taking antipsychotics or antidepressants had metabolic syndrome. In patients having metabolic syndrome, 25 (36.76%) were on antipsychotics and 8 (11.76%) were on antidepressants. This was in accordance to a study done in India which shows that 37.8% patients attending psychiatric units had metabolic syndrome.
According to several studies, it was noted that the prevalence of metabolic syndrome and its various components are notably higher in populations with psychiatric disorders when compared with the general populations.,, The reason found for this association may be due to psychotropic drug use, lifestyle factors, and the psychiatric disorders itself.
Majority of the patients who developed metabolic syndrome (±40 years), i.e., 16 were on antipsychotics (48.48%) and 4 (12.12%) were on antidepressants. In <40 years group, 9 (27.27%) patients were on antipsychotics and 4 (12.12%) were on antidepressants. The difference was not significant. Previous studies also indicate that patients aged more than 40 years have higher chances of developing metabolic syndrome as compared to other group and significant relation between age and metabolic syndrome was reported.
The majority of patients who were having metabolic syndrome were females 18 (72%) were on antipsychotics and 6 (24%) were on antidepressants, and in males, 7 (28%) were on antipsychotics and 2 (25%) were on antidepressants. No significant association was found between sex and metabolic syndrome, but the data showed that females were more prone to metabolic syndrome as compared to males. This was in accordance to a study which showed that there is a significant relation between metabolic syndrome and female sex. In our study, population more patients were females who were suffering from psychosis and were on antipsychotics, and it is hypothesized that women may be more likely to develop metabolic syndrome in response to antipsychotic agents.
In the present study, no statistical significant relation was found between disease type and metabolic syndrome. This was in contrast to an earlier study which found that the prevalence of metabolic syndrome was more in patients with schizophrenia, nonaffective and affective psychosis as compared to patients without psychotic disorders.
The association between duration of treatment taken and metabolic syndrome showed that all patients on antidepressants for ≥3 months were having metabolic syndrome and 80% patients on antipsychotics had metabolic syndrome. No significant association was found between duration of treatment and metabolic syndrome. The above finding was in contrast to other studies were patients on antipsychotics are more prone to metabolic syndrome. This could be due to small sample size of the study. Other biological mechanisms include genetic variability in antipsychotic-induced weight gain and H1-receptor antagonism in antidepressants might increase the risk of metabolic syndrome.
There was no significant association found between substance abuse and metabolic syndrome.
This was in accordance to a study where substance use was found more in patients having metabolic syndrome, but no significant relation was found between them. However, another study reported that the prevalence of smoking was more in patients diagnosed with metabolic syndrome as compared to patients who were not having metabolic syndrome, but in this study also no significant relation was found between the two.
The association between physical activity and metabolic syndrome showed that in patients who were diagnosed as metabolic syndrome and on antipsychotic 18 (72%) were doing mild physical activity and 7 (28%) were doing moderate/vigorous physical activity. In patients having metabolic syndrome and who are on antidepressant 7 (87.5%) were doing mild activity and 1 (12.5%) were doing mild/vigorous activity. No significant association between physical activity group and metabolic syndrome was found. This was in accordance with an earlier study which observed that patients having metabolic syndrome were significantly less physically active in comparison to general population.
Among the metabolic syndrome, patients who were on antidepressants, all of them had increased BMI. In contrast to this in patients on antipsychotics, 15 (60%) had normal BMI, while 10 (40%) had high BMI. A significant association between metabolic syndrome and antidepressants was found. This finding was in contrast to other studies which show that antipsychotics are more prone to increase BMI. This can be due to small sample size of the study. This finding has therapeutic implications. Cognitive behavior therapy (CBT) can be offered to treat obesity because CBT interventions were found to help in the reduction of binge eating and maintenance of weight loss.
The association between FRS with metabolic syndrome showed that patients with metabolic syndrome on antipsychotics had a mean value of 7.48 and standard deviation of 6.71 and in patients who were on antidepressants mean FRS was 4.78 with standard deviation of 5.56. No significant difference of FRS according to metabolic syndrome was found. The association between coronary artery heart disease risk with patients who were on antipsychotics in them 0%–5% risk was seen in 39 (79.59%) cases and >5% risk was seen in 10 (20.40%) patients. In patients who were on antidepressants 0%–5% risk was seen in 18 (94.73%) cases and >5% risk was seen in 1 (5.26%) patient. A significant association between coronary artery heart disease risk and metabolic syndrome was found. This was in accordance to various studies done where 10-year risk of having coronary artery heart disease was found to be significantly higher in patients diagnosed with metabolic syndrome.
- Small sample size and the cross-sectional nature of the study
- Noninclusion of apparently healthy population as control group
- This study did not access the severity of symptoms which may have been a contributing factor to the presence of metabolic syndrome.
| Conclusion|| |
Patients suffering from psychiatric disorders and on treatment with antipsychotics or antidepressants are at high risk of developing metabolic syndrome. In the present study, the score on the 10-year coronary artery heart disease risk was found to be significantly higher in patients on antipsychotics as compared to patients on antidepressants. Routine screening for metabolic disturbances is essential for patients suffering from psychiatric disorders and receiving antidepressants or antipsychotics. Simple lifestyle advice such as exercises and balanced diet which can reduce the morbidity and mortality rates in patients receiving antidepressants or antipsychotics may lead to improvement in their quality of life.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Alberti KG, Zimmet P, Shaw J. Metabolic syndrome – A new world-wide definition. A Consensus statement from the international diabetes federation. Diabet Med 2006;23:469-80.
Carpiniello B, Pinna F, Velluzzi F, Loviselli A. Mental disorders in patients with metabolic syndrome. The key role of central obesity. Eat Weight Disord 2012;17:e259-66.
Stanley SH, Laugharne JD. Obesity, cardiovascular disease and type 2 diabetes in people with a mental illness: A need for primary health care. Aust J Prim Health 2012;18:258-64.
Luppino FS, de Wit LM, Bouvy PF, Stijnen T, Cuijpers P, Penninx BW, et al.
Overweight, obesity, and depression: A systematic review and meta-analysis of longitudinal studies. Arch Gen Psychiatry 2010;67:220-9.
Cyrus SH, Ho CS, Zhang MW, Mak A, Ho RC. Metabolic syndrome in psychiatry: Advances in understanding and management. Adv Psychiatr Treat 2014;20:101-12.
Simon GE, Von Korff M, Saunders K, Miglioretti DL, Crane PK, van Belle G, et al.
Association between obesity and psychiatric disorders in the US adult population. Arch Gen Psychiatry 2006;63:824-30.
Stunkard AJ, Faith MS, Allison KC. Depression and obesity. Biol Psychiatry 2003;54:330-7.
Quek YH, Tam WW, Zhang MW, Ho RC. Exploring the association between childhood and adolescent obesity and depression: A meta-analysis. Obes Rev 2017;18:742-54.
Yang JL, Liu X, Jiang H, Pan F, Ho CS, Ho RC, et al.
The effects of high-fat-diet combined with chronic unpredictable mild stress on depression-like behavior and leptin/LepRb in male rats. Sci Rep 2016;6:35239.
Lu Y, Andiappan AK, Lee B, Ho R, Lim TK, Kuan WS, et al.
Neuropeptide Y associated with asthma in young adults. Neuropeptides 2016;59:117-21.
Lu Y, Van Bever HP, Lim TK, Kuan WS, Goh DY, Mahadevan M, et al.
Obesity, asthma prevalence and IL-4: Roles of inflammatory cytokines, adiponectin and neuropeptide Y. Pediatr Allergy Immunol 2015;26:530-6.
Allison DB, Mentore JL, Heo M, Chandler LP, Cappelleri JC, Infante MC, et al.
Antipsychotic-induced weight gain: A comprehensive research synthesis. Am J Psychiatry 1999;156:1686-96.
Hasnain M, Vieweg WV, Hollett B. Weight gain and glucose dysregulation with second-generation antipsychotics and antidepressants: A review for primary care physicians. Postgrad Med 2012;124:154-67.
Deuschle M. Effects of antidepressants on glucose metabolism and diabetes mellitus type 2 in adults. Curr Opin Psychiatry 2013;26:60-5.
Pan A, Lucas M, Sun Q, van Dam RM, Franco OH, Manson JE, et al.
Bidirectional association between depression and type 2 diabetes mellitus in women. Arch Intern Med 2010;170:1884-91.
Mahmood SS, Levy D, Vasan RS, Wang TJ. The Framingham heart study and the epidemiology of cardiovascular disease: A historical perspective. Lancet 2014;383:999-1008.
Lakhan R, Ekúndayò OT. National sample survey organization survey report: An estimation of prevalence of mental illness and its association with age in India. J Neurosci Rural Pract 2015;6:51-4.
] [Full text]
Malhotra S, Shah R. Women and mental health in India: An overview. Indian J Psychiatry 2015;57:S205-11.
Das A. Epidemiology of mental health and mental health issues of women in India: A literature review. Int J Indian Psychol 2017;4:92.
Gomes VF, Miguel TL, Miasso AI. Common mental disorders: Socio-demographic and pharmacotherapy profile. Rev Lat Am Enfermagem 2013;21:1203-11.
Manners A, Schnabel L, Hernandez JE, Silberg E. The relationship between education and mental health: new evidence from a discordant twin study. Soc Forces 2016;95:107-31.
Halpern-Manners A, Schnabel L, Hernandez E, Silberg J, Eaves L. The relationship between education and mental health: New evidence from a discordant twin study. Soc Forces 2016;95:107-31.
Sidhu J, Virk J. Epidemiological study of mental disorders in Bathinda district of Punjab. J Res Med Educ Ethics 2013;3:191.
Desai S, Andrist L. Gender scripts and age at marriage in India. Demography 2010;47:667-87.
Rosenheck R, Leslie D, Keefe R, McEvoy J, Swartz M, Perkins D, et al.
Barriers to employment for people with schizophrenia. Am J Psychiatry 2006;163:411-7.
Schretlen DJ, Cascella NG, Meyer SM, Kingery LR, Testa SM, Munro CA, et al.
Neuropsychological functioning in bipolar disorder and schizophrenia. Biol Psychiatry 2007;62:179-86.
Khattri JB, Poudel BM, Thapa P, Godar ST, Tirkey S, Ramesh K, Chakraborty PK. An epidemiological study of psychiatric cases in a rural community of Nepal. Nepal J Med Sci 2013;2:52-6.
Maan CG, Munnawar Hussain MS, Heramani N, Lenin RK. Factors affecting non-compliance among psychiatric patients in the regional institute of medical sciences, Imphal. IOSR J Pharm 2015;5:1-7.
Turner J, Kelly B. Emotional dimensions of chronic disease. West J Med 2000;172:124-8.
Foley DL, Mackinnon A, Morgan VA, Watts GF, Castle DJ, Waterreus A, et al.
Common familial risk factors for schizophrenia and diabetes mellitus. Aust N
Z J Psychiatry 2016;50:488-94.
Poirier MF, Canceil O, Baylé F, Millet B, Bourdel MC, Moatti C, et al.
Prevalence of smoking in psychiatric patients. Prog Neuropsychopharmacol Biol Psychiatry 2002;26:529-37.
Huang MC, Yu CH, Chen CT, Chen CC, Shen WW, Chen CH, et al.
Prevalence and identification of alcohol use disorders among severe mental illness inpatients in Taiwan. Psychiatry Clin Neurosci 2009;63:94-100.
Harris KM, Edlund MJ. Self-medication of mental health problems: New evidence from a national survey. Health Serv Res 2005;40:117-34.
Daumit GL, Goldberg RW, Anthony C, Dickerson F, Brown CH, Kreyenbuhl J, et al.
Physical activity patterns in adults with severe mental illness. J Nerv Ment Dis 2005;193:641-6.
Nyboe L, Moeller MK, Vestergaard CH, Lund H, Videbech P. Physical activity and anomalous bodily experiences in patients with first-episode schizophrenia. Nord J Psychiatry 2016;70:514-20.
Mileibys S, Mary L, Elevina P, Sara B, Miguel AF, et al
. Dyslipidemia prevalence of severe mentally ill patients who are under pharmacotherapy scheme. Food Sci Nutri Tech 2016;1:FSNT-MS -ID-000101.
Bradshaw T, Mairs H. Obesity and serious mental ill health: A Critical review of the literature. Healthcare (Basel) 2014;2:166-82.
Linu Mohan P, Jishnu NA, Remya PJ. Prevalence of metabolic syndrome in psychiatric outpatients in a tertiary care hospital, Kerala. Indian J Pharm Pract 2012;5:57-61.
Chuki P, Gupta A, Sharma A, Dahiya N. Prevalence of metabolic syndrome in patients on antipsychotic drug therapy. Eur J Pharm Med Res 2016;3:288-93.
Shakeri J, Karimi K, Farnia V, Golshani S, Alikhani M. Prevalence of metabolic syndrome in patients with schizophrenia referred to farabi hospital, Kermanshah, Iran. Oman Med J 2016;31:270-5.
Suvisaari JM, Saarni SI, Perälä J, Suvisaari JV, Härkänen T, Lönnqvist J, et al.
Metabolic syndrome among persons with schizophrenia and other psychotic disorders in a general population survey. J Clin Psychiatry 2007;68:1045-55.
Ho CS, Zhang MW, Mak A, Ho RC. Metabolic syndrome in psychiatry: Advances in understanding and management. Adv Psychiatr Treat 2014;20:101-12.
Vancampfort D, Stubbs B, Mitchell AJ, De Hert M, Wampers M, Ward PB, et al.
Risk of metabolic syndrome and its components in people with schizophrenia and related psychotic disorders, bipolar disorder and major depressive disorder: A systematic review and meta-analysis. World Psychiatry 2015;14:339-47.
Said MA, Sulaiman AH, Habil MH, Das S, Bakar AK, Yusoff RM, et al.
Metabolic syndrome and cardiovascular risk among patients with schizophrenia receiving antipsychotics in Malaysia. Singapore Med J 2012;53:801-7.
Zhang MW, Ho RC, Cassin SE, Hawa R, Sockalingam S. Online and smartphone based cognitive behavioral therapy for bariatric surgery patients: Initial pilot study. Technol Health Care 2015;23:737-44.
Wysokiński A, Kazmierski J, Kłoszewska I. Comparison of metabolic parameters and Framingham cardiovascular risk scores before and after in hospital treatment with antipsychotics. Arch Psychiatry Psychother 2014;16:21-9.
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5]