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INT’L. J. PSYCHIATRY IN MEDICINE, Vol. 45(3) 203-226, 2013

METABOLIC SYNDROME: DIFFERENCES BETWEEN PSYCHIATRIC AND INTERNAL MEDICINE PATIENTS

FRANCESCO MARGARI

GIUSEPPINA ZAGARIA

MADIA LOZUPONE

FRANCESCO MINERVA

ROSSELLA PISANI

GIUSEPPE PALASCIANO

ADRIANA PASTORE

VINCENZO PALMIERI

ORLANDO TODARELLO University “Aldo Moro” of Bari, Italy

ABSTRACT

Objectives: The existence of specific features of Metabolic Syndrome (MetS) in psychiatric population in comparison to not psychiatric patients has not been systematically investigated. The purpose of this study is to evaluate the differences of MetS among a group of psychiatric patients and a group of internal medicine patients in terms of anthropometric measurements, biochemical variables, and cardiovascular risk. Methods: We enrolled 83 psychiatric inpatients under pharmacological treatment (schizophrenia n = 24, bipolar disorder n = 27, major depression n = 14, other n = 18) and 77 internal medicine patients visited for supposed MetS as affected by overweight or arterial hypertension. Results: Psychiatric patients differed from control subjects by age (yrs) (47 ± 9 vs. 52 ± 8.6, p = 0.001), waist circumference (cm) (111.9 ± 10.9 vs. 106 ± 12.6, p = 0.02), HDL cholesterol (mg/dl) (36.8 ± 7 vs. 48 ± 11.3, p = 0.001), serum insulin (mU/ml) (26 ± 12.5 vs. 16.4 ± 8.8, p = 0.001), triglyceride/HDL cholesterol ratio (4.8 ± 2.7 vs. 3.3 ± 2.2, p = 0.01). Female psychiatric patients had higher levels of triglycerides (mg) (178 + 86 vs. 115 + 53, p = 0.002) and of HOMA index (7.8 + 5 vs. 3.8 + 3.3, p = 0.005). Triglycerides and triglycerides/HDL ratio levels were 203 Ó 2013, Baywood Publishing Co., Inc. doi: http://dx.doi.org/10.2190/PM.45.3.a http://baywood.com

204 / MARGARI ET AL.

higher in Unipolar Depression. A positive association was found between antidepressant drug treatment with triglycerides and triglycerides/HDL ratio levels, neuroleptic treatment with the HOMA index, and antipsychotics drugs with the Framingham index. Limitations: Psychiatric study population numerosity and duration of psychiatric illness and drug treatment. Conclusions: Specific features of MetS in psychiatric population are mainly represented by young age of onset, hyperinsulinemia, increased abdominal adiposity, and low HDL cholesterol whose common denominator may be insulin-resistance. (Int’l. J. Psychiatry in Medicine 2013;45:203-226)

Key Words: severe mental illness, metabolic syndrome, low HDL, insulin resistance

INTRODUCTION The Metabolic Syndrome (MetS) is characterized by several metabolic disorders simultaneously present in the same patient, each of which represents itself with a known cardiovascular risk factor: insulin resistance, glucose intolerance, visceral obesity, hypertension, atherogenic plasma lipid profile, low-grade inflammatory state, oxidative alterations, and certain neuroendocrine derangements including elevated levels of “stress” hormones [1-3]. People with severe mental illness like schizophrenia, schizoaffective, bipolar, and major depression disorder tend to have more physical illnesses and a shorter lifespan, having a life expectancy that is approximately 20% shorter than the general population [4, 5] and a high incidence of cardiovascular diseases (CVD) and mortality [6]. The high cardiovascular risk can be explained by modifiable risk factors for CVD including smoking [7, 8], obesity [9, 10], diabetes [11], arterial hypertension [12], dyslipidemia [13], and metabolic syndrome [14-18]. Furthermore, previous studies underlined the role of the psychotropic drug’s side effects in the incidence of the various criterions of MetS, such as weight gain, diabetes mellitus, and dyslipidemia [19-22]. Nevertheless, some studies on this topic reported higher amounts of visceral fat and abnormalities in glucose tolerance in people with severe mental illness even before antipsychotic medication [23, 24]. MetS has been found in 37% of patients with long-term schizophrenia [25] compared with the 23% in the general population [26]. Its prevalence in major depression is 2.4 times fold greater than the general population [27]. The MetS rate in patients with schizoaffective disorder has been reported to be 42% [28]. A great amount of research reported MetS features in psychiatric population in comparison to the general population, but few studies have reported the existence of specific features of MetS in the psychiatric population, and the possible difference in comparison to non-psychiatric patients has not been systematically

METABOLIC SYNDROME /

205

investigated. For instance, recently Ratliff et al. [29] have compared obese schizophrenia spectrum patients with demographically matched obese controls without severe mental illness and have found a higher cardiovascular risk among psychiatric patients. Nevertheless, this study has only considered subjects with BMI > 28 and is limited to the schizophrenic patients. The purpose of this study is to evaluate the differences of MetS among a group of psychiatric patients and a group of internal medicine patients in terms of anthropometric measurements, biochemical and socio-demographic features, and cardiovascular risk including the influence of psychopharmacological treatment. METHODS Participants and Recruitment Procedures In our study, we enrolled 83 psychiatric inpatients at the University Psychiatric Unit, Neuroscience and Sense Organs Department, Policlinico Hospital of Bari, which were overweight (Body Mass Index (BMI) ³ 25) and under treatment for a psychiatric condition (number of drugs per patient: 3.19 ± 1.07) and affected by different severe mental disorders. The control group was represented by 77 patients consecutively admitted at the Internal Medicine “A. Murri” Unit, at the Policlinico Hospital of Bari, for supposed MetS as affected by overweight (BMI ³ 25) or arterial hypertension. After a complete description of the study to each patient, a written informed consent was obtained. All psychiatric and internal medicine subjects underwent a clinical-anamnestic evaluation and biochemical examinations. The clinical evaluation in both groups was performed at the time of the interview and included sociodemographic variables (sex, age, socioeconomic level, education), physiological data on the lifestyle (smoking status and alcohol habits), medical and family history, and current treatments. For each patient the following anthropometric data was collected: weight (kg), height (cm), BMI (kg/m2), abdominal circumference (AC) (indicative of visceral obesity, measured at the midpoint between the superior border of the iliac crest and the inferior margin of the ribs in cm), and systolic and diastolic blood pressure (SBP and DBP) (mmHg). The biochemical examinations included: fasting glucose (mg/dl), total HDL and LDL cholesterol (mg/dl), triglycerides (mg/dl), glycosylated hemoglobin (%), fasting insulin (mU/ml), transaminases (AST and ALT) (U/l), GGT (U/l), CPK (U/l), and uric acid (mg/dl). Triglyceride/HDL ratio (indicative of insulin resistance [30]), Framingham risk index [31], and HOMA index (Homeostasis Model Assessment [32]) were also calculated. In both groups, MetS was diagnosed according to the NCEP ATP III criteria [33]. Clinical evaluation of psychiatric inpatients was performed using the Structured Diagnostic Interview according to the DSM-IV TR (SCID) [34], distributing patients into four


diagnostic categories (Schizophrenia-Schizoaffective (SCZ), Major Depression (MD), Bipolar Disorder (BD), and Others). A comprehensive psychopathological evaluation, designed to exclude a psychiatric disorder in patients attending the internal medicine unit, was performed by the BPRS (Brief Psychiatric Rating Scale ) [35], the Hamilton Rating Scale for Depression [36], the STAI-t (State Trait Anxiety Inventory) [37], and the PDQ 4+ (Personality Diagnostic Questionnaire version 4) [38]. For both groups the exclusion criteria was established as follows: individuals under 18 years of age, pregnancy or postpartum, presence of malignancy or chronic disease in advanced stages, difficulty in understanding the proposed questionnaires, and refusal to take part in the study; moreover, only for the internal medicine patients, the presence of a Axis I psychiatric illness according to DSM-IV or the intake of psychopharmacological treatment were exclusion criteria. Statistical Analysis The effect of MetS diagnosis in terms of specific anthropometric measurements, biochemical and sociodemographic differences between the two groups of patients, were analyzed using the statistical program SPSS version 17 for Windows. The characteristics of the subjects are expressed as mean ± standard deviation for continuous variables and as frequency (percentages) for categorical variables. Within the two study populations, we selected psychiatric and internal medicine patients with full criteria for MetS (2005 ATPIII definition) as a grouping factor for the analyses. The differences in parameters between the two patient groups were calculated by Student’s t-test for continuous variables and by c2 test for dichotomous variables. The relationship between pairs of metabolic parameters was assessed by Pearson’s correlations. A univariate analysis of variance (ANOVA) was conducted for the difference between mean values to increasing MS criteria number in each population of the study. A factorial ANOVA with multiple comparisons for Bonferroni also enabled us to evaluate potential differences in metabolic parameters between three major psychiatric diagnoses. A P value of two tails of less than 0.05 was considered statistically significant. RESULTS Table 1 stratifies the two study populations on the number of MetS criteria satisfied, as defined by NCEP ATPIII. The frequency of MetS was 56.5% among psychiatric patients and 66.3% among internal medicine patients; no differences were found between the two population number and gender. Table 2 shows the distribution of psychiatric diagnosis on the basis of MetS criteria. MetS diagnosis was positive in 74% of Bipolar Disorder patients, in 46% of Schizophrenic-Schizoaffective patients, and in 50% of both Major Depression and other psychiatric patients without any statistical difference of distribution


207

Table 1. Distribution of the Two Study Populations on the Basis of MetS Criteria [33] Internal medicine N N criteria (mean ± SD) 1 (%)

Psychiatric patients

p Value

77

83

n.s.

2.90 ± 1.07

2.75 ± 0.89

n.s.

9 (11.7%)

4 (5%)

n.s.

2 (%)

17 (22%)

32 (38.5%)

n.s.

3 (%)

28 (36.4%)

30 (36.1%)

n.s.

4 (%)

19 (24.7%)

15 (18%)

n.s.

5 (%)

4 (5.2%)

2 (2.4%)

n.s.

(p = 0.16). We did not find any statistically significant difference even when the distribution by psychiatric diagnosis of each criterion of MetS was considered. Schizophrenia-Schizoaffective diagnosis was more common in males (n = 19 vs. n = 5, p = 0.004), Major Depression diagnosis was less common in males (n = 2 vs. n = 12, p = 0.001). The other two diagnoses were equally distributed between genders (Bipolar Disorder n = 12 vs. n = 15, n.s.; other n = 12 vs. n = 6, n.s.). Table 3 shows the values of metabolic parameters of each study population. Psychiatric and internal medicine patients showed significant differences in age (47 yrs ± 9 yrs vs. 52 yrs ± 8.6 yrs), abdominal circumference (111.9 ± 10.9 vs. 106 ± 12.6), HDL cholesterol (36.8 ± 7 vs. 48 ± 11.3), fasting insulin (26 ± 12.5 vs. 16.4 ± 8.8). The differences in abdominal circumference, TG, fasting insulin, HOMA index, and TG/HDL ratio were evident in the female gender of the psychiatric population. The Framingham risk index was lower in male psychiatric patients (10.8 ± 6 vs. 14.6 ± 5.3). HDL cholesterol was lower in male and female psychiatric patients. ALT was higher in psychiatric females only (38 ± 14 vs. 47 ± 14.8) and SBP and DBP were higher in the internal medicine females. Hypertension is the most frequent criterion in the internal medicine population and was statistically more frequent in the previously mentioned than in psychiatry (92% vs. 68%), both in males (95.5% vs. 72%, p = 0.03) and females (89.7% vs. 64%, p = 0.02). All hypertensive internal medicine patients and 17% (n = 14) of the psychiatric ones were on pharmacological treatment for hypertension. The rate of visceral obesity, which is the most frequent criterion in psychiatric patients, did not differ between the two populations (84.3% vs. 95.7%); hyperglycemia was more common in internal medicine than psychiatry (64.7% vs. 40.4%, p = 0.02), where it is the less frequent criterion and 13% (n = 11) of psychiatric patients are on anti-diabetic treatment); in terms of frequency, hypertriglyceridemia was the fourth most frequent criterion in both

13 (54%) 17 (71% 7 (29%) 10 (42%) 14 (58%) 11 (46%)

Description

Hypertension

Visceral obesity

Hyperglycemia

Hyper TG

Low HDL cholesterol

At least three of MetS1-MetS5

Criterion

MetS1

MetS2

MetS3

MetS4

MetS5

MetS

p Value n.s. n.s. n.s. n.s. n.s. n.s.

Total (N = 83) 47 (57%) 69 (83%) 25 (30%) 35 (42%) 52 (63%) 47 (57%)

Othera (N = 18) 11 (61%) 15 (83%) 3 (17%) 8 (44%) 11 (61%) 9 (50%)

Major depression (N = 14) 5 (36%) 13 (93%) 2 (14%) 7 (50%) 10 (71%) 7 (50%)

Bipolar disorder (N = 27) 18 (66%) 24 (89%) 13 (48%) 10 (37%) 17 (63%) 20 (74%)

aOthers: Psychosis Nos, Anxiety disorders, and Personality disorders.

Schizophrenia (N = 24)

Table 2. Distribution of Psychiatric Diagnosis on the MetS Criteria



209

populations (56.9% vs. 59.6%). The low HDL cholesterol was more common in the psychiatric population (76.6% vs. 51%, p = 0.01); this difference was due to the higher prevalence in psychiatric females (95.5% vs. 48.3%, p = 0.00001). Furthermore, psychiatric patients resulted to consume alcoholic beverages more frequently (27% vs. 5%, p = 0.0001) and to smoke cigarettes (53% vs. 17%, p = 0.0001) in comparison to the internal medicine subjects in both sexes. Neither smoking habits nor alcoholic consumption was related to the lower values of HDL cholesterol in the psychiatric population. HDL values were lower than those observed in the internal medicine population for each of the psychiatric diagnosis class (data not shown). Pearson’s analysis on the whole sample of psychiatric patients with at least one criterion for MetS, showed that the MetS criteria numbers are positively correlated with: waist circumference (r = 0.40, p = 0.0002), BMI (r = 0.32, p = 0.002), TG (r = 0.44, p = 0.00003), fasting plasma glucose (r = 0.47, p = 0.00001), insulin levels (r = 0.42, p = 0.0002), HOMA value (r = 0.46, p = 0.00001), Framingham score (r = 0.30, p = 0.006), and TG/HDL ratio (r = 0.51, p = 0.00001), and negatively correlated with HDL cholesterol (r = –0.48, p = 0.00001); age had positive correlation with fasting glucose levels (r = 0.26, p = 0.02) and HOMA value (r = 0.59, p = 0.00001); waist circumference had a positive correlation with BMI (r = 0.84, p = 0.00001), insulin levels (r = 0.48, p = 0.00003) and TG/HDL (r = 0.29, p = 0.01), while it had a negative correlation with HDL levels (r = –0.24, p = 0.004); BMI had a positive correlation with insulin levels (r = 0.39, p = 0.001); LDL levels presented a positive correlation with insulin concentration (r = 0.27, p = 0.04); HDL levels had a negative correlation with insulin levels (r = –0.37, p = 0.003); TG levels correlated positively with insulin concentration (r = 0.32, p = 0.007); TG/ HDL ratio presented a positive correlation with insulin levels (r = 0.4, p = 0.001). Pearson’s analysis within the MetS sample of psychiatric patients showed that the MetS criteria numbers are positively correlated with age (r = 0.44, p = 0.002), fasting plasma insulin levels (r = 0.36, p = 0.03), fasting plasma glucose (r = 0.57, p = 0.0001), glycated hemoglobin (r = 0.50, p = 0.002) and HOMA value (r = 0.48, p = 0.001) and negatively correlated with HDL levels (r = –0.37, p = 0.01); age was positively correlated with the HOMA value (r = 0.67, p = 0.0001) and Framingham score (r = 0.33, p = 0.02); waist circumference had positive correlation with BMI (r = 0.82, p = 0.0001); HOMA value had a weak positive correlation with the Framingham score (r = 0.29, p = 0.04). The comparison of metabolic parameters on the basis of psychiatric diagnosis showed that patients affected by Bipolar Disorder seem to be older than Schizophrenic patients even if this difference does not reach the statistical significance (Table 4a). The same analyses applied to the MetS psychiatric population highlighted that TG and TG/ HDL ratio values of the Major Depression patients were higher than those observed in Schizophrenic and Bipolar patients (Table 4b). The distribution of treatments in both all and MetS psychiatric population is showed in Tables 5a and 5b. We have evaluated the association between clinical

0.037 0.160 0.462

77.5 ±9.7 192 ± 40 130 ± 33.6 137.5 ± 38

0.692 0.430

129.6 ± 10 84 ± 6.9

131 ± 19 86 ±11 195 ± 36.9

0.06 0.06 0.11

127 ± 10 80.9 ± 8.9

Systolic blood pressure (mmHg) 133.5 ± 20

0.002 0.908

178 ± 86 109 ± 34.7 111.1 ± 66

6.14 ± 1.29

24 ± 11.8 0.121 5.4 ± 0.59 0.001

0.00 0.07

26 ± 12.5 5.7 ± 1.05

6.2 ± 1.1

Glycosylated hemoglobin (%)

6.3 ± 0.89

15 ± 8

102.8 ± 24.5 0.251 111 ± 24 18.6 ± 9.8

0.67

106.7 ±48

110 ± 30 16.4 ± 8.8

6.2 ± 1.4

0.904

28.8 ± 13.3 0.000

0.000 37.6 ± 7 52 ± 11.4 115 ± 53

Insulinemia (mU/ml)

0.557

Glycemia (mg/dl)

0.011

184 ± 86.9 169.96 ± 78

0.07

36 ± 7

42.5 ± 8.7

0.00

Triglyceride (mg/dl)

36.8 ± 7

48 ± 11.3

HDL_cholesterol (mg/dl)

0.871

0.481 206.5 ±31 127 ± 38

173.7 ± 81

128 ± 31.9

LDL_cholesterol (mg/dl)

144.8 ± 77

189 ± 43.5 132.5 ± 37.9

201.6 ± 33.7

Tot_cholesterol (mg/dl)

186.4 ± 47

0.035 135 ± 20.8 124.7 ± 9.7

0.757

31.92 ± 4

0.46

32.8 ± 4.8

32 ± 5.7

Body Mass Index (kg/m2)

0.54 125.7 ± 30

0.188

0.566

110.8 ± 9

109 ± 11 32.4 ± 5.9

0.02

111.9 ± 10.9

106 ± 12.6

Waist circumference (cm)

84 ± 11.8

113 ± 12.7 0.019 33.9 ± 5.5

104 ± 13 31.9 ± 5.5

0.266

97 ± 20

0.88

89 ± 21

Weight (kg)

85 ± 11.5

0.026 46 ± 9

87.6 ± 16.4 0.460

52 ± 9 83.6 ± 20.5

0.032

47 ± 9 91.92 ± 11

53 ± 8.2

0.00

47 ± 9 89.9 ± 13.9

52 ± 8.6

Mean age (years)

Diastolic blood pressure (mmHg)

p


Internal medicine

p


Internal medicine

p

Women (N = 51)


Men (N = 47)

Internal medicine

All patients (N = 98)

Table 3. Results of Bioantropometric Variables in the Two MetS Population (Internal Medicine vs. Psychiatric Patients) by Gendera


0.177 0.005 0.050

7.8 ± 5 5.36 ±3.8

5.02 ± 3.17 0.000

0.089 112.6 ± 72.9 3.8 ±3.3 7.7 ±4.5 2.3 ±1.3

0.070 0.031 0.943

5.98 ± 3.7 10.8 ± 6 4.5 ± 2.1

3.9 ± 3.2 14.6 ± 5.3 4.59 ± 2.4

0.13 0.05 0.01

6.7 ± 4.4 8.3 ± 5.8 4.8 ± 2.7

3.9 ± 3.2 10.7 ± 5.9 3.3 ± 2.2

0.209 0.017 0.490 0.000

14 (64%) 22 (100%) 7 (31.8%) 12 (54.5%) 21 (95.5%)

26 (89.7%) 27 (93%) 19 (65.5%) 13 (44.8%) 14 (48.3%0

0.079 0.280 0.520 0.706

18 (72%) 23 (92%) 12 (48%) 16 (64%) 15 (60%)

21 (95.5%) 16 (72.7%) 14 (63.6%) 16 (72.7%) 12 (54.5%)

0.06 0.02 0.78 0.01

32 (68.1%) 45 (95.7%) 19 (40.4%) 28 (59.6%) 36 (76.6%)

47 (92%) 43 (84.3%) 33 (64.7%) 29 (56.9%) 26 (51%)

Hypertension

Visceral obesity

Hyperglycemia

Hyper triglyceride

Low HDL cholesterol

aValues are expressed as M ± SD and as distribution of frequency, n (%).

n.s. 0.025

22 (47%) 29 (57%)

n.s. 0.033

25 (53%)

22 (43%)

n.s. 0.00

47 (48%)

51 (52%)

Metabolic syndrome

TG/HDL

Framingham score

HOMA

0.503

55 ± 68 85.7 ± 62

43.5 ± 53.9

61 ± 42.8 0.472

0.29 138.11 ± 76.2 246.2 ± 247

171 ± 200

CPK (U/I)

53 ± 26.8

0.29

47.47 ± 44.78 58.30 ± 55.6

GGT (U/I) 122.48 ± 74.4

0.277

38 ± 14

56.6 ±26

0.19

51.9 ± 25.1

ALT (U/I)

47 ± 14.8 0.035

24.3 ± 8.6

21.5 ± 9.7

0.301

56 ± 31.2 0.971

25.25 ± 8.4

0.10

27.7 ± 17.3

23 ± 9.3 45.6 ± 21.8

AST (U/I)

30.7 ± 22

0.117

4.2 ±1.16

4.8 ± 1.1

5.4 ± 1.06 0.630

5.6 ± 1.2

0.32

4.9 ± 1.2

5.1 ± 1.2

Acid uric (mg/dl)

METABOLIC SYNDROME / 211

0.081 0.060 0.475 0.485 0.192 0.349 0.858 0.743

2.61 2.57 0.84 0.82 1.62 1.11 0.25 0.42

2.74 46.00 106.28 30.94 125.28 81.11 178.61 119.69

2.64 104.43 30.07 118.93 77.86 187.36 127.07

110.52 32.30 126.30 80.56 173.85 114.25

106.63 30.29 127.08 83.13 179.79 126.20

Waist circumference (cm) (kg/m2)

Systolic blood pressure (mmHg)





0.905 0.563 0.437 0.622 0.251 0.513 0.072 0.349

0.19 0.69 0.92 0.59 1.40 0.77 2.42 1.11

39.69 141.39 90.50 25.00 5.67 5.15 9.22 3.81

39.64 174.36 94.00 17.92 6.58 3.96 4.79 4.93

41.42 141.52 108.44 22.83 5.74 6.07 9.74 3.38

39.70 97.17 20.82 5.36 4.81 7.50 3.55

Glycemia (mg/dl)

Insulinemia (mU/ml)


HOMA

Framingham score

TG/HDL

aOthers: Psychosis Nos, Anxiety disorders, and Personality disorders.


138.79

Body Mass Index

Mean age (years)

N criteria 44.00

p

F

3.07

Othersa (N = 18)

50.00

Major depression (N = 14)

2.54

Bipolar disorder (N = 27)

43.38


Table 4a. Comparison by ANOVA of Metabolic Parameters Values on the Basis of Psychiatric Diagnosis in the Whole Psychiatric Population (N = 83)


32.36

(kg/m2)

6.243 8.09 4.1

HOMA

Framingham score

TG/HDL

4.05

9.05

7.636

5.9375

27.625

114.65

163.25

37.58

127.23

181.6

80.75

128.5

33.5

114.1

48.75

3.5

Bipolar disorder (N = 20)

7.85

4.14

5.308

5.8

24

98.85

260.85

36.14

145.14

201.14

78.57

124.28

31.85

109.142

42.42

3.42

Major depression (N = 7)

aOthers: Psychosis Nos, Anxiety disorders, and Personality disorders. bMajor Depression vs. Schizophrenia p = 0.013; Major Depression vs. Bipolar Disorder p = 0.027. cMajor Depression vs. Schizophrenia p = 0.023; Major Depression vs. Bipolar Disorder p = 0.009.

5.4


24.8

103.72

Glycemia (mg/dl)

Insulinemia (mU/ml)

143.81

35.7



135.7


83.63 194.09



128.63

Systolic blood pressure (mmHg)

Body Mass Index

112.09

44.9

3.27


Mean age (years)

N criteria


4.78

10.00

6.36

5.80

27.20

98.89

165.89

37.22

129.33

190.78

80.00

125.56

32.89

109.00

47.33

3.32

Othersa (N = 9)

Table 4b. Comparison by ANOVA of Metabolic Parameters Values on the Basis of Psychiatric Diagnosis in the MetS Psychiatric Population (N = 47)

4.31

1.64

0.43

0.52

0.16

0.32

3.99

0.17

0.39

0.41

0.52

0.43

0.24

0.61

1.03

0.59

F

0.010c

0.195

0.733

0.669

0.922

0.810

0.014b

0.917

0.758

0.745

0.669

0.730

0.867

0.611

0.390

0.560

p

METABOLIC SYNDROME / 213


Table 5a. Effect of Different Psychopharmacological Treatments on Metabolic Parameters in the Whole Psychiatric Population (N = 83) Mood stabilizers N = 51 (61%) Intake

Antidepressant N = 27 (33%)

Yes

No

29:22

16:16

N criteria

2.74 ± 0.89

2.75 ± 0.92

0.98

3±1

2.62 ± 0.82 0.07

Mean age (years)

44.76 ± 9.08

48.5 ± 9.72

0.08

48.55 ± 9.89

45.07 ± 9.10 0.11

M:F

p

108.27 ± 13.16 106.12 ± 12.57 0.46 Waist circumference (cm) Body Mass Index (kg/m2) Systolic blood pressure (mmHg) Diastolic blood pressure (mmHg) Tot_cholesterol (mg/dl)

31.34 ± 5.22

30.55 ± 5.43

0.51

Yes

No

6:5

39:33

p

106.85 ± 13.32 107.73 ± 12.81 0.77

30.52 ± 4.89

31.28 ± 5.49 0.54

122.54 ± 10.88 129.06 ± 12.41 0.013 122.77 ± 11.12 126.16 ± 12.14 0.22

79.6 ± 7.54

83.12 ± 10.06 0.07

176.13 ± 41.28 183.25 ± 54.77 0.5

80 ± 10.10

81.42 ± 8.02 0.48

193.29 ± 37.76 171.92 ± 49.32 0.05

LDL_cholesterol 114.47 ± 35.89 130.76 ± 47.14 0.09 130.615 ± 38.97 115.91 ± 42.02 0.14 (mg/dl) HDL_cholesterol (mg/dl) Triglyceride (mg/dl) Glycemia (mg/dl) Insulinemia (mU/ml)

39.47 ± 7.96

41.36 ± 10.77 0.38

155.82 ± 87.37 130.96 ± 65.77 0.17

39.73 ± 9.63

40.52 ± 9.02 0.72

177.59 ± 83.37 131.12 ± 74.81 0.012

95.6 ± 21.86 104.03 ± 56.14 0.33

105.88 ± 60.83 95.46 ± 21.23 0.25

22.93 ± 15.28 19.69 ± 11.20 0.35

21.04 ± 13.19 22.02 ± 14.32 0.78 5.7 ± 1.89


5.71 ± 1.88

5.73 ± 1.23

0.95

5.75 ± 1.03

HOMA

5.13 ± 3.67

5.14 ± 4.74

0.99

5.38 ± 4.60

5.02 ± 3.85 0.73

Framingham score

7.66 ± 5.98

8.9 ± 6.32

0.37

9 ± 7.09

7.73 ± 5.59 0.38

TG/HDL

3.95 ± 2.75

3.56 ± 2.42

0.54

5.01 ± 3.35

0.91

3.13 ± 1.83 0.002


Neuroleptics N = 56 (67%)

215

Antipsychotics N = 35 (42%)

Yes

No

28:28

17:10

2.82 ± 0.94

2.59 ± 0.80

45.69 ± 8.41

p

Yes

No

p

29:6

16:32

0.27

2.71 ± 0.89

2.77 ± 0.90

0.77

47.25 ± 11.42

0.48

44.97 ± 10.65

47.1 ± 8.48

0.31

108.58 ± 13.73

105.07 ± 10.85

0.24

105.77 ± 10.01

108.66 ± 14.64

0.31

31.49 ± 5.71

30.08 ± 4.20

0.25

30.21 ± 4.05

31.64 ± 6.00

0.22

125.53 ±11.78

124.07 ± 12.17

0.6

125.57 ± 12.53

124.68 ± 11.46

0.74

80.89 ± 8.74

81.11 ± 8.81

0.91

81.42 ± 8.10

80.62 ± 9.20

0.68

184.3 ± 50.95

167.62 ± 34.74

0.12

175.81 ± 43.68

181.12 ± 49.19

0.61

125.78 ± 43.44

109.95 ± 34.14

0.13

120.44 ± 45.08

121.44 ± 39.49

0.92

40.59 ± 9.17

39.4 ± 9.36

0.61

37.81 ± 7.08

41.63 ± 10

0.08

156.87 ± 89.89

124.18 ± 49.62

0.08

141.57 ± 69.62

149.64 ± 87.73

0.65

103.28 ± 45.40

89.66 ± 15.53

0.13

95.51 ± 18.52

101.29 ± 48.52

0.5

22.28 ± 12.36

20.62 ± 16.61

0.63

22.15 ± 15.46

21.3 ± 12.47

0.8

5.69 ± 1.07

5.76 ± 2.42

0.86

5.77 ± 2.17

5.67 ± 0.99

0.8

5.62 ± 4.35

4.22 ± 3.40

0.17

4.92 ± 3.79

5.33 ± 4.36

0.68

7.58 ± 5.39

9.29 ± 7.35

0.23

9.14 ± 6,48

7.41 ± 5.78

0.2

4.04 ± 2.90

3.21 ± 1.65

0.21

3.42 ± 1.51

4.01 ± 3.06

0.35


Table 5b. Effect of Different Psychopharmacological Treatments on Metabolic Parameters in the MetS Psychiatric Sample (N = 47) Mood stabilizers N = 31 (66%) Intake M:F

Yes

No

17:14

8:8 3.5 ± 0.73

Antidepressant N = 18 (38%) p

0.42

Yes

No

8:10

17:12

3.55 ± 0.70

p

3.31 ± 0.47 0.15

N criteria

3.35 ± 0.49

Mean age (years)

45.13 ± 7.96


112.8 ± 11.3 110.19 ± 10.36 0.44 111.83 ± 11.44 111.96 ± 10.83 0.96

Body Mass Index (kg/m2)

33.13 ± 4.81

Systolic blood pressure (mmHg) Diastolic blood pressure (mmHg) Tot_cholesterol (mg/dl)

49.56 ± 10.44 0.11

32.37 ± 5.03 0.62

47.83 ± 10.51 45.89 ± 8.07 0.48

32 ± 4.80

33.41 ± 4.88 0.33

125.32 ± 10.24 131.25 ± 9.03 0.06 123.88 ± 10.36 129.48 ± 9.57 0.06

80.48 ± 7.46

81.87 ± 11.38 0.61

79.72 ± 10.06 81.72 ± 8.16 0.45

182.77 ± 43.68 201.62 ± 41.84 0.16 201.66 ± 36.19 181.44 ± 46.46 0.12

LDL_cholesterol 124.25 ± 35.55 146.56 ± 38.86 0.06 137.88 ± 37.20 128.72 ± 38.78 0.44 (mg/dl) HDL_cholesterol (mg/dl) Triglyceride (mg/dl)

37.18 ± 6.08

36.25 ± 8.77 0.68

36.77 ± 7.84

36.88 ± 6.69 0.96

178.06 ± 87.54 165.37 ± 68.58 0.62 216.38 ± 72.36 147.27 ± 75.60 0.003

Glycemia (mg/dl) 101.64 ± 23.72 116.56 ± 73.36 0.32 114.94 ± 72.97 101.62 ± 22.51 0.36 26.21 ± 13.85 26.31 ± 11.86 0.98

Insulinemia (mU/ml)

27.5 ± 12.79 23.83 ± 11.98 0.42


5.71 ± 0.81

5.83 ± 1.47

0.74

6.07 ± 1.27

HOMA

6.61 ± 3.51

7.02 ± 5.97

0.79

7.1 ± 4.98

6.52 ± 4.10 0.7081

Framingham score

7.58 ± 5.11

9.62 ± 6.94

0.26

8.27 ± 6.96

8.27 ± 5.08 0.99

TG/HDL

4.77 ± 2.80

4.93 ± 2.76 0.85

6.44 ± 3.27

3.68 ± 1.54 0.0006

5.54 ± 0.86 0.15


Neuroleptics N = 33 (70%)

217

Antipsychotics N = 18 (38%)

Yes

No

15:18

10:4

3.48 ± 0.56

3.21 ± 0.57

46.09 ± 6.69

47.92 ± 13.24

p

Yes

No

p

16:2

9:20

0.14

3.44 ± 0.61

3.38 ± 0.56

0.71

0.53

47.27 ± 9.41

46.24 ± 8.41

0.7

113.84 ± 11.68

107.35 ± 7.51

0.06

108.33 ± 6.47

114.13 ± 12.57

0.07

33.39 ± 5.28

31.64 ± 3.47

0.26

31.27 ± 3.12

33.86 ± 5.48

0.07

126.21 ±10.60

130 ± 8.77

0.24

129.44 ± 8.02

126.03 ± 11.21

0.27

80.3 ± 9.43

82.5 ± 7.53

0.44

82.5 ± 3.12

80 ± 5.48

0.35

196.63 ± 44.02

171.64 ± 38.30

0.07

180.27 ± 47.06

194.72 ± 41.09

0.27

138.43 ± 37.45

119 ± 36.96

0.12

128.6 ± 40.94

134.68 ± 36.86

0.62

38.07 ± 8.07

0.12

37.23 ± 7.45

35.92 ± 6.42

0.58

34.53 ± 4.12

187.72 ± 88.09

140.78 ± 49.70

0.06

162.05 ± 78.27

181 ± 83.23

0.44

113.57 ± 55.51

90.57 ± 14.90

0.13

101.16 ± 17.60

110.17 ± 59.91

0.54

28.28 ± 12.47

21.72 ± 11.79

0.14

25.64 ± 12.40

26.84 ± 12.86

0.78

5.88 ± 1.2

5.45 ± 0.52

0.27

5.5 ± 0.62

6 ± 1.3

0.13

7.73 ± 4.67

4.51 ± 2.76

0.042

6.09 ± 3.89

7.33 ± 4.84

0.4

7.45 ± 4.33

10.21 ± 8.20

0.13

10.5 ± 5.96

6.89 ± 5.34

0.037

5.2 ± 3.07

4 ± 1.63

0.19

4.2 ± 1.42

5.17 ± 3.23

0.27


and metabolic parameters and the type of psychopharmacological treatment for Mood Stabilizers, Antidepressants, Neuroleptics, and Antipsychotics. Table 5a shows that in all psychiatric patients TG concentrations and TG/HDL ratio were higher in the patients assuming antidepressants and that SBP was lower in subjects treated with mood stabilizers. In the Table 5b we confirmed that TG levels and TG/HDL ratio were higher in patients assuming antidepressant and we also found higher values of HOMA index in patients assuming neuroleptics and higher Framingham index in the patients under antipsychotic treatment. DISCUSSION In the complex and contradictory background of literature about the relationship between psychiatric disease and MetS, in this study we demonstrated distinctive differences in bio-anthropometric features between a group of internal medicine patients and psychiatric patients affected by Metabolic Syndrome. The first important finding of our study was the lower mean age in the psychiatric sample in comparison to the internal medicine patients in both genders according to previously published data both in schizophrenic and bipolar patients affected by MetS [3, 9, 28, 39]. The mean age of our psychiatric sample is also in line with the mean age of general inpatient population reported in the Psychiatric Units in Italy [40]. The development of MetS in psychiatric patients at a younger age than in the internal medicine settings may also result from the presence of specific risk factors for MetS described only for the psychiatric population, such as the effect of the illness itself, food intake, energy expenditure, neuroendocrine dysregulation, and psychotropic medications [41]. We can deduce that a systematic screening for the MetS in psychiatric patients is necessary even when patients have only one criterion for MetS, regardless of the age. Consistently with the previous studies [42], elevated abdominal circumference was the most frequent criterion found in the psychiatric sample of our study (95.7%), followed by low HDL cholesterol (76.6%) (about 95.5% of females meet this criterion) and hypertension (68.1%). In contrast, the most frequent criterion in internal medicine was hypertension (92%) followed by hyperglycemia and abdominal obesity. Therefore, it seems that MetS in psychiatric patients is characterized by an elevated prevalence of lipidic alterations and visceral obesity associated to insulin resistance. Our findings showed that HDL cholesterol is lower in males and female psychiatric patients, while abdominal circumference, TG, fasting insulin, HOMA index, and TG/HDL ratio were higher only in the female gender of psychiatric population in comparison to the internal medicine sample. Lower values of HDL cholesterol were evident not only in the psychiatric sample as a whole but also in each psychiatric diagnostic group and were


219

independent from exogenous affecting factors such as cigarette smoking, alcohol use, and drug treatments. Unfortunately, we did not collect specific data on the formal dietary habits and the physical activity style that some author has shown to have some influence on the development of visceral obesity [43]. HDL cholesterol levels were significantly and inversely correlated to insulin levels and to abdominal circumference. This data was especially evident in the female gender. Literature discusses whether lipid metabolism is altered in psychiatric patients. For instance, the results of some of the most extensive studies suggested inverse relationships between high-density lipoprotein cholesterol and depressive symptomatology in females, and this effect seems to be sex-specific [44-46]. More recently, Shively et al. showed a relationship between depressive behavior, HDL cholesterol, and coronary atherogenesis in adult females cynomolgus monkeys that underwent a 52-month diet containing a moderate amount of fat and cholesterol [47]. Conversely, D’Ambrosio et al. [48] did not support the hypothesis of a strong association between serum lipid levels (LDL-C, HDL-C, TG) and suicide in patients with bipolar disorder. Furthermore, the presence of low HDL cholesterol levels in patients affected by schizophrenia treated with antipsychotics agents seems to be proven [29, 49]. Finally, Beumer et al., have recently showed the association between schizophrenia and Metabolic Syndrome as a consequence of alterations in the levels of cytokines, chemokines, and adipokines resulting in the activation of the monocyte/macrophage system [50]. Nevertheless, in most of these studies a valid pathogenetic hypothesis of the presence of low HDL cholesterol levels is not reported. In our study, the prevalence of MetS in psychiatric patients seemed to be independent from the diagnosis of the main psychiatric syndromes enclosed, suggesting that a common underlying pathogenetic mechanism may be hypothesized. Several pathogenetic factors have been described to correlate depression and schizophrenia to MetS: activation of chronic inflammation [51] and of the cytokine network [52, 53]; altered activity of the hypothalamic-pituitaryadrenocortical axis [54] and hypercortisolemia [55, 56]; hyperprolactinemia is associated with many components of MetS in patients that are neither psychotic nor taking antipsychotic medication: reduced insulin sensitivity, increased serum insulin, glucose, C-Reactive Protein, and homocysteine levels and lower serum HDL cholesterol [57]; alterations of autonomic nervous system, inflammatory and neurotransmitter system activity [58]; duration and type of treatment in patients with a first episode of psychosis [59]; effect of genetic polymorphism [60]; alterations of dietary and physical activity habits [61]. Moreover, the female gender could be another risk factor for MetS since the higher prevalence of overweight, insulin resistance, and reduced HDL cholesterol in psychiatric female patients in comparison to psychiatric male patients in our study, could be


attributable to the influence of sex-related hormonal alterations such as those of the hypothalamic-pituitary-gonadal axis [62]. Another important finding of our study was that TG and TG/ HDL ratio values were higher in depressed patients (mainly females) than those observed in Schizophrenic and Bipolar Disorder patients. This is in line with literature since positive association is most often reported between depression and central obesity/body mass index or HDL cholesterol and triglycerides [63, 64]. The relationship between fasting triglycerides and high density lipoproteins TG/ HDL > 3 could become an indicator and predictor of insulin resistance [30]. It could mean that dyslipidemia in terms of TG value and TG/HDL index is due to Major Depression diagnosis more than antidepressant medication. Interestingly, we found that internal medicine and psychiatric patients had a similar Framingham index, despite a very large age difference and metabolic parameters. This index has been widely used and validated in different populations to predict a cardiovascular risk in 10 years including angina, myocardial infarction, and cardiac death [31]. The difference of the Framingham score (more evident for internal medicine males) could probably be attributable to the prevalence of hypertension and hyperglycemia in the older internal medicine population; for the younger population of the psychiatric patients it is probably due to HDL cholesterol and to the smoking habit. As expected, the proportion of smokers (not presented) was three times higher in the psychiatric population (53% vs. 17%), considering the greater vulnerability to nicotine dependence in this population, as reported in the literature [65]. The studies regarding the influence of a pharmacological treatment on metabolic parameters are controversial [66, 67]. In our psychiatric population we found that TG and TG/HDL ratio are higher in patients assuming antidepressants and that HOMA index and the Framingham risk are higher in patients receiving neuroleptic and antipsychotic treatments. Moreover, in our study neuroleptic and antipsychotic treatments were not related to a diagnosis group. We have not found correlation between any diagnostic group and psychotropic drugs probably due to the features of our sample; in fact, our psychiatric population was not selected for diagnosis or pharmacotherapy. According to literature, people with severe mental illness treated with antipsychotics have increased both metabolic dysfunction and risk for cardiovascular disease [68]. Although elevation in CVD risk factors is due in part to unhealthy lifestyles and lower primary care quality in people with severe mental illness, atypical antipsychotics likely contribute substantially to increasing CVD risk factors through weight gain, glucose dysregulation, and lipid abnormalities [69, 70]. These differences in individual antipsychotic drug effects on CVD risk in the CATIE study appear to be due principally to changes in total and HDL cholesterol [71]. If replicated, identification of physiologic or molecular mechanisms underlying race differences in antipsychotic effects on HDL cholesterol


221

will be of considerable interest. The mechanisms for antipsychotic-related dyslipidemia are not fully understood. Certainly weight gain and glucose intolerance are well known to increase risk of hyperlipidemia, yet we also know that these factors are not necessary for antipsychotic-induced adverse changes in lipid profiles to occur [72]. Finally, we have found that psychiatric patients receiving neuroleptics had higher HOMA index than patients that did not receive them. Neuroleptics are the most frequent drugs taken by our psychiatric sample (70%) after benzodiazepines in line with the literature data [40]. In the previous studies, the insulin resistance would have been attributed to the antipsychotics assumption. This result would have been surprising if it was not related to the action of the neuroleptic medications on the tuber-infundibular pathway. It is reported that hyperprolactinemia due to first or second generation antipsychotics may decrease insulin sensitivity [73]. In conclusion, this is a real world setting study that investigated MetS in psychiatric acute inpatients compared to internal medicine control group. The comparison between the two high risk groups for CVD aims to identify specific anthropometric, biochemical, and sociodemographic features so that prevention and care of psychiatric patients physical comorbidity could improve. Consistently with previous studies, MetS scored very high in the psychiatric group, confirming that people with severe mental illnesses hold an increased CVD risk. Additionally, we found that MetS parameters has no different features among the psychiatric diagnostic groups considered and it develops at a lower mean age than observed in internistic patients. We can deduce that a systematic screening for the MetS in psychiatric patients is necessary, even when patients have only one criterion for MetS, regardless of the age. MetS in psychiatric patients is also characterized by an elevated prevalence of lipidic alterations and visceral obesity, both associated to insulin resistance. Results give support to the role of HDL cholesterol as one of the main components of MetS altered lipid profile, since it turned out to be significantly lower in the whole psychiatric sample and without difference by psychiatric diagnosis. HDL was also not related neither to smoking habits nor to alcoholic use but inversely correlated to insulin levels and to waist circumference, especially in female gender. However, no mechanism by itself may explain the relationship we found between each major psychiatric diagnosis and different drug treatments and some specific features of MetS. Anthropometric and biochemical features in a MetS psychiatric population are different from an internal medicine population, so that many factors may involve several common physiological pathways that need further research. Limitations of our study include the numerous psychiatric study populations for each diagnosis and potential differences linked to the duration of the illness and drug treatment.


REFERENCES 1. Bjontorp P, Rosmond R. Neuroendocrine abnormalities in visceral obesity. International Journal of Obesity Related Metabolic Disorders 2000;24(Suppl 2):S80-S85. 2. Moller DE, Kaufman KD. Metabolic syndrome: A clinical and molecular perspective. Annual Review of Medicine 2005;56:45-62. 3. Palmieri VO, Grattagliano I, Portincasa P, Palasciano G. Systemic oxidative alterations are associated with visceral adiposity and liver steatosis in patients with metabolic syndrome. Journal of Nutrition 2006;136(12):3022-3026. 4. Heald A. Physical health in schizophrenia: A challenge for antipsychotic therapy. European Psychiatry 2010;25(2):S6-S11. 5. De Hert M, Correll CU, Bobes J, Cetkovich-Bakmas M, Cohen D, Asai I, Detraux J, Gautam S, Möller HJ, Ndetei DM, Newcomer JW, Uwakwe R, Leucht S. Physical illness in patients with severe mental disorders. I. Prevalence, impact of medications and disparities in health care. World Psychiatry 2011;10(1):52-77. 6. Colton CW, Manderscheid RW. Congruencies in increased mortality rates, years of potential life lost, and causes of death among public mental health clients in eight states. Prevention of Chronic Diseases 2006;3(2):A42. 7. Bobes J, Arango C, Garcia-Garcia M, Rejas J. Healthy lifestyle habits and 10-year cardiovascular risk in schizophrenia spectrum disorders: An analysis of the impact of smoking tobacco in the CLAMORS schizophrenia cohort. Schizophrenia Research 2010;119(1-3):101-109. 8. Ucok A, Polat A, Bozkurt O, et al. Cigarette smoking among patients with schizophrenia and bipolar disorders. Psychiatry in Clinical Neuroscience 2004;58(4): 434-437. 9. Fagiolini A, Frank E, Scott JA, et al. Metabolic syndrome in bipolar disorder: Findings from the Bipolar Disorder Center for Pennsylvanians. Bipolar Disorders 2005;7:424-430. 10. Hennekens CH, Hennekens AR, Hollar D, et al. Schizophrenia and increased risk of cardiovascular disease. American Heart Journal 2005;150(6):1115-1112. 11. Kilbourne AM, Cornelius JR, Han X, et al. Burden of general medical conditions among individuals with bipolar disorder. Bipolar Disorders 2004;6(5):368-373. 12. Goff DC, Sullivan LM, McEvoy JP, et al. A comparison of ten-year cardiac risk estimates in schizophrenia patients from the CATIE study and matched controls. Schizophrenia Research 2005;80(1):45-53. 13. Nasrallah HA. An overview of common medical comorbidities in patients with schizophrenia. Journal of Clinical Psychiatry 2005;66(Suppl. 6):3-4. 14. Cohn T, Prud’homme D, Streiner D, et al. Characterizing coronary heart disease risk in chronic schizophrenia: High prevalence of the metabolic syndrome. Canadian Journal of Psychiatry 2004;49(11):753-760. 15. Kato MM, Currier MB, Gomez CM, et al. Prevalence of metabolic syndrome in Hispanic and non-Hispanic patients with schizophrenia. Primary Care Companion Journal of Clinical Psychiatry 2004;6(2):74-77. 16. McEvoy JP, Meyer JM, Goff DC, et al. Prevalence of the metabolic syndrome in patients with schizophrenia: Baseline results from the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) schizophrenia trial and comparison with national estimates from NHANES III. Schizophrenia Research 2005; 80(1):19-32.


223

17. Meyer JM. Novel antipsychotics and severe hyperlipidemia. Journal of Clinical Psychopharmacology 2001;21(4):369-374. 18. Yumru M, Savas HA, Kurt E, et al. Atypical antipsychotics related metabolic syndrome in bipolar patients. Journal of Affective Disorders 2007;98(3):247-522. 19. Arango C, Bobes J, Aranda P, Carmena R, Garcia-Garcia M, Rejas J, CLAMORS Study Collaborative Group. A comparison of schizophrenia outpatients treated with antipsychotics with and without metabolic syndrome: Findings from the CLAMORS study. Schizophrenia Research 2008;104(1-3):1-12. 20. Reynolds GP, Kirk SL. Metabolic side effects of antipsychotic drug treatment— Pharmacological mechanisms. Pharmacological Therapy 2010;125(1):169-179. 21. Fava M, Judge R, Hoog SL, Nilsson ME, Koke SC. Fluoxetine versus sertraline and paroxetine in major depressive disorder: Changes in weight with long term treatment. Journal of Clinical Psychiatry 2000;61(11): 863-867. 22. Bowden CL, Calabrese JR, McElroy SL, Gyulai L, Wassef A, Petty F, Pope HG Jr, Chou JC, Keck PE Jr, Rhodes LJ, Swann AC, Hirschfeld RM, Wozniak PJ. A randomized, placebo-controlled 12-month trial of divalproex and lithium in treatment of outpatients with bipolar I disorder. Divalproex Maintenance Study Group. Archives of General Psychiatry 2000;57(5):481-489. 23. Thakore JH, Mann JN, Vlahos I, Martin A, Reznek R. Increased visceral fat distribution in drug-naive and drug-free patients with schizophrenia. International Journal of Obesity Related Metabolic Disorders 2002;26(1):137-141. 24. Lieberman JA 3rd. Metabolic changes associated with antipsychotic use. Primary Care Companion Journal of Clinical Psychiatry 2004;6(Suppl 2):8-13. 25. Heiskanen T, Niskanen L, Lyytikainen R, Saarinen PI, Hintikka J. Metabolic syndrome in patients with schizophrenia. Journal of Clinical Psychiatry 2003;64:575-579. 26. Ford ES, Giles WH, Dieta WH. Prevalence of the metabolic syndrome among US adults. Findings from the Third National Health and Nutrition Examination Survey. Journal of the American Medical Association 2002;287:356-359. 27. Kahl KG, Greggersen W, Schweiger U, Cordes J, Balijepalli C, Lösch C, Moebus S. Prevalence of the metabolic syndrome in unipolar major depression. European Archives of Psychiatry in Clinical Neuroscience 2011;262(4):313-320. 28. Basu R, Brar JS, Chengappa KN, et al. The prevalence of the metabolic syndrome in patients with schizoaffective disorder-bipolar subtype. Bipolar Disorders 2004;6: 314-318. 29. Ratliff JC, Palmese LB, Reutenauer EL, Srihari VH, Tek C. Obese schizophrenia spectrum patients have significantly higher 10-year general cardiovascular risk and vascular ages than obese individuals without severe mental illness. Psychosomatics 2012;54(1):67-73. 30. McLaughlin T, Abbasi F, Cheal K, Chu J, Lamendola C, Reaven G. Use of metabolic markers to identify overweight individuals who are insulin resistant. Annals of Internal Medicine 2003;139:802-809. 31. D’Agostino RB Sr, Vasan RS, Pencina MJ, Wolf PA, Cobain M, Massaro JM, Kannel WB. General cardiovascular risk profile for use in primary care: The Framingham Heart Study. Circulation 2008;117(6):743-753. 32. Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC. Homeostasis model assessment: Insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia 1985;28,412-419.


33. 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). Journal of the American Medical Association 2001;285(19):2486-2497. 34. First MB, Spitzer RL, Gibbon M, Williams JB. The structured clinical interview for DSM-IV Axis I disorders—Patients Edition (SCID-I/P, Version 2.0). New York: New York State Psychiatric Institute, 1996. 35. Overall JE, Gorham DR. The Brief Psychiatric Rating Scale. Psychology Report 1962;10:799-812. 36. Hamilton M. A rating scale for depression. Journal of Neurology and Neurosurgery Psychiatry 1960;23:56-62. 37. Spielberger CD, Gorsuch R, Lushene R. Manual for the state-trait anxiety inventory. Palo Alto, CA: Consulting Psychologist Press, 1970. 38. Hyler SE. Personality Questionnaire PDQ-4+. New York: New York State Psychiatric Institute, 1994. 39. Palmieri VO, De Rasmo D, Signorile A, Sardanelli A, Grattagliano I, Cardinale G, Portincasa P, Papa S, Palasciano G. T16189C Mitochondrial DNA variant is associated with metabolic syndrome in Caucasian subjects Nutrition 2011;27:773-777. 40. Ballerini A, Boccalon RM, Boncompagni G, Casacchia M, Margari F, Minervini L, Righi R, Russo F, Salteri A, Frediani S, Rossi A, Scatigna M, PERSEO Study Group. Clinical features and therapeutic management of patients admitted to Italian acute hospital psychiatric units: The PERSEO (psychiatric emergency study and epidemiology) survey. Annals of General Psychiatry 2007;6:29. 41. Masand P, Culpepper L, Henderson D, et al. Metabolic and endocrine disturbances in psychiatric disorders: A multidisciplinary approach to appropriate atypical antipsychotic utilization. CNS Spectrum 2005;10:1-15. 42. Salvi V, Albert U, Chiarle A, Soreca I, Bogetto F, Maina G. Metabolic syndrome in Italian patients with bipolar disorder. General Hospital Psychiatry 2008;30(4): 318-323. 43. Mendelson SD. Metabolic syndrome and psychiatric illness: Interactions, pathophysiology, assessment and treatment. New York, NY: Elsevier, 2008. ISBN: 978-0-12-374240-7. 44. Zhang J, McKeown RE, Hussey JR, Thompson SJ, Woods JR, Ainsworth BE. Low HDL cholesterol is associated with suicide attempt among young healthy women: The Third National Health and Nutrition Examination Survey. Journal of Affective Disorders 2005;89:25-33. 45. Chen CC, Lu F-H, Wu J-S, Chang C-J. Correlation between serum lipid concentrations and psychological distress. Psychiatry Research 2001;102:153-162. 46. Tedders SH, Fokong KD, McKenzie LE, Wesley C, Yu L, Zhang J. Low cholesterol is associated with depression among US household population. Journal of Affective Disorders 2011;135(1-3):115-121. 47. Shively CA, Register TC, Adams MR, Golden DL, Willard SL, Clarkson TB. Depressive behavior and coronary artery atherogenesis in adult female cynomolgus monkeys. Psychosomatic Medicine 2008;70(6):637-645. 48. D’Ambrosio V, Salvi V, Bogetto F, Maina G. Serum lipids, metabolic syndrome and lifetime suicide attempts in patients with bipolar disorder. Progressive Neuropsychopharmacologic and Biologic Psychiatry 2012;37(1):136-140. Epub 2011 Dec 30.


225

49. Watanabe J, Suzuki Y, Sugai T, Fukui N, Ono S, Tsuneyama N, Saito M, Someya T. The lipid profiles in Japanese patients with schizophrenia treated with antipsychotic agents. General Hospial Psychiatry 2012;34(5):525-528. 50. Beumer W, Drexhage RC, De Wit H, Versnel MA, Drexhage HA, Cohen D. Increased level of serum cytokines, chemokines and adipokines in patients with schizophrenia is associated with disease and metabolic syndrome. Psychoneuroendocrinology 2012;37(12):1901-1911. 51. Howren MB, Lamkin DM, Suls J. Associations of depression with C-reactive protein, IL-1, and IL-6: A meta-analysis. Psychosomatic Medicine 2009;71(2): 171-186. Epub2009 Feb 2. Review. 52. Hocaoglu C, Kural B, Aliyazicioglu R, Deger O, Cengiz S. IL-1b, IL-6, IL-8, IL-10, IFN-g, TNF-a and its relationship with lipid parameters in patients with major depression. Metabolic Brain Disease 2012;27(4):425-430. 53. Pan A, Keum N, Okereke OI, Sun Q, Kivimaki M, Rubin RR, Hu FB. Bidirectional association between depression and metabolic syndrome: A systematic review and meta-analysis of epidemiological studies. Diabetes Care 2012;35(5):1171-1180. 54. Brown ES, Varghese FP, McEwen BS. Association of depression with medical illness: Does cortisol play a role? Biology and Psychiatry 2004;55:1-9. 55. Brunner EJ, Hemingway H, Walker BR, Page M, Clarke P, Juneja M, et al. Adrenocortical, autonomic, and inflamatory causes of the metabolic syndrome: Nested casecontrol study. Circulation 2002;106:2659-2665. 56. Frayn KN. Adipose tissue and the insulin resistance syndrome. Proceedings of the Nutrition Society 2001;60:375-380. 57. Heshmati HM, Turpin G, de Gennes JL. Chronic hyperprolactinemia and plasma lipids in women. Klin. Wochenschr. 1987;65(11):516-519. 58. Licht CM, Vreeburg SA, van Reedt Dortland AK, Giltay EJ, Hoogendijk WJ, DeRijk RH, et al. Increased sympathetic and decreased parasympathetic activity rather than changes in hypothalamic-pituitary-adrenal axis activity is associated with metabolic abnormalities. Journal of Clinical Endocrinology, and Metabolism 2010;95:2458-2466. 59. Sengupta S, Parrilla-Escobar MA, Klink R, Fathalli F, Ying Kin Ng, Stip E, Baptista T, Malla A, Joober R. Are metabolic indices different between drug-naïve first-episode psychosis patients and healthy controls? Schizophrenia Research 2008;102(1-3): 329-336. 60. Yevtushenko OO, Cooper SJ, O’Neill R, Doherty JK, Woodside JV, Reynolds GP. Influence of 5-HT2c receptor and leptin gene polymorphism, smoking and drug treatment on metabolic disturbances in patients with schizophrenia. British Journal of Psychiatry 2008;192:424-428. 61. Strine TW, Mokdad AH, Dube SR, et al. The association of depression and anxiety with obesity and unhealthy behaviors among community-dwelling US adults. General Hospital Psychiatry 2008;30:127-137. 62. Grambsch P, Young EA, Meller WH. Pulsatile luteinizing hormone disruption in depression. Psychoneuroendocrinology 2004;29:825-829. 63. Vaccarino V, McClure C, Johnson BD, Sheps DS, Bittner V, Rutledge T, Shaw LJ, Sopko G, Olson MB, Krantz DS, Parashar S, Marroquin OC, Merz CN. Depression, the metabolic syndrome and cardiovascular risk. Psychosomatic Medicine 2008; 70(1):40-48.


64. Dunbar JA, Reddy P, Davis-Lameloise N, Philpot B, Laatikainen T, Kilkkinen A, Bunker SJ, Best JD, Vartiainen E, Kai Lo S, Janus ED. Depression: An important comorbidity with metabolic syndrome in a general population. Diabetes Care 2008; 31(12):2368-2373. 65. Salin-Pascual RJ, Alcocer-Castillejos NV, Alejo-Galarza G. Nicotine dependence and psychiatric disorders. Review of Investment Clinics 2003;55:677-693. 66. McIntyre RS, Park KY, Law CW, Sultan F, Adams A, Lourenco MT, Lo AK, Soczynska JK, Woldeyohannes H, Alsuwaidan M, Yoon J, Kennedy SH. The association between conventional antidepressants and the metabolic syndrome: A review of the evidence and clinical implications. CNS Drugs 2010;24(9):741-753. 67. Pyykkönen AJ, Raikkonen K, Tuomi T, Eriksson JG, Groop L, Isomaa B. Association between depressive symptoms and metabolic syndrome is not explained by antidepressant medication: Results from the PPP-Botnia Study. Annals of Medicine 2011;44(3):279-288. 68. Mackin P, Bishop D, Watkinson H, Gallagher P, Ferrier IN. Metabolic disease and cardiovascular risk in people treated with antipsychotics in the community. British Journal of Psychiatry 2007;191:23-29. 69. Allison DB, Mentore JL, et al. Antipsychotic-induced weight gain: A comprehensive research synthesis. American Journal of Psychiatry 1999;156(11):1686-1696. 70. Kreyenbuhl J, Dickerson FB, et al. Extent and management of cardiovascular risk factors in patients with type 2 diabetes and serious mental illness. Journal of Nervous and Mental Disorders 2006;194(6):404-410. 71. Daumit GL, Goff DC, Meyer JM, Davis VG, Nasrallah HA, McEvoy JP, Rosenheck R, Davis SM, Hsiao JK, Stroup TS, Lieberman JA. Antipsychotic effects on estimated 10-year coronary heart disease risk in the CATIE schizophrenia study. Schizophrenia Research 2008;105(1-3):175-187. 72. Meyer J, Koro CE, L’Italien GJ. The metabolic syndrome and schizophrenia: A review. International Review of Psychiatry 2005;17(3):173-180. 73. Melkersson K, Berinder K, Hulting AL. Effect of antipsychotic-induced hyperprolactinemia on anthropometric measures, insulin sensitivity and lipid profile in patients with schizophrenia or related psychoses. Neurology and Endocrinology Letters 2011; 32(4):428-436.

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