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Review Paper
Is Psychosis a Neurobiological Syndrome?
Daryl E Fujii, Iqbal Ahmed
(PDF)

Capgras Syndrome: A Review of the Neurophysiological Correlates and Presenting Clinical Features in Cases Involving Physical Violence
Dominique Bourget, Laurie Whitehurst
(PDF)

Perinatal Risks of Untreated Depression During Pregnancy
Lori Bonari, Natasha Pinto, Eric Ahn, Adrienne Einarson, Meir Steiner, Gideon Koren
(PDF)

Original Research Attempted Suicide: Factors Leading to Hospitalization
Urs Hepp, Hanspeter Moergeli, Stefan N Trier, Gabriella Milos, Ulrich Schnyder
(PDF)

Testing the Goodness-of-Fit of a Multifaceted Preventive Intervention for Children at Risk for Conduct Disorder
George M Realmuto, Gerald J August, Elizabeth A Egan
(PDF)

Characterizing Coronary Heart Disease Risk in Chronic Schizophrenia: High Prevalence of the Metabolic Syndrome
Tony Cohn, Denis Prud'homme, David Streiner, Homa Kameh, Gary Remington
(PDF)

Children's Persistence With Methylphenidate Therapy: A Population-Based Study
Anton R Miller, Christopher E Lalonde, Kimberlyn M McGrail
(PDF)

Frequency of Mental Health Disorders in a Sample of Elementary School Students Receiving Special Educational Services for Behavioural Difficulties
Michèle Déry, Jean Toupin, Robert Pauzé, Pierrette Verlaan
(PDF)

Brief Communication
Serum Lipid Concentrations in Obsessive-Compulsive Disorder Patients With and Without Panic Attacks
Mehmet Yucel Agargun, Haluk Dulger, Rifat Inci, Hayrettin Kara, Omer Akil Ozer, Mehmet Ramazan Sekeroglu, Lutfullah Besiroglu
(PDF)

Book Reviews
(PDF)

Affect Regulation and the Development of Psychopathology
Review by
Mary V Seeman

Psychosocial Treatment for Medical Conditions: Principles and Techniques
Review by
Alex Adsett

Quick Cognitive Screening for Clinicians
Review by
Martin Cole

The Neuropsychiatry of Epilepsy
Review by
Erwin K Koranyi

Annual Progress in Child Psychiatry and Child Development, 2000-2001
Review by
Joseph H Beitchman

Letters to the Editor
(PDF)

Re: From Chlorpromazine to Clozapine - Antipsychotic Adverse Effects and the Clinician's Dilemma

Reply: From Chlorpromazine to Clozapine - Antipsychotic Adverse Effects and the Clinician's Dilemma

Autism: Multiple Genes Acting on a Distributed Neural Target

Recurrent Paroxetine-Induced Hyponatremia

Spontaneous Orgasm Started With Venlafaxine and Continued With Citalopram

Venlafaxine-Induced Mania

Episodic Ataxia vs Somatization Disorder

Mirtazapine for Charles Bonnet Syndrome

Olanzapine Augmentation of Fluoxetine in the Treatment of Pathological Skin Picking

Internet Use in Adolescents: Hobby or Avoidance

Light Therapy, Nonseasonal Depression, and Night Eating Syndrome

Original Research

Characterizing Coronary Heart Disease Risk in Chronic Schizophrenia:
High Prevalence of the Metabolic Syndrome

Tony Cohn, MB, ChB, FRCPC¹, Denis Prud'homme, MD, MSc², David Streiner, PhD³, Homa Kameh, MSc⁴, Gary Remington, MD, PhD, FRCPC⁵

Schizophrenia has been described as a “life-shortening illness” (1) that reduces life expectancy by 10 or 15 years (2). This excess mortality cannot be explained by suicide and accidental deaths alone. In a metaanalysis, Brown and others found that physical conditions account for 60% of the excess mortality (3). Further, several studies have established a twofold increase in the standardized mortality ratio for cardiovascular disorders (4–7). For example, Osby and others report a cardiovascular standardized mortality ratio of 2.3 (95%CI, 1.6 to 4.2) for men and 2.1 (95%CI, 1.9 to 2.4) for women who received a first hospital diagnosis of schizophrenia from 1973 to 1995 in Stockholm County, Sweden (8).

Coronary heart disease (CHD) is the leading cause of death for both men and women in developed countries. Patients with schizophrenia are known to have high prevalence rates of cigarette smoking (9), diabetes (10,11), and less healthy lifestyles (12), which raises concerns about cardiovascular health. In addition, weight gain (13–16), emergent diabetes (17–20), and dyslipidemia (21,22) have been attributed to antipsychotic treatment. We sought to characterize the CHD risk profile in longer-term patients with schizophrenia and schizoaffective disorder under standard treatment and to see whether this profile is consistent with increased cardiovascular mortality.

CHD risk factors developed out of the Framingham studies in the 1950s have traditionally included elevated plasma total cholesterol (Chol) and low-density lipoproteins (LDL), decreased high-density lipoproteins (HDL), hypertension, and cigarette smoking. These risk factors have been incorporated into tables that predict the risk of myocardial infarction (MI) (23). These risk estimates are applied to adults over age 20 years who do not have heart disease or diabetes (24).

In addition, such newer risk markers as the metabolic syndrome (syndrome X) have been described. The term syndrome X was first used in 1988 to describe a metabolic syndrome, the central feature of which is insulin resistance, that carries an increased risk of CHD (25). Obesity, and especially visceral obesity, is considered a major correlate associated with insulin resistance and a related cluster of metabolic disturbances. Waist circumference is a good clinical measure of visceral obesity and a practical marker of the features of syndrome X (26). The metabolic disturbances associated with syndrome X include glucose intolerance, hyperinsulinemia, high plasma LDL and triglyceride levels, lower HDL, postprandial lipemia, high blood pressure (BP), and higher levels of tissue plasminogen activator 1. These factors contribute to increased risk of CHD (27).

The third report of the National Cholesterol Education Program Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (ATP III) established operational criteria for diagnosing metabolic syndrome and highlighted the importance of treating patients with metabolic syndrome to prevent CHD (24). At least 3 of 5 criteria are required for a diagnosis of metabolic syndrome (see Methods).

The Canadian Heart Health Survey was a large national survey (n = 26 293) conducted between 1986 and 1990. It established mean values and prevalence rates of individual CHD risks in men and women (28). These risk parameters included body mass index (BMI); waist circumference; fasting plasma Chol, HDL, LDL, and triglycerides; rates of cigarette smoking; and hypertension. Because the fasting plasma glucose (FPG) was not measured, metabolic syndrome rates could not be calculated from this survey. However, metabolic syndrome rates in US adults obtained from the Third National Health and Nutrition Examination Survey (NHANES III) were recently published and allowed comparison with our sample (29).

Methods

Subjects
We drew our sample from inpatients and outpatients in the Schizophrenia Program at the Centre for Addiction and Mental Health in Toronto, Ontario. We included in the study patients with a diagnosis of schizophrenia or schizoaffective disorder who had been taking a single antipsychotic medication for more than 3 months. DSM-IV diagnosis was established by chart review, and there was no exclusion for concomitant psychotropic or medical pharmacotherapy. We obtained Research Ethics Board approval, and patients gave their signed informed consent.

Risk Factor Evaluation
Smoking status was established by self-report and verified by nursing staff or case managers.

The research team used standard hospital scales and height measurement to measure patients’ weight (W) and height (Ht). BMI was calculated using the following formula: weight in kg / (height in metres)². Waist circumference was measured in the standing position, midway between the lowest rib and the iliac crest, after a modest expiration. Resting BP was measured in the sitting position on one occasion, according to standard procedures. After an overnight fast of 12 to 14 hours, venous blood was taken to assess FPG and fasting lipid profile. For inpatients, fasting status was verified by patients and ward nursing staff. Outpatients were contacted the evening before to ensure an adequate fast; the following morning, patients were questioned closely in this regard before blood was taken. We measured plasma glucose, Chol, HDL, and triglycerides, using standard techniques on automated chemistry analyzers. LDL was calculated from the Chol, triglycerides, and HDL.

We used the ATP III criteria to evaluate subjects for a diagnosis of metabolic syndrome (24). Three of the following 5 criteria were required: 1) abdominal obesity (waist circumference > 102 cm, or 40 inches, in men and > 88 cm, or 35 inches, in women; 2) fasting hypertriglyceridemia, (> 1.69 mmol/L, or 150 mg/dL); 3) low fasting HDL (< 1.04 mmol/L, or 40 mg/dL in men and < 1.29 mmol/L, or 50 mg/dL in women); 4) high blood pressure (> 130/85 mm Hg or current treatment with antihypertensive medication); and 5) high fasting glucose (> 6.1 mmol/L, or 11 mg/dL) or current treatment with antidiabetic medication.

Statistical Methods
We established the control group by randomly selecting the largest possible sample from the Heart Health Survey database to match the age distribution of the patients, who in turn were stratified by decade. We achieved this by calculating the largest sample from the Heart Health Survey database that would match the patients’ age distribution. We selected separate control samples for men and women. For each sex, we compared patients’ and control subjects’ individual risks and Framingham 10-year risk of MI.

In evaluating risks, we used independent sample t tests to compare continuous variables of patients and control subjects; we used the chi-square test to compare categorical variables. To avoid a type I error with multiple comparisons, we used a P value of < 0.01 to establish significance. When a significant difference between the patient group and the reference population was established for an individual risk factor, we undertook a two-way analysis of variance (ANOVA) to explore for interaction between group and sex. Antipsychotic medication groups were compared using one-way ANOVA. We excluded patients on quetiapine (n = 8) and ziprasidone (n = 1) from this comparison because of the small sample size. We used the SPSS 10.1 statistical software package (31) for analyses.

For the metabolic syndrome, we compared rates in the study population with published crude rates in the US adult population. We compared these rates for different age ranges, without further statistical analysis.

Results

Table 1 and Table 2 summarize the study and reference sample characteristics. Figure 1 compares individual risk factors separately for men and women in the study and reference populations.

Individual Risks
Among the patients, 31% of the men and 43% of the women were obese (BMI > 30), compared with 19% and 20%, respectively, in the reference population. Similarly, 44% of male and 73% of female patients had waist circumference measurements over the threshold value (102 cm, or approximately 40 inches, in men and 88 cm, or approximately 35 inches, in women) compared with 19% and 24% in the male and female reference population. Both BMI and waist circumference risks were greater for female patients, such that there was a significant interaction between group and sex for BMI (F_1,6398 = 11.965, P = 0.001) and between group and sex for waist circumference (F_1,3370 = 200.476, P < 0.001).

Male and female patients had significantly increased plasma fasting triglycerides and decreased HDL levels, compared with the reference population. However, no significant interaction between sex and group was found. Total Chol and LDL plasma levels did not differ between patients and the reference population.

As expected, smoking rates were higher in the patients (74% of men and 66% of women), compared with the reference population (30% of men and 28% of women). There was no interaction between sex and group.

Rates of hypertension (that is, BP > 140/90 mm Hg or subject on antihypertensive medication) were similar for the subjects and the reference population.

Framingham Risk
When Framingham tables were used to calculate the 10-year risk of MI, male patients had an increased risk (8.9%), compared with control subjects (6.3%) (t₃₀₉₁ = 4.35, P < 0.001); however, the risk for women was similar for patients (2.6%) and control subjects (2.0%) (Figure 2).

Metabolic Syndrome Risk
According to operationally defined criteria (see Method), the rate of the metabolic syndrome was 42.6% in male patients and 48.5% in female patients (Figure 3). Fasting glucose levels, a component of the metabolic syndrome, were not recorded in the Heart Health Survey; therefore, we could not compare the reference population with the study population. However, the published crude rate of the metabolic syndrome in the US adult population with an age range similar to that of the study population is 24% in men and 23% in women (29).

To explore rates of the metabolic syndrome at different ages, we divided the patients into 2 groups of similar size: those under age 45 years (n = 129; mean age 35.3, SD 6.2 years) and those aged 45 years and over (n = 111; mean age 53.5, SD 6.5 years). The rate of the metabolic syndrome was similar in patients under age 45 years (43.8%) and patients aged 45 years and over (45.8%). In contrast, the US adult population rate of the metabolic syndrome increased with age and was approximately 13% in the third decade, approximaately 33% in the fifth decade, and 43.5% in the sixth decade (29).

Comparison of Risks Between Inpatients and Outpatients and Among Antipsychotic Medication Groups
Risk prevalence did not differ between inpatients and outpatients. Only fasting plasma triglycerides differed among antipsychotic groups (clozapine mean 2.60, SD 2.02 mmol/L; olanzapine mean 2.22, SD 1.64 mmol/L; risperidone mean 1.89, SD 0.87 mmol/L; typical antipsychotics mean 1.83, SD 1.06 mmol/L; F_3,203 = 2.75, P = 0.04). Framingham risks and metabolic syndrome risks did not differ between antipsychotic groups.

Discussion

The major finding of the present study is that patients with chronic schizophrenia or schizoaffective disorder are at increased risk of CHD, compared with individuals in the general population. The risk profile is characterized by increased rates of obesity, particularly central obesity; cigarette smoking; increased fasting triglycerides; and reduced HDL levels.

There were more inpatients then outpatients in the study, while the control group was a community sample. This raises the question of whether the above findings can be explained by factors related to the probability of hospitalization, such as illness severity, or by factors related to the consequences of hospitalization, such as diet change and reduced physical activity. Arguing against this, however, we found no differences in individual, Framingham, and metabolic syndrome risks when we compared inpatients and outpatients. This suggests that hospitalization is unlikely to account for the differences between the patients and the control subjects.

We found striking differences between patients and control subjects in BMI and waist circumference, particularly in women. In the Heart Health Survey, men have a greater mean BMI and waist circumference, compared with women; this trend was reversed in the patient population, with women having a greater BMI and similar waist circumference, compared with men.

As a caveat, it must be pointed out that, while the Heart Health Survey was conducted between 1986 and 1990, the patients described in this paper were sampled in 1999 and 2000. Therefore, temporal trends in body weight could account for some of the observed differences. Indeed, the prevalence of obesity increased in North America during the 1990s (31). However, the obesity rate among the patients in this study (31% of men and 43% of women) remains high, even by current standards. For example, the prevalence of obesity among US adults in 2000 was reported to be 20.2% in men and 19.4% in women (32). Therefore, secular trends in obesity are unlikely to account for all the difference observed between patients and control subjects—particularly in women, where the differences were so pronounced.

We contrast Framingham risk predictions with the metabolic syndrome and point out that the metabolic syndrome conceptualization better captures CHD risk, especially in female patients. This distinction is offered with the caveat that a few patients and control subjects were under age 20 years, the lower age limit for applying the Framingham tables. In addition, because information related to diabetes was absent from the Heart Health Survey, we did not exclude people with diabetes from the Framingham risk predictions. The effect of this limitation would be to underestimate risk in the patients where, as we describe below, we anticipate a higher rate of diabetes.

Glucose intolerance, a feature of the metabolic syndrome, also connotes an increased risk of CHD and diabetes. A subsample of these patients (n = 162) were screened for diabetes with both fasting plasma glucose and a 2-hour glucose tolerance test (33). At 18%, the rate of diabetes was markedly elevated, compared with a rate of 6.4% in the general population with similar age distribution, screened in the same manner (34).

Therefore, with the exception of hypertension, all the criteria for the metabolic syndrome were markedly increased in the patient group and account for the more sensitive estimate of CHD risk, compared with Framingham criteria. While it is somewhat surprising that hypertension rates were not elevated in the patients, we hypothesize that alpha blockade and anticholinergic effects of antipsychotic treatment may have masked the expected increased hypertension rates associated with the metabolic syndrome.

Another important finding is that, in the population studied, there also appears to be a risk of developing the metabolic syndrome at a younger age. Rates of the metabolic syndrome in the general population increase dramatically with age; however, this pattern was less apparent in the patients, for whom rates were similar in those under age 45 years and those aged 45 years and over. Further, patients in their third decade had a metabolic similar profile to those in the general population in their sixth decade.

In summary, the metabolic syndrome conceptualization combined with the high prevalence of cigarette smoking appears to best capture the increased risk of CHD in our patients. The patient group’s twofold increase in the metabolic syndrome, compared with the general population, is consistent with the doubling of the standardized mortality ratio for death from cardiovascular disorder in both male and female schizophrenia patients (8).

Limits of this study include its cross-sectional design and lack of control over concomitant medication, which made it difficult to separate the relative contribution of medication treatment to cardiovascular risk. However, this was not the study’s primary intention; indeed, we found differences in fasting triglyceride levels among antipsychotic medications, in keeping with other reports (35,36). We forward this distinction with caution though, given our study methodology. While we required patients to be taking a single antipsychotic for a period of 3 months or more, it cannot be overlooked that this sample was drawn from a population with chronic illness, meaning that individuals had been exposed to other antipsychotics for variable periods beforehand. Prospective and first-episode studies are needed to tease out the relative contribution of illness, lifestyle, and medication factors in the development of cardiac and metabolic risks in these patients.

Lately, awareness has increased that the medical needs of patients with chronic psychosis have for the most part been neglected. This has been aptly described as “dual neglect by patients and the system” (37). On the one hand, self-neglect is often an inherent aspect of the illness; at the same time, medical and psychiatric care systems have traditionally been poorly integrated, particularly in the US (38) but also internationally. The substantial medical comorbidity occurring in schizophrenia (39,40) contributes to poor physical and mental health outcomes (41), as well as reduced quality of life and reduced life expectancy (3). Clearly, there is a need to integrate psychiatric and medical care through innovative shared care models. This study illustrates the high prevalence and characteristics of cardiovascular risk and underscores the importance of identifying potentially reversible factors contributing to the development of CHD in this high-risk population. To this end, we recommend routine evaluation of CHD risk factors, especially of the metabolic syndrome and cigarette smoking. Further, attention should be paid to lifestyle factors such as an unhealthy diet (42), physical inactivity (43), and cigarette smoking (44). Finally, patients should be appropriately screened and treated for diabetes and hyperlipidemia.

Funding and Support

This research was supported in part by an unrestricted educational grant from Janssen-Ortho.

Acknowledgements

The authors acknowledge the contribution of Penny Barsoum and Sajeevan Punniyamoorthy.

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Author(s)

Manuscript received June 2003, revised, and accepted May 2004.
Previously presented at the IXth International Congress on Schizophrenia Research; March 2003; Colorado Springs (CO).

1. Lecturer, Department of Psychiatry, University of Toronto, Toronto, Ontario; Staff Psychiatrist, Schizophrenia Program, Centre for Addiction and Mental Health, Toronto, Ontario.

2. Dean, Faculty of Health Sciences, University of Ottawa, Ottawa, Ontario.

3. Professor, Department of Psychiatry, University of Toronto, Toronto, Ontario; Director, Kunin-Lunenfeld Applied Research Unit, Baycrest Centre for Geriatric Care, Toronto, Ontario.

4. Research Analyst, Centre for Addiction and Mental Health, Toronto, Ontario.

5. Professor, Department of Psychiatry, University of Toronto, Toronto, Ontario; Director, Medication Assessment Program for Schizophrenia, Centre for Addiction and Mental Health, Toronto, Ontario.

Address for correspondence: Dr Tony Cohn, Centre for Addiction and Mental Health, 1001 Queen Street West, Toronto, ON M6J 1H4

e-mail: Tony_Cohn@CAMH.net

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