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Psychosomatics 48:412-417, October 2007
doi: 10.1176/appi.psy.48.5.412
© 2007 Academy of Psychosomatic Medicine
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Cardiovascular Disease and Metabolic Risk Factors in Male Patients With Schizophrenia, Schizoaffective Disorder, and Bipolar Disorder

Amy M. Kilbourne, Ph.D., M.P.H., Jaspreet S. Brar, M.D., M.P.H., Rebecca A. Drayer, M.D., Xiangyan Xu, M.S., and Edward P. Post, M.D., Ph.D.

Received March 27, 2006; revised June 26, 2006; accepted July 10, 2006. From the VA Ann Arbor National Serious Mental Illness Treatment, Research, and Evaluation Center and the Depts. of Medicine and Psychiatry, Univ. of Michigan, Ann Arbor, MI; the Canandaigua VA Medical Center, Canandaigua, NY; the Univ. of Rochester School of Medicine and Dentistry, Rochester, NY; and the Dept. of Psychiatry, Univ. of Pittsburgh School of Medicine, Pittsburgh, PA. Send correspondence and reprint requests to Amy M. Kilbourne, Ph.D., M.P.H., VA Ann Arbor SMITREC (11H), 2215 Fuller Rd., Ann Arbor, MI 48105. e-mail: amykilbo{at}umich.edu
© 2007 The Academy of Psychosomatic Medicine


  ABSTRACT

 
TOP
 ABSTRACT
INTRODUCTION
 METHOD
 RESULTS
 DISCUSSION
 REFERENCES
 
The authors determined whether diagnoses of cardiovascular disease (CVD) and CVD-related conditions differed by psychiatric diagnosis among male Veterans Administration patients from the mid-Atlantic region. Among 7,529 patients (mean age: 54.5 years), the prevalence of diagnoses ranged from 3.6% (stroke) to 35.4% (hypertension). Compared with schizophrenia patients, those with bipolar disorder were 19% more likely to have diabetes, 44% more likely to have coronary artery disease, and 18% more likely to have dyslipidemia, after adjustment. Clinical suspicion for CVD-related conditions, as well as risk-modification strategies, in patients with serious mental illness should incorporate differences in prevalence across specific psychiatric diagnoses.


  INTRODUCTION

 
TOP
 ABSTRACT
 INTRODUCTION
METHOD
 RESULTS
 DISCUSSION
 REFERENCES
 
Serious mental illnesses (SMI), especially schizophrenia and bipolar disorder, are ranked among the top 10 leading causes of disability worldwide.1 The shortened life expectancy observed in these patients may be attributable to the higher likelihood for cardiovascular and metabolic-related comorbidities.2,3 The Framingham Heart Study has firmly established the elevated risk of cardiovascular disease (CVD) in patients with obesity,4 diabetes,5 hypertension, and dyslipidemia.6 These CVD-related risk factors occur at a higher frequency in patients with schizophrenia than in the general population (about 1.5 to 2 times greater).7,8 More recently, the prevalence of the metabolic syndrome, which is a clustering of multiple CVD risk factors, with central obesity and insulin-resistance at its core, has been examined in SMI patients and has been found to be approximately 2 times the prevalence observed in nonpsychiatric populations.9–11

Multiple behavioral and treatment-related factors contribute to the etiology and pathogenesis of medical comorbidities in patients with SMI; these include overeating, sedentary lifestyle,12 inadequate medical care,13–15 and the iatrogenic effects of psychotropic medications.16 Although much attention has been paid to the introduction of atypical antipsychotics as the major cause for the increase in obesity and diabetes in patients with SMI, CVD-related risk in this population predates the introduction of antipsychotic medications and is frequently observed in drug-naive, first-episode patients.17–19

Moreover, the role of specific psychiatric diagnosis in the increased risk of CVD-related conditions has not been fully explored. Most studies of medical comorbidity in patients with SMI have either detailed the prevalence of these conditions within specific psychiatric diagnoses, such as schizophrenia7 or bipolar disorder,20 or made comparisons between SMI and non-SMI populations.8,20

Although patients with different SMI diagnoses, such as schizophrenia and bipolar disorder, may be similar in their level of functioning, psychiatric treatment strategies often differ because of the predominance of some types of episodes (e.g., mania or depression in bipolar disorder) over others (e.g., psychosis). These episodes may also differentially affect the patient’s risk of CVD. For example, it has been theorized that the alternating manic and depressive episodes in bipolar disorder may exacerbate the metabolic syndrome and subsequent CVD because of "allostatic load," defined as the "wear-and-tear" on the body and brain resulting from chronic overactivity or inactivity of physiological systems that are normally involved in adaptation to environmental stressors (e.g., glucocorticoids and catecholamines).21,22 Understanding how different SMI diagnoses affect CVD risk can inform the tailoring of different treatment and screening strategies across these groups. Hence, in a population-based sample of patients diagnosed with SMI, we compared the prevalence of CVD-related comorbidities across different SMI diagnoses; namely, schizophrenia, schizoaffective disorder, and bipolar disorder.


  METHOD

 
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 ABSTRACT
 INTRODUCTION
 METHOD
RESULTS
 DISCUSSION
 REFERENCES
 
Data for these analyses were obtained from the National Patient Care Database (NPCD), maintained by the Veterans Administration (VA). Given the relatively small number of women in the VA, the study sample was limited to male VA patients diagnosed with SMI. The focus on VA patients allows us to examine differences in prevalence rates in a setting where patients have equal access to care, mitigating potential socioeconomic differences in our study. Details regarding the methods used for obtaining data from the NPCD have been described earlier.23 Briefly, all subjects with a diagnosis of schizophrenia (International Classification of Disease, 9th Revision [ICD-9] codes 295.0–295.6, or 295.8–295.9), schizoaffective disorder (ICD-9 code 295.7), or bipolar disorder (ICD-9 codes 296.0, 296.1, 296.4–296.8, or 301.1) who had a clinical encounter (either inpatient or outpatient, or both) at any facility within the VA mid-Atlantic regional network (Pennsylvania, Delaware, and areas of West Virginia, New Jersey, and New York), in fiscal year (FY) 2001 (October 1, 2000 through September 30, 2001) were included.

As in the ascertainment criteria used in previous studies, subjects were included only if the particular SMI diagnosis of interest was recorded on at least one inpatient or two separate outpatient visits.23,24 Although the use of one inpatient or two outpatient codes to identify patients with mental disorders maximizes specificity while retaining sensitivity, we are also aware that many patients may receive overlapping psychiatric diagnoses. Hence, we used the following decision hierarchy (in order of inclusion) to identify unique patient groups: schizophrenia, schizoaffective disorder, and bipolar disorder. For example, if patients were diagnosed with schizophrenia and were also diagnosed with one of the other mental disorders, then they were considered to have a diagnosis of schizophrenia. We chose to use this hierarchy because evidence from the World Health Organization’s Global Burden of Disease Report suggested that schizophrenia is the most debilitating of the SMI diagnoses.1

CVD-related comorbidities in FY 2001 were identified with the following ICD-9 codes: 401.0–401.5 for hypertension; 272.0–272.4 for dyslipidemia; 250.0–250.9 for diabetes; 410.0–414.9 for coronary artery disease or myocardial infarction; 278.0, 278.1, or 783.1 for obesity; and 430.0–438 for stroke. These ICD-9 codes are based on algorithms used by VA researchers and the Agency for Healthcare Research and Quality (AHRQ) Clinical Classifications Software.25 Providers and professional coders determine ICD-9 codes as part of the administrative data routinely collected by the VA healthcare facilities. As with psychiatric diagnoses, CVD-related comorbidities were included only if the particular medical diagnosis of interest was recorded on at least one inpatient or two separate outpatient visits.20–23

Statistical analyses were done with SAS Version 8.1 (SAS Institute; Cary, NC). Descriptive statistics were applied to estimate the percentage of patients with each CVD-related condition. Mean age across SMI diagnosis groups was compared by t-test, and chi-square tests were used to compare covariates (race, tobacco use, and prevalence of medical diagnosis) by SMI group. Multivariable logistic-regression analyses were used to compare the probability of receiving each CVD-related diagnosis (with schizophrenia as the reference group), adjusting for key patient factors previously demonstrated to be associated with both SMI diagnosis and CVD-related condition prevalence: age (in years) and race (African American and non-African American, given the relatively few numbers of other minority groups). Smoking status was defined by the presence of ICD-9 codes 305.1: Tobacco Use Disorder, or V15.82: History of Tobacco Use in the administrative data.


  RESULTS

 
TOP
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 RESULTS
DISCUSSION
 REFERENCES
 
Of 7,529 male patients, the mean age was 54.5 years (standard deviation [SD]: 12.3; range: 19–100 years); 21.8% (N=1,640) were African American, and 12.3% (N=923) used tobacco. These demographic characteristics are comparable to those of VA patients across the United States.26 Overall, 62.7% (N=4,721) were diagnosed with schizophrenia, 8.4% (N=632) were diagnosed with schizoaffective disorder, and 28.9% (N=2,176) were diagnosed with bipolar disorder. Patients diagnosed with schizophrenia were, on average, slightly older than those diagnosed with schizoaffective disorder or bipolar disorder (mean age, respectively, 55.4, 53.4, and 52.9 years; F[2]=34.28; p<0.001). Patients diagnosed with schizophrenia were also more likely to be African American (respectively, 27.7%, 18.7%, and 9.8%; {chi}2[2]=285.24; p<0.001) than those diagnosed with schizoaffective disorder or bipolar disorder. There was no difference in tobacco use by diagnosis among patients diagnosed with schizophrenia, schizoaffective disorder, or bipolar disorder (respectively, 12.4%, 11.7%, and 12.0%; {chi}2[2]=0.41; p≥0.82).

CVD-related conditions among our population are listed in Table 1. The most common overall conditions were hypertension (35.4%), dyslipidemia (24.8%), and diabetes (17.6%). Unadjusted bivariate results revealed significant differences in the prevalence of dyslipidemia and obesity across diagnosis groups. Male patients with schizoaffective disorder were more likely than those in the other SMI groups to be diagnosed with dyslipidemia (respectively, 29.3%; versus 23.2% [schizophrenia], and 27.2% [bipolar disorder]; {chi}2[2]=20.38; p<0.001) or obesity (respectively, 12.8%; versus 9.9% [schizophrenia], and 11.6% [bipolar disorder]; {chi}2[2]=7.96; p<0.02).


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TABLE 1. CVD-Related Conditions Comparing Male Patients Diagnosed With Various Severe Mental Illnesses



Multivariable logistic-regression analyses revealed differences in the adjusted probability of CVD-related conditions by SMI diagnosis, with schizophrenia as the reference group (Table 1). Notably, after adjusting for age, race, and tobacco use, patients with bipolar disorder were 13% more likely to be diagnosed with hypertension (adjusted odds ratio [OR]=1.13; p<0.05), 18% more likely to be diagnosed with dyslipidemia (adjusted OR=1.18; p<0.01), 19% more likely to be diagnosed with diabetes (adjusted OR=1.19; p<0.05), and 44% more likely to be diagnosed with coronary artery disease (adjusted OR=1.44; p<0.01). Patients with bipolar disorder were also more likely than those with schizophrenia to be diagnosed with any CVD-related comorbidity (adjusted OR=1.24; p<0.001). Patients diagnosed with schizoaffective disorder were more likely than those with schizophrenia to be diagnosed with dyslipidemia (adjusted OR=1.36; p<0.01) and obesity (adjusted OR=1.30; p<0.05).


  DISCUSSION

 
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 ABSTRACT
 INTRODUCTION
 METHOD
 RESULTS
 DISCUSSION
REFERENCES
 
We found a substantial prevalence of CVD-related conditions in our cohort of patients diagnosed with SMI. Our unadjusted prevalence estimates are similar to those reported elsewhere based on both administrative data (i.e., ICD-9) as well as medical-record review across diverse VA and non-VA patient populations for hypertension (26%–34%), dyslipidemia (13%–27%), diabetes (9%–17%), coronary artery disease (4%–9%), obesity (10%–33%), and stroke (2%–4%).9,10,27–30

After adjusting for age, race, and tobacco use, patients with bipolar disorder were the most likely to be diagnosed with most CVD-related conditions, notably hypertension, dyslipidemia, diabetes, and coronary artery disease, as compared with schizophrenia or schizoaffective-disorder patients. A post-hoc analysis in which we limited the sample to non-African American patients produced similar results (See Appendix 1). The increased prevalence of these diagnoses in the adjusted findings is particularly surprising, given that age is the predominant demographic factor associated with these conditions (patients with schizophrenia were, on average, older). The higher probability of these chronic conditions in patients with bipolar disorder may reflect physiological changes (e.g., allostatic load),21,22 as well as behaviors associated with mania and depression. Treatment nonadherence is often associated with manic episodes in bipolar disorder, and undertreated conditions can exacerbate the risk of CVD.31,32 The 44% increased risk of coronary artery disease may be explained by depressive episodes that are common in bipolar disorder,33 given that depression can lead to adverse physiologic effects leading to CVD, including decreased heart rate variability and increased aggregation of platelets.34


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APPENDIX 1. CVD-Related Conditions Among Male Non-African American Patients Diagnosed With Schizophrenia, Schizoaffective Disorder, and Bipolar Disorder: Multivariable Analyses



After demographic adjustment, patients diagnosed with schizoaffective disorder were the most likely to be diagnosed with obesity and dyslipidemia. Basu and colleagues9 also found an increased prevalence of these two conditions in a non-VA sample of patients with schizo-affective disorder. Perhaps these patients represent a more severely ill population because of overlapping mood and psychotic symptoms associated with this diagnosis, and so they are subsequently more likely to lead a sedentary lifestyle.

Despite our comprehensive assessment of CVD-related conditions in a large sample of patients with serious mental illness, there are limitations to this study that warrant consideration. Foremost, we relied on administrative data and not formal psychiatric assessment to identify patients with SMI, and our data were unable to discern patients by current episode status (e.g., manic, depressive, psychotic). Our data also did not contain information on patient health behaviors or medications, especially psychotropics that may be associated with increased risk of diabetes and obesity (e.g., atypical antipsychotics). However, as noted earlier, CVD-related risk has been observed in patients with SMI before the introduction of antipsychotic medications.17–19 As of 2001, atypical antipsychotics were mostly used to treat psychosis in schizophrenia and schizoaffective disorder, and were less likely used to be as mood stabilizers. Hence, our results may have underestimated the association between bipolar-disorder diagnosis and CVD-related conditions among patients with bipolar disorder. Also, the cross-sectional nature of the study cannot establish causality between psychiatric diagnosis and CVD-related comorbidity. The prevalence of CVD-related comorbidity may have been underestimated because we relied on secondary diagnostic data, rather than a comprehensive clinical exam. Finally, given the relative rarity of women in the VA system, we were unable to examine gender-specific factors in psychiatric diagnosis and CVD. Still, many individuals with SMI receive care from publicly-funded healthcare providers (e.g., Medicaid, VA), and, hence, our study population may be similar to other samples of SMI patients.

Despite these limitations, our study is one of the first to compare CVD-related comorbidities across different SMI diagnoses. Recently, the Institute of Medicine report "Improving Quality of Health Care for Mental and Substance Use Conditions"35 noted the high prevalence of general-medical conditions in persons with serious mental illnesses and strongly suggested the need to improve the integration and quality of general-medical care for persons with SMI. Patients with SMI receive substantially fewer services for diabetes, hypertension, and other cardiac disease than those without a psychiatric diagnosis.13–15

Our findings suggest that strategies to improve care for CVD risk factors among men with SMI should take into consideration how CVD risk may differ across SMI diagnosis. The increased risk of chronic CVD-related conditions associated with bipolar disorder among male patients suggests the need to improve access to a broad scope of services, including general-medical care as well as CVD monitoring and risk-factor modification for this group. In contrast, the high prevalence of obesity and dyslipidemia in patients with schizoaffective disorder suggests that these patients may benefit from efforts that are focused more specifically on changing health behaviors (e.g., diet and exercise).36,37 Further research regarding the underlying mechanisms for the increased risk of CVD-related conditions in patients with different SMI diagnoses is warranted, especially regarding the role of manic and depressive episodes and their impact on health behaviors, adherence behaviors, and physiological changes. Such findings can inform the customization of screening and treatment strategies to reduce the risk of CVD across all diagnostic groups.


  ACKNOWLEDGMENTS

 
This research was supported by the VA, Veterans Health Administration, Health Services Research and Development Service (IIR 02-283-2; A. Kilbourne, PI). This work was also completed with the support of the Center for Health Equity Research and Promotion, VA Pittsburgh Healthcare System (M. Fine, PI). Dr. Kilbourne is funded by the Career Development Award Merit Review Entry Program from the VA Health Services Research and Development program. Dr. Post is funded by a Career Development Award from the NIMH (K23 MH001879). The authors of this manuscript warrant that we have no actual or perceived conflicts of interest, financial or non-financial, in the procedures described in the enclosed manuscript.


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 DISCUSSION
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