The Journals of Gerontology Series B: Psychological Sciences and Social Sciences 62:P295-P299 (2007)
© 2007 The Gerontological Society of America
DSM-IV Personality Disorders and Coronary Heart Disease in Older Adults: Results From the National Epidemiologic Survey on Alcohol and Related Conditions
Robert H. Pietrzak,
Julie A. Wagner and
Nancy M. Petry
1 Department of Psychiatry, University of Connecticut Health Center, Farmington, Connecticut.
2 Department of Behavioral Sciences and Community Health, University of Connecticut Health Center, Farmington, Connecticut.
Address correspondence to Nancy M. Petry, PhD, Department of Psychiatry, University of Connecticut Health Center, 263 Farmington Avenue, Farmington, CT 06030-3944. E-mail: petry{at}psychiatry.uchc.edu
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Abstract
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We evaluated the relationship between seven personality disorders listed in the fourth edition of the Diagnostic and Statistical Manual of Mental Disorders and coronary heart disease (CHD) in a nationally representative sample of U.S. older adults. We analyzed data on 10,573 adults aged 60 or older from the National Epidemiologic Survey on Alcohol and Related Conditions. In our results, we found that 13.30% of older adults reported a diagnosis of CHD confirmed by a health professional. Age (odds ratio or OR = 1.04), morbid obesity (OR = 1.59), hypertension (OR = 2.30), nicotine dependence (OR = 1.39), any drug use disorder (OR = 2.13), and any mood disorder (OR = 1.87) increased the odds of having CHD. Female gender (OR = 0.72) and social drinking (OR = 0.71) decreased the odds of having CHD. Controlling for these variables, we found that avoidant (OR = 1.80), schizoid (OR = 1.63), and obsessive-compulsive (OR = 1.37) personality disorders increased the odds of having CHD. Personality disorders may increase the risk of CHD in older adults. Putative mechanisms and directions for future research are proposed.
Over the past three decades, there has been an effort to identify novel psychosocial risk factors for coronary heart disease (CHD; Kuper, Marmot, & Hemingway, 2002
). Although most of this research has focused on depression, personality variables have also been investigated as potential risk factors for CHD. Early studies demonstrated a relationship between Type A behavior, characterized by competitiveness, anger, and hostility, and CHD (Rosenman, Brand, Sholtz, & Friedman, 1976). More recently, Type D personality, consisting of negative affectivity and social inhibition, has been linked to cardiac disease and mortality (Denollet, Pedersen, Vrints, & Conraads, 2006).
To date, however, no known study has investigated the relationship between CHD and personality disorders as listed in the fourth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV-TR; American Psychiatric Association, 2000). This lack of research is likely due to lower population base rates of personality disorders relative to personality types and traits, and greater assessment demands of the diagnostic approach. DSM criteria, nevertheless, provide the most standardized and relatively stable conceptualization of personality problems. Additional limitations of existing literature include sampling issues and substantial overlap between personality and other psychiatric risk factors for CHD, particularly depression (Kubzansky, Cole, Kawachi, Vokonas, & Sparrow, 2006). Epidemiologic research using nationally representative samples, rather than clinical cardiac samples, is also lacking.
In this study, we examined the relationship between DSM-IV personality disorders and CHD in a nationally representative sample of U.S. older adults, with careful control of demographic, biological, behavioral, and other psychiatric variables. To our knowledge, the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC) is the largest psychiatric epidemiology study ever conducted (Grant, Moore, Shepard, & Kaplan, 2003). It assessed a wide range of DSM-IV disorders, including seven personality disorders, as well as several medical conditions. Given the paucity of data on the relationship between personality disorders and CHD in noncardiac populations, this data set provides a unique opportunity to examine this relationship in a large, nationally representative sample of older adults.
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METHODS
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Participants
The NESARC is a nationally representative survey of civilian, noninstitutionalized adults age 18 years and older living in the United States. It was conducted by the National Institute on Alcohol Abuse and Alcoholism (NIAAA) in 2001–2002. A total of 43,093 individuals completed face-to-face interviews, with a response rate of 81%. Young adults (aged 18–24 years) and African-American and Hispanic racial or ethnic groups were oversampled. Data were weighted to account for oversampling and design characteristics of the survey, and then they were further adjusted on the basis of the 2000 Decennial Census in terms of socioeconomic variables such as age, sex, race–ethnicity, and region of the country (Grant et al., 2003). A total 10,573 (21.6%) of the 43,093 individuals surveyed were 60 years of age or older.
Medical Conditions
Respondents were asked if they had experienced tachycardia, hypertension, angina, arteriosclerosis, myocardial infarction, cirrhosis, other liver disease, stomach ulcer, gastritis, or arthritis within the past year. If they responded affirmatively, they were then asked whether a physician or other health professional made the diagnosis. In this study, we considered only those diagnoses that respondents stated were made by a physician or other health professional to be affirmative. We derived a composite CHD outcome measure based on physician or other health professional diagnoses of angina, arteriosclerosis, and myocardial infarction. We classified older adults who reported a diagnosis of angina (8.77%, SE = 0.36%), arteriosclerosis (5.61%, SE = 0.29%), or myocardial infarction (2.82%, SE = 0.19%) as having CHD. A total of 13.30% (SE = 0.45%) of older adults who responded to all CHD items had a diagnosis of angina, arteriosclerosis, or myocardial infarction in the year prior to being surveyed.
Body Mass Index
We computed body mass index (BMI) by using self-reported weight and height, by dividing weight in kilograms by the square of height in meters. We classified respondents whose BMI values were 
40 kg/m2 as morbidly obese (National Heart, Lung, and Blood Institute, 1998).
DSM-IV Personality Disorder Assessment
Researchers used the NIAAA Alcohol Use Disorder and Associated Disabilities Interview Schedule–DSM-IV Version (AUDADIS-IV) to assess seven DSM-IV personality disorders: antisocial, avoidant, dependent, histrionic, obsessive-compulsive, paranoid, and schizoid. Following DSM-IV (American Psychiatric Association, 2000), respondents must have met the required number of criteria and had at least one symptom cause social or occupational dysfunction to receive a personality disorder diagnosis. Respondents were instructed to not include times when they were physically ill, depressed, anxious, manic, drinking heavily, using medicine or drugs, or experiencing withdrawal symptoms in considering their responses. The internal consistency of the AUDADIS-IV personality disorder diagnoses in the full NESARC sample is fair to good, with intraclass correlation coefficients (ICCs) ranging from 0.40 to 0.67 for diagnoses (histrionic = 0.40; paranoid = 0.42; avoidant = 0.45; obsessive-compulsive = 0.52; schizoid = 0.53; dependent = 0.66; antisocial = 0.67) and 0.60 to 0.79 for dimensional symptom scales (histrionic = 0.50; avoidant = 0.55; obsessive-compulsive = 0.55; schizoid = 0.56; paranoid = 0.60; dependent = 0.73; antisocial = 0.79; see Grant, Dawson, Stinson, Chou, Kay, & Pickering, 2003).
DSM-IV Mood and Anxiety Disorder Assessment
The AUDADIS-IV also assessed lifetime and past-year DSM-IV mood and anxiety disorders. The assessed mood disorders included major depressive episode, dysthymia, manic episode, and hypomanic episode. The assessed anxiety disorders included generalized anxiety disorder, agoraphobia with panic disorder, agoraphobia without panic disorder, social phobia, and specific phobia. We included only primary diagnoses in the analyses. We did not include mood and anxiety disorders that were substance induced or due to a general medical condition or bereavement (about 1.0% of all cases). Internal consistency of AUDADIS-IV mood (ICC = 0.57–0.71) and anxiety (ICC = 0.71–0.86) disorder diagnoses is fair to good (Grant et al., 2003).
Assessment of DSM-IV Alcohol and Drug Use Disorders
The AUDADIS-IV assessed DSM-IV diagnoses of nicotine dependence, alcohol abuse and dependence, and drug abuse and dependence for 10 classes of drugs, including cannabis, cocaine, heroin, opiates (other than heroin or methadone), stimulants, tranquilizers, sedatives, hallucinogens, inhalants or solvents, and other drugs. Respondents must have met at least one of four abuse criteria in the 12-month period preceding the interview or before the 12-month period to receive a lifetime diagnosis of alcohol or drug abuse. Lifetime AUDADIS-IV dependence diagnoses required respondents to meet at least three of seven dependence criteria during the past year or prior to the past year. We classified all drug use disorders other than nicotine and alcohol into one general category of "any lifetime DSM-IV drug use disorder," because prevalence rates of individual categories of drug of abuse and dependence were low among older adults. Because moderate alcohol consumption appears to be protective against CHD (Rimm, Williams, Fosher, Criqui, & Stampfer, 1999), we categorized respondents into three groups based on their lifetime alcohol use. We classified respondents who reported never consuming alcohol as "lifetime abstainers;" we classified respondents who were not lifetime abstainers and had no lifetime or past-year alcohol abuse or dependence as "social drinkers." We also included lifetime DSM-IV nicotine dependence in the model. The internal consistency of AUDADIS-IV alcohol (ICC = 0.81–0.89), drug (ICC = 0.65–0.99), and nicotine (ICC = 0.75–0.77) use diagnoses is good to excellent (Grant, Harford, Dawson, Chou, & Pickering, 1995; Grant et al., 2003).
Statistical Analyses
We classified respondents who were 60 years of age or older into one of two groups on the basis of whether or not they had CHD. Cross-tabulations evaluated group differences in demographics and psychiatric disorders.
Logistic regressions evaluated the relationship between any personality disorder and CHD after we controlled for demographics (age, sex, race or ethnicity, education, marital status, and income), health variables (morbid obesity and hypertension), substance use (lifetime alcohol use and disorders, nicotine dependence, and any drug use disorder), and psychiatric variables (any lifetime mood and anxiety disorder). We also evaluated the Sex x Personality Disorder interaction. Finally, we evaluated the relationship between each personality disorder and CHD by using the same covariates already noted here.
Complete data were available for 9,913 older adults; most of the missing data were for self-reported height and weight, which were used to calculate BMI. Odds ratios (ORs) and 95% confidence intervals (CIs) are presented for each independent variable. We used SUDAAN, a software package that uses Taylor series linearization to adjust for the complex sampling methodology, to conduct all analyses (Research Triangle Institute, 2003).
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RESULTS
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Demographic Characteristics
Table 1 shows demographic and clinical characteristics of older adults with and without CHD. Compared with older adults without CHD, older adults with CHD were older and had lower education and incomes; marital status also differed between groups. Older adults with CHD were also more likely to be morbidly obese and to have hypertension. Lifetime alcohol use also differed between the groups. Older adults with CHD were also significantly more likely to have lifetime nicotine dependence, any mood disorder, any anxiety disorder, and any personality disorder.
Any DSM-IV Personality Disorder and CHD
Table 2 shows the ORs and 95% CIs from the overall logistic regression model with all demographic, health, and psychiatric covariates included. Older age, morbid obesity, hypertension, lifetime nicotine dependence, and any lifetime drug use disorder were significantly associated with CHD. Women and social drinkers had decreased odds of CHD compared with men and alcohol abstainers, respectively. Any lifetime mood disorder was also significantly associated with increased odds of CHD, but any lifetime anxiety disorder was not significant in this multivariate analysis. Any personality disorder increased the odds of having CHD. The interaction between sex and any personality disorder was not significantly associated with CHD; Wald F(1, 65) = 2.30; p =.13.
Specific DSM-IV Personality Disorders and CHD
Table 3 displays specific personality disorders and their prevalence in this sample of older adults with and without CHD. In the bivariate analyses, prevalence rates of all personality disorders except antisocial and histrionic personality disorder were significantly elevated in older adults with CHD compared with those without CHD.
Table 3 also shows results of individual multivariate logistic regression analyses. Obsessive-compulsive, schizoid, and avoidant personality disorders remained significantly associated with CHD, after we adjusted for demographic, health, and psychiatric covariates.
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DISCUSSION
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In this study, we examined the relationship between DSM-IV personality disorders and CHD in a nationally representative sample of older adults. Results showed that any DSM-IV personality disorder was associated with a 26% increased odds of CHD, even after we controlled for demographic, biological, behavioral, and other psychiatric risk factors. Specific personality disorders associated with CHD included avoidant, schizoid, and obsessive-compulsive personality disorders.
The personality disorders associated with CHD in this study are all characterized by known CHD risk factors, including low social support (Orth-Gomer, Rosengren, & Wilhelmsen, 1993) and high distress (Denollet et al., 2006). According to the DSM-IV (American Psychiatric Association, 2000), schizoid personality disorder is characterized by a pervasive pattern of detachment from social relationships and a restricted range of expression of emotions; avoidant personality disorder is defined by social inhibition and avoidance of activities involving interpersonal contact. Interpersonal control to the exclusion of relationships typifies obsessive-compulsive personality disorder; when relationships do exist, they have a formal quality largely devoid of affect.
A number of potential mediators of the relationship between personality and CHD have been proposed. Candidate behavioral mechanisms include social isolation, interpersonal conflict, and job stress (Smith & Ruiz, 2002). Physiological mechanisms include cardiovascular reactivity (Gross & Levenson, 1997), impaired hypothalamic-pituitary-adrenal axis regulation (Habra, Linden, Anderson, & Weinberg, 2003), and immune and inflammatory changes (Denollet, Conraads, Brutsaert, DeClerck, Stevens, & Vrints, 2003). More research is needed to elucidate mediators of the relationship between personality disorders and CHD and the interactions among these mediators. Ultimately, the identification of these mediators may lead to targeted psychological and pharmacological interventions.
Methodological limitations of this study include the cross-sectional design, which precludes examination of the causal relationship between personality disorders and CHD; potential psychometric limitations of the AUDADIS-IV in assessing personality disorders; possible recall and reporting bias of cardiovascular disorders; and the operationalization of CHD, which was limited to self-reported past-year diagnoses of angina, arteriosclerosis, and myocardial infarction. Further, personality may change as a function of normal aging, cognitive decline, or medical illness (e.g., Lautenschlager & Forstl, 2007). These changes, which may be independent of personality disorder diagnoses, may also influence the odds of having CHD.
Despite these limitations, results of this study indicate that any lifetime DSM-IV personality disorder is associated with an increased likelihood of CHD in older adults, even after one has adjusted for a range of potentially confounding variables. These results, combined with a growing body of literature demonstrating a link between personality and mortality (Denollet et al., 2006; Wilson, Mendes de Leon, Bienas, Evans, & Bennett, 2004), underscore the importance of personality disorders as a potential risk factor for CHD. Future research should examine causal relationships between personality disorders and CHD, behavioral and biological mediators of this association, and the utility of psychosocial, pharmacologic, and combined interventions in ameliorating deleterious effects of personality disorders on cardiovascular morbidity and mortality.
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Acknowledgments
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Preparation of this report was supported in part by the National Institutes of Health under Grants R01-MH60417, R01-MH60417-Supp, R01-DA13444, R01-DA018883, R01-DA14618, R01-DA016855, P50-AA03510, and P50-DA09241. We thank the NIAAA and the U.S. Census Bureau field representatives who administered the NESARC interview.
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Footnotes
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Decision Editor: Karen Hooker, PhD
Received for publication December 27, 2006.
Accepted for publication April 13, 2007.
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References
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- American Psychiatric Association. (2000). Diagnostic and statistical manual of mental disorders (4th ed., rev.). Washington, DC: American Psychiatric Association.
- Denollet, J., Conraads, V. M., Brutsaert, D. L., DeClerck, L. S., Stevens, W. J., Vrints, C. J. (2003). Cytokines and immune activation in systolic heart failure: The role of type D personality. Brain, Behavior, and Immunology, 17,304-309.[Medline]
- Denollet, J., Pedersen, S. S., Vrints, C. J., Conraads, V. M. (2006). Usefulness of type D personality in predicting five-year cardiac events above and beyond concurrent symptoms of stress in patients with coronary heart disease. American Journal of Cardiology, 97,970-973.[Medline]
- Grant, B. F., Dawson, D. A., Stinson, F. S., Chou, S. P., Kay, W., Pickering, R. (2003). The Alcohol Use Disorder and Associated Disabilities Interview Schedule (AUDADIS): Reliability of alcohol consumption, tobacco use, family history of depression and psychiatric diagnostic modules in a general population sample. Drug and Alcohol Dependence, 71,7-16.[Medline]
- Grant, B. F., Harford, T. C., Dawson, D. A., Chou, S. P., Pickering, R. P. (1995). The Alcohol Use Disorder and Associated Disabilities Interview Schedule (AUDADIS): Reliability of alcohol and drug modules in a general population sample. Drug and Alcohol Dependence, 39,37-44.[Medline]
- Grant, B. F., Moore, T. C., Shepard, J., Kaplan, K. (2003). Source and accuracy statement: Wave 1 National Epidemiologic Survey on Alcohol and Related Conditions (NESARC). Bethesda, MD: National Institute on Alcohol Abuse and Alcoholism.
- Gross, J. J., Levenson, R. W. (1997). Hiding feelings: The acute effects of inhibiting negative and positive emotion. Journal of Abnormal Psychology, 106,95-103.[Medline]
- Habra, M. E., Linden, W., Anderson, J. C., Weinberg, J. (2003). Type D personality is related to cardiovascular and neuroendocrine reactivity to acute stress. Journal of Psychosomatic Research, 55,235-245.[Medline]
- Kuper, H., Marmot, M., Hemingway, H. (2002). Systematic review of prospective cohort studies of psychosocial factors in the etiology and prognosis of coronary heart disease. Seminars in Vascular Medicine, 2,267-314.[Medline]
- Kubzansky, L. D., Cole, S. R., Kawachi, I., Vokonas, P., Sparrow, D. (2006). Shared and unique contributions of anger, anxiety, and depression to coronary heart disease: A prospective study in the normative aging study. Annals of Behavioral Medicine, 31,21-29.[Medline]
- Lautenschlager, N. T., Forstl, H. (2007). Personality change in old age. Current Opinion in Psychiatry, 20,62-66.[Medline]
- National Heart, Lung, and Blood Institute. (1998). Clinical guidelines on the identification, evaluation, and treatment of overweight and obesity in adults: Evidence report (NIH Publication No. 98-4083). Washington, DC: Author.
- Orth-Gomer, K., Rosengren, A., Wilhelmsen, L. (1993). Lack of social support and incidence of coronary heart disease in middle-aged Swedish men. Psychosomatic Medicine, 55,37-43.[Abstract/Free Full Text]
- Research Triangle Institute. (2003). Software for Survey Data Analysis (SUDAAN) (Version 8.1) [Computer software]. Research Triangle Park, NC: Author.
- Rimm, E. B., Williams, P., Fosher, K., Criqui, M., Stampfer, M. J. (1999). Moderate alcohol intake and lower risk of coronary heart disease: Meta-analysis of effects on lipids and haemostatic factors. British Medical Journal, 319,1523-1528.[Abstract/Free Full Text]
- Rosenman, R. H., Brand, R. J., Sholtz, R. I., Friedman, M. (1976). Multivariate prediction of coronary heart disease during 8.5 year follow-up in the Western Collaborative Group Study. American Journal of Cardiology, 37,903-910.[Medline]
- Smith, T. W., Ruiz, J. M. (2002). Psychosocial influences on the development and course of coronary heart disease: Current status and implications for research and practice. Journal of Consulting and Clinical Psychology, 70,548-568.[Medline]
- Wilson, R. S., Mendes de Leon, C. F., Bienias, J. L., Evans, D. A., Bennett, D. A. (2004). Personality and mortality in old age. Journal of Gerontology: Psychological Sciences, 59B,P110-P116.[Abstract/Free Full Text]
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Abstract
Methods
