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Published online before print November 1, 2006, 10.1097/01.psy.0000240779.55022.ff
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Psychosomatic Medicine 68:844-850 (2006)
© 2006 American Psychosomatic Society

ORIGINAL ARTICLES

Covariation of Psychological Attributes and Incident Coronary Heart Disease in U.S. Air Force Veterans of the Vietnam War

Stephen H. Boyle, PhD, Joel E. Michalek, PhD and Edward C. Suarez, PhD

From the Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, North Carolina (S.H.B., E.C.S.); and the Air Force Research Laboratory, Brooks-City Base, Texas, University of Texas Health Science Center at San Antonio, Texas (J.E.M.).

Address correspondence and reprint requests to Stephen H. Boyle, PhD, or Edward C. Suarez, PhD, Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, PO Box 3328, Durham, NC 27710. E-mail: boyle020{at}mc.duke.edu or suare001{at}mc.duke.edu


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 NOTES
 REFERENCES
 
Objective: The purpose of the present investigation was to examine the prospective associations of hostility, anger, depression, and anxiety, alone and in combination, to incident coronary heart disease (CHD).

Methods: Subjects were 2105 men who participated in the Air Force Health Study, a 20-year study designed to evaluate the effects of herbicide exposure on various health outcomes in Air Force veterans of Operation Ranch Hand. Psychological attributes were assessed in 1985 using scales constructed from the Minnesota Multiphasic Personality Inventory. Participants were followed for an average of 15 years for evidence of ischemic heart disease (International Classification of Diseases codes 410–414, 428.4, or 36). The relation between psychological attributes and CHD was examined with Cox proportional hazard models.

Results: Adjusting for CHD risk factors, depression, anxiety, hostility, and trait anger were significant predictors of incident CHD. In addition, a factor analytically derived psychological risk factor composite score was the strongest predictor of CHD.

Conclusions: These results suggest that the covariation of hostility, anger, depression, and anxiety accounts for the increased risk of CHD associated with each individual factor. The results of this study challenge the conventional approach of examining these psychological attributes in isolation.

Key Words: anger • hostility • depression • anxiety • coronary heart disease • men

Abbreviations: BMI = body mass index; CMHS = Cook Medley Hostility Scale; CHD = coronary heart disease; CRP = C-reactive protein; HDL = high-density lipoproteins; IL-6 = interleukin-6; MMPI = Minnesota Multiphasic Personality Inventory; PRF = psychological risk factor.


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
METHODS
 RESULTS
 DISCUSSION
 NOTES
 REFERENCES
 
"Are disease-prone people both angry and depressed or angry but not depressed, or is either of these states sufficient? This is a question that deserves immediate attention" (H.S. Friedman & Booth-Kewley, 1987, p. 552).

The field of psychosomatic medicine has witnessed an explosion of research documenting the negative impact of individual psychological attributes on the development and progression of coronary heart disease (CHD). The results of those research efforts have yielded evidence from both prospective and cross-sectional studies suggesting that an increased risk of CHD is associated with anger, hostility, depression, and anxiety (1,2). Under the assumption that each attribute exerts an independent effect on CHD, most researchers have examined the impact of each individual psychological attribute in isolation. In contrast, little attention has been directed to the questions posed by Friedman and Booth-Kewley (3) regarding the effect of multiple psychological attributes on the development and progression of CHD (e.g., (4)). Empirical evidence addressing these issues is relevant not only in understanding the role of multiple psychological attributes in disease onset and progression, but also in developing effective intervention strategies that target more than one attribute.

It is well established that anger, hostility, depression, and anxiety are unique psychological constructs; that they tend to cluster within individuals; and that measures of these constructs typically showing modest intercorrelations (1). The degree of shared variance among these constructs has led some to suggest that the overlap among these constructs accounts for the increased risk of CHD associated with each attribute. Angry people may be at greater risk for CHD because they are also hostile, depressed, and anxious. Similarly, depressed people may be at greater risk for CHD because they are also angry, anxious, and hostile. It is possible that the covariation of these attributes represents distinct processes that influence the development of CHD (1,2).

To date, no studies have examined the covariation of hostility, depression, anxiety, and anger in relation to the development of CHD. This, however, has not been the case with research on cardiovascular risk factors. The prevalent approach in this laboratory has been to examine the relation of cardiovascular risk factors to both the unique and shared variance among psychological attributes associated with increased risk of CHD. For example, Suarez (5,6) examined the relation of depressive symptoms, anger, and hostility to C-reactive protein (CRP) and interleukin (IL)-6, well-established biomarkers of inflammation shown to predict increased risk of CHD (7,8). Although the data suggested unique associations, a factor analytically derived composite score was the strongest predictor of both CRP and IL-6. Similarly, fasting insulin and estimated insulin resistance were associated with hostility, anger expression, and severity of depressive symptoms but a factor composed of these attributes appeared to be a better predictor (9). Although those data were specific to risk factors, it is likely that the same approach would help refine our understanding of the role of psychological attributes of CHD.

The current study examined the unique and joint contributions of hostility, depression, anxiety, and anger to incident CHD in a sample of men. In light of our previous observations, we hypothesized that hostility, depression, anxiety, and anger would significantly predict incident CHD, but the combination of these factors would be the best predictor.


   METHODS
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
RESULTS
 DISCUSSION
 NOTES
 REFERENCES
 
Subjects
The sample used in this study consisted of participants in the Air Force Health Study (AFHS). A detailed description of the study design and the participant selection procedure has been published previously (10). Briefly, the AFHS was designed to evaluate the health of the veterans of Operation Ranch Hand, the unit responsible for the aerial spraying of Agent Orange and other dioxin-contaminated herbicides in Vietnam from 1962 to 1971. Initially, all living Ranch Hands and a matched comparison group of Air Force veterans who served in Southeast Asia but were not occupationally exposed to herbicides in Vietnam were invited to participate in a 20-year health study. Physical and psychological examinations were administered in 1982, 1985, 1987, 1992, 1997, and 2002. Participation was voluntary and informed consent was obtained at the examination sites. A total of 2309 (1017 Ranch Hands and 1292 comparisons) participated in the 1985 examination. The examination content emphasized detection of medical end points suspected of being associated with exposure to dioxin, so extensive data on health status and health behaviors were collected. The 1985 examination also included the administration of the Minnesota Multiphasic Personality Inventory (MMPI). For the purposes of these analyses, the 1985 examination was considered the baseline and exposure was computed from that point. Participants were excluded from analyses if they showed evidence of ischemic heart disease (N = 134) in 1985, if they completed the 1985 examination but did not participate in any future examinations (N = 64), if they were missing MMPI data (N = 2), or were missing data on one or more of the covariates (N = 4). The final sample size used in the analyses for this study was 2105. The mean age of the participants in 1985 was 46.7 (standard deviation = 7.6) and 6.3% were black. See Table 1 for a further description of study participants. This study was approved by the Institutional Review Board of Brooks City-Base.


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  		TABLE 1. Baseline Characteristics of Study Participants (N = 2105)

 

Measurement of Psychological Risk Factors
All participants were administered the 566-item MMPI at entry. Participants who failed to complete 20% of the items on any psychological scale (N = 2) were excluded from the analyses. Scores for subjects with <20% incomplete items were prorated. Assessments of psychological attributes were derived from specific MMPI items.

Hostility
Hostility was assessed by a 25-item abbreviated version of the 50-item Cook-Medley Hostility Scale (CMHS) (11). The reason for using this abbreviated version was partly based on a rational analysis of the item content of the CMHS by Barefoot et al. (12). They identified four subsets of items reflecting the cognitive (i.e., cynicism and hostile attributions), affective (i.e., hostile affect), and the behavioral (i.e., aggressive responding) dimensions of hostility and two additional item subsets (i.e., social avoidance and other) that reflected constructs other than hostility. The items from these two subsets were not used in the current study because, in addition to not reflecting the hostility construct, evidence suggests that these subscales are poor predictors of health outcomes (12–15). Also, because the affective dimension was assessed using a separate scale (see subsequently), we used a scale comprised of the items that were identified by Barefoot et al. (12) as reflecting the cognitive dimension (e.g., "It is safer to trust nobody"). Previous studies have shown items that assess the cognitive aspect of hostility to significantly predict CHD (13,16), coronary calcification (17), progression of carotid atherosclerosis (18), and mortality from all causes (12,13).

Anxiety
Symptoms of anxiety were assessed by a short form of the anxiety content scale from the MMPI-2 (19,20). This scale has been shown to correlate highly with other symptom-based measures of anxiety (21,22). The anxiety scale (e.g., "I frequently find myself worrying about something") used in the present study contained 19 of the 23 items from that scale that also appear in the MMPI.

Depression
The 40-item Obvious Depression Scale (OBD) was used to measure depression. Although the D scale is the most widely used MMPI-based measure of depression in psychiatric contexts, this scale has not been used extensively in studies examining the relation of depression to incident CHD. One reason is that an inspection of the items reveals the content to be quite heterogeneous with only some being face-valid reflections of depression. On the basis of face validity, this scale has been divided into obvious and subtle subscales. The OBD is a straightforward measure of depressive symptoms experienced outside the psychiatric context (e.g., "I am happy most of the time") and has been shown to be more appropriate for nonclinical samples than the widely known D scale (23). Obvious indicators of depression have been shown to be more highly correlated with several criterion measures than the more subtle items (24,25). The OBD has been shown to correlate 0.72 with the CES-D (26) and 0.78 with the Zung Self-Rating Depression Scale (27) in a community sample (28). In one previous study, the OBD scale predicted myocardial infarction (MI) and mortality in a population sample (29). The OBD scale shares four items with the anxiety content scale. Because the content of those items appeared to reflect anxiety (e.g., "I believe I am no more nervous than most others"), we removed them from the OBD scale to eliminate the redundancy.

Trait Anger
Trait anger was assessed with an 11-item scale. The selection of these particular items was based on a previous factor analysis of MMPI-2 items that resulted in a 16-item trait anger scale. That study found a significant relation between trait anger and incident CHD in a sample of 1300 men (30). The trait anger scale (e.g., "I am not easily angered") used in this study consisted of the 11 items from the 16-item MMPI-2-derived scale that also appear in the original MMPI-1*. This 11-item scale correlated 0.58 with the SCL-90 hostility subscale in a sample of 774 army veterans.

Psychological Risk Factor Score
The four psychological variables (i.e., hostility, anger, depression, anxiety) were subjected to a principle components analysis. This analysis yielded a single factor, Psychological Risk Factor (PRF) (eigenvalue = 2.65, percent of variance accounted = 66.1%). As expected from the intercorrelations, all four variables positively loaded on this factor (see Table 2). Thus, high scores on this composite measure reflected individuals who were hostile, prone to anger, and had elevated levels of symptoms of depression and anxiety (5).


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  		TABLE 2. Factor Loadings for Psychological Attributes (N = 2105)

 

We explored the construct validity of this measure in an independent sample of 350+ men and women enrolled in laboratory studies of physiological mechanisms. Hostility, anger, depression, and anxiety were assessed through the Cook Medley Hostility Scale (11), the Buss-Perry Anger Scale (31), the Beck Depression Inventory (32), and Spielberger’s Trait Anxiety Scale (33). Scales were selected on the basis of methodological (i.e., self-report) and construct similarities the measures in the current study. Participants were also administered the NEO-PI (34), which contained the following five scales: neuroticism, extraversion, agreeableness, conscientiousness, and openness to experience. A principle components analysis yielded a single factor (eigenvalue = 2.34, percent of variance accounted = 66%) that was similar to the one described in Table 2. The PRF score was positively associated with neuroticism (r = 0.80, p < .0001) and negatively associated with agreeableness (r = –0.53, p < .0001). The PRF score was also significantly associated with conscientiousness (r = –0.18, p < .003) and extraversion (r = –.23, p < .0001), although the magnitude of these correlations was much smaller. Finally, the PRF score was not significantly related to the openness to experience domain (r = –0.07, not significant). Although the latent construct represented by the PRF scores appears to incorporate aspects of neuroticism and agreeableness, it shares a greater percentage of variance with the neuroticism domain. The magnitude of the correlations between PRF and the other domains were trivial in size.

Baseline Indicators of Risk
Hypertensive Status
Hypertensive status was measured as a dichotomous variable (i.e., hypertensive/normotensive). The basis for this classification was the physician’s diagnosis. All reported conditions were verified by medical record review and were coded according to the International Classification of Diseases, 9th Edition, Clinical Modification (ICD-9-CM). We studied diagnosed hypertension (ICD 401). We did not study blood pressure measurements because many study participants had taken or were taking antihypertensive medications.

Body Mass Index
Body mass index (BMI) was calculated as weight (in kilograms) divided by height (in meters squared).

Blood Chemistry
Blood specimens were obtained following an overnight fast. Participants were requested to adhere to a 250-g carbohydrate diet and avoid alcohol consumption for 3 days before their arrival to prepare for 2-hour postprandial glucose testing. These samples yielded measures of total serum cholesterol, high-density lipoproteins (HDL), and glucose.

Diabetes Status
Presence of diabetes was measured as a dichotomous variable. Evidence of diabetes was defined by physician diagnosis or by a 2-hour postprandial glucose ≥200 mg/dL at the 1982 or 1985 physical examinations (N = 95).

Smoking
Smoking was measured as the number of cigarettes per day during the 2-week period before the physical examination.

Preexisting Coronary Heart Disease
The possible existence of CHD was evaluated in two ways. First, participants provided a detailed medical history that included questions about previous heart trouble. Medical records were used to verify all reported conditions and to determine the time of occurrence of major cardiac conditions. Second, an electrocardiogram (ECG) evaluated the possible existence of a previous heart condition. ECGs were obtained after a 4-hour fast and abstinence from tobacco. Participants with ischemic heart disease (ICD-9 codes 410–414) diagnosed during or before the 1985 AFHS physical examination were excluded from these analyses.

Coronary Heart Disease Morbidity
Participants in the AFHS were invited to participate in a series of follow-up examinations that were conducted in 1987, 1992, 1997, and 2002. Participation rates for these examinations were high. During the examination health interviews, each participant was asked if they had a heart condition. Medical records were sought to verify the existence of any major heart conditions (e.g., MI), including whether they had undergone surgical procedures suggestive of coronary disease (e.g., percutaneous transluminal coronary angioplasty) and to determine the date of its first occurrence. In addition, a resting ECG was performed to detect evidence of a heart condition, including a prior MI. Over the follow-up period from 1985 to 2003, 425 new cases of ischemic heart disease (IHD) (ICD codes 410–414, 428.4, 36) were detected. The median length of follow up for those participants that did not experience an event was 16.9 years (minimum, 1.4 years; maximum, 18.7 years).

Data Analytic Strategy
The relation of the psychological attributes to incident CHD were examined using Cox proportional hazard models. An initial set of models were fitted that included age as a covariate. A second set of models were fitted with age, total cholesterol, smoking status, hypertensive status, diabetes status, HDL, and BMI measured in 1985 as covariates. Effect sizes are reported as hazard ratios (HRs) comparing a person at the 75th percentile of the scale to the 25th percentile. Effect sizes are interpreted as the risk of a person in the middle of the upper half of the distribution compared with the risk of a person in the middle of the lower half of the distribution of the scale. The dependent variable was time to onset of CHD, defined as the minimum of the number of years from the 1985 physical examination to the first diagnosis of CHD, death, or the last physical examination attended.


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
DISCUSSION
 NOTES
 REFERENCES
 
Pearson correlations were used to examine the relation of the psychological attributes to the CHD risk factors (see Table 3). All psychological attributes were significantly and positively associated with number of cigarettes smoked per day. Hostility was significantly and negatively associated with HDL. Depression, anxiety, hostility, and the composite score were positively and significantly associated with diabetes status. Anger, hostility, anxiety, and the composite score were significantly and negatively associated with age. None of the scales were significantly associated with BMI, hypertensive status, or total cholesterol.


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  		TABLE 3. Correlations Between Psychological Attributes and Coronary Heart Disease Risk Factors (N = 2105)

 

In age-adjusted models, all four psychological attributes were significantly associated with risk of developing CHD. Increased risk of incident CHD was significantly associated with higher levels of anger ({chi}2 [1] = 12.95, p < .0004, HR = 1.24, 95% confidence interval [CI] = 1.10–1.39), depression ({chi}2 [1] = 18.30, p < .0001, HR = 1.21, 95% CI = 1.11–1.32), anxiety ({chi}2 [1] =13.90, p < .0003, HR = 1.18, 95% CI = 1.08–1.29), and hostility ({chi}2 [1] = 12.60, p < .0005, HR = 1.28, 95% CI = 1.12–1.47).

The results from the fully adjusted models were somewhat attenuated but were significant for all psychological attributes. The results were significant for trait anger ({chi}2 [1] = 12.04, p < .0006, HR = 1.23, 95% CI = 1.09–1.38), depression{dagger} ({chi}2 [1] = 9.82, p < .002, HR = 1.16, 95% CI = 1.06–1.27), anxiety ({chi}2 [1] = 9.08, p < .003, HR = 1.15, 95% CI = 1.05–1.25), and hostility{ddagger}§ ({chi}2 [1] = 11.44, p < .0008, HR = 1.19, 95% CI = 1.03–1.36).

Although each scale was associated with incident CHD in independent analysis, we examined whether any of the scales were uniquely associated with incident CHD by fitting a model that simultaneously tested the effects of anger, hostility, depression, and anxiety. Using this analytic approach, none of the scales significantly predicted incident CHD in either age-adjusted or fully adjusted models (all ps > .05). The failure of any one variable to predict incident CHD suggests that it is the shared variance that largely accounts for the relation of each individual scale to incident CHD.

We then examined whether the shared variance among the scales predicted incident CHD by using the factor-analytically derived PRF score. The PRF score, which accounted for 66% of the shared variance, was a significant predictor of incident CHD in age-adjusted ({chi}2 [1] = 22.35, p < .0001, HR = 1.28, 95% CI = 1.16–1.42) and fully adjusted models ({chi}2 [1] = 14.20, p < .0003, HR = 1.23, 95% CI = 1.10–1.36). Given these results, we sought to determine if the PRF score was a significantly better predictor of CHD than any of the individual scales. We refitted the fully adjusted models that examined the individual scales as predictors of CHD and included the PRF score in each model. We then compared the –2 log likelihood associated with the models with and without the PRF score. Results suggested that the PRF score was a significantly better predictor of incident CHD than the hostility ({chi}2 [1] = 7.44, p < .007), depression ({chi}2 [1] = 4.05, p < .05), and anxiety ({chi}2 [1] = 5.33, p < .03) scales. The result for trait anger ({chi}2 [1] = 2.20, p < .15) was similar but did not reach a conventional level of significance. Thus, the PRF score appears to be as good a predictor of incident CHD than any individual scale and a significantly better predictor than some of the individual scales.

Finally, these data were reanalyzed by including exposure group (Ranch Hand, comparison) in the models and the results remained essentially unchanged. Furthermore, there was no evidence of an interaction between any of the four psychological variables and exposure group or between PRF and exposure group.


   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
NOTES
 REFERENCES
 
The focus of this study was to examine the relation of hostility, anger, depression, and anxiety, alone and in combination, to incident CHD over a 15-year follow up. Evaluation of these psychological factors showed that each attribute was significantly associated with an increased risk of CHD. In a model that simultaneously evaluated their independent effects, however, none of the scales significantly predicted incident CHD. A factor score representing the shared variance among hostility, depression, anxiety, and anger scales, however, was a significant predictor of incident CHD over a 15-year period. This latent variable, which accounted for 66.1% of the shared variance of the individual scales, was a significantly better predictor of incident CHD than the hostility, depression, and anxiety scales and was marginally better than the anger scale alone. The results, although adding to the growing literature that the individual attributes of anger (35–37), hostility (13,36,38,39), depression (29,40–44), and anxiety (1,2) are significant predictors of CHD, suggest that these psychological attributes share important features that significantly improve prediction of disease risk.

As noted in the "Introduction," the focus of the current study was to address the question initially posed by Friedman and Booth-Kewley (3), and recently reiterated by Suls and Bunde (2), regarding the unique and combined effects of hostility, anger, depression, and anxiety on CHD. Although the current study focused on anger, hostility, depression, and anxiety, this should not be interpreted as suggesting that these psychological attributes are the only components that incur risk and that other psychosocial variables are less important determinants of coronary health. The selection of these variables was based on a) previous observations suggesting hostility, anger, depression, and anxiety are significant predictors of CHD in prospective studies; b) our ability to use MMPI scales to assess these constructs; and c) previous work in our laboratory examining the covariation of psychological attributes in relation to measures of inflammation (5,45). We recognized, however, that other factors such as job stress (46,47) and social isolation (1,48) have also been associated with CHD and have been shown to covary with depression, anxiety, anger, and hostility (49). Thus, future research should examine whether other combinations of psychosocial risk factors are better predictors of CHD.

One unique aspect of this study was the use of the MMPI to assess trait anger. Previous studies have used the MMPI to investigate the relation of psychological factors such as hostility, depression, and anxiety to various health criteria. Because a measure of trait anger was not available, these studies were not able to examine the relation of anger to disease end points. The current study addressed this issue by using an abbreviated version of an anger scale developed from the MMPI-2 (30). In so doing, we demonstrated the predictive validity of this MMPI-derived anger scale with respect to incident CHD.

As noted, our rationale for the analytic approach used in this study was theoretically driven and empirically justified as exemplified by our studies of inflammatory markers. For example, a number of independent studies have suggested that depression (50–52), anger (53), and hostility (53,54) are associated with measures of inflammation such as CRP and IL-6. Although we have also observed these unique associations, we have demonstrated that the combination of hostility, anger, and depression is significantly associated with CRP and IL-6 in apparently healthy adults (5,45). Those findings led us to hypothesize that similar associations would exist between psychological characteristics and incident CHD. The combination of the current data and our previous laboratory observations leads us to suggest that inflammation may be one important pathophysiological mechanisms linking PRF to incident CHD.

Given that the composite score was the strongest predictor of incident CHD, the question arises, "What does the composite score measure?" The five-factor model of personality provides a useful framework for investigating the construct validity of the PRF score. Using an independent sample of 350+ adult males and females, we have shown that the composite score, defined by hostility, anger, depression, and anxiety, was strongly associated with higher levels of neuroticism and lower levels of agreeableness as assessed by the NEO-Personality Inventory (34). The observed pattern of correlations suggests that the composite score captured aspects of neuroticism and to a lesser extent agreeableness; domains of personality that have been theoretically implicated in the development of CHD (1). Although the composite score was more strongly correlated with the neuroticism domain score of the NEO-PI, it may be not be appropriate to simply label it neuroticism. As described by Costa and McCrae, the neuroticism personality domain is a multidimensional construct that encompasses aspects of impulsivity, self-consciousness, and vulnerability as well as angry hostility, depression, and anxiety (34). Given the smaller number of indicators used to define our latent variable (i.e., PRF), we suggest that a more appropriate label would be negative affectivity as recently suggested by Suls and Bunde (2).

What accounts for the shared characteristics is also open to speculation. One possibility is that cynically hostile individuals are more likely to perceive others’ behavior as threatening and respond with anger. People who are prone to anger may demonstrate higher levels of antagonistic behavior and elicit hostile behavior from others that further reinforces their negative attitude toward their social environment. Finally, high levels of hostility and anger may increase the likelihood for depression and anxiety through reduced social support. Smith and Ruiz (1) suggest the overlap among psychological risk factors may reflect transactional processes in which people both influence and are influenced by their social environment. Over time, the presence of these transactional processes may lead to an accumulation of health-eroding social contexts that ultimately result in disease (55).

Other mechanisms may help explain the covariation of these psychological attributes. For example, serotonergic dysregulation has been hypothesized to underlie depression, anxiety, hostility, and anger (56–58). In one study, depressed patients with anger attacks, who also demonstrated heightened levels of hostility, showed a significantly greater blunted prolactin response to fenfluramine challenge than depressed patients without these characteristics (59). Genetic factors may also underlie the overlap among psychological risk factors. One study (60) examined the heritability depressive symptoms, hostility, and social support in monozygotic and dizygotic twin pairs. They found that the covariation of these scales was accounted for by a single common genetic factor and a common nonshared environmental factor. Thus, serotonergic dysregulation and genetic factors may play role in the overlap observed among these scales.

The current findings may have implications on the design of intervention strategies aimed at modifying psychological attributes associated with increased risk of CHD. Psychosocial interventions on recurrent MI and survival in patients with documented MI have yielded mixed findings with few studies reporting a reduction in risk (61–63). One possibility for the mixed findings may be that the focus of these interventions was too narrow such that the interventions were aimed at reducing either one or two psychological dimensions and thus not effectively ameliorating those aspects that are shared. In view of the present findings, a more effective approach may be one that targets a broader spectrum of psychological risk factors such as hostility, anger, depression, and anxiety. Mendes de Leon (64) has expressed similar thoughts in recommending the development of interventions that target negative emotions and psychosocial risk factors in general. Such an approach recognizes that these psychological variables mutually influence one another and the effective treatment of one attribute (e.g., depression or low perceived social support) may require the effective treatment of another PRF (e.g., hostility and anger) (1).

There are some limitations of this study that should be noted. First, the participants in this study were all men and mostly nonblack, thus limiting the generalizability of these findings to women and other ethnic groups. It is important to note, however, that hostility, anger, and symptoms of depression and anxiety have been associated with increased risk of CHD in ethnically diverse samples of men and women (35,40,42,65). Subjects were men without preexisting coronary disease. It is not clear whether the combined effects of these four psychological attributes would predict adverse outcomes in patient populations. However, depression (66), and to a lesser extent anger (67) and hostility (14,68), have emerged as predictors of adverse outcomes in coronary patients. Future studies should examine these associations in more ethnically diverse samples of males and females as well as patients with preexisting disease.

Among men free of CHD, independent analyses of self-report measures of anger, hostility, depression, and anxiety were significant predictors of incident CHD. When considered simultaneously, however, none of these psychological attributes significantly predicted incident CHD. The shared variance among these four psychological characteristics emerged as the strongest predictor of disease. Although these results suggest that the overlap among psychological factors accounts for the increased risk of CHD associated with each one, there is need for replication in other large-scale prospective studies. These results suggest that it is time to move beyond the pursuit of individual psychological risk factors to consider the effects of multiple psychological attributes acting in concert in the development of CHD. The specific cause(s) of the covariation of these attributes should be thoroughly investigated.

We are grateful to Jerry Suls, PhD, for his helpful comments on an earlier version of the manuscript, especially because his assistance came during a time when the Midwest was experiencing extreme tornado activity.


   NOTES
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 NOTES
REFERENCES
 
*The corresponding MMPI item numbers for the trait anger scale are as follows: 30, 39, 96 (reversed), 105, 129, 148, 234, 336, 381, 399 (reversed), and 468. Back

{dagger}We also examined the MMPI D scale as a predictor of CHD. Adjusting for age, the D scale was a significant predictor of CHD ({chi}2 [1] = 6.27, p < .02, HR = 1.14, 95% CI = 1.03–1.26). However, this relation was no longer significant in a model that included the other CHD risk factors ({chi}2 [1] = 3.15, p < .08, HR = 1.10, 95% CI = .99–1.21). Comparing the –2 log likelihood of the previous model with one that included the D scale and OBD scale revealed that the OBD scale was a significantly better predictor of incident CHD than the D scale ({chi}2 [1] = 9.13, p < .003). Back

{ddagger}We also examined the total CMHS as a predictor of incident CHD. Adjusting for age, the CMHS was significantly associated with CHD ({chi}2 [1] = 6.87, p < 0.009, HR = 1.19, 95% CI = 1.04–1.35). However this association was no longer significant after further adjustment for other CHD risk factors ({chi}2 [1] = 2.95, p < 0.09, HR = 1.12, 95% CI = 0.98–1.27). Comparing the –2 log likelihood of this model with one that included the total CMHS score and the cynical mistrust scale revealed that the cynical mistrust scale was a significantly better predictor of incident CHD than the total CMHS ({chi}2 [1] = 5.20, p < 0.05). This is consistent with previous studies suggesting that abbreviated forms of the CMHS that more closely reflect the construct of hostility are better predictors of health outcomes. Back

§Data were reanalyzed removing those participants who showed evidence of diabetes as defined physician diagnosis or by a 2-hour postprandial glucose ≥200 mg/dL at the 1982 or 1985 physical examinations (N = 95). The pattern of results was essentially the same. Back

Received for publication April 20, 2005. Revision received June 12, 2006.

DOI:10.1097/01.psy.0000240779.55022.ff


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 NOTES
 REFERENCES
 

  1. Smith TW, Ruiz JM. Psychosocial influences on the development and course of coronary heart disease: current status and implications for research and practice. J Consult Clin Psychol 2002;70:548–68.[CrossRef][Medline]
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