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Psychosomatic Medicine 63:248-256 (2001)
© 2001 American Psychosomatic Society

SPECIAL ISSUE: COMORBIDITY STUDIES

Depression and Self-Reported Physical Health in Patients With Coronary Disease: Mediating and Moderating Factors

Mark D. Sullivan, MD, PhD, Andrea Z. LaCroix, PhD, Joan E. Russo, PhD and Edward A. Walker, MD

From the Department of Psychiatry and Behavioral Sciences (M.D.S., J.E.R., E.A.W.), University of Washington, and the Group Health Cooperative Center for Health Studies (A.Z.L.), Seattle, Washington.

Address reprint requests to: Mark D. Sullivan, MD, PhD, Associate Professor, Psychiatry and Behavioral Sciences, University of Washington, Box 356560, Seattle, WA 98195. Email: sullimar{at}u washington.edu


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 CONCLUSIONS
 REFERENCES
 
OBJECTIVES: The purpose of this study was to define how the relation between depression and self-reported physical health in patients with coronary disease is modified by other patient-centered factors.

METHODS: We conducted a prospective cohort study of 111 patients (members of a health maintenance organization) with angiographically documented coronary disease, examining factors (physical symptoms, psychological states and traits, and spousal support) modifying the relation between depression and patient-reported physical health 5 years later using multiple hierarchical regression models.

RESULTS: Five regression models (all including demographic and disease severity covariates) were constructed to predict physical health from depression only (R2 = 0.22); depression plus angina and fatigue (R2 = 0.53); depression plus positive affect and novelty seeking and their interaction (R2 = 0.48); depression plus spousal support (R2 = 0.27); and depression, angina, fatigue, positive affect, and novelty seeking (overall model) (R2 = 0.65). Depression remained significant in each model, but the proportion of variance it predicted was diminished in the presence of the other variables (bivariate r = 0.39, partial r = 0.37–0.13).

CONCLUSIONS: The effect of depression on self-reported physical health is significantly mediated by physical symptoms (angina and fatigue), personality states and traits (positive affect and novelty seeking), and spousal support. Positive affect and novelty seeking had more marked effects on physical health in the presence of more depression. Thus, a broad range of factors beyond the severity of coronary disease itself affect the perceived physical health of patients with coronary heart disease.

Key Words: coronary heart disease • depression • personality • perceived health.

Abbreviations: CAD = coronary artery disease; HMO = health maintenance organization; MAF = Multidimensional Assessment of Fatigue; MPI = Multidimensional Pain Inventory; PANAS = Positive and Negative Affect Scale; PCS = physical health component score from the SF-36; SAQ = Seattle Angina Questionnaire; SF-36 = Medical Outcomes Study Short Form-36; TPQ = Tridimensional Personality Questionnaire.


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
METHODS
 RESULTS
 DISCUSSION
 CONCLUSIONS
 REFERENCES
 
Cross-sectional studies have demonstrated a significant relationship between depression and physical disability in community (1) and clinical populations (2). Longitudinal studies of primary care patients have shown that depression and physical disability tend to change together. Those who remain depressed tend to remain disabled, whereas those whose depression improves show a reduction in disability (3, 4). New prospective studies have demonstrated that depression increases the risk (approximately 1.5 times) of physical disability onset in primary care patients (5) and community-dwelling elders (6).

The association between depression and physical disability may be strongest for those with preexisting physical vulnerability, such as the elderly and those with chronic disease (7). In these individuals, there is likely a reciprocal relationship between disability and depression (8). In studies of a single chronic disease, in which it is possible to quantify objective disease severity (eg, systemic lupus erythematosus), depression and disability are associated with each other but not with disease severity (9, 10). Depression is associated with increased physical disability and somatic symptoms in neurology patients even though the patients attribute these to their neurological disorder (11).

We have previously shown that depression and anxiety predict self-reported physical disability in coronary disease patients for up to 5 years (12, 13). The process by which this occurs largely remains to be elucidated. The effect of depression on disability in this population is so powerful that any exploration of other psychosocial predictors of disability should include consideration of the depression effect. Reduction in self-efficacy seems to play a role but accounts for only a small portion of the depression effect on disability (14). Better understanding of the factors through which depression exerts its effect on physical health (mediating variables) and factors that modify the effect of depression on physical health (moderating variables) could clarify the nature of the depression effect and help inform clinical interventions. If angina mediates the effect of depression on physical health, for example, it means controlling for angina will diminish the strength of the relation between depression and physical health. This might occur clinically if depression increases the severity of angina. If positive affect moderates the effect of depression on physical health, for example, patients with low positive affect may show a greater effect of depression on physical health than those with higher positive affect. This might occur clinically if positive affect is protective for physical health in the presence of significant depression but plays little role in the absence of depression.

We examined three types of potential mediating and moderating factors: 1) physical symptoms, 2) psychological states and traits, and 3) spousal support. We hypothesized that physical symptoms would mediate the depression effect and that psychological and spousal variables would moderate the depression effect.


   METHODS
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
RESULTS
 DISCUSSION
 CONCLUSIONS
 REFERENCES
 
Patient Sample
Patients were recruited from the Group Heath Cooperative of Puget Sound, a consumer-owned HMO in western Washington. Between December 1991 and February 1993, all Group Health Cooperative members aged 45 to 80 years undergoing elective cardiac catheterization for suspected CAD were screened for participation in the study. Inclusion criteria were as follows: 1) at least 50% occlusion of one major coronary vessel confirmed by angiography, 2) treadmill stress test within the past year, 3) CAD was the subject’s most disabling disease, and 4) the subject was ambulatory at the time of catheterization. Two hundred six members (86% of eligibles) provided consent and completed an extensive baseline psychosocial interview. One hundred sixty-one subjects completed all assessments at baseline and 1 year later. One hundred twenty-seven subjects completed a 6-year assessment done by phone interview and a mailed questionnaire. A total of 111 patients had complete baseline, 1-year, and 6-year data for the present analyses ( Figure 1). Of the 34 subjects lost to follow-up during the 5-year follow-up interval (between the 1- and 6-year time points), 21 were ineligible for the following reasons: death (10), dementia (2), critical illness (4), left Group Health Cooperative before completion of the 5-year follow-up period (3), or could not be contacted (2). Fourteen additional subjects declined to complete the 6-year interview or questionnaires. Two subjects had too many missing data to be included.



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  		Fig. 1. Subject flow chart.

 
Procedures
Subjects who had completed the baseline and 1-year assessments were mailed postcards notifying them of the planned 6-year follow-up study. A research assistant then called all of these subjects, except those who requested not to be contacted, to obtain informed consent for the follow-up study. A reminder postcard was sent 2 weeks later if the questionnaires had not been received. A phone call was made 1 month later. Another packet was mailed or the questionnaire was administered over the phone if necessary. The research protocol and informed consent procedures were approved by the Human Subjects Review Committees of the University of Washington and the Group Health Cooperative of Puget Sound.

Measures
Primary outcome.
The physical health component score (PCS) from the Medical Outcomes Study SF-36 administered 6 years after cohort inception was used. This score provides a broader summary of physical health than the physical functioning score of the SF-36 and has similar relative validity. The PCS positively weights scores from the physical function, physical-role, bodily pain, and general health perception scales. The PCS negatively weights the mental health and emotional-role scales to provide an orthogonal relationship between the PCS and the mental health component score of the SF-36 (15). Simon et al. (16) have criticized this artificial "cleansing" of mental health elements from the PCS. For our purposes, it provides a conservative estimate of the impact of psychosocial variables on perceived physical health.

Predictor variable.
The Hamilton Rating Scale for Depression was used to assess severity of depressive symptoms. This was administered 12 months after cohort inception using a phone interview by a research assistant trained and supervised by Dr. Sullivan. This 24-item interviewer-administered scale is the psychiatric standard for the assessment of the severity of depression and can correct for reporting bias that can affect self-report scales, allowing for more accurate characterization of psychiatric symptoms (17). It has been validated for phone administration (18).

Mediating and moderating variables.
All mediating and moderating variables were assessed concurrently with the main outcome variable at 6 years to maximize their relevance to the outcome. The exceptions were the TPQ score, which was assessed at 0 months because it is a trait variable, and spousal support, which was assessed at 12 months to provide prospective data (see Figure 2). The following variables were assessed: 1) physical symptoms: angina frequency (using the SAQ, a disease-specific quality-of-life measure for patients with coronary artery disease that has been validated against both clinical and other self-report measures; Ref. 19) and fatigue severity and frequency (using the MAF; Ref. 20); 2) psychological states and traits: current positive and negative affect (using PANAS) and personality traits (harm avoidance, novelty seeking, and reward dependence, using the TPQ); and 3) subject report of spousal support: overall support and solicitous, punishing, and distracting responses to subject’s illness behavior (using the MPI) and two questions concerning change in quality or closeness of marital relationship in the presence of heart disease.



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  		Fig. 2. Model variables.

 
Covariates.
The following covariates were included: 1) age; 2) gender; 3) cardiovascular events (myocardial infarction, bypass grafting, or angioplasty) during the follow-up period as ascertained through automated HMO utilization data; 4) cardiac disease severity (number of four main coronary vessels stenosed >70% as confirmed by angiography at baseline; this was chosen from among various standard measures of objective disease severity because it showed the strongest relation to physical function in our previous study on this cohort; see Ref. 12); and 5) a pharmacy-derived chronic disease score covering the 12 months before the 1-year assessment (this was used to control for the effect of medical comorbidity on physical health; see Ref. 19). Conceptual grouping and relative timing of study variables is shown in Figure 2.

Statistical Analyses
The purpose of the analyses was to determine whether physical symptoms, psychological states and traits, and spousal support mediate or moderate the longitudinal relationship between depression and self-reported physical health. The dependent variable for all the analyses was the PCS from the SF-36 assessed at the 6-year follow-up. After examining the distributions of all study variables, we first tested multiple regression models within each construct group: symptom variables, psychological variables, and marital variables. In every model six covariates were included: age, gender, medical comorbidity (chronic disease score), coronary disease severity (number of vessels stenosed >70%), cardiovascular events during follow-up, and education level. For each construct the main effects were tested to examine mediating effects, and the interactions between depression and construct variable were tested to examine moderating effects. Because of the amount of collinearity within models, each interaction or moderating effect was tested individually. For each construct a final model was constructed using all significant interactions, the main effects necessary to support them, any other significant main effects, depression, and the covariates. This procedure resulted in a model for each of the personality, medical, and marital variables. The significant terms from these three models were combined to produce an overall summary model. Variables that became insignificant (with the exception of covariates) were omitted from the overall summary model. In the event of significant interactions, post hoc Pearson correlations were computed to interpret the findings.


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
DISCUSSION
 CONCLUSIONS
 REFERENCES
 
Study Cohort
Characteristics of subjects in the current study are shown in Table 1. The typical patient was a man in his 60s with at least a high school education. Twenty-nine percent of the sample underwent a revascularization procedure during the first year after the index catheterization. An additional 30% underwent a revascularization procedure during the 5-year follow-up period. No statistically significant differences were found in demographic, coronary disease, or psychiatric variables between subjects completing follow-up and those lost to follow-up.


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  		Table 1. Sample Characteristics
 
Table 2 shows the model with just baseline demographics (including severity of coronary artery disease and medical comorbidity), cardiovascular events during follow-up, and depression at 1 year. Baseline demographics accounted for 7% of the variance in the 6-year physical component score. The 1-year depression score added an additional 15% of explained variance so the total model explained 22% of the variance in self-reported physical health at 6 years.


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  		Table 2. Depression-Only Modela
 
Table 3 describes the physical symptoms model. All three candidate variables (fatigue severity, fatigue frequency, and angina frequency) were significant mediators of the effect of depression on physical health. Subjects with more frequent or severe fatigue and more frequent angina reported poorer physical health. The correlation between depression and physical health was reduced by two-thirds (from -0.39 to -0.13) after adding fatigue and angina to the model. None of these variables had a significant interaction with depression, indicating that they did not moderate the depression effect on physical health. The model was highly significant (p < .001) and accounted for 53% of the variance in the PCS.


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  		Table 3. Physical Symptoms Modela
 
Table 4 describes the psychological states/traits model. Six-year positive and negative affect were entered into the model with the 1-year Hamilton Depression score. Because of collinearity between the 6-year negative affect and 1-year Hamilton Depression score, the interaction term could not be sustained in the model. Positive affect had significant main and interaction effects, indicating that it both mediated and moderated the effects of depression on physical health. The correlation between depression and physical health was reduced by one-third (from -0.39 to -0.24) after adding positive affect, novelty seeking, and their interactions with depression to the model.


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  		Table 4. Psychological States and Traits Modela
 
To examine the moderating effect of positive affect on the depression effect, two depression groups were formed. Subjects were stratified above and below a Hamilton score of 8. A score of 8 or below is accepted as depression remission in psychopharmacology and psychotherapy trials (21). For patients with low depression, there was no difference in physical health by amount of positive affect. In sharp contrast, patients with higher levels of depression reported much better physical health if they also reported higher levels of positive affect. This effect is demonstrated in Figure 3.



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  		Fig. 3. Interaction of 12-month Hamilton Depression scores with 72-month positive affect. Means were adjusted for covariates.

 
Neither harm avoidance nor reward dependence were significant predictors of the PCS. Novelty seeking had no significant main effect but did have a significant interaction effect with depression, indicating that it serves as a moderator of the depression effect. For patients with low depression levels (Hamilton score <=8), novelty seeking was not related to physical health. For patients with higher depression levels, higher novelty seeking was associated with worse physical health. This effect is shown in Figure 4. The psychological states/traits model accounted for 48% of the variance in the 6-year PCS.



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  		Fig. 4. Interaction of 12-month Hamilton Depression scores with TPQ novelty seeking. Means were adjusted for covariates.

 
Table 5 describes the spousal support model. Twelve-month subject reports of spousal support and response to illness behavior were entered into the model with the 12-month Hamilton Depression score. Reports of specific spouse behaviors (coded as solicitous, punishing, or distracting) were not significant mediators or moderators of the depression effect on physical health. However, perceived support from the spouse did mediate the effect of depression on physical health with those reporting more support also reporting worse physical health 5 years later. The correlation between depression and physical health was only slightly reduced (from -0.39 to -0.37) after adding spouse support to the model This model accounted for 27% of the variance in the 6-year PCS.


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  		Table 5. Spouse Behavior Modela
 
Table 6 describes the overall summary model, into which all of the above variables were entered. Two physical symptom variables (fatigue severity and angina frequency) and two psychological state/trait variables (positive affect and novelty seeking, as well as their interactions), but no spouse behavior variables, remained in the model. The correlation between depression and physical health was reduced by almost three-fourths (from -0.39 to -0.10) after adding fatigue, angina, positive affect, and novelty seeking to the model. This overall model accounted for 65% of the variance in the 6-year PCS.


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  		Table 6. Overall Summary Modela
 

   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
CONCLUSIONS
 REFERENCES
 
The results of this 5-year prospective study demonstrate that physical symptoms, psychological states and traits, and spouse behavior mediate and/or moderate the effect of depression on self-reported physical health. Once all variables are entered, spousal support no longer remains significant in the model predicting physical health. With the exception of the spouse model (which accounted for 27% of the variation in physical health), the models accounted for large fractions of the variation (48% to 65%) in physical health reported by our subjects. Consistent with our hypotheses, physical symptoms had only a mediating effect, whereas psychological factors had both mediating and moderating effects. Spousal support had a mediating effect in the model with depression only. Although depression has strong independent effects on physical health over a 5-year period for patients with CAD, this occurs in the context of other nondisease factors that shape illness experience and impact. Figure 5 provides examples of mediating and moderating effects.



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  		Fig. 5. Examples of mediating (top) and moderating (bottom) effects.

 
Angina and fatigue are considered cardinal symptoms of coronary heart disease. They are prime targets for disease-specific medical and surgical therapies (22). However, our physical symptoms model suggests that these symptoms may be one way in which depression reduces physical health in patients with heart disease. Depression may manifest itself in patients with coronary disease through a worsening of angina and fatigue. This is consistent with findings of previous studies. Fatigue was not related to cardiorespiratory fitness in one study of 140 patients with cardiac disease but clearly was associated with negative affect (23). In our study, 72-month fatigue may mediate the effect of 1-year depression because this fatigue is strongly correlated with 6-year depression (r = 0.50, p < .001). Depression is predictive of angina in post-MI patients (24) and in patients undergoing exercise testing (25). This is not meant to imply that depression is the sole cause of angina or fatigue in these patients. Depression, angina, and fatigue exist in a complex, mutually reinforcing relationship (26). Depression may increase ischemia through sleep and autonomic changes (27), particularly in those with established atherosclerosis (28).

Although early explorations of psychological factors in heart disease focused on Type A behavior, recent studies have found negative affectivity to be a better predictor of disease outcomes (29). This broad construct encompasses aspects of depression, anxiety, anger, and hostility (30). The relative contributions of state and trait factors has not been studied. Positive affect and negative affect are claimed to represent independent dimensions of current psychological state. This seems to be true in our sample, in which positive and negative affect were very weakly correlated (r = 0.03). We found that concurrent negative affect did not add to the power of depression measured 5 years earlier to predict physical health. However, positive affect did moderate the effect of depression. In those with some depressive symptoms (Hamilton score >8), low positive affect was associated with worse reported physical health. This suggests that negative and positive affect may each make important contributions to perceived health in patients with coronary disease.

Neuroticism is the trait measure most associated with negative affectivity. The TPQ scale that most closely corresponds to neuroticism is the harm avoidance scale. In our study, this scale (measured at baseline) did not add to the power of 1-year depression to predict physical health. Like the state of negative affect, the trait of harm avoidance is likely too closely related to depression to remain in the model. However, novelty seeking did mediate and moderate the depression effect. Among more depressed subjects, those with high novelty seeking reported worse physical health than those with low novelty seeking. High novelty seeking suggests impulsivity and has been linked with suicide and substance abuse in multiple studies (31). Why novelty seeking should amplify the effect of depression on perceived physical health is not clear. Given its link with substance abuse, novelty seeking might be linked with increased cigarette smoking. But in our sample, subjects who currently smoked (N = 6) or ever smoked (N = 105) were not higher in novelty seeking than those who did not. Increased disease progression by another mechanism is also possible. But the metabolic cardiovascular (or insulin resistance) syndrome, a risk factor for coronary disease progression, has been linked with high reward dependence, average novelty seeking, and low harm avoidance (32). Of the four subscales of novelty seeking, we see the strongest relation with "impulsiveness vs. reflection." This suggests that individuals high in novelty seeking may react in an "all-or-nothing" way to symptoms and functional deficits, producing worse perceived health, especially in the face of depression.

Spousal support in chronic disease is almost always thought to provide benefit. However, some recipients of spousal caregiving respond negatively (33). There is also evidence that support can be disabling if spouses are too solicitous in response to illness behavior (34). Here we found that neither solicitous, distracting, nor punishing behavior from spouses (as reported by subjects) affected perceived health, but overall perceived support from the spouse did have an effect. Subjects who saw their spouses as helpful/supportive, worried, and attentive to them because of their heart symptoms at 12 months reported poorer physical health at 72 months. Subjects who felt more supported at 12 months were also somewhat more depressed at 12 (r = 0.21, p = .01) and 72 months (r = 0.20, p = .04). Interestingly, these feelings of support at 12 months were negatively associated with subject-reported marital quality (assessed by Dyadic Adjustment Scale) at baseline. The marital satisfaction subscale in particular was negatively associated with later reports of support (r = -0.32, p = .001). This suggests that illness may be improving marital closeness in these couples. However, direct questions about improved closeness and satisfaction with marriage failed to confirm this relationship with perceived support or reported physical health. These findings thus remain to be confirmed and clarified in future studies. Marital support did not remain significant in the model once physical symptoms and psychological states and traits were entered.

The final model included fatigue severity, angina frequency, positive affect (and depression interaction), and novelty seeking (and depression interaction). This final model accounted for 65% of the variation in the SF-36 PCS. This suggests that a large portion of the reduction in physical health reported by those with coronary disease may be due to factors other than organ impairment. (Angina and fatigue could be driven by cardiac ischemia not picked up by our disease severity measures.)

There are a number of limitations to our study. First, our coronary disease severity measure from angiography was obtained 1 year before the time period examined in our study. We corrected this measure for intervening revascularization and cardiovascular events, but it remains an imperfect measure. Second, we relied on self-reports of physical health for our primary outcome measure. Self-reports allow assessment of symptoms and function as they occur in daily life. This is important because of the weak relations noted between laboratory assessments of functional capacity in coronary disease and performance of daily activities (35). To address the possibility of response bias, we asked spouses for their assessment of subjects’ performance in their daily activities and roles. These showed only slightly less strong relationships with subjects’ depression (data not shown), suggesting that this effect cannot be attributed solely to subject response bias. Third, our population was almost entirely white and was highly educated compared with the whole population with coronary disease. We (36) and others (37) have shown that social class has potent effects on coronary disease outcomes. Therefore, we must be careful about generalizing to other coronary disease populations from our group. Fourth, this was an observational study of a clinical population. Although our prospective data suggest that depression and the other patient-reported factors examined decrease perceived health in patients with coronary disease over a 5 year period, definitive demonstration of a causal relationship would require an experimental design in which depression was treated and disability reduced.


   CONCLUSIONS
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 CONCLUSIONS
REFERENCES
 
More than 60 million Americans have some form of cardiovascular disease. The costs of treating this disease are still increasing, from $128 billion in 1994 to $151 billion in 1996 (38). Nevertheless, these direct medical costs are dwarfed by the indirect costs linked to disability caused by CAD (39). For example, CAD is the leading reason for Social Security disability payments, accounting for 25% to 35% of the cost of this program (40). Because more people with CAD are living longer, it is increasingly important to manage this disease to minimize not only its progression but also its impact on patients’ lives. A recent study showed that the SF-36 PCS was an independent risk factor for 6-month mortality after coronary artery bypass graft surgery (41). This suggests that perceived health may affect mortality rates as well.

The results of our study suggest that management of depression in combination with training in symptom management and coping strategies (such as relaxation training and positive activity scheduling) might be a valuable addition to the coronary disease care maps now common in managed-care settings (42). Randomized trials of cardiac rehabilitation services have demonstrated reduced levels of depression (43). Further research will be needed to determine how cost-effective these interventions are toward improving the quality of life of patients with CAD.

Received for publication July 18, 2000.


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 CONCLUSIONS
 REFERENCES
 

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