Depression and social support in elderly patients with cardiac disease

Depression and social support in elderly patients with cardiac disease

Depression and social support in elderly patients with cardiac disease K. Ranga Rama Krishnan, MD,a Linda K. George, PhD,b Carl F. Pieper, DrPH,c Wei ...

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Depression and social support in elderly patients with cardiac disease K. Ranga Rama Krishnan, MD,a Linda K. George, PhD,b Carl F. Pieper, DrPH,c Wei Jiang, MD,d Rebekka Arias, CCRA,a Adair Look, MA,a and Christopher O’Connor, MDd Durham, N.C.

Background Depression is common among patients with cardiac disease. A number of psychosocial factors may affect the relationship between physical health and depression. There is evidence from the psychiatric literature suggesting that negative life events and social support are important factors in the development and outcome of depression. It is unknown if these factors are important in the context of depression in medically ill patients. Thus it is important to examine the relationship among social support, negative life events, and the presence of depression in elderly patients with cardiac disease.

Methods Patients with coronary artery disease were assessed with the Duke Depression Evaluation Schedule for the Elderly. This includes the mood and anxiety disorder section of the Diagnostic Interview Schedule modified for Diagnostic and Statistical Manual of Mental Disorders diagnoses, life events, and multidimensional assessment of social support. Two hypotheses were tested: (1) the number of concurrent negative life events will be higher in patients with coronary artery disease with major depression than those without depression, and (2) social support will be less in patients with major depression than in those without.

Results Presence of major depression was associated with increased negative life events and lowered subjective social support after accounting for age, sex, and race.

Conclusions The finding that subjective social support and negative life events are related to major depression suggests that even in the context of medical illness, social factors are still important in the development of major depression. (Am Heart J 1998;136:491-5.)

Depression is common among persons with cardiac disease. The prevalence of major depression is reported to be about 20%.1-4 By comparison, the prevalence of major depression in the elderly in the community is low, 1% to 3%.5 The role of depression in morbidity and mortality of patients with coronary artery disease (CAD) has been the focus of much research. Depression after myocardial infarction (MI) has also been associated with increased risk of death and other cardiac events such as reinfarction and cardiac arrest.6-11 There has been mounting evidence in the psychiatric literature suggesting that social support and negative life events are important factors in the development and outcome of depression.12-16 Literally hundreds of From the aDepartments of Psychiatry and Behavioral Sciences, bSociology, and cCommunity and Family Health, and the dDivision of Cardiology, Department of Medicine, Duke University Medical Center. Supported in part by MH51191, MH 40159, and MH 50570. Submitted Sept. 2, 1997; accepted March 16, 1998. Reprint requests: K. Ranga R. Krishnan, MD, Department of Psychiatry & Behavioral Sciences, Box 3018, Duke University Medical Center, Durham, NC 27710. Copyright © 1998 by Mosby, Inc. 0002-8703/98/$5.00 + 0 4/1/90412

cross-sectional studies have examined the relationships among stress, social support, and depression. The following conclusions are warranted on the basis of previous research based on samples of adults of all ages and samples restricted to older adults: (1) negative life events and chronic stress are robustly positively related to depressive symptoms and depressive disorders, (2) social support has significant main effects on depressive symptoms and disorders, (3) most (but not all) studies support the stress-buffering hypothesis, which posits that social support has stronger protective effects on depression under conditions of high stress than under conditions of low stress, and (4) subjective social support is a more powerful negative predictor of depression than objective dimensions of social support.12 There is also growing evidence suggesting a role for social support in behavioral and physical recovery in patients with CAD and MI.17,18 Low perceived social support increased post-MI17 mortality and also mortality rate in patients with CAD.19 What is not known is the importance of social factors in relation to depression in CAD. This study is designed to assess the

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Table I. Univariate statistics for total, depressed, and nondepressed samples: Percent or mean (SD) Variable Nonwhite* (%) Women (%) Currently married Education (y) Age (y) Negative life events (n) Subjective social support scale Instrumental social support scale Social network size Nonfamily interactions scale

Total (n = 184)

Depressed (n = 20)

Nondepressed (n = 164)

P value

12.5 37.5 94.6 12.0 (3.4) 66.2 (8.7) 1.00 (1.2) 26.3 (2.2) 9.4 (1.7) 2.9 (2.2) 7.3 (2.7)

30.0 55.0 95.0 11.0 (2.9) 64.8 (9.1) 1.95 (1.2) 24.3 (3.4) 9.2 (2.4) 2.7 (2.5) 5.6 (1.8)

10.4 35.4 94.5 12.1 (3.4) 66.4 (8.6) 0.88(1.1) 26.6 (1.9) 9.4 (1.6) 2.9 (2.1) 7.5 (2.7)

0.012 0.087 0.92 0.15 0.45 0.0009 0.007 0.67 0.74 0.003

*Black and Native American.

relationship among negative life events, social support, and major depression in patients with CAD. If it is shown that social support and life events are indeed important, then in future studies it becomes necessary to account for social support and negative life events while examining the role of psychologic factors in patients with cardiac disease.

order, Parkinson’s disease, Huntington’s chorea, multiple sclerosis, other neurologic diseases, endocrine disorder), (3) severe physical disability (visual, sensory, or motor) that may interfere with psychiatric assessment and cognitive testing, and (4) a previous diagnosis of psychiatric disorder other than affective disorder.

Methods

The study was approved by the Duke University Medical Center Institutional Review Board. Potential patients were screened at the in-patient cardiology units to ensure eligibility by a checklist. The purpose and procedures of the studies were explained, and informed consent was obtained from each patient before entry into the study. As an integral component of the diagnostic evaluation, all subjects recruited for this study at Duke were administered the evaluation protocol developed by the NIMH-supported Duke Center for the Study of Depression in the Elderly. These procedures, the core of which is the Duke Depression Evaluation Schedule for the Elderly (DDESE), were developed to improve the reliability of diagnosis.

On the basis of the previous literature, which indicates that negative life events are increased in depressed patients and that social support is low in depressed patients relative to those without depression, we posited the following hypotheses. Hypothesis 1: There will be more concurrent negative life events in CAD patients with major depression than those without depression. Hypothesis 2: Social support will be less in patients with CAD and major depression than those without depression.

Sample One thousand ninety-three patients with cardiac disease were screened. Two hundred ten did not meet screen criteria. Of the remaining, 656 either refused or were discharged before completing the interview. A total of 196 patients with CAD were assessed at the in-patient cardiology units. The data were complete for 184 patients. The demographic data are shown in Table I.

Subject criteria Inclusion criteria were hospitalized patients with documented CAD (as evidenced by documentation of MI or by catheterization studies) who were >53 years of age. Exclusion criteria were (1) history of alcohol or drug dependence within the past year, (2) medications or other medical illness that can affect cognitive function, cause depression, or cause neuroanatomic changes (eg, seizure dis-

Screening and assessment procedures

Depressive diagnoses and symptoms The Duke Center for the Study of Depressive Disorders in Late Life has used the DDESE to define and validate depressive subtypes, and its reliability has been established.20 The depression sections included the Center for Epidemiologic Studies-Depression and the Diagnostic Interview Schedule. The Center for Epidemiologic Studies-Depression was used as a screen before administration of the entire depression battery. The Diagnostic Interview Schedule Depression Section was used for making the ultimate diagnosis of depression. This section was expanded to allow for differentiation between the following subtypes: (1) major depressive disorder with and without melancholia, and (2) major depressive disorder with and without psychotic features. Patients were classified on the basis of Diagnostic and Statistical Manual of

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Mental Disorders (DSM-IV) criteria for this study. Patients classified as depressed met DSM-IV criteria for major depressive disorder.

Stress The scale inquired about 20 discrete changes in major areas of life (health, family, work, economics), as well as an open-ended item that elicited information about personally significant events not included in the event list. For each event reported, the respondent was asked if the event was positive, neutral, or negative; expected or unexpected; and was very important, somewhat important, or unimportant. The time frame for the life events was the past year time frame, comparable to that in most standardized measures. As noted earlier, our major approach to scaling life events was to sum the number of negative events reported by respondents. We also were able to examine other configurations of events (eg, loss events and negative, unexpected, and very important events). Because we were recruiting a medically ill sample, for most purposes, illness events were excluded to preclude artificially inflated correlations between life events and other variables of interest. This tool has been shown to be predictive of both depression onset21 and course and outcome22 in our previous research. Moreover, its relationship with age and applicability to older adults has received careful empirical scrutiny.23-25 The scale is shorter and easier to use than other more extensive questionnaires.

Social support The Duke Social Support Index (DSSI) was included in the DDESE and was administered to all study participants. The DSSI was developed in the Duke Epidemiologic Catchment Area project and was included in our Clinical Research Center research.21,22,26-30 The DSSI assessed 4 dimensions of social support: social network size, levels of interaction with network members, receipt of instrumental assistance from network members, and subjective social support ratings.

Data analysis With a dichotomous outcome variable, depression (yes/no), and several possible covariates and independent variables of interest, logistic regression was used. Because several hypothesized social support and life events were assumed to relate to depression controlling for the covariates, a “chunk test” for these several variables was used.31 Chunk tests are used to control the overall type I error rate when any of several variables within a domain (here, social support and life events) are hypothesized to relate to the outcome of interest. The total effect of the chunk or group of variables is then tested simultaneously to derive an overall effect. Only if the chunk was significant would follow-up tests of significance be performed. If the chunk was signifi-

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Table II. Final forward stepwise logistic regression of model of negative life events and social support Variable Nonwhite race Education (y) Women Married Age (y) Negative life events (n) Subjective social support scale

Odds ratio (95% CI) 2.64 (0.71, 10.05) 0.98 (0.81, 1.14) 2.32 (0.74, 7.25) 1.61 (0.15, 16.86) 0.98 (0.92, 1.04) 2.02 (1.35, 3.02) 0.79 (0.65, 0.96)

P value 0.15 0.66 0.15 0.69 0.47 0.0007 0.016

cant, a final model was derived to assess which particular variables of the set were significant by use of forward stepwise logistic regression.

Results Results from the first 196 cases are presented. Because of missing values, only 184 subjects had complete information on the dependent variable, life events, social support, and demographic variables. The 12 subjects with missing variables did not differ from any of the 184 with complete information on any of the demographic variables (age, sex, race, education, or marital status) for all tests. In addition, they reported no difference on any of the stressful events or support variables, with the exception of negative events. The subjects with at least 1 missing data point reported fewer negative events (P = .04). Univariate statistics for this group for the independent variables and covariates of interest are shown in Table I for the total sample and separately for the depressed and nondepressed subsamples. Hypotheses 1 and 2 were first tested with univariate statistics. As can be seen, depressed subjects were more likely to be nonwhite, have a higher number of negative events in the previous year, have lower subjective social support, and have lower nonfamily interactions. To assess if these effects held in controlled analyses, a series of logistic regressions was performed. First, to control the family-wise or overall type I error rate, a full model with all 5 stressors and support variables and the 5 covariates was estimated. The effect of the 5 support and stressor variables was tested as a chunk conditional on the 5 demographic variables (age, sex, race, marital status, and education). Because this 5 degrees of frequency test was significant (P < .001), follow-up stepwise forward logistic regression was performed to assess which particular social support and stressor measures were significant and to arrive at a final model. The result of this is shown in Table II.

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As can be seen, one of the events indicators (number of negative life events) and one of the measures of social support (subjective social support) was related to the presence of depression controlling for demographics. Each additional negative life event was related to an estimated doubling of the odds of depression, whereas the presence of subjective social support was protective for depression.

Discussion The finding that negative life events and subjective social support is related to major depression in CAD suggests that even in the context of medical illness, social factors are still important in the development of depressive disorder. The findings are in accord with the existing literature in patients with depressive disorder. Although negative life events have been linked with major depression in community-dwelling adults, this is the first study that has examined the impact on the medically ill. The finding has implications for research examining the impact of depression on health outcomes in CAD patients. The data suggest that in these studies the role of social support has to be considered before assigning importance to depression (as a diagnosis) as an independent factor. The study suggests that although cardiovascular disease may increase the susceptibility to depression, life stressors may moderate the relationship. Concurrent negative life events often add to the stress of physical illness and thus contribute to the initiation, persistence, or worsening of depressive illness.32,33 For example, a family member becoming sick or a decline in financial status may lead to a greater chance of developing depression, especially in the absence of social support and other health coping strategies. The role of negative life events has not been well studied in the context of medical illness. This study clearly indicates the further need to examine this relationship. Also of interest is the role of race in the context of depression in patients with cardiac disease. The results suggest that depression is highest among nonwhites, and that is not accounted for by life stress or social support factors. This raises the need to evaluate this issue further. The greater rate of depression in women is consistent with previous literature.34,35 One of the limitations of this study is the cross-sectional nature of the data. Cross-sectional data limit causal inference. Depression itself may affect social support and life events and thus the directionality of the relationship cannot be proved in the context of this

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study. However, on the basis of longitudinal studies in community populations, one can infer that subjective social support and negative life events are related to the development and progression of depression. Inasmuch as most studies that assess the impact of social factors (such as social support) on morbidity and mortality assess these factors only at baseline, it is possible that a diagnosis of depression may have developed in the intervening period and that depression (as a diagnosis) may indeed be the predominant risk factor. Thus longitudinal studies are needed of both psychosocial factors and depression on assessing morbidity and mortality in CAD patients. Other psychosocial factors such as family functioning27 and pattern of interaction with extended family should also be assessed. The issue of whether the items measuring subjective social support too closely resemble those used to measure depression itself has been raised. We have argued that subjective social support is, in fact, a separate and distinct entity that measures the quality of support received and is perhaps the most important dimension of social support as far as health outcomes are concerned.12 This belief is based on longitudinal studies of depressed patients, which have demonstrated a significant and independent prospective effect for subjective support on depression outcome after controlling for other factors, including baseline depression.22 The relationship between social factors and symptoms of depression and whether the relationship is true only for diagnosis of major depression is of interest because of findings that suggest depressive symptoms are themselves predictors of morbidity and mortality in CAD patients.11 We plan to address this in a larger cohort of patients. Additional studies are required to evaluate the clinical significance of assessing life events and social support. Many of the questionnaires are easily adaptable for self-assessment by the patient. These questionnaires would need to be validated. A practical level clinician should be aware that patients who complain of social isolation or indicate a recent (within the last year) major life event (ie, divorce or bereavement) may be at increased risk for depression and possibly at greater risk for increased morbidity from the medical illness. Ongoing clinical trials may provide clues to treatment strategies that may be of benefit. Overall, the study emphasizes the importance of social support and life stressors in depression in patients with cardiac disease. It clearly indicates the

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need for longitudinal studies of both psychosocial factors and depression on assessing morbidity and mortality and suggests that caution should be exercised in extrapolating single time frame assessment of depression and social factors to evaluate morbidity and mortality in patients with CAD. Thus in studying the impact of changes in health and functional status on mood states, one must account for negative life events and other psychosocial factors.

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