Psychosocial factors predict coronary heart disease, but what predicts psychosocial risk in women.

Objectives: Psychosocial factors, including depression, anger, and social isolation, have been associated with increased morbidity and mortality from coronary heart disease (CHD), but predictors of psychosocial burden among women with CHD are poorly defined. The purpose of this study was to determine whether readily measured demographic and risk factors could identify women with psychosocial risk factors that are more difficult to assess in a clinical setting.

Methods: Baseline data on 304 women (mean age 62 years, 52% minority) hospitalized with CHD at 3 academic medical centers participating in a clinical study of adherence to prevention guidelines were evaluated. Standardized questionnaires were used to measure depression (4-item self-report tool from the Primary Care Evaluation of Mental Disorders questionnaire) and anger (Spielberger Trait Anger Scale). One self-report question was used to assess social isolation.

Results: Thirty-seven percent of women with CHD reported depression, 50% reported anger, and 41% reported social isolation. In a logistical model controlling for confounders, independent predictors of depression were having dependents (odds ratio [OR] = 2.27, p = .006), age (< or = 65 years) (OR = 1.91, p = .02), and exercise (< 3 days/week) (OR = 3.92, p < .001). Anger was associated with having dependents (OR = 3.16, p < .001), age (< or = 65 years) (OR = 1.95, p = .02), and smoking (OR = 2.05, p = .04). Subjects who had dependents (OR = 2.24, p = .005), were unemployed (OR = 1.93, p = .03), and who did not get enough exercise (< 3 days/week) (OR = 2.07, p = .03) reported higher isolation in adjusted models. Differences in prevalence of psychosocial factors by ethnicity were not statistically significant. However, there was a trend toward increased prevalence of psychosocial risk factors among white women, possibly reflecting the need for more culturally sensitive screening tools.

Conclusion: These data may be helpful in identifying women who are at risk of increased CHD morbidity and mortality because of psychosocial burden.