Perception of risk and knowledge of risk factors in women at high risk for stroke

Abstract

Background and purpose: Women face a higher mortality after stroke and have different risk factors than men. Despite educational campaigns, women continue to underestimate their own risk for stroke. We present a theoretical model to understand risk perception in high-risk women.

Methods: Eight hundred five women, ages 50 to 70 years, were selected from the University of Connecticut Cardiology Center with at least one risk factor for stroke. A 5-part questionnaire addressed stroke knowledge, risk perception, risk factors, access to health care, and demographics. Two hundred fifteen women responded by mail (28% response rate) and deidentified data were entered in SPSS. Descriptive, bivariate, and multivariate techniques assessed the proposed model.

Results: The cohort was predominantly white (91.5%), higher income (33.1% of the population earned >$75,000), and well-educated (28.6% attended graduate or professional school). Only 2 of the 37 (5.4%) women with atrial fibrillation and 11 of the 71 women with heart disease (15.5%) identified their health condition as a risk factor for stroke. Predictors of risk perception included: other women's risk (B=0.336, P<0.001), worrying about stroke (B=0.734, P<0.001), having hypertension (B=0.686, P=0.037), and having diabetes (B=0.893, P=0.004). Only 63.9% of women with atrial fibrillation (n=23) reported taking warfarin.

Conclusions: Women were often unable to identify their health condition as a risk factor for stroke. In addition, many women were not undertaking primary prevention behaviors. Risk perception was low, and high-risk women perceived their risk of stroke to be the same as their peers. Educational strategies must advocate for and target high-risk women.

Figure 1. Research model

We hypothesized that a woman’s risk factors for stroke and risk perception, as well as her access to medical care, would mediate the success of primary prevention measures. We also predicted that health literacy measures, such as education and knowledge of stroke warning signs/risk factors would predict perceived risk.

Figure 2. A) Warning signs of stroke and B) Identification of personal risk factors

A) Shown is the percentage of women who identified a particular warning sign for stroke. Subjects were asked to list up to five warning signs. Only the above responses were coded. B) RF=risk factor; HBP=high blood pressure; Chol=high cholesterol; Tob=lifetime tobacco use; DM=Diabetes Mellitus; HD/MI=heart disease or myocardial infarction; CS=carotid stenosis; A Fib =atrial fibrillation; Total= # women responding The dark grey bar identifies the number of women who had the particular risk factor and identified it as a risk factor for stroke. The light grey bar is the number of women responding to the question. The difference between the two bars is the number of women with a particular risk factor who did not identify it as a risk factor for stroke.

Figure 2. A) Warning signs of stroke and B) Identification of personal risk factors

A) Shown is the percentage of women who identified a particular warning sign for stroke. Subjects were asked to list up to five warning signs. Only the above responses were coded. B) RF=risk factor; HBP=high blood pressure; Chol=high cholesterol; Tob=lifetime tobacco use; DM=Diabetes Mellitus; HD/MI=heart disease or myocardial infarction; CS=carotid stenosis; A Fib =atrial fibrillation; Total= # women responding The dark grey bar identifies the number of women who had the particular risk factor and identified it as a risk factor for stroke. The light grey bar is the number of women responding to the question. The difference between the two bars is the number of women with a particular risk factor who did not identify it as a risk factor for stroke.