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Incongruence between perceived long-term risk and actual risk of stroke in rural African Americans.


Stroke has increased among young adults. In addition, the accuracy by which African Americans perceive their risk of stroke is unclear. The purpose of the study was to examine the accuracy of perceived stroke risk of African Americans aged 19-54 years. A descriptive-correlational design was used. Accuracy of perceived stroke risk was determined by comparing perceived risk with actual risk. Participants (N = 66) had a mean age of 43.3 (5D = 9.4) years and were mostly female, high school graduates, and unemployed. Most (66%) perceived themselves as having no/low risk of future stroke. However, actual risk factors averaged 2.98 + 1.63 of 8, placing 59% of the sample in the moderate-high category of actual stroke risk. Comparisons of perceived and actual risk showed that 44% underestimated their risk, 47% were accurate, and 9% overestimated their risk. Strategies to address risk misperceptions should be explored to improve accuracy of perceived stroke risk and culturally relevant interventions to reduce stroke among African Americans.

Keywords: African American, health belief model, primary prevention, risk assessment, risk perception, stroke


Stroke rates among young to middle-aged adults are increasing worldwide. The incidence of stroke in people aged 20-64 years has increased by 25% (Krishnamurthi et al., 2013). More than 30% of first strokes now occur in people younger than 65 years (Krishnamurthi et al., 2013). This is a concern, especially for African Americans or Blacks, who tend to have stroke at an earlier age than other groups and experience more severe stroke-related outcomes. To address this public health issue, this study was undertaken to determine how young to middle-aged African Americans perceive their risk of future stroke.


African Americans aged 20-14 years are twice as likely to experience a stroke as Caucasians of the same age (National Stroke Association [NSA], 2009), and African Americans aged 35-64 years have three-to-four times the risk of dying from stroke than Caucasians have (Howard et al., 2011). Stroke can be more devastating for younger adults than older adults because they may live longer with disabilities and with the threat of future cardiovascular events and have greater healthcare costs as well as a loss of productivity (Goldstein et al., 2011; Roger et al., 2012). Indirect costs for stroke in adults aged <65 years are estimated to be six times higher than for adults aged [greater than or equal to] 65 years (Roger et al., 2012).

Hypertension, diabetes, and obesity are factors contributing to stroke in younger adults (George, Tong, Kuklina, & Labarthe, 2011; Kissela et al., 2012; Krishnamurthi et al., 2013), and these diseases are more common among African Americans with stroke than other groups (McGruder, Malarcher, Antoine, Greenlund, & Croft, 2004; Pathak & Sloan, 2009; Waddy et al., 2009). Therefore, primary prevention is of utmost importance. Up to 80% of strokes could be prevented if people recognized and eliminated or controlled their risks (NSA, 2013). However, many young adults are unaware of how their lifestyle choices affect their risk of stroke (American Heart Association, 2011). Because stroke is more common among older adults, younger adults may not perceive the threat of stroke or hold accurate perceptions of their risk. As a result, they may not take actions to reduce their risk.

Theoretical Framework

The health belief model served as the conceptual basis for this study. This model explains why people do or do not engage in a health action in response to a specific disease threat (Rosenstock, 1974). Perceived susceptibility/risk, a major concept of the health belief model, is defined as an individual's belief about his or her chances of becoming ill (Hay et al., 2007). According to the model, individuals who perceive themselves as being susceptible or at risk of disease (e.g., stroke), actually understanding their risk, are more likely to engage in activities (e.g., healthy diet, exercise) to reduce their risk (Rosenstock, 1974). Perceived risk is often based on personal factors that contribute to disease. Several modifiable and nonmodifiable factors increase a person's chances of having a stroke. However, individuals may not translate knowledge of personal risk factors into accurate estimations of stroke risk. Accuracy of perceived stroke risk, however, has not been widely studied.


Empirical evidence indicates that at-risk individuals tend to underestimate their risk of stroke (Al Shafaee, Ganguly, & Al Asmi, 2006; Anderson et al., 2013; Dearborn & McCullough, 2009; Powers, Oddone, Grubber, Olsen, & Bosworth, 2008; Yang et al., 2013). For example, Dearborn and McCullough (2009) found that, among Caucasian American perimenopausal women (N = 215) with at least one risk factor for stroke, risk perception was low, and women at higher risk perceived their risk to be similar to that of their peers. Powers et al. (2008), investigating hypertensive American male veterans (N = 296; 40% Black), found that men with higher actual stroke risk were more likely to underestimate their risk than men with lower actual risk. In a sample of 941 individuals in China, perception of risk for stroke increased as the number of self-reported risk factors for stroke increased, but only 41% of those with three or more risk factors perceived themselves to be at risk (Yang et al., 2013). In a study of 400 Southwestern Asian patients with known risk factors for stroke, most (62%) did not believe they were at increased risk for stroke (Al Shafaee et al., 2006). Finally, in a recent telephone survey (N= 1959) of American adults with a mean age of 66.3 ([+ or -] 14.7) years, the researchers found that Black respondents had lower perceived risks of stroke than Whites (Anderson et al., 2013). No studies, however, have examined how younger African Americans perceive their risk of future stroke. Therefore, this study examined the accuracy of perceived stroke risk among African Americans aged 19-54 years by comparing perceived risk of future stroke with actual risk of stroke.


Design and Sample

A descriptive-correlational design was used with a nonrandom sample of participants recruited from a mobile health clinic that traveled to four rural counties over 4 months. The mobile health clinic offers free medical screenings, diagnostic testing, direct patient care, health education, and medications. Volunteers in the mobile health clinic set up at a public facility (e.g., church, school gymnasium) and provide services to 30-60 patients each month; most are African American/Black, middle-aged to older adults, and female.

Eligible participants for this study were patients of the mobile health clinic who self-identified as African American or Black and were 19-54 years old, current residents of rural counties, and able to read and write English or understand survey questions read to them. Because some questions related to exercise, participants also could not have any physical impairment that prohibited them from exercising. Two hundred eight participants were screened for inclusion; 135 (65%) did not meet age requirements, and one did not self-identify as African American/Black. Six (3%) individuals declined to participate for the following reasons: not interested (2), lack of time (3), and not feeling well (1). Sixty-six participants were enrolled.


Accuracy of perceived stroke risk was assessed by comparing two measures, a subjective measure of perceived risk of future stroke (Figure 1, available as Supplemental Digital Content 1 at and an individual actual stroke risk assessment form (Figure 2, available as Supplemental Digital Content 2 at To determine perceived risk of future stroke, participants were asked to select the risk level (no risk, little risk, moderate risk, or high risk) that represented what they believed was their risk or chance of having a stroke in the next 10-20 years. Similar measures of risk perception for stroke have been used in prior research with community samples (Dearborn & McCullough, 2009; Kraywinkel, Heidrich, Heuschmann, Wagner, & Berger, 2007). To explore what participants based their personal risk estimates on, an open-ended question was used. Participants were asked, based on the category they selected for their perceived risk of future stroke, what they believed was putting them at no, low, moderate, or high risk of stroke.

Actual stroke risk factors, defined as clinically accepted risk factors for stroke, were collected using a researcher-developed stroke risk assessment form adapted from the American Stroke Association's stroke risk assessment form (American Stroke Association, 2003). This form included health, social, and family histories associated with stroke risk and biophysiological health measures. The stroke risk factors were confirmed with those risk factors identified by the American Stroke Association (2012) and NSA (2013). The form was also reviewed for content validity by an expert in acute care of patients with stroke and an expert in measurement.

To gain an overview of the occurrence of risk factors in this cohort, we included all potential modifiable and nonmodifiable risk factors for stroke recognized by the American Stroke Association (2012), except for African American/Black race. The total possible number of risk factors for all characteristics and conditions was 0-13 and included family history of stroke (parent, grandparent, or sibling), prior stroke/transient ischemic attack, prior myocardial infarction, hypertension (reported history of hypertension or clinic systolic blood pressure [greater than or equal to] 140 mm Hg or diastolic blood pressure [greater than or equal to] 90 mm Hg), current cigarette smoking, diabetes (reported history of diabetes or clinic blood glucose reading > 200 mg/dl), atrial fibrillation, sickle cell disease, obesity (body mass index [BMI] [greater than or equal to] 30), heart disease or peripheral artery disease, hypercholesterolemia (reported histoiy of hypercholesterolemia), excessive alcohol consumption (greater than two drinks a day for men and greater than one drink a day for women), and inadequate exercise (Godin Leisure Time Exercise Questionnaire score < 20; Godin & Shephard, 1985).

To obtain a risk factor score, we used an established risk scoring system as a guide. Only those risk factors recognized in the NSA's (2011) Stroke Risk Scorecard were used. This scorecard has been used in clinical and community-based settings to help individuals become more familiar with personal risk of stroke (NSA, 2011). In this study, the scorecard was used to develop an actual stroke risk score based on clinically accepted risk factors. The goal was to identify risk factors present among young African American adults that could be improved through lifestyle behavior change. Participants received a point for each of the following personal risk factors: reported history of hypertension, high cholesterol, diabetes, atrial fibrillation, cigarette smoking, BMI [greater than or equal to] 30 (height and weight measured), inadequate exercise (Godin Leisure Time Exercise Questionnaire score < 20; Godin & Shephard, 1985), and family history of stroke (i.e., parent, sibling, or grandparent). Actual stroke risk scores were obtained by summing these factors, with possible scores ranging from 0 to 8. The actual stroke risk scores were then categorized as (0) no risk or having none of the eight risk factors; (1) low risk, with one-to-two risk factors; and (2) moderate-to-high risk, with three or more risk factors. The single-item measure of perceived stroke risk was compared with the actual stroke risk score to obtain the accuracy of perceived stroke risk. As shown in Table 1, participants were then placed into one of three risk accuracy categories: accurate, underestimated, and overestimated personal risk.


The study received approval from a university institutional review board, and written informed consent was obtained from all participants before data collection. Data were collected by three master's-prepared nurses and one nutritionist through in-person administration of questionnaires and clinic chart review. Data collectors received a study procedure protocol and were trained on the importance of collecting data consistently and without bias. When individuals checked into the mobile health clinic, they received a recruitment flyer and/or were asked by a researcher about their interest in participating in a study. For those interested, a researcher explained the study, determined study eligibility, and obtained informed consent. Participants were given the option to complete questionnaires on their own or have a researcher read the questionnaires to them and document their responses. A stroke risk assessment form was completed by abstracting data (e.g., blood pressure and blood glucose readings) from each participant's mobile health clinic chart and by questioning participants about their health, social, and family histories. After completing the study, participants received $5.00 cash and a stroke prevention packet that included stroke education brochures and the American Heart Association's Heart Healthy Cookbook.

Data Analysis

Descriptive statistics (i.e., frequencies, percentages, mean, and standard deviations) were used to characterize the sample, risk factors for stroke, and accuracy of perceived stroke risk. Associations between the accuracy of perceived stroke risk and sample characteristics and risk factors were examined using independent-sample t tests and chi-square analysis as appropriate. For this analysis, accuracy of perceived stroke risk was dichotomized--accurate and overestimates risk or underestimates risk. Content coding was used to summarize the open-ended responses to the question about what contributes to your perceived risk of stroke with an intrarater reliability of .97, conducted by the first author.


Participants were primarily female (71%) and middle aged (M = 43, SD = 9.4 years) with at least a high school education (89%). Most were not working (62%), and 55% had health insurance, either Medicaid or Blue Cross Blue Shield. Table 2 provides a summary of the demographic characteristics of the sample. The characteristics of the sample were not associated with the accuracy by which participants perceived their future risk of stroke. Most participants perceived their risk of future stroke as low (n = 28, 42%) or no (n = 16, 24%) risk, whereas 15 (23%) felt they were at moderate risk, and seven (11%) perceived a high risk of future stroke. Although the sample was fairly young, they had a number of risk factors, as shown in Table 3. The number of risk factors ranged from 0 to 7 of a possible 13 with a mean of 3.33 (SD = 1.72). The actual risk factor scores, which included only those factors in the NSA Stroke Risk Scorecard (marked with an a in Table 3), ranged from 0 to 6 of 8, with a slightly lower mean of 2.98 (SD = 1.63); 39 (59%) participants were in the moderate-to-high actual risk category. Risk factors common in the sample were obesity (59%), history of hypertension (53%), inadequate exercise (53%), and a family history of stroke (50%). About one third of the sample were cigarette smokers.

When participants' perceived risk of stroke were compared with their actual risk factor score, 31 (47%) participants were found to have an accurate perception of their stroke risk, whereas 29 (44%) underestimated their risk, and six (9%) overestimated their risk. As shown in Table 4, 22 (33%) participants perceived themselves to be at moderate or high risk of future stroke. However, 39 (59%) participants had three or more actual risk factors for stroke, which put them in the moderate-to-high risk category.

The most common responses to the open-ended question asking participants what they felt contributed to their risk/chances of having a stroke were having a family history of stroke (n = 11) and a history of hypertension (n = 11). However, 67% of the participants with a family history of stroke (n = 33) and 69% with a history of hypertension (n = 35) did not identify these factors as contributors to their risk of future stroke. In addition, 80% of cigarette smokers (n = 25), 93% of participants with diabetes (n = 13), and 88% of overweight/obese participants (n = 49) did not identify these as personal risk factors.


We found a high burden of stroke risk among this sample of young to middle-aged rural African Americans. The percentage of participants with modifiable stroke risk factors was found higher than other African American cohorts with risk factors of hypertension (12%-20%), diabetes (12%--14%), obesity (49%), and cigarette smoking (17%; Frank & Grubbs, 2008; Sallar, Williams, Omishakin, & Lloyd, 2010). The mean number of risk factors (3.33 of a possible 13) was similar to the mean (2.98 of 8) when only the NS A Stroke Risk Scorecard factors were used. Because stroke is more common among African Americans and African Americans tend to have more stroke risk factors (Centers for Disease Control and Prevention, 2005), it is important for clinicians to assess all documented factors and educate those at risk. In addition to traditional risk factors, other less well-documented factors, more commonly seen among younger adults, such as alcohol consumption and sickle cell disease, which were assessed in this study, and migraine headaches, illicit drug use, and prescribed contraceptives (Goldstein et al., 2011) should be assessed.

Despite the number of risk factors found in this sample, in general, participants did not perceive a high risk of future stroke. This finding is consistent with other studies examining perceived risk of stroke (Dearborn & McCullough, 2009) and cardiovascular disease (Homko et al., 2008) among at-risk populations. Of the 39 participants who had three or more risk factors for stroke, only 19 (49%) perceived themselves at moderate-to-high risk of stroke. Other researchers have also found that people with three or more risk factors for stroke did not perceive themselves to be at risk (Harwell et al., 2005; Yang et al., 2013). A lack of understanding of the causes of stroke, the way comorbidities contribute to higher risk, and the benefits of risk reduction behaviors could help to explain the inaccuracies among those at risk. Participants' responses to open-ended questions about factors contributing to their risk of stroke indicated poor understanding of personal risk factors. For example, many did not list smoking cigarettes, which the Centers for Disease Control and Prevention (2012) have identified as the single most preventable cause of disease. Furthermore, these individuals may not understand that even relatively small reductions in weight loss and increases in physical activity could reduce risk. Another explanation for the low perceived risk of stroke is that the individuals may not have wanted to accept or claim their risk out of fear that stroke could then occur.

Relevance to Clinical Practice

Stroke awareness campaigns and individual risk assessment counseling are needed to help younger African American adults identify and better understand their risk. Researchers in Germany found that mass media stroke education campaigns improved participants' risk perceptions for stroke (Kraywinkel et al., 2007; Marx, Nedelmann, Haertle, Dieterich, & Eicke, 2008). Personalized risk communication has also led to improvements in accuracy of perceived stroke risk and better decision making about stroke risk reduction strategies (Powers et al., 2011; Sheridan et al., 2010). However, like many primary prevention studies in the area of cardiovascular disease, these studies focused on older adults. Further development and testing of stroke risk reduction counseling, including assessment and educational tools that are relevant to younger African Americans, are needed to help determine their usefulness in predicting future stroke and promoting healthier lifestyles.

Almost half of this sample underestimated their risk of future stroke. This is a serious concern because individuals who underestimate their risk may not perceive stroke as a serious threat and may therefore be less likely to engage in preventive health behaviors. It is unclear, however, whether perceived risk of stroke, accurate or not, actually promotes positive behavior changes because research in this area for stroke is limited. In the literature on cardiovascular disease, findings on the relationship between perceived risk of cardiovascular disease and health-related behavior change were inconsistent, and researchers suggested that personal risk factor awareness was necessary but not sufficient to promote behavior change (Imes & Lewis, 2014). Clearly, studies are needed to explore how improving perceived stroke risk can be incorporated with other strategies to increase risk reduction behaviors.

Limitations and Strengths

There were limitations to this study. The small sample size, nonrandom sampling, and a sample restricted to rural African American mobile health clinic participants limit generalizability. However, although the sample may not be representative of all younger African Americans, it does represent a socioeconomically vulnerable group, not often represented in studies. The authors recognize that perception of stroke risk likely differs from someone aged 19 years compared with someone aged 54 years; however, it is important to think about prevention early, and the purpose of the study was to explore the concept of accuracy of perceived stroke risk. There is also a potential for bias with self-report information on risk factors. However, reports of traditional risk factors were confirmed by the results of physiological measures (e.g., calculated BMI, blood pressure, and blood glucose readings).


In a fairly young cohort of rural African American adults, we found a mean number of 3 of 8 risk factors for stroke, and half the sample had a mismatch between their perceived risk of future stroke and actual risk of stroke. Addressing these problems is crucial to reduce the growing rates of early-onset stroke and its clinical, economic, and social burdens. Expanded efforts by nurses in clinical and community-based settings are needed to target young to middle-aged adults, at-risk African Americans or Blacks, to improve their awareness of stroke and preventative actions. Education for these adults should start with an evaluation of perceived personal risk of stroke and an assessment of potential risk factors to identify and correct inaccurate risk perceptions. Nurses can then address ways to reduce stroke risk such as achieving and maintaining blood pressure and blood glucose goals, losing weight, smoking cessation, and increasing exercise because hypertension, diabetes, and smoking have been identified as the most important contributors to stroke in African Americans (Boan et al., 2014). In addition, assessment and education on drinking alcohol in moderation, if at all; avoiding illicit drugs; and seeking professional guidance for use of hormonal contraceptives is important, especially if one or more other risk factors are already present.


Appreciation to members of the research team who assisted with project development and/or data collection: Anne Alexandrov, PhD, RN; Karen Albright, DO, MPH; Kenya D. Kirkendoll, MSN, MPH, RN; Kisha C. Coleman, DNP, RN; and Dana DaCosta, RD. Additional thanks to Dr. Sandra Ford and Mr. Henry Ford, Directors of "A Promise to Help" healthcare initiative.


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Questions or comments about this article may be directed to Dawn M. Aycock, PhD RN ANP-BC, at She is an Assistant Professor, Byrdine F. Lewis School of Nursing and Health Professions, Georgia State University, Atlanta, GA.

Patricia C. Clark, PhD RN FAHA FAAN, is Professor, Byrdine F. Lewis School of Nursing and Health Professions, Georgia State University, Atlanta, GA.

The authors declare no conflicts of interest.

Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal's Web site (

DOI: 10.1097/JNN.0000000000000180
TABLE 1. Accuracy of Perceived Stroke
Risk Categories

Accuracy         Perceived Risk             Actual Risk

Accurate              Low                       1-2
                Moderate to high   [greater than or equal to] 3
Underestimate          No          [greater than or equal to] 1
                      Low          [greater than or equal to] 3
Overestimate          Low                        0
                Moderate to high     [less than or equal to] 2

TABLE 2. Characteristics of the Sample
(N = 66)

Characteristic                             n (%)

  Female                                  47 (71)
  Male                                    19 (29)
Age, years (M = 43, SD = 9.4, Md = 47)
  19-29                                    5 (8)
  30-45                                   22 (33)
  45-54                                   39 (59)
Years of school
  <12                                     7 (11)
  12                                      38 (57)
  >12                                     21 (32)
Work status
  Full/part time                          25 (38)
  Unemployed                              26 (39)
  Retired/disability/homemaker            15 (23)
Health insurance
  Yes                                     36 (55)
  No                                      30 (45)

TABLE 3. Frequency of Stroke Risk
Factors (N = 66)

Risk Factor                            n (%)

Obesity (BMI [greater than or         39 (59)
  equal to] 30) (a)
Inadequate exercise (a)               35 (53)
  History only (a)                    35 (53)
  History or no history               46 (70)
    with SBP [greater than or
    equal to] 140/DBP
    [greater than or equal to] 90
Family history of stroke (a)          33 (50)
Cigarette smoker (a)                  25 (38)
High cholesterol (a)                  18 (27)
  History only (a)                    13 (20)
Heart disease/PVD                      5 (8)
Atrial fibrillation (a)                3 (5)
Heart attack                           2 (3)
TIA/stroke                             2 (3)
Alcohol abuse                          2 (3)
Sickle cell disease                    1 (2)

Note. BMI = body mass index; SBP = systolic blood pressure;
DBP = diastolic blood pressure; PVD = peripheral vascular
disease; TIA = transient ischemic attack.

(a) Risk factors included in the accuracy of perceived x
equal to] 30) (a) analysis.

TABLE 4. Descriptive Statistics for Accuracy of Perceived Stroke
Risk (N = 66)

                                  Actual Risk Based on Number of
                                        Risk Factors, n (%)

                 Total                                   [greater than
Perceived       Perceived                  Low, 1-2      or equal to]
Risk              Risk,      No Risk         Risk           3 Risk
Levels              N        Factors        Factors         Factors

No risk            16       --           9 (56) (a)      7 (44) (a)
Low risk           28       3 (11) (c)   12 (43) (b)     13 (46) (a)
Moderate risk      15       1 (7) (c)    2 (13) (c)      12 (80) (b)
High risk           7       --           --              7 (100) (b)
Total actual                4            23              39
  risk, N

(a) Participants who underestimated their risk. (b) Participants who
had an accurate perception of their risk. (c) Participants who
overestimated their risk.
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Author:Aycock, Dawn M.; Clark, Patricia C.
Publication:Journal of Neuroscience Nursing
Article Type:Report
Date:Feb 1, 2016
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