Racial disparities in stroke awareness: African Americans and Caucasians.
Abstract: onsiderable evidence supports the existence of racial disparities in incidence, mortality, and morbidity related to stroke. Awareness of risk factors could substantially lower the probability of stroke incidence. Awareness of stroke warning signs and treatment options could significantly alter the outcome of a stroke if patients immediately seek emergency help. This article examines the disparities in awareness of stroke risk factors, stroke signs, and action to be taken when stroke occurs. Survey results from 422 Caucasian Americans and 368 African Americans in West Virginia were analyzed. Significant disparities in recognition of cholesterol, smoking, prior stroke, and race as stroke risk factors were observed. The study also found a significant and substantial difference in awareness of stroke signs. There was also a significant difference in the way African Americans and Caucasians would respond to a stroke. The study found no evidence of disparities in recognition of stroke risk factors, such as hypertension, diabetes, heart disease, obesity, alcoholism, and family history.
Article Type: Survey
Subject: African Americans (Surveys)
Health education (Surveys)
Stroke (Disease) (Surveys)
Stroke (Disease) (Risk factors)
Authors: Alkadry, Mohamad G.
Bhandari, Ruchi
Wilson, Christina S.
Blessett, Brandi
Pub Date: 03/22/2011
Publication: Name: Journal of Health and Human Services Administration Publisher: Southern Public Administration Education Foundation, Inc. Audience: Academic Format: Magazine/Journal Subject: Government; Health Copyright: COPYRIGHT 2011 Southern Public Administration Education Foundation, Inc. ISSN: 1079-3739
Issue: Date: Spring, 2011 Source Volume: 33 Source Issue: 4
Geographic: Geographic Scope: United States Geographic Code: 1USA United States
Accession Number: 250033486
Full Text: A stroke occurs when the blood supply to brain cells is suddenly interrupted, causing some brain cells to immediately die, while damaging others in the region of injury. Permanent injury and disability may be curtailed with immediate intervention that restores blood flow to the compromised brain cells (American Heart Association, 2004). Stroke is the leading cause of disability and the third leading cause of death (Centers for Disease Control and Prevention, 2000). Each year, 700,000 Americans are predicted to experience a stroke, of which over 150,000 are fatal (American Heart Association, 2003). Consequently, the estimated cost of stroke and disability has reached approximately $62.7 billion nationally (DHHS, 2007).

Research consistently shows that stroke mortality and morbidity are more severe among African Americans than any other racial or ethnic group (Gillum, 1999; American Heart Association, 2004). For example, African Americans had the highest incidence of high blood pressure, which is associated with the largest death rates related to coronary heart disease (CHD) and stroke (DHHS, 2007). Disparities in impact and intensity of stroke are well documented, and so are racial disparities in stroke risk factors. Effective stroke prevention encompasses awareness of stroke risk-factors, stroke warning signs, and appropriate actions to be taken in case of a stroke (Alkadry, Wilson & Nicholas, 2005; Becker, Fruin, Gooding, Tirschwell, Love & Mankowski, 2001). However, the contribution of disparities in knowledge about stroke risk factors and warning signs to the disparity in stroke incidence remains largely uninvestigated.

This study compares stroke awareness of racial minority residents to their white counterparts in West Virginia. First, we will briefly review the literature regarding racial disparities involving strokes. Next, we review and present the persistent differences in cardiovascular risk factors, stroke incidence and type, and survival following stroke that exist between African Americans and whites. Then, we test some stroke awareness hypotheses using data from 456 Caucasian and 400 African American residents of West Virginia.

DISPARITIES IN STROKE INCIDENCE AND MORTALITY

Stroke is one of the diseases that African Americans experience at higher rates than any other racial or ethnic group (Feldman & Fulwood, 1999; Howard & Howard, 2001). Despite substantial improvement in stroke incidence and survival since the 1970s, African Americans continue to have a higher rate of stroke incidence, 30% higher hospitalizations from stroke than Caucasians (Centers for Disease Control, 2004), and a higher rate of stroke mortality than any other racial group in the nation (Gaines, 1997; Gillum, 1999; Howard & Howard, 2001). The national death rate from stroke among African Americans is 166 per 100,000, which is much higher than 117 per 100,000 for Caucasians (Casper, Barnett, Williams, Halverson, Braham, & Greenlund, 2003). There are also significant racial disparities in the age distribution of stroke deaths. African Americans' critical age for stroke is closer to 35 while that of Caucasians is 45 (Rimmer, Braunschweig, Silverman, Riley, Creviston, & Nicola 2000; Jacobs, Boden-Albala, Lin, & Sacco, 2002; Morgenstern, Spears, Goff, Grotta, & Nichaman, 1997). While 25% of stroke deaths occur among Caucasians younger than 65, the rate is almost doubled (49%) among African Americans in the same age group (Casper et al., 2003).

Stroke among African Americans is considered more lethal (Gillum, 1999) because of a higher percentage of hemorrhagic strokes (Ayala, 2002) and cerebral infarction (Bian, Oddone, & Samsa, 2003) compared to Caucasians. Shen, Washington, and Aponte-Soto (2004) corroborated these findings in their study that demonstrated that cerebral artery disease was more prevalent among African-American and Hispanic populations than among Caucasians. Bian et al. (2003) found racial differences in stroke incidence and mortality among the elderly.

DISPARITIES IN STROKE RISK FACTORS

Stroke incidence can often be traced back to the presence of one or more of several non-modifiable and modifiable risk factors. While race, age, family history, and prior stroke are considered non-modifiable stroke risk factors, hypertension, smoking, obesity, cholesterol, diabetes, physical inactivity, and alcohol use are all modifiable risk factors that can be managed to effectively lower the likelihood of future stroke (National Stroke Association, 2003). Disparities in stroke incidence, mortality, and morbidity may be linked to disparities in the prevalence of risk factors between African Americans and Caucasians (Becker, Tuggle, & Prentice, 2001). Gaines and Burke (1995) report greater prevalence of risk factors of stroke among African Americans of all ages.

African Americans also have a higher prevalence of modifiable stroke risk factors such as diabetes, hypertension, high cholesterol, and high blood pressure (Feldman & Fulwood, 1999; Becker, Tuggle, & Prentice, 2001, Ruland, Raman, Chaturvedi, Leurgans, & Gorelick, 2003). The American Heart Association (2003) reports that one in three African American adults - compared to the national average of one in four American adults - has hypertension. Subsequently, the effects modifiable stroke risk factors are more frequent and severe in the African American population. Therefore, when adjusted for age, stroke deaths are almost 40% higher for African Americans than whites (CDC, 2005).

The racial disparities in risk factors are adequately captured by the Behavioral Risk Factor Surveillance System (BRFSS), conducted by the Centers for Disease Control and Prevention (CDC). According to the BRFSS, African Americans are at a higher risk than White Americans for all the modifiable stroke risk factors, with the exception of cholesterol, smoking, and alcohol consumption (BRFSS, 2003). Higher percentage of African Americans have hypertension (31.4% compared to 25.8% Whites), higher Body Mass Index (68.5% compared to 57.4% of Whites), diabetes (10.2% compared to 6.6% of Whites), and lack physical activity (30% compared to 21% Whites).

DISPARITIES IN STROKE AND SOCIO-ECONOMIC STATUS

In addition to a higher prevalence of risk factors among African Americans, there are other explanations for the disparities in stroke mortality and morbidity. Several studies document the relationship between disparities in stroke and socio-economic status (Ayanian, Udvarhelyi, Gastonis, Pashos, & Epstein, 1993; Burstin, Lipsitz, & Brennan 1992; Becker & Newsom, 2003; Cooper, 1993; Fiscella, Franks, Gold, & Clancy, 2000; Gornick, Eggers, Reilly, Mentnech, Fitterman, Kucken, & Vladeck, 1996; Nickens, 1995; Oddone, Horner, Diers, Lipscomb, McIntyre, Cauffman et al., 1998; Dries, Exner, Derek, Gersh, Cooper, Carson, et al. 1999; Whittle, Conigliaro, Good, & Lofgren, 1993).

These studies associate disparities in healthcare with socio-economic status, to the extent of regarding it as a key determinant of disease outcome (Chung, 2003), particularly for African-American health (Lillie-Blanton & Laveist, 1996; Gornick, 2000; Burstin, et al., 1992; Becker et al. 2003). Wilson (1987) suggests that socio-economic status is a greater determinant of African-American problems than even race. Low socioeconomic status has been associated with lesser access to care and lesser utilization of healthcare, even among those with health insurance (Morgenstern et. al., 1997, Newacheck, Hughes, & Stoddard, 1996; Adler, Boyce, Chesney, Folkman, & Syme, 1993). Gillum and Mussolino (2003) found that African Americans with eight or more years of education had significantly lower risk of stroke compared to those with less than eight years of education. Bone, Hill, Stallings, Gelber, Barker, Baylor, et al. (2000) studied 2,196 adult African Americans and found that respondents with hypertension were more likely to have less than 12 years education, be unemployed, or have low income. Some studies suggest that racial disparities would appear smaller if people with the same education and socioeconomic status are compared to each other (Sowers, Ferdinand, Bakris, & Douglas, 2002; Jamerson, 1993).

Some investigations associate the racial disparity in stroke incidence with differential treatment by healthcare providers (Smith, 1998; Watson, 2001). Mitchell, Ballard, Matchar, Whisnant, and Samsa (2000) found that African Americans were less likely to receive current standards for stroke treatment as compared to Caucasians even after accounting for differences in the ability to pay, health provider characteristics, patient demographics, and comorbidity. A report by Lillie-Blanton, Rushing, Ruiz, Mayberry, and Boone (2002) evaluated 81 studies published between 1985 and 2001 that included minorities in adequate numbers. The majority of the studies (68 out of 81) revealed that the minorities received sub-standard care. Racial differences have been confirmed in the use of diagnostic procedures, anticoagulant therapy (Christian, Lapane, & Toppa, 2003), thrombolytic therapy, carotid endarterectomy (Goldstein, Matchar, Hoff-Lindquist, Horner, & Samsa, 2003), and revascularization procedures (Ibrahim, Whittle, Bean-Mayberry, Kelley, Good, & Conigliaro, 2003).

Alkadry and Tower (2010) assert that geographical location (e.g. rural West Virginia) also restricts the type of treatment available to residents, particularly access to quality healthcare, availability of qualified health care providers, facilities and insurance coverage. Uneven access to healthcare services and lower quality of care combined with cultural barriers (Reese & Ahern, 1999) and Tuskegee-like abuses of African Americans tend to decrease minority trust in the healthcare system (Eric, 1997; Shavers & Lynch, 1997). This lack of trust makes it even harder for healthcare professionals to access and recruit African Americans in order to provide stroke education and management. The paucity of medical research information from under-served minorities also amplifies stroke research and treatment challenges.

DISPARITIES IN AWARENESS

The most easily modifiable barrier to acute and preventive stroke therapy is poor knowledge of stroke risks, warning signs, and the necessity of seeking emergency care as soon as a stroke is suspected (Hachinski, 2002). Researchers assessing American adults, largely composed of Caucasians, consistently report poor stroke knowledge in the general population (Travis, Flemming, Brown, Meissner, McClelland, & Weigand, 2003; Reeves, Hogan, & Rafferty, 2002; Rowe, Frankel, & Sanders, 2001; Pratt, Ha, Levine, & Pratt, 2003; and Hux, Rogers, & Mongar, 2000). Stroke knowledge includes awareness of warning signs, stroke factors, and appropriate emergency action. The 'act F.A.S.T.' (Face, Arms, Speech, and Time) campaign as promoted by the National Stroke Association may be a great way to educate people on what to do if someone suffers from a stroke. The acronym prompts people to look for signs (such as a droopy face, numbness or weakness on one side of the body, and slurred speech) and act immediately to prevent permanent physical damage (AHA, 2009). Awareness and action can therefore be the key to lessening the detrimental physical and financial implications of stroke related disabilities.

Studies (such as Rowe et al., 2001) have demonstrated that respondents agree that a person can reduce the risk of having a stroke, yet several of them cannot even recognize the risk factors. In an interview of 2,512 adults, Reeves et al. (2002) reported that 80% of respondents could report at least one stroke risk factor, but only 28% could correctly identify three. Pancioli, Broderick, Kothari, Brott, Tuchfarber, Miller et al. (1998) revealed an even lower percentage (32%) of respondents who were able to identify one of the three risk factors.

Early recognition of stroke symptoms and immediate emergency care are the best ways to reduce the impact of a stroke once it is eminent. However, many people fail to identify a stroke and consequently do no seek timely medical intervention. According to a report by the Centers for Disease Control and Prevention (2004), only 17% of the public recognize enough of the major warning signs of stroke to call 911. Yoon, Heller, Levi, Wiggers, and Fitzgerald (2001) found that only 49.8% of respondents correctly identified more than one warning sign of stroke. Another study reported that 39% of 163 patients admitted to the emergency room with possible stroke were unable to identify a single sign of stroke (Kothari, Sauerbeck, Jauch, Broderick, Brott, Khoury et al., 1997). Rowe et al. (2001) found that of the 602 respondents, none could name all five stroke warning signs and only 39% could spontaneously name at least one warning sign.

Rapid action is important because the only Food and Drug Administration-approved acute stroke therapy is effective only if given intravenously within 3-6 hours of stroke symptom onset (American Heart Association, 2004; Morgenstern et. al., 1997). An individual's inability to identify a stroke causes delay in seeking medical attention, and ultimately leads to more severe impacts of stroke (Yoon & Byles, 2002). Parahoo, Thompson, Cooper, Stringer, Ennis, and McCollam (2003) found that almost half of those surveyed would not contact an ambulance service if they thought they were having a stroke. Menon, Pandey, and Morgenstern (1998) revealed that compared to 34% of White non-Hispanic patients, 28% of African American, 18% of Hispanic American, and 26% of women patients were seen by a neurologist within that three-hour window.

What remains largely unclear is the contribution of racial, or other socioeconomic or regional disparities related to knowledge of stroke and its incidence. Ferris, Robertson, Fabunmin, and Mosca (2005), and Pratt et al. (2003) found that knowledge of stroke warning signs is poor among Americans, particularly among racial and ethnic minorities who have a greater non-modifiable risk burden. Pratt et al. (2003) used structured telephone interviews to assess stroke knowledge among 379 older African American adults who had received previous medical treatment in Detroit, Michigan. They concluded that while these adults were aware of the need for urgent attention in the event of stroke, accurate stroke knowledge such as knowledge of stroke warning signs (29% correct), risk factors (58% correct), and modifiable risks (29%) was extremely poor, substantially below levels reported in separate studies of Caucasian adults.

Two additional studies assessed stroke awareness only among women, though limited minority sampling also hampered their ability to directly assess racial disparities in stroke knowledge. The first study of 71 Hispanic and 144 non-Hispanic white hospitalized women over 39 years of age demonstrated that Hispanics were significantly less likely to report stroke risk factors such as hypertension (Kattapong et al., 1998). Ferris et. al. (2005) conducted a national survey of about 1000 women including 12% African Americans and 12% Hispanics to assess trends in stroke awareness and knowledge. Database constraints did not allow for adjustment of potential confounders in evaluating the association between race and stroke awareness.

Data from the National Health and Nutrition Examination Survey (NHANES) concluded that a third of the excess mortality in African Americans over Whites was due to risk factors such as hypertension, smoking, high cholesterol, and obesity, another third resulted from socioeconomic factors, but the remaining third could not be explained (Otten, Teustsch, Williamson, & Marks, 1990; Gaines & Burke, 1995). In the next section, we test whether disparities in awareness of stroke risks, signs, and treatment could explain that remaining portion of the unexplained disparity.

METHODS

Target Population

Twelve West Virginia counties with sizeable African American populations were targeted for data collection. A regular mail survey was used to reach the Caucasian population. The original mail survey had a very poor response rate of African Americans, which is consistent with previous stroke surveys in West Virginia (Alkadry et al., 2005). The difficulty of recruitment and retention of African Americans into research studies can be attributed to historical mistrust of biomedical research, lack of cultural relevance and competence, and less access to care (Loftin, Barnett, Bunn, & Sullivan, 2005; Shavers-Hornaday & Lynch, 1997). These barriers required the researchers to actively seek alternative ways for the inclusion of African Americans in the study. As a result, local and state African American representatives were consulted for advice on overcoming low response rates. These community leaders suggested data collection at local, county, and state African American community events and festivals, as well as through community and church organizations. African American adults approached at these events were asked to voluntarily complete the questionnaire. The use of convenience sampling to reach target populations is a common practice in the field of stroke (Okwumabua, Martin, Clayton-Davis, & Pearson, 1997; Travis et al., 2003; Pratt et al., 2003; Hux et al., 2000).

Study Population

Using both methods, 400 African Americans and 456 Caucasians responded to the 27-question survey between August 2004 and February 2005. Response rates were 51% for Caucasians and approximately 70% for African Americans. The survey included questions about previous stroke and individuals who reported previous stroke were excluded from these analyses.

Data Analysis

All data analyses were carried out using SAS. Initial analysis described the characteristics of the sample. A multiple logistic regression was used to understand the contribution of factors in predicting high stroke risk factor awareness (defined as >= 95 percentile of risk factor awareness scores). Further analysis was done to evaluate the awareness of modifiable and non-modifiable risk factors and awareness of signs. High awareness for all of these outcome variables was defined as greater than or equal to the 95 percentile of awareness scores. Awareness scores were based on unweighted sum of scores from a set of questions.

Awareness of risk factor scores were computed on seven modifiable (hypertension, diabetes, high cholesterol, heart disease, obesity, alcoholism, and smoking) and five non-modifiable (age, history of stroke, family history of stroke, race, and gender) risk factors. Respondents were asked to report whether they thought each one of these risk factors was in fact a risk factor for stroke, and an accuracy score was computed for each of the respondents. Composite scores on awareness of signs were also computed on seven items related to clinical signs and symptoms.

RESULTS

This study is based on responses from 823 respondents (without history of stroke). Self-identified racial status was not provided by 33 respondents, resulting in 422 Whites and 368 African Americans (AA). Table 1 shows a comparison of socio-demographic factors of this sample with West Virginia census and Behavioral Risk Factor Surveillance System (BRFSS), as well as United States 2000 census. The age and gender distribution of this sample was significantly different from West Virginia 2000 census. West Virginia census data clearly shows the difference in age structure between West Virginia and US population census. This sample also differed from West Virginia BRFSS data on risk factor distribution. Initial univariate analysis showed significant differences in the ages of Whites and AA. The average age of respondents was 53.3 years with African Americans significantly younger than whites (Whites: 54.4 [+ or -] 16.6 vs. AA: 49.7 [+ or -] 16.9 years, P value <0.01). The education of the respondents was notably different between two races with a bimodal distribution. Significantly higher proportion of whites did not graduate from high school compared to AA (13.3 % vs. 9.5 %). At the same time, a greater proportion of whites had a graduate degree (14.1% vs. 10.7%). Although there was no significant difference in income between the races, the proportion of AA respondents without health insurance was greater than Whites (16% in AA vs. 10% in Whites). Table 2 shows the sociodemographic and health behavior characteristics of study sample by race.

Prevalence of Risk Factors for Stroke

There was a significant difference between Whites and AA in terms of prevalence of smoking (2.9% of white respondents vs. 16.7% of AA respondents). However, there was no difference in the prevalence of diabetes, hypertension, sleep apnea, and heart disease between AA and White respondents. However, high cholesterol was more prevalent in Whites than AA (44.9% vs. 32.9%) (Table 3). There was no significant disparity in the prevalence of physical inactivity, chewing tobacco, and family history of stroke.

Awareness of Risk Factors

Seven modifiable risk factors for stroke (hypertension, diabetes, high cholesterol, heart disease, obesity, alcoholism, and smoking) and five non-modifiable risk factors for stroke (age, history of stroke, family history of stroke, race, and gender) were considered. Respondents were asked to check whether they thought each one of these risk factors was in fact a risk factor for stroke. A total composite score was computed for each of the respondents based on responses to questions on stroke risk factors. There was a statistically significant difference in the awareness of risk factors between Whites and African Americans in univariate analysis of the prevalence of risk factors (Table 4).

Awareness of Stroke Signs

A total composite score was computed for each of the respondents based on response to questions on signs of stroke. Univariate analysis was carried out which showed significant difference between Whites and African Americans (Table 3). In order to control for confounders such as income, education, age, and other risk markers that may contribute to the prediction of high awareness, a stepwise multiple logistic regression was carried out after examining the collinearity between explanatory variables. If two variables were highly correlated, only one of them was used in the regression model. The final selected model for each outcome variable is presented in Table 5. For awareness of signs, race was a significant variable in that Whites were 2.3 times as likely as African Americans to be aware of stroke signs. However, for awareness of risk factors (modifiable and non-modifiable) race was not an independent risk factor (Table 5).

Awareness of Treatment Options

Key to surviving a stroke is immediate evaluation and treatment at a critical care emergency room. In this sample, 72.7% of White respondents indicated that they would go to an emergency room or call 911, 70.9% of African Americans indicated that they would do so. Among African American respondents, 13.4% would call their doctor if they thought they were having a stroke while only 7% of whites indicated that they would do so.

DISCUSSION

The most noticeable finding of this study is the racial disparity in knowledge about stroke warning signs. Prompt identification and reaction to stroke warning signs, and rushing to obtain hospital emergency treatment are critical to survival following onset of stroke symptoms. This rural study revealed a racial disparity in awareness of stroke signs and appropriate action to be taken. In this sample, 26.3% of all rural Caucasian respondents were able to identify all 7 warning signs of stroke versus 13.3% (almost half) of rural African Americans. Failure to recognize any of these stroke warning signs could lead to death or permanent disability. The fact that these racial disparities in stroke awareness exist should alert policy makers to the potential reduction in stroke incidence that could be achieved through targeted awareness campaigns. The cost of public education campaigns on stroke prevention is minimal relative to the costly expense of acute hospitalization, rehabilitation treatment, or long-term disability care.

One of the most important implications of this study is that stroke prevention efforts should target both minority and white communities as all rural residents show poor knowledge of stroke warning signs, appropriate emergency action, and risk factors. To begin to remediate their elevated stroke incidence rates, rural minorities need culturally sensitive stroke prevention training, highlighting stroke warning signs and their increased stroke risk, combined with effective risk factor management in culturally appropriate formats. Stroke prevention interventions may need to be customized according to the specific cultural and ethnic needs of the targeted group in order to more effectively bring about behavior change. The results from this study suggest that integrating intervention efforts with rural and cultural characteristics would serve to enhance non-urban participants' acceptance of health information (Thomas, 2004). Culturally sensitive public education interventions have the potential of increasing the awareness of stroke signs and of prompting emergency action to reduce the impact of a stroke (McGruder, Malarcher, Antoine, Greenlund, & Croft, 2004). Rimmer et. al. (2000) found that a short term intervention for health promotion among African Americans was effective in improving their clients' management of risk factors such as high cholesterol, obesity, and low physical activity. Educational interventions related to cardiovascular prevention have had positive effects on preventive behavior (Heath, Fuchs, Croft, Temple, & Wheeler, 1995).

The present study has several limitations. This sample of respondents may not be comparable to the West Virginia State census or BRFSS population and, as such, it is difficult to extrapolate the results to all Whites or African Americans in this state. The non-random sampling conducted to recruit African Americans also raises concerns about non-response bias. However, most of the demographic characteristics of the survey respondents are similar to the general population of the selected geographic areas of West Virginia. The one exception to that consistency is the higher percentage of females who answered the survey. Given the findings in a gender and stroke study conducted by Alkadry and Tower (2010) in West Viginia, this gender non-response issue is likely to have little effect on the conclusions made in this study. The self reported data format may have fostered social desirability and recall biases. One methodologically challenging alternative would have been patient medical record review as described by both Travis et al. (2003) and Pratt et al. (2003), although this procedure may hamper minority participation in this community. Also, the use of close-ended and multiple-choice questions may have prompted respondents to provide answers that may not represent a true-to-life experience. An alternative format has been described by Rowe et al. (2001) whose project utilized open-ended questions.

Finally, race is an important variable in understanding the reasons contributing to health disparities in the United States. However, it should not be overlooked that race is intricately linked with various social factors that have modifiable societal structures. This investigation was designed with the sample size and statistical power to evaluate racial differences in stroke awareness. The challenge before policy makers is to direct more attention and resources toward stroke awareness campaigns.

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MOHAMAD G. ALKADRY

Old Dominion University

RUCHI BHANDARI

CHRISTINA S. WILSON

West Virginia University

BRANDI BLESSETT

University of Central Florida
Table 1
Demographic Comparisons between Study Respondents,
West Virginia, and U.S. Residents

Description            All     Whites   Blacks      West
                       897      442      400     Virginia *
Age
Under 35               15.8%    12%     20.3%      28.5%
35-49 Years            24.6%    23.5%   25.6%      29.5%
50-64 Years            32.6%    32.4%
65-74 Years            14.8%    17%     12.8%      10.6%
75-84 Years             9.4%    12.2%    6.1%       6.8%
85 and Older            2.7%     2.9%    1.9%       2.3%
Gender
Male                   22.2%    13%     32.7%       49%
Female                 77.8%    87%     67.3%       51%
Household Income
< $15,000              25.9%    27%     23.8%      25.4%
$15,000-$34,999        30.4%    29.9%   31.5%      32.0%
$35,000-$49,999        20.4%    21.2%   18.9%      16.4%
$50,000-$99,999        19.6%    18.5%   21.6%      21.2%
> $100,000              3.6%     3.4%    4.1%        5%
Risk Factors
Hypertension           48.7%    49.5%   48.5%      32.5%
Smoking                30.2%    13%     43.9%       23%
Obesity                35.3%    30.4%   40.9%       28%
High Cholesterol        40%      46%    33.3%       38%
Diabetes               16.7%    14.2%    19%       10.2%
Physical Inactivity    39.6%    39.1%   41.3%      28.4%
Description            United
                      Starter *
Age
Under 35                49.5%
35-49 Years              38%
50-64 Years
65-74 Years             6.5%
75-84 Years             4.4%
85 and Older            1.5%
Gender
Male                    49.1
Female                  50.9%
Household Income
< $15,000               15.8%
$15,000-$34,999         25.6%
$35,000-$49,999         16.5%
$50,000-$99,999         19.7%
> $100,000              12.3%
Risk Factors
Hypertension            25.6%
Smoking                 28.4%
Obesity                 22.2%
High Cholesterol         30%
Diabetes                6.7%
Physical Inactivity     24.4%

* Source: 2000 Census & BRFSS

Table 2
Univariate Analysis of Differences by Race (Non-Hispanic
Whites vs. African Americans): Socio-Demographic &
Obesity Status

Variables                                   Race

Socio-Demographic and Obesity     Non Hispanic    African
Status Differences                   Whites      Americans
                                     N (%)         N (%)

No health insurance                42 (10.1)      58 (16.1)
Gender
  Male                             53 (12.6)     117 (32.4)
  Female                          368 (87.4)     244 (67.6)
Obesity status
  Underweight                       8 (2.0)        2 (0.61)
  Normal                          127 (31.8)      73 (22.3)
  Overweight                      144 (36.1)     119 (36.3)
  Obese                           120 (30.1)     134 (40.9)
Education
  Did not graduate high school     55 (13.4)      34 (9.6)
  High school diploma or GED      150 (36.5)      67 (18.9)
  Technical school                 21 (5.1)       21 (5.9)
  Some college                     52 (12.7)      90 (25.4)
  2-year degree of college         24 (5.8)       39 (11.0)
  4-year degree of college         51 (12.4)      66 (18.6)
  Graduate degree                  58 (14.1)      38 (10.7)
Employment status
  Work < 40 hrs/week               60 (14.3)      44 (12.3)
  Work [greater than              132 (31.5)     179 (50.1)
    or equal to] 40 hrs/week
  Unemployed                       66 (15.8)      27 (7.6)
  Retired                         142 (33.9)      92 (25.8)
  Disabled                         19 (4.5)       15 (4.2)

Variables

Socio-Demographic and Obesity     P-value based
Status Differences                on Chi-Square
                                      test

No health insurance                 0.0132
Gender                            < 0.0001
  Male
  Female
Obesity status                      0.0023
  Underweight
  Normal
  Overweight
  Obese
Education                         < 0.0001
  Did not graduate high school
  High school diploma or GED
  Technical school
  Some college
  2-year degree of college
  4-year degree of college
  Graduate degree
Employment status                 < 0.0001
  Work < 40 hrs/week
  Work [greater than
    or equal to] 40 hrs/week
  Unemployed
  Retired
  Disabled

Table 3
Univariate Analysis of Differences by Race (Non-Hispanic
Whites vs. African Americans): Health Status, Perceived
Signs and Health Practice

Variables                                  Race

                                Non Hispanic     African
                                Whites, N (%)   Americans
                                                  N (%)

Health Behavior/
Lifestyle Factors

Exercise
  Never                          39 (9.4)        17 (4.7)
  Rarely                         90 (21.6)       91 (24.9)
  Once a month                   31 (7.4)        39 (10.7)
  1-2 times per week            124 (29.7)      116 (31.8)
  3-5 times per week            133 (31.9)      102 (29.0)
Smoke                            11 (2.9)        61 (16.7)
High Cholesterol                188 (44.9)      120 (32.9)
Perceived Signs of Stroke
  High fever                     37 (8.0)        90 (24.6)
  Excessive sweating            218 (52.0)      215 (60.4)
  Sudden numbness or weakness   409 (97.4)      322 (89.0)
  Sudden severe headache        332 (79.6)      246 (69.1)
  Loss of appetite               69 (16.8)       79 (23.0)
  Loss of vision                335 (80.1)      256 (71.7)
  Loss of speech                404 (96.7)      318 (89.6)

Variables

                                P-value based
                                on Chi-Square
                                    test

Health Behavior/
Lifestyle Factors

Exercise                          0.0327
  Never
  Rarely
  Once a month
  1-2 times per week
  3-5 times per week
Smoke                           < 0.0001
High Cholesterol                  0.027
Perceived Signs of Stroke
  High fever                    < 0.0001
  Excessive sweating              0.0194
  Sudden numbness or weakness   < 0.0001
  Sudden severe headache          0.0008
  Loss of appetite                0.0319
  Loss of vision                  0.0059
  Loss of speech                < 0.0001

Table 4
Univariate Analysis of Differences by Race (Non-Hispanic
Whites vs. African Americans): Perceived Risk Factors for
Stroke

Variables                                Race

                              Non Hispanic     African
                              Whites, N (%)   Americans
                                                N (%)

Perceived Risk Factors for
Stroke

Are you at risk of stroke     122 (31.2)      136 (40.7)
Age                           306 (73.2)      203 (56.1)
High cholesterol              355 (85.0)      283 (79.0)
Depression                     90 (21.5)      110 (30.6)
Smoking                       308 (73.7)      236 (65.6)
History of previous stroke    359 (85.9)      242 (67.2)
Race                          141 (33.7)      211 (58.6)
Environment                    79 (19.0)      105 (29.2)
Gender                        105 (25.1)      113 (31.4)

Variables

                              P-value based
                              on Chi-Square
                                   test

Perceived Risk Factors for
Stroke

Are you at risk of stroke       0.0076
Age                           < 0.0001
High cholesterol                0.027
Depression                      0.0041
Smoking                         0.0137
History of previous stroke    < 0.0001
Race                          < 0.0001
Environment                     0.0008
Gender                          0.052

Table 5.
Odds Ratios of Statistically Significant Variables from
Stepwise Logistic Regression for Stroke Awareness

Model                            Variable         Odds       95% CI
                                                 Ratio *
1                            Gender (male vs.     0.537    0.303-0.952
Awareness of Signs           female)
([greater than or equal
to] 95 percentile of         Obesity status       1.742    1.058-2.867
composite score)             (overweight vs.
                             normal)

                             Smoke (yes vs.       0.478    0.236-0.967
                             no)

                             Race (white vs.      2.302    1.460-3.630
                             black)

2                            High cholesterol     2.141    1.174-3.906
Awareness of All Risk        (yes vs. no)
Factors ([greater than or
equal to] 95 percentile      Obesity status       2.058    1.041-4.069
of composite score)          (obese vs.
                             normal)

3                            Exercise (rarely     0.528    0.349-0.798
Awareness of                 vs. often)
Modifiable Risk ([greater
than or equal to] 95
percentile of composite
score)

4                            High cholesterol     1.854    1.168-2.943
Awareness of Non-            (yes vs. no)
Modifiable Risk ([greater
than or equal to] 95         Insurance (no vs.    0.484    0.247-0.949
percentile of composite      yes)
score)

Model                            Variable         P-
                                                 value

1                            Gender (male vs.    0.0333
Awareness of Signs           female)
([greater than or equal
to] 95 percentile of         Obesity status      0.0290
composite score)             (overweight vs.
                             normal)

                             Smoke (yes vs.      0.0401
                             no)

                             Race (white vs.     0.0003
                             black)

2                            High cholesterol    0.0131
Awareness of All Risk        (yes vs. no)
Factors ([greater than or
equal to] 95 percentile      Obesity status      0.0380
of composite score)          (obese vs.
                             normal)

3                            Exercise (rarely    0.0024
Awareness of                 vs. often)
Modifiable Risk ([greater
than or equal to] 95
percentile of composite
score)

4                            High cholesterol    0.0088
Awareness of Non-            (yes vs. no)
Modifiable Risk ([greater
than or equal to] 95         Insurance (no vs.   0.0348
percentile of composite      yes)
score)

* Odds Ratio adjusted for gender, diabetes, high cholesterol,
sleep apnea, heart disease, smoke, obesity status, exercise,
education, see doctor, insurance
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