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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Public Health</journal-id>
<journal-title>Frontiers in Public Health</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Public Health</abbrev-journal-title>
<issn pub-type="epub">2296-2565</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fpubh.2024.1362979</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Public Health</subject>
<subj-group>
<subject>Original Research</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Stroke awareness and knowledge in Sudan: a cross-sectional analysis of public perceptions and understanding</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author" equal-contrib="yes">
<name><surname>Eltayib</surname> <given-names>Eyman M.</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="author-notes" rid="fn0001"><sup>&#x2020;</sup></xref>
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<contrib contrib-type="author" equal-contrib="yes">
<name><surname>Jirjees</surname> <given-names>Feras</given-names></name>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<xref ref-type="author-notes" rid="fn0001"><sup>&#x2020;</sup></xref>
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<contrib contrib-type="author">
<name><surname>Suliman</surname> <given-names>Duaa</given-names></name>
<xref ref-type="aff" rid="aff3"><sup>3</sup></xref>
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<contrib contrib-type="author">
<name><surname>AlObaidi</surname> <given-names>Hala</given-names></name>
<xref ref-type="aff" rid="aff4"><sup>4</sup></xref>
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</contrib>
<contrib contrib-type="author">
<name><surname>Ahmed</surname> <given-names>Munazza</given-names></name>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
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<contrib contrib-type="author">
<name><surname>Kharaba</surname> <given-names>Zelal J.</given-names></name>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<xref ref-type="aff" rid="aff5"><sup>5</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/1695472/overview"/>
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<contrib contrib-type="author">
<name><surname>Alfoteih</surname> <given-names>Yassen</given-names></name>
<xref ref-type="aff" rid="aff6"><sup>6</sup></xref>
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<contrib contrib-type="author">
<name><surname>Barakat</surname> <given-names>Muna</given-names></name>
<xref ref-type="aff" rid="aff7"><sup>7</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/1015841/overview"/>
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<contrib contrib-type="author">
<name><surname>Khidhair</surname> <given-names>Zainab</given-names></name>
<xref ref-type="aff" rid="aff8"><sup>8</sup></xref>
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</contrib>
<contrib contrib-type="author">
<name><surname>ALSalamat</surname> <given-names>Husam</given-names></name>
<xref ref-type="aff" rid="aff9"><sup>9</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/1889143/overview"/>
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<contrib contrib-type="author">
<name><surname>Mustafa</surname> <given-names>Nazik</given-names></name>
<xref ref-type="aff" rid="aff10"><sup>10</sup></xref>
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<contrib contrib-type="author">
<name><surname>Cherri</surname> <given-names>Sarah</given-names></name>
<xref ref-type="aff" rid="aff11"><sup>11</sup></xref>
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<contrib contrib-type="author">
<name><surname>El Khatib</surname> <given-names>Sami</given-names></name>
<xref ref-type="aff" rid="aff12"><sup>12</sup></xref>
<xref ref-type="aff" rid="aff13"><sup>13</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/379954/overview"/>
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<contrib contrib-type="author">
<name><surname>Hallit</surname> <given-names>Souheil</given-names></name>
<xref ref-type="aff" rid="aff14"><sup>14</sup></xref>
<xref ref-type="aff" rid="aff15"><sup>15</sup></xref>
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<contrib contrib-type="author" corresp="yes">
<name><surname>Malaeb</surname> <given-names>Diana</given-names></name>
<xref ref-type="aff" rid="aff16"><sup>16</sup></xref>
<xref ref-type="corresp" rid="c001"><sup>&#x002A;</sup></xref>
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<contrib contrib-type="author">
<name><surname>Hosseini</surname> <given-names>Hassan</given-names></name>
<xref ref-type="aff" rid="aff17"><sup>17</sup></xref>
<xref ref-type="aff" rid="aff18"><sup>18</sup></xref>
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<aff id="aff1"><sup>1</sup><institution>College of Pharmacy, Jouf University</institution>, <addr-line>Sakaka</addr-line>, <country>Saudi Arabia</country></aff>
<aff id="aff2"><sup>2</sup><institution>College of Pharmacy, University of Sharjah</institution>, <addr-line>Sharjah</addr-line>, <country>United Arab Emirates</country></aff>
<aff id="aff3"><sup>3</sup><institution>Health Policy, Mohammed Bin Rashid School of Government</institution>, <addr-line>Dubai</addr-line>, <country>United Arab Emirates</country></aff>
<aff id="aff4"><sup>4</sup><institution>School of Pharmacy, Queen's University Belfast</institution>, <addr-line>Belfast</addr-line>, <country>United Kingdom</country></aff>
<aff id="aff5"><sup>5</sup><institution>College of Pharmacy, Al Ain University</institution>, <addr-line>Abu Dhabi</addr-line>, <country>United Arab Emirates</country></aff>
<aff id="aff6"><sup>6</sup><institution>College of Dentistry and College of Humanities, City University College of Ajman</institution>, <addr-line>Ajman</addr-line>, <country>United Arab Emirates</country></aff>
<aff id="aff7"><sup>7</sup><institution>Faculty of Pharmacy, Applied Science Private University</institution>, <addr-line>Amman</addr-line>, <country>Jordan</country></aff>
<aff id="aff8"><sup>8</sup><institution>College of Science, University of Baghdad</institution>, <addr-line>Baghdad</addr-line>, <country>Iraq</country></aff>
<aff id="aff9"><sup>9</sup><institution>Faculty of Medicine, Al-Balqa Applied University</institution>, <addr-line>Al-Salt</addr-line>, <country>Jordan</country></aff>
<aff id="aff10"><sup>10</sup><institution>Department of Pharmacology, Faculty of Pharmacy, Al Neelain University</institution>, <addr-line>Khartoum</addr-line>, <country>Sudan</country></aff>
<aff id="aff11"><sup>11</sup><institution>Lebanese International University, School of Pharmacy</institution>, <addr-line>Beirut</addr-line>, <country>Lebanon</country></aff>
<aff id="aff12"><sup>12</sup><institution>Department of Biomedical Sciences, Lebanese International University</institution>, <addr-line>Bekaa</addr-line>, <country>Lebanon</country></aff>
<aff id="aff13"><sup>13</sup><institution>Center for Applied Mathematics and Bioinformatics (CAMB), Gulf University for Science and Technology</institution>, <addr-line>West Mishref</addr-line>, <country>Kuwait</country></aff>
<aff id="aff14"><sup>14</sup><institution>School of Medicine and Medical Sciences, Holy Spirit University of Kaslik</institution>, <addr-line>Jounieh</addr-line>, <country>Lebanon</country></aff>
<aff id="aff15"><sup>15</sup><institution>Applied Science Research Center, Applied Science Private University</institution>, <addr-line>Amman</addr-line>, <country>Jordan</country></aff>
<aff id="aff16"><sup>16</sup><institution>College of Pharmacy, Gulf Medical University</institution>, <addr-line>Ajman</addr-line>, <country>United Arab Emirates</country></aff>
<aff id="aff17"><sup>17</sup><institution>UPEC-University Paris-Est</institution>, <addr-line>Creteil</addr-line>, <country>France</country></aff>
<aff id="aff18"><sup>18</sup><institution>RAMSAY SANT&#x00C9;, HPPE</institution>, <addr-line>Champigny-sur-Marne</addr-line>, <country>France</country></aff>
<author-notes>
<fn fn-type="edited-by" id="fn0002">
<p>Edited by: Kayode Ayodele, Obafemi Awolowo University, Nigeria</p>
</fn>
<fn fn-type="edited-by" id="fn0003">
<p>Reviewed by: Vishal Vennu, King Saud University, Saudi Arabia</p>
<p>Bhavesh Modi, All India Institute of Medical Sciences, India</p>
</fn>
<corresp id="c001">&#x002A;Correspondence: Diana Malaeb, <email>dr.diana@gmu.ac.ae</email></corresp>
<fn fn-type="equal" id="fn0001">
<p><sup>&#x2020;</sup>These authors have contributed equally to this work and share first authorship</p>
</fn>
</author-notes>
<pub-date pub-type="epub">
<day>01</day>
<month>05</month>
<year>2024</year>
</pub-date>
<pub-date pub-type="collection">
<year>2024</year>
</pub-date>
<volume>12</volume>
<elocation-id>1362979</elocation-id>
<history>
<date date-type="received">
<day>29</day>
<month>12</month>
<year>2023</year>
</date>
<date date-type="accepted">
<day>18</day>
<month>04</month>
<year>2024</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#x00A9; 2024 Eltayib, Jirjees, Suliman, AlObaidi, Ahmed, Kharaba, Alfoteih, Barakat, Khidhair, ALSalamat, Mustafa, Cherri, El Khatib, Hallit, Malaeb and Hosseini.</copyright-statement>
<copyright-year>2024</copyright-year>
<copyright-holder>Eltayib, Jirjees, Suliman, AlObaidi, Ahmed, Kharaba, Alfoteih, Barakat, Khidhair, ALSalamat, Mustafa, Cherri, El Khatib, Hallit, Malaeb and Hosseini</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/">
<p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</p>
</license>
</permissions>
<abstract>
<sec id="sec1">
<title>Introduction</title>
<p>Stroke, a leading cause of morbidity and mortality globally, demands heightened awareness and knowledge for effective preventive strategies and tailored response. Sudan is classified as a low income country with a low rate of literacy, lack of knowledge, and awareness about diseases. Thus, this study aimed to assess stroke awareness and knowledge among Sudanese population, and identify the associated factors influencing awareness.</p>
</sec>
<sec id="sec2">
<title>Methods</title>
<p>A cross-sectional study conducted between October and November 2022 through a self-administered online survey distributed via various social media platforms. The study involved adults aged 18&#x2009;years and above through snow-ball sampling technique. The survey covered general awareness and knowledge concerning stroke risk factors, consequences, and the appropriate responses taken during acute stroke attacks.</p>
</sec>
<sec id="sec3">
<title>Results</title>
<p>A total of 410 participants were enrolled in the study, majority (93.4%) were from urban area and had university degree (92.4%). Furthermore, 92.2% were aware about stroke and 74.9% were able to recognize the symptoms of stroke. Only 40.2% identified all correct answers, 96.3, 92.3, and 95.1% recognized at least one risk factor, early symptom, and consequences, respectively. Females were significantly more than males able to identify at least one risk factor. Almost all participants (99.5%) perceived stroke as a serious disease (99.5%). Notably, 86.3% would promptly transport a suspected stroke patient to the hospital. The multivariable analysis showed that females versus males and patients with depression versus without depression had significantly higher odds to identify at least one risk factor (OR of 14.716 [95% CI 1.901; 113.908] and 0.241 [95% CI 0.059; 0.984], respectively).</p>
</sec>
<sec id="sec4">
<title>Conclusion</title>
<p>The study concluded that stroke knowledge and awareness among Sudanese population is suboptimal. Furthermore, early stroke recognition and intake of the appropriate management strategies are lacking which highlights the need for targeted education and awareness campaigns.</p>
</sec>
</abstract>
<kwd-group>
<kwd>stroke</kwd>
<kwd>Sudan</kwd>
<kwd>knowledge</kwd>
<kwd>risk factor</kwd>
<kwd>awareness</kwd>
<kwd>source of information</kwd>
</kwd-group>
<counts>
<fig-count count="2"/>
<table-count count="5"/>
<equation-count count="0"/>
<ref-count count="37"/>
<page-count count="10"/>
<word-count count="6664"/>
</counts>
<custom-meta-wrap>
<custom-meta>
<meta-name>section-at-acceptance</meta-name>
<meta-value>Public Health Education and Promotion</meta-value>
</custom-meta>
</custom-meta-wrap>
</article-meta>
</front>
<body>
<sec sec-type="intro" id="sec5">
<title>Introduction</title>
<p>Stroke is a major cause of disability and one of the leading causes of death worldwide (<xref ref-type="bibr" rid="ref1">1</xref>). It is typically defined as a neurological deficit pertaining to an acute focal injury of the central nervous system (CNS) via vascular causes, which include cerebral infarction, intracerebral hemorrhage, and subarachnoid hemorrhage (<xref ref-type="bibr" rid="ref2">2</xref>). The most common risk factors for stroke include hypertension, impaired cardiac function, smoking, poor lifestyle factors, dyslipidemia, obesity, diabetes, and having a family history of stroke (<xref ref-type="bibr" rid="ref3">3</xref>). The majority of ischemic stroke occurs in low- and middle-income countries, where incidents of fatal hemorrhage and ischemic strokes develop more often at younger ages. Additionally, compared to developed countries, the prevalence of stroke has recently increased in developing nations (<xref ref-type="bibr" rid="ref4">4</xref>).</p>
<p>Sudan, a least developed country according to the United Nations, had about 25% of stroke admissions among patients older than 60&#x2009;years old (<xref ref-type="bibr" rid="ref5">5</xref>). Furthermore, stroke was reported to be among the top 25 causes of premature death in Sudan between 1990 and 2019 (<xref ref-type="bibr" rid="ref6">6</xref>). Moreover, statistics from the World Health Organization (WHO) in 2019 show that stroke was the third-top cause of death in both genders, with 48.09 deaths per 100,000 people, in addition to 48,595 new stroke cases recorded in 2019 (<xref ref-type="bibr" rid="ref7">7</xref>).</p>
<p>Unfortunately, stroke risk factors were found to be higher in poor socioeconomic level societies. Nonetheless, community stroke awareness programs are one of the several components that is considered absolutely necessary for stroke care (<xref ref-type="bibr" rid="ref8">8</xref>). The outcome of stroke can be greatly improved through early detection, prompt transfer to medical care, and implementation of appropriate medical therapy (<xref ref-type="bibr" rid="ref9">9</xref>). However, preventive approaches mostly revolve around understanding stroke risk factors, identifying the warning signs, and treating the concomitant conditions. According to the World Bank classification, Sudan is a low-income country (<xref ref-type="bibr" rid="ref10">10</xref>). In addition, the literacy rates in Sudan is low, particularly among young women (<xref ref-type="bibr" rid="ref11">11</xref>). With the adult literacy rate of 60.7% (<xref ref-type="bibr" rid="ref12">12</xref>), identifying the existing gaps in knowledge among Sudanese population regarding stroke can help recognize areas to be targeted to improve overall public health and healthcare practices. Additionally, increased understanding about stroke has been linked with high income status, smoking history, and educational attainment (<xref ref-type="bibr" rid="ref13">13</xref>). Therefore, it is essential to screen for socioeconomic status, educational achievement, and lifestyle factors.</p>
<p>Comprehensive research focusing on the factors associated with knowledge and awareness of stroke among Sudanese population is extremely essential as it allows the design for targeted interventions and educational campaigns tailored to the unique challenges faced by the population. This research seeks to provide valuable insights into the importance of enhancing stroke knowledge and awareness, aiming to minimize the occurrence of strokes, preventing recurrence, and ensuring early patient recognition. We intend to expand upon existing knowledge by examining a cohort of participants across Sudan. Additionally, the findings from this study could potentially influence the development and implementation of effective interventions, drawing upon reliable population-based data. Thus, the study aimed to evaluate the awareness and knowledge of stroke within the general population in Sudan and identify factors influencing this awareness.</p>
</sec>
<sec sec-type="methods" id="sec6">
<title>Method</title>
<sec id="sec7">
<title>Study design and period</title>
<p>A cross-sectional study conducted between October and November 2022 through a self-administered closed-ended online survey designed for the general Sudanese population. The study involved adults aged 18&#x2009;years and above through snow-ball sampling technique. The survey covered general awareness and knowledge concerning stroke risk factors and consequences. The survey adhered to the general principles of good survey design (<xref ref-type="bibr" rid="ref14">14</xref>). The survey was developed on Google form and the link was circulated through online platforms like Facebook&#x00AE; and WhatsApp&#x00AE; Participation in the study was voluntary, and eligibility criteria included individuals aged 18 and above, with exclusion of those with a history of stroke. The survey, conducted in the Arabic language, the native language of Sudanese citizens and typically took approximately 10&#x2009;min to be completed.</p>
</sec>
<sec id="sec8">
<title>Validation of the survey</title>
<p>The questionnaire was similarly structured to a survey used in a study conducted in Jordan (<xref ref-type="bibr" rid="ref15">15</xref>). Three academic professionals reviewed the questionnaire. Then the survey underwent a six-person with no medical background pilot test to ensure the clarity of the questions. Subsequently, the questions were modified based on their feedback. The first section of the questionnaire covered the socio-demographic data. The second section assessed the overall knowledge about stroke and evaluated awareness about stroke risk factors, consequences of stroke, and response when facing somebody with a stroke attack. Moreover, it examined knowledge of early warning signs and score of one point was awarded per correct answer to the above statements. The third section identified sources of information related to stroke among the participants.</p>
</sec>
<sec id="sec9">
<title>Sample size calculation</title>
<p>The target sample size was estimated to be 385 participants using the Raosoft&#x00AE; software sample size calculator (<xref ref-type="bibr" rid="ref16">16</xref>). This calculation was determined for the minimum sample size required for an unlimited population size, using a 95% confidence interval, a standard deviation of 0.5, and a margin of error of 5%.</p>
</sec>
<sec id="sec10">
<title>Ethical approval</title>
<p>The study got ethical approval from the research ethics committee of the Faculty of Pharmacy, Al Neelain University, Khartoum, Sudan (NPH1021). All participants agreed to participate in the study by selecting &#x201C;I agree&#x201D; on the electronic informed consent form before filling out the questionnaire. All methods were performed in accordance with the relevant guidelines and regulations or declaration of Helsinki.</p>
</sec>
<sec id="sec11">
<title>Statistical analysis</title>
<p>The data obtained were subjected to analysis using the Statistical Package for the Social Sciences (SPSS) version 27.0. Continuous variables were presented as mean &#x00B1; standard deviation (SD) with a 95% confidence interval (CI). Categorical and ordinal variables were reported as frequencies and percentages. Logistic regression was performed to identify factors linked to the ability to automatically recognize one or more stroke risk factors, warning signs, consequences, and the inclination to promptly seek emergency room care upon experiencing a stroke. Variables demonstrating a significance level of <italic>p</italic>&#x2009;&#x003C;&#x2009;0.2 in the bivariate analysis were incorporated into the regression analysis. Results were presented as odds ratios (OR) with corresponding 95% CI. All statistical tests were two-tailed, and a <italic>p</italic>-value of &#x003C;0.05 was considered statistically significant.</p>
</sec>
</sec>
<sec sec-type="results" id="sec12">
<title>Results</title>
<sec id="sec13">
<title>Sample description</title>
<p>From the total of 410 Sudanese participants enrolled in the study; 195 (47.6%) were females, 149 (36.6%) were under 30&#x2009;years of age, almost half of the participants (51.2%) were married, majority were in urban areas (93.4%), and had university degree (92.4%). More than two thirds of the participants (71.1%) were from the capital city &#x201C;Khartoum,&#x201D; in addition, more than quarter (28.3%) were from other regions of Sudan. The most common chronic diseases among the participants were hypertension (26.8%), dyslipidemia (19.8%) and diabetes mellitus (17.3%). The sociodemographic factors displayed in <xref ref-type="table" rid="tab1">Table 1</xref>.</p>
<table-wrap position="float" id="tab1">
<label>Table 1</label>
<caption>
<p>Participants&#x2019; socio-demographic characteristics, past medical history and familiarity with stroke (<italic>n</italic>&#x2009;=&#x2009;410).</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top" colspan="2">Variables</th>
<th align="center" valign="top">Frequency (%)</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="top" colspan="3">Socio-demographic characteristics</td>
</tr>
<tr>
<td align="left" valign="top" rowspan="2">Gender</td>
<td align="left" valign="top">Male</td>
<td align="center" valign="top">215 (52.4%)</td>
</tr>
<tr>
<td align="left" valign="top">Female</td>
<td align="center" valign="top">195 (47.6%)</td>
</tr>
<tr>
<td align="left" valign="top" rowspan="3">Age groups (years)</td>
<td align="left" valign="top">Less than 30&#x2009;years</td>
<td align="center" valign="top">149 (36.3%)</td>
</tr>
<tr>
<td align="left" valign="top">Between 30&#x2013;49&#x2009;years</td>
<td align="center" valign="top">199 (48.5%)</td>
</tr>
<tr>
<td align="left" valign="top">More than 50&#x2009;years</td>
<td align="center" valign="top">62 (15.1%)</td>
</tr>
<tr>
<td align="left" valign="top" rowspan="2">Residence area</td>
<td align="left" valign="top">Urban</td>
<td align="center" valign="top">383 (93.4%)</td>
</tr>
<tr>
<td align="left" valign="top">Rural</td>
<td align="center" valign="top">27 (6.6%)</td>
</tr>
<tr>
<td align="left" valign="middle" rowspan="5">Living place</td>
<td align="left" valign="top">Khartoum (the capital)</td>
<td align="center" valign="top">294 (71.7%)</td>
</tr>
<tr>
<td align="left" valign="top">Central states</td>
<td align="center" valign="top">44 (10.7%)</td>
</tr>
<tr>
<td align="left" valign="top">Eastern states</td>
<td align="center" valign="top">17 (4.1%)</td>
</tr>
<tr>
<td align="left" valign="top">Northern states</td>
<td align="center" valign="top">29 (7.1%)</td>
</tr>
<tr>
<td align="left" valign="top">Western states</td>
<td align="center" valign="top">26 (6.3%)</td>
</tr>
<tr>
<td align="left" valign="middle" rowspan="3">Marital status</td>
<td align="left" valign="top">Single</td>
<td align="center" valign="top">181 (44.1%)</td>
</tr>
<tr>
<td align="left" valign="top">Married</td>
<td align="center" valign="top">210 (51.2%)</td>
</tr>
<tr>
<td align="left" valign="top">Divorced/Widowed</td>
<td align="center" valign="top">19 (4.6%)</td>
</tr>
<tr>
<td align="left" valign="top" rowspan="2">Education level</td>
<td align="left" valign="top">School</td>
<td align="center" valign="top">31 (7.6%)</td>
</tr>
<tr>
<td align="left" valign="top">University</td>
<td align="center" valign="top">379 (92.4%)</td>
</tr>
<tr>
<td align="left" valign="top" rowspan="2">Employment status</td>
<td align="left" valign="top">Unemployed</td>
<td align="center" valign="bottom">117 (28.5%)</td>
</tr>
<tr>
<td align="left" valign="top">Employed</td>
<td align="center" valign="bottom">293 (71.5%)</td>
</tr>
<tr>
<td align="left" valign="top" rowspan="3">Income level&#x002A;</td>
<td align="left" valign="top">Low</td>
<td align="center" valign="bottom">74 (18.0%)</td>
</tr>
<tr>
<td align="left" valign="top">Medium</td>
<td align="center" valign="bottom">156 (38.1%)</td>
</tr>
<tr>
<td align="left" valign="top">High</td>
<td align="center" valign="bottom">180 (43.9%)</td>
</tr>
<tr>
<td align="left" valign="top">Smoking status</td>
<td align="left" valign="top">Yes</td>
<td align="center" valign="bottom">158 (38.5%)</td>
</tr>
<tr>
<td align="left" valign="top" rowspan="8">Past medical history</td>
<td align="left" valign="top">Hypertension</td>
<td align="center" valign="bottom">110 (26.8%)</td>
</tr>
<tr>
<td align="left" valign="top">Diabetes Mellitus</td>
<td align="center" valign="bottom">71 (17.3%)</td>
</tr>
<tr>
<td align="left" valign="top">Dyslipidemia</td>
<td align="center" valign="bottom">81 (19.8%)</td>
</tr>
<tr>
<td align="left" valign="top">Heart diseases</td>
<td align="center" valign="bottom">57 (13.9%)</td>
</tr>
<tr>
<td align="left" valign="top">Kidney disease</td>
<td align="center" valign="bottom">34 (8.3%)</td>
</tr>
<tr>
<td align="left" valign="top">Gastro problems</td>
<td align="center" valign="bottom">61 (14.9%)</td>
</tr>
<tr>
<td align="left" valign="top">Depression</td>
<td align="center" valign="bottom">40 (9.8%)</td>
</tr>
<tr>
<td align="left" valign="top">Obesity</td>
<td align="center" valign="bottom">63 (15.4%)</td>
</tr>
<tr>
<td align="left" valign="top" rowspan="3">Familiarity with stroke</td>
<td align="left" valign="top">Ever heard of stroke</td>
<td align="center" valign="bottom">378 (92.2%)</td>
</tr>
<tr>
<td align="left" valign="top">History of stroke in the family</td>
<td align="center" valign="bottom">134 (32.7%)</td>
</tr>
<tr>
<td align="left" valign="top">Personally know someone with stroke</td>
<td align="center" valign="top">307 (74.9%)</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<p>&#x002A;Counted based on Sudanese income per month: (low income less than 20,000 Sudanese pounds, Medium income between 20,000 and 50,000 Sudanese pounds, and high income more than 50,000 Sudanese pounds).</p>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="sec14">
<title>Respondents&#x2019; general knowledge about stroke</title>
<p><xref ref-type="table" rid="tab2">Table 2</xref> shows analysis of correct responses among the participants related to general knowledge, and identification of risk factors, early symptoms, and consequences of stroke. Most participants had heard of stroke (92.2%), around three quarters (74.9%) knew about stroke if a patient developed the disease. The majority (97.3%) had at least two correct answers regarding general knowledge of stroke. However, 40.2% of the participants could identify all correct answers regarding general knowledge of stroke. In addition, most of the participants were able to correctly identify at least one stroke risk factors, early symptoms, and consequences of stroke with 96.3, 92.3, and 95.1%, respectively. However, 34.4% of the participants identified all the risk factors, 42.7% recognized all the symptoms, and more than half of the participants (53.9%) stated all possible consequences of stroke.</p>
<table-wrap position="float" id="tab2">
<label>Table 2</label>
<caption>
<p>Number of stroke risk factors, early symptoms, and consequences that were identified by the participants (<italic>n</italic>&#x2009;=&#x2009;410).</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th/>
<th/>
<th align="center" valign="top">Frequency (%)</th>
<th align="center" valign="top">Cumulative, frequency (%)</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="top" rowspan="5">Number of correct answers regarding general knowledge of stroke</td>
<td align="left" valign="top">Less than two</td>
<td align="center" valign="bottom">11 (2.7)</td>
<td align="center" valign="bottom">11 (2.7)</td>
</tr>
<tr>
<td align="left" valign="top">Two</td>
<td align="center" valign="bottom">26 (6.3)</td>
<td align="center" valign="bottom">37 (9.0)</td>
</tr>
<tr>
<td align="left" valign="top">Three</td>
<td align="center" valign="bottom">55 (13.4)</td>
<td align="center" valign="bottom">92 (22.4)</td>
</tr>
<tr>
<td align="left" valign="top">Four</td>
<td align="center" valign="bottom">153 (37.3)</td>
<td align="center" valign="bottom">245 (59.8)</td>
</tr>
<tr>
<td align="left" valign="top">Five</td>
<td align="center" valign="bottom">165 (40.2)</td>
<td align="center" valign="bottom">410 (100)</td>
</tr>
<tr>
<td align="left" valign="top" rowspan="11">Number of identified risk factors of stroke</td>
<td align="left" valign="top">Zero</td>
<td align="center" valign="bottom">15 (3.7)</td>
<td align="center" valign="bottom">15 (3.7)</td>
</tr>
<tr>
<td align="left" valign="top">One</td>
<td align="center" valign="bottom">8 (2.0)</td>
<td align="center" valign="bottom">23 (5.6)</td>
</tr>
<tr>
<td align="left" valign="top">Two</td>
<td align="center" valign="bottom">3 (0.7)</td>
<td align="center" valign="bottom">26 (6.3)</td>
</tr>
<tr>
<td align="left" valign="top">Three</td>
<td align="center" valign="bottom">10 (2.4)</td>
<td align="center" valign="bottom">36 (8.8)</td>
</tr>
<tr>
<td align="left" valign="top">Four</td>
<td align="center" valign="bottom">14 (3.4)</td>
<td align="center" valign="bottom">50 (12.2)</td>
</tr>
<tr>
<td align="left" valign="top">Five</td>
<td align="center" valign="bottom">20 (4.9)</td>
<td align="center" valign="bottom">70 (17.1)</td>
</tr>
<tr>
<td align="left" valign="top">Six</td>
<td align="center" valign="bottom">32 (7.8)</td>
<td align="center" valign="bottom">102 (24.9)</td>
</tr>
<tr>
<td align="left" valign="top">Seven</td>
<td align="center" valign="bottom">41 (10.0)</td>
<td align="center" valign="bottom">143 (34.9)</td>
</tr>
<tr>
<td align="left" valign="top">Eight</td>
<td align="center" valign="bottom">56 (13.7)</td>
<td align="center" valign="bottom">199 (48.5)</td>
</tr>
<tr>
<td align="left" valign="top">Nine</td>
<td align="center" valign="bottom">70 (17.1)</td>
<td align="center" valign="bottom">269 (65.6)</td>
</tr>
<tr>
<td align="left" valign="top">Ten</td>
<td align="center" valign="bottom">141 (34.4)</td>
<td align="center" valign="bottom">410 (100)</td>
</tr>
<tr>
<td align="left" valign="top" rowspan="8">Number of identified early symptoms of stroke</td>
<td align="left" valign="top">Zero</td>
<td align="center" valign="bottom">31 (7.6)</td>
<td align="center" valign="bottom">31 (7.6)</td>
</tr>
<tr>
<td align="left" valign="top">One</td>
<td align="center" valign="bottom">5 (1.2)</td>
<td align="center" valign="bottom">36 (8.8)</td>
</tr>
<tr>
<td align="left" valign="top">Two</td>
<td align="center" valign="bottom">21 (5.1)</td>
<td align="center" valign="bottom">57 (13.9)</td>
</tr>
<tr>
<td align="left" valign="top">Three</td>
<td align="center" valign="bottom">27 (6.6)</td>
<td align="center" valign="bottom">84 (20.5)</td>
</tr>
<tr>
<td align="left" valign="top">Four</td>
<td align="center" valign="bottom">30 (7.3)</td>
<td align="center" valign="bottom">114 (27.8)</td>
</tr>
<tr>
<td align="left" valign="top">Five</td>
<td align="center" valign="bottom">57 (13.9)</td>
<td align="center" valign="bottom">171 (41.7)</td>
</tr>
<tr>
<td align="left" valign="top">Six</td>
<td align="center" valign="bottom">64 (15.6)</td>
<td align="center" valign="bottom">235 (57.3)</td>
</tr>
<tr>
<td align="left" valign="top">Seven</td>
<td align="center" valign="bottom">175 (42.7)</td>
<td align="center" valign="bottom">410 (100)</td>
</tr>
<tr>
<td align="left" valign="top" rowspan="6">Number of identified consequences of stroke</td>
<td align="left" valign="top">Zero</td>
<td align="center" valign="bottom">20 (4.9)</td>
<td align="center" valign="bottom">20 (4.9)</td>
</tr>
<tr>
<td align="left" valign="top">One</td>
<td align="center" valign="bottom">5 (1.2)</td>
<td align="center" valign="bottom">25 (6.1)</td>
</tr>
<tr>
<td align="left" valign="top">Two</td>
<td align="center" valign="bottom">21 (5.1)</td>
<td align="center" valign="bottom">46 (11.2)</td>
</tr>
<tr>
<td align="left" valign="top">Three</td>
<td align="center" valign="bottom">56 (13.7)</td>
<td align="center" valign="bottom">102 (24.9)</td>
</tr>
<tr>
<td align="left" valign="top">Four</td>
<td align="center" valign="bottom">87 (21.2)</td>
<td align="center" valign="bottom">189 (46.1)</td>
</tr>
<tr>
<td align="left" valign="top">Five</td>
<td align="center" valign="bottom">221 (53.9)</td>
<td align="center" valign="bottom">410 (100)</td>
</tr>
</tbody>
</table>
</table-wrap>
<p>Most participants (86.3%) stated that they would transport patients with suspected stroke (based on symptoms) to hospital, while 7.3% did not know what to do in case of stroke. In general, when people were asked about rating their knowledge about stroke, more than three-quarters of the participants (78.5%) reported they had general knowledge about the stroke, while the rest (21.5%) either reported knowing the name of the disease or having no knowledge of the disease. Finally, most of the participants (94.6%) would like more information about stroke.</p>
<p><xref ref-type="fig" rid="fig1">Figure 1</xref> presents the knowledge of Sudanese participants related to different issues about the stroke. For general stroke knowledge (<xref ref-type="fig" rid="fig1">Figure 1A</xref>), the majority of the participants were aware that stroke is not a contagious disease (96.8%), it is affecting the brain (93.2%), and it can be preventable (83.4%). For early symptoms of stroke (<xref ref-type="fig" rid="fig1">Figure 1B</xref>), most of the respondents answered that the two main early symptoms of stroke were sudden difficulty speaking, and weakness, numbness, and/or tingling of arm and leg, with 84.9, and 84.4%, respectively. For the stroke related risk factors (<xref ref-type="fig" rid="fig1">Figures1C</xref>), most of the participants (90.2%) believed that hypertension was the most common risk factor of stroke, followed by psychological stress (83.9%) and obesity (82.4%). Finally, knowledge related to consequences of stroke (<xref ref-type="fig" rid="fig1">Figure 1D</xref>), most of the participants reported that stroke can cause movement/functional problems and long-term disabilities with 91.7, and 91.2%, respectively.</p>
<fig position="float" id="fig1">
<label>Figure 1</label>
<caption>
<p>Knowledge of Sudanese participants (<italic>n</italic>&#x2009;=&#x2009;410) related to <bold>(A)</bold> Stroke, <bold>(B)</bold> Early symptoms of stroke, <bold>(C)</bold> Risk factors related to stroke, and <bold>(D)</bold> Consequences of stroke.</p>
</caption>
<graphic xlink:href="fpubh-12-1362979-g001.tif"/>
</fig>
<p>Although the sample showed a variable level of knowledge about stroke, only females were significantly more able to list at least one correct risk factors related to stroke compared to males (99.5% versus 93.5%, <italic>p</italic>&#x2009;=&#x2009;0.001). There was no other significant relationships between the sociodemographic characteristics or past medical history with risk factors, early symptoms and consequences of stroke (<xref ref-type="table" rid="tab3">Table 3</xref>).</p>
<table-wrap position="float" id="tab3">
<label>Table 3</label>
<caption>
<p>Association of risk factors, early symptoms and consequences of stroke with the sociodemographic characteristics and past medical history (<italic>n</italic>&#x2009;=&#x2009;410).</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="center" valign="top" colspan="2" rowspan="2">Variables</th>
<th align="center" valign="top" colspan="3">Risk factor(s) identified (&#x2265;1)</th>
<th align="center" valign="top" colspan="3">Early symptom(s) identified (&#x2265;1)</th>
<th align="center" valign="top" colspan="3">Consequence(s) identified (&#x2265;1)</th>
</tr>
<tr>
<th align="center" valign="top">Yes (<italic>n</italic>&#x2009;=&#x2009;395)<break/><italic>n</italic> (%)</th>
<th align="center" valign="top">No (<italic>n</italic>&#x2009;=&#x2009;15)<break/><italic>n</italic> (%)</th>
<th align="center" valign="top"><italic>p</italic>-value</th>
<th align="center" valign="top">Yes (<italic>n</italic>&#x2009;=&#x2009;379)<break/><italic>n</italic> (%)</th>
<th align="center" valign="top">No (<italic>n</italic>&#x2009;=&#x2009;31)<break/><italic>n</italic> (%)</th>
<th align="center" valign="top"><italic>p</italic>-value</th>
<th align="center" valign="top">Yes (<italic>n</italic>&#x2009;=&#x2009;390)<break/><italic>n</italic> (%)</th>
<th align="center" valign="top">No (<italic>n</italic>&#x2009;=&#x2009;20)<break/><italic>n</italic> (%)</th>
<th align="center" valign="top"><italic>p</italic>-value</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="middle" colspan="11">Socio-demographic characteristics</td>
</tr>
<tr>
<td align="left" valign="middle" rowspan="2">Gender</td>
<td align="left" valign="top">Male</td>
<td align="center" valign="middle">201 (93.5)</td>
<td align="center" valign="middle">14 (6.5)</td>
<td align="center" valign="middle" rowspan="2">
<bold>0.001</bold>
</td>
<td align="center" valign="middle">196 (91.2)</td>
<td align="center" valign="middle">19 (8.8)</td>
<td align="center" valign="middle" rowspan="2">0.352</td>
<td align="center" valign="middle">201 (93.5)</td>
<td align="center" valign="middle">14 (6.5)</td>
<td align="center" valign="middle" rowspan="2">0.115</td>
</tr>
<tr>
<td align="left" valign="top">Female</td>
<td align="center" valign="middle">194 (99.5)</td>
<td align="center" valign="middle">1 (0.5)</td>
<td align="center" valign="middle">183 (93.8)</td>
<td align="center" valign="middle">12 (6.2)</td>
<td align="center" valign="middle">189 (96.9)</td>
<td align="center" valign="middle">6 (3.1)</td>
</tr>
<tr>
<td align="left" valign="top" rowspan="3">Age groups (years)</td>
<td align="left" valign="top">Less than 30&#x2009;years</td>
<td align="center" valign="middle">146 (98.0)</td>
<td align="center" valign="middle">3 (2.0)</td>
<td align="center" valign="middle" rowspan="3">0.276</td>
<td align="center" valign="middle">142 (95.3)</td>
<td align="center" valign="middle">7 (4.7)</td>
<td align="center" valign="middle" rowspan="3">0.095</td>
<td align="center" valign="middle">143 (96.0)</td>
<td align="center" valign="middle">6 (4.0)</td>
<td align="center" valign="middle" rowspan="3">0.604</td>
</tr>
<tr>
<td align="left" valign="top">Between 30 and 49 years</td>
<td align="center" valign="middle">191 (96.0)</td>
<td align="center" valign="middle">8 (4.0)</td>
<td align="center" valign="middle">178 (89.4)</td>
<td align="center" valign="middle">21 (10.6)</td>
<td align="center" valign="middle">187 (94.0)</td>
<td align="center" valign="middle">12 (6.0)</td>
</tr>
<tr>
<td align="left" valign="top">More than 50&#x2009;years</td>
<td align="center" valign="middle">58 (93.5)</td>
<td align="center" valign="middle">4 (6.5)</td>
<td align="center" valign="middle">59 (95.2)</td>
<td align="center" valign="middle">3 (4.8)</td>
<td align="center" valign="middle">60 (96.8)</td>
<td align="center" valign="middle">2 (3.2)</td>
</tr>
<tr>
<td align="left" valign="top" rowspan="2">Residence area</td>
<td align="left" valign="top">Urban</td>
<td align="center" valign="middle">370 (96.6)</td>
<td align="center" valign="middle">13 (3.4)</td>
<td align="center" valign="middle" rowspan="2">0.259</td>
<td align="center" valign="middle">354 (92.4)</td>
<td align="center" valign="middle">29 (7.6)</td>
<td align="center" valign="middle" rowspan="2">1</td>
<td align="center" valign="middle">305 (95.3)</td>
<td align="center" valign="middle">18 (4.7)</td>
<td align="center" valign="middle" rowspan="2">0.633</td>
</tr>
<tr>
<td align="left" valign="top">Rural</td>
<td align="center" valign="middle">25 (92.6)</td>
<td align="center" valign="middle">2 (7.4)</td>
<td align="center" valign="middle">25 (92.6)</td>
<td align="center" valign="middle">2 (7.4)</td>
<td align="center" valign="middle">25 (92.6)</td>
<td align="center" valign="middle">2 (7.4)</td>
</tr>
<tr>
<td align="left" valign="middle" rowspan="3">Marital status</td>
<td align="left" valign="top">Single</td>
<td align="center" valign="middle">174 (96.1)</td>
<td align="center" valign="middle">7 (3.9)</td>
<td align="center" valign="middle" rowspan="3">1</td>
<td align="center" valign="middle">166 (91.7)</td>
<td align="center" valign="middle">15 (8.3)</td>
<td align="center" valign="middle" rowspan="3">0.968</td>
<td align="center" valign="middle">171 (94.5)</td>
<td align="center" valign="middle">10 (5.5)</td>
<td align="center" valign="middle" rowspan="3">0.932</td>
</tr>
<tr>
<td align="left" valign="top">Married</td>
<td align="center" valign="middle">202 (96.2)</td>
<td align="center" valign="middle">8 (3.8)</td>
<td align="center" valign="middle">194 (92.4)</td>
<td align="center" valign="middle">16 (7.6)</td>
<td align="center" valign="middle">200 (95.2)</td>
<td align="center" valign="middle">10 (4.8)</td>
</tr>
<tr>
<td align="left" valign="top">Divorced/Widowed</td>
<td align="center" valign="middle">19 (100)</td>
<td align="center" valign="middle">0 (0)</td>
<td align="center" valign="middle">19 (100)</td>
<td align="center" valign="middle">0 (0)</td>
<td align="center" valign="middle">19 (100)</td>
<td align="center" valign="middle">0 (0)</td>
</tr>
<tr>
<td align="left" valign="top" rowspan="2">Educational level</td>
<td align="left" valign="top">School</td>
<td align="center" valign="middle">29 (93.5)</td>
<td align="center" valign="middle">2 (6.5)</td>
<td align="center" valign="middle" rowspan="2">0.316</td>
<td align="center" valign="middle">30 (96.8)</td>
<td align="center" valign="middle">1 (3.2)</td>
<td align="center" valign="middle" rowspan="2">0.495</td>
<td align="center" valign="middle">30 (96.8)</td>
<td align="center" valign="middle">1 (3.2)</td>
<td align="center" valign="middle" rowspan="2">1</td>
</tr>
<tr>
<td align="left" valign="top">University</td>
<td align="center" valign="middle">336 (96.6)</td>
<td align="center" valign="middle">13 (3.4)</td>
<td align="center" valign="middle">349 (92.1)</td>
<td align="center" valign="middle">30 (7.9)</td>
<td align="center" valign="middle">360 (95.0)</td>
<td align="center" valign="middle">19 (5.0)</td>
</tr>
<tr>
<td align="left" valign="top" rowspan="2">Employment status</td>
<td align="left" valign="top">Unemployed</td>
<td align="center" valign="middle">115 (98.3)</td>
<td align="center" valign="middle">2 (1.7)</td>
<td align="center" valign="middle" rowspan="2">0.250</td>
<td align="center" valign="middle">109 (93.2)</td>
<td align="center" valign="middle">8 (6.8)</td>
<td align="center" valign="middle" rowspan="2">0.838</td>
<td align="center" valign="middle">112 (95.7)</td>
<td align="center" valign="middle">5 (4.3)</td>
<td align="center" valign="middle" rowspan="2">0.805</td>
</tr>
<tr>
<td align="left" valign="top">Employed</td>
<td align="center" valign="middle">280 (95.6)</td>
<td align="center" valign="middle">13 (4.4)</td>
<td align="center" valign="middle">270 (92.2)</td>
<td align="center" valign="middle">23 (7.8)</td>
<td align="center" valign="middle">278 (94.9)</td>
<td align="center" valign="middle">15 (5.1)</td>
</tr>
<tr>
<td align="left" valign="top" rowspan="3">Income level</td>
<td align="left" valign="top">Low</td>
<td align="center" valign="middle">72 (97.3)</td>
<td align="center" valign="middle">2 (2.7)</td>
<td align="center" valign="middle" rowspan="3">0.889</td>
<td align="center" valign="middle">71 (95.9)</td>
<td align="center" valign="middle">3 (4.1)</td>
<td align="center" valign="middle" rowspan="3">0.400</td>
<td align="center" valign="middle">71 (95.9)</td>
<td align="center" valign="middle">3 (4.1)</td>
<td align="center" valign="middle" rowspan="3">0.515</td>
</tr>
<tr>
<td align="left" valign="top">Medium</td>
<td align="center" valign="middle">150 (96.2)</td>
<td align="center" valign="middle">6 (3.8)</td>
<td align="center" valign="middle">144 (92.3)</td>
<td align="center" valign="middle">12 (7.7)</td>
<td align="center" valign="middle">146 (93.6)</td>
<td align="center" valign="middle">10 (6.4)</td>
</tr>
<tr>
<td align="left" valign="top">High</td>
<td align="center" valign="middle">173 (96.1)</td>
<td align="center" valign="middle">7 (3.9)</td>
<td align="center" valign="middle">164 (91.1)</td>
<td align="center" valign="middle">16 (8.9)</td>
<td align="center" valign="middle">173 (96.1)</td>
<td align="center" valign="middle">7 (3.9)</td>
</tr>
<tr>
<td align="left" valign="top" rowspan="2">Smoking status</td>
<td align="left" valign="top">No</td>
<td align="center" valign="middle">244 (96.8)</td>
<td align="center" valign="middle">8 (3.2)</td>
<td align="center" valign="middle" rowspan="2">0.592</td>
<td align="center" valign="middle">230 (91.3)</td>
<td align="center" valign="middle">22 (8.7)</td>
<td align="center" valign="middle" rowspan="2">0.338</td>
<td align="center" valign="middle">240 (95.2)</td>
<td align="center" valign="middle">12 (4.8)</td>
<td align="center" valign="middle" rowspan="2">1</td>
</tr>
<tr>
<td align="left" valign="top">Yes</td>
<td align="center" valign="middle">151 (95.6)</td>
<td align="center" valign="middle">7 (4.4)</td>
<td align="center" valign="middle">149 (94.3)</td>
<td align="center" valign="middle">9 (5.7)</td>
<td align="center" valign="middle">150 (94.9)</td>
<td align="center" valign="middle">8 (5.1)</td>
</tr>
<tr>
<td align="left" valign="middle" colspan="11">Past medical history</td>
</tr>
<tr>
<td align="left" valign="top" rowspan="2">Hypertension</td>
<td align="left" valign="top">No</td>
<td align="center" valign="middle">287 (95.7)</td>
<td align="center" valign="middle">13 (4.3)</td>
<td align="center" valign="middle" rowspan="2">0.373</td>
<td align="center" valign="middle">275 (91.7)</td>
<td align="center" valign="middle">25 (8.3)</td>
<td align="center" valign="middle" rowspan="2">0.403</td>
<td align="center" valign="middle">284 (94.7)</td>
<td align="center" valign="middle">16 (5.3)</td>
<td align="center" valign="middle" rowspan="2">1</td>
</tr>
<tr>
<td align="left" valign="top">Yes</td>
<td align="center" valign="middle">108 (98.2)</td>
<td align="center" valign="middle">2 (1.8)</td>
<td align="center" valign="middle">104 (94.5)</td>
<td align="center" valign="middle">6 (5.5)</td>
<td align="center" valign="middle">106 (96.4)</td>
<td align="center" valign="middle">4 (3.6)</td>
</tr>
<tr>
<td align="left" valign="top" rowspan="2">Diabetes Mellitus</td>
<td align="left" valign="top">No</td>
<td align="center" valign="middle">325 (95.9)</td>
<td align="center" valign="middle">14 (4.1)</td>
<td align="center" valign="middle" rowspan="2">0.532</td>
<td align="center" valign="middle">312 (92.0)</td>
<td align="center" valign="middle">27 (8.0)</td>
<td align="center" valign="middle" rowspan="2">0.610</td>
<td align="center" valign="middle">323 (95.3)</td>
<td align="center" valign="middle">16 (4.7)</td>
<td align="center" valign="middle" rowspan="2">1</td>
</tr>
<tr>
<td align="left" valign="top">Yes</td>
<td align="center" valign="middle">70 (98.6)</td>
<td align="center" valign="middle">1 (1.4)</td>
<td align="center" valign="middle">67 (94.4)</td>
<td align="center" valign="middle">4 (5.6)</td>
<td align="center" valign="middle">67 (94.4)</td>
<td align="center" valign="middle">4 (5.6)</td>
</tr>
<tr>
<td align="left" valign="top" rowspan="2">Dyslipidemia</td>
<td align="left" valign="top">No</td>
<td align="center" valign="middle">315 (95.7)</td>
<td align="center" valign="middle">14 (4.3)</td>
<td align="center" valign="middle" rowspan="2">0.322</td>
<td align="center" valign="middle">301 (91.5)</td>
<td align="center" valign="middle">28 (8.5)</td>
<td align="center" valign="middle" rowspan="2">0.166</td>
<td align="center" valign="middle">312 (94.8)</td>
<td align="center" valign="middle">17 (5.2)</td>
<td align="center" valign="middle" rowspan="2">0.776</td>
</tr>
<tr>
<td align="left" valign="top">Yes</td>
<td align="center" valign="middle">80 (98.8)</td>
<td align="center" valign="middle">1 (1.2)</td>
<td align="center" valign="middle">78 (96.3)</td>
<td align="center" valign="middle">3 (3.7)</td>
<td align="center" valign="middle">78 (96.3)</td>
<td align="center" valign="middle">3 (3.7)</td>
</tr>
<tr>
<td align="left" valign="top" rowspan="2">Heart diseases</td>
<td align="left" valign="top">No</td>
<td align="center" valign="middle">339 (96.0)</td>
<td align="center" valign="middle">14 (4.0)</td>
<td align="center" valign="middle" rowspan="2">0.705</td>
<td align="center" valign="middle">324 (91.8)</td>
<td align="center" valign="middle">29 (8.2)</td>
<td align="center" valign="middle" rowspan="2">0.285</td>
<td align="center" valign="middle">334 (94.6)</td>
<td align="center" valign="middle">19 (5.4)</td>
<td align="center" valign="middle" rowspan="2">0.334</td>
</tr>
<tr>
<td align="left" valign="top">Yes</td>
<td align="center" valign="middle">56 (98.2)</td>
<td align="center" valign="middle">1 (1.8)</td>
<td align="center" valign="middle">55 (96.5)</td>
<td align="center" valign="middle">2 (3.5)</td>
<td align="center" valign="middle">56 (98.2)</td>
<td align="center" valign="middle">1 (1.8)</td>
</tr>
<tr>
<td align="left" valign="top" rowspan="2">Kidney disease</td>
<td align="left" valign="top">No</td>
<td align="center" valign="middle">361 (96.0)</td>
<td align="center" valign="middle">15 (4.0)</td>
<td align="center" valign="top" rowspan="2">0.625</td>
<td align="center" valign="top">345 (91.8)</td>
<td align="center" valign="top">31 (8.2)</td>
<td align="center" valign="top" rowspan="2">0.095</td>
<td align="center" valign="top">356 (94.7)</td>
<td align="center" valign="top">20 (5.3)</td>
<td align="center" valign="top" rowspan="2">0.394</td>
</tr>
<tr>
<td align="left" valign="top">Yes</td>
<td align="center" valign="top">34 (100)</td>
<td align="center" valign="top">0 (0)</td>
<td align="center" valign="top">34 (100)</td>
<td align="center" valign="top">0 (0)</td>
<td align="center" valign="top">34 (100)</td>
<td align="center" valign="top">0 (0)</td>
</tr>
<tr>
<td align="left" valign="top" rowspan="2">Gastro problems</td>
<td align="left" valign="top">No</td>
<td align="center" valign="top">335 (96.0)</td>
<td align="center" valign="top">14 (4.0)</td>
<td align="center" valign="top" rowspan="2">0.709</td>
<td align="center" valign="top">322 (92.3)</td>
<td align="center" valign="top">27 (7.7)</td>
<td align="center" valign="top" rowspan="2">1</td>
<td align="center" valign="top">331 (94.8)</td>
<td align="center" valign="top">18 (5.2)</td>
<td align="center" valign="top" rowspan="2">0.751</td>
</tr>
<tr>
<td align="left" valign="top">Yes</td>
<td align="center" valign="top">60 (98.4)</td>
<td align="center" valign="top">1 (1.6)</td>
<td align="center" valign="top">57 (93.4)</td>
<td align="center" valign="top">4 (6.6)</td>
<td align="center" valign="top">59 (96.7)</td>
<td align="center" valign="top">2 (3.3)</td>
</tr>
<tr>
<td align="left" valign="top" rowspan="2">Depression</td>
<td align="left" valign="top">No</td>
<td align="center" valign="top">358 (96.8)</td>
<td align="center" valign="top">12 (3.2)</td>
<td align="center" valign="top" rowspan="2">0.172</td>
<td align="center" valign="top">344 (93.0)</td>
<td align="center" valign="top">2.6 (7.0)</td>
<td align="center" valign="top" rowspan="2">0.209</td>
<td align="center" valign="top">353 (95.4)</td>
<td align="center" valign="top">17 (4.6)</td>
<td align="center" valign="top" rowspan="2">0.430</td>
</tr>
<tr>
<td align="left" valign="top">Yes</td>
<td align="center" valign="top">37 (92.5)</td>
<td align="center" valign="top">3 (7.5)</td>
<td align="center" valign="top">35 (87.5)</td>
<td align="center" valign="top">5 (12.5)</td>
<td align="center" valign="top">37 (92.5)</td>
<td align="center" valign="top">3 (7.5)</td>
</tr>
<tr>
<td align="left" valign="top" rowspan="2">Obesity</td>
<td align="left" valign="top">No</td>
<td align="center" valign="top">332 (95.7)</td>
<td align="center" valign="top">15 (4.3)</td>
<td align="center" valign="top" rowspan="2">0.142</td>
<td align="center" valign="top">319 (91.9)</td>
<td align="center" valign="top">28 (8.1)</td>
<td align="center" valign="top" rowspan="2">0.448</td>
<td align="center" valign="top">327 (94.2)</td>
<td align="center" valign="top">20 (5.8)</td>
<td align="center" valign="top" rowspan="2">0.054</td>
</tr>
<tr>
<td align="left" valign="top">Yes</td>
<td align="center" valign="top">63 (100)</td>
<td align="center" valign="top">0 (0)</td>
<td align="center" valign="top">60 (95.2)</td>
<td align="center" valign="top">3 (4.8)</td>
<td align="center" valign="top">63 (100)</td>
<td align="center" valign="top">0 (0)</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<p>Fisher&#x2019;s exact test was used when the cell counts was less than 5.Numbers in bold indicate significant <italic>p</italic>-values.</p>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="sec15">
<title>Sources of information</title>
<p><xref ref-type="fig" rid="fig2">Figure 2</xref> lists the sources of stroke information mentioned by respondents. The main source of information was internet/social media (79.3%), followed by healthcare professionals (60.0%), family and relatives (54.9%).</p>
<fig position="float" id="fig2">
<label>Figure 2</label>
<caption>
<p>Sources of information about stroke as reported by Sudanese respondents (<italic>n</italic>&#x2009;=&#x2009;410).</p>
</caption>
<graphic xlink:href="fpubh-12-1362979-g002.tif"/>
</fig>
</sec>
<sec id="sec16">
<title>Respondents&#x2019; attitudes about stroke</title>
<p>The majority of participants believed that stroke was a serious disease, and that patient&#x2019;s life would be affected after stroke of 99.5 and 98.8%, respectively. Furthermore, the majority (96.6%) believed that family care was helpful for early recovery of patients with stroke after leaving the hospitals. However, more than a third of participants (34.4%) stated that stroke disease cannot lead to happy life of patients.</p>
</sec>
<sec id="sec17">
<title>Bivariate analysis associated with response to somebody with symptoms of stroke</title>
<p>Most of the participants (86.3%) reported that the first action in response to patients with stroke symptoms would be to take the patient directly to a hospital. There were no significant relationships between all sociodemographic characteristics, or past medical history with respondents reactions to a patient with stroke (<xref ref-type="table" rid="tab4">Table 4</xref>).</p>
<table-wrap position="float" id="tab4">
<label>Table 4</label>
<caption>
<p>Association of taking a patient who is experiencing stroke to the hospital with sociodemographic characteristics, and past medical history (<italic>n</italic>&#x2009;=&#x2009;410).</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="center" valign="top" colspan="2" rowspan="2">Variables</th>
<th align="center" valign="top" colspan="3">Taking a patient who is experiencing stroke to the hospital</th>
</tr>
<tr>
<th align="center" valign="top">Yes (<italic>n</italic>&#x2009;=&#x2009;354)<break/><italic>n</italic> (%)</th>
<th align="center" valign="top">No (<italic>n</italic>&#x2009;=&#x2009;56)<break/><italic>n</italic> (%)</th>
<th align="center" valign="top"><italic>p</italic>-value</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="top" colspan="5">Sociodemographic characteristics</td>
</tr>
<tr>
<td align="left" valign="top" rowspan="2">Gender</td>
<td align="left" valign="top">Male</td>
<td align="center" valign="bottom">181 (84.2)</td>
<td align="center" valign="bottom">34 (15.8)</td>
<td align="center" valign="middle" rowspan="2">0.197</td>
</tr>
<tr>
<td align="left" valign="top">Female</td>
<td align="center" valign="bottom">173 (88.7)</td>
<td align="center" valign="bottom">22 (11.3)</td>
</tr>
<tr>
<td align="left" valign="top" rowspan="3">Age group (years)</td>
<td align="left" valign="top">Less than 30&#x2009;years</td>
<td align="center" valign="bottom">133 (89.3)</td>
<td align="center" valign="bottom">16 (10.7)</td>
<td align="center" valign="middle" rowspan="3">0.255</td>
</tr>
<tr>
<td align="left" valign="top">Between 30 and 49&#x2009;years</td>
<td align="center" valign="bottom">166 (83.4)</td>
<td align="center" valign="bottom">33 (16.6)</td>
</tr>
<tr>
<td align="left" valign="top">More than 50&#x2009;years</td>
<td align="center" valign="bottom">55 (88.7)</td>
<td align="center" valign="bottom">7 (11.3)</td>
</tr>
<tr>
<td align="left" valign="top" rowspan="2">Residence area</td>
<td align="left" valign="top">Urban</td>
<td align="center" valign="bottom">332 (86.7)</td>
<td align="center" valign="bottom">51 (13.3)</td>
<td align="center" valign="middle" rowspan="2">0.349</td>
</tr>
<tr>
<td align="left" valign="top">Rural</td>
<td align="center" valign="bottom">22 (81.5)</td>
<td align="center" valign="bottom">5 (18.5)</td>
</tr>
<tr>
<td align="left" valign="top" rowspan="3">Marital status</td>
<td align="left" valign="top">Single</td>
<td align="center" valign="bottom">157 (86.7)</td>
<td align="center" valign="bottom">24 (13.3)</td>
<td align="center" valign="middle" rowspan="3">0.853</td>
</tr>
<tr>
<td align="left" valign="top">Married</td>
<td align="center" valign="bottom">179 (85.2)</td>
<td align="center" valign="bottom">31 (14.8)</td>
</tr>
<tr>
<td align="left" valign="top">Divorced/Widowed</td>
<td align="center" valign="top">18 (94.7)</td>
<td align="center" valign="top">1 (5.3)</td>
</tr>
<tr>
<td align="left" valign="top" rowspan="2">Educational level</td>
<td align="left" valign="top">School</td>
<td align="center" valign="bottom">26 (83.9)</td>
<td align="center" valign="bottom">5 (16.1)</td>
<td align="center" valign="middle" rowspan="2">0.595</td>
</tr>
<tr>
<td align="left" valign="top">University</td>
<td align="center" valign="bottom">328 (86.5)</td>
<td align="center" valign="bottom">51 (3.5)</td>
</tr>
<tr>
<td align="left" valign="top" rowspan="2">Employment status</td>
<td align="left" valign="top">Unemployed</td>
<td align="center" valign="bottom">101 (86.3)</td>
<td align="center" valign="bottom">16 (13.7)</td>
<td align="center" valign="middle" rowspan="2">1</td>
</tr>
<tr>
<td align="left" valign="top">Employed</td>
<td align="center" valign="bottom">253 (86.3)</td>
<td align="center" valign="bottom">40 (13.7)</td>
</tr>
<tr>
<td align="left" valign="top" rowspan="3">Income level</td>
<td align="left" valign="top">Low</td>
<td align="center" valign="bottom">64 (86.5)</td>
<td align="center" valign="bottom">10 (13.5)</td>
<td align="center" valign="middle" rowspan="3">0.688</td>
</tr>
<tr>
<td align="left" valign="top">Medium</td>
<td align="center" valign="bottom">132 (84.6)</td>
<td align="center" valign="bottom">24 (15.4)</td>
</tr>
<tr>
<td align="left" valign="top">High</td>
<td align="center" valign="bottom">158 (87.8)</td>
<td align="center" valign="bottom">22 (12.2)</td>
</tr>
<tr>
<td align="left" valign="top" rowspan="2">Smoking status</td>
<td align="left" valign="top">No</td>
<td align="center" valign="bottom">215 (85.3)</td>
<td align="center" valign="bottom">37 (14.7)</td>
<td align="center" valign="middle" rowspan="2">0.465</td>
</tr>
<tr>
<td align="left" valign="top">Yes</td>
<td align="center" valign="bottom">139 (88.0)</td>
<td align="center" valign="bottom">19 (12.0)</td>
</tr>
<tr>
<td align="left" valign="middle" colspan="5">Past medical history</td>
</tr>
<tr>
<td align="left" valign="top" rowspan="2">Hypertension</td>
<td align="left" valign="top">No</td>
<td align="center" valign="bottom">258 (86.0)</td>
<td align="center" valign="bottom">42 (14.0)</td>
<td align="center" valign="middle" rowspan="2">0.751</td>
</tr>
<tr>
<td align="left" valign="top">Yes</td>
<td align="center" valign="bottom">96 (87.3)</td>
<td align="center" valign="bottom">14 (12.7)</td>
</tr>
<tr>
<td align="left" valign="top" rowspan="2">Diabetes mellitus</td>
<td align="left" valign="top">No</td>
<td align="center" valign="bottom">292 (86.1)</td>
<td align="center" valign="bottom">47 (13.9)</td>
<td align="center" valign="middle" rowspan="2">0.852</td>
</tr>
<tr>
<td align="left" valign="top">Yes</td>
<td align="center" valign="bottom">62 (87.3)</td>
<td align="center" valign="bottom">9 (12.7)</td>
</tr>
<tr>
<td align="left" valign="top" rowspan="2">Dyslipidemia</td>
<td align="left" valign="top">No</td>
<td align="center" valign="bottom">258 (86.6)</td>
<td align="center" valign="bottom">44 (13.4)</td>
<td align="center" valign="middle" rowspan="2">0.857</td>
</tr>
<tr>
<td align="left" valign="top">Yes</td>
<td align="center" valign="bottom">69 (85.2)</td>
<td align="center" valign="bottom">12 (14.8)</td>
</tr>
<tr>
<td align="left" valign="top" rowspan="2">Heart diseases</td>
<td align="left" valign="top">No</td>
<td align="center" valign="bottom">303 (85.8)</td>
<td align="center" valign="bottom">50 (14.2)</td>
<td align="center" valign="middle" rowspan="2">0.539</td>
</tr>
<tr>
<td align="left" valign="top">Yes</td>
<td align="center" valign="bottom">51 (89.5)</td>
<td align="center" valign="bottom">6 (10.5)</td>
</tr>
<tr>
<td align="left" valign="top" rowspan="2">Kidney disease</td>
<td align="left" valign="top">No</td>
<td align="center" valign="bottom">322 (85.6)</td>
<td align="center" valign="bottom">54 (14.4)</td>
<td align="center" valign="middle" rowspan="2">0.202</td>
</tr>
<tr>
<td align="left" valign="top">Yes</td>
<td align="center" valign="bottom">32 (94.1)</td>
<td align="center" valign="bottom">2 (5.9)</td>
</tr>
<tr>
<td align="left" valign="top" rowspan="2">Gastro problems</td>
<td align="left" valign="top">No</td>
<td align="center" valign="middle">52 (85.2)</td>
<td align="center" valign="middle">47 (13.5)</td>
<td align="center" valign="middle" rowspan="2">0.840</td>
</tr>
<tr>
<td align="left" valign="top">Yes</td>
<td align="center" valign="middle">52 (85.2)</td>
<td align="center" valign="middle">9 (14.8)</td>
</tr>
<tr>
<td align="left" valign="top" rowspan="2">Depression</td>
<td align="left" valign="top">No</td>
<td align="center" valign="middle">318 (85.9)</td>
<td align="center" valign="middle">52 (14.1)</td>
<td align="center" valign="middle" rowspan="2">0.630</td>
</tr>
<tr>
<td align="left" valign="top">Yes</td>
<td align="center" valign="middle">36 (90.0)</td>
<td align="center" valign="middle">4 (10.0)</td>
</tr>
<tr>
<td align="left" valign="top" rowspan="2">Obesity</td>
<td align="left" valign="top">No</td>
<td align="center" valign="middle">297 (85.6)</td>
<td align="center" valign="middle">50 (14.4)</td>
<td align="center" valign="middle" rowspan="2">0.329</td>
</tr>
<tr>
<td align="left" valign="top">Yes</td>
<td align="center" valign="middle">57 (90.5)</td>
<td align="center" valign="middle">6 (9.5)</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<p>Fisher&#x2019;s exact test was used when the cell counts was less than 5.</p>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="sec18">
<title>Multivariable analysis associated with stroke knowledge</title>
<p>In the logistic regression analysis, when considering identification of at least a risk factor as the dependent variable, the multivariable analysis showed that females compared to males and patients with depression versus without depression had significantly higher odds to identify at least a risk factor (OR of 14.716 [95% CI 1.901;113.908] and 0.241 [95% CI 0.059; 0.984], respectively). <xref ref-type="table" rid="tab5">Table 5</xref> shows the results of multivariate analysis.</p>
<table-wrap position="float" id="tab5">
<label>Table 5</label>
<caption>
<p>Multivariate analysis associated with stroke knowledge among the participants (<italic>n</italic>&#x2009;=&#x2009;410).</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top">Variables</th>
<th align="center" valign="top"><italic>&#x03B2;</italic> (SE)</th>
<th align="center" valign="top">OR (95% CI)</th>
<th align="center" valign="top"><italic>p</italic>-value</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="top" colspan="4">Risk factor(s) identified (&#x2265;1)</td>
</tr>
<tr>
<td align="left" valign="top">Gender (female versus male&#x002A;)</td>
<td align="center" valign="bottom">2.689 (1.044)</td>
<td align="center" valign="bottom">14.716 (1.901;113.908)</td>
<td align="center" valign="bottom"><bold>0.01</bold></td>
</tr>
<tr>
<td align="left" valign="top">Depression (yes versus no&#x002A;)</td>
<td align="center" valign="bottom">&#x2212;1.421 (0.717)</td>
<td align="center" valign="bottom">0.241 (0.059; 0.984)</td>
<td align="center" valign="bottom"><bold>0.047</bold></td>
</tr>
<tr>
<td align="left" valign="top" colspan="4">Consequence(s) identified (&#x2265;1)</td>
</tr>
<tr>
<td align="left" valign="top">Gender (female versus male&#x002A;)</td>
<td align="center" valign="bottom">0.829 (0.5)</td>
<td align="center" valign="bottom">2.3 (0.6; 8.4)</td>
<td align="center" valign="bottom">0.214</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<p><italic>&#x03B2;</italic>, Beta; SE, standard error; OR, adjusted ratio; CI, confidence interval.</p>
<p>Logistic regression taking identification of stroke risk factors, stroke early symptoms, stroke consequences as the dependent variables and sociodemographic factors (gender, age, depression, dyslipidemia, kidney disease, and obesity) as independent variables. Numbers in bold indicate significant <italic>p</italic>-values. &#x002A;Stands for the reference category.</p>
</table-wrap-foot>
</table-wrap>
</sec>
</sec>
<sec sec-type="discussion" id="sec19">
<title>Discussion</title>
<p>The present study aimed at examining factors associated with stroke knowledge and awareness among the general population of Sudan. It is extremely important to prevent stroke and initiate early and timely management through assessing people&#x2019;s knowledge and awareness of risk factors and their modifications, as well as their warning symptoms and management. Therefore, creating effective educational and preventative measures are crucial for assessing the factors associated with stroke knowledge among different sociodemographic groups within communities.</p>
<p>The results indicated that around half of the sample were females, and aged between 30 and 49&#x2009;years old. Moreover, more than half of the participants have low- or medium-monthly incomes. In addition, the majority of the participants have university education, with more than two-thirds of them were employed. Most of the participants had heard of the condition previously and reported that stroke is a disease of brain, and it is a serious disease. Overall, participants&#x2019; general knowledge about stroke was insufficient, with only about a third of participants correctly identifying all risk factors, all consequences, and early symptoms of stroke.</p>
<p>Previous studies reported suboptimal in different communities regarding strokes, even among those who had experienced it before (<xref ref-type="bibr" rid="ref17 ref18 ref19">17&#x2013;19</xref>). A recent study in Sudan reported a relatively low mean awareness score among Sudanese people (<xref ref-type="bibr" rid="ref20">20</xref>). In addition, the mean awareness score was found to be statistically associated with the level of education (<xref ref-type="bibr" rid="ref20">20</xref>). According to our study findings, a variable level of knowledge about stroke was found among participants. The participants in our study expressed better general knowledge about stroke compared to previous study in Sudan (<xref ref-type="bibr" rid="ref20">20</xref>). Our findings can be interpreted by the fact that the majority of our participants had university educational level which could have raised the level of knowledge. Additionally, most of our participants identified at least one risk factor, one symptom related to stroke and one consequence. In addition, the percentages were higher than those reported in the literature (<xref ref-type="bibr" rid="ref21 ref22 ref23">21&#x2013;23</xref>), revealing that at least one stroke risk factor may be identified by the majority of the study sample, probably as most of our study participants had higher educational levels and were employed.</p>
<p>As for the risk factors, there are several modifiable and non-modifiable risk factors associated with stroke, including age, race, hypertension, diabetes, and many more (<xref ref-type="bibr" rid="ref24">24</xref>), which are becoming more prevalent among the Sudanese community according to the stepwise approach to surveillance survey of 2005 (STEPS) (<xref ref-type="bibr" rid="ref25">25</xref>). In our study, 96.3% of 410 participants identified at least one associated risk factor for stroke compared to previous published studies in the last 3&#x2009;years, which reported in the UAE (99.8%, <italic>n</italic>&#x2009;=&#x2009;545), Saudi Arabia (99.5%, <italic>n</italic>&#x2009;=&#x2009;398), Jordan (98.1%, <italic>n</italic>&#x2009;=&#x2009;573), Lebanon (97.8%, <italic>n</italic>&#x2009;=&#x2009;551), and Iraq (85.6%, <italic>n</italic>&#x2009;=&#x2009;609) (<xref ref-type="bibr" rid="ref8">8</xref>, <xref ref-type="bibr" rid="ref26 ref27 ref28 ref29">26&#x2013;29</xref>).</p>
<p>Considering recent studies in the Middle East region to our study results, the aware that stroke is a type of brain disease were various among the participants with the highest in Jordan and Lebanon with more than 95.0% of the participants (<xref ref-type="bibr" rid="ref28">28</xref>), then Iraq (92.8%) (<xref ref-type="bibr" rid="ref27">27</xref>), Saudi Arabia (89.7%) (<xref ref-type="bibr" rid="ref29">29</xref>), and the UAE (70.8%) (<xref ref-type="bibr" rid="ref26">26</xref>), while the results of our studies indicated that 93.2% of the participants. In related to the participants&#x2019; awareness of stroke is preventable, the results reported by the participants were also various among the countries, with the highest in Iraq (85.6%) (<xref ref-type="bibr" rid="ref27">27</xref>), then our Sudan sample with 83.4%, then Jordan and Saudi Arabia with 81.0% (<xref ref-type="bibr" rid="ref8">8</xref>, <xref ref-type="bibr" rid="ref29">29</xref>), Lebanon (80.0%) (<xref ref-type="bibr" rid="ref28">28</xref>), and the UAE (42.9%) (<xref ref-type="bibr" rid="ref26">26</xref>).</p>
<p>A significant improvement in the rates of identified risk factors of stroke among the Sudanese community was noticed, as a previous study reported that 27.6% of their study participants did not have sufficient knowledge about stroke risk factors, contrary to our findings, where it was only 3.7% (<xref ref-type="bibr" rid="ref20">20</xref>). According to this study, hypertension was the most reported risk factor, followed by psychological stress and obesity. Similarly, a comparative study of risk factors in young adults and older adult stroke patients in Sudan reported that arterial hypertension was the dominant risk factor among young adults and the older adult, followed by smoking (<xref ref-type="bibr" rid="ref30">30</xref>). As well as previous studies conducted in Lebanon revealed that hypertension and psychological stress were among the most reported risk factors as well (<xref ref-type="bibr" rid="ref28">28</xref>), in Jordan (<xref ref-type="bibr" rid="ref8">8</xref>), Saudi (<xref ref-type="bibr" rid="ref29">29</xref>), UAE (<xref ref-type="bibr" rid="ref26">26</xref>), and Iraq (<xref ref-type="bibr" rid="ref27">27</xref>).</p>
<p>Regarding warning signs and consequences of stroke, almost 85% reported sudden difficulty in speaking or understanding speech as the most common warning sign, followed by sudden weakness/numbness/tingling, which is similar to the findings of Lebanese and New Zealand studies (<xref ref-type="bibr" rid="ref28">28</xref>, <xref ref-type="bibr" rid="ref31">31</xref>). However, a previous Sudanese survey reported paralysis of one side of the body as the most commonly identified warning symptom by 30.7%, followed by sudden difficulty in speaking or understanding by 27.1%. In comparison to the findings of the previous study, the rates of the identified consequences of stroke were significantly improved among Sudanese people. Almost 33% of the previous study participants did not know any stroke warning symptoms (<xref ref-type="bibr" rid="ref20">20</xref>), while in our study, the percentage was only 4.9%. The improvement in the knowledge of the Sudanese community regarding risk factors, symptoms, and consequences related to stroke in our study could be attributed to the higher educational level and employment of the majority of our study participants.</p>
<p>Our results revealed a significant correlation between gender and knowledge about stroke risk factors, as females had better knowledge compared to males. In agreement with our study findings, other studies reported similar results (<xref ref-type="bibr" rid="ref32 ref33 ref34 ref35">32&#x2013;35</xref>). On the other hand, better knowledge of stroke warning signs among males was reported as well (<xref ref-type="bibr" rid="ref8">8</xref>, <xref ref-type="bibr" rid="ref27">27</xref>). Based on the literature, the lack of consistency in the results of different studies makes it ambiguous to call for a clear association between gender differences and knowledge of stroke warning signs and risk factors (<xref ref-type="bibr" rid="ref8">8</xref>, <xref ref-type="bibr" rid="ref27">27</xref>). As well as the multivariable analysis showed that patients with no depression had a significant correlation in identifying stroke risk factors, early stroke symptoms, and stroke consequences. A previous study revealed a significant inverse correlation between depression and knowledge. It is reported that depressed patients had poorer knowledge and a decline in knowledge as depression increases, suggesting that cognitive function may be impaired by depression (<xref ref-type="bibr" rid="ref36">36</xref>, <xref ref-type="bibr" rid="ref37">37</xref>).</p>
<sec id="sec20">
<title>Strengths and limitations</title>
<p>There are some limitations to this study that can be identified. First, the study utilized an online survey that mandates technical requirements and access to internet and mobile/computer and reading ability, hence the population in this study does not represent the whole population in Sudan. Second, information bias connected to on-demand resource accessibility can jeopardize answer credibility. Third, selection bias associated with the snowball collection technique could be an issue, as there is no guarantee for random selection. Furthermore, there is a high percentage of missing data that leads to big odds ratio. On the other hand, our study has several strengths as it added data to the literature about stroke disease awareness which highlighted the lack of knowledge regarding stroke among the Sudanese population.</p>
</sec>
</sec>
<sec sec-type="conclusions" id="sec21">
<title>Conclusion</title>
<p>In general, the Sudanese community demonstrated suboptimal knowledge regarding stroke risk factors, early symptoms, and consequences. Females and individuals without a medical history of depression exhibited higher knowledge scores. Recognition of specific aspects varied, with social media serving as a prominent information source. Tailored interventions focusing on individuals with inadequate stroke literacy are needed to improve stroke awareness. Further studies, more representative of the general Sudanese population and with a larger sample size, are necessary to confirm our findings.</p>
</sec>
<sec sec-type="data-availability" id="sec22">
<title>Data availability statement</title>
<p>The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.</p>
</sec>
<sec sec-type="ethics-statement" id="sec23">
<title>Ethics statement</title>
<p>The studies involving humans were approved by the research ethics committee of the Faculty of Pharmacy, Al Neelain University, Khartoum, Sudan (NPH1021). The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.</p>
</sec>
<sec sec-type="author-contributions" id="sec24">
<title>Author contributions</title>
<p>EE: Writing &#x2013; review &#x0026; editing, Writing &#x2013; original draft. FJ: Writing &#x2013; original draft, Writing &#x2013; review &#x0026; editing, Conceptualization, Methodology. DS: Methodology, Writing &#x2013; original draft. HaA: Writing &#x2013; original draft. MA: Writing &#x2013; original draft, Writing &#x2013; review &#x0026; editing. ZKha: Methodology, Writing &#x2013; original draft. YA: Writing &#x2013; original draft, Writing &#x2013; review &#x0026; editing. MB: Writing &#x2013; original draft, Writing &#x2013; review &#x0026; editing. ZKhi: Writing &#x2013; original draft. HuA: Writing &#x2013; original draft. NM: Investigation, Writing &#x2013; original draft. SC: Formal analysis, Writing &#x2013; original draft. SK: Writing &#x2013; review &#x0026; editing. SH: Formal analysis, Writing &#x2013; review &#x0026; editing. DM: Writing &#x2013; review &#x0026; editing, Conceptualization, Data curation, Methodology, Supervision. HH: Writing &#x2013; review &#x0026; editing.</p>
</sec>
</body>
<back>
<sec sec-type="funding-information" id="sec25">
<title>Funding</title>
<p>The author(s) declare that no financial support was received for the research, authorship, and/or publication of this article.</p>
</sec>
<sec sec-type="COI-statement" id="sec26">
<title>Conflict of interest</title>
<p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
</sec>
<sec id="sec100" sec-type="disclaimer">
<title>Publisher&#x2019;s note</title>
<p>All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.</p>
</sec>
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