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<b><i>Introduction:</i></b> We aimed to determine knowledge of stroke risk factors and signs in an urban population of northern Benin. <b><i>Methods:</i></b> A door-to-door purposeful sampling survey was conducted in resident population (age ≥15 years) of the district of Titirou in the city of Parakou (<i>N</i> = 255,478) in Benin between March 15 and July 15, 2016. In-person interviews were conducted with data collection on structured questionnaires with close and open questions, according to standard definitions. Multivariable logistic regression was used to assess predictors of good knowledge, defined by provision of a correct response in pre-defined set of questions on stroke risk factors and warning signs. <b><i>Results:</i></b> Of 4,671 participants (mean age 27.7 ± 12.9 years; females 50.6%), only 404 (8.6%) knew at least 1 stroke risk factor. Knowledge level of stroke risk factors (odds ratio, 95% confidence interval) was related to age (1.37, 1.27–1.48), level of education (2.54, 1.73–3.72), and family history of stroke (3.01, 2.08–4.26). Only 230 (4.9%) were able to cite at least 1 stroke symptom, and this knowledge was great with increasing age (1.04, 1.02–1.06), family (3.63, 2.41–5.49) and personal history of stroke (3.71, 1.86–7.42), and high level of education (4.35, 2.68–7.07). <b><i>Conclusion:</i></b> Knowledge of stroke risk factors and signs is low in northern Benin. Greater public education and awareness campaigns are required to address the burden of stroke.

Sub-Saharan Africa faces a heavy burden of stroke due to the growth of its risk factors. We aimed to estimate the prevalence of stroke risk factors and identify the factors associated with metabolic risk factors in the district of Titirou, in Parakou (northern Benin) in 2016. A cross-sectional study was conducted. It included people aged at least 15 years, living in Titirou for at least 6 months, and who had given their written consent to participate in the study. A door-to-door survey was performed from 15 march to 15 July 2016 in each neighborhood until the pre-determined number was reached. Sociodemographic data, medical histories, anthropometric and blood pressure measures were recorded using the WHO STEPS approach. The prevalence of stroke risk factors was calculated, and a multivariable logistic regression was done to identify the factors associated with metabolic risk factors for stroke. A total of 4671 participants were included with a mean age of 27.7±12.9 years and a sex ratio of 0.98. Concerning the behavioral risk factors for stroke, 17.2% were alcohol consumers, 3.5% were smokers, 21.5% had low fruit and vegetable intake, and 51.1% had low physical activity practice. The prevalence of metabolic risk factors for stroke was respectively of 8.7% for obesity, 7.1% for high blood pressure, 1.7% for self-reported diabetes, and 2.2% for dyslipidemia. Age (p<0.001), sex (p<0.001), marital status (p<0.001) and professional occupation (p = 0.010) were associated with obesity. Age was also associated with high blood pressure (p<0.001) and diabetes (p<0.001). Dyslipidemia varied according to smoking (p = 0.033) and low physical activity practice (p = 0.003). The study revealed a significant prevalence of some stroke risk factors. Targeted local interventions for primary prevention of stroke should be promoted in this community.

Background: Sub-Saharan Africa faces a high burden of stroke due to growing of their risk factors. We aimed to estimate the prevalence of stroke risk factors and to identify associated factors in the district of Titirou in Parakou (northern Benin), in 2016.Methods: It was a cross-sectional study. It included adults living in Titirou and having given their consent. A door-to-door survey was performed from 15 march to 15 July 2016 in each neighbourhood or village until the expected number reached. We recorded the socio-demographic data, medical histories, anthropometric and blood pressure measures using WHO steps approach. Prevalences of stroke risk factors were calculated and a logistic regression was done to identify factors associated with metabolic risk factors.Results: A total of 4671 participants was included with a mean age of 27.7±12.9 years and a sex ratio of 0.97. Prevalences of behavioural risk factors were estimated at: 17.2% of alcohol consumption, 21.5% of low fruits and vegetables consumption, 51.1% of low physical activity practice, and 3.5% of smoking. Metabolic risk factors prevalence’s amounted to: 8.7% of obesity, 7.1% of high blood pressure, 1.7% of self-reported diabetes and 2.2% of dyslipidaemia. Age (p<0.001), sex (p<0.001), marital status (p<0.001) and professional occupation (p=0.010) were associated with obesity. Age was also associated with high blood pressure (p<0.001) and diabetes (p<0.001). Dyslipidaemia varied according to smoking (p=0.033) and low physical activity practice (p=0.003). Conclusion: The study showed high prevalences of low physical activity practice and obesity. Targeted local interventions focused on these factors should be conducted for primary prevention of stroke in this community, or even beyond in Benin.