An Estimate of the Incidence,…
Authors: Streletz Leopold 
Published: July 2019

IntroductionStroke, a neurological disorder that continues to be considerable burden on health systems due to high fatality rates and a major disability in survivors. Despite a decline in stroke incidence in the developed world, developing nations are still facing the problem at its eminent peak. Over 80% of all stroke deaths in the world occur in developing countries. This includes the MENA region, which not only comprises of the hugely populated and lesser developed countries in the world but some nations also has varied ethnic group due to prominent immigration predominantly from South Asia and South-east Asia.Studies have shown that different ethnic groups have different pre-disposing factors, epidemiological patterns and outcomes of stroke. These variations can be due to lifestyle, demographic, and/or socioeconomic factors. These differences can not only significantly change the course of treatment and management of stroke, but also change the methods applied towards the prevention of stroke, which is shown to be significant in order to reduce the incidence of stroke in a region. In the absence of significant global public health response the morbidity and mortality rates will only go higher.The MENA region comprises of a unique mix of low to middle income countries and high-income countries. But the common elements in all these countries include increase urbanization, unchecked population growth, increased consumption of western diet, obesity and inactivity. Moreover, the health services and public health response is not at par with the growing problem in hand.MethodsData sources and search strategyWe conducted a systematic review of the prevalence and incidence of Stroke in the 23 countries of MENA region (Sudan, Somalia, Djibouti, Pakistan, Afghanistan, Algeria, Bahrain, Egypt, Jordan, Kuwait, Lebanon, Libya, Iran, Iraq, Morocco, Oman, Qatar, Saudi Arabia, Syria, Tunisia, United Arab Emirates, Palestine and Yemen). The review was conducted following the PRISMA guidelines and the PRISMA checklist can be found on Figure S1 in Supporting Information (SI). Our search criteria can be found in Figure S2 in SI. Briefly, PubMed and EMBASE databases were used for this review. The databases were searched using text terms and MeSH/Emtree terms exploded to cover all sub-heading. We used a broad search criterion with no restrictions for language, or year of publication.Study selectionThe search results were imported to a reference manager, Endnote, and screened for duplicate papers. After exclusion of duplicates the titles and abstracts of the final set of distinctive papers was exported to Microsoft Excel. All the extracted articles were screened for relevance by two authors (SA and DD). The process of Screening was conducted in two separate steps: First level of screening involved screening titles and abstracts of all papers to exclude all non-relevant articles; second level involved screening the full-text of all relevant or potentially relevant articles thus, excluding all non-eligible articles. Any paper reporting the incidence or prevalence of stroke based on primary data were included in this review. All forms study designs except literature reviews, case reports, case series editorials, and letters to editors were included in the review. A publication is included in the review if it had a data point on either the prevalence of acute stroke, or the incidence of acute stroke, or both.Data extraction and data synthesisData from relevant articles was extracted by two authors, SA and DD, for the following indicators: author, year of publication, year of study, country of study,study design, sampling technique, population, sample size, stroke incidence and stroke prevalence. Though the articles were not search for mortality and risk factors, this information was extracted from relevant reports when available. Data was extracted from abstracts when the full text is unavailable. Any studies in Arabic or French were screened by author DD.ResultsConclusionFigure 1
Reasons for exclusion
Full-text did not include data on relevant indicators (n = 191)Article is an editorial/commentary/letter to editor (n = 4)Full-text could not be retrieved and abstract does not have data on relevant outcomes (n = 15)Reasons for exclusionSame dataset as another included relevant publication (n = 5)Paper presents contradictory/unclear numbers that could not be verified (n = 0)References