Epidemiology and Clinical Features of Multiple Sclerosis in Rafsanjan City, Kerman Province, Iran: A Cross-Sectional Study from 2011 to 2020

Epidemiology and Clinical Features of Multiple Sclerosis in Rafsanjan City, Kerman Province, Iran: A Cross-Sectional Study from 2011 to 2020 | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Epidemiology and Clinical Features of Multiple Sclerosis in Rafsanjan City, Kerman Province, Iran: A Cross-Sectional Study from 2011 to 2020 Fatemeh Rostami, Alireza Vakilian, Saeid Esmaeilian, Nazanin Jalali, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3851895/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Multiple sclerosis (MS) is a chronic inflammatory demyelinating disease of the central nervous system with variable epidemiology and clinical features. This study aimed to examine the epidemiology and clinical characteristics of MS in Rafsanjan City, Iran, from 2011 to 2020. Methods: A cross-sectional study was conducted on patients diagnosed with MS and registered in the Committee for Diagnosis and Treatment of MS. Data were collected using a revised checklist of demographic and clinical variables. The annual incidence and prevalence of MS were calculated with a 95% confidence interval. Descriptive statistics, t-test, and chi-square or Fisher's exact test were used to analyze the data. Results: Out of 361 eligible cases, 220 patients with MS were enrolled. The mean age was 39.44 ± 9.71 years, with 82.3% females and a female-to-male ratio of 4.64. Most patients lived in urban areas (70.5%) and were housekeepers (55.9%). Most births occurred in spring (30.4%) and summer (35.5%). Only 13.2% had a positive family history of MS, and 2.3% had a smoking history. The most common initial symptoms were sensory (28.6%) and visual (17.7%). The dominant disease course was relapsing-remitting MS (RRMS) (79.1%), followed by RPMS (10.9%), PPMS (4.5%), SPMS (4.1%), and CIS (1.4%). The disease course was associated with several demographic and clinical variables. The incidence rate was 4.84 per 100,000, and the prevalence rate was 97.68 per 100,000. Conclusion: MS has a low incidence and prevalence rate in Rafsanjan City. MS mainly affects young urban women who are housekeepers. Sensory and visual impairments are the most frequent initial manifestations, and RRMS is the most common disease course. Multiple Sclerosis Epidemiology Rafsanjan Figures Figure 1 Introduction Multiple sclerosis (MS) is a chronic inflammatory demyelinating central nervous system disease affecting more than 2.8 million people worldwide[ 1 ]. MS is characterized by heterogeneous clinical manifestations, variable disease courses, and unpredictable outcomes[ 2 ]. MS can cause various neurological impairments, such as sensory disturbances, motor weakness, visual loss, cognitive decline, and fatigue, that can affect the quality of life and productivity of patients[ 3 ]. The etiology of MS is still unclear, but it is believed to involve a complex interplay of genetic and environmental factors[ 4 , 5 ]. Some ecological factors associated with MS risk or progression are latitude, sunlight exposure, vitamin D levels, Epstein-Barr virus infection, smoking, obesity, and diet[ 6 , 7 ]. However, the exact mechanisms by which these factors influence MS pathogenesis still need to be fully understood. The epidemiology of MS varies widely across different regions and populations. MS is more prevalent in temperate zones than in tropical or polar regions, and it is more common in women than in men[ 8 ]. The global prevalence of MS has increased over the past decades, partly due to improved diagnostic methods and increased awareness[ 9 – 12 ]. However, there are still gaps in the epidemiological data on MS in some parts of the world, especially in low- and middle-income countries[ 13 ]. Iran has a diverse geography and climate, located in the Middle East. The prevalence of multiple sclerosis (MS) in Iran has been documented to vary from 5.3 to 74.8 per 100,000 individuals, contingent upon the geographical area and the methodology employed in the study [ 14 ]. Nevertheless, a more comprehensive and up-to-date collection of epidemiological data on MS in Iran is indispensable, particularly in specific regions such as Kerman. Consequently, the primary objective of this investigation was to examine the demographic and clinical attributes, as well as the incidence and prevalence of MS in Rafsanjan City, located within Kerman Province, Iran, spanning the period from 2011 to 2020. Methods A cross-sectional investigation was conducted to analyze the epidemiological and clinical attributes of individuals diagnosed with multiple sclerosis (MS) in the city of Rafsanjan, Iran, spanning the years 2011 to 2020. This research design was appropriate for elucidating the distribution and characteristics of MS within a specific population and time frame. Nevertheless, it was not capable of establishing causative relationships or temporal sequences, and there existed the potential for biased selection or recall. The study cohort comprised all patients with MS who were officially registered with the Committee for Diagnosis and Treatment of MS (CDTMS) overseen by the Rafsanjan University of Medical Sciences. The CDTMS bears the responsibility of monitoring and addressing insurance matters concerning all known MS cases within the city. By utilizing a census approach, we incorporated all patients supported by the CDTMS into the study and procured their demographic data from the deputy health department of Rafsanjan City for the designated study period. Patients were diagnosed and categorized in accordance with the McDonald criteria of 2017, which necessitate the presence of disseminated central nervous system damage over both space and time. Such evidence can be obtained through clinical episodes, MRI scans, cerebrospinal fluid analysis, or visual evoked potentials. We selected these criteria due to their recent nature and widespread acceptance as the diagnostic standards for MS[ 15 ]. We obtained the data through the utilization of an updated inventory that encompassed variables such as age, gender, profession, marital status, place of residence, season of birth, family history, initial symptoms of MS, year of symptom onset, year of diagnosis, and smoking habits. The inventory's credibility was verified by two neurologists and its reliability and validity were tested on a preliminary sample of 10 patients. The data was extracted from the medical records of the patients in the CDTMS and supplemented with telephonic interviews when necessary. The data was entered into a computer system with a unique code and analyzed using SPSS version 22 software. Descriptive statistics, including mean, standard deviation, and frequency tables, were used to succinctly summarize the data. The annual incidence and prevalence of MS were calculated, along with a 95% confidence interval, based on population data procured from the Statistical Center of Iran. The population data was adjusted for age and gender through the direct method. A t-test was employed to compare means, while a chi-square test or Fisher's exact test was used to compare categorical variables. The assumptions of normality, homogeneity of variance, and independence of observations were verified for each test. Multivariate analysis was conducted to control for potential confounding variables, such as age, gender, and profession. The effect sizes and confidence intervals of the results were reported, rather than solely relying on p-values. A p-value less than 0.05 was deemed statistically significant. Results We enrolled 220 patients with multiple sclerosis (MS) out of 361 eligible cases (Fig. 1 ). The mean age of the patients was 39.44 ± 9.71 years, ranging from 19 to 66 years. The majority of the patients were female, 181(82.3), with a female-to-male ratio of 4.64. The mean age of male and female patients was 42.34 ± 9.09 years and 38.82 ± 9 years, respectively, with no significant difference between the sexes (P = 0.107). The age distribution of the patients was as follows: 122 (55.5%) were in the 20–40 years group, 65 (29.5%) were in the 40–50 years group, 32 (14.5%) were above 50 years, and only one patient was below 20 years. Most of the patients lived in urban areas 155 (70.5%), and were housewives, 123(55.9%). The marital status of the patients was: married 17+(81.4%), single 27(12.3%), divorced 11(5%), and widowed 3(1.4%). The season of birth of the patients was: spring 67(30.4%), summer 78(35.5%), fall 32(14.5%) and winter 43(19.5%). Only 13.2% of the patients (n = 29) had a positive family history of MS, and only 2.3% of the patients (n = 5) had a history of smoking. The most common initial symptoms of MS were sensory symptoms 63(28.6%) and vision loss 39(17.7%). The least common initial symptom was urinary control problems (0.5%, n = 1). Additionally, 25.5% (n = 56) of the patients had more than one initial symptom. The most prevalent disease course was RRMS 174(79.1%), followed by RPMS 24(10.9%), PPMS 10(4.5%), SPMS 9(4.1%,), and CIS 3(1.4%,). We found significant associations between the disease course and the following variables: mean age, age group, sex, marital status, job, season of birth, and first symptom of MS (Table 1 ). We calculated the incidence and prevalence of MS in our study population from 2011 to 2020 as follows: the incidence rate was low at 4.84 per 100,000 people with a confidence interval of CI95% [2.304–7.373], and the prevalence rate was also low at 97.68 per 100,000 people with a confidence interval of CI95% [87.37-109.33]. More details are provided in Table 2. Table 1 Comparing the frequency of variables of multiple sclerosis according to disease patterns. Variables MS pattern P-value CIS RR PP SP RP Age Mean age (yr) 28.33 ± 4.93 38.19 ± 9.05 45.10 ± 5.84 46.56 ± 12.14 44.88 ± 11.08 0.0001 50 yr 0 (0%) 20 (62.5%) 2 (6.3%) 3 (9.4%) 7 (21.9%) sex male 0 (0%) 26 (68.4%) 4(10.5%) 1 (2.6%) 7 (18.4%) 0.111 female 3(1.6%) 148(81.3%) 6 (3.3%) 8 (4.4%) 17 (9.3%) Family history 0 (0%) 24 (82.8%) 1 (3..4%) 1(3..4%) 3 (10.3%) 0.958 Accommodation Urban 3(1.9%) 124(80.0%) 8(5.2%) 6 (3.9%) 14(80.0%) 0.47 Rural 0 (0%) 50 (76.9%) 2 (3.1%) 3 (4.6%) 10(15.4%) Marital status Single 1 (3.7%) 21 (77.8%) 0 (0.0%) 2(7.4%) 3 (11.1%) 0.001 married 1(0.6%) 146(81.6%) 10(5.6%) 7 (3.9%) 15 (8.4%) Divorced 1(9.4%) 4 (36.4%) 0 (0.0%) 0 (0.0%) 6(54.5%) widow 0(0.0%) 3 (100%) 0 (0.0%) 0 (0.0%) 0 (0.0%) job unemployment 0(0.0%) 14 (87.5%) 0 (0.0%) 0 (0.0%) 2 (12.5%) 0.0001 Student 1(10.0%) 8 (80.0%) 0 (0.0%) 1(10.0%) 0 (0.0%) employed 0 (0.0%) 44 (89.2%) 1 (1.8%) 2 (3.6%) 3 (5.4%) Housewife 2 (1.6%) 102(82.9%) 6 (4.9%) 5 (4.1%) 8 (6.5%) Incompetent 0 (0.0%) 1 (7.7%) 1 (7.7%) 1 (7.7%) 10(76.9%) Retired 0 (0.0%) 5 (62.5%) 2(25.0%) 0 (0.0%) 1 (12.5%) Season of Birth spring 1 (1.6%) 50 (77.8%) 0 (0%) 4 (6.3%) 12(14.3%) 0.002 summer 0 (0%) 64 (82.1%) 8(10.3%) 1 (1.3%) 5 (6.4%) fall 0 (0%) 25 (0%) 1 (3.1%) 2 (6.3%) 4 (12.5%) winter 2 (0%) 35 (0%) 1(2.3%) 2 (4.7%) 3 (7.0%) The first symptom of the diagnosis Vision 1(2.6%) 34 (87.2%) 1 (2.6%) 1 (2.6%) 2 (5.1%) 0.017 Sensory 0 (0%) 51 (81.0%) 4 (6.3%) 2 (3.2%) 6(9.5%) movement 0 (0%) 14 (100%) 0 (0%) 0 (0%) 0 (0%) imbalance 0 (0%) 5 (71.4%) 1(14.3%) 0 (0%) 1 (14.3%) diplopia 2 (7.1%) 17 (60.7%) 1 (3.6%) 2 (7.1%) 6 (21.4%) Urinary 0 (0%) 0 (0%) 1 (100%) 0 (0%) 0 (0%) other 0 (0%) 8 (66.7%) 1 (8.3%) 1 (8.3%) 2 (16.7%) Multiple symp 3 (1.4%) 45 (80.4%) 1 (1.8%) 3 (5.4%) 7 (12.5%) Table 2. Incidence rate and prevalence of multiple sclerosis according to the studied years in Rafsanjan Year Population Size New MS Patients Incidence*(CI95%) Cumulative Prevalence *(CI95%) 2011 252,103 17 6.74(4.211–10.802) 83.69(73.14–95.77) 2012 255,457 7 2.74(1.328–5.661) 91.89(80.87–104.40) 2013 255,735 27 10.56 (7.263–15.375) 102.44(90.77-115.62) 2014 263,268 14 5.32(3.171–8.935) 104.83(93.18-117.94) 2015 266,060 14 5.26(3.137–8.842) 108.99(97.15-122.27) 2016 273,902 14 5.11(3.048–8.589) 110.98(99.19-124.17) 2017 278,570 17 6.10(3.814–9.784) 115.23(103.30-128.53) 2018 295,603 16 5.41(3.335–8.802) 114.00(102. 47-126.83) 2019 309,171 17 5.50(3.438–8.819) 114.49(103.18-127.05) 2020 319,410 7 2.19(1.063–4.529) 113.02(101.95-125.28) * Per 100,000 population Discussion Our study evaluated the epidemiology and clinical features of MS in Rafsanjan City, Iran from 2011 to 2020. The incidence rate (4.84 per 100,000) and prevalence rate (97.68 per 100,000) of MS were low compared to other regions[ 9 , 12 , 16 , 17 ]. MS affects women in early adulthood and urban lifestyles. The representation of married housewives highlights the impact on childbearing years. Sensory dysfunction and vision loss were common initial symptoms. Younger patients had RRMS while older individuals had progressive forms. Factors such as age, sex, marital status, occupation, season of birth, and symptoms were associated with disease pattern. Our findings are consistent with previous studies that have reported a low incidence and prevalence of MS in Kerman Province[ 14 ]. One possible explanation for this regional variation is the difference in environmental factors, such as latitude, sunlight exposure, vitamin D levels, and diet[ 6 ]. Kerman Province's location in southeast Iran yields high sun exposure and heat along with arid conditions, which prior studies suggest are protective against MS[ 18 ]. However, further studies are needed to confirm this hypothesis and to explore other potential factors that may influence MS epidemiology in this region. We also observed a female predominance of MS in our study population, with a female-to-male ratio of 4.64. This is similar to the global trend of MS being more common in women than men [ 8 ]. The reasons for this sex disparity are not fully elucidated, but they may involve hormonal, immunological, genetic, and epigenetic factors [ 19 ]. Some studies have suggested that estrogen may have a neuroprotective role in MS, while testosterone may have an immunomodulatory role [ 20 ]. Moreover, some genes that are involved in MS susceptibility or severity are located on the X chromosome or are influenced by sex hormones [ 21 ]. Additionally, some environmental factors, such as smoking and obesity, may have different effects on MS risk or progression between men and women [ 22 ]. Another finding of our study was that the mean age of the patients was 39.44 ± 9.71 years, and most of them were in the 20–40 years age group. This is in line with previous studies that have shown that MS typically affects young adults [ 2 ]. However, we also found that the mean age of male patients was higher than that of female patients, although not significantly. This is contrary to some studies that have reported a lower mean age of onset or diagnosis in men than in women [ 23 ]. This discrepancy may be due to the small sample size of male patients in our study or to other factors that may affect the age distribution of MS patients in different populations. We also found that most of the patients lived in urban areas and were housewives. This may reflect the socio-economic status and lifestyle of our study population. Urbanization may be associated with increased exposure to environmental pollutants or infections that may trigger or exacerbate MS [ 24 ]. Housewives may have less physical activity or social support than other occupations, which may affect their mental health or immune system [ 25 ]. However, these associations need to be further investigated in future studies. The season of birth of the patients was another variable that we examined in our study. We found that most of the patients were born in summer, followed by spring. This is consistent with some studies that have reported a higher risk of MS among people born in summer or spring than among those born in winter or fall [ 26 ]. One possible explanation for this seasonal effect is the influence of maternal vitamin D levels during pregnancy on fetal immune system development [ 27 ]. The skin synthesizes vitamin D upon exposure to sunlight and has anti-inflammatory and immunoregulatory properties [ 28 ]. Other Dietary habits, vitamin D levels, rates of infectious triggers like Epstein-Barr virus, genetics, and ancestry within this distinct population likely also play a role. Dietary habits, vitamin D levels, rates of infectious triggers like Epstein-Barr virus, genetics, and ancestry within this distinct population likely also play a role[ 6 , 24 , 26 – 30 ]. The family history of MS was another factor that we considered in our study. We found that only 13.2% of the patients had a positive family history of MS, which is lower than some studies that have reported a family history rate of up to 30% among MS patients [ 29 ]. This may indicate a lower genetic contribution to MS risk in our study population or a lack of awareness or diagnosis of MS among relatives. However, it is well established that MS has a vital genetic component, with more than 200 genes identified as associated with MS susceptibility or severity[ 30 ]. Therefore, further genetic studies are needed to identify the specific genes or variants involved in MS pathogenesis in our population. The initial symptoms and disease course of the patients were also analyzed in our study. We found that sensory symptoms and vision loss were the most common initial manifestations of MS, followed by motor weakness and balance problems. This is similar to previous studies that have reported sensory and visual disturbances as frequent presenting symptoms of MS [ 31 ]. These symptoms reflect the involvement of the spinal cord, optic nerve, or cerebellum by MS lesions [ 32 ]. The least common initial symptom in our study was urinary control problems, which may reflect the brainstem or spinal cord involvement by MS lesions [ 33 ]. The disease course of the patients aligned with previous studies, showing that RRMS is the most common form of MS for about 85% of the cases[ 2 ]. However, our study found RPMS to be more prevalent than PPMS or SPMS, which differs from other studies[ 34 ].. This difference could be due to variations in disease definitions or follow-up periods. We also identified significant associations between disease course and demographic and clinical variables, indicating that these factors influence the natural history or prognosis of MS in different ways. However, further research is needed to understand the underlying mechanisms and causal relationships. Limitations This study provides valuable insights into MS in Rafsanjan City, but it has limitations. The design prevents longitudinal data on disease progression, which a retrospective cohort study could provide. The data source limits generalizability to the wider population. A larger registry would allow for comparisons with standardized data collection. Existing medical records lack important clinical information. Prospective studies should include comprehensive assessments and patient interviews. The genetic and immunologic profiles are unknown, hindering understanding of the disease. Analyzing markers could reveal differences between populations. More research is needed to understand regional variations and biological determinants. Large-scale collaborative research may identify factors that inform prevention and management strategies. Conclusion This cross-sectional study presents significant epidemiological data regarding Multiple Sclerosis (MS) in Rafsanjan City, Iran, spanning from 2011 to 2020. Our findings indicate a relatively low incidence rate of 4.84 per 100,000 individuals and a prevalence rate of 97.68 per 100,000 individuals, suggesting that MS is less prevalent in this region compared to other areas within Iran and globally. Most patients affected by MS were young women under the age of 40 residing in urban settings, aligning with recognized demographic risk factors. While most patients were diagnosed with Relapsing-Remitting MS (RRMS), cases of the relapsing-progressive course were also frequently observed. Sensory and visual symptoms predominated during the onset of the disease. Key factors significantly associated with the course of the disease encompassed age group, gender, marital status, occupation, season of birth, and the manifestation of neurological symptoms at presentation. Notably, the progressive forms of MS tended to manifest in older patients, whereas the relapsing-remitting course was more prevalent in individuals under the age of 40. These discrepancies underscore the potential influence of demographic and early clinical characteristics on long-term prognosis. Furthermore, both environmental and genetic factors may impact MS susceptibility and outcomes within this distinctive population. The underlying reasons for the relative rarity of MS in Rafsanjan City remain unexplained, thereby necessitating further investigation into potentially protective factors, including sunlight exposure, dietary patterns, infections, and ancestral lineage. Abbreviations MS Multiple Sclerosis CNS Central Nervous System RRMS Relapsing-Remitting Multiple Sclerosis SPMS Secondary Progressive Multiple Sclerosis PPMS Primary Progressive Multiple Sclerosis PRMS Progressive Relapsing Multiple Sclerosis CIS Clinically Isolated Syndrome CDTMS Committee for Diagnosis and Treatment of Multiple Sclerosis EDSS Expanded Disability Status Scale CI Confidence Interval. Declarations Availability of Data and Materials The data that support the findings of this study are available from Rafsanjan University of Medical Sciences (RUMS), but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are however available from the corresponding author upon reasonable request and with permission of RUMS. Please contact the corresponding author at “ [email protected] ” for data access inquiries. Consent for publication Not applicable Competing interests The authors declare that there is no conflict of interest in relation to the publication of this paper. Funding This research also did not benefit from any external funding. Declaration of generative AI in scientific writing The authors used “Grammarly” to check the grammar and originality of this work. They also revised and edited the content as needed and took full responsibility for the publication. Ethical Approval The study protocol was approved by the Ethics Committee of Rafsanjan University of Medical Sciences (approval number: IR.RUMS.REC.1399.126). All experiments were performed in accordance with relevant guidelines and regulations. 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Ann Neurol. 2001;50(1):121–7. 10.1002/ana.1032 . Miller DH, Leary SM. Primary-progressive multiple sclerosis. Lancet Neurol. 2007;6 10:903 – 12; doi: 10.1016/S1474-4422(07)70243-0. Kurtzke JF. Rating neurologic impairment in multiple sclerosis: an expanded disability status scale (EDSS). Neurology. 1983;33 11:1444–52. 10.1212/wnl.33.11.1444 . Lublin FD, Reingold SC, Cohen JA, Cutter GR, Sorensen PS, Thompson AJ, et al. Defining the clinical course of multiple sclerosis: the 2013 revisions. Neurology. 2014;83 3:278–86. 10.1212/WNL.0000000000000560 . Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3851895","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":267721389,"identity":"d4d80496-cc65-4f48-8808-d56bd6150997","order_by":0,"name":"Fatemeh Rostami","email":"","orcid":"","institution":"Rafsanjan University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Fatemeh","middleName":"","lastName":"Rostami","suffix":""},{"id":267721390,"identity":"8d577086-2821-45ae-be43-bf9a799165f8","order_by":1,"name":"Alireza Vakilian","email":"","orcid":"","institution":"Rafsanjan University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Alireza","middleName":"","lastName":"Vakilian","suffix":""},{"id":267721391,"identity":"8c445601-002a-4d21-a1aa-7576146bdf2e","order_by":2,"name":"Saeid Esmaeilian","email":"","orcid":"","institution":"Shiraz University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Saeid","middleName":"","lastName":"Esmaeilian","suffix":""},{"id":267721392,"identity":"5739c0d2-41f4-43eb-b7df-00f814900692","order_by":3,"name":"Nazanin Jalali","email":"","orcid":"","institution":"Rafsanjan University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Nazanin","middleName":"","lastName":"Jalali","suffix":""},{"id":267721393,"identity":"94967fd1-044d-45ea-b70b-0edbfa763106","order_by":4,"name":"Hossein Tahernia","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9ElEQVRIiWNgGAWjYFACHhAhwcDG3nzgwAcgk42doAaoFj6eY4kHZ4C0MBOnhYFBTiLH+DCYTUiLPfvZg48rd1jIs0nkGBy2+bVNno+ZgfHDxxw8tvDkJRuePSNh2MbzrOBwbt9twzZmBmbJmdvwOSzHTLKxTYKxjT15w+HcntuMQC1szLz4tPC/Mf8J1GLfxpBgcNiy57Y9YS0SOWaMQC2JbRwpBocZftxOJKzlxhtjkMOS23iOJRzsbbid3MbM2IzXL+z9OYYfG9vqbOe3Nx/+8OPPbRDj4IePeLSgAsY2MNlArHoQ+EOK4lEwCkbBKBgpAABEd0+BTVrcIwAAAABJRU5ErkJggg==","orcid":"","institution":"Rafsanjan University of Medical Sciences","correspondingAuthor":true,"prefix":"","firstName":"Hossein","middleName":"","lastName":"Tahernia","suffix":""}],"badges":[],"createdAt":"2024-01-11 01:14:42","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3851895/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3851895/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":49825471,"identity":"e68cd701-13c0-4cfd-8ebb-64f7399520a1","added_by":"auto","created_at":"2024-01-18 15:44:25","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":72590,"visible":true,"origin":"","legend":"\u003cp\u003eflow chart of study\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-3851895/v1/f457fc99e9752434dce8015e.jpeg"},{"id":50757356,"identity":"58129d85-52dd-42da-8eb9-be881a42278c","added_by":"auto","created_at":"2024-02-06 19:52:48","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":298394,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3851895/v1/83bb8b45-b299-4f4f-bf87-5531bbdc31a7.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Epidemiology and Clinical Features of Multiple Sclerosis in Rafsanjan City, Kerman Province, Iran: A Cross-Sectional Study from 2011 to 2020","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMultiple sclerosis (MS) is a chronic inflammatory demyelinating central nervous system disease affecting more than 2.8\u0026nbsp;million people worldwide[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. MS is characterized by heterogeneous clinical manifestations, variable disease courses, and unpredictable outcomes[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. MS can cause various neurological impairments, such as sensory disturbances, motor weakness, visual loss, cognitive decline, and fatigue, that can affect the quality of life and productivity of patients[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. The etiology of MS is still unclear, but it is believed to involve a complex interplay of genetic and environmental factors[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Some ecological factors associated with MS risk or progression are latitude, sunlight exposure, vitamin D levels, Epstein-Barr virus infection, smoking, obesity, and diet[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. However, the exact mechanisms by which these factors influence MS pathogenesis still need to be fully understood. The epidemiology of MS varies widely across different regions and populations. MS is more prevalent in temperate zones than in tropical or polar regions, and it is more common in women than in men[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. The global prevalence of MS has increased over the past decades, partly due to improved diagnostic methods and increased awareness[\u003cspan additionalcitationids=\"CR10 CR11\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. However, there are still gaps in the epidemiological data on MS in some parts of the world, especially in low- and middle-income countries[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Iran has a diverse geography and climate, located in the Middle East. The prevalence of multiple sclerosis (MS) in Iran has been documented to vary from 5.3 to 74.8 per 100,000 individuals, contingent upon the geographical area and the methodology employed in the study [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Nevertheless, a more comprehensive and up-to-date collection of epidemiological data on MS in Iran is indispensable, particularly in specific regions such as Kerman. Consequently, the primary objective of this investigation was to examine the demographic and clinical attributes, as well as the incidence and prevalence of MS in Rafsanjan City, located within Kerman Province, Iran, spanning the period from 2011 to 2020.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eA cross-sectional investigation was conducted to analyze the epidemiological and clinical attributes of individuals diagnosed with multiple sclerosis (MS) in the city of Rafsanjan, Iran, spanning the years 2011 to 2020. This research design was appropriate for elucidating the distribution and characteristics of MS within a specific population and time frame. Nevertheless, it was not capable of establishing causative relationships or temporal sequences, and there existed the potential for biased selection or recall.\u003c/p\u003e \u003cp\u003eThe study cohort comprised all patients with MS who were officially registered with the Committee for Diagnosis and Treatment of MS (CDTMS) overseen by the Rafsanjan University of Medical Sciences. The CDTMS bears the responsibility of monitoring and addressing insurance matters concerning all known MS cases within the city. By utilizing a census approach, we incorporated all patients supported by the CDTMS into the study and procured their demographic data from the deputy health department of Rafsanjan City for the designated study period.\u003c/p\u003e \u003cp\u003ePatients were diagnosed and categorized in accordance with the McDonald criteria of 2017, which necessitate the presence of disseminated central nervous system damage over both space and time. Such evidence can be obtained through clinical episodes, MRI scans, cerebrospinal fluid analysis, or visual evoked potentials. We selected these criteria due to their recent nature and widespread acceptance as the diagnostic standards for MS[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWe obtained the data through the utilization of an updated inventory that encompassed variables such as age, gender, profession, marital status, place of residence, season of birth, family history, initial symptoms of MS, year of symptom onset, year of diagnosis, and smoking habits. The inventory's credibility was verified by two neurologists and its reliability and validity were tested on a preliminary sample of 10 patients. The data was extracted from the medical records of the patients in the CDTMS and supplemented with telephonic interviews when necessary.\u003c/p\u003e \u003cp\u003eThe data was entered into a computer system with a unique code and analyzed using SPSS version 22 software. Descriptive statistics, including mean, standard deviation, and frequency tables, were used to succinctly summarize the data. The annual incidence and prevalence of MS were calculated, along with a 95% confidence interval, based on population data procured from the Statistical Center of Iran. The population data was adjusted for age and gender through the direct method. A t-test was employed to compare means, while a chi-square test or Fisher's exact test was used to compare categorical variables. The assumptions of normality, homogeneity of variance, and independence of observations were verified for each test. Multivariate analysis was conducted to control for potential confounding variables, such as age, gender, and profession. The effect sizes and confidence intervals of the results were reported, rather than solely relying on p-values. A p-value less than 0.05 was deemed statistically significant.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eWe enrolled 220 patients with multiple sclerosis (MS) out of 361 eligible cases (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). The mean age of the patients was 39.44\u0026thinsp;\u0026plusmn;\u0026thinsp;9.71 years, ranging from 19 to 66 years. The majority of the patients were female, 181(82.3), with a female-to-male ratio of 4.64. The mean age of male and female patients was 42.34\u0026thinsp;\u0026plusmn;\u0026thinsp;9.09 years and 38.82\u0026thinsp;\u0026plusmn;\u0026thinsp;9 years, respectively, with no significant difference between the sexes (P\u0026thinsp;=\u0026thinsp;0.107). The age distribution of the patients was as follows: 122 (55.5%) were in the 20\u0026ndash;40 years group, 65 (29.5%) were in the 40\u0026ndash;50 years group, 32 (14.5%) were above 50 years, and only one patient was below 20 years. Most of the patients lived in urban areas 155 (70.5%), and were housewives, 123(55.9%). The marital status of the patients was: married 17+(81.4%), single 27(12.3%), divorced 11(5%), and widowed 3(1.4%). The season of birth of the patients was: spring 67(30.4%), summer 78(35.5%), fall 32(14.5%) and winter 43(19.5%). Only 13.2% of the patients (n\u0026thinsp;=\u0026thinsp;29) had a positive family history of MS, and only 2.3% of the patients (n\u0026thinsp;=\u0026thinsp;5) had a history of smoking. The most common initial symptoms of MS were sensory symptoms 63(28.6%) and vision loss 39(17.7%). The least common initial symptom was urinary control problems (0.5%, n\u0026thinsp;=\u0026thinsp;1). Additionally, 25.5% (n\u0026thinsp;=\u0026thinsp;56) of the patients had more than one initial symptom. The most prevalent disease course was RRMS 174(79.1%), followed by RPMS 24(10.9%), PPMS 10(4.5%), SPMS 9(4.1%,), and CIS 3(1.4%,). We found significant associations between the disease course and the following variables: mean age, age group, sex, marital status, job, season of birth, and first symptom of MS (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). We calculated the incidence and prevalence of MS in our study population from 2011 to 2020 as follows: the incidence rate was low at 4.84 per 100,000 people with a confidence interval of CI95% [2.304\u0026ndash;7.373], and the prevalence rate was also low at 97.68 per 100,000 people with a confidence interval of CI95% [87.37-109.33]. More details are provided in Table\u0026nbsp;2.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"char\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\u0026nbsp;\u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eComparing the frequency of variables of multiple sclerosis according to disease patterns.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"8\"\u003e\u003c/colgroup\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\" rowspan=\"2\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003eMS pattern\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCIS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRP\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"5\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean age (yr)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28.33\u0026thinsp;\u0026plusmn;\u0026thinsp;4.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38.19\u0026thinsp;\u0026plusmn;\u0026thinsp;9.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45.10\u0026thinsp;\u0026plusmn;\u0026thinsp;5.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e46.56\u0026thinsp;\u0026plusmn;\u0026thinsp;12.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44.88\u0026thinsp;\u0026plusmn;\u0026thinsp;11.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;20 yr\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (100%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"4\"\u003e\n \u003cp\u003e0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21\u0026ndash;40 yr\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3(2.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e108(88.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (1.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (0.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8 (6.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41\u0026ndash;50 yr\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45 (69.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 (9.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (7.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9 (13.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;50 yr\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20 (62.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (6.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (9.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7 (21.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003esex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003emale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26 (68.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4(10.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (2.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7 (18.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"2\"\u003e\n \u003cp\u003e0.111\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003efemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3(1.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e148(81.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 (3.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8 (4.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17 (9.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFamily history\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24 (82.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (3..4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1(3..4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (10.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.958\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eAccommodation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUrban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3(1.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e124(80.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8(5.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 (3.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14(80.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"2\"\u003e\n \u003cp\u003e0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50 (76.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (3.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (4.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10(15.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003eMarital status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSingle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (3.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21 (77.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2(7.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (11.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"4\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003emarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1(0.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e146(81.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10(5.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7 (3.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15 (8.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDivorced\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1(9.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (36.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6(54.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ewidow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (100%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"6\"\u003e\n \u003cp\u003ejob\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eunemployment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14 (87.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (12.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"6\"\u003e\n \u003cp\u003e0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStudent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1(10.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8 (80.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1(10.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eemployed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44 (89.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (1.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (3.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (5.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHousewife\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (1.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e102(82.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 (4.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (4.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8 (6.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIncompetent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (7.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (7.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (7.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10(76.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRetired\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (62.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2(25.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (12.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003eSeason of Birth\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003espring\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (1.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50 (77.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (6.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12(14.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"4\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003esummer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e64 (82.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8(10.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (1.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (6.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003efall\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (3.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (6.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (12.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ewinter\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1(2.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (4.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (7.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"8\"\u003e\n \u003cp\u003eThe first symptom of the diagnosis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVision\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1(2.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34 (87.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (2.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (2.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (5.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"8\"\u003e\n \u003cp\u003e0.017\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSensory\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e51 (81.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (6.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (3.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6(9.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003emovement\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14 (100%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eimbalance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (71.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1(14.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (14.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ediplopia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (7.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17 (60.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (3.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (7.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 (21.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUrinary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (100%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eother\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8 (66.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (8.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (8.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (16.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMultiple symp\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (1.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45 (80.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (1.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (5.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7 (12.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"char\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\n \u003cdiv align=\"char\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\n \u003cdiv align=\"char\" class=\"colspec\"\u003e\u003cstrong\u003eTable 2.\u003c/strong\u003e Incidence rate and prevalence of multiple sclerosis according to the studied years in Rafsanjan\u003c/div\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\u0026nbsp;\u003ctable id=\"Taba\" border=\"1\"\u003e\n \u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eYear\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePopulation Size\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNew MS Patients\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eIncidence*(CI95%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCumulative Prevalence\u003c/p\u003e\n \u003cp\u003e*(CI95%)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e252,103\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6.74(4.211\u0026ndash;10.802)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e83.69(73.14\u0026ndash;95.77)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e255,457\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.74(1.328\u0026ndash;5.661)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e91.89(80.87\u0026ndash;104.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e255,735\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10.56 (7.263\u0026ndash;15.375)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e102.44(90.77-115.62)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e263,268\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.32(3.171\u0026ndash;8.935)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e104.83(93.18-117.94)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e266,060\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.26(3.137\u0026ndash;8.842)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e108.99(97.15-122.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e273,902\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.11(3.048\u0026ndash;8.589)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e110.98(99.19-124.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e278,570\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6.10(3.814\u0026ndash;9.784)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e115.23(103.30-128.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e295,603\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.41(3.335\u0026ndash;8.802)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e114.00(102. 47-126.83)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e309,171\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.50(3.438\u0026ndash;8.819)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e114.49(103.18-127.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e319,410\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.19(1.063\u0026ndash;4.529)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e113.02(101.95-125.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003e* \u003cstrong\u003ePer 100,000 population\u003c/strong\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur study evaluated the epidemiology and clinical features of MS in Rafsanjan City, Iran from 2011 to 2020. The incidence rate (4.84 per 100,000) and prevalence rate (97.68 per 100,000) of MS were low compared to other regions[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. MS affects women in early adulthood and urban lifestyles. The representation of married housewives highlights the impact on childbearing years. Sensory dysfunction and vision loss were common initial symptoms. Younger patients had RRMS while older individuals had progressive forms. Factors such as age, sex, marital status, occupation, season of birth, and symptoms were associated with disease pattern.\u003c/p\u003e \u003cp\u003eOur findings are consistent with previous studies that have reported a low incidence and prevalence of MS in Kerman Province[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. One possible explanation for this regional variation is the difference in environmental factors, such as latitude, sunlight exposure, vitamin D levels, and diet[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Kerman Province's location in southeast Iran yields high sun exposure and heat along with arid conditions, which prior studies suggest are protective against MS[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. However, further studies are needed to confirm this hypothesis and to explore other potential factors that may influence MS epidemiology in this region.\u003c/p\u003e \u003cp\u003eWe also observed a female predominance of MS in our study population, with a female-to-male ratio of 4.64. This is similar to the global trend of MS being more common in women than men [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. The reasons for this sex disparity are not fully elucidated, but they may involve hormonal, immunological, genetic, and epigenetic factors [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Some studies have suggested that estrogen may have a neuroprotective role in MS, while testosterone may have an immunomodulatory role [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Moreover, some genes that are involved in MS susceptibility or severity are located on the X chromosome or are influenced by sex hormones [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Additionally, some environmental factors, such as smoking and obesity, may have different effects on MS risk or progression between men and women [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAnother finding of our study was that the mean age of the patients was 39.44\u0026thinsp;\u0026plusmn;\u0026thinsp;9.71 years, and most of them were in the 20\u0026ndash;40 years age group. This is in line with previous studies that have shown that MS typically affects young adults [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. However, we also found that the mean age of male patients was higher than that of female patients, although not significantly. This is contrary to some studies that have reported a lower mean age of onset or diagnosis in men than in women [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. This discrepancy may be due to the small sample size of male patients in our study or to other factors that may affect the age distribution of MS patients in different populations.\u003c/p\u003e \u003cp\u003eWe also found that most of the patients lived in urban areas and were housewives. This may reflect the socio-economic status and lifestyle of our study population. Urbanization may be associated with increased exposure to environmental pollutants or infections that may trigger or exacerbate MS [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Housewives may have less physical activity or social support than other occupations, which may affect their mental health or immune system [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. However, these associations need to be further investigated in future studies.\u003c/p\u003e \u003cp\u003eThe season of birth of the patients was another variable that we examined in our study. We found that most of the patients were born in summer, followed by spring. This is consistent with some studies that have reported a higher risk of MS among people born in summer or spring than among those born in winter or fall [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. One possible explanation for this seasonal effect is the influence of maternal vitamin D levels during pregnancy on fetal immune system development [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. The skin synthesizes vitamin D upon exposure to sunlight and has anti-inflammatory and immunoregulatory properties [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Other Dietary habits, vitamin D levels, rates of infectious triggers like Epstein-Barr virus, genetics, and ancestry within this distinct population likely also play a role.\u003c/p\u003e \u003cp\u003eDietary habits, vitamin D levels, rates of infectious triggers like Epstein-Barr virus, genetics, and ancestry within this distinct population likely also play a role[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan additionalcitationids=\"CR27 CR28 CR29\" citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. The family history of MS was another factor that we considered in our study. We found that only 13.2% of the patients had a positive family history of MS, which is lower than some studies that have reported a family history rate of up to 30% among MS patients [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. This may indicate a lower genetic contribution to MS risk in our study population or a lack of awareness or diagnosis of MS among relatives. However, it is well established that MS has a vital genetic component, with more than 200 genes identified as associated with MS susceptibility or severity[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Therefore, further genetic studies are needed to identify the specific genes or variants involved in MS pathogenesis in our population.\u003c/p\u003e \u003cp\u003eThe initial symptoms and disease course of the patients were also analyzed in our study. We found that sensory symptoms and vision loss were the most common initial manifestations of MS, followed by motor weakness and balance problems. This is similar to previous studies that have reported sensory and visual disturbances as frequent presenting symptoms of MS [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. These symptoms reflect the involvement of the spinal cord, optic nerve, or cerebellum by MS lesions [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. The least common initial symptom in our study was urinary control problems, which may reflect the brainstem or spinal cord involvement by MS lesions [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe disease course of the patients aligned with previous studies, showing that RRMS is the most common form of MS for about 85% of the cases[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. However, our study found RPMS to be more prevalent than PPMS or SPMS, which differs from other studies[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e].. This difference could be due to variations in disease definitions or follow-up periods. We also identified significant associations between disease course and demographic and clinical variables, indicating that these factors influence the natural history or prognosis of MS in different ways. However, further research is needed to understand the underlying mechanisms and causal relationships.\u003c/p\u003e"},{"header":"Limitations","content":"\u003cp\u003eThis study provides valuable insights into MS in Rafsanjan City, but it has limitations. The design prevents longitudinal data on disease progression, which a retrospective cohort study could provide. The data source limits generalizability to the wider population. A larger registry would allow for comparisons with standardized data collection. Existing medical records lack important clinical information. Prospective studies should include comprehensive assessments and patient interviews. The genetic and immunologic profiles are unknown, hindering understanding of the disease. Analyzing markers could reveal differences between populations. More research is needed to understand regional variations and biological determinants. Large-scale collaborative research may identify factors that inform prevention and management strategies.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis cross-sectional study presents significant epidemiological data regarding Multiple Sclerosis (MS) in Rafsanjan City, Iran, spanning from 2011 to 2020. Our findings indicate a relatively low incidence rate of 4.84 per 100,000 individuals and a prevalence rate of 97.68 per 100,000 individuals, suggesting that MS is less prevalent in this region compared to other areas within Iran and globally. Most patients affected by MS were young women under the age of 40 residing in urban settings, aligning with recognized demographic risk factors. While most patients were diagnosed with Relapsing-Remitting MS (RRMS), cases of the relapsing-progressive course were also frequently observed. Sensory and visual symptoms predominated during the onset of the disease. Key factors significantly associated with the course of the disease encompassed age group, gender, marital status, occupation, season of birth, and the manifestation of neurological symptoms at presentation. Notably, the progressive forms of MS tended to manifest in older patients, whereas the relapsing-remitting course was more prevalent in individuals under the age of 40. These discrepancies underscore the potential influence of demographic and early clinical characteristics on long-term prognosis. Furthermore, both environmental and genetic factors may impact MS susceptibility and outcomes within this distinctive population. The underlying reasons for the relative rarity of MS in Rafsanjan City remain unexplained, thereby necessitating further investigation into potentially protective factors, including sunlight exposure, dietary patterns, infections, and ancestral lineage.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMultiple Sclerosis\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCNS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCentral Nervous System\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eRRMS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eRelapsing-Remitting Multiple Sclerosis\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSPMS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSecondary Progressive Multiple Sclerosis\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePPMS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePrimary Progressive Multiple Sclerosis\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePRMS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eProgressive Relapsing Multiple Sclerosis\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCIS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eClinically Isolated Syndrome\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCDTMS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCommittee for Diagnosis and Treatment of Multiple Sclerosis\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eEDSS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eExpanded Disability Status Scale\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eConfidence Interval.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAvailability of Data and Materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are available from Rafsanjan University of Medical Sciences (RUMS), but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are however available from the corresponding author upon reasonable request and with permission of RUMS. Please contact the corresponding author at \u0026ldquo;[email protected]\u0026rdquo; for data access inquiries.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that there is no conflict of interest in relation to the publication of this paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research also did not benefit from any external funding.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of generative AI in scientific writing\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors used \u0026ldquo;Grammarly\u0026rdquo; to check the grammar and originality of this work. They also revised and edited the content as needed and took full responsibility for the publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical Approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study protocol was approved by the Ethics Committee of Rafsanjan University of Medical Sciences (approval number: IR.RUMS.REC.1399.126). All experiments were performed in accordance with relevant guidelines and regulations. Medical records and other patient data were protected in accordance with local data protection standards and were kept private. Participant anonymity was guaranteed, and identifiable information was not disclosed. Informed consent was obtained from all subjects and/or their legal guardian(s) before enrolling them in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone\u003c/p\u003e\n"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eWho gets MS? | National Multiple Sclerosis Society.. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.nationalmssociety.org/What-is-MS/Who-Gets-MS\u003c/span\u003e\u003cspan address=\"https://www.nationalmssociety.org/What-is-MS/Who-Gets-MS\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2023). Accessed.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHarb A, Kishner S. Modified ashworth scale. StatPearls [Internet]. StatPearls Publishing; 2021.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDobson R, Giovannoni G. Multiple sclerosis - a review. 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Neurology. 2014;83 3:278\u0026ndash;86. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1212/WNL.0000000000000560\u003c/span\u003e\u003cspan address=\"10.1212/WNL.0000000000000560\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Multiple Sclerosis, Epidemiology, Rafsanjan","lastPublishedDoi":"10.21203/rs.3.rs-3851895/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3851895/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eMultiple sclerosis (MS) is a chronic inflammatory demyelinating disease of the central nervous system with variable epidemiology and clinical features. This study aimed to examine the epidemiology and clinical characteristics of MS in Rafsanjan City, Iran, from 2011 to 2020.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eA cross-sectional study was conducted on patients diagnosed with MS and registered in the Committee for Diagnosis and Treatment of MS. Data were collected using a revised checklist of demographic and clinical variables. The annual incidence and prevalence of MS were calculated with a 95% confidence interval. Descriptive statistics, t-test, and chi-square or Fisher's exact test were used to analyze the data.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eOut of 361 eligible cases, 220 patients with MS were enrolled. The mean age was 39.44 ± 9.71 years, with 82.3% females and a female-to-male ratio of 4.64. Most patients lived in urban areas (70.5%) and were housekeepers (55.9%). Most births occurred in spring (30.4%) and summer (35.5%). Only 13.2% had a positive family history of MS, and 2.3% had a smoking history. The most common initial symptoms were sensory (28.6%) and visual (17.7%). The dominant disease course was relapsing-remitting MS (RRMS) (79.1%), followed by RPMS (10.9%), PPMS (4.5%), SPMS (4.1%), and CIS (1.4%). The disease course was associated with several demographic and clinical variables. The incidence rate was 4.84 per 100,000, and the prevalence rate was 97.68 per 100,000.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eMS has a low incidence and prevalence rate in Rafsanjan City. MS mainly affects young urban women who are housekeepers. Sensory and visual impairments are the most frequent initial manifestations, and RRMS is the most common disease course.\u003c/p\u003e","manuscriptTitle":"Epidemiology and Clinical Features of Multiple Sclerosis in Rafsanjan City, Kerman Province, Iran: A Cross-Sectional Study from 2011 to 2020","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-01-18 15:44:21","doi":"10.21203/rs.3.rs-3851895/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"0b80e3b0-9708-459a-8beb-52f650986f7e","owner":[],"postedDate":"January 18th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-02-06T19:44:41+00:00","versionOfRecord":[],"versionCreatedAt":"2024-01-18 15:44:21","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3851895","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3851895","identity":"rs-3851895","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}