Literature DB >> 30964886

Epidemiology of multiple sclerosis in Iran: A systematic review and meta-analysis.

Milad Azami1, Mohammad Hossein YektaKooshali2, Masoumeh Shohani3, Ali Khorshidi4, Leily Mahmudi5.   

Abstract

BACKGROUND: Multiple sclerosis (MS) is one of the most common neurological disorders and is one of the main causes of disability. The prevalence and incidence of MS in Iran is reported to range from 5.3 to 89/ 100,000and 7 to 148.1/ 100,000, respectively. There are no systematic and meta-analysis studies on MS in Iran. Therefore, this study was conducted to investigate the prevalence and incidence of MS in Iran using meta-analysis.
METHOD: A systematic review of the present study focused on MS epidemiology in Iran based on PRISMA guidelines for systematic review and meta-analysis. We searched eight international databases including Scopus, PubMed, Science Direct, Cochrane Library, Web of Science, EMBASE, PsycINFO, Google Scholar search engine and six Persian databases for peer-reviewed studies published without time limit until May 2018. Data were analyzed using Comprehensive meta-analysis ver. 2 software. The review protocol has been registered in PROSPERO with ID: CRD42018114491.
RESULTS: According to searching on different databases, 39 (15%) articles finalized. The prevalence of MS in Iran was estimated 29.3/ 100,000 (95%CI: 25.6-33.5) based on random effects model. The prevalence of MS in men and women was estimated to be 16.5/ 100,000 (95%CI: 13.7-23.4) and 44.8/ 100,000 (95%CI: 36.3-61.6), respectively. The incidence of MS in Iran was estimated to be 3.4/ 100,000 (95%CI: 1.8-6.2) based on random effects model. The incidence of MS in men was estimated to be 16.5/ 100,000 (95%CI: 13.7-23.4) and the incidence of MS in women was 44.8/ 100,000 (95%CI: 36.3-61.6). The meta-regression model for prevalence and incidence of MS was significantly higher in terms of year of study (p<0.001).
CONCLUSIONS: The results of this study can provide a general picture of MS epidemiology in Iran. The current meta-analysis showed that the prevalence and incidence of MS in Iran is high and is rising over time.

Entities:  

Mesh：

Year:  2019        PMID： 30964886      PMCID： PMC6456231          DOI： 10.1371/journal.pone.0214738

Source DB:  PubMed          Journal:  PLoS One        ISSN： 1932-6203            Impact factor:   3.240


1. Introduction

Multiple sclerosis (MS) is a neurodegenerative and immune-mediated demyelinating disease of the human central nervous system[1-4]. The clinical manifestations of MS include opiate neuritis, central paralysis, sensory imbalance, balance disorder, cognitive impairment, fatigue and sleep disorders[5]. Women are approximately 2–3 times more likely to suffer from MS[6], and most patients are 20 to 50 years old. Residents of Eastern Europe are more likely to suffer from MS compared with residents of Asia, Africa and Latin America[7, 8]. Iran is muslim country in the Middle East with a latitude of 32°00 and a longitude of 53°00 and has 31 provinces. There are various ethnic groups in Iran, including Fars, Kurds, Mazani, Gilak, Lor, Turks, Arabs, and Baluch, and are now united by Iranian culture. According to the World Health Organization (WHO) in 2008, around 1.3 million people had MS worldwide, while in 2013, the prevalence of MS was 73 per 100,000 in the world and was 60 per 100,000 in Iran[9, 10]. At the moment, Iran is well known for its high prevalence of MS in the world, whereas 15 years ago, it was assumed based on the MS slope hypothesis that Iran could be a low-risk area for MS with an incidence of less than 5 per 100,000 people[11-13]. Despite numerous studies, the main cause of MS is still unknown. According to a hypothesis, MS carries out an autoimmune attack against self-myelin or oligodendrocytic antigens by macrophages, deadly T cells, Lymphokines, and antibodies when they enter the brain[14]. A combination of genetic and environmental factors such as latitude, vitamin D use, skin color, migration, meal, smoking, occupational exposure to toxins, stress, or even recent studies of specific viral infections such as Epstein-Barr virus (EBV)[15] and bacterial infections like mycoplasma pneumonia [16, 17] may affect this disease[6, 15–19]. Basic epidemiological information helps to quickly identify, diagnose and control the disease complications[20]. One of the most important goals of meta-analysis, which results from the combination of existing studies, is to increase the volume of samples and the number of studies, to reduce the difference between the available parameters and the confidence interval, which ultimately leads to solving a problem, especially in the field of medicine. In fact, such studies are a vital link between research studies and decision-making at the bedside or policies[21-23]. The prevalence of MS in Iran has been reported to be 5.3–89 per 100,000[2, 5, 10, 11, 13, 21, 22, 24–46]. Considering the above-mentioned issues, controversy in the prevalence of MS, the lack of global access to the precise prevalence of MS in Iran, as well as expressing the final conclusion for policy making and operational planning in Iran, this study was conducted to estimate the prevalence and incidence of MS in Iran by systematically reviewing all available documentations and their combination through meta-analysis.

2. Materials and methods

2.1. Study protocol

The present systematic review focused on MS epidemiology in Iran based on PRISMA guidelines [47](S1 File) for systematic review and meta-analysis. All the steps of research, including search, selection of studies, qualitative assessment, and data extraction were done independently by two researchers. The agreement was reached by group discussion. The protocol of this review registered at: International Prospective Register of Systematic Reviews(PROSPERO) (https://www.crd.york.ac.uk/PROSPERO/) Identifier: CRD42018114491 [48, 49](S2 File).

2.2. Search strategy

The search was performed by two researchers independently. We searched the titles and abstracts of articles in six Persian databases including Scientific Information Database (SID) (http://www.sid.ir/), Barakat Knowledge Network System (http://health.barakatkns.com), (Iranian Research Institute for Information Science and Technology (IranDoc) (https://irandoc.ac.ir), Regional Information Center for Science and Technology (RICST) (http://en.ricest.ac.ir/), Magiran (http://www.magiran.com/), Iranian National Library (http://www.nlai.ir/) and eight international databases including Scopus, PubMed/Medline, Science Direct, Cochrane Library, Web of Science, Embase, PsycINFO as well as Google Scholar search engine for peer-reviewed studies published without time limit until May 2018. The keywords used were 'incidence', 'prevalence', 'epidemiology', 'MS', 'multiple sclerosis' and 'Iran'. Boolean operators (AND & OR) were used to search by a combination of words. A sample of search strategy in PubMed database is shown in Appendix 1. The list of references of the studies was searched manually for additional reports.

2.3. Inclusion criteria (PICO)

Inclusion criteria according to PICO (Problem or Population, Interventions, Comparison and Outcome) [50, 51]: (1) opulation: all Iranian population, in all age ranges and both genders; (2) ntervention: diagnosis of MS by Poser or McDonald criteria for confirmed MS; (3) omparison: variable aimed for incidence and prevalence of MS such as gender, province, year of study and etc; (4) utcome: Estimate the prevalence and incidence of MS.

2.4. Exclusion criteria

The inclusion criteria were all epidemiological studies on MS. The exclusion criteria included: 1. non-random sample size; 2. sample size other than Iranian population; 3. Articles published in languages other than Persian and English; 4. Not relevant to the subject; 5. qualitative studies; case report; review articles, case reports and interventional studies, and 6. duplicate articles.

2.5. Quality assessment

Researchers assessed the quality of the selected articles using a scoring system based on the 8-item the modified Newcastle Ottawa Scale (NOS) for non-randomized studies [52] (S2 File). Each question was given a score between 0 and 1. Points 0–5, 6–7 and 8–9 were considered low quality, moderate quality and high quality, respectively. The minimum score for entering the quantitative meta-analysis process was 5 and the articles that acquired the minimum qualitative assessment score entered the process of data extraction and meta-analysis.

2.6. Screening and data extraction

Two independent researchers (Azami M, YektaKooshali MH) screened all the articles retrieved by the search strategy based on title and abstract for eligibility according to inclusion and exclusion criteria. Any contradiction between the two researchers was discussed and finally, a consensus was reached. In addition, if necessary, the full text was examined further for more clarification at this stage. In the next step, the researchers were provided with the full text of eligible articles. Each qualified full text was reviewed independently by two researchers and a third expert (Expert-epidemiologist) was there to provide consultations on disagreements between the two researchers. Data extraction was done by the researchers using a pre-prepared form. The data for the study included the first author, year of publication, year of study, study setting, location, sample size, geographical area, province, the prevalence of MS and MS diagnostic method, which was extracted independently by two researchers and blinded to the author's name, institute, and journal. If necessity, further information, and raw data were requested by contacting the author (first author, corresponding author or contacting the authors' department) (Table 1).
Table 1

Characteristics of studies into the meta-analysis.

Ref.First author, Published Year *Year of StudyStudy TypePlaceDiagnostic criteriaSample size
[33]Etemadifar M, 20062004–5Cross-sectionalIsfahanMcDonald3923255
[67]Sahraian MA, 20101999–2010Cross-sectionalTehranMcDonald13422366
[55]Elhami SR, 20111989–2009Population basedTehranPoser(up to 2001)McDonald14103853
[36]Heydarpour P, 20131991–2011Population basedTehranMcDonald14103853
[45]Saadatnia M, 20072003–6Cross-sectionalIsfahanMcDonald3923255
[34]Etemadifar M, 20102003–2010Cross-sectionalIsfahanMcDonald4804458
[59]Ghandehari K, 20102009Population basedRazaviKhorasanMcDonald5593079
[59]Ghandehari K, 20102009Population basedNorth KhorasanMcDonald811572
[59]Ghandehari K, 20102009Population basedSouthern KhorasanMcDonald636420
[2]Abedini M, 20082007Cross-sectionalMazandaranMcDonald2893087
[35]Hashemilar M, 20112005–9Population basedEast AzerbaijanMcDonald3724620
[40]Moghtaderi A, 20121996–2006Cross-sectionalSistan and BalouchestanMcDonald1346367
[46]Sharafaddinzadeh N, 20121997–2009Cross-sectionalKhuzestanMcDonald4200000
[31]Etemadifar M, 20132003–2013Population basedIsfahanMcDonald4879312
[62]Kalanie H, 20031996–2001Cross-sectionalTehranPoser
[26]Jajvandian R, 20112005–2011Population basedNorth Khorasan-867727
[54]Ebrahimi HA, 20132013Population basedKerman-2947346
[39]Moghaddam AH, 20132013Population basedKermanMcDonald207192
[68]Saman-Nezhad B,20122012Population basedKermanshah-851405
[25]Majdinasab N, 20122005–2011Population basedKhuzestanMcDonald4531720
[43]Rezaali S, 20132011Population basedQomPoser (up to 2001) andMcDonald1151672
[61]Izadi S, 20152013Population basedFars-4551718
[53]Ashtari F, 20112007Cross-sectionalIsfahan
[37]Maghzi A, 20102003–2007Population basedIsfahanMcDonald’s criteriaand 2005 revisions4559256
[32]Etemadifar M, 2014 (Isfahan)2006–2013Population basedIsfahanNR4879312
[32]Etemadifar M, 2014 (Tehran)2006–2013Population basedTehranNR12183391
[32]Etemadifar M, 2014 (Fars)2006–2013Population basedFarsNR4596658
[32]Etemadifar M, 2014 (Alborz)2006–2013Population basedAlborzNR2412513
[32]Etemadifar M, 2014 (Markazi)2006–2013Population basedMarkaziNR1413959
[32]Etemadifar M, 2014 (ChaharMahaa)2006–2013Population basedChaharMahaal and BakhtiariNR895263
[32]Etemadifar M, 2014 (East Azerbaijan)2006–2013Population basedEast AzerbaijanNR3724263
[32]Etemadifar M, 2014 (Semnan)2006–2013Population basedSemnanNR631218
[32]Etemadifar M, 2014 (Hamadan)2006–2013Population basedHamadanNR1758268
[32]Etemadifar M, 2014 (Qom)2006–2013Population basedQomNR1151672
[32]Etemadifar M, 2014 (West Azerbaijan)2006–2013Population basedWest AzerbaijanNR3080576
[32]Etemadifar M, 2014(Yazd)2006–2013Population basedYazdNR1074428
[32]Etemadifar M, 2014(Kordestan)2006–2013Population basedKordestanNR1493645
[32]Etemadifar M, 2014(Ardabil)2006–2013Population basedArdabilNR1248488
[32]Etemadifar M, 2014 (Kohgiluyeh)2006–2013Population basedKohgiluyeh and Boyer-AhmadNR658621
[32]Etemadifar M, 2014 (Mazandaran)2006–2013Population basedMazandaranNR3073943
[32]Etemadifar M, 2014 (Guilan)2006–2013Population basedGuilanNR2480874
[32]Etemadifar M, 2014 (Kerman)2006–2013Population basedKermanNR2938988
[32]Etemadifar M, 2014 (Khorasan-Razavi)2006–2013Population basedRazavi KhorasanNR5994402
[32]Etemadifar M, 2014 (Bushehr)2006–2013Population basedBushehrNR103949
[32]Etemadifar M, 2014 (Ilam)2006–2013Population basedIlamNR557599
[32]Etemadifar M, 2014 (Khuzestan)2006–2013Population basedKhuzestanNR4531720
[32]Etemadifar M, 2014 (Golestan)2006–2013Population basedGolestanNR1777014
[32]Etemadifar M, 2014 (Lorestan)2006–2013Population basedLorestanNR1754244
[32]Etemadifar M, 2014 (Zanjan)2006–2013Population basedZanjanNR1015734
[32]Etemadifar M, 2014(Kermanshah)2006–2013Population basedKermanshahNR1945227
[32]Etemadifar M, 2014 (Hormozgan)2006–2013Population basedHormozganNR1578183
[32]Etemadifar M, 2014 (North Khorasan)2006–2013Population basedNorth KhorasanNR867727
[32]Etemadifar M, 2014 (South Khorasan)2006–2013Population basedSouth KhorasanNR662534
[32]Etemadifar M, 2014(Qazvin)2006–2013Population basedQazvinNR1201565
[32]Etemadifar M, 2014 (Sistan and Baluchestan)2006–2013Population basedSistan and BaluchestanNR2534327
[44]Saadat SMS, 20132010Cross-sectionalGuilanMcDonald2480874
[42]Raiesi R, 20141991–2011Population basedKohgiluyeh and Boyer-AhmadMcDonald895263
[60]Izadi S, 20152011Population basedFarsNR4596658
[5]Nedjat S, 20062006Population basedTehranNR7803883
[71]Yousefi B, 20172005–2009Population basedEast AzerbaijanMcDonald3724620
[71]Yousefi B, 20172010–2014Population basedEast AzerbaijanMcDonald3909652
[64]Mazdeh M, 20162015–2018Population basedHamadanMcDonald
[70]Tolou-Ghamari Z, 20152010–2014Population basedIsfahanMcDonald4879312
[69]Shahbeigi S, 20122010–2014Population based12 different major provinces of IranMcDonald46695319
[63]Khamarnia M, 20162010Population basedFarsMcDonald4596658
[63]Khamarnia M, 20162011Population basedFarsMcDonald4596658
[63]Khamarnia M, 20162012Population basedFarsMcDonald4596658
[13]Dehghani R, 20152006Population basedAll IranMcDonald70495782
[13]Dehghani R, 20152011Population basedAll IranMcDonald75149669
[57]Eskandarieh Sh, 20172013Population basedTehranMcDonald12559000
[57]Eskandarieh Sh, 20172014Population basedTehranMcDonald12559000
[57]Eskandarieh Sh, 20172014Population basedTehranMcDonald12559000
[66]Sabbagh S, 20172015–2018Population basedKhuzestanMcDonald957133
[65]Mousavizadeh A, 20172015–2018Population basedKohgiluyeh and Boyer-AhmadMcDonald713052
[56]Eskandarieh Sh, 20172015Population basedTehranMcDonald13267637
[58]Eskandarieh Sh, 20182017Population basedTehranMcDonald13441124

NR: Not reported

* Repetitive studies have been included and estimated the prevalence and incidence for more than 1 year and also regions. Each data was considered separately because of assessing the slope of prevalence and incidence in the years and estimating which region is the highest or lowest.

NR: Not reported * Repetitive studies have been included and estimated the prevalence and incidence for more than 1 year and also regions. Each data was considered separately because of assessing the slope of prevalence and incidence in the years and estimating which region is the highest or lowest.

2.7. Data analysis

To evaluate the heterogeneity of the studies, Cochran's Q and I2 tests were used. Heterogeneity was defined as I2> 50% and the Cochran's Q test was defined as < 0.05. Therefore, the random effects model was used to estimate the prevalence and incidence of MS with high heterogeneity. To estimate the effect of gender, we used the total number and the number of events (MS) in men and women groups and we calculated the odds ratio (OR) and 95% CI. In this study, a sensitivity analysis was also performed to verify the stability of the data. In order to find the source of heterogeneity, a subgroup analysis was conducted in terms of geographic area, year of study, province, and study setting while a meta-regression model was used for the prevalence and incidence of MS in terms of year of studies. Begg and Egger’s tests were used to assess publication bias. Data were analyzed using Comprehensive meta-analysis ver. 2 software. P<0.05 was considered significant.

3. Results

3.1. Study characteristics and methodological quality

Of 392 studies found in the initial search using the search strategy, 138 potentially relevant studies were found to be eligible for retrieval and evaluation. By examining the full text of the studies, 65 studies were excluded due to non-MS or non-Iranian patients (27), non-randomized (18) and inadequate data according to the data extraction checklist (14), articles to the editor without original data, review and case report (5) and low quality (1). Finally, 39 articles (included 103 studies for prevalence and 34 studies for incidence) entered the meta-analysis process after qualitative assessment. The flow diagram of the identification and selection of studies is illustrated in (Fig 1) and the characteristics of studies are shown in (Table 1) [2, 5, 13, 25, 26, 31–37, 39, 40, 42–46, 53–71].
Fig 1

Study flow diagram.

3.2. Pooled prevalence of MS and sensitivity analysis

The total heterogeneity was high (I2 = 99.92% and P< 0.001). The prevalence of MS in Iran was estimated to be 29.3/ 100,000 (95% CI: 25.6–33.5) based on random effects model (Fig 2). The lowest and highest prevalence was found in studies in Southern Khorasan in 2009 (5.3/ 100,000) and Isfahan in 2013 (89/ 100,000), respectively (Figs 2 and 3). The sensitivity analysis of the prevalence of MS and its 95% CI was estimated irrespective of one study at a time, and the results showed that the pooled estimate was robust (S1 Fig).
Fig 2

The prevalence of multiple sclerosis in Iran.

Random effect model.

Fig 3

Distribution of MS in Iran based on geographical classification.

High risk 30/100,000 intermediate risk 5-30/100,000 and low risk 5/100,000 (as Wade scaled prevalence of MS globally [72]).

The prevalence of multiple sclerosis in Iran.

Random effect model.

Distribution of MS in Iran based on geographical classification.

High risk 30/100,000 intermediate risk 5-30/100,000 and low risk 5/100,000 (as Wade scaled prevalence of MS globally [72]).

3.3. Subgroup analysis of MS prevalence based on region, province, study design, and year of study

The Subgroup analysis of MS prevalence in Iran is shown in (Table 2) and (S1–S6 Figs). Significant difference was observed in the prevalence of MS in the geographical regions (P< 0.001) (S2 Fig), province (P< 0.001) (S3 Fig), study design (P = 0.015) (S4 Fig), and year of study (P< 0.001) (S5 Fig).
Table 2

MS prevalence based on region, gender, provinces, year of study and design.

VariableStudies (N)*Sample (N)Heterogeneity95% CIPooled(Per 100,000)
MSAllI2P-Value
Region12 different11952446695319--41.2–42.442.4
All Iran25196214564545199.97< 0.00120.4–57.434.2
Center4717422936814905999.94< 0.00128.6–43.135.1
East837562401142199.62< 0.0015.3–18.19.8
North14116403225022699.50< 0.00118.7–32.024.5
South13174664050454499.69< 0.00125.6–44.633.8
West742371253478698.01< 0.00122.4–41.930.6
Test for subgroup differences: Q = 45.66, df(Q) = 6, P< 0.001
GenderMale31257117690708294.77<0.000113.3–20.516.5
Female31743567543213199.87< 0.00136.2–55.444.8
Rate ratio of female to male: OR = 3.01 (2.79–2 = 3.24, P<0.001)
Province12 different major provinces of Iran11952446695319--41.2–42.441.8
Alborz117372412513--68.7–75.572.0
All Iran25196214564545199.97< 0.00120.4–57.434.2
Ardabil15061248488--37.1–44.240.5
Bushehr133103949--22.6–44.731.7
Chahar Mahaal and Bakhtiari1537895263--55.1–65.360.0
East Azerbaijan46971150831599.74< 0.00125.8–67.441.7
Fars4118671844169299.12< 0.00152.3–76.963.4
Golestan13731777014--19.0–23.221.0
Guilan21643496174897.19< 0.00124.5–43.932.8
Hamadan19851758268--52.6–59.656.0
Hormozgan13001578183--17.0–21.319.0
Ilam1162557599--24.9–33.929.1
Isfahan7213023255901599.79< 0.00143.5–79.358.7
Kerman32102608516885.39< 0.00131.0–40.435.4
Kermanshah2818389045486.51< 0.00117.4–25.321.0
Khuzestan431641429555298.11< 0.00115.3–26.220.1
Kohgiluyeh and Boyer-Ahmad41163203030296.72< 0.00140.3–76.855.7
Kordestan16121493645--37.9–44.441.0
Lorestan13511754244--18.0–22.220.0
Markazi18621413959--57.0–65.261.0
Mazandaran21781599637599.43< 0.00114.4–53.927.9
North Khorasan3332254702692.70< 0.0018.3–18.812.5
Qazvin11921201565--13.9–18.416.0
Qom21180230334400.6048.8–54.251.2
Razavi Khorasan228791158748199.82< 0.0017.9–59.021.6
Semnan1353631218--50.4–62.155.9
Sistan and Balouchestan57711176140675.34< 0.0015.6–7.56.5
South Khorasan2140129895499.77< 0.0013.2–27.39.3
Tehran2814627032261171899.96< 0.00120.7–36.727.6
West Azerbaijan113093080576--20.7–36.727.6
Yazd14401074428--37.3–45.041.0
Zanjan11931015734--16.5–21.919.0
Test for subgroup differences: Q = 2559.92, df(Q) = 32, P< 0.001
Year of study< 1990211101753955269.130.0725.7–7.06.3
1990–1994543824722214497.14< 0.0017.6–10.89.1
1995–1999597635325198198.62< 0.00115.1–21.317.9
2000–20045204126095502999.27< 0.00127.9–38.632.8
2005–2009205854518227742899.82< 0.00115.5–23.619.1
2010–20145115169028016572699.81< 0.00135.8–45.840.5
2015–20184369122837894699.76< 0.00150.7–85.065.6
Test for subgroup differences: Q = 744.07, df(Q) = 6, P< 0.001
Study designPopulation based8226617562782110299.83< 0.00127.0–35.931.1
Cross-sectional10166394196970499.92< 0.00111.7–27.317.9
Test for subgroup differences: Q = 5.89, df(Q) = 1, P = 0.015

N: Number; CI: confidence interval

* Some studies have been included and estimated the prevalence and incidence for more than 1 year and also regions. Each data was considered separately because of assessing the slope of prevalence and incidence in the years and estimating which region is the highest or lowest.

N: Number; CI: confidence interval * Some studies have been included and estimated the prevalence and incidence for more than 1 year and also regions. Each data was considered separately because of assessing the slope of prevalence and incidence in the years and estimating which region is the highest or lowest.

3.4. Prevalence of MS based on gender

The prevalence of MS in men and women was estimated to be 16.5/ 100,000 (95% CI: 13.7–23.4) and 44.8/ 100,000 (95% CI: 36.3–61.6), respectively (Fig 4). The OR female/ male of MS prevalence was estimated to be 3.01 (95% CI: 2.79–3.24, P< 0.001) (Table 2) (S6 Fig).
Fig 4

The prevalence of multiple sclerosis in men (A) and women (B). Random effect model.

The prevalence of multiple sclerosis in men (A) and women (B). Random effect model.

3.5. Pooled incidence of MS and sensitivity analysis

The total heterogeneity was high (I2 = 99.96% and P< 0.001). The incidence of MS in Iran was estimated according to 34 studies to be 3.4/ 100,000 (95% CI: 1.8–6.2) based on random effects model (Fig 5). The sensitivity analysis results are shown in (S7 Fig).
Fig 5

The incidence of multiple sclerosis in Iran.

Random effect model.

The incidence of multiple sclerosis in Iran.

Random effect model.

3.6. Subgroup analysis of MS incidence based on region, province, study design, and year of study

The Subgroup analysis of MS incidence in Iran is shown in (Table 3). Significant difference was observed in the prevalence of MS in the geographical regions (P < 0.001) (S8 Fig), province (P< 0.001) (S9 Fig) and year of study (P< 0.001) (S10 Fig), but study design was no significant difference (P = 0.123) (S11 Fig).
Table 3

MS incidence based on region, gender, provinces, year of study and design.

VariableStudies (N)*Sample (N)Heterogeneity95% CIPooled(Per 100,000)
MSAllI2P-Value
RegionCenter264113428452233399.97< 0.0012.0–7.63.9
East494922707967.800.0250.7–1.41.0
South410021786023398.43< 0.0012.9–8.24.9
Test for subgroup differences: Q = 28.94, df(Q) = 2, P< 0.001
GenderMale31215813655542799.87< 0.0011.0–1.41.2
Female31761567543213199.87< 0.00139.3–59.148.2
Rate ratio of female to male: OR = 3.04 (2.85–3.24, P< 0.001)
ProvinceFars39081358525497.40< 0.0014.2–9.66.3
Isfahan2574880256798.81< 0.0012.4–13.55.7
Khuzestan1944274979--1.8–2.72.2
Sistan and Balouchestan494922707967.800.0250.7–1.41.0
Tehran244056027571976699.97< 0.0011.8–7.63.7
Test for subgroup differences: Q = 49.07, df(Q) = 4, P< 0.001
Year of study< 19901608769776--0.5–0.90.7
1990–199455864722214493.90< 0.0010.8–1.61.2
1995–1999514025325198179.37< 0.0012.3–2.92.6
2000–2004629196529190790.76< 0.0013.9–5.04.4
2005–20091134747670733798.09< 0.0012.2–3.72.8
2010–20145138874692537699.96< 0.0012.0–56.710.6
2015–201811990213441124--146.0–150.1148.1
Test for subgroup differences: Q = 10943.73, df(Q) = 6, P< 0.001
Study designPopulation based274146828930502098.66< 0.0012.0–7.74.0
Cross-sectional77622230462599.97< 0.0010.9–3.81.8
Test for subgroup differences: Q = 2.38, df(Q) = 1, P = 0.123

N: Number; CI: confidence interval

* Some studies have been included and estimated the prevalence for more than 1 year and also regions. Each data was considered separately because of assessing the slope of prevalence in the years and estimating which region is the highest or lowest.

N: Number; CI: confidence interval * Some studies have been included and estimated the prevalence for more than 1 year and also regions. Each data was considered separately because of assessing the slope of prevalence in the years and estimating which region is the highest or lowest.

3.7. Incidence of MS based on gender

The incidence of MS in men was estimated to be 16.5/ 100,000 (95% CI: 13.7–23.4) and the incidence of MS in women was 44.8/ 100,000 (95% CI: 36.3–61.6) (Fig 6). The OR female/male of MS incidence was estimated to be 3.04 (2.85–3.24, P< 0.001) (Table 2) (S12 Fig).
Fig 6

The incidence of multiple sclerosis in men (A) and women (B). Random effect model.

The incidence of multiple sclerosis in men (A) and women (B). Random effect model.

3.8. Meta-regression

The meta-regression model for prevalence and incidence of MS was significantly higher in terms of year of study [(meta-regression coefficient: 0.065, 95% CI 0.053 to 0.077, P< 0.001) for prevalence of MS and (meta-regression coefficient: 0.100, 95% CI 0.063 to 0.136, P< 0.001) for incidence of MS] (Fig 7). Moreover, the meta-regression model for prevalence and incidence of MS based on the year was also studied in men [(meta-regression coefficient: 0.202, 95% CI 0.157 to 0.248, P< 0.001) for prevalence of MS and (meta-regression coefficient: 0.065, 95% CI 0.046 to 0.0840, P< 0.001) for incidence of MS] and women [(meta-regression coefficient: 0.216, 95% CI 0.169 to 0.264, P< 0.001) for prevalence of MS and (meta-regression coefficient: 0.219, 95% CI 0.176 to 0.263, P< 0.001) for incidence of MS] and it was increasing significantly (S13 and S14 Figs).
Fig 7

Meta-regression of MS in Iran according to year of studies.

Prevalence (A) and incidence (B).

Meta-regression of MS in Iran according to year of studies.

Prevalence (A) and incidence (B).

3.9. Publication bias

Publication bias in the studies of incidence (Egger< 0.001, and Begg’s< 0.001) and prevalence (Egger< 0.001, and Begg’s = 0.045) of MS was significant (S15 Fig).

4. Discussion

The present study is the first systematic review and meta-analysis on the epidemiology of MS in Iran. According to the results of the present meta-analysis, the prevalence and incidence of MS in Iran is estimated to be 29.3/ 100,000 and 3.4/ 100,000, which is more than some Middle Eastern countries (Oman, Libya, Lebanon, Iraq, Kuwait, and Tunisia)[73-78] and less than some other countries (UAE, city of Amman in Jordan and Saudi Arabia) [79-81]. However, it should be noted that most studies in our meta-analysis process were based on data from MS centers, and the lack of recording the information of some people with MS was due to non-compulsory membership in this center and the real prevalence of MS is expected to be greater than this figure. In 2016, Nasr et al. [41] investigated the prevalence of MS among Iranian migrants. The prevalence of MS among Iranian migrants was 21/ 100,000 in Mumbai (India) in 1985 and 433/ 100,000 in British Columbia (Canada) in 2012. In five different studies, the MS prevalence in the studied areas was reported from 1.33 in Mumbai (India) to 240 in British Columbia (Canada)[82-86]. The acculturative stress in migrants may help to relate the onset of illness and migration. The acculturative stress is the tension or pressure associated with the experience of a second culture that may have adverse effects on physical or mental health [87] and shows that stress and anxiety have a potential role in MS development[88]. Nish et al. recently showed in a study that acculturative stress is related to higher inflammatory markers in a Chinese migrant population[89]. In the past, the behavior and distribution of MS disease were associated with latitude and was reported to be lower in areas with a higher latitude. Overall, according to a report by WHO in 2008, the highest reported MS prevalence was in North America and Europe, and the lowest reported MS prevalence was in countries near the equator. However, this pattern is changing and areas with lower prevalence are changing to areas with higher prevalence[10, 15, 18, 90]. In the present study, there was a significant difference between the five geographical regions of Iran in terms of the prevalence and incidence of MS based on the results of the initial studies. Based on the present meta-analysis, the OR of prevalence and incidence of MS in women was 2.52 and 3.04, respectively compared with men, which was a significant relationship (P< 0.001). This result is similar to the results in previous studies [21, 38, 55, 91–93]. According to the meta-regression model, the prevalence and incidence of MS in Iran increased significantly (p< 0.001) with an increase in year of studies[21, 38, 91–93]. Various factors such as the lack of prevention and screening programs can be important factors in increasing the prevalence of the disease. In addition to changes in the pattern of food consumption, food quality has also changed a lot recently [10, 13, 30]. According to the WHO, the use of tobacco, fat, salt and sugar higher than the limit in foods that cause overweight and obesity, industrialization, urbanization and economic development can play a significant role in the development of chronic diseases[94]. In a study in the United States on 8983 MS patients, it was found that 25% of patients were obese and 31.3% were overweight. In addition, 18.2% were at risk of alcohol misuse by themselves or their relatives[95]. Since there are no particular laws and regulations on the purchase and use of chemicals in Iran, they are easily accessible to people and this may increase the risk of diseases such as MS, which is caused by exposure to chemicals. Although in some studies, contact with industrial solvents has been identified as a risk factor for MS, it has not yet been confirmed for sure[96-98]. The existence of particles such as PM10 in the air of Iranian cities[10, 28, 30, 99–102], natural radiation of radon from soil (Ramsar, Iran) [103] and unsupervised use of decorative stones and granite in Iran[27, 104] may increase the risk of MS. However, few studies have been conducted regarding the relationship between the above parameters and MS. According to the Ministry of Health in Iran, the rate of smoking has risen to about 60 billion cigarettes per year[29, 105]. Inhaling cigarette smoke exacerbates the effect on chronic diseases [106, 107]. According to an ecological study by Dehghani et al. in Iran, the prevalence of illness is higher in provinces where cigarette smoking is higher among males[13]. Since cigarette smoking increases the frequency and duration of respiratory infections and it causes MS relapse[37], the risk of cigarette smoking for MS with an OR of 1.55, 95% CI [1.48–1.62], P<0.001 was confirmed in the recent meta-analysis. According to the WHO, the prevalence of MS is higher in countries with higher income levels. However, the diseases may progress more in less developed countries due to less access to diagnostic facilities, although the disparity is so high that scarce diagnostic facilities cannot be considered as the main factor[108]. Studies have shown that vitamin D deficiency is inversely related to the risk of MS [109, 110] and its deficiency is an epidemic, which affects 20–25% of the population in Asia, America, Canada, Europe and Australia[111]. This is becoming acuter in the Middle East because of changes in lifestyle conditions and less sunlight[112]. Systematic reviews and meta-analyses in Iran have reported a high prevalence of vitamin D deficiency[91, 92]. The period of MS is often unpredictable, but some factors can predict a patient's prognosis. The indicators of a good prognosis can be female gender, those with a history of disease before the age of 35, those who were only attacked in one area of the brain, those who had no brain stem involvement and patients who had recovered after the attacks[10]. To achieve successful symptom control, multiple controls are needed to prevent or stop the symptoms. Effective communication, training, exercise, professional support, and pharmacological interventions are vital for effective control of multiple sclerosis symptoms.

5. Limitations

1. The insensitivity of internal databases to operators “AND” and “OR” to search for the combination. 2. Since Tehran is the main medical center of many cities and provinces, patients in the studies in Tehran, are not just from Tehran. 3. No separation of rural and urban prevalence of MS

6. Conclusion

The present meta-analysis showed that the prevalence and incidence of MS in Iran is high (as Wade scaled prevalence of MS globally[72]) and is rising over time. The results of this study provide useful information for neurologists and health policy makers and can provide a general overview of MS epidemiology in Iran. Exp. 'Epidemiology' Exp.'Prevalence' Exp.'Incidence’' Exp.MS' Exp.'Multiple Sclerosis ' Exp.'Iran' 1 OR 2 OR 3 4 OR 5 7 AND 8 AND 9

PRISMA checklist.

(DOC) Click here for additional data file.

The review protocol which has been registered in PROSPERO International Prospective Register of Systematic Reviews.

(PDF) Click here for additional data file.

Newcastle-Ottawa scale checklist.

(PDF) Click here for additional data file.

Sensitivity analysis for prevalence of multiple sclerosis in Iran.

(TIF) Click here for additional data file.

Subgroup analysis for multiple sclerosis prevalence based on region.

(TIF) Click here for additional data file.

Subgroup analysis for multiple sclerosis prevalence based on province.

(TIF) Click here for additional data file.

Subgroup analysis for multiple sclerosis prevalence based on study design.

(TIF) Click here for additional data file.

Subgroup analysis for multiple sclerosis prevalence based on study year.

(TIF) Click here for additional data file. The OR female to male of MS prevalence (A) and incidence (B). (TIF) Click here for additional data file. (TIF) Click here for additional data file.

Subgroup analysis for multiple sclerosis incidence based on region.

(TIF) Click here for additional data file.

Subgroup analysis for multiple sclerosis incidence based on province.

(TIF) Click here for additional data file.

Subgroup analysis for multiple sclerosis incidence based on study year.

(TIF) Click here for additional data file.

Subgroup analysis for multiple sclerosis incidence based on study design.

(TIF) Click here for additional data file.

The OR female/male of MS incidence.

(TIF) Click here for additional data file. Prevalence of Multiple Sclerosis in Iran in terms of men (A) and women (B). (TIF) Click here for additional data file. Incidence of Multiple Sclerosis in Iran in terms of men (A) and women (B). (TIF) Click here for additional data file. Publication bias for prevalence studies (A) and update (B) multiple sclerosis in Iran. (TIF) Click here for additional data file.
  75 in total

1.  Abstracts of the 5th Joint Triennial Congress of the European and Americas Committees for Treatment and Research in Multiple Sclerosis. October 19-22, 2011. Amsterdam, The Netherlands.

Authors: 
Journal:  Mult Scler       Date:  2011-10       Impact factor: 6.312

Review 2.  Multiple sclerosis: geoepidemiology, genetics and the environment.

Authors:  Ron Milo; Esther Kahana
Journal:  Autoimmun Rev       Date:  2009-11-20       Impact factor: 9.754

Review 3.  Epidemiology of Toxoplasma gondii among blood donors in Iran: A systematic review and meta-analysis.

Authors:  Akram Mansouri; Mohammad Reza Adhami Mojarad; Gholamreza Badfar; Lila Abasian; Shoboo Rahmati; Wesam Kooti; Mohammad Hossein YektaKooshali; Ali Soleymani; Milad Azami
Journal:  Transfus Apher Sci       Date:  2017-03-29       Impact factor: 1.764

4.  Prevalence and pattern of multiple sclerosis in Benghazi, north-eastern Libya.

Authors:  K Radhakrishnan; P P Ashok; R Sridharan; M E Mousa
Journal:  J Neurol Sci       Date:  1985-08       Impact factor: 3.181

5.  Sharp increase in the incidence and prevalence of multiple sclerosis in Isfahan, Iran.

Authors:  Masoud Etemadifar; Amir-Hadi Maghzi
Journal:  Mult Scler       Date:  2011-04-01       Impact factor: 6.312

6.  Increasing female preponderance of multiple sclerosis in Isfahan, Iran: a population-based study.

Authors:  A H Maghzi; H Ghazavi; M Ahsan; M Etemadifar; Sa Mousavi; F Khorvash; A Minagar
Journal:  Mult Scler       Date:  2010-01-19       Impact factor: 6.312

7.  Prevalence study of neurologic disorders in Kelibia (Tunisia).

Authors:  N Attia Romdhane; M Ben Hamida; A Mrabet; A Larnaout; S Samoud; A Ben Hamda; M Ben Hamda; S Oueslati
Journal:  Neuroepidemiology       Date:  1993       Impact factor: 3.282

8.  Acculturative stress and psychotic-like experiences among Asian and Latino immigrants to the United States.

Authors:  Jordan E Devylder; Hans Y Oh; Lawrence H Yang; Leopoldo J Cabassa; Fang-Pei Chen; Ellen P Lukens
Journal:  Schizophr Res       Date:  2013-08-07       Impact factor: 4.939

9.  Air pollution and non-respiratory health hazards for children.

Authors:  Roya Kelishadi; Parinaz Poursafa
Journal:  Arch Med Sci       Date:  2010-09-07       Impact factor: 3.318

10.  Epidemiology of multiple sclerosis in Qom: Demographic study in Iran.

Authors:  Saeed Rezaali; Ahad Khalilnezhad; Abdorreza Naser Moghadasi; Samira Chaibakhsh; Mohammad Ali Sahraian
Journal:  Iran J Neurol       Date:  2013
View more
  18 in total

1.  Letter to the Editor: Sexual Support for Iranian Women with Multiple Sclerosis During Treatment Process: Sufficient or Insufficient?

Authors:  Vida Ghasemi; Masoumeh Simbar; Seyed Massood Nabavi; Giti Ozgoli; Hamid Alavi Majd
Journal:  Int J MS Care       Date:  2021-06-17

2.  Prevalence of Multiple Sclerosis (MS) in Zanjan Province of Iran.

Authors:  Mahsa Ghajarzadeh; Abbas R Foroushani; Parviz Ghezelbash; Abdoreza Ghoreishi; Mehdi Maghbooli; Mehran Yousefi; Babak K Rahgoshai; Farhad G Maemodan; Mehdi Mohammadifar; Mohammad A Sahraian
Journal:  Int J Prev Med       Date:  2020-08-06

3.  Seroprevalence of anti-Toxocara antibody among multiple sclerosis patients: a case-control study.

Authors:  Nastaran Khalili; Neda Khalili; Ali Nickhah; Bahman Khalili
Journal:  J Parasit Dis       Date:  2019-10-29

4.  Temporal trends of incidence and prevalence of multiple sclerosis in Razavi Khorasan Province, Northeast Iran.

Authors:  Mohammad Sarmadi; Hanie Saravani; Omid Azizi; Fereshteh Najafi; Mostafa Hadei; Jalil Momeni; Edris Bazrafshan
Journal:  Neurol Sci       Date:  2021-05-03       Impact factor: 3.307

5.  Explaining the facilitators of quality of life in patients with multiple sclerosis: a qualitative study.

Authors:  Atefeh Homayuni; Sedigheh Abedini; Zahra Hosseini; Masoud Etemadifar; Amin Ghanbarnejad
Journal:  BMC Neurol       Date:  2021-05-11       Impact factor: 2.474

6.  Effectiveness of massage therapy on fatigue and pain in patients with multiple sclerosis: A systematic review and meta-analysis.

Authors:  Shahin Salarvand; Mohammad Eghbal Heidari; Kazem Farahi; Erfan Teymuri; Mohammad Almasian; Saeid Bitaraf
Journal:  Mult Scler J Exp Transl Clin       Date:  2021-06-14

7.  Self-Care Practices and Related Factors in Patients with Multiple Sclerosis (MS) Based on the Health Belief Model.

Authors:  Hajar Habibi; Behnaz Sedighi; Yunes Jahani; Marziyeh Hasani; Abedin Iranpour
Journal:  J Caring Sci       Date:  2021-05-24

8.  Multiple Sclerosis in the Emirati Population: Onset Disease Characterization by MR Imaging.

Authors:  Manzoor Ahmed; Ruqqiya Mir; Mustafa Shakra; Safana Al Fardan
Journal:  Mult Scler Int       Date:  2019-11-25

9.  Clinical Characteristics and Disability Progression of Early- and Late-Onset Multiple Sclerosis Compared to Adult-Onset Multiple Sclerosis.

Authors:  Omid Mirmosayyeb; Serge Brand; Mahdi Barzegar; Alireza Afshari-Safavi; Nasim Nehzat; Vahid Shaygannejad; Dena Sadeghi Bahmani
Journal:  J Clin Med       Date:  2020-05-02       Impact factor: 4.241

10.  Assessment of mental health, knowledge, and attitude of patients with multiple sclerosis and neuromyelitis optica spectrum disorder in response to 2019 novel coronavirus.

Authors:  Vahid Shaygannejad; Alireza Afshari-Safavi; Boshra Hatef
Journal:  Neurol Sci       Date:  2020-11-20       Impact factor: 3.830
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.