Evidence map›Paper›PMID 34376167›Full record

ArticleBMC neurology2021

Multiple sclerosis incidence rate in southern Iran: a Bayesian epidemiological study.

Naeimehossadat Asmarian, Zahra Sharafi, Amin Mousavi, Reis Jacques, Ibon Tamayo, Marie-Abèle Bind, Marzie Abutorabi-Zarchi, Mohammad Javad Moradian, Sadegh Izadi

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC neurology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.2field-weighted citation impact, top 23% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 10 citations in OpenAlex.

  1. Trial
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 6 institutions in 4 countries.

Naeimehossadat Asmarian *Anesthesiology and Critical Care Research Center, Shiraz University of Medical Sciences, Shiraz, Iran.
Zahra Sharafi *Health Promotion Research Center, Zahedan University of Medical Sciences, Zahedan, Iran. Zahra10926@gmail.com.
Amin MousaviDepartment of Educational Psychology and Special Education, College of Education, University of Saskatchewan, Saskatoon, Canada.
Reis JacquesService de Neurologie, Centre Hospitalier Universitaire, Hôpital de Hautepierre, 1, avenue Molière, 67200, Strasbourg, France.
Ibon TamayoDepartment of Statistics, Faculty of Arts and Science, Harvard University, Cambridge, MA, USA.
Marie-Abèle BindDepartment of Statistics, Faculty of Arts and Science, Harvard University, Cambridge, MA, USA.
Marzie Abutorabi-ZarchiDepartment of neurology, Faculty of Medicine, Shahid Sadoughi University of Medical Sciences, Yazd, IR, Iran.
Mohammad Javad MoradianTrauma Research Center, Shahid Rajaee (Emtiaz) Trauma Hospital, Shiraz University of Medical Sciences, Shiraz, Iran.
Sadegh IzadiClinical Neurology Research Center, Shiraz University of Medical Sciences, Shiraz, Iran.
Shiraz University of Medical Sciences · IRHarvard University · USHôpital d'Hautepierre · FRShahid Sadoughi University of Medical Sciences and Health Services · IRUniversity of Saskatchewan · CAZahedan University of Medical Sciences · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMultiple Sclerosis (MS) remains to be a public health challenge, due to its unknown biological mechanisms and clinical impacts on young people. The prevalence of this disease in Iran is reported to be 5.30 to 74.28 per 100,000-person. Because of high prevalence of this disease in Fars province, the purpose of this study was to assess the spatial pattern of MS incidence rate by modeling both the associations s of spatial dependence between neighboring regions and risk factors in a Bayesian Poisson model, which can lead to the improvement of health resource allocation decisions.

methodData from 5468 patients diagnosed with MS were collected, according to the McDonald's criteria. New cases of MS were reported by the MS Society of Fars province from 1991 until 2016. The association between the percentage of people with low vitamin D intake, smoking, abnormal BMI and alcohol consumption in addition to spatial structure in a Bayesian spatio-temporal hierarchical model were used to determine the relative risk and trend of MS incidence rate in 29 counties of Fars province.

resultsCounty-level crude incidence rates ranged from 0.22 to 11.31 cases per 100,000-person population. The highest relative risk was estimated at 1.80 in the county of Shiraz, the capital of Fars province, while the lowest relative risk was estimated at 0.11 in Zarindasht county in southern of Fars. The percentages of vitamin D supplementation intake and smoking were significantly associated with the incidence rate of MS. The results showed that 1% increase in vitamin D supplementation intake is associated with 2% decrease in the risk of MS and 1% increase in smoking is associated with 16% increase in the risk of MS.

conclusionBayesian spatio-temporal analysis of MS incidence rate revealed that the trend in the south and south east of Fars province is less steep than the mean trend of this disease. The lower incidence rate was associated with a higher percentage of vitamin D supplementation intake and a lower percentage of smoking. Previous studies have also shown that smoking and low vitamin D, among all covariates or risk factors, might be associated with high incidence of MS.

Indexed as

Multiple SclerosisAdolescentBayes TheoremEpidemiologic StudiesHumansIncidenceIranBayesian spatio-temporal modelIncidence rateMultiple sclerosis

Identifiers

PMID34376167
PMCPMC8353854
OpenAlexW3111303207

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.