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Published on: December 9, 2015
Multiple sclerosis projection in Tehran, Iran using Bayesian structural time series
Payam Amini1, Amir Almasi-Hashiani2, Mohammad Ali Sahraian3
1Department of Biostatistics and Epidemiology, School of Public Health, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran.
Background:
The prevalence of Multiple Sclerosis (MS) has been increasing worldwide and the highest prevalence ratio among Asian countries was reported in Iran. This study aims to estimate the increase in MS occurrence during more than three decades in Tehran and forecast the future condition of the disease using time series approaches for the next ten years.
Methods:
The cross-sectional study was conducted from 1999 to 2019 based on records of MS cases from Iranian MS Society (IMSS) registry system. The prevalence was estimated using population data presented by the Statistical Centre of Iran. Through Bayesian Structural Time Series (BSTS) model, we want to predict the prevalence of familial and sporadic MS in the next ten years. .
Results:
Among 22,421 cases with MS, 16,831 (75.1 %) were female and 5589 (24.9 %) were male. Female to male ratio was 3.0:1 and the number of familial MS cases were 2982 (13.3 %) of subjects. Female gender was less responsible for higher rate of MS in familial definition (beta = 0.020) in comparison to sporadic cases (beta = 0.034). Forecasting by BSTS revealed an increase in MS prevalence for the next ten years so that the prevalence rate for total, familial and sporadic MS respectively begins with 189.50 (183.94-195.14), 25.69 (24.97-26.45) and 163.74(159.06-168.57) in 2020 and ends with 220.84 (171.48-266.92), 30.79 (24.16-37.15), and 189.33(146.97-230.19) in 2029.
Conclusions:
According to the findings, MS prevalence increased during three decades and it will increase over the next ten years. Tehran province is one of the regions with highest MS prevalence in Asia. The results of present study indicated that females are at higher risk for MS than males in both sporadic and familial MS.
