Time-trend analysis and developing a forecasting model for the prevalence of multiple sclerosis in Kohgiluyeh and Boyer-Ahmad Province, southwest of Iran.

OBJECTIVE: This study was designed and implemented to assess the current situation and to estimate the time trend of multiple sclerosis (MS), as well as to explain potential factors associated with such a trend.

METHODS: This longitudinal study was carried out based on analysis of the data from the monitoring and treatment surveillance system for 421 patients with MS in Kohgiluyeh and Boyer-Ahmad Province, Iran, from 1990 to 2015. To this end, curve estimation approach was used to investigate the changes in prevalence and incidence of the disease, and univariate time series model analysis was applied in order to estimate the disease incidence in the next 10 years.

RESULTS: The mean and standard deviation of age were 29.78 and 8.5 years at the time of diagnosis, and the mean and 95% confidence interval of age were 29.18 (28.86-30.77) and 29.68 (28.06-31.30) at the time of diagnosis for women and men, respectively. The sex ratio (males to females) was estimated as 3.3, and the prevalence of the disease was estimated as 60.14 in 100,000 people. The diagram of the 35-year trend of the disease indicated three distinct patterns with a tendency to increase in recent years.

CONCLUSION: The prevalence and incidence trend of the disease in the study population is consistent with regional and global changes. Climatic and environmental factors such as extreme weather changes, dust particles, expansion of the application of new industrial materials, and regional wars with potential use of banned weapons are among the issues that may, in part, be able to justify the global and regional changes of the disease. Predictive models indicate a growing trend of the disease, highlighting the need for more regular monitoring of the disease trend in upcoming years.