Type 2 Diabetes Trends in Semnan Province of Iran and Forecasting until 2025: A Time Series Modeling Study in 2015 - 2020

Abstract

Background: To decrease diabetes prevalence, society will have to make efficient policies. Objectives: This study was done to raise public awareness by estimating the incidence of type 2 diabetes mellitus (T2DM) in Semnan province from 2015 to 2020 and predicting its incidence until 2025. Methods: A Box-Jenkins time series analysis was used in this longitudinal study. The number of referrals with diabetes was estimated month by month from 2015 to 2020. The autoregressive integrated moving average (ARIMA) model parameters were determined using the Time Autocorrelation Function and Partial Autocorrelation Function graphs after using appropriate data transformation methods to create a stationary time series. Dickey-Fuller test was used to perform an accurate examination of the static assumption. ARIMA (3,1,4) was selected as the best fit for the data after analyzing the Akaike statistics of the proposed models. Finally, until 2025, the ARIMA (3,1,4) model projected the number of diabetic patients in Semnan province. Results: The total incidence of T2DM ranged by year was 75203 in 2015 and 165143 in 2020. The time series has an increasing trend, but there is no seasonal variation or periodic pattern. The data about the T2DM incidence indicated an upward trend. Furthermore, the number of T2DM patients is expected to reach 14546.35 (95% CI: 13667.88 - 15374.72) in 2021 and will reach 16956.45 (95% CI: 13499.26 - 19819.49) by the end of 2025. Conclusions: This study reported an increasing trend in T2DM incidence, which necessitates a national commitment to proactive remedies, including public policies and economic incentives for localities to begin diabetes preventive initiatives.