Open AccessMathematical Regression Models for Analyzing and Forecasting Diabetes prevalence in Oman
Author(s) -
Jabar H. Yousif
Publication year - 2021
Publication title -
applied computing journal
Language(s) - English
Resource type - Journals
ISSN - 2788-9688
DOI - 10.52098/acj.202132
Subject(s) - diabetes mellitus , blindness , productivity , medicine , work (physics) , regression analysis , environmental health , econometrics , computer science , gerontology , risk analysis (engineering) , actuarial science , optometry , mathematics , economic growth , economics , engineering , machine learning , mechanical engineering , endocrinology
Diabetes mellitus has a significant impact on people's lives and drugs financial burden. On the other hand, diabetes also has substantial economic effects on countries and national health systems. Most countries spend between 5% and 20% of their total health expenditures on diabetes. This is due to the increased use of health services, lack of productivity, and the long-term demand for complications associated with diabetes, such as kidney failure, blindness, and heart problems. This is why diabetes poses a significant challenge to healthcare systems and hinders sustainable economic development. This work is concerned with proposing mathematical models characterized by accuracy and ease in predicting the number of diabetics type 2 in the Sultanate of Oman. By analyzing the proposed mathematical models of the current work (1, 2, and 3), it was found that the proposed mathematical model in Equation 6 can accurately predict the number of diabetics in Oman up to 2050. In order to test the model's accuracy and validity, we revised it with actual data. The results prove the accuracy of the proposed model in predicting future data of 99%. Lastly, several recommendations were recorded that could help to reduce the prevalence of diabetes type 2 in Oman.