Using the generalized linear Model (GLM) to model (specific) chronic diseases

Abstract

As per the World Health Organization, chronic diseases rank highly in incidence, prevalence, and mortality on a global scale with around 60% of the 56.5 million total global deaths in 2001. Among the most prevalent of the chronic diseases is diabetes. Diabetes is rapidly increasing in its rates of incidence and mortality. It was ranked as the seventh leading cause of mortality in 2016, despite the fact that it was not even featured in the top 10 list in the year 2000. Furthermore, according to the International Diabetes Federation there are around 552,400 diagnosed cases of diabetes in Kenya. It is evident fi"om the above that diabetes is a serious and prevalent chronic disease in the countly. As a result, the aim of this research project is to mod~l and perform a regression analysis on diabetes using Kenyan data. The modeling process was done using a Generalized Linear Model. The estimators are expected to display optimal propetties since GLMs use the MLE method of parameter estimation. Once the model was completed the model diagnosis displayed a significant R2, suboptimum deviances and a high AIC value. In conclusion, the most significant ,risk factors of diabetes in the country are high blood pressure, age, gender, and level of education.