NON GAUSSIAN LONGITUDINAL ANALYSIS OF PROGRESSION OF DIABETES MELLITUS PATIENTS USING FASTING BLOOD SUGAR LEVEL: A CASE OF DEBRE BERHAN REFERRAL HOSPITAL, ETHIOPIA

Abstract

Diabetes mellitus is a group of metabolic diseases characterized by hyperglycaemia resulting from defects in insulin secretion, insulin action, or both. It is a chronic disease with a high prevalence and growing concern in world wide. There are two Types of diabetes, which are Type I and Type II. A longitudinal data analysis retrospective based study was conducted between 1^stSeptember, 2012 to 30^thAugust 2015 in Debre Berhan referral hospital. The main objective of the study was Non Gaussian longitudinal analysis of progression of Diabetes mellitus patients using fasting blood sugar level count following insulin, metformin and to identify factors predicting the progression of diabetic infection. A total of 248 Diabetes mellitus patients were included in the study whom 111(44.8%) were females and the rest 137(55.8%) were males. The generalized estimating equation would be used to estimate the progression of diabetic infection. The most appropriate working correlation structure was exchangeable correlation selected for this study. This study showed that age, male, primary, urban and the interaction effects of primary and age with time was statistically associated with the progression of fasting blood sugar level over time. Moreover, on average fasting blood glucose decreases in a quadratic pattern over time after patients initiated to insulin and metformin program. Finally we obtained generalized estimating equation model exhibited the best fit for this data with smaller disturbance for their estimated standard error.