Gaussian Longitudinal Analysis of Diabetes Mellitus Patients

Diabetes mellitus is a metabolic disorder where by glucose cannot effectively get transported out of the blood. A longitudinal data analysis retrospective based study was conducted between 1st September, 2012 to 30th August 2015 in Debre Berhan referral hospital. The main objective of the study was Gaussian longitudinal analysis of progression of DM patients using fasting blood sugar level count and to identify factors predicting the progression of diabetic infection. A total of 248 DM patients were included in the study that 44.8% were females and the rest 55.8% were males.LMM and GLMM would be used to model the progression of diabetic. This study showed that age, sex, time, illiterate with time, primary with time, address with time, age with time and time with time were statistically significant factors for the progression of fasting blood sugar level at a logarithmic fasting sugar level over time in GLMM.The statistical modeling approaches LMM and GLMM have been compared for the analysis of fasting data and we obtained GLMM exhibited the best for this data with smaller disturbance than LMM for their estimated standard error.