A LONGITUDINAL RECORD ANALYSIS ON RISK DETERMINANTS FOR DIABETES MELLITUS: IN AYDER REFERRAL HOSPITA TIGRAY REGION, ETHIOPIA
European Journal of Molecular & Clinical Medicine,
2020, Volume 7, Issue 11, Pages 4654-4668
AbstractBackground: Diabetes mellitus (DM) is set of metabolic infections arranged by hypernym glucose levels that outcome from blemishes in either insulin emission or its adventure. This is characterized by long suffering disease with a high frequency and a growing anxiety in worldwide.
Objectives: The study mainly be situated on longitudinal analysis of diabetes mellitus risk factor by utilizing fasting blood glucose level and identify the associated risk factor of patients in Mekele and surrounding area, Tigray Ethiopia.
Method: This study used a retrospective data of DM patients demographic and health survey was conducted on patients from April, 2018 to February, 2020 by collaboration with Minster of health and other stockholders. The entire number of patient contained within this study was 210. The data analysis began with descriptive statistics followed by exploring structure of fasting blood glucose data set Using SAS 9.4. The study used linear mixed eﬀect model to perform the ﬁnal model ﬁt, and a number of methods were used to conduct the model diagnosis.
Result: the ﬁnal model ﬁt indicates that patient from total of 210 DM patients were studied to analyze the longitudinal data. Time was one factor that significance affect to patient of FBG level (p-value<0.0001) and estimate (0.0247), the rate of change in logFBG level is 0.024per unit increase in time. This proposes that the extent of progress in logFBG level increments with time.
Conclusion: The result from this investigation revealed that visiting times, BP (diastolic), types of diagnosis (type1) and educational level (primary) had statistically signiﬁcant eﬀect on the longitudinal bio-marker and missing after imputation observed that time (duration of follow up), patients that are not hypertensive, type one diabetes were negatively significant effect factors for fasting glucose level count progression.
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