Modified Bayesian survival analysis of Diabetes Mellitus in selected hospital facilities in Nasarawa, Nigeria

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Peter Enesi Omaku Ganaka Kubi Musa Titus Onyi


Diabetes mellitus is a global chronic health problem affecting over 400 million people. The study focused on the commonest type of Diabetes-Type II diabetes. The disease is associated with morbidity and mortality. Bayesian survival model may be utilized to assess the risk factors associated with Diabetes. The study utilized secondary data from 532 diabetic patients from two General Hospital facilities in Nasarawa State, Nigeria. The aim of the paper was to apply a Bayesian survival model on diabetic dataset to assess some risk factors pertaining to the disease. This Bayesian model was modified to Diabetic Additive Models (DAMS) and further extended to the Diabetic Additive Constant Hazard Model (DACHM), the coded version C. DACHM (when all metrical covariates were coded) and Diabetic Additive Accelerated Failure Time Model (DAAFTM). The results show that C.DACHM outperforms the other model with least values of Watanabe Akaike Information Criterion (WAIC), Deviance Information Criterion (DIC), and a large predictive power measured by the Log Pseudo Maximum Likelihood (LPML). The C.DACH model suggests that; good management of type II diabetes patients aged 40 years and above in both hospitals reduced the risk of death. Considerably, low Body Mass Index (BMI) increased the risk of death of patients with the disease. Body Mass Index, BMI greater than 24.9 (overweight) are 5.41E-17 times at risk of death from diabetes than those of normal weight. High Systolic Blood Pressure, SBP, greater than 140 (high) increases the risk of dying from the diseases by 1.51 times than those of normal SBP. High Diastolic Blood Pressure, DBP, greater than or equal to 90 (high) increases the risk of dying from the diseases by 7.81 times than those of normal DBP. Male patients were 1.28 times at risk of death from diabetes than their female patients. Patients of General Hospital Keffi experience are 1.02 times at risk of death than those of the General Hospital Nasarawa. The research recommends patients’ drug compliance especially for patients above 40 years, maintenance of a healthy body mass index and maintenance of a healthy blood pressure.

Keywords: Diabetes, Bayesian Survival Model, Proportional Hazard, Accelerated Failure Time Model, Additive Model

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How to Cite
OMAKU, Peter Enesi; MUSA, Ganaka Kubi; ONYI, Titus. Modified Bayesian survival analysis of Diabetes Mellitus in selected hospital facilities in Nasarawa, Nigeria. Medical Research Archives, [S.l.], v. 11, n. 4, apr. 2023. ISSN 2375-1924. Available at: <>. Date accessed: 29 may 2023. doi:
Research Articles


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