Abstract

Logistic regressions widely used to model the outcome of a categorical dependent variable with one or ‎more explanatory variables. Logistic regression model is statistical tools used to test relationship ‎between nominal dependent variable and one or more independent variables (explanatory variables). ‎Logistic regression coefficients can be used to estimate odds ratios for each of the dependent variables ‎in the model, The main objective of this paper is to enhance methodology in the field of medical ‎research and biostatistics by adding new data to the existing knowledge in Sudan and the specific ‎objectives are to to explor the socioeconomic and biomedical factors affecting to the chronic renal ‎failure in Rive Nile State. This paper uses descriptive analysis, which was used to ‎describe the study ‎data using tables and also uses logistic regression to predictors on the risk of a certain dichotomous ‎outcome variable, (Socioeconomic factors) educational level, occupation, income, residence, health ‎insurance and marital status, the (Biomedical factors) hypertension, diabetes, kidney stones, ‎cardiovascular, urinary tract infection, kidney infection, liver disease and cancer. Significance tests for ‎logistic coefficients using the Wald test and likelihood ratio showed that the results of the independent ‎variables showed significance and odds ratio that the significant variables in were level of education, ‎income, type of residence, high blood pressure, kidney infection, diabetes, cardiovascular and kidney ‎urinary stone. The study recommended the following: The study showed that blood pressure, recurrent ‎kidney infections, and diabetes are the most common diseases associated with chronic kidney failure, ‎therefore, we recommend making a preventive health plan to reduce the risks of these diseases through ‎awareness and providing the necessary treatment, the Ministry of Health must adopt a statistical records ‎system in all dialysis centers.‎

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