Background: Kidney failure is a common public health problem around the world. The vast majority of kidney failure cases in Sub-Saharan African nations, including Ethiopia, go undetected and untreated, resulting in practically certain mortality cases. This study was aimed primarily to model the time to (right and left) kidneys failure in the patients at Adama Hospital Medical College using the copula model. Study design: A retrospective cohort study. Methods: The copula model was used to examine join time to the right and left kidneys failure in the patients by specifying the dependence between the failure times. We employed Weibull, Gompertz, and Log-logistic marginal baseline distributions with Clayton, Gumbel, and Joe Archimedean copula families. Results: This research comprised a total of 431 patients, out of which, 170 (39.4%) of the total patients failed at least one kidney during the follow-up period. Factors such as sex, age, family history of kidney disease, diabetes mellitus, hypertension, and obesity were found to be the most predictive variables for kidney failure in the patients. There was a 41 percent correlation between the patients’ time to the right and left kidneys failure. Conclusion: The patients’ kidney failure risk factors included being a male, older adult, obese, hypertensive, diabetic and also having a family history of kidney disease. The dependence between the patient’s time to the right and left kidneys failure was strong. The best statistical model for describing the kidney failure datasets was the log-logistic-Clayton Archimedean copula model.

Background: Globally, there is an increase in the prevalence of high birth weight. In Sub-Sahara African countries, including Ethiopia, weighting newborns at birth are not well addressed thereby awareness of high birth weight is limited. In this paper, we aimed to assess the between-region variability of the prevalence and identify the associated factors with high birth weight in Ethiopia.Methods: The study is based on the Ethiopian Demographic and Health Survey which is conducted in 2016. A total of 2110 newborns across all regions of Ethiopia are included in the study. The multilevel logistic regression model is applied to identify the associated factors of high birth weight and to evaluate the variation of the prevalence of high birth weight across the regions of Ethiopia. Results: The prevalence of high birth weight in Ethiopia was 10.4%. Based on our analysis, mother's age, residence, mother’s educational level, mother's body mass index gestational age, socio-economic class, and the sex of the newborn baby were the significant factors associated with high birth weight. With inter-class correlation of 14%, there is a significant variation of high birth weight among the regions of Ethiopia.Conclusion: Controlling mother’s BMI, strengthening follow up for elder women and women in high socio-economic class, and prevention of post maturity (≥40 weeks) gestational age could be effective personal and public health measures to combat high birth weight in Ethiopia.