Incidence and predictors of neonatal mortality among neonates admitted in Amhara regional state referral hospitals, Ethiopia: prospective follow up study.

BACKGROUND: Globally, about 2.7 million neonates die annually and more than 99% of these deaths happened in developing countries. Although most neonatal deaths are preventable and attempts had been taken to tackle these deaths, an aggregate of 30 neonatal deaths per 1000 live births had been reported in Ethiopia. In this regard, identifying the predictors could be an important step. However, evidence on the incidence and predictors of neonatal mortality has been limited in Ethiopia, in the study area in particular. Even the available studies were limited in scope and were retrospective or cross section in nature. Thus, this study is aimed at assessing the incidence and predictors of neonatal mortality among neonates admitted in Amhara regional state referral hospitals, Ethiopia.. METHOD: A multi center prospective follow up study was conducted on 612 neonates admitted in Amhara region referral hospitals from July 01 to August 30, 2018. A simple random sampling technique was used to select three of all referral hospitals in the study settings and all neonates admitted in the selected hospitals were included. Data were entered into Epi info version 7.0 and exported to STATA 14.0 for analysis. Cox proportional hazard regression model was fitted to identify predictors of neonatal mortality. Crude and Adjusted hazard ratio with 95% confidence interval was computed and variables' statistical significance was declared based on its AHR with 95% CI and p-value /= 35 years (AHR = 2.60; 95%CI: 1.44, 4.72), mothers unable to read and write (AHR = 1.40; 95%CI: 1.23, 2.44), multiple pregnancy (AHR = 3.96; 95%CI: 2.10, 7.43) and positive maternal HIV status (AHR = 6.57; 95%CI: 2.53, 17.06) were predictors of neonatal mortality. CONCLUSION: In this study, the neonatal mortality rate was higher than the national figure. Its most predictors were found to be modifiable. Thus, the stakeholders would better consider the aforementioned predictors to decrease this higher burden.