Abstract
BACKGROUND: To scale up a comprehensive way of implementation to reduce neonatal mortality evaluation of factors for neonatal near-miss cases is very important. Certain studies were done in assessing near-miss cases, but they failed in identifying the proximate factors affecting profoundly. So, this study is to fill those gaps in the aforementioned studies, in assessing the factors affecting neonatal near-miss cases. METHODS: A nested case-control study was conducted in selected three Hospitals of Gamo and Gofa Zones, Southern Ethiopia from April 5, 2018, to March 5, 2019. The structured standard tool was used to identify neonatal near-miss cases. Data were entered into Epi data version 3.1 and exported to Stata version 15 for analysis. A conditional logistic regression model was used to identify factors associated with near-miss cases. The goodness of fit was tested by a log-likelihood ratio (LR). In this study P-value < 0.05 was considered to declare a result as a statistically significant association. RESULTS: In this study 121 neonatal near-miss cases, and 363 controls were involved. The identified factors that affect neonatal near-miss were multiparty (AOR = 3.81, 95%CI: 1.72, 8.42), antenatal care follow up (AOR = 0.02, 95%CI: 0.01, 0.05), premature rupture of membrane (AOR = 3.40, 95%CI: 1.53, 7.55), non-vertex presentation (AOR = 2.83, 95%CI: 1.44, 5.58), and cesarean delivery (AOR = 4.89, 95%CI: 2.34, 10.24). CONCLUSIONS: Those identified factors are better should be intervened. Strengthening antenatal care services by providing appropriate information for the mother and counseling about the consequences of multiparty and providing information on family planning. There is a need to identify, screen and critical follow high-risk mothers and give immediate and appropriate intervention as early as possible.