Evaluation par régression logistique binaire de déterminants de la mortalité néonatale dans la province du Kongo Central - CSN

Evaluation par régression logistique binaire de déterminants de la mortalité néonatale dans la province du Kongo Central

Publication Date : 08/11/2024

DOI: 10.59228/rcst.024.v3.i3.99


Author(s) :

Mabola Tsinu Sébastien, Bapidia Nzengu Samuel, Ngimbi Ngimbi Jean, Onoya Wedi Josué, Ntoto Kunzi Bernard, Kafinga Luzolo Emeri.


Volume/Issue :
Volume 3
,
Issue 3
(11 - 2024)



Abstract :

Neonatal mortality disturbs the whole of humanity. Its frequency remains very high throughout the world, but more so in developing countries. The DRC is ranked among the countries with the highest number of neonatal deaths in the world with the ratio of 47 per 1000 live births, (Kalonji DC et al 2018). Indeed, the province of Kongo Central has not remained indifferent to this health problem. With a view to improving newborn health during the neonatal period, the present study is conducted and envisages identifying the determinants of neonatal mortality in Kongo Central Province. For this study, the general population consisted of all newborns in the Province of Kongo Central from 2021 to 2022. A random sample of 117 cases met the inclusion criteria, of which we matched 1 case to 2 controls. After data analysis, we found the following results: the overall neonatal mortality rate was 333 per thousand live births. The logistic regression model identified the following determinants of neonatal mortality: age (OR= 1.16562 IC95 [1.035635 -1.3163]. p=0.0105), age less than 2 years (OR= 2.01966 IC95 [1.021601-4.058]. p=0.0449) and acute fetal distress (OR=2.62027IC95 [1.179464-5.878]. p=0.0181). In order to improve neonatal health, pregnant women should be made aware of the importance of prenatal consultations for early detection and appropriate management of high-risk pregnancies. They should be present at the onset of labor and give birth in the presence of qualified personnel.


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