Determinants of birth asphyxia among newborn live births in public hospitals of Gamo and Gofa zones, Southern Ethiopia

Abstract

Background Birth asphyxia is the inability of a newborn to start and conserve breathing immediately after birth. Globally, 2.5 million infants die within their first month of life every year, contributing nearly 47% of all deaths of children. It is the third cause of neonatal deaths next to infections and preterm birth. Ethiopia is one of the countries with the highest neonatal mortality and high burden of birth asphyxia in the world. The state of birth asphyxia is about 22.52% in Ethiopia, with incidence of 18.0% in East Africa Neonatal mortality incidence ratio was 9.6 deaths per 1000 live births among which 13.5% of neonatal mortality cases were due to birth asphyxia in southern Ethiopia. The effect of birth asphyxia is not only limited to common clinical problems and death; it also has a socio-economic impact on the families. Therefore, this study is aimed to identify determinants of birth asphyxia among newborn live births in public hospitals Southern Ethiopia. Methods An Institution based unmatched case–control study was conducted among newborn live births in public hospitals of Gamo & Gofa zones, with a total sample size of 356 (89 cases and 267 controls, 1:3 case to control ratio) from March 18 to June 18, 2021, after obtaining ethical clearance from Arba Minch University. Cases were selected consecutively and controls were selected by systematic random sampling method. Data were collected using an adapted pretested semi-structured questionnaire through face-to-face interviews and record reviews using an extraction checklist for intrapartum & neonatal-related information. The collected data were entered into Epi data version 4.4 and exported to STATA version 14 for analysis. Finally, bi-variable and multivariable logistic regression analyses were performed to identify determinants of birth asphyxia. Statistical significance was declared at p-value ≤ 0.05 along with corresponding 95% CI of AOR used to declare statistical significance. Results: Anemia during pregnancy [AOR = 3.87, 95% CI (1.06- 14.09)], breech presentation [AOR = 3.56, 95% CI (1.19–10.65)], meconium stained amniotic fluid [AOR = 6.16, 95% CI (1.95–19.46)], cord prolapse [AOR = 4.69, 95%CI (1.04–21.05)], intrapartum fetal distress [AOR = 9.83, 95% CI (3.82–25.25)] and instrumental delivery [AOR = 5.91, 95% CI (1.51–23.07)] were significantly associated with birth asphyxia. Conclusion The study revealed that anemia during pregnancy, breech presentation, meconium-stained amniotic fluid, cord prolapse, intrapartum fetal distress, and instrumental delivery were identified as determinants of birth asphyxia. Therefore, health professional and health institutions should give emphasis on care of mother and the newborn in actively detecting and managing asphyxia.

The determinants of neonatal asphyxia in the tropical province of China: A case-control study

“…[34] Besides, malpresentation is often followed by prolonged labor, head entrapment and birth injury, which are known obstetric emergency endangering feto-neonatal life. [29] In this study, low birth weight (LBW) was also a factor associated with NA. Low-birth-weight neonates were 10.51 times more likely than normal birth weight neonates to suffer from NA.…”

ROP-like retinopathy in full/near-term newborns: A etiology, risk factors, clinical and genetic characteristics, prognosis and management

“…It has been reported that the pathogenesis of ROPLR is associated with perinatal hypoxia-ischemia ( 8 , 24 ). A study revealed that meconium-stained amniotic fluid was identified as determinants of birth asphyxia ( 25 ). However, there is no consensus regarding the etiology or diagnostic criteria for ROPLR.…”

Hypoxic-ischaemic encephalopathy based on clinical signs and symptoms and associated factors among neonates, Southern Ethiopian public hospitals: a case-control study

“…We used the Open Epi version 7 statistical software package and a formula for two population proportions to calculate the sample size. Based on a previous study in southern Ethiopia, we assumed that 6.74% of the controls who were exposed 26 . The assumptions for the sample size calculation are; 17.98% of the cases were exposed, a 95% CI, an 80% power of the study, and a 2:1 ratio of controls to cases with 3.87 odds ratio.…”