Neonatal mortality and associated factors in newborn infants admitted to a Neonatal Care Unit

Lona-Reyes, Juan Carlos; Ro, Pérez Ramírez; L, Llamas Ramos; Ruiz, Gómez; Ea, Benítez Vázquez; Patino, Rodríguez

doi:10.5546/aap.2018.eng.42

Cited by 21 publications

(23 citation statements)

References 11 publications

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“…This study also identified lack of partograph utilization as one of the determinants of perinatal death. 17,20 Although obstetric complications, birth weight, sex of the fetus/newborn, and previous history of stillbirth have been identified previously as determinants of perinatal mortality, our study did not find significant associations with these variables.…”

Section: Discussioncontrasting

confidence: 87%

“…The possible explanation for this is that ANC follow-up allows for earlier detection and management of pregnancy complications that could affect birth outcomes. 18,20 Premature birth is a known determinant for perinatal death even in facilities with advanced neonatal care capabilities. In rural areas where advanced neonatal care is not available, prematurity is an even greater contributor to neonatal mortality.…”

Section: Discussionmentioning

confidence: 99%

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Determinants of Perinatal Mortality in Public Hospitals of Iluu Abbaa Boor Oromia Region, South West Ethiopia, 2019: Unmatched Case–Control Study

Geda¹,

Shemsu²,

Debalke³

2021

RRN

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Background: Globally, about 2.5 million children die in the first month after birth; this amounts to 7000 neonatal deaths every day. Almost half of neonatal deaths occur on the first postnatal day, and the vast majority of the rest occurs within the first postnatal week. In Ethiopia, efforts to reduce perinatal mortality did not meet the United Nations Millennium Development Goal (MDG) in 2020. Objective: To identify determinants of perinatal death in public hospitals of Iluu Abbaa Boor Zone, Oromia regional state, Southwest Ethiopia, 2019. Methods: An institution-based, case-control study was employed from March 1 to April 30, 2019 in Iluu Abbaa Boor Zone governmental hospitals. A total of 90 cases were taken consecutively. Four controls were assigned for each case. Maternal and neonatal data were collected by interview using a semi-structured questionnaire and hospital record review. Results: The likelihood of perinatal mortality was 2.8 times greater for those whose mothers did not have regular ANC follow-up (AOR 2.8; 95% CI [1.4-4.8]). The odds of perinatal mortality were 2.8 times higher among newborns of mothers with less than two years birth interval (AOR 2.8; 95% CI [1.8-12.4]). The odds of perinatal mortality were 14.3 times higher among preterm deliveries compared to newborns with term deliveries (AOR 14.3;). Conclusion:In a medical resource-limited region of Ethiopia, not having ANC follow-up, short birth interval, preterm and postterm births, maternal hemoglobin level, use of partograph, were independent determinants of perinatal mortality. Targeting education and medical resources in these areas for women in the reproductive age group could influence regional perinatal mortality.

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Section: Discussioncontrasting

confidence: 87%

Section: Discussionmentioning

confidence: 99%

Determinants of Perinatal Mortality in Public Hospitals of Iluu Abbaa Boor Oromia Region, South West Ethiopia, 2019: Unmatched Case–Control Study

Geda¹,

Shemsu²,

Debalke³

2021

RRN

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“…It is clear that neonatal sepsis is one of the public health problems affecting the survival of children, primarily in countries included in this study [ 48 ]. Neonatal sepsis is frequently reported by prior studies as a predictor of NM [ 2 , 49 , 50 ]. Likewise, perinatal asphyxia is found to have a main predictor of NM.…”

Section: Discussionmentioning

confidence: 99%

Incidence Density Rate of Neonatal Mortality and Predictors in Sub-Saharan Africa: A Systematic Review and Meta-Analysis

Bitew

Alemu

Ayele

et al. 2020

International Journal of Pediatrics

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Background. Neonatal mortality in Sub-Saharan countries is remarkably high. Though there are inconsistent studies about the incidence density rate of neonatal mortalities (IDR) and predictors in Sub-Saharan Africa, they are inconclusive to policymakers and program planners. In this study, the IDR of neonatal mortalities and predictors was determined. Methods. Electronic databases (Web of Science, PubMed, EMBASE (Elsevier), Scopus, CINAHL (EBSCOhost), World Cat, Google Scholar, and Google) were explored. 20 out of 818 studies were included in this study. The IDRs and predictors of neonatal mortality were computed from studies conducted in survival analysis. Fixed and random effect models were used to compute pooled estimates. Subgroup and sensitivity analyses were performed. Results. Neonates were followed for a total of 1,095,611 neonate-days; 67142 neonate-days for neonates treated in neonatal intensive care units and 1,028,469 neonate-days for community-based studies. The IDRs of neonatal mortalities in neonatal intensive care units and in the community were 24.53 and 1.21 per 1000 person-days, respectively. The IDRs of early and late neonatal mortalities neonatal intensive care units were 22.51 and 5.09 per 1000 neonate-days, respectively. Likewise, the IDRs of early and late neonatal mortalities in the community were 0.85 and 0.31, respectively. Not initiating breastfeeding within one hour, multiple births, rural residence, maternal illness, low Apgar score, being preterm, sepsis, asphyxia, and respiratory distress syndrome were independent predictors of time to neonatal mortality in neonatal intensive care units and male gender, perceived small size, multiple births, and ANC were predictors of neonatal mortality in the community. Conclusion. The incidence density rate of neonatal mortality in Sub-Saharan Africa is significantly high. Multiple factors (neonatal and maternal) were found to be independent predictors. Strategies must be designed to address these predictors, and prospective studies could reveal other possible factors of neonatal mortalities.

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“…According to different studies suggested there are many factors contributing to neonatal mortality. Among these: educational level [10], sex of the neonate, duration of pregnancy [11], home delivery without skilled provider [12], pregnancy complication [13], birth weight [14, 15], delay in seeking care during illness [16, 17], lack of preparedness of families and care providers, harmful cultural practices [18], economic status [19], social exclusion, maternal illiteracy [20], negative parental attitudes arising from the social environment, gender bias, inability to pay for care [20], and lack of basic prenatal, natal, and postnatal services [7, 21] were the main determinants of poor newborn survival rates in developing countries [22–26].…”

Section: Introductionmentioning

confidence: 99%

Factors affecting neonatal mortality in the general population: evidence from the 2016 Ethiopian Demographic and Health Survey (EDHS)—multilevel analysis

et al. 2019

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Objective: This study was aimed to identify factors affecting neonatal mortality in Ethiopia. Results:According to the multilevel multivariable logistic regression analysis, the odds of neonatal mortality was significantly associated with husbands with no education (AOR = 2.30, 95% CI 1.10, 4.83), female birth (AOR = 0.57, 95% CI 0.39, 0.83), twin birth (AOR = 13.62, 95% CI 7.14, 25.99), pre-term birth (AOR = 15.07, 95% CI 7.80, 29.12) and mothers with no antenatal care (ANC) visit during pregnancy (AOR = 1.90 95% CI 1.11, 3.25).

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Neonatal mortality and associated factors in newborn infants admitted to a Neonatal Care Unit

Cited by 21 publications

References 11 publications

Determinants of Perinatal Mortality in Public Hospitals of Iluu Abbaa Boor Oromia Region, South West Ethiopia, 2019: Unmatched Case–Control Study

Determinants of Perinatal Mortality in Public Hospitals of Iluu Abbaa Boor Oromia Region, South West Ethiopia, 2019: Unmatched Case–Control Study

Incidence Density Rate of Neonatal Mortality and Predictors in Sub-Saharan Africa: A Systematic Review and Meta-Analysis

Factors affecting neonatal mortality in the general population: evidence from the 2016 Ethiopian Demographic and Health Survey (EDHS)—multilevel analysis

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