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Predictors, causes, and trends of neonatal mortality at Nekemte Referral Hospital, east Wollega Zone, western Ethiopia (2010–2014). Retrospective cohort study

BACKGROUND: Neonatal mortality is a significant contributor to infant mortality. Causes and predictors of neonatal death are known to vary in different settings and across different contexts. This study aimed to assess predictors, causes, and trends of neonatal mortality amongst neonates admitted to...

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Autores principales: Roro, Elias Merdassa, Tumtu, Meseret Itana, Gebre, Dejene Seyoum
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6785121/
https://www.ncbi.nlm.nih.gov/pubmed/31596859
http://dx.doi.org/10.1371/journal.pone.0221513
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author Roro, Elias Merdassa
Tumtu, Meseret Itana
Gebre, Dejene Seyoum
author_facet Roro, Elias Merdassa
Tumtu, Meseret Itana
Gebre, Dejene Seyoum
author_sort Roro, Elias Merdassa
collection PubMed
description BACKGROUND: Neonatal mortality is a significant contributor to infant mortality. Causes and predictors of neonatal death are known to vary in different settings and across different contexts. This study aimed to assess predictors, causes, and trends of neonatal mortality amongst neonates admitted to Nekemte Referral Hospital neonatal unit between 2010–2014. METHODS: Retrospective data was collected for 2090 live born neonates admitted to the neonatal intensive care unit of Nekemte Referral Hospital by reviewing records between 2010 to 2014. Variables were collected from the neonatal registration book and patient card on the predictors, causes, and trends of neonatal death using a standard checklist developed by the World Health Organization (WHO). Data was analyzed using Epi info version 3.5.1, and SPSS version 25 for windows. The level of significance was set at P<0.05 with the corresponding confidence intervals at 95%. A logistic regression model was used for analysis and to control for confounders. Microsoft Excel 2007 was used to construct the trend analysis. RESULTS: There were 183 deaths in the cohort equivalent to 8.8% of deaths among total admitted neonates during the study period. Early neonatal deaths accounted for 8% and late neonatal deaths accounted for 0.71% of deaths among total admitted neonates. Main predictors identified for an increased risk of neonatal mortality were; neonates from rural residents [AOR 1.35, (95% CI, 1.35–1.87)], birth order of greater than five [AOR 5.10, (95% CI, 1.15–22.63)], home delivery [AOR 3.41, (95% CI, 2.24–5.19)], very low birth weight [AOR 6.75, (95% CI, 3.63–12.54)] and low birth weight [AOR 2.81, (95% CI, 1.95–4.05)] and inability to cry at birth [AOR 2.21, (95% CI, 1.51–3.22)]. The trend analysis showed a sharp fall for the neonatal mortality over the last five years with a mean reduction of 16%. CONCLUSIONS: Data from the Nekemte Referral Hospital Neonatal Intensive Care Unit analysis revealed majority of the deaths were occurred during early neonatal period. The main predictors of neonatal mortality identified from this study needs strengthening an appropriate public health intervention through addressing antenatal care, curbing home delivery.
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spelling pubmed-67851212019-10-19 Predictors, causes, and trends of neonatal mortality at Nekemte Referral Hospital, east Wollega Zone, western Ethiopia (2010–2014). Retrospective cohort study Roro, Elias Merdassa Tumtu, Meseret Itana Gebre, Dejene Seyoum PLoS One Research Article BACKGROUND: Neonatal mortality is a significant contributor to infant mortality. Causes and predictors of neonatal death are known to vary in different settings and across different contexts. This study aimed to assess predictors, causes, and trends of neonatal mortality amongst neonates admitted to Nekemte Referral Hospital neonatal unit between 2010–2014. METHODS: Retrospective data was collected for 2090 live born neonates admitted to the neonatal intensive care unit of Nekemte Referral Hospital by reviewing records between 2010 to 2014. Variables were collected from the neonatal registration book and patient card on the predictors, causes, and trends of neonatal death using a standard checklist developed by the World Health Organization (WHO). Data was analyzed using Epi info version 3.5.1, and SPSS version 25 for windows. The level of significance was set at P<0.05 with the corresponding confidence intervals at 95%. A logistic regression model was used for analysis and to control for confounders. Microsoft Excel 2007 was used to construct the trend analysis. RESULTS: There were 183 deaths in the cohort equivalent to 8.8% of deaths among total admitted neonates during the study period. Early neonatal deaths accounted for 8% and late neonatal deaths accounted for 0.71% of deaths among total admitted neonates. Main predictors identified for an increased risk of neonatal mortality were; neonates from rural residents [AOR 1.35, (95% CI, 1.35–1.87)], birth order of greater than five [AOR 5.10, (95% CI, 1.15–22.63)], home delivery [AOR 3.41, (95% CI, 2.24–5.19)], very low birth weight [AOR 6.75, (95% CI, 3.63–12.54)] and low birth weight [AOR 2.81, (95% CI, 1.95–4.05)] and inability to cry at birth [AOR 2.21, (95% CI, 1.51–3.22)]. The trend analysis showed a sharp fall for the neonatal mortality over the last five years with a mean reduction of 16%. CONCLUSIONS: Data from the Nekemte Referral Hospital Neonatal Intensive Care Unit analysis revealed majority of the deaths were occurred during early neonatal period. The main predictors of neonatal mortality identified from this study needs strengthening an appropriate public health intervention through addressing antenatal care, curbing home delivery. Public Library of Science 2019-10-09 /pmc/articles/PMC6785121/ /pubmed/31596859 http://dx.doi.org/10.1371/journal.pone.0221513 Text en © 2019 Roro et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Roro, Elias Merdassa
Tumtu, Meseret Itana
Gebre, Dejene Seyoum
Predictors, causes, and trends of neonatal mortality at Nekemte Referral Hospital, east Wollega Zone, western Ethiopia (2010–2014). Retrospective cohort study
title Predictors, causes, and trends of neonatal mortality at Nekemte Referral Hospital, east Wollega Zone, western Ethiopia (2010–2014). Retrospective cohort study
title_full Predictors, causes, and trends of neonatal mortality at Nekemte Referral Hospital, east Wollega Zone, western Ethiopia (2010–2014). Retrospective cohort study
title_fullStr Predictors, causes, and trends of neonatal mortality at Nekemte Referral Hospital, east Wollega Zone, western Ethiopia (2010–2014). Retrospective cohort study
title_full_unstemmed Predictors, causes, and trends of neonatal mortality at Nekemte Referral Hospital, east Wollega Zone, western Ethiopia (2010–2014). Retrospective cohort study
title_short Predictors, causes, and trends of neonatal mortality at Nekemte Referral Hospital, east Wollega Zone, western Ethiopia (2010–2014). Retrospective cohort study
title_sort predictors, causes, and trends of neonatal mortality at nekemte referral hospital, east wollega zone, western ethiopia (2010–2014). retrospective cohort study
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6785121/
https://www.ncbi.nlm.nih.gov/pubmed/31596859
http://dx.doi.org/10.1371/journal.pone.0221513
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