Bayesian spatial analysis of factors influencing neonatal mortality and its geographic variation in Ethiopia.

Kibret, GD; Demant, D; Hayen, A

Bayesian spatial analysis of factors influencing neonatal mortality and its geographic variation in Ethiopia.

Kibret, GD Demant, D

Hayen, A

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Publisher:: Public Library of Science (PLoS)
Publication Type:: Journal Article
Citation:: PLoS One, 2022, 17, (7), pp. 1-16
Issue Date:: 2022

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Field	Value	Language
dc.contributor.author	Kibret, GD
dc.contributor.author	Demant, D https://orcid.org/0000-0003-3330-2972
dc.contributor.author	Hayen, A https://orcid.org/0000-0003-4046-8030
dc.date.accessioned	2022-10-10T01:29:55Z
dc.date.available	2022-06-17
dc.date.available	2022-10-10T01:29:55Z
dc.date.issued	2022
dc.identifier.citation	PLoS One, 2022, 17, (7), pp. 1-16
dc.identifier.issn	1932-6203
dc.identifier.issn	1932-6203
dc.identifier.uri	http://hdl.handle.net/10453/162413
dc.description.abstract	BACKGROUND: Ethiopia is a Sub-Saharan country with very high neonatal mortality rates, varying across its regions. The rate of neonatal mortality reduction in Ethiopia is slow, and Ethiopia may not meet the third United Nations sustainable development target by 2030. This study aimed to investigate the spatial variations and contributing factors for neonatal mortality rates in Ethiopia. METHODS: We analysed data from the 2016 Ethiopian Demographic and Health Survey (EDHS), which used a two-stage cluster sampling technique with a census enumeration area as primary and households as secondary sampling units. A Bayesian spatial logistic regression model using the Stochastic Partial Differential Equation (SPDE) method was fitted accounting for socio-economic, health service-related and geographic factors. RESULTS: Higher neonatal mortality rates were observed in eastern, northeastern and southeastern Ethiopia, and the Somali region had higher risks of neonatal mortality. Neonates from frequently drought-affected areas had a higher mortality risk than less drought-affected areas. Application of traditional substances on the cord increased the risk of neonatal mortality (Adjusted Odds Ratio (AOR) = 2.07, 95% Credible Interval (CrI): 1.12 to 4.30) and getting health facility delivery services had a lower odds of neonatal mortality (AOR = 0.60, 95% CrI: 0.37, 0.98). CONCLUSIONS: Residing in drought-affected areas, applying traditional substances on the umbilical cord and not delivering at health facilities were associated with a higher risk of neonatal mortality. Policy-makers and resource administrators at different administrative levels could leverage the findings to prioritise and target areas identified with higher neonatal mortality rates.
dc.format	Electronic-eCollection
dc.language	eng
dc.publisher	Public Library of Science (PLoS)
dc.relation.ispartof	PLoS One
dc.relation.isbasedon	10.1371/journal.pone.0270879
dc.rights	info:eu-repo/semantics/openAccess
dc.subject.classification	General Science & Technology
dc.subject.mesh	Bayes Theorem
dc.subject.mesh	Ethiopia
dc.subject.mesh	Humans
dc.subject.mesh	Infant Mortality
dc.subject.mesh	Infant, Newborn
dc.subject.mesh	Risk Factors
dc.subject.mesh	Spatial Analysis
dc.subject.mesh	Bayes Theorem
dc.subject.mesh	Ethiopia
dc.subject.mesh	Humans
dc.subject.mesh	Infant Mortality
dc.subject.mesh	Infant, Newborn
dc.subject.mesh	Risk Factors
dc.subject.mesh	Spatial Analysis
dc.subject.mesh	Humans
dc.subject.mesh	Infant Mortality
dc.subject.mesh	Bayes Theorem
dc.subject.mesh	Risk Factors
dc.subject.mesh	Infant, Newborn
dc.subject.mesh	Ethiopia
dc.subject.mesh	Spatial Analysis
dc.title	Bayesian spatial analysis of factors influencing neonatal mortality and its geographic variation in Ethiopia.
dc.type	Journal Article
utslib.citation.volume	17
utslib.location.activity	United States
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Health
pubs.organisational-group	/University of Technology Sydney/Faculty of Health/Public Health
utslib.copyright.status	open_access	*
pubs.consider-herdc	false
dc.date.updated	2022-10-10T01:29:24Z
pubs.issue	7
pubs.publication-status	Published
pubs.volume	17
utslib.citation.issue	7

Abstract:

BACKGROUND: Ethiopia is a Sub-Saharan country with very high neonatal mortality rates, varying across its regions. The rate of neonatal mortality reduction in Ethiopia is slow, and Ethiopia may not meet the third United Nations sustainable development target by 2030. This study aimed to investigate the spatial variations and contributing factors for neonatal mortality rates in Ethiopia. METHODS: We analysed data from the 2016 Ethiopian Demographic and Health Survey (EDHS), which used a two-stage cluster sampling technique with a census enumeration area as primary and households as secondary sampling units. A Bayesian spatial logistic regression model using the Stochastic Partial Differential Equation (SPDE) method was fitted accounting for socio-economic, health service-related and geographic factors. RESULTS: Higher neonatal mortality rates were observed in eastern, northeastern and southeastern Ethiopia, and the Somali region had higher risks of neonatal mortality. Neonates from frequently drought-affected areas had a higher mortality risk than less drought-affected areas. Application of traditional substances on the cord increased the risk of neonatal mortality (Adjusted Odds Ratio (AOR) = 2.07, 95% Credible Interval (CrI): 1.12 to 4.30) and getting health facility delivery services had a lower odds of neonatal mortality (AOR = 0.60, 95% CrI: 0.37, 0.98). CONCLUSIONS: Residing in drought-affected areas, applying traditional substances on the umbilical cord and not delivering at health facilities were associated with a higher risk of neonatal mortality. Policy-makers and resource administrators at different administrative levels could leverage the findings to prioritise and target areas identified with higher neonatal mortality rates.

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http://hdl.handle.net/10453/162413