Neonatal mortality clustering in the central districts of Ghana.

<h4>Introduction</h4>Identifying high risk geographical clusters for neonatal mortality is important for guiding policy and targeted interventions. However, limited studies have been conducted in Ghana to identify such clusters.<h4>Objective</h4>This study aimed to identify h...

Full description

Bibliographic Details
Main Authors: George Adjei, Eugene K M Darteh, David Teye Doku
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2021-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0253573
id doaj-e6b15f9f1fa14fe4956407f076262da6
record_format Article
spelling doaj-e6b15f9f1fa14fe4956407f076262da62021-07-10T04:30:22ZengPublic Library of Science (PLoS)PLoS ONE1932-62032021-01-01166e025357310.1371/journal.pone.0253573Neonatal mortality clustering in the central districts of Ghana.George AdjeiEugene K M DartehDavid Teye Doku<h4>Introduction</h4>Identifying high risk geographical clusters for neonatal mortality is important for guiding policy and targeted interventions. However, limited studies have been conducted in Ghana to identify such clusters.<h4>Objective</h4>This study aimed to identify high-risk clusters for all-cause and cause-specific neonatal mortality in the Kintampo Districts.<h4>Materials and methods</h4>Secondary data, comprising of 30,132 singleton neonates between January 2005 and December 2014, from the Kintampo Health and Demographic Surveillance System (KHDSS) database were used. Verbal autopsies were used to determine probable causes of neonatal deaths. Purely spatial analysis was ran to scan for high-risk clusters using Poisson and Bernoulli models for all-cause and cause-specific neonatal mortality in the Kintampo Districts respectively with village as the unit of analysis.<h4>Results</h4>The study revealed significantly high risk of village-clusters for neonatal deaths due to asphyxia (RR = 1.98, p = 0.012) and prematurity (RR = 5.47, p = 0.025) in the southern part of Kintampo Districts. Clusters (emerging clusters) which have the potential to be significant in future, for all-cause neonatal mortality was also identified in the south-western part of the Kintampo Districts.<h4>Conclusions</h4>Study findings showed cause-specific neonatal mortality clustering in the southern part of the Kintampo Districts. Emerging cluster was also identified for all-cause neonatal mortality. More attention is needed on prematurity and asphyxia in the identified cause-specific neonatal mortality clusters. The emerging cluster for all-cause neonatal mortality also needs more attention to forestall any formation of significant mortality cluster in the future. Further research is also required to understand the high concentration of prematurity and asphyxiated deaths in the identified clusters.https://doi.org/10.1371/journal.pone.0253573
collection DOAJ
language English
format Article
sources DOAJ
author George Adjei
Eugene K M Darteh
David Teye Doku
spellingShingle George Adjei
Eugene K M Darteh
David Teye Doku
Neonatal mortality clustering in the central districts of Ghana.
PLoS ONE
author_facet George Adjei
Eugene K M Darteh
David Teye Doku
author_sort George Adjei
title Neonatal mortality clustering in the central districts of Ghana.
title_short Neonatal mortality clustering in the central districts of Ghana.
title_full Neonatal mortality clustering in the central districts of Ghana.
title_fullStr Neonatal mortality clustering in the central districts of Ghana.
title_full_unstemmed Neonatal mortality clustering in the central districts of Ghana.
title_sort neonatal mortality clustering in the central districts of ghana.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2021-01-01
description <h4>Introduction</h4>Identifying high risk geographical clusters for neonatal mortality is important for guiding policy and targeted interventions. However, limited studies have been conducted in Ghana to identify such clusters.<h4>Objective</h4>This study aimed to identify high-risk clusters for all-cause and cause-specific neonatal mortality in the Kintampo Districts.<h4>Materials and methods</h4>Secondary data, comprising of 30,132 singleton neonates between January 2005 and December 2014, from the Kintampo Health and Demographic Surveillance System (KHDSS) database were used. Verbal autopsies were used to determine probable causes of neonatal deaths. Purely spatial analysis was ran to scan for high-risk clusters using Poisson and Bernoulli models for all-cause and cause-specific neonatal mortality in the Kintampo Districts respectively with village as the unit of analysis.<h4>Results</h4>The study revealed significantly high risk of village-clusters for neonatal deaths due to asphyxia (RR = 1.98, p = 0.012) and prematurity (RR = 5.47, p = 0.025) in the southern part of Kintampo Districts. Clusters (emerging clusters) which have the potential to be significant in future, for all-cause neonatal mortality was also identified in the south-western part of the Kintampo Districts.<h4>Conclusions</h4>Study findings showed cause-specific neonatal mortality clustering in the southern part of the Kintampo Districts. Emerging cluster was also identified for all-cause neonatal mortality. More attention is needed on prematurity and asphyxia in the identified cause-specific neonatal mortality clusters. The emerging cluster for all-cause neonatal mortality also needs more attention to forestall any formation of significant mortality cluster in the future. Further research is also required to understand the high concentration of prematurity and asphyxiated deaths in the identified clusters.
url https://doi.org/10.1371/journal.pone.0253573
work_keys_str_mv AT georgeadjei neonatalmortalityclusteringinthecentraldistrictsofghana
AT eugenekmdarteh neonatalmortalityclusteringinthecentraldistrictsofghana
AT davidteyedoku neonatalmortalityclusteringinthecentraldistrictsofghana
_version_ 1721310099610271744