TY - JOUR
T1 - Mapping maternal mortality rate via spatial zero-inflated models for count data
T2 - A case study of facility-based maternal deaths from Mozambique
AU - Loquiha, Osvaldo
AU - Hens, Niel
AU - Chavane, Leonardo
AU - Temmerman, Marleen
AU - Osman, Nafissa
AU - Faes, Christel
AU - Aerts, Marc
N1 - Publisher Copyright:
© 2018 Loquiha et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
PY - 2018/11
Y1 - 2018/11
N2 - Maternal mortality remains very high in Mozambique, with estimates from 2015 showing a maternal mortality ratio of 489 deaths per 100,000 live births, even though the rates tend to decrease since 1990. Pregnancy related hemorrhage, gestational hypertension and diseases such as malaria and HIV/AIDS are amongst the leading causes of maternal death in Mozambique, and a significant number of these deaths occur within health facilities. Often, the analysis of data on maternal mortality involves the use of counts of maternal deaths as outcome variable. Previously we showed that a class of hierarchical zero-inflated models were very successful in dealing with overdispersion and clustered counts when analyzing data on maternal deaths and related risk factors within health facilities in Mozambique. This paper aims at providing additional insights over previous analyses and presents an extension of such models to account for spatial variation in a disease mapping framework of facility-based maternal mortality in Mozambique.
AB - Maternal mortality remains very high in Mozambique, with estimates from 2015 showing a maternal mortality ratio of 489 deaths per 100,000 live births, even though the rates tend to decrease since 1990. Pregnancy related hemorrhage, gestational hypertension and diseases such as malaria and HIV/AIDS are amongst the leading causes of maternal death in Mozambique, and a significant number of these deaths occur within health facilities. Often, the analysis of data on maternal mortality involves the use of counts of maternal deaths as outcome variable. Previously we showed that a class of hierarchical zero-inflated models were very successful in dealing with overdispersion and clustered counts when analyzing data on maternal deaths and related risk factors within health facilities in Mozambique. This paper aims at providing additional insights over previous analyses and presents an extension of such models to account for spatial variation in a disease mapping framework of facility-based maternal mortality in Mozambique.
UR - http://www.scopus.com/inward/record.url?scp=85056394366&partnerID=8YFLogxK
U2 - 10.1371/journal.pone.0202186
DO - 10.1371/journal.pone.0202186
M3 - Article
C2 - 30412633
AN - SCOPUS:85056394366
SN - 1932-6203
VL - 13
JO - PLoS ONE
JF - PLoS ONE
IS - 11
M1 - e0202186
ER -