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<title>MODEL-BASED SUB-POPULATION ESTIMATES OF MATERNAL MORTALITY  RATES AND RATIO FROM SIBLINGS’ SURVIVORSHIP HISTORIES IN  NIGERIA (2008 -2018)</title>
<link>http://hdl.handle.net/123456789/1587</link>
<description/>
<pubDate>Sun, 19 Apr 2026 05:27:59 GMT</pubDate>
<dc:date>2026-04-19T05:27:59Z</dc:date>
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<title>MODEL-BASED SUB-POPULATION ESTIMATES OF MATERNAL MORTALITY  RATES AND RATIO FROM SIBLINGS’ SURVIVORSHIP HISTORIES IN  NIGERIA (2008 -2018)</title>
<link>http://hdl.handle.net/123456789/1588</link>
<description>MODEL-BASED SUB-POPULATION ESTIMATES OF MATERNAL MORTALITY  RATES AND RATIO FROM SIBLINGS’ SURVIVORSHIP HISTORIES IN  NIGERIA (2008 -2018)
BABAJIDE, Opeyemi Oluwatosin
Despite several interventions, Maternal Mortality (MM) remains high in Nigeria. This is &#13;
further complicated by lack of reliable estimates of MM for subnational levels such as states &#13;
and geopolitical regions. A plausible estimate of MM levels is essential to provide evidence based national and state-level planning, resource allocation and monitoring of progress. It &#13;
will reflect the population diversity in the country and assist in closing MM gaps. This study &#13;
was designed to adapt sisterhood method and small area estimation techniques to derive &#13;
plausible estimates of MM rates and ratios for subnational populations in Nigeria. &#13;
Survivorship history data of 293,769 female siblings provided by 114,154 women in the &#13;
Nigeria Demographic and Health Surveys conducted in 2008, 2013 and 2018 were analysed. &#13;
The dataset from each survey was reconstructed into a panel data structure such that each &#13;
reported sibling was captured as an observation. The MM Rates (maternal deaths per &#13;
women-years of exposure to childbearing) and Ratios (maternal deaths per 100,000 live &#13;
births) were estimated using direct and indirect sisterhood methods. Empirical Bayesian &#13;
technique for small area demographic estimates was used to obtain MM rates and ratios at &#13;
state-levels. The James-Stein estimator was used to shrink the estimates closer to the &#13;
population mean values at 95% Confidence Interval (CI). Zero-inflated Poisson regression &#13;
model was fitted to investigate association between selected covariates and maternal death &#13;
counts at the community levels. Incident Risk Ratio (IRR) was reported as measures of &#13;
effect. All analyses were weighted to adjust for the effects of clustering.&#13;
MM rates in 2008 were high in rural areas and North-West region at 1.21 and 1.65 per 1,000 &#13;
women-exposure years and lowest in South-West at 0.45 per 1,000 women-exposure years. &#13;
Levels of MM Ratios were highest in the rural areas and South-South region at 624 and 679 &#13;
respectively and lowest in South-West (281 per 100,000 live births). In 2013, the levels of &#13;
MM Ratio were highest in North-Central (712) and lowest in South-West (367 per 100,000 &#13;
livebirths) and for 2018, it was higher in rural areas (548) compared to urban (523); highest &#13;
in North-West (901) and lowest in the South-East (268). MM Ratio was consistently lower &#13;
in the South-West (2008=281; 2013=367; 2018=392) and higher among the Northern &#13;
regions of the country, particularly the North-East (2008=654; 2013=612; 2018=901). &#13;
Overall, Kebbi, Adamawa and Taraba states had high MM Ratio across the three surveys. &#13;
From 2008 to 2018, MM Ratio declined by 18% in the North-West and 54.2% in the South East region. However, there was a 4.8% increase in MM Ratio for South-West from 2008 to &#13;
2018. At the community levels, geopolitical zone, knowledge (IRR=1.33, CI=0.98-6.1) and &#13;
actual use of family planning (IRR=1.92, CI=1.1-9.1) were associated with maternal death &#13;
counts.&#13;
This study has derived and shown differentials in subnational estimates of maternal &#13;
mortality in Nigeria and has identified geopolitical region, the knowledge and use of family &#13;
planning as major covariates of maternal mortality. This has produced a baseline upon &#13;
which improvements in maternal mortality in states and geopolitical zones in Nigeria can be &#13;
based.
</description>
<pubDate>Thu, 01 Apr 2021 00:00:00 GMT</pubDate>
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<dc:date>2021-04-01T00:00:00Z</dc:date>
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