Variations in Under-five Child Mortality among Regional States of Ethiopia: A Multi-level Modelling Approach

Bedane, Ashenafi Senbeta; Asena, Tilahun Ferede; Shamenna, Aklilu Toma; Abshoko, Amanuel Disassa

doi:10.9734/bjast/2016/24448

Cited by 13 publications

(23 citation statements)

References 10 publications

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“…This showed that perinatal mortality variation across the region is decreasing over time. This study is consistent with the findings (Ashenafi Senbeta et al, 2016;Adedini et al, 2015).…”

Section: Results Of Bayesian Multilevel Random Coefficient Modelsupporting

confidence: 94%

“…Three different multilevel models such as Bayesian random intercept only multilevel models, Bayesian random intercept multilevel model and Bayesian random coefficient multilevel model and model comparison results depicted that random coefficient multilevel model is best fit the data very well. We also found that the perinatl mortality proporion is least in Dire Dawa, Addis Ababa and Amhara which is similar whith the study (Ashenafi Senbeta et al, 2016). In the…”

Section: Discussionsupporting

confidence: 89%

“…The variable of interest in this study was perinatal mortality, and it has been dichotomized as 1 indicating one or more perinatal mortality occcured or 0 for no mortality. The explanatory variables have been selected considering all dimensions of perinatal mortality in Ethiopia which includes demographic factors, such as sex of child, age of mothers, birth order, child twin and family size, socio-econimic factors, such as wealth index, educational level, place of residence, place of delivery, religion and region and environmental factors, such as source of drinking water, use of contraceptives, smoking cigarettes have been included in the study (Ashenafi Senbeta et al, 2016).…”

Section: Data Descriptionmentioning

confidence: 99%

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Bayesian multilevel model application on determinants of perinatal mortality in Ethiopia using 2011 and 2016 EDHS data

Debelu

Belay

Terye

2021

Eth J Sci & Technol

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Perinatal mortality is the death of a fetus after the age of viability until the 7th day of life. Perinatal mortality is estimated by the addition of stillbirths plus the early neonatal mortality, which represents deaths occurring during the first 7 days after delivery. Perinatal mortality remains a great burden in Ethiopia. The purpose of this study was to assess and compare the demographic and socio-economic determinant factors of perinatal mortality in Ethiopia using the 2011 and 2016 Ethiopian Demographic Health Surveys (EDHS). For data analysis, the Bayesian multilevel Model was used in this study. The study revealed that there is a regional variation in perinatal mortality and this variation was high in 2011 EDHS than in 2016 EDHS data. Factors like sex of the child, age of mother, wealth index, family size, birth order, source of drinking water, place of residence, place of delivery, and child twin were found to be the determinant factors of perinatal mortality in both 2011 and 2016 EDHS. In this study, we found that perinatal mortality variation across regions has decreased from 2011 to 2016 surveys which shows the promising progress of health intervention in the country.

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“…This showed that perinatal mortality variation across the region is decreasing over time. This study is consistent with the findings (Ashenafi Senbeta et al, 2016;Adedini et al, 2015).…”

Section: Results Of Bayesian Multilevel Random Coefficient Modelsupporting

confidence: 94%

Section: Discussionsupporting

confidence: 89%

Section: Data Descriptionmentioning

confidence: 99%

See 1 more Smart Citation

Bayesian multilevel model application on determinants of perinatal mortality in Ethiopia using 2011 and 2016 EDHS data

Debelu

Belay

Terye

2021

Eth J Sci & Technol

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“…The mean survival time for multiple birth type of the children was exp (-9.9) = 0.034 times less than single birth type of children with 95% CI was between 0.02 and 0.06. This result was consistent with the studies (5,24).…”

Section: Discussionsupporting

confidence: 94%

“…Our ndings showed that the under-ve children from Afar, Somali and Harari geopolitical regions of Ethiopia were signi cantly associated with the highest likelihood of under-ve death as compared with children from Addis Ababa city. This high risk might be attributed to social improvement in the community, population density, territorial advancement, as well as regional economic resources (5,(19)(20)(21).…”

Section: Discussionmentioning

confidence: 99%

Research title on Multilevel Modelling of Time to Death for Under-Five Children: 2016 Ethiopia Demographic and Health Survey, 2019

Argawu

Hirko

2020

Preprint

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Background: Reducing child mortality is now a global concern. Globally, Under-five child mortality rate was decreased by 58% in 2017. In the 2016 EDHS report, under-five mortality was declined to 60% in Ethiopia in 2016. Methods: The data for the study was obtained from EDHS data conducted in 2016. In the study, we analysed the data using stratified Cox proportional hazard model and multilevel lognormal parametric survival model. Results: From the total of 10,331 under-five children, 635 (6.1%) deaths had occurred in the 2016 EDHS data. And, the overall probability of survival value was near to 0.92 with the estimated mean survival time was 55.4 months. In the study we found that covariates like birth type of the child, family size, wealth index, frequency of listening radio, place of delivery, place of residence, and geographical region were significant factors for the death of under-five children in stratified Cox proportional hazard model. In the multilevel lognormal parametric survival model, we found that the random-intercept effects of variations between region and household levels on the mean survival times of the children were 1.7 and 0.9, respectively. These values indicated that we had enough evidence for the existence of unobserved heterogeneities between regions and households. Conclusion: The covariates like birth type of the child, family size, wealth index, frequency of listening radio, place of delivery, place of residence, and geographical region covariates were significant factors for under-five children mortality using stratified Cox proportional hazard regression model. In the random-intercept effects model, the two estimated variances of the random-intercept effects for regional and household levels were 1.7 and 0.9, respectively. The values indicate that we have enough evidence that there were unobserved heterogeneities on the mean survival times of the under-five children between regions and households levels. Further studies should be conducted to identify the individual, household, and community-level factors associated with infant and child mortality in Ethiopia.

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Determinant factors of under-five mortality in rural Ethiopia

Yemane¹

2022

Annals of Medicine &Amp; Surgery

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Variations in Under-five Child Mortality among Regional States of Ethiopia: A Multi-level Modelling Approach

Cited by 13 publications

References 10 publications

Bayesian multilevel model application on determinants of perinatal mortality in Ethiopia using 2011 and 2016 EDHS data

Bayesian multilevel model application on determinants of perinatal mortality in Ethiopia using 2011 and 2016 EDHS data

Research title on Multilevel Modelling of Time to Death for Under-Five Children: 2016 Ethiopia Demographic and Health Survey, 2019

Determinant factors of under-five mortality in rural Ethiopia

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