Bayesian geo-additive model to analyze spatial pattern and determinants of maternal mortality in Ethiopia.

Yitagesu Eshetu, Tigist Getachew
Author Information
  1. Yitagesu Eshetu: Department of Statistics, College of Natural and Computational Sciences, Dambi Dollo University, Dambi Dollo, Ethiopia. yitagesueshetustat2019@gmail.com.
  2. Tigist Getachew: Department of Statistics, College of Natural and Computational Sciences, Dambi Dollo University, Dambi Dollo, Ethiopia.

Abstract

BACKGROUND AND AIMS: Maternal mortality is defined as the death of a woman from any cause associated to or made worse by her pregnancy, either during her pregnancy or within 42 days of the pregnancy's termination, regardless of the length of the pregnancy or its location. The objective of this study is to determine the factors influencing maternal mortality as well as to examine the regional distribution of maternal deaths in Ethiopia.
METHOD: This study was conducted in Ethiopia and the data was basically secondary which is obtained from 2016 Ethiopian Demographic and Health survey (EDHS). The Bayesian Geo-additive regression model is used to identify the major risk factors and spatial effects (spatial pattern) on maternal death in Ethiopia.
RESULT: Pregnancy-related problems or childbirth were the cause of death for 1.43% of the 10,009 women in the research, whose ages ranged from 15 to 49. In contrast to the semi-parametric and generalized linear models, the Bayesian Geo-additive regression model is based on the DIC and better fits the data. According to the Bayesian Geo-additive regression model's results, maternal death is significantly affected by the place of delivery, the number of prenatal care visits, marital status, wealth index, mother's age and the number of birth orders. The Afar, Somali, Benishangul Gumuz, and Gambela regions have higher rates of maternal death, according to evidence of geographic variation in a model.
CONCLUSION: The findings of the study revealed that maternal mortality is influenced by numerous social, demographic, and geographic variables. Geographic variations exist in the patterns of maternal mortality.

Keywords

References

  1. Obstet Gynecol Int. 2019 Jan 20;2019:5698436 [PMID: 30805003]
  2. Afr J Reprod Health. 1997 Mar;1(1):14-24 [PMID: 10214399]
  3. J R Stat Soc Ser C Appl Stat. 1999;48(2):253-68 [PMID: 12294883]
  4. Science. 1889 Jun 14;13(332):462-5 [PMID: 17830982]
  5. Med J Islam Repub Iran. 2016 Apr 23;30:360 [PMID: 27453890]
  6. Int J Health Geogr. 2005 Aug 02;4:18 [PMID: 16076391]
  7. Soc Sci Med. 2002 Nov;55(10):1849-69 [PMID: 12383469]

MeSH Term

Humans
Bayes Theorem
Female
Ethiopia
Adult
Maternal Mortality
Pregnancy
Young Adult
Adolescent
Spatial Analysis
Middle Aged
Risk Factors
Health Surveys
Prenatal Care
Socioeconomic Factors

Word Cloud

Created with Highcharts 10.0.0maternaldeathmortalityBayesianmodelEthiopiaGeo-additiveregressionpregnancystudyMaternalcausefactorsdataspatialnumbergeographicpatternBACKGROUNDANDAIMS:definedwomanassociatedmadeworseeitherwithin42 dayspregnancy'sterminationregardlesslengthlocationobjectivedetermineinfluencingwellexamineregionaldistributiondeathsMETHOD:conductedbasicallysecondaryobtained2016EthiopianDemographicHealthsurveyEDHSusedidentifymajorriskeffectsspatial patternRESULT:Pregnancy-relatedproblemschildbirth143%10009womenresearchwhoseagesranged1549contrastsemi-parametricgeneralizedlinearmodelsbasedDICbetterfitsAccordingmodel'sresultssignificantlyaffectedplacedeliveryprenatalcarevisitsmaritalstatuswealthindexmother'sagebirthordersAfarSomaliBenishangulGumuzGambelaregionshigherratesaccordingevidencevariationCONCLUSION:findingsrevealedinfluencednumeroussocialdemographicvariablesGeographicvariationsexistpatternsgeo-additiveanalyzedeterminantsSpatial

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