Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2024 Nov 29;24(1):3334.
doi: 10.1186/s12889-024-20812-2.

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

Yitagesu Eshetu  1 , Tigist Getachew  2
Affiliations

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

Yitagesu Eshetu et al. BMC Public Health. .

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: Bayesian Geo-additive regression model; Maternal death; Spatial pattern.

PubMed Disclaimer

Conflict of interest statement

Declarations. Ethics approval and consent for publication: For the secondary data analysis, the investigator has received permission from the public domain of the DHS website and reanalyzed the dataset. Consent for publication: Not applicable. Competing interests: The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Maps of Ethiopia for maternal death showing structured spatial effects
Fig. 2
Fig. 2
Maps of Ethiopia for maternal death showing unstructured spatial effects
See this image and copyright information in PMC

Similar articles

See all similar articles

References

    1. Anselin and Bera. (1998). Spatial Dependence in Linear Regression Models with an Introduction to Spatial Econometrics. In A. Ullah (Ed.), Handbook of Applied Economic Statistics (pp. 237–289).
    1. Anselin L. SpaceStat tutorial: A workbook for using SpaceStat in the analysis of spatial data. Urbana-Champaign: University of Illinois; 1992. p. 263.
    1. Bayati M, Vahedi S, Esmaeilzadeh F, Kavosi Z, Jamali Z, Rajabi A, Alimohamadi Y. Determinants of maternal mortality in Eastern Mediterranean region: A panel data analysis. Med J Islamic Republic Iran. 2016;30(1):3–5. - PMC - PubMed
    1. Besag J, York J, Mollie A. Bayesian image restoration, with application in spatial statistics with discussion. Ann Inst Stat Math. 1991;43(1):1–20.
    1. Central Statistic Agency, E. (2016). Ethiopian Demographic and Health survey Final Report.

LinkOut - more resources