Evidence map›Paper›PMID 39188539›Full record

ArticleFrontiers in global women's health2024

Spatial variation of skilled birth attendance and associated factors among reproductive age women in Ethiopia, 2019; a spatial and multilevel analysis.

Fantu Mamo Aragaw, Gela Atlie, Amensisa Hailu Tesfaye, Daniel Gashaneh Belay

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Article in Frontiers in global women's health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

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5citing papers in PubMed
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5 citing papers in PubMed.

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5 · Who and what money

Authors and funding

4 authors.

Fantu Mamo AragawDepartment of Epidemiology and Biostatistics, Institute of Public Health, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia.
Gela AtlieDepartment of Internal Medicine, College of Medicine and Health Sciences, Madda Walabu University, Goba, Oromia, Ethiopia.
Amensisa Hailu TesfayeDepartment of Environmental and Occupational Health and Safety, Institute of Public Health, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia.
Daniel Gashaneh BelayDepartment of Epidemiology and Biostatistics, Institute of Public Health, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The majority of maternal deaths were associated with a lack of access to skilled birth attendance. Because childbirth accounts for most maternal deaths, skilled birth attendance is crucial for reducing maternal mortality. The use of skilled birth attendance in Ethiopia is low, and it is crucial to identify factors that determine the use of skilled birth attendance. Hence, this study aimed to assess the spatial distribution, wealth-related inequality, and determinants for skilled birth attendance in Ethiopia. Methods: Secondary data analysis was done with a total weighted sample of 5,251 reproductive-aged women using the 2019 mini EDHS. The concentration index and graph were used to assess wealth-related inequalities. Spatial analysis was done to identify the spatial distribution and multilevel logistic regression analysis was used to identify predictors of skilled birth attendance in Ethiopia. Analysis was done using STATA version 14, ArcGIS, and SaTscan software. Results: The prevalence of skilled birth attendance was 50.04% (95% CI: 48.69%, 51.40%) in Ethiopia. Old age, being married, being educated, having television and radio, having ANC visits, being multiparous, having large household sizes, having a rich wealth index, living in rural residence, and living in a high level of community poverty and women's education were significant predictors of skilled birth attendance. Skilled birth attendance was disproportionately concentrated in rich households [C = 0.482; 95% CI: 0.436, 0.528]. High prevalence of unskilled birth attendance was found in Somalia, SNNP, Afar, and southern parts of the Amhara regions. Primary clusters of unskilled birth attendance Somalia and some parts of Oromia region of Ethiopia. Conclusion: Half of the women in Ethiopia did not utilize skilled birth attendants with significant spatial clustering. Age, marital status, educational status, ANC Visit, having television and radio, parity, household size, wealth index, residence, community level poverty, and community level of women's education were significant predictors of skilled birth attendance. Skilled birth attendance was unevenly concentrated in rich households. The regions of Somalia, SNNP, Afar, and southern Amhara were identified as having a high prevalence of using unskilled birth attendance. Public health interventions should target those women at high risk of using unskilled birth attendants.

Indexed as

Ethiopiamultilevel analysisskilled birth attendancespatial variationwomen

Identifiers

PMID39188539
PMCPMC11345201

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.