Evidence map›Paper›PMID 37116949›Full record

ArticleBMJ health & care informatics2023

Women's health service access and associated factors in Ethiopia: application of geographical information system and multilevel analysis.

Addisalem Workie Demsash, Agmasie Damtew Walle

Abstract read
In one paragraph

Article in BMJ health & care informatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

26 citing papers in PubMed.

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  10. Rheumatic heart disease burden and determinants in cardiac patients: A follow up care concern in Ethiopia.International journal of cardiology. Cardiovascular risk and prevention · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Addisalem Workie DemsashMettu University, College of Health Science, Health Informatics Department, Mettu, Ethiopia addisalemworkie599@gmail.com.ORCID http://orcid.org/0000-0002-9356-8126
Agmasie Damtew WalleMettu University, College of Health Science, Health Informatics Department, Mettu, Ethiopia.ORCID http://orcid.org/0000-0001-9583-5876

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesWomen's access to healthcare services is challenged by various factors. This study aimed to assess women's health service access and identify associated factors.

methodsA cross-sectional study design with a two-stage stratified sampling technique, and 12 945 women from the 2016 Ethiopia Demographic and Health Survey dataset were used. The spatial hotspot analysis and purely Bernoulli-based model scan statistics were used to highlight hot and cold spot areas, and to detect significant local clusters of women's health service access. A multilevel logistic regression analysis was used to assess factors that affect women's access to health services. A variable with a p<o.o5 was considered as a significant factor.

resultsOverall, 29.8%% of women had health services access. 70.2% of women had problems with health services access such as: not wanting to go alone (42%), distance to health facilities (51%), getting the money needed for treatment (55%) and getting permission to go for medical care (32.3%). The spatial distribution of health service access in Ethiopia was clustered, and low health service access was observed in most areas of the country. Women who lived in primary, secondary and tertiary clusters were 96%, 39% and 72% more likely to access health services. Educational status, rich wealth status, media exposure and rural residence were statistically significant factors.

conclusionsIn Ethiopia, women have problems with health services access. The spatial distribution of health services access was non-random, and hotspot areas of women's health service access were visualised in parts of Benishangul Gumez, Amhara, Afar, DireDawa, Harari, and Somali regions. Creating job opportunities, public health promotion regarding maternal health service utilisation and constructing nearby health facilities are required for better healthcare service access for women.

Indexed as

Geographic Information SystemsHealth Services AccessibilityCross-Sectional StudiesEthiopiaFemaleHumansMultilevel AnalysisWomen's Health Services

Identifiers

PMID37116949
PMCPMC10151888

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LicenceCC BY
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Registered trials

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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.