Using geographically weighted regression analysis to assess predictors of home birth hot spots in Ethiopia

Annually, 30 million women in Africa become pregnant, with the majority of deliveries taking place at home without the assistance of skilled healthcare personnel. In Ethiopia the proportion of home birth is high with regional disparity. Also limited evidence on spatial regression and deriving predic...

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Published in:PloS one 2023-06, Vol.18 (6), p.e0286704-e0286704
Main Authors: Hailegebreal, Samuel, Haile, Firehiwot, Haile, Yosef, Simegn, Atsedu Endale, Enyew, Ermias Bekele
Format: Article
Language:English
Subjects:
Analysis
Attended births
Biology and Life Sciences
Birth
Childbirth
Childbirth & labor
Childbirth at home
Distribution
Earth Sciences
Education
Educational Status
Ethiopia - epidemiology
Evaluation
Female
Geographical variations
Health care
Health care industry
Health facilities
Health services
Home births
Home Childbirth
Humans
Infant mortality
Least squares method
Maternal mortality
Medicine and Health Sciences
Nutrition research
People and Places
Pregnancy
Pregnant women
Prenatal Care
Public health
Regression analysis
Religion
Sepsis
Skilled labor
Social Sciences
Software
Spatial Analysis
Spatial Regression
Statistical analysis
Statistics
Surveys
Variables
Womens health
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cited_by cdi_FETCH-LOGICAL-c693t-e023248f91aeebcfad8ffe0cde509de631df8df395b131a77527643e8affac473
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creator Hailegebreal, Samuel
Haile, Firehiwot
Haile, Yosef
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Enyew, Ermias Bekele
description Annually, 30 million women in Africa become pregnant, with the majority of deliveries taking place at home without the assistance of skilled healthcare personnel. In Ethiopia the proportion of home birth is high with regional disparity. Also limited evidence on spatial regression and deriving predictors. Therefore, this study aimed to assess the predictors of home birth hot spots using geographically weighted regression in Ethiopia. This study used secondary data from the 2019 Ethiopian Mini Demographic and Health Survey. First, Moran's I and Getis-OrdGi* statistics were used to examine the geographic variation in home births. Further, spatial regression was analyzed using ordinary least squares regression and geographically weighted regression to predict hotspot area of home delivery. According to this result, Somalia, Afar, and the SNNPR region were shown to be high risk locations for home births. Women from rural residence, women having no-education, poorest wealth index, Muslim religion follower, and women with no-ANC visit were predictors of home delivery hotspot locations. The spatial regression revealed women from rural resident, women having no-education, women being in the household with a poorest wealth index, women with Muslim religion follower, and women having no-ANC visit were predictors of home delivery hotspot regions. Therefore, governmental and other stakeholders should remain the effort to decrease home childbirth through access to healthcare services especially for rural resident, strengthen the women for antenatal care visits.
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subjects Analysis
Attended births
Biology and Life Sciences
Birth
Childbirth
Childbirth & labor
Childbirth at home
Distribution
Earth Sciences
Education
Educational Status
Ethiopia - epidemiology
Evaluation
Female
Geographical variations
Health care
Health care industry
Health facilities
Health services
Home births
Home Childbirth
Humans
Infant mortality
Least squares method
Maternal mortality
Medicine and Health Sciences
Nutrition research
People and Places
Pregnancy
Pregnant women
Prenatal Care
Public health
Regression analysis
Religion
Sepsis
Skilled labor
Social Sciences
Software
Spatial Analysis
Spatial Regression
Statistical analysis
Statistics
Surveys
Variables
Womens health
title Using geographically weighted regression analysis to assess predictors of home birth hot spots in Ethiopia
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-30T07%3A17%3A50IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_plos_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Using%20geographically%20weighted%20regression%20analysis%20to%20assess%20predictors%20of%20home%20birth%20hot%20spots%20in%20Ethiopia&rft.jtitle=PloS%20one&rft.au=Hailegebreal,%20Samuel&rft.date=2023-06-06&rft.volume=18&rft.issue=6&rft.spage=e0286704&rft.epage=e0286704&rft.pages=e0286704-e0286704&rft.issn=1932-6203&rft.eissn=1932-6203&rft_id=info:doi/10.1371/journal.pone.0286704&rft_dat=%3Cgale_plos_%3EA752018589%3C/gale_plos_%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c693t-e023248f91aeebcfad8ffe0cde509de631df8df395b131a77527643e8affac473%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2823023828&rft_id=info:pmid/37279238&rft_galeid=A752018589&rfr_iscdi=true