Loading…

Geospatial disparities and predictors of anaemia among pregnant women in Sub-Saharan Africa

BackgroundAnaemia has become a major public health concern among women in Sub-Saharan Africa (SSA). However, little is known about the spatial disparities in anaemia prevalence and their associated factors among pregnant women in the region. This study analysed the spatial disparities in anaemia and...

Full description

Saved in:
Bibliographic Details
Published in:BMC pregnancy and childbirth 2023-10, Vol.23 (1), p.1-743, Article 743
Main Authors: Nyarko, Samuel H., Boateng, Ebenezer N.K, Dickson, Kwamena S., Adzrago, David, Addo, Isaac Y., Acquah, Evelyn, Ayebeng, Castro
Format: Article
Language:English
Subjects:
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by cdi_FETCH-LOGICAL-c541t-a2143c513e66df0b02428a0d9195c7b8fc08cdd7afce1954009f0ebe66ce622e3
cites cdi_FETCH-LOGICAL-c541t-a2143c513e66df0b02428a0d9195c7b8fc08cdd7afce1954009f0ebe66ce622e3
container_end_page 743
container_issue 1
container_start_page 1
container_title BMC pregnancy and childbirth
container_volume 23
creator Nyarko, Samuel H.
Boateng, Ebenezer N.K
Dickson, Kwamena S.
Adzrago, David
Addo, Isaac Y.
Acquah, Evelyn
Ayebeng, Castro
description BackgroundAnaemia has become a major public health concern among women in Sub-Saharan Africa (SSA). However, little is known about the spatial disparities in anaemia prevalence and their associated factors among pregnant women in the region. This study analysed the spatial disparities in anaemia and their associated factors among pregnant women in rural and urban settings in SSA.MethodsThis is a secondary analysis of the most recent demographic and health surveys of 26 countries in SSA. Spatial autocorrelation and hotspot assessment were conducted, while a multivariate logistic regression model was used to identify demographic factors associated with anaemia.ResultsAnaemia was reported among ~50% of pregnant women in urban and rural areas of SSA. The hotspot analysis identified the West African sub-region as having a higher concentration of anaemia cases in rural settings. In urban areas, the odds of anaemia were significantly higher among pregnant women in their second trimester (Adjusted OR = 2.39, CI = 1.99, 2.76). On the other hand, pregnant women in their third trimester (Adjusted OR = 1.98, CI = 1.77, 2.22) and those who had taken intestinal parasite drugs (Adjusted OR = 1.12 CI = 1.02, 1.23) had a higher likelihood of having anaemia in rural areas. Pregnant women aged 35–39 years (Adjusted OR = 0.52, CI = 0.33, 0.81) and those aged 40–44 years (Adjusted OR = 0.69, CI = 0.50, 0.95) had a lesser likelihood of having anaemia compared to women aged 15–19 years in urban and rural areas respectively. Compared to Congo DR, Benin (OR = 2.22, CI = 1.51, 3.28) and Mali (OR = 3.71, CI = 2.73, 5.05) had higher odds of anaemia in urban and rural areas respectively.ConclusionsSpatial disparities in anaemia persist among pregnant women in rural and urban settings in SSA. Prevailing spatial variations in anaemia may be addressed by specialised interventions considering the contextual residential settings and socio-economic factors highlighted in this study.
doi_str_mv 10.1186/s12884-023-06008-3
format article
fullrecord <record><control><sourceid>proquest_doaj_</sourceid><recordid>TN_cdi_doaj_primary_oai_doaj_org_article_79ad25c159544fc7b4755ced67bbe93b</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><doaj_id>oai_doaj_org_article_79ad25c159544fc7b4755ced67bbe93b</doaj_id><sourcerecordid>2890066574</sourcerecordid><originalsourceid>FETCH-LOGICAL-c541t-a2143c513e66df0b02428a0d9195c7b8fc08cdd7afce1954009f0ebe66ce622e3</originalsourceid><addsrcrecordid>eNpdks1u1TAQRiMEoqXwAqwisWETGP_FzgpVFZRKlVgUViysiT259VViX-wExNvj9laIsvJo5ujImvma5jWDd4yZ_n1h3BjZARcd9ACmE0-aUyY167gYxNN_6pPmRSl7AKaNgufNidCmlxzEafP9klI54Bpwbn2oVQ5roNJi9O0hkw9uTbm0aaodpCVgi0uKu7vZLmJc219podiG2N5sY3eDt5gxtudTDg5fNs8mnAu9enjPmm-fPn69-Nxdf7m8uji_7pySbO2QMymcYoL63k8wApfcIPiBDcrp0UwOjPNe4-SotiTAMAGNlXbUc07irLk6en3CvT3ksGD-bRMGe99IeWcxr8HNZPWAnivHVPXIqdqlVsqR7_U40iDG6vpwdB22cSHvKK4Z50fSx5MYbu0u_bQMlDHM6Gp4-2DI6cdGZbVLKI7mGSOlrdh6M2D1ZkJV9M1_6D5tOdZdVWoA6HulZaX4kXI5lZJp-vsbBvYuCPYYBFul9j4IVog_G3KlSw</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2890066574</pqid></control><display><type>article</type><title>Geospatial disparities and predictors of anaemia among pregnant women in Sub-Saharan Africa</title><source>NCBI_PubMed Central(免费)</source><source>Publicly Available Content (ProQuest)</source><creator>Nyarko, Samuel H. ; Boateng, Ebenezer N.K ; Dickson, Kwamena S. ; Adzrago, David ; Addo, Isaac Y. ; Acquah, Evelyn ; Ayebeng, Castro</creator><creatorcontrib>Nyarko, Samuel H. ; Boateng, Ebenezer N.K ; Dickson, Kwamena S. ; Adzrago, David ; Addo, Isaac Y. ; Acquah, Evelyn ; Ayebeng, Castro</creatorcontrib><description>BackgroundAnaemia has become a major public health concern among women in Sub-Saharan Africa (SSA). However, little is known about the spatial disparities in anaemia prevalence and their associated factors among pregnant women in the region. This study analysed the spatial disparities in anaemia and their associated factors among pregnant women in rural and urban settings in SSA.MethodsThis is a secondary analysis of the most recent demographic and health surveys of 26 countries in SSA. Spatial autocorrelation and hotspot assessment were conducted, while a multivariate logistic regression model was used to identify demographic factors associated with anaemia.ResultsAnaemia was reported among ~50% of pregnant women in urban and rural areas of SSA. The hotspot analysis identified the West African sub-region as having a higher concentration of anaemia cases in rural settings. In urban areas, the odds of anaemia were significantly higher among pregnant women in their second trimester (Adjusted OR = 2.39, CI = 1.99, 2.76). On the other hand, pregnant women in their third trimester (Adjusted OR = 1.98, CI = 1.77, 2.22) and those who had taken intestinal parasite drugs (Adjusted OR = 1.12 CI = 1.02, 1.23) had a higher likelihood of having anaemia in rural areas. Pregnant women aged 35–39 years (Adjusted OR = 0.52, CI = 0.33, 0.81) and those aged 40–44 years (Adjusted OR = 0.69, CI = 0.50, 0.95) had a lesser likelihood of having anaemia compared to women aged 15–19 years in urban and rural areas respectively. Compared to Congo DR, Benin (OR = 2.22, CI = 1.51, 3.28) and Mali (OR = 3.71, CI = 2.73, 5.05) had higher odds of anaemia in urban and rural areas respectively.ConclusionsSpatial disparities in anaemia persist among pregnant women in rural and urban settings in SSA. Prevailing spatial variations in anaemia may be addressed by specialised interventions considering the contextual residential settings and socio-economic factors highlighted in this study.</description><identifier>ISSN: 1471-2393</identifier><identifier>EISSN: 1471-2393</identifier><identifier>DOI: 10.1186/s12884-023-06008-3</identifier><identifier>PMID: 37864203</identifier><language>eng</language><publisher>London: BioMed Central</publisher><subject>Anaemia ; Anemia ; Geospatial ; Health insurance ; Hematology ; Hemoglobin ; Households ; Iron ; Literacy ; Marital status ; Maternal &amp; child health ; Pregnancy ; Pregnant women ; Rural areas ; Socioeconomic factors ; Statistical analysis ; Sub-Saharan Africa ; Urban areas ; Variables ; Womens health</subject><ispartof>BMC pregnancy and childbirth, 2023-10, Vol.23 (1), p.1-743, Article 743</ispartof><rights>2023. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>BioMed Central Ltd., part of Springer Nature 2023</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c541t-a2143c513e66df0b02428a0d9195c7b8fc08cdd7afce1954009f0ebe66ce622e3</citedby><cites>FETCH-LOGICAL-c541t-a2143c513e66df0b02428a0d9195c7b8fc08cdd7afce1954009f0ebe66ce622e3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC10588187/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2890066574?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,25751,27922,27923,37010,37011,44588,53789,53791</link.rule.ids></links><search><creatorcontrib>Nyarko, Samuel H.</creatorcontrib><creatorcontrib>Boateng, Ebenezer N.K</creatorcontrib><creatorcontrib>Dickson, Kwamena S.</creatorcontrib><creatorcontrib>Adzrago, David</creatorcontrib><creatorcontrib>Addo, Isaac Y.</creatorcontrib><creatorcontrib>Acquah, Evelyn</creatorcontrib><creatorcontrib>Ayebeng, Castro</creatorcontrib><title>Geospatial disparities and predictors of anaemia among pregnant women in Sub-Saharan Africa</title><title>BMC pregnancy and childbirth</title><description>BackgroundAnaemia has become a major public health concern among women in Sub-Saharan Africa (SSA). However, little is known about the spatial disparities in anaemia prevalence and their associated factors among pregnant women in the region. This study analysed the spatial disparities in anaemia and their associated factors among pregnant women in rural and urban settings in SSA.MethodsThis is a secondary analysis of the most recent demographic and health surveys of 26 countries in SSA. Spatial autocorrelation and hotspot assessment were conducted, while a multivariate logistic regression model was used to identify demographic factors associated with anaemia.ResultsAnaemia was reported among ~50% of pregnant women in urban and rural areas of SSA. The hotspot analysis identified the West African sub-region as having a higher concentration of anaemia cases in rural settings. In urban areas, the odds of anaemia were significantly higher among pregnant women in their second trimester (Adjusted OR = 2.39, CI = 1.99, 2.76). On the other hand, pregnant women in their third trimester (Adjusted OR = 1.98, CI = 1.77, 2.22) and those who had taken intestinal parasite drugs (Adjusted OR = 1.12 CI = 1.02, 1.23) had a higher likelihood of having anaemia in rural areas. Pregnant women aged 35–39 years (Adjusted OR = 0.52, CI = 0.33, 0.81) and those aged 40–44 years (Adjusted OR = 0.69, CI = 0.50, 0.95) had a lesser likelihood of having anaemia compared to women aged 15–19 years in urban and rural areas respectively. Compared to Congo DR, Benin (OR = 2.22, CI = 1.51, 3.28) and Mali (OR = 3.71, CI = 2.73, 5.05) had higher odds of anaemia in urban and rural areas respectively.ConclusionsSpatial disparities in anaemia persist among pregnant women in rural and urban settings in SSA. Prevailing spatial variations in anaemia may be addressed by specialised interventions considering the contextual residential settings and socio-economic factors highlighted in this study.</description><subject>Anaemia</subject><subject>Anemia</subject><subject>Geospatial</subject><subject>Health insurance</subject><subject>Hematology</subject><subject>Hemoglobin</subject><subject>Households</subject><subject>Iron</subject><subject>Literacy</subject><subject>Marital status</subject><subject>Maternal &amp; child health</subject><subject>Pregnancy</subject><subject>Pregnant women</subject><subject>Rural areas</subject><subject>Socioeconomic factors</subject><subject>Statistical analysis</subject><subject>Sub-Saharan Africa</subject><subject>Urban areas</subject><subject>Variables</subject><subject>Womens health</subject><issn>1471-2393</issn><issn>1471-2393</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNpdks1u1TAQRiMEoqXwAqwisWETGP_FzgpVFZRKlVgUViysiT259VViX-wExNvj9laIsvJo5ujImvma5jWDd4yZ_n1h3BjZARcd9ACmE0-aUyY167gYxNN_6pPmRSl7AKaNgufNidCmlxzEafP9klI54Bpwbn2oVQ5roNJi9O0hkw9uTbm0aaodpCVgi0uKu7vZLmJc219podiG2N5sY3eDt5gxtudTDg5fNs8mnAu9enjPmm-fPn69-Nxdf7m8uji_7pySbO2QMymcYoL63k8wApfcIPiBDcrp0UwOjPNe4-SotiTAMAGNlXbUc07irLk6en3CvT3ksGD-bRMGe99IeWcxr8HNZPWAnivHVPXIqdqlVsqR7_U40iDG6vpwdB22cSHvKK4Z50fSx5MYbu0u_bQMlDHM6Gp4-2DI6cdGZbVLKI7mGSOlrdh6M2D1ZkJV9M1_6D5tOdZdVWoA6HulZaX4kXI5lZJp-vsbBvYuCPYYBFul9j4IVog_G3KlSw</recordid><startdate>20231020</startdate><enddate>20231020</enddate><creator>Nyarko, Samuel H.</creator><creator>Boateng, Ebenezer N.K</creator><creator>Dickson, Kwamena S.</creator><creator>Adzrago, David</creator><creator>Addo, Isaac Y.</creator><creator>Acquah, Evelyn</creator><creator>Ayebeng, Castro</creator><general>BioMed Central</general><general>BMC</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7RV</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>K9-</scope><scope>K9.</scope><scope>KB0</scope><scope>M0R</scope><scope>M0S</scope><scope>M1P</scope><scope>NAPCQ</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope></search><sort><creationdate>20231020</creationdate><title>Geospatial disparities and predictors of anaemia among pregnant women in Sub-Saharan Africa</title><author>Nyarko, Samuel H. ; Boateng, Ebenezer N.K ; Dickson, Kwamena S. ; Adzrago, David ; Addo, Isaac Y. ; Acquah, Evelyn ; Ayebeng, Castro</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c541t-a2143c513e66df0b02428a0d9195c7b8fc08cdd7afce1954009f0ebe66ce622e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Anaemia</topic><topic>Anemia</topic><topic>Geospatial</topic><topic>Health insurance</topic><topic>Hematology</topic><topic>Hemoglobin</topic><topic>Households</topic><topic>Iron</topic><topic>Literacy</topic><topic>Marital status</topic><topic>Maternal &amp; child health</topic><topic>Pregnancy</topic><topic>Pregnant women</topic><topic>Rural areas</topic><topic>Socioeconomic factors</topic><topic>Statistical analysis</topic><topic>Sub-Saharan Africa</topic><topic>Urban areas</topic><topic>Variables</topic><topic>Womens health</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Nyarko, Samuel H.</creatorcontrib><creatorcontrib>Boateng, Ebenezer N.K</creatorcontrib><creatorcontrib>Dickson, Kwamena S.</creatorcontrib><creatorcontrib>Adzrago, David</creatorcontrib><creatorcontrib>Addo, Isaac Y.</creatorcontrib><creatorcontrib>Acquah, Evelyn</creatorcontrib><creatorcontrib>Ayebeng, Castro</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Nursing &amp; Allied Health Database (ProQuest)</collection><collection>ProQuest_Health &amp; Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>ProQuest Central Essentials</collection><collection>AUTh Library subscriptions: ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>Consumer Health Database</collection><collection>ProQuest Health &amp; Medical Complete (Alumni)</collection><collection>Nursing &amp; Allied Health Database (Alumni Edition)</collection><collection>Consumer Health Database</collection><collection>Health &amp; Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Nursing &amp; Allied Health Premium</collection><collection>Publicly Available Content (ProQuest)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>BMC pregnancy and childbirth</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Nyarko, Samuel H.</au><au>Boateng, Ebenezer N.K</au><au>Dickson, Kwamena S.</au><au>Adzrago, David</au><au>Addo, Isaac Y.</au><au>Acquah, Evelyn</au><au>Ayebeng, Castro</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Geospatial disparities and predictors of anaemia among pregnant women in Sub-Saharan Africa</atitle><jtitle>BMC pregnancy and childbirth</jtitle><date>2023-10-20</date><risdate>2023</risdate><volume>23</volume><issue>1</issue><spage>1</spage><epage>743</epage><pages>1-743</pages><artnum>743</artnum><issn>1471-2393</issn><eissn>1471-2393</eissn><abstract>BackgroundAnaemia has become a major public health concern among women in Sub-Saharan Africa (SSA). However, little is known about the spatial disparities in anaemia prevalence and their associated factors among pregnant women in the region. This study analysed the spatial disparities in anaemia and their associated factors among pregnant women in rural and urban settings in SSA.MethodsThis is a secondary analysis of the most recent demographic and health surveys of 26 countries in SSA. Spatial autocorrelation and hotspot assessment were conducted, while a multivariate logistic regression model was used to identify demographic factors associated with anaemia.ResultsAnaemia was reported among ~50% of pregnant women in urban and rural areas of SSA. The hotspot analysis identified the West African sub-region as having a higher concentration of anaemia cases in rural settings. In urban areas, the odds of anaemia were significantly higher among pregnant women in their second trimester (Adjusted OR = 2.39, CI = 1.99, 2.76). On the other hand, pregnant women in their third trimester (Adjusted OR = 1.98, CI = 1.77, 2.22) and those who had taken intestinal parasite drugs (Adjusted OR = 1.12 CI = 1.02, 1.23) had a higher likelihood of having anaemia in rural areas. Pregnant women aged 35–39 years (Adjusted OR = 0.52, CI = 0.33, 0.81) and those aged 40–44 years (Adjusted OR = 0.69, CI = 0.50, 0.95) had a lesser likelihood of having anaemia compared to women aged 15–19 years in urban and rural areas respectively. Compared to Congo DR, Benin (OR = 2.22, CI = 1.51, 3.28) and Mali (OR = 3.71, CI = 2.73, 5.05) had higher odds of anaemia in urban and rural areas respectively.ConclusionsSpatial disparities in anaemia persist among pregnant women in rural and urban settings in SSA. Prevailing spatial variations in anaemia may be addressed by specialised interventions considering the contextual residential settings and socio-economic factors highlighted in this study.</abstract><cop>London</cop><pub>BioMed Central</pub><pmid>37864203</pmid><doi>10.1186/s12884-023-06008-3</doi><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 1471-2393
ispartof BMC pregnancy and childbirth, 2023-10, Vol.23 (1), p.1-743, Article 743
issn 1471-2393
1471-2393
language eng
recordid cdi_doaj_primary_oai_doaj_org_article_79ad25c159544fc7b4755ced67bbe93b
source NCBI_PubMed Central(免费); Publicly Available Content (ProQuest)
subjects Anaemia
Anemia
Geospatial
Health insurance
Hematology
Hemoglobin
Households
Iron
Literacy
Marital status
Maternal & child health
Pregnancy
Pregnant women
Rural areas
Socioeconomic factors
Statistical analysis
Sub-Saharan Africa
Urban areas
Variables
Womens health
title Geospatial disparities and predictors of anaemia among pregnant women in Sub-Saharan Africa
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-14T14%3A24%3A24IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_doaj_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Geospatial%20disparities%20and%20predictors%20of%20anaemia%20among%20pregnant%20women%20in%20Sub-Saharan%20Africa&rft.jtitle=BMC%20pregnancy%20and%20childbirth&rft.au=Nyarko,%20Samuel%20H.&rft.date=2023-10-20&rft.volume=23&rft.issue=1&rft.spage=1&rft.epage=743&rft.pages=1-743&rft.artnum=743&rft.issn=1471-2393&rft.eissn=1471-2393&rft_id=info:doi/10.1186/s12884-023-06008-3&rft_dat=%3Cproquest_doaj_%3E2890066574%3C/proquest_doaj_%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c541t-a2143c513e66df0b02428a0d9195c7b8fc08cdd7afce1954009f0ebe66ce622e3%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2890066574&rft_id=info:pmid/37864203&rfr_iscdi=true