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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...
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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. |
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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 & 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 & 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 & 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 & Allied Health Database (ProQuest)</collection><collection>ProQuest_Health & 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 & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>Consumer Health Database</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Nursing & 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> |
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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 |
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