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Female education and maternal health care utilization: evidence from Uganda
Background Maternal health care is among the key indicators of population health and economic development. Therefore, the study attempted to explore female education and maternal healthcare utilization in Uganda. The study identified the causal effect of introduction of free education by exploiting...
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Published in: | Reproductive health 2022-06, Vol.19 (1), p.1-142, Article 142 |
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description | Background Maternal health care is among the key indicators of population health and economic development. Therefore, the study attempted to explore female education and maternal healthcare utilization in Uganda. The study identified the causal effect of introduction of free education by exploiting the age as an instrument at the second stage model (BMC Health Serv Res. 2015. https://doi.org/10.1186/s12913-015-0943-8; Matern Child Health J. 2009;14:988–98). This instrument provided an exogenous source of variation in the years of schooling and allowed to implement a regression discontinuity design which accounted for heterogeneity in the cohort overtime. Methods The study used the Ordinary Least Squares (OLS) to help predict years of schooling that were used in the second stage model in the Two Stage Least Squares (2SLS). The study further used the Regression Discontinuity Design (RDD) model with a running variable of birth years to observe its effect on education. To control for heterogeneity in regions in the second stage model, a fixed effects model was used. Results Female education indeed had a positive impact on maternal health care utilization. It was further found out that age also influences maternal health care utilization. Conclusions Therefore, as an effort to improve professional maternal health care utilisation, there is need to focus on education beyond primary level. Uganda Government should also ensure that there is an improvement in community infrastructure and security across all regions and locations. |
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Therefore, the study attempted to explore female education and maternal healthcare utilization in Uganda. The study identified the causal effect of introduction of free education by exploiting the age as an instrument at the second stage model (BMC Health Serv Res. 2015. https://doi.org/10.1186/s12913-015-0943-8; Matern Child Health J. 2009;14:988–98). This instrument provided an exogenous source of variation in the years of schooling and allowed to implement a regression discontinuity design which accounted for heterogeneity in the cohort overtime. Methods The study used the Ordinary Least Squares (OLS) to help predict years of schooling that were used in the second stage model in the Two Stage Least Squares (2SLS). The study further used the Regression Discontinuity Design (RDD) model with a running variable of birth years to observe its effect on education. To control for heterogeneity in regions in the second stage model, a fixed effects model was used. Results Female education indeed had a positive impact on maternal health care utilization. It was further found out that age also influences maternal health care utilization. Conclusions Therefore, as an effort to improve professional maternal health care utilisation, there is need to focus on education beyond primary level. Uganda Government should also ensure that there is an improvement in community infrastructure and security across all regions and locations.</description><identifier>ISSN: 1742-4755</identifier><identifier>EISSN: 1742-4755</identifier><identifier>DOI: 10.1186/s12978-022-01432-8</identifier><identifier>PMID: 35725605</identifier><language>eng</language><publisher>London: BioMed Central</publisher><subject>2SLS ; Birth order ; Births ; Developing countries ; Economic growth ; Education ; Fertility ; Fixed effects ; Health care policy ; Health services utilization ; Health surveys ; Households ; LDCs ; Life expectancy ; Marital status ; Maternal & child health ; Maternal mortality ; MHC ; OLS ; Pregnancy ; Prenatal care ; RDD ; Religion ; Reproductive health ; Rural areas ; Tetanus ; Womens health</subject><ispartof>Reproductive health, 2022-06, Vol.19 (1), p.1-142, Article 142</ispartof><rights>2022. 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>The Author(s) 2022</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3888-81c7fa64250019347420c237669f1475a7837a944bd66aa5606855adf9a90f593</citedby><cites>FETCH-LOGICAL-c3888-81c7fa64250019347420c237669f1475a7837a944bd66aa5606855adf9a90f593</cites><orcidid>0000-0001-6412-5169</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC9208099/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2691525143?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,881,25728,27898,27899,36986,36987,44563,53763,53765</link.rule.ids></links><search><creatorcontrib>Amwonya, David</creatorcontrib><creatorcontrib>Kigosa, Nathan</creatorcontrib><creatorcontrib>Kizza, James</creatorcontrib><title>Female education and maternal health care utilization: evidence from Uganda</title><title>Reproductive health</title><description>Background Maternal health care is among the key indicators of population health and economic development. Therefore, the study attempted to explore female education and maternal healthcare utilization in Uganda. The study identified the causal effect of introduction of free education by exploiting the age as an instrument at the second stage model (BMC Health Serv Res. 2015. https://doi.org/10.1186/s12913-015-0943-8; Matern Child Health J. 2009;14:988–98). This instrument provided an exogenous source of variation in the years of schooling and allowed to implement a regression discontinuity design which accounted for heterogeneity in the cohort overtime. Methods The study used the Ordinary Least Squares (OLS) to help predict years of schooling that were used in the second stage model in the Two Stage Least Squares (2SLS). The study further used the Regression Discontinuity Design (RDD) model with a running variable of birth years to observe its effect on education. To control for heterogeneity in regions in the second stage model, a fixed effects model was used. Results Female education indeed had a positive impact on maternal health care utilization. It was further found out that age also influences maternal health care utilization. Conclusions Therefore, as an effort to improve professional maternal health care utilisation, there is need to focus on education beyond primary level. Uganda Government should also ensure that there is an improvement in community infrastructure and security across all regions and locations.</description><subject>2SLS</subject><subject>Birth order</subject><subject>Births</subject><subject>Developing countries</subject><subject>Economic growth</subject><subject>Education</subject><subject>Fertility</subject><subject>Fixed effects</subject><subject>Health care policy</subject><subject>Health services utilization</subject><subject>Health surveys</subject><subject>Households</subject><subject>LDCs</subject><subject>Life expectancy</subject><subject>Marital status</subject><subject>Maternal & child health</subject><subject>Maternal mortality</subject><subject>MHC</subject><subject>OLS</subject><subject>Pregnancy</subject><subject>Prenatal care</subject><subject>RDD</subject><subject>Religion</subject><subject>Reproductive health</subject><subject>Rural areas</subject><subject>Tetanus</subject><subject>Womens health</subject><issn>1742-4755</issn><issn>1742-4755</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNpdkU1rFTEUhgdRbG39A64CbtyM5vvDhSDFamnBTbsO5yYn9-YyM6mZmYL-emfuLWK7Ssh58vJw3qZ5x-hHxqz-NDLujG0p5y1lUvDWvmhOmZG8lUapl__dT5o347inVDBLzevmRCjDlabqtLm-xB46JBjnAFMuA4Ehkh4mrAN0ZIfQTTsSoCKZp9zlPwfoM8GHHHEISFItPbnbLr_gvHmVoBvx7eN51txdfru9-NHe_Px-dfH1pg3CWttaFkwCLbmilDkhF0kauDBau8QWWzBWGHBSbqLWAIuntkpBTA4cTcqJs-bqmBsL7P19zT3U375A9oeHUrce6pRDhz4iuphwWQ8YaQBtZBthxUZLRw0mXLK-HLPu502PMeAwVeiehD6dDHnnt-XBO04tdavMh8eAWn7NOE6-z2PAroMByzx6ro3jQiq9ou-fofsyr2teKccUV0uLC8WPVKhlHCumfzKM-rV3f-zdL737Q-_eir_NpJ2j</recordid><startdate>20220620</startdate><enddate>20220620</enddate><creator>Amwonya, David</creator><creator>Kigosa, Nathan</creator><creator>Kizza, James</creator><general>BioMed Central</general><general>BMC</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</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>M0S</scope><scope>M1P</scope><scope>PHGZM</scope><scope>PHGZT</scope><scope>PIMPY</scope><scope>PJZUB</scope><scope>PKEHL</scope><scope>PPXIY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0001-6412-5169</orcidid></search><sort><creationdate>20220620</creationdate><title>Female education and maternal health care utilization: evidence from Uganda</title><author>Amwonya, David ; Kigosa, Nathan ; Kizza, James</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3888-81c7fa64250019347420c237669f1475a7837a944bd66aa5606855adf9a90f593</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>2SLS</topic><topic>Birth order</topic><topic>Births</topic><topic>Developing countries</topic><topic>Economic growth</topic><topic>Education</topic><topic>Fertility</topic><topic>Fixed effects</topic><topic>Health care policy</topic><topic>Health services utilization</topic><topic>Health surveys</topic><topic>Households</topic><topic>LDCs</topic><topic>Life expectancy</topic><topic>Marital status</topic><topic>Maternal & child health</topic><topic>Maternal mortality</topic><topic>MHC</topic><topic>OLS</topic><topic>Pregnancy</topic><topic>Prenatal care</topic><topic>RDD</topic><topic>Religion</topic><topic>Reproductive health</topic><topic>Rural areas</topic><topic>Tetanus</topic><topic>Womens health</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Amwonya, David</creatorcontrib><creatorcontrib>Kigosa, Nathan</creatorcontrib><creatorcontrib>Kizza, James</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>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>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>ProQuest Health & Medical Complete (Alumni)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>PML(ProQuest Medical Library)</collection><collection>ProQuest Central (New)</collection><collection>ProQuest One Academic (New)</collection><collection>Publicly Available Content (ProQuest)</collection><collection>ProQuest Health & Medical Research Collection</collection><collection>ProQuest One Academic Middle East (New)</collection><collection>ProQuest One Health & Nursing</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>Directory of Open Access Journals</collection><jtitle>Reproductive health</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Amwonya, David</au><au>Kigosa, Nathan</au><au>Kizza, James</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Female education and maternal health care utilization: evidence from Uganda</atitle><jtitle>Reproductive health</jtitle><date>2022-06-20</date><risdate>2022</risdate><volume>19</volume><issue>1</issue><spage>1</spage><epage>142</epage><pages>1-142</pages><artnum>142</artnum><issn>1742-4755</issn><eissn>1742-4755</eissn><abstract>Background Maternal health care is among the key indicators of population health and economic development. Therefore, the study attempted to explore female education and maternal healthcare utilization in Uganda. The study identified the causal effect of introduction of free education by exploiting the age as an instrument at the second stage model (BMC Health Serv Res. 2015. https://doi.org/10.1186/s12913-015-0943-8; Matern Child Health J. 2009;14:988–98). This instrument provided an exogenous source of variation in the years of schooling and allowed to implement a regression discontinuity design which accounted for heterogeneity in the cohort overtime. Methods The study used the Ordinary Least Squares (OLS) to help predict years of schooling that were used in the second stage model in the Two Stage Least Squares (2SLS). The study further used the Regression Discontinuity Design (RDD) model with a running variable of birth years to observe its effect on education. To control for heterogeneity in regions in the second stage model, a fixed effects model was used. Results Female education indeed had a positive impact on maternal health care utilization. It was further found out that age also influences maternal health care utilization. Conclusions Therefore, as an effort to improve professional maternal health care utilisation, there is need to focus on education beyond primary level. Uganda Government should also ensure that there is an improvement in community infrastructure and security across all regions and locations.</abstract><cop>London</cop><pub>BioMed Central</pub><pmid>35725605</pmid><doi>10.1186/s12978-022-01432-8</doi><orcidid>https://orcid.org/0000-0001-6412-5169</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | 2SLS Birth order Births Developing countries Economic growth Education Fertility Fixed effects Health care policy Health services utilization Health surveys Households LDCs Life expectancy Marital status Maternal & child health Maternal mortality MHC OLS Pregnancy Prenatal care RDD Religion Reproductive health Rural areas Tetanus Womens health |
title | Female education and maternal health care utilization: evidence from Uganda |
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