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Spatial variation and inequities in antenatal care coverage in Kenya, Uganda and mainland Tanzania using model-based geostatistics: a socioeconomic and geographical accessibility lens

BACKGROUND: Pregnant women in sub-Saharan Africa (SSA) experience the highest levels of maternal mortality and stillbirths due to predominantly avoidable causes. Antenatal care (ANC) can prevent, detect, alleviate, or manage these causes. While eight ANC contacts are now recommended, coverage of the...

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Autores principales: Macharia, Peter M., Joseph, Noel K., Nalwadda, Gorrette Kayondo, Mwilike, Beatrice, Banke-Thomas, Aduragbemi, Benova, Lenka, Johnson, Olatunji
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9724345/
https://www.ncbi.nlm.nih.gov/pubmed/36474193
http://dx.doi.org/10.1186/s12884-022-05238-1
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author Macharia, Peter M.
Joseph, Noel K.
Nalwadda, Gorrette Kayondo
Mwilike, Beatrice
Banke-Thomas, Aduragbemi
Benova, Lenka
Johnson, Olatunji
author_facet Macharia, Peter M.
Joseph, Noel K.
Nalwadda, Gorrette Kayondo
Mwilike, Beatrice
Banke-Thomas, Aduragbemi
Benova, Lenka
Johnson, Olatunji
author_sort Macharia, Peter M.
collection PubMed
description BACKGROUND: Pregnant women in sub-Saharan Africa (SSA) experience the highest levels of maternal mortality and stillbirths due to predominantly avoidable causes. Antenatal care (ANC) can prevent, detect, alleviate, or manage these causes. While eight ANC contacts are now recommended, coverage of the previous minimum of four visits (ANC4+) remains low and inequitable in SSA. METHODS: We modelled ANC4+ coverage and likelihood of attaining district-level target coverage of 70% across three equity stratifiers (household wealth, maternal education, and travel time to the nearest health facility) based on data from malaria indicator surveys in Kenya (2020), Uganda (2018/19) and Tanzania (2017). Geostatistical models were fitted to predict ANC4+ coverage and compute exceedance probability for target coverage. The number of pregnant women without ANC4+ were computed. Prediction was at 3 km spatial resolution and aggregated at national and district -level for sub-national planning. RESULTS: About six in ten women reported ANC4+ visits, meaning that approximately 3 million women in the three countries had <ANC4+ visits. The majority of the 366 districts in the three countries had ANC4+ coverage of 50–70%. In Kenya, 13% of districts had < 70% coverage, compared to 10% and 27% of the districts in Uganda and mainland Tanzania, respectively. Only one district in Kenya and ten districts in mainland Tanzania were likely met the target coverage. Six percent, 38%, and 50% of the districts had at most 5000 women with <ANC4+ visits in Kenya, Uganda, and mainland Tanzania, respectively, while districts with > 20,000 women having <ANC4+ visits were 38%, 1% and 1%, respectively. In many districts, ANC4+ coverage and likelihood of attaining the target coverage was lower among the poor, uneducated and those geographically marginalized from healthcare. CONCLUSIONS: These findings will be invaluable to policymakers for annual appropriations of resources as part of efforts to reduce maternal deaths and stillbirths. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12884-022-05238-1.
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spelling pubmed-97243452022-12-07 Spatial variation and inequities in antenatal care coverage in Kenya, Uganda and mainland Tanzania using model-based geostatistics: a socioeconomic and geographical accessibility lens Macharia, Peter M. Joseph, Noel K. Nalwadda, Gorrette Kayondo Mwilike, Beatrice Banke-Thomas, Aduragbemi Benova, Lenka Johnson, Olatunji BMC Pregnancy Childbirth Research BACKGROUND: Pregnant women in sub-Saharan Africa (SSA) experience the highest levels of maternal mortality and stillbirths due to predominantly avoidable causes. Antenatal care (ANC) can prevent, detect, alleviate, or manage these causes. While eight ANC contacts are now recommended, coverage of the previous minimum of four visits (ANC4+) remains low and inequitable in SSA. METHODS: We modelled ANC4+ coverage and likelihood of attaining district-level target coverage of 70% across three equity stratifiers (household wealth, maternal education, and travel time to the nearest health facility) based on data from malaria indicator surveys in Kenya (2020), Uganda (2018/19) and Tanzania (2017). Geostatistical models were fitted to predict ANC4+ coverage and compute exceedance probability for target coverage. The number of pregnant women without ANC4+ were computed. Prediction was at 3 km spatial resolution and aggregated at national and district -level for sub-national planning. RESULTS: About six in ten women reported ANC4+ visits, meaning that approximately 3 million women in the three countries had <ANC4+ visits. The majority of the 366 districts in the three countries had ANC4+ coverage of 50–70%. In Kenya, 13% of districts had < 70% coverage, compared to 10% and 27% of the districts in Uganda and mainland Tanzania, respectively. Only one district in Kenya and ten districts in mainland Tanzania were likely met the target coverage. Six percent, 38%, and 50% of the districts had at most 5000 women with <ANC4+ visits in Kenya, Uganda, and mainland Tanzania, respectively, while districts with > 20,000 women having <ANC4+ visits were 38%, 1% and 1%, respectively. In many districts, ANC4+ coverage and likelihood of attaining the target coverage was lower among the poor, uneducated and those geographically marginalized from healthcare. CONCLUSIONS: These findings will be invaluable to policymakers for annual appropriations of resources as part of efforts to reduce maternal deaths and stillbirths. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12884-022-05238-1. BioMed Central 2022-12-06 /pmc/articles/PMC9724345/ /pubmed/36474193 http://dx.doi.org/10.1186/s12884-022-05238-1 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Macharia, Peter M.
Joseph, Noel K.
Nalwadda, Gorrette Kayondo
Mwilike, Beatrice
Banke-Thomas, Aduragbemi
Benova, Lenka
Johnson, Olatunji
Spatial variation and inequities in antenatal care coverage in Kenya, Uganda and mainland Tanzania using model-based geostatistics: a socioeconomic and geographical accessibility lens
title Spatial variation and inequities in antenatal care coverage in Kenya, Uganda and mainland Tanzania using model-based geostatistics: a socioeconomic and geographical accessibility lens
title_full Spatial variation and inequities in antenatal care coverage in Kenya, Uganda and mainland Tanzania using model-based geostatistics: a socioeconomic and geographical accessibility lens
title_fullStr Spatial variation and inequities in antenatal care coverage in Kenya, Uganda and mainland Tanzania using model-based geostatistics: a socioeconomic and geographical accessibility lens
title_full_unstemmed Spatial variation and inequities in antenatal care coverage in Kenya, Uganda and mainland Tanzania using model-based geostatistics: a socioeconomic and geographical accessibility lens
title_short Spatial variation and inequities in antenatal care coverage in Kenya, Uganda and mainland Tanzania using model-based geostatistics: a socioeconomic and geographical accessibility lens
title_sort spatial variation and inequities in antenatal care coverage in kenya, uganda and mainland tanzania using model-based geostatistics: a socioeconomic and geographical accessibility lens
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9724345/
https://www.ncbi.nlm.nih.gov/pubmed/36474193
http://dx.doi.org/10.1186/s12884-022-05238-1
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