Spatial variation and inequities in antenatal care coverage in Kenya, Uganda and mainland Tanzania using model-based geostatistics: a socioeconomic and geographical accessibility lens
Abstract 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, coverag...
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Format: | Article |
Language: | English |
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BMC
2022-12-01
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Series: | BMC Pregnancy and Childbirth |
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Online Access: | https://doi.org/10.1186/s12884-022-05238-1 |
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author | Peter M. Macharia Noel K. Joseph Gorrette Kayondo Nalwadda Beatrice Mwilike Aduragbemi Banke-Thomas Lenka Benova Olatunji Johnson |
author_facet | Peter M. Macharia Noel K. Joseph Gorrette Kayondo Nalwadda Beatrice Mwilike Aduragbemi Banke-Thomas Lenka Benova Olatunji Johnson |
author_sort | Peter M. Macharia |
collection | DOAJ |
description | Abstract 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. |
first_indexed | 2024-04-13T07:19:30Z |
format | Article |
id | doaj.art-d9d0b922969c49e7a018f84923f9cf84 |
institution | Directory Open Access Journal |
issn | 1471-2393 |
language | English |
last_indexed | 2024-04-13T07:19:30Z |
publishDate | 2022-12-01 |
publisher | BMC |
record_format | Article |
series | BMC Pregnancy and Childbirth |
spelling | doaj.art-d9d0b922969c49e7a018f84923f9cf842022-12-22T02:56:39ZengBMCBMC Pregnancy and Childbirth1471-23932022-12-0122111610.1186/s12884-022-05238-1Spatial variation and inequities in antenatal care coverage in Kenya, Uganda and mainland Tanzania using model-based geostatistics: a socioeconomic and geographical accessibility lensPeter M. Macharia0Noel K. Joseph1Gorrette Kayondo Nalwadda2Beatrice Mwilike3Aduragbemi Banke-Thomas4Lenka Benova5Olatunji Johnson6Population Health Unit, Kenya Medical Research Institute-Wellcome Trust Research ProgrammePopulation Health Unit, Kenya Medical Research Institute-Wellcome Trust Research ProgrammeCollege of Health Sciences, Makerere UniversityCommunity Health Nursing Department, School of Nursing, Muhimbili University of Health and Allied SciencesSchool of Human Sciences, University of GreenwichDepartment of Public Health, Institute of Tropical MedicineDepartment of Mathematics, The University of ManchesterAbstract 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.https://doi.org/10.1186/s12884-022-05238-1Antenatal careInequitiesHousehold wealthMaternal educationTravel time to healthcareModel-based geostatistics |
spellingShingle | Peter M. Macharia Noel K. Joseph Gorrette Kayondo Nalwadda Beatrice Mwilike Aduragbemi Banke-Thomas Lenka Benova Olatunji Johnson Spatial variation and inequities in antenatal care coverage in Kenya, Uganda and mainland Tanzania using model-based geostatistics: a socioeconomic and geographical accessibility lens BMC Pregnancy and Childbirth Antenatal care Inequities Household wealth Maternal education Travel time to healthcare Model-based geostatistics |
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 | Antenatal care Inequities Household wealth Maternal education Travel time to healthcare Model-based geostatistics |
url | https://doi.org/10.1186/s12884-022-05238-1 |
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