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...

Full description

Saved in:
Bibliographic Details
Main Authors: Peter M. Macharia (Author), Noel K. Joseph (Author), Gorrette Kayondo Nalwadda (Author), Beatrice Mwilike (Author), Aduragbemi Banke-Thomas (Author), Lenka Benova (Author), Olatunji Johnson (Author)
Format: Book
Published: BMC, 2022-12-01T00:00:00Z.
Subjects:
Online Access:Connect to this object online.
Tags: Add Tag
No Tags, Be the first to tag this record!

MARC

LEADER 00000 am a22000003u 4500
001 doaj_d9d0b922969c49e7a018f84923f9cf84
042 |a dc 
100 1 0 |a Peter M. Macharia  |e author 
700 1 0 |a Noel K. Joseph  |e author 
700 1 0 |a Gorrette Kayondo Nalwadda  |e author 
700 1 0 |a Beatrice Mwilike  |e author 
700 1 0 |a Aduragbemi Banke-Thomas  |e author 
700 1 0 |a Lenka Benova  |e author 
700 1 0 |a Olatunji Johnson  |e author 
245 0 0 |a Spatial variation and inequities in antenatal care coverage in Kenya, Uganda and mainland Tanzania using model-based geostatistics: a socioeconomic and geographical accessibility lens 
260 |b BMC,   |c 2022-12-01T00:00:00Z. 
500 |a 10.1186/s12884-022-05238-1 
500 |a 1471-2393 
520 |a 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. 
546 |a EN 
690 |a Antenatal care 
690 |a Inequities 
690 |a Household wealth 
690 |a Maternal education 
690 |a Travel time to healthcare 
690 |a Model-based geostatistics 
690 |a Gynecology and obstetrics 
690 |a RG1-991 
655 7 |a article  |2 local 
786 0 |n BMC Pregnancy and Childbirth, Vol 22, Iss 1, Pp 1-16 (2022) 
787 0 |n https://doi.org/10.1186/s12884-022-05238-1 
787 0 |n https://doaj.org/toc/1471-2393 
856 4 1 |u https://doaj.org/article/d9d0b922969c49e7a018f84923f9cf84  |z Connect to this object online.