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Published in: BMC Public Health 1/2018

Open Access 01-12-2018 | Research article

Temporal trends in spatial inequalities of maternal and newborn health services among four east African countries, 1999–2015

Authors: Corrine W. Ruktanonchai, Kristine Nilsen, Victor A. Alegana, Claudio Bosco, Rogers Ayiko, Andrew C. Seven Kajeguka, Zöe Matthews, Andrew J. Tatem

Published in: BMC Public Health | Issue 1/2018

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Abstract

Background

Sub-Saharan Africa continues to account for the highest regional maternal mortality ratio (MMR) in the world, at just under 550 maternal deaths per 100,000 live births in 2015, compared to a global rate of 216 deaths. Spatial inequalities in access to life-saving maternal and newborn health (MNH) services persist within sub-Saharan Africa, however, with varied improvement over the past two decades. While previous research within the East African Community (EAC) region has examined utilisation of MNH care as an emergent property of geographic accessibility, no research has examined how these spatial inequalities have evolved over time at similar spatial scales.

Methods

Here, we analysed temporal trends of spatial inequalities in utilisation of antenatal care (ANC), skilled birth attendance (SBA), and postnatal care (PNC) among four East African countries. Specifically, we used Bayesian spatial statistics to generate district-level estimates of these services for several time points using Demographic and Health Surveys data in Kenya, Tanzania, Rwanda, and Uganda. We examined temporal trends of both absolute and relative indices over time, including the absolute difference between estimates, as well as change in performance ratios of the best-to-worst performing districts per country.

Results

Across all countries, we found the greatest spatial equality in ANC, while SBA and PNC tended to have greater spatial variability. In particular, Rwanda represented the only country to consistently increase coverage and reduce spatial inequalities across all services. Conversely, Tanzania had noticeable reductions in ANC coverage throughout most of the country, with some areas experiencing as much as a 55% reduction. Encouragingly, however, we found that performance gaps between districts have generally decreased or remained stably low across all countries, suggesting countries are making improvements to reduce spatial inequalities in these services.

Conclusions

We found that while the region is generally making progress in reducing spatial gaps across districts, improvement in PNC coverage has stagnated, and should be monitored closely over the coming decades. This study is the first to report temporal trends in district-level estimates in MNH services across the EAC region, and these findings establish an important baseline of evidence for the Sustainable Development Goal era.
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Literature
1.
go back to reference Boerma J, Bryce J, Kinfu Y, Axelson H, Victora C. Mind the gap: equity and trends in coverage of maternal, newborn, and child health services in 54 countdown countries. Lancet Lond Engl. 2008;371:1259–67.CrossRef Boerma J, Bryce J, Kinfu Y, Axelson H, Victora C. Mind the gap: equity and trends in coverage of maternal, newborn, and child health services in 54 countdown countries. Lancet Lond Engl. 2008;371:1259–67.CrossRef
2.
go back to reference Nguhiu PK, Barasa EW, Chuma J. Determining the effective coverage of maternal and child health services in Kenya, using demographic and health survey data sets: tracking progress towards universal health coverage. Tropical Med Int Health. 2017;22:442–53.CrossRef Nguhiu PK, Barasa EW, Chuma J. Determining the effective coverage of maternal and child health services in Kenya, using demographic and health survey data sets: tracking progress towards universal health coverage. Tropical Med Int Health. 2017;22:442–53.CrossRef
5.
go back to reference Barros AJD, Victora CG. Measuring coverage in MNCH: determining and interpreting inequalities in coverage of maternal, newborn, and child health interventions. PLoS Med. 2013;10:e1001390.CrossRefPubMed Barros AJD, Victora CG. Measuring coverage in MNCH: determining and interpreting inequalities in coverage of maternal, newborn, and child health interventions. PLoS Med. 2013;10:e1001390.CrossRefPubMed
8.
go back to reference Kerber KJ, de Graft-Johnson JE, Bhutta ZA, Okong P, Starrs A, Lawn JE. Continuum of care for maternal, newborn, and child health: from slogan to service delivery. Lancet. 2007;370:1358–69.CrossRef Kerber KJ, de Graft-Johnson JE, Bhutta ZA, Okong P, Starrs A, Lawn JE. Continuum of care for maternal, newborn, and child health: from slogan to service delivery. Lancet. 2007;370:1358–69.CrossRef
9.
go back to reference Golding N, Burstein R, Longbottom J, Browne AJ, Fullman N, Osgood-Zimmerman A, et al. Mapping under-5 and neonatal mortality in Africa, 2000–15: a baseline analysis for the sustainable development goals. Lancet. 2017;390:2171–82.CrossRefPubMed Golding N, Burstein R, Longbottom J, Browne AJ, Fullman N, Osgood-Zimmerman A, et al. Mapping under-5 and neonatal mortality in Africa, 2000–15: a baseline analysis for the sustainable development goals. Lancet. 2017;390:2171–82.CrossRefPubMed
10.
go back to reference Graetz N, Friedman J, Osgood-Zimmerman A, Burstein R, Biehl MH, Shields C, et al. Mapping local variation in educational attainment across Africa. Nature. 2018;555:48–53.CrossRef Graetz N, Friedman J, Osgood-Zimmerman A, Burstein R, Biehl MH, Shields C, et al. Mapping local variation in educational attainment across Africa. Nature. 2018;555:48–53.CrossRef
11.
go back to reference Osgood-Zimmerman A, Millear AI, Stubbs RW, Shields C, Pickering BV, Earl L, et al. Mapping child growth failure in Africa between 2000 and 2015. Nature. 2018;555:41–7.CrossRef Osgood-Zimmerman A, Millear AI, Stubbs RW, Shields C, Pickering BV, Earl L, et al. Mapping child growth failure in Africa between 2000 and 2015. Nature. 2018;555:41–7.CrossRef
12.
go back to reference Victora CG, Requejo JH, Barros AJD, Berman P, Bhutta Z, Boerma T, et al. Countdown to 2015: a decade of tracking progress for maternal, newborn, and child survival. Lancet. 2016;387:2049–59.CrossRef Victora CG, Requejo JH, Barros AJD, Berman P, Bhutta Z, Boerma T, et al. Countdown to 2015: a decade of tracking progress for maternal, newborn, and child survival. Lancet. 2016;387:2049–59.CrossRef
13.
go back to reference Alkema L, Chou D, Hogan D, Zhang S, Moller A-B, Gemmill A, et al. Global, regional, and national levels and trends in maternal mortality between 1990 and 2015, with scenario-based projections to 2030: a systematic analysis by the UN maternal mortality estimation inter-agency group. Lancet. 2016;387:462–74.CrossRef Alkema L, Chou D, Hogan D, Zhang S, Moller A-B, Gemmill A, et al. Global, regional, and national levels and trends in maternal mortality between 1990 and 2015, with scenario-based projections to 2030: a systematic analysis by the UN maternal mortality estimation inter-agency group. Lancet. 2016;387:462–74.CrossRef
14.
go back to reference Black RE, Cousens S, Johnson HL, Lawn JE, Rudan I, Bassani DG, et al. Global, regional, and national causes of child mortality in 2008: a systematic analysis. Lancet. 2010;375:1969–87.CrossRef Black RE, Cousens S, Johnson HL, Lawn JE, Rudan I, Bassani DG, et al. Global, regional, and national causes of child mortality in 2008: a systematic analysis. Lancet. 2010;375:1969–87.CrossRef
15.
go back to reference Ruktanonchai CW, Ruktanonchai NW, Nove A, Lopes S, Pezzulo C, Bosco C, et al. Equality in maternal and newborn health: modelling geographic disparities in utilisation of Care in Five East African Countries. PLoS One. 2016;11:e0162006.CrossRefPubMed Ruktanonchai CW, Ruktanonchai NW, Nove A, Lopes S, Pezzulo C, Bosco C, et al. Equality in maternal and newborn health: modelling geographic disparities in utilisation of Care in Five East African Countries. PLoS One. 2016;11:e0162006.CrossRefPubMed
18.
go back to reference SAS Institute Inc. SAS version 9.4. Cary, NC, USA: SAS Institute Inc.; 2013. SAS Institute Inc. SAS version 9.4. Cary, NC, USA: SAS Institute Inc.; 2013.
20.
go back to reference Kenya National Bureau of Statistics - KNBS, National AIDS Control Council/Kenya, National AIDS/STD Control Programme/Kenya, Ministry of Public Health and Sanitation/Kenya, Kenya Medical Research Institute. Kenya Demographic and Health Survey 2008–09. Calverton, Maryland, USA: KNBS and ICF Macro; 2010. http://dhsprogram.com/pubs/pdf/FR229/FR229.pdf. Accessed 29 Mar 2018. Kenya National Bureau of Statistics - KNBS, National AIDS Control Council/Kenya, National AIDS/STD Control Programme/Kenya, Ministry of Public Health and Sanitation/Kenya, Kenya Medical Research Institute. Kenya Demographic and Health Survey 2008–09. Calverton, Maryland, USA: KNBS and ICF Macro; 2010. http://​dhsprogram.​com/​pubs/​pdf/​FR229/​FR229.​pdf. Accessed 29 Mar 2018.
21.
go back to reference Kenya National Bureau of Statistics, Ministry of Health/Kenya, National AIDS Control Council/Kenya, Kenya Medical Research Institute, National Council for Population and Development/Kenya. Kenya Demographic and Health Survey 2014. Rockville, MD, USA; 2015. http://dhsprogram.com/pubs/pdf/FR308/FR308.pdf. Accessed 29 Mar 2018. Kenya National Bureau of Statistics, Ministry of Health/Kenya, National AIDS Control Council/Kenya, Kenya Medical Research Institute, National Council for Population and Development/Kenya. Kenya Demographic and Health Survey 2014. Rockville, MD, USA; 2015. http://​dhsprogram.​com/​pubs/​pdf/​FR308/​FR308.​pdf. Accessed 29 Mar 2018.
24.
go back to reference National Institute of Statistics of Rwanda, Ministry of Finance and Economic Planning/Rwanda, Ministry of Health/Rwanda, ICF International. Rwanda Demographic and Health Survey 2014–15. Kigali, Rwanda: National Institute of Statistics of Rwanda, Ministry of Finance and Economic Planning/Rwanda, Ministry of Health/Rwanda, and ICF International; 2016. http://dhsprogram.com/pubs/pdf/FR316/FR316.pdf. Accessed 29 Mar 2018. National Institute of Statistics of Rwanda, Ministry of Finance and Economic Planning/Rwanda, Ministry of Health/Rwanda, ICF International. Rwanda Demographic and Health Survey 2014–15. Kigali, Rwanda: National Institute of Statistics of Rwanda, Ministry of Finance and Economic Planning/Rwanda, Ministry of Health/Rwanda, and ICF International; 2016. http://​dhsprogram.​com/​pubs/​pdf/​FR316/​FR316.​pdf. Accessed 29 Mar 2018.
27.
go back to reference Ministry of Health CD, Ministry of Health - MoH/Zanzibar, National Bureau of Statistics - NBS/Tanzania, Office of Chief Government Statistician - OCGS/Zanzibar, ICF. Tanzania Demographic and Health Survey and Malaria Indicator Survey 2015-2016. Dar es Salaam, Tanzania: MoHCDGEC, MoH, NBS, OCGS, and ICF; 2016. http://dhsprogram.com/pubs/pdf/FR321/FR321.pdf. Accessed 29 Mar 2018. Ministry of Health CD, Ministry of Health - MoH/Zanzibar, National Bureau of Statistics - NBS/Tanzania, Office of Chief Government Statistician - OCGS/Zanzibar, ICF. Tanzania Demographic and Health Survey and Malaria Indicator Survey 2015-2016. Dar es Salaam, Tanzania: MoHCDGEC, MoH, NBS, OCGS, and ICF; 2016. http://​dhsprogram.​com/​pubs/​pdf/​FR321/​FR321.​pdf. Accessed 29 Mar 2018.
31.
go back to reference Environmental Syst Res Institute. ArcGIS Desktop: Release 10.2.2. Redlands; 2014. Environmental Syst Res Institute. ArcGIS Desktop: Release 10.2.2. Redlands; 2014.
33.
go back to reference Rue H, Martino S, Chopin N. Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations. J R Stat Soc Ser B Stat Methodol. 2009;71:319–92.CrossRef Rue H, Martino S, Chopin N. Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations. J R Stat Soc Ser B Stat Methodol. 2009;71:319–92.CrossRef
34.
35.
go back to reference Niragire F, Achia TNO, Lyambabaje A, Ntaganira J. Bayesian mapping of HIV infection among women of reproductive age in Rwanda. PLoS One. 2015;10:e0119944.CrossRefPubMed Niragire F, Achia TNO, Lyambabaje A, Ntaganira J. Bayesian mapping of HIV infection among women of reproductive age in Rwanda. PLoS One. 2015;10:e0119944.CrossRefPubMed
37.
go back to reference Neal SE, Chandra-Mouli V, Chou D. Adolescent first births in East Africa: disaggregating characteristics, trends and determinants. Reprod Health. 2015;12:13.CrossRefPubMed Neal SE, Chandra-Mouli V, Chou D. Adolescent first births in East Africa: disaggregating characteristics, trends and determinants. Reprod Health. 2015;12:13.CrossRefPubMed
38.
go back to reference Gabrysch S, Campbell OM. Still too far to walk: literature review of the determinants of delivery service use. BMC Pregnancy Childbirth. 2009;9:34.CrossRefPubMed Gabrysch S, Campbell OM. Still too far to walk: literature review of the determinants of delivery service use. BMC Pregnancy Childbirth. 2009;9:34.CrossRefPubMed
39.
go back to reference Spiegelhalter DJ, Best NG, Carlin BP, Van Der Linde A. Bayesian measures of model complexity and fit. J R Stat Soc Ser B Stat Methodol. 2002;64:583–639.CrossRef Spiegelhalter DJ, Best NG, Carlin BP, Van Der Linde A. Bayesian measures of model complexity and fit. J R Stat Soc Ser B Stat Methodol. 2002;64:583–639.CrossRef
41.
go back to reference Bosco C, Alegana V, Bird T, Pezzulo C, Bengtsson L, Sorichetta A, et al. Exploring the high-resolution mapping of gender-disaggregated development indicators. J R Soc Interface. 2017;14:20160825.CrossRefPubMed Bosco C, Alegana V, Bird T, Pezzulo C, Bengtsson L, Sorichetta A, et al. Exploring the high-resolution mapping of gender-disaggregated development indicators. J R Soc Interface. 2017;14:20160825.CrossRefPubMed
42.
go back to reference Bailey P, Paxton A, Lobis S, Fry D. The availability of life-saving obstetric services in developing countries: an in-depth look at the signal functions for emergency obstetric care. Int J Gynecol Obstet. 2006;93:285–91.CrossRef Bailey P, Paxton A, Lobis S, Fry D. The availability of life-saving obstetric services in developing countries: an in-depth look at the signal functions for emergency obstetric care. Int J Gynecol Obstet. 2006;93:285–91.CrossRef
43.
go back to reference Say L, Raine R. A systematic review of inequalities in the use of maternal health care in developing countries: examining the scale of the problem and the importance of context. Bull World Health Organ. 2007;85:812–9.CrossRefPubMed Say L, Raine R. A systematic review of inequalities in the use of maternal health care in developing countries: examining the scale of the problem and the importance of context. Bull World Health Organ. 2007;85:812–9.CrossRefPubMed
44.
go back to reference Logie DE, Rowson M, Ndagije F. Innovations in Rwanda’s health system: looking to the future. Lancet. 2008;372:256–61.CrossRef Logie DE, Rowson M, Ndagije F. Innovations in Rwanda’s health system: looking to the future. Lancet. 2008;372:256–61.CrossRef
45.
go back to reference Ayiko R, Antai D, Kulane A. Trends and determinants of under-five mortality in Uganda. East Afr J Public Health. 2009;6:136–40. Ayiko R, Antai D, Kulane A. Trends and determinants of under-five mortality in Uganda. East Afr J Public Health. 2009;6:136–40.
46.
go back to reference Parkhurst JO, Penn-Kekana L, Blaauw D, Balabanova D, Danishevski K, Rahman SA, et al. Health systems factors influencing maternal health services: a four-country comparison. Health Policy. 2005;73:127–38.CrossRef Parkhurst JO, Penn-Kekana L, Blaauw D, Balabanova D, Danishevski K, Rahman SA, et al. Health systems factors influencing maternal health services: a four-country comparison. Health Policy. 2005;73:127–38.CrossRef
47.
go back to reference Roberts DA, Ng M, Ikilezi G, Gasasira A, Dwyer-Lindgren L, Fullman N, et al. Benchmarking health system performance across regions in Uganda: a systematic analysis of levels and trends in key maternal and child health interventions, 1990–2011. BMC Med. 2015;13:285.CrossRefPubMed Roberts DA, Ng M, Ikilezi G, Gasasira A, Dwyer-Lindgren L, Fullman N, et al. Benchmarking health system performance across regions in Uganda: a systematic analysis of levels and trends in key maternal and child health interventions, 1990–2011. BMC Med. 2015;13:285.CrossRefPubMed
48.
go back to reference Hanson C, Gabrysch S, Mbaruku G, Cox J, Mkumbo E, Manzi F, et al. Access to maternal health services: geographical inequalities, United Republic of Tanzania. Bull World Health Organ. 2017;95:810–20.CrossRefPubMed Hanson C, Gabrysch S, Mbaruku G, Cox J, Mkumbo E, Manzi F, et al. Access to maternal health services: geographical inequalities, United Republic of Tanzania. Bull World Health Organ. 2017;95:810–20.CrossRefPubMed
49.
go back to reference Armstrong CE, Martínez-Álvarez M, Singh NS, John T, Afnan-Holmes H, Grundy C, et al. Subnational variation for care at birth in Tanzania: is this explained by place, people, money or drugs? BMC Public Health. 2016;16(Suppl 2):795.CrossRefPubMed Armstrong CE, Martínez-Álvarez M, Singh NS, John T, Afnan-Holmes H, Grundy C, et al. Subnational variation for care at birth in Tanzania: is this explained by place, people, money or drugs? BMC Public Health. 2016;16(Suppl 2):795.CrossRefPubMed
50.
go back to reference Makanga PT, Schuurman N, von Dadelszen P, Firoz T. A scoping review of geographic information systems in maternal health. Int J Gynecol Obstet. 2016;134:13–7.CrossRef Makanga PT, Schuurman N, von Dadelszen P, Firoz T. A scoping review of geographic information systems in maternal health. Int J Gynecol Obstet. 2016;134:13–7.CrossRef
Metadata
Title
Temporal trends in spatial inequalities of maternal and newborn health services among four east African countries, 1999–2015
Authors
Corrine W. Ruktanonchai
Kristine Nilsen
Victor A. Alegana
Claudio Bosco
Rogers Ayiko
Andrew C. Seven Kajeguka
Zöe Matthews
Andrew J. Tatem
Publication date
01-12-2018
Publisher
BioMed Central
Published in
BMC Public Health / Issue 1/2018
Electronic ISSN: 1471-2458
DOI
https://doi.org/10.1186/s12889-018-6241-8

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