Small area estimation of under-5 mortality in Bangladesh,Cameroon, Chad,Mozambique, Uganda,and Zambia using spatially misaligned data |
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| Authors: | Laura Dwyer-Lindgren Ellen R. Squires Stephanie Teeple Gloria Ikilezi D. Allen Roberts Danny V. Colombara Sarah Katherine Allen Stanley M. Kamande Nicholas Graetz Abraham D. Flaxman Charbel El Bcheraoui Kristjana Asbjornsdottir Gilbert Asiimwe Ângelo Augusto Orvalho Augusto Baltazar Chilundo Caroline De Schacht Sarah Gimbel Carol Kamya Faith Namugaya Felix Masiye Cremildo Mauieia Yodé Miangotar Honoré Mimche Acácio Sabonete Haribondhu Sarma Kenneth Sherr Moses Simuyemba Aaron Chisha Sinyangwe Jasim Uddin Bradley H. Wagenaar Stephen S. Lim |
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| Affiliation: | 1.Institute for Health Metrics and Evaluation,University of Washington,Seattle,USA;2.Health Alliance International,Seattle,USA;3.Infectious Disease Research Collaboration,Kampala,Uganda;4.Instituto Nacional da Saúde,Maputo,Mozambique;5.Department of Community Medicine,Eduardo Mondlane University,Maputo,Mozambique;6.Health Alliance International,Maputo,Mozambique;7.Department of Family & Child Nursing,University of Washington,Seattle,USA;8.University of Zambia,Lusaka,Zambia;9.University of N’Djamena,N’Djamena,Chad;10.Institut de Formation et de Recherche Démographiques,University of Yaoundé II,Yaoundé,Cameroon;11.International Centre for Diarrhoeal Disease Research,Dhaka,Bangladesh;12.Department of Global Health,University of Washington,Seattle,USA |
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| Abstract: | BackgroundThe under-5 mortality rate (U5MR) is an important metric of child health and survival. Country-level estimates of U5MR are readily available, but efforts to estimate U5MR subnationally have been limited, in part, due to spatial misalignment of available data sources (e.g., use of different administrative levels, or as a result of historical boundary changes).MethodsWe analyzed all available complete and summary birth history data in surveys and censuses in six countries (Bangladesh, Cameroon, Chad, Mozambique, Uganda, and Zambia) at the finest geographic level available in each data source. We then developed small area estimation models capable of incorporating spatially misaligned data. These small area estimation models were applied to the birth history data in order to estimate trends in U5MR from 1980 to 2015 at the second administrative level in Cameroon, Chad, Mozambique, Uganda, and Zambia and at the third administrative level in Bangladesh.ResultsWe found substantial variation in U5MR in all six countries: there was more than a two-fold difference in U5MR between the area with the highest rate and the area with the lowest rate in every country. All areas in all countries experienced declines in U5MR between 1980 and 2015, but the degree varied both within and between countries. In Cameroon, Chad, Mozambique, and Zambia we found areas with U5MRs in 2015 that were higher than in other parts of the same country in 1980. Comparing subnational U5MR to country-level targets for the Millennium Development Goals (MDG), we find that 12.8% of areas in Bangladesh did not meet the country-level target, although the country as whole did. A minority of areas in Chad, Mozambique, Uganda, and Zambia met the country-level MDG targets while these countries as a whole did not.ConclusionsSubnational estimates of U5MR reveal significant within-country variation. These estimates could be used for identifying high-need areas and positive deviants, tracking trends in geographic inequalities, and evaluating progress towards international development targets such as the Sustainable Development Goals. |
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