Small area estimation of under-5 mortality in Bangladesh, Cameroon, Chad, Mozambique, Uganda, and Zambia using spatially misaligned data

Abstract

Background: The 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).

Methods: We 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.

Results: We 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.

Conclusions: Subnational 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.

Keywords: Geographic disparities; Inequalities; Small area estimation; Subnational; U5MR.

Fig. 1

Data and estimates for selected areas. a Amtali, Bangladesh (sub-district); b Bamboutos, Cameroon (department); c Batha Est, Chad (department); d Kalangala, Uganda (district)

Fig. 2

Under-5 mortality rate by sub-district in Bangladesh. a Under-5 mortality rate in 2015 and (b) relative change in the under-5 mortality rate between 1980 and 2015

Fig. 3

Under-5 mortality rate by department in Cameroon. a Under-5 mortality rate in 2015 and (b) relative change in the under-5 mortality rate between 1980 and 2015

Fig. 4

Under-5 mortality rate by department in Chad. a Under-5 mortality rate in 2015 and (b) relative change in the under-5 mortality rate between 1980 and 2015

Fig. 5

Under-5 mortality rate by district in Mozambique. a Under-5 mortality rate in 2015 and (b) relative change in the under-5 mortality rate between 1980 and 2015

Fig. 6

Under-5 mortality rate by district in Uganda. a Under-5 mortality rate in 2015 and (b) relative change in the under-5 mortality rate between 1980 and 2015

Fig. 7

Under-5 mortality rate by district in Zambia. a Under-5 mortality rate in 2015 and (b) relative change in the under-5 mortality rate between 1980 and 2015

Fig. 8

Subnational under-5 mortality rates compared to international targets, 1980–2015. Within each boxplot vertical lines indicate the range, boxes indicate the interquartile range, horizontal lines indicate the median, and dot indicates the national rate. The solid black lines indicate the country-level Millennium Development Goal target (i.e., a two-thirds reduction of the 1990 U5MR by 2015) and the black dashed line indicates the Sustainable Development Goal target (25 deaths per 1000 by 2030)