Mapping for maternal and newborn health: the distributions of women of childbearing age, pregnancies and births

Abstract

Background: The health and survival of women and their new-born babies in low income countries has been a key priority in public health since the 1990s. However, basic planning data, such as numbers of pregnancies and births, remain difficult to obtain and information is also lacking on geographic access to key services, such as facilities with skilled health workers. For maternal and newborn health and survival, planning for safer births and healthier newborns could be improved by more accurate estimations of the distributions of women of childbearing age. Moreover, subnational estimates of projected future numbers of pregnancies are needed for more effective strategies on human resources and infrastructure, while there is a need to link information on pregnancies to better information on health facilities in districts and regions so that coverage of services can be assessed.

Methods: This paper outlines demographic mapping methods based on freely available data for the production of high resolution datasets depicting estimates of numbers of people, women of childbearing age, live births and pregnancies, and distribution of comprehensive EmONC facilities in four large high burden countries: Afghanistan, Bangladesh, Ethiopia and Tanzania. Satellite derived maps of settlements and land cover were constructed and used to redistribute areal census counts to produce detailed maps of the distributions of women of childbearing age. Household survey data, UN statistics and other sources on growth rates, age specific fertility rates, live births, stillbirths and abortions were then integrated to convert the population distribution datasets to gridded estimates of births and pregnancies.

Results and conclusions: These estimates, which can be produced for current, past or future years based on standard demographic projections, can provide the basis for strategic intelligence, planning services, and provide denominators for subnational indicators to track progress. The datasets produced are part of national midwifery workforce assessments conducted in collaboration with the respective Ministries of Health and the United Nations Population Fund (UNFPA) to identify disparities between population needs, health infrastructure and workforce supply. The datasets are available to the respective Ministries as part of the UNFPA programme to inform midwifery workforce planning and also publicly available through the WorldPop population mapping project.

Figure 1

Mapping settlements and population distribution. (a) Landsat Enhanced Thematic Mapper (ETM) image showing a city and surrounding smaller settlements; (b) Settlements extracted using automated mapping approach; (c) Census data for Tanzania in 2002 at village level showing total number of people per unit; (d) Population distribution map for 2012 produced through using the satellite derived settlement and land cover information to reallocate census unit populations to a 100×100 m resolution grid, followed by application of UN urban/rural growth rates.

Figure 2

Mapping women of childbearing age. (a) Proportion of the population that are women of childbearing age (15-49 yrs) from village-level census data; (b) Population distribution map showing estimated number of women of childbearing age per 100×100 m grid cell.

Figure 3

Age-specific fertility rates and mapped live births. (a) Fertility rates for women aged 20-24 mapped in five categories and constructed from the 2010 Tanzania Demographic and Health Survey; (b) Fertility rates for women aged 30-34 mapped in five categories and constructed from the 2010 Tanzania Demographic and Health Survey; (c) Fertility rates for women aged 40-44 mapped in five categories and constructed from the 2010 Tanzania Demographic and Health Survey; (d) Map showing estimated total number of live births per 100×100 m grid cell in 2012.

Figure 4

Gridded datasets of estimated numbers of pregnancies per 100×100 m grid cell for 2012 for (a) Afghanistan, with close-up of Kabul area shown; (b) Bangladesh, with close-up of Dhaka area shown; (c) Tanzania, with close-up of Dar Es Salaam and Zanzibar area shown; (d) Ethiopia, with close-up of Addis Ababa area shown.

Figure 5

Quantifying the proximity of pregnancies to CEmONC facilities. (a) Dataset illustrating the estimated number of pregnancies per 100×100 m grid cell on a standard deviation colour scale in 2012 for Ethiopia, with the location of comprehensive EmONC facilities overlaid; (b) Estimated percentage of pregnancies within 50km of a comprehensive EmONC facility in Ethiopia in 2012 by woreda administrative unit.