Mapping adolescent first births within three east African countries using data from Demographic and Health Surveys: exploring geospatial methods to inform policy

Abstract

Background: Early adolescent pregnancy presents a major barrier to the health and wellbeing of young women and their children. Previous studies suggest geographic heterogeneity in adolescent births, with clear "hot spots" experiencing very high prevalence of teenage pregnancy. As the reduction of adolescent pregnancy is a priority in many countries, further detailed information of the geographical areas where they most commonly occur is of value to national and district level policy makers. The aim of this study is to develop a comprehensive assessment of the geographical distribution of adolescent first births in Uganda, Kenya and Tanzania using Demographic and Household (DHS) data using descriptive, spatial analysis and spatial modelling methods. Methods: The most recent Demographic and Health Surveys (DHS) among women aged 20 to 29 in Tanzania, Kenya, and Uganda were utilised. Analyses were carried out on first births occurring before the age of 20 years, but were disaggregated in to three age groups: <16, 16/17 and 18/19 years. In addition to basic descriptive choropleths, prevalence maps were created from the GPS-located cluster data utilising adaptive bandwidth kernel density estimates. To map adolescent first birth at district level with estimates of uncertainty, a Bayesian hierarchical regression modelling approach was used, employing the Integrated Nested Laplace Approximation (INLA) technique. Results: The findings show marked geographic heterogeneity among adolescent first births, particularly among those under 16 years. Disparities are greater in Kenya and Uganda than Tanzania. The INLA analysis which produces estimates from smaller areas suggest "pockets" of high prevalence of first births, with marked differences between neighbouring districts. Many of these high prevalence areas can be linked with underlying poverty. Conclusions: There is marked geographic heterogeneity in the prevalence of adolescent first births in East Africa, particularly in the youngest age groups. Geospatial techniques can identify these inequalities and provide policy-makers with the information needed to target areas of high prevalence and focus scarce resources where they are most needed.

Modelling the Wealth Index of Demographic and Health Surveys within Cities Using Very High-Resolution Remotely Sensed Information

“…In most Sub-Saharan African (SSA) cities, census data is hard to access or outdated. For regional or national assessments a lot of survey indicators have been produced at coarser resolutions [6,[43][44][45][46][47][48][49][50][51] but this was the first DHS fine-scale indicator production derived from VHR earth observation information directed specifically for intra-urban policy making and decision support. An additional highlight of this work is that not only were VHR variables able to train robust models based on DHS surveys, but also their predictions were in relative agreement with exhaustive census data at various geographical resolutions.…”

Using geospatial modelling to estimate the prevalence of adolescent first births in Nepal

“…Within our models, the dependent variables of interest were age at first birth at: (1) less than 16 years of age, (2) between 16 and 17 years of age, (3) between 18 and 19 years of age and (4) less than 20 years of age. These groupings have been used previously within the literature and have been shown to have important differences in age patterns 32 34. To predict these outcomes at a spatially disaggregated scale, we employed a Besag model incorporating both spatial effects plus random effects within the INLA package, allowing for representation of the spatial component of outcome variability 35 36.…”

“…Finally, covariates in the model included urban/rural residence, education status and wealth quintile as specified through the DHS. We chose these covariates to reflect covariates based on similar models published elsewhere exploring adolescent motherhood in East Africa, promoting comparability across regions 34…”

“…Marked spatial inequalities in prevalence of adolescent pregnancies are common in both low-income and higher-income countries and are underpinned by geographic patterns of deprivation as well as cultural norms and practices within communities. These factors can lead to hidden pockets of high levels of adolescent fertility within small geographic areas, particularly for pregnancies among very young adolescents which are rarer and tend to reflect specific local sociocultural characteristics 14. Data sampling, however, tends to occur at the national or regional level, necessitating the use of spatial statistics to infer estimates at a higher resolution scale.…”

Using three indicators to understand the parity-specific contribution of adolescent childbearing to all births

“…Adolescent childbearing (also called adolescent-girl pregnancy): the percentage of women aged 20–24 (or 20–29) who had a live birth before age 15 years (early adolescent childbearing),<18 years, or<20 years 12 29 31…”