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Using geospatial modelling to estimate the prevalence of adolescent first births in Nepal
Sarah Neal1, Corrine Warren Ruktanonchai2, Venkatraman Chandra-Mouli3
1Social Statistics and Demography Department, University of Southampton, Southampton, UK.
Introduction:
Adolescent pregnancy is associated with significant risks and disadvantages for young women and girls and their children. A clear understanding of population subgroups with particularly high prevalence of first births in adolescence is vital if appropriate national responses are to be developed. This paper aims to provide detailed data on socioeconomic and geographic inequities in first births to adolescents in Nepal, including wealth quintile, education, rural/urban residence and geographic region. A key element is the use of geospatial modelling to develop estimates for the prevalence of adolescent births at the district level.
Methods:
The study uses data from the 2011 Nepal Demographic and Health Survey. Initial cross-tabulations present disaggregated data by socioeconomic status and basic geographic region. Estimates of prevalence of adolescent first births at the district level are creating by regression modelling using the Integrated Nested Laplace Approximation package in R software.
Results:
Our findings show that 40% of women had given birth before the age of 20 years, with 5% giving birth before 16 years. First births to adolescents remain common among poorer, less educated and rural women. Geographic disparities are striking, with estimates for the percentage of women giving birth before 20 years ranging from 35% to 53% by region. District level estimates showed even more marked differentials (26%-67% had given birth by 20 years), with marked heterogeneity even within regions. In some districts, estimates for the prevalence of first birth among the youngest age groups (<16 years) are high.
Conclusion:
Important geographic and socioeconomic inequities exist in adolescent first births. In some districts and within some subgroups, there remain high levels of adolescent first births, including births to very young adolescents. The use of Bayesian geospatial modelling techniques can be used by policymakers to target resources.
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