A Bayesian additive spatiotemporal model for young adolescent birth records in the Philippines

Abstract

Quantitative studies about young adolescent pregnancy in the Philippines had been done through the analysis of survey data. Official birth records provide a more advantageous data source in examining the dynamics of the young adolescent pregnancy due to regular recording of births. In this study, we propose a statistical methodology utilizing official birth records through a Bayesian hierarchical framework. The method accounts for the unique features of the aggregated young adolescent birth counts such as being a spatiotemporal data with known upper bounds and being characterized by the presence of excess zero counts. Our framework consists of the binomial hurdle model and Poisson hurdle model with offset, the Leroux model for spatial effects (Leroux et al., 2000), and an additive nonparametric trend model for temporal effects (Knorr-Held, 2000). We analyze and assess the performance of the proposed models using the quarterly data on young adolescent birth counts in Luzon, Philippines from 2006 to 2019 via Hamiltonian Monte Carlo. Areas that are more prone to observe a young adolescent birth and a temporal pattern about the occurrence of young adolescent births are identified.