A Bayesian Spatio-Network Model for Multiple Adolescent Adverse Health Behaviours

Abstract

The use of alcohol, cigarettes and marijuana among adolescents are major public health concerns, and a number of epidemiological studies have been conducted to understand the drivers of these individual health behaviours. However, there is no literature that jointly models these health behaviours with the aim of understanding the relative importance of individual factors, friendship effects and spatial effects in determining the prevalence of alcohol, cigarette and marijuana use among adolescents. To address this gap in the literature, we propose a novel multivariate spatio-network model for jointly modelling all three of these behaviours, with inference conducted in a Bayesian setting using Markov chain Monte Carlo simulation. The model is motivated by survey data from five schools in Los Angeles, California, and the results indicate the important roles that individual factors and friendship networks play in driving the uptake of these health behaviours.