Uncovering Polysubstance Use Patterns in Canadian Youth with Machine Learning on Longitudinal COMPASS Data

Abstract

AbstractUnderstanding polysubstance use (PSU) patterns and their associated factors among youth is crucial for addressing the complex issue of substance use in this population. This study aims to investigate PSU patterns in a large sample of Canadian youth and explore associated factors using data from COMPASS, a longitudinal health survey of Canadian secondary school students. The study sample consisted of 8824 students from grades 9 and 10 at baseline in 2016/17, followed over 3 years until 2018/19. Leveraging machine learning methods, especially the least absolute shrinkage and selection operator (LASSO) and multivariate latent Markov models, we conducted a comprehensive examination of PSU patterns. Our analyses revealed distinct PSU patterns among Canadian youth, including no-use (C1), alcohol-only (C2), concurrent use of e-cigarettes and alcohol (C3), and poly-use (C4). C1 showed the highest prevalence (60.5%) in 2016/17, declining by 2.4 times over 3 years, while C3 became the dominant pattern (32.5%) in 2018/19. The prevalence of C3 and C4 increased by 2.3 and 4.4 times, respectively, indicating a growing trend of dual and multiple substance use. Risk factors associated with PSU patterns included truancy (ORC2 = 1.67, 95 % CI [1.55, 1.79]; ORC3 = 1.92, 95 % CI [1.80, 2.04]; ORC4 = 2.79, 95 % CI [2.64, 2.94]), having more smoking friends, more weekly allowance, elevated BMI, being older, and attending schools unsupportive in quitting drugs/alcohol. In contrast, not gambling online (ORC2 = 0.22, 95 % CI [−0.16, 0.58]; ORC3 = 0.14, 95 % CI [-0.24, 0.52]; ORC4 = 0.08, 95 % CI [−0.47, 0.63]), eating breakfast, residing in urban areas, and having higher school connectedness were protective factors against a higher-use pattern. This study provides insights for policymakers, educators, and health professionals to design targeted and evidence-based interventions, addressing youth substance use challenges through a comprehensive examination of PSU patterns and influential factors impacting substance use behaviors.