Schools Influence Adolescent E-Cigarette use, but when? Examining the Interdependent Association between School Context and Teen Vaping over time

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Abstract
Schools are important contexts for adolescent health and health-risk behaviors, but how stable is this relationship? We develop a conceptual model based on Ecological Systems Theory describing the changing role of schools for adolescent health outcomes—in this case, teen e-cigarette use. To examine this change, we fit Bayesian multilevel regression models to two-year intervals of pooled cross-sectional data from the 2011–2017 U.S. National Youth Tobacco Survey, a school-based study of the nicotine use behaviors of roughly 65,000 middle and high school students (49.5% female; 41.1% nonwhite; x̄ age of 14.6 ranging from 9 to 18) from over 700 schools. We hypothesized that school-level associations with student e-cigarette use diminished over time as the broader popularity of e-cigarettes increased. Year-specific variance partitioning coefficients (VPC) derived from the multilevel models indicated a general decrease in the extent to which e-cigarette use clusters within specific schools, suggesting that students across schools became more uniform in their propensity to vape over the study period. This is above and beyond adjustments for personal characteristics and vicarious exposure to smoking via friends and family. Across all years, model coefficients indicate a positive association between attending schools where vaping is more versus less common and student-level odds of using e-cigarettes, suggesting that school contexts are still consequential to student vaping, but less so than when e-cigarettes were first introduced to the US market. These findings highlight how the health implications of multiply-embedded ecological systems like schools shift over time with concomitant changes in other ecological features including those related to policy, culture, and broader health practices within society. Though not uniformly reported in multilevel studies, variance partitioning coefficients could be used more thoughtfully to empirically illustrate how the influence of multiple developmentally-relevant contexts shift in their influence on teen health over time.

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