Predictors of vaping marijuana initiation among US adolescents: Results from the Population Assessment of Tobacco and Health (PATH) study Wave 3 (2015-2016) and Wave 4 (2016-2018)
Predictors of vaping marijuana initiation among US adolescents: Results from the Population Assessment of Tobacco and Health (PATH) study Wave 3 (2015-2016) and Wave 4 (2016-2018)
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DOI：
10.1016/j.drugalcdep.2021.108905
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发表时间：
2021-07-23
影响因子：
4.2
通讯作者：
Salloum, Ramzi G.
中科院分区：
文献类型：
--
作者：
Lee, Juhan;Kong, Grace;Salloum, Ramzi G.
简介：青少年中的Mariovaping是一个日益增长的公共卫生问题。Marijuana vaping使年轻人暴露于更高水平的四氢大麻酚（THC），可能与电子烟或vaping产品使用相关的肺损伤（EVALI）有关。这项研究调查了美国青少年开始吸食大麻的风险因素。方法：我们分析了烟草与健康人口评估（PATH）研究的第3波（2015-2016）和第4波（2016-2018）。我们估计了一个多变量逻辑回归模型，以模拟在第3波从未吸过大麻的人（N = 7，821）在第4波吸大麻，作为与青少年物质使用相关的关键风险因素的函数。结果如下：开始使用电子尼古丁输送系统（ENDS）与目前使用电子尼古丁输送系统有关（aOR = 2.16，95%CI = 1.20，3.89），吸烟（aOR = 2.65，95%CI = 1.10，6.35）、其他大麻制品（aOR = 7.78，95%CI = 3.74，6.15）和酒精（aOR = 1.98，95%CI = 1.35，2.91）。导致大麻vaping开始的其他因素包括15-17岁（aOR = 1.51，95% CI = 1.19，1.90）和西班牙裔（aOR = 1.37，95%CI = 1.08，1.76），以及父母教育程度低于大学水平（aOR = 1.35，95% CI = 1.07，1.70），vaping peers（aOR = 2.31;高内化倾向（aOR = 1.49，95%CI = 1.10，2.02）和外化倾向（aOR = 1.66，95%CI = 1.14，2.41）。结论：需要多层次的努力来针对导致青少年开始吸食大麻的不同风险因素。了解这些风险因素可以帮助政策制定者和卫生项目管理人员识别风险个体，并设计干预措施，以防止在个人、家庭、学校、临床和公共卫生层面开始吸食大麻。
Introduction: Marijuana vaping among adolescents is a growing public health concern. Marijuana vaping exposes youth to greater levels of tetrahydrocannabinol (THC) and may be related to e-cigarette or vaping product use-associated lung injury (EVALI). This study examined the risk factors for initiating marijuana vaping among US adolescents. Methods: We analyzed Waves 3 (2015-2016) and 4 (2016-2018) of the Population Assessment of Tobacco and Health (PATH) Study. We estimate a multivariable logistic regression to model marijuana vaping initiation at Wave 4 among those who never vaped marijuana at Wave 3 (N = 7,821) as a function of key risk factors associated with youth substance use. Results: Marijuana vaping initiation is associated with current use of electronic nicotine delivery system (ENDS) (aOR = 2.16, 95 % CI = 1.20, 3.89), cigarettes (aOR = 2.65, 95 % CI = 1.10, 6.35), other marijuana products (aOR = 7.78, 95 % CI = 3.74, 6.15), and alcohol (aOR = 1.98, 95 % CI = 1.35, 2.91). Other factors contributing to marijuana vaping initiation include being 15-17 years old (aOR = 1.51, 95 % CI = 1.19, 1.90) and Hispanic (aOR = 1.37, 95 % CI = 1.08, 1.76), as well as having less than college-level parental education (aOR = 1.35, 95 % CI = 1.07, 1.70), vaping peers (aOR = 2.31; 95 % CI = 1.81, 2.96), and a high internalizing (aOR = 1.49, 95 % CI = 1.10, 2.02) and externalizing tendency (aOR = 1.66, 95 % CI = 1.14, 2.41). Conclusions: Multi-level efforts are needed to target the varying risk factors leading to marijuana vaping initiation in adolescents. Knowledge of these risk factors can help policymakers and health program administrators to identify at-risk individuals and design interventions that can prevent marijuana vaping initiation at the indi-vidual, household, school, clinical and public health levels.