Bio-Behavioral and Environmental Factors in Teen Smoking

描述(由申请人提供)： 这项建议的目的是调查青少年烟草使用中生物行为和环境因素之间的相互关系。国家青少年健康纵向研究(ADD Health)的多层次分析将评估对青少年吸烟的多重影响。多层次办法的基本原理是，没有从一个层次确定完全解释青少年烟草使用的单一因素。相反，近端和远端环境的风险和保护因素之间的复杂相互作用需要采取多方面的方法。 这项拟议的研究将考察州和学校的烟草控制政策对青少年吸烟行为的影响，受父母吸烟和父母教养方式的影响，同时控制个人的人口统计特征。实现这一目标的方法是使用具有全国代表性的数据集来指定和估计一个结合了生物行为和环境影响的模型。无论是生物行为影响模型还是环境影响模型本身都不能充分解释青少年为什么吸烟以及他们为什么继续吸烟。拟议的研究将使用一种新的方法，因为它将这两种方法结合到对青少年吸烟行为的多水平分析中，通过准确地考虑与模型的每个水平相关联的非独立影响，使得对不同政策和因素的联合影响的估计更加准确。来自Add Health、Waves I和Waves III(为期5年的纵向调查)的具有全国代表性的数据将被用来估计一个具有固定效应和来自州和学校的两级随机效应的混合效应模型。 研究结果将使烟草控制政策制定者了解如何引导支出，以便在短期内防止开始吸烟，在长期内促进普遍戒烟方面发挥最大效力。

DESCRIPTION (provided by applicant): The purpose of this proposal is to investigate the inter-relationships between bio-behavioral and environmental factors in adolescent tobacco use. A multilevel analysis of The National Longitudinal Study of Adolescent Health (Add Health) will assess multiple influences on adolescent smoking. The rationale underlying the multilevel approach is that no single factor from one level has been identified that completely accounts for adolescent tobacco use. Instead, a complex interaction between risk and protective factors from proximal and distal environments requires the adoption of a multi-faceted approach. The proposed study will examine the effect of state and school tobacco control policies on adolescent smoking behavior as moderated by parental smoking and parenting styles while controlling for individual demographic characteristics. The approach to achieve this goal is to specify and estimate a model combining bio-behavioral and environmental influences using a nationally-representative data set. Neither the bio-behavioral influences models nor the environmental influences models alone adequately explain why adolescents take up smoking and why they continue to smoke. The proposed study will use a novel approach in that it incorporates these two approaches in a multilevel analysis of smoking behavior in youth, which permits more precision in the estimates of the effects of the conjunction of various policies and factors by accurately accounting for nonindependence effects associated with each level of the model. Nationally representative data from Add Health, Waves I and III (a 5-year longitudinal survey) will be used to estimate a mixed-effects model with fixed effects and two-levels of random effects from state and school. The findings will inform tobacco control policy makers as to how to direct spending so as to maximize efficacy in terms of the prevention of smoking initiation in the short term and the promotion of cessation in general in the long term.