Using cross-classified multilevel models to disentangle school and neighborhood effects: An example focusing on smoking behaviors among adolescents in the United States
Using cross-classified multilevel models to disentangle school and neighborhood effects: An example focusing on smoking behaviors among adolescents in the United States
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DOI：
10.1016/j.healthplace.2014.12.001
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发表时间：
2015-01-01
期刊：
影响因子：
4.8
通讯作者：
Subramanian, S. V.
中科院分区：
文献类型：
--
作者：
Dunn, Erin C.;Richmond, Tracy K.;Subramanian, S. V.
背景：尽管人们对了解环境对健康的影响很感兴趣，但大多数研究一次只关注一种环境，忽视了个人同时在多种环境中拥有成员身份的现实。方法：以全国青少年健康纵向研究中的青少年吸烟行为为例，应用交叉分类多层次模型（CCMM）对学校和社区的固定效应和随机效应进行检验。我们将CCMM的结果与分别关注学校和社区的传统多层模型（MEM）的结果进行了比较。结果：在MEMs中，52%的吸烟变化是由于社区之间的差异（当忽略学校时），6.3%的吸烟变化是由于学校之间的差异（当忽略社区时）。然而，在同时考察社区和学校变化的CCMM中，社区水平的变化减少到0.4%。结论：结果表明，使用MEM而不是CCMM可能会导致高估某些背景的重要性，并最终导致针对错误背景的干预措施或政策。(C) 2014 Elsevier Ltd.版权所有。
Background: Despite much interest in understanding the influence of contexts on health, most research has focused on one context at a time, ignoring the reality that individuals have simultaneous memberships in multiple settings.Method: Using the example of smoking behavior among adolescents in the National Longitudinal Study of Adolescent Health, we applied cross classified multilevel modeling (CCMM) to examine fixed and random effects for schools and neighborhoods. We compared the CCMM results with those obtained from a traditional multilevel model (MEM) focused on either the school and neighborhood separately.Results: In the MEMs, 52% of the variation in smoking was due to differences between neighborhoods (when schools were ignored) and 6.3% of the variation in smoking was due to differences between schools (when neighborhoods were ignored). However in the CCMM examining neighborhood and school variation simultaneously, the neighborhood level variation was reduced to 0.4%.Conclusion: Results suggest that using MEM, instead of CCMM, could lead to overestimating the importance of certain contexts and could ultimately lead to targeting interventions or policies to the wrong settings. (C) 2014 Elsevier Ltd. All rights reserved.