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调查学校毒品预防项目与学生毒品使用之间的关联:考虑信息性聚类规模。

Investigating the association between school substance programs and student substance use: accounting for informative cluster size.

作者信息

Mitani Aya A, Zou Yushu, Leatherdale Scott T, Patte Karen A

机构信息

Dalla Lana School of Public Health, University of Toronto, Toronto, Canada.

School of Public Health Sciences, University of Waterloo, Waterloo, Canada.

出版信息

Epidemiol Methods. 2025 Aug 26;14(1):20240028. doi: 10.1515/em-2024-0028. eCollection 2025 Jan.

Abstract

OBJECTIVES

The use of substances in adolescents is an increasing public health problem. Many high schools in Canada have implemented school-based programs to mitigate student substance use, but their utility is not conclusive. Polysubstance use data collected on students from multiple schools may be subject to informative cluster size (ICS). The objective of this study was to investigate whether a multivariate analysis approach that addresses ICS provides different conclusions from univariate analyses and methods that do not account for ICS.

METHODS

We used data from the 2018/2019 cycle of the Cannabis, Obesity, Mental health, Physical activity, Alcohol, Smoking, and Sedentary Behaviour (COMPASS) study, an ongoing prospective cohort study that annually collects data from Canadian high schools and students. We compared results from four analytical approaches that estimate marginal associations between each school substance program and the four substance use behaviours (binge drinking, cannabis, e-cigarette, and cigarette): univariate generalized estimating equations (GEE), univariate cluster-weighted GEE (CWGEE), multivariate GEE, and multivariate CWGEE.

RESULTS

We observed that the proportion of students who engage in each of the four behaviours was higher in small schools and lower in large schools. In general, the univariate and multivariate analyses produced comparable results. Some differences existed between multivariate CWGEE and GEE. CWGEE indicated that the school program on cannabis had an odds ratio (OR) and 95 % confidence interval (CI) of 0.83 (0.73, 0.95) on all substance use, but GEE produced a null association with an OR (95 % CI) of 0.92 (0.79, 1.07).

CONCLUSIONS

When ICS is present in clustered school data, weighted and unweighted analyses may produce different results. Care is needed to investigate the relationship between cluster size and the outcome, and use appropriate methods for analysis. Certain substance programs may influence student behaviour in other substances, highlighting the need for a multivariate analytical approach when studying the use of substances by adolescents.

摘要

目的

青少年使用药物是一个日益严重的公共卫生问题。加拿大许多高中已实施以学校为基础的项目来减少学生药物使用,但这些项目的效用尚无定论。从多所学校收集的学生多物质使用数据可能受到信息性聚类规模(ICS)的影响。本研究的目的是调查一种解决ICS问题的多变量分析方法是否会得出与单变量分析以及未考虑ICS的方法不同的结论。

方法

我们使用了大麻、肥胖、心理健康、身体活动、酒精、吸烟和久坐行为(COMPASS)研究2018/2019周期的数据,这是一项正在进行的前瞻性队列研究,每年从加拿大高中和学生中收集数据。我们比较了四种分析方法的结果,这些方法估计每个学校药物项目与四种药物使用行为(暴饮、大麻、电子烟和香烟)之间的边际关联:单变量广义估计方程(GEE)、单变量聚类加权GEE(CWGEE)、多变量GEE和多变量CWGEE。

结果

我们观察到,在小学校中,从事这四种行为中每一种行为的学生比例较高,而在大学校中较低。总体而言,单变量和多变量分析产生了可比的结果。多变量CWGEE和GEE之间存在一些差异。CWGEE表明,大麻学校项目对所有药物使用的优势比(OR)和95%置信区间(CI)为0.83(0.73,0.95),但GEE得出的是无关联,OR(95%CI)为0.92(0.79,1.07)。

结论

当聚类学校数据中存在ICS时,加权和未加权分析可能会产生不同的结果。需要谨慎研究聚类规模与结果之间的关系,并使用适当的分析方法。某些药物项目可能会影响学生对其他药物的使用行为,这凸显了在研究青少年药物使用情况时采用多变量分析方法的必要性。

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