Evidence map›Paper›PMID 40861313›Full record

ArticleEpidemiologic methods2025

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

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

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Article in Epidemiologic methods, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Aya A MitaniDalla Lana School of Public Health, University of Toronto, Toronto, Canada.ORCID https://orcid.org/0000-0002-0373-5032
Yushu ZouDalla Lana School of Public Health, University of Toronto, Toronto, Canada.
Scott T LeatherdaleSchool of Public Health Sciences, University of Waterloo, Waterloo, Canada.
Karen A PatteDepartment of Health Sciences, Brock University, St. Catharines, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

adolescent healthclustered datacluster-weighted generalized estimating equationsmarginal modelsmultivariate analysis

Identifiers

PMID40861313
PMCPMC12376993

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