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Adolescents’ Substance Use and Physical Activity Before and During the COVID-19 Pandemic

Educational Objective
To identify the key insights or developments described in this article
1 Credit CME
Key Points

Question  How have adolescents’ substance use and physical activity behaviors changed under stay-at-home orders related to the COVID-19 pandemic?

Findings  In this cohort study of adolescents in Northern California, the overall prevalence of e-cigarette, cannabis, or alcohol use did not meaningfully change with a statewide stay-at-home order, but physical activity declined considerably.

Meaning  While youth substance use prevention and cessation support should continue, enhanced efforts to increase physical activity are needed.

Abstract

Importance  Stay-at-home policies related to the COVID-19 pandemic could disrupt adolescents’ substance use and physical activity.

Objective  To compare adolescents’ substance use and physical activity behaviors before and after stay-at-home restrictions.

Design, Setting, and Participants  Ongoing prospective cohort study of tobacco use behaviors among ninth- and tenth-grade students enrolled at 8 public high schools in Northern California from March 2019 to February 2020 and followed up from September 2019 to September 2020. Race/ethnicity was self-classified from investigator-provided categories and collected owing to racial/ethnic differences in tobacco and substance use.

Exposures  In California, a COVID-19 statewide stay-at-home order was imposed March 19, 2020. In this study, 521 six-month follow-up responses were completed before the order and 485 were completed after the order.

Main Outcomes and Measures  The prevalence of substance use (ie, past 30-day use of e-cigarettes, other tobacco, cannabis, and alcohol) and physical activity (active ≥5 days/week) was compared at baseline and follow-up. A difference-in-difference approach was used to assess whether changes from baseline to 6-month follow-up varied if follow-up occurred after the stay-at-home order, adjusting for baseline behaviors and characteristics. All models were weighted for losses to follow-up using the inverse probability method. Weights were derived from a logistic regression model for having a follow-up response (dependent variable), as predicted by baseline characteristics and behaviors.

Results  Of 1423 adolescents enrolled at baseline, 1006 completed 6-month follow-up (623 [62%] were female, and 492 [49%] were non-Hispanic White). e-Cigarette use declined from baseline to 6-month follow-up completed before the stay-at-home order (17.3% [89 of 515] to 11.3% [58 of 515]; McNemar χ2 = 13.54; exact P < .001) and 6-month follow-up completed after the stay-at-home order (19.9% [96 of 482] to 10.8% [52 of 482]; McNemar χ2 = 26.16; exact P < .001), but the extent of decline did not differ statistically between groups responding before vs after the stay-at-home order (difference-in-difference adjusted odds ratio, 0.84; 95% CI, 0.47-1.52; P = .58). In contrast, being physically active was unchanged from baseline if follow-up was before the order (53.7% [279 of 520] to 52.9% [275 of 520]; McNemar χ2 = 0.09; exact P = .82) but declined sharply from baseline if follow-up was after the order (54.0% [261 of 483] to 38.1% [184 of 483]; McNemar χ2 = 30.72; exact P < .001), indicating a pronounced difference in change from baseline after the stay-at-home order (difference-in-difference adjusted odds ratio, 0.49; 95% CI, 0.35-0.69; P < .001). Overall in the cohort, reported use of other tobacco, cannabis, and alcohol did not differ meaningfully before and after the order.

Conclusions and Relevance  In this cohort, a reduction in e-cigarette use occurred independently of COVID-19 stay-at-home restrictions, but persistent cannabis and alcohol use suggest continued need for youth substance use prevention and cessation support. Declining physical activity during the pandemic is a health concern.

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Article Information

Corresponding Author: Benjamin W. Chaffee, DDS, MPH, PhD, University of California, San Francisco, 3333 California St, Ste 495, San Francisco, CA 94118 (benjamin.chaffee@ucsf.edu).

Accepted for Publication: February 3, 2021.

Published Online: May 3, 2021. doi:10.1001/jamapediatrics.2021.0541

Author Contributions: Dr Chaffee had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Chaffee, Couch, Hoeft, Halpern-Felsher.

Acquisition, analysis, or interpretation of data: Chaffee, Cheng, Hoeft.

Drafting of the manuscript: Chaffee, Halpern-Felsher.

Critical revision of the manuscript for important intellectual content: All authors.

Statistical analysis: Chaffee, Cheng.

Obtained funding: Chaffee, Halpern-Felsher.

Administrative, technical, or material support: Couch, Halpern-Felsher.

Supervision: Chaffee.

Conflict of Interest Disclosures: Dr Chaffee reports personal fees from Westat for consulting related to design and data analysis of studies of tobacco and oral health. Dr Halpern-Felsher reports personal fees from e-cigarette litigation outside the submitted work and is an unpaid scientific advisor and expert witness regarding some tobacco-related policies. No other disclosures were reported.

Funding/Support: Support was from the National Institutes of Health (grant U54 HL147127).

Role of the Funder/Sponsor: The funder had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Disclaimer: The content is solely the responsibility of the authors and does not necessarily represent the official views of the funder.

Additional Contributions: We thank Manali V. Vora, BDS, MPH, Divya Persai, BDS, MPH, and Claudia Guerra, MSW, of the University of California, San Francisco, for contributing to data collection. We also thank Janelle Urata, RDH, MS, and Miranda Werts, BA, of the University of California, San Francisco, and David Cash, BA, of Stanford University for contributing to data collection and project management. These individuals made their contributions as part of their roles as paid employees of their institutions at the time of the study.

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