Abstract
Introduction:
E-cigarette use increased dramatically among U.S. students during 2017–2019, and school plays an important role in preventing and reducing youth substance use. This study examines the prevalence and correlates of self-reported youth observation of e-cigarette use on school grounds.
Methods:
Data from the 2019 National Youth Tobacco Survey (N=19,018) were analyzed to examine the prevalence and factors associated with youth observation of e-cigarette use in or around the school. Multivariable logistic regressions were performed to assess the associations between youth observation of e-cigarette use and susceptibility to initiate cigarettes or e-cigarettes. Analyses were conducted in 2020.
Results:
In 2019, about 63.9% of students (16.8 million) reported noticing youth use of e-cigarettes in or around the school with bathroom or locker room as the most common location (33.2%). Female (versus male) students, high school (versus middle school) students, non-Hispanic Whites (versus other groups), former and past 30–day e-cigarette users (versus never users), students with exposure to tobacco marketing (versus none), and students living with a household member using e-cigarettes (versus not) had higher odds of reporting observation of vaping in schools. Among never tobacco users (n=11,518), observation of vaping in schools was associated with higher odds of being susceptible to smoking cigarettes (AOR=1.2, 95% CI=1.0, 1.3) and using e-cigarettes (AOR=1.7, 95% CI=1.6, 1.9), especially among middle school students.
Conclusions:
E-cigarette use is common on school grounds, and youth observation of vaping in school may increase the risk of initiating tobacco use in the future. School vaping policy and education programs are needed to curb youth e-cigarette use.
INTRODUCTION
Although the cigarette smoking rate among youth has been declining over the last several decades,1,2 the prevalence of current e-cigarette use among teens increased dramatically during 2017–2019.2,3 In 2019, more than 1 in 4 students in the 12th grade and more than 1 in 5 in the 10th grade reported using e-cigarettes in the past 30 days.3 In September 2018, the U.S. Food and Drug Administration warned that youth e-cigarette use is reaching an epidemic proportion.4 It is critical to identify risk factors that may influence youth vaping and inform strategies to prevent and reduce youth e-cigarette use.
Recently, pod-mod style e-cigarette products, such as JUUL, are gaining popularity among teens. These products closely resemble a USB flash drive with nicotine salts and high levels of nicotine concentration.5 School is an essential venue for youth growth, and adolescents spend a significant amount of time studying and playing with their friends in the school environment.6 Anecdotal evidence suggests that many students use JUUL in school hallways, bathrooms, and even in the classrooms.7 A previous study also reported a large number of YouTube videos regarding “JUUL at school,” “JUUL in class,” and “JUUL in the school bathroom” as of June 2018, and the search of stealth products to conceal vaping in school continues to grow.8 However, the prevalence at the population level and factors associated with youth observation of vaping behaviors on school grounds remain unknown. Such knowledge will be important to develop school policies and evidence-based programs in preventing and reducing youth vaping.
Youth observation of e-cigarette use in or around the school may normalize the vaping behaviors and reduce the perceived harmfulness of e-cigarette use, thus increasing the susceptibility to initiating e-cigarette use. Furthermore, youth use of e-cigarettes may serve as a gateway to cigarette smoking, marijuana, and other substance use.9,10 However, no studies have examined the relationship between youth observation of e-cigarette use in the school and future tobacco use behaviors. Meanwhile, adolescents undergo multiple stages of development, with younger adolescents more likely to be influenced by peers, which could increase the risk of initiating substance use.11 The author hypothesizes that there might be an interaction between youth observation of vaping in schools and the developmental stage (i.e., middle school versus high school) in association with adolescents’ susceptibility to tobacco use.
To address the gaps in knowledge, this study uses data from the 2019 National Youth Tobacco Survey (NYTS) to analyze the prevalence and correlates of youth observation of e-cigarette use in or around the school. Further, this paper reports population estimates of youth noticing vaping at specific locations on school grounds and assesses whether this observation is associated with susceptibility to smoking cigarettes or using e-cigarettes among never tobacco users.
METHODS
Study Sample
The NYTS is a cross-sectional, school-based survey conducted annually to produce a nationally representative sample of U.S. middle school (Grades 6–8) and high school (Grades 9–12) students. The 2019 NYTS was conducted using a stratified, 3-stage cluster sampling procedure and a detailed description of the 2019 NYTS survey can be found on the NYTS website.12 In 2019, a total of 19,018 students (aged 11–18 years) from 251 schools completed the NYTS questionnaire. The school participation rate was 77.2%, and the student response rate was 85.8%, yielding an overall response rate of 66.3%.13 The 2019 NYTS was electronically administrated in the school classroom setting for the first time, and a previous study has demonstrated that an electronic administration of NYTS can lead to more timely and valid surveillance of youth tobacco use.14 Given the use of public data with de-identified information, this study is exempt from the University of Nebraska Medical Center IRB.
Measures
The survey participants were asked the question: Have you ever seen anyone using an e-cigarette, such as JUUL, Vuse, MarkTen, or blu in any locations in or around your school? (Select one or more). Response options were in the sequence of no; yes, inside a school bathroom or locker room; yes, inside a classroom, yes, inside some other area of the school (hallway, cafeteria), yes, outside of the school, such as in the parking lot, sidewalk, or other school grounds; and yes, somewhere else not listed here. Those who responded affirmatively were defined with observations of e-cigarette use in or around the school.
Student e-cigarettes status was defined as never (students who reported having never tried an e-cigarette), former (students who reported having ever tried an e-cigarette but having not used it in the last 30 days), and past 30–day users (students who reported having used an e-cigarette ≥ 1 day in the past 30 days).15 Similarly, this study defined the status of cigarette smoking and other tobacco use as never, former, and past 30–day users. Other tobacco products included cigars (cigars, little cigars, and cigarillos), smokeless tobacco (chewing tobacco, snuff, dip, snus, and dissolvable tobacco), hookahs, pipe tobacco, bidis, and heated tobacco products.16
Among never tobacco users, the susceptibility to smoke cigarettes was measured on the basis of 3 NYTS questionnaire items:
Do you think you will try a cigarette soon?
Do you think you will smoke a cigarette in the next year?
If one of your best friends were to offer you a cigarette, would you smoke it?
Responses for these questions included: definitely yes, probably yes, probably not, and definitely not. The respondents who answered definitely not to all 3 questions were classified into the group no susceptibility to smoking cigarettes.17 A similar method was used to create a dichotomous variable for susceptibility to use e-cigarettes.
Demographic variables included sex (male or female), race/ethnicity (non-Hispanic White, non-Hispanic Black, Hispanic, or non-Hispanic others), and school level (middle or high school). As exposure to tobacco marketing and tobacco use by household members could increase the risk of tobacco use,15 these confounding variables are also included in the analysis as covariates.
Statistical Analysis
Weighted estimates along with 95% CIs of the prevalence of youth observation of vaping in or around the school were calculated, both overall and stratified by demographic characteristics and tobacco-related variables. Multivariable logistical regression was performed to examine factors (explanatory variables) associated with youth observation of vaping (dependent variable). This study further reported the prevalence and population estimates of youth vaping at separate locations, overall and by grade and e-cigarette use status. Sampling weights, survey stratum, and primary sampling units were included in the analysis to account for the complex survey design. Among never tobacco users, logistic regression models were conducted to examine the associations between youth observation of e-cigarette use in or around the school (explanatory variable) and susceptibility to smoke cigarettes and use e-cigarettes (separate dependent variables). Stratified analyses were performed by middle and high school students. AORs were calculated in the multivariable analysis to adjust for confounding effects from covariates. Statistical analyses were performed using SAS, version 9.4 and p<0.05 was considered statistically significant. Analyses were conducted in 2020.
RESULTS
Table 1 depicts the sample characteristics of 2019 NYTS data, which included 48.0% female students, 55.9% high school students, 56.2% non-Hispanic Whites, 13.3% non-Hispanic Blacks, 25.0% Hispanics, 20.0% past 30–day e-cigarette users, 4.3% past 30–day cigarette smokers, and 9.4% other tobacco users. Exposure to tobacco marketing was common among adolescents with 81.7% of respondents reporting exposure to cigarette/other tobacco marketing and 69.0% reporting exposure to e-cigarette marketing. About 14.2% of students reported living with a household member who uses e-cigarettes.
Table 1.
Sample Characteristics of 2019 NYTS (n=19,018)
| Characteristic | n | Weighted % (95% CI)a |
|---|---|---|
| Overall | 19,018 | 100 |
| Sex | ||
| Male | 9,803 | 52.0 (50.4, 53.7) |
| Female | 9,099 | 48.0 (46.3, 49.6) |
| School level | ||
| Middle school | 8,837 | 44.1 (39.8, 48.3) |
| High School | 10,097 | 55.9 (51.7, 60.2) |
| Race/ethnicity | ||
| NH White | 9,351 | 56.2 (51.7, 60.7) |
| NH Black | 2,430 | 13.3 (10.5, 16.2) |
| Hispanic | 5,564 | 25.0 (21.8, 28.1) |
| Others | 1,227 | 5.5 (4.4, 6.6) |
| Cigarette smoking | ||
| Never | 16,061 | 83.7 (81.5, 86.0) |
| Former | 2,161 | 12.0 (10.4, 13.5) |
| Past 30 days | 748 | 4.3 (3.4, 5.2) |
| E-cigarette useb | ||
| Never | 12,563 | 65.2 (63.0, 67.3) |
| Former | 2,720 | 14.8 (13.5, 16.1) |
| Past 30 days | 3,627 | 20.0 (18.5, 21.5) |
| Other tobacco usec | ||
| Never | 15,058 | 78.3 (75.9, 80.6) |
| Former | 2,258 | 12.3 (10.8, 13.8) |
| Past 30 days | 1,702 | 9.4 (8.3, 10.6) |
| Exposure to cigarette and other tobacco marketingd | ||
| No | 3,391 | 18.3 (17.2, 19.3) |
| 1 | 6,392 | 34.8 (33.6, 36.0) |
| ≥2 | 8,417 | 46.9 (45.2, 48.5) |
| Exposure to e-cigarette marketingd | ||
| No | 5,830 | 31.0 (29.5, 32.5) |
| 1 | 4,778 | 25.8 (24.9, 26.8) |
| ≥2 | 7,721 | 43.1 (41.8, 44.4) |
| Tobacco use by household memberse | ||
| None | 11,265 | 59.7 (57.2, 62.2) |
| Cigarettes and other tobacco productsb | 4,718 | 26.1 (24.2, 28.0) |
| E-cigarettes | 2,449 | 14.2 (13.0, 15.3) |
Weighted percentage (95% CI) within the column.
Students were provided instruction that The next several questions are about electronic cigarettes or e-cigarettes. Some brand examples include JUUL, Vuse, MarkTen, and blu. E-cigarettes are battery powered devices that usually contain a nicotine-based liquid that is vaporized and inhaled. You may also know them as e-cigs, vape-pens, e-hookahs, vapes, or mods.
Other tobacco products include cigars (cigars, little cigars, and cigarillos), smokeless tobacco (chewing tobacco, snuff, dip, snus, and dissolvable tobacco), hookahs, pipe tobacco, bidis, and heated tobacco product.
Four dichotomous variables were created to measure the channels of exposure to advertising: the Internet, newspapers/magazines, stores, and TV/streaming services/movies, with 0 including response options of I don’t use, Never, and Rarely, were coded as 0 (no exposure), while response options of Sometimes, Most of the time, and Always were coded as 1 (exposure). The number of exposures from multiple channels were further summed as exposure from 0, 1, ≥2 types of channels.
Tobacco use by other household members was defined as “none,” “e-cigarette”, and “other tobacco product use” by the question Does anyone who lives with you now…? (CHOOSE ALL THAT APPLY) with the following response options: Smoke cigarettes, Smoke cigars, cigarillos, or little cigars, Use chewing tobacco, snuff, or dip, Use electronic cigarettes or e-cigarettes, Smoke tobacco from a hookah or waterpipe, Smoke pipes filled with tobacco (not waterpipes), Use snus, Use dissolvable tobacco products, Smoke bidis (small brown cigarettes wrapped in a leaf), Use heated tobacco products, and No one who lives with me now uses any form of tobacco.
NYTS, National Youth Tobacco Survey; NH, non-Hispanic.
The prevalence and population estimates of youth observation of e-cigarette use in specific locations are presented in Table 2. Overall, 63.9% (weighted n=16,850,000) of U.S. students reported observation of e-cigarette use in or around the school. Inside a school bathroom or locker room was the most common location, with 33.2% of students (8,964,000) reporting observation of someone vaping, followed by outside of the school (32.8%, 8,851,000), somewhere else not listed here (28.4%, 7,661,000), inside a classroom (21.4%, 5,792,000), and inside some other area of the school (hallway, cafeteria; 19.8%, 5,338,000). Moreover, 33.5% of students (n=8,818,000) reported observation of youth e-cigarette use in only 1 location in or around the school, 8.4% (n=2,222,000) reported on 2 locations, 6.7% (n=1,777,000) on 3 locations, 8.2% (n=2,148,000) on 4 locations, and 7.2% (n=1,884,000) on all 5 locations.
Table 2.
Distribution of Youth Observation of E-cigarette Use in or Around School, NYTS, 2019 (n=19,018)
| Overall | School levelb | E-cigarette use status, weighted % (95% CI)b | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Observations | n | Weigh ted % (95% CI) | Weigh ted n (thous ands)a | Middle school, weighted % (95% CI) | High school, weighted % (95% CI) | P-valuec | Never use, weighted % (95% CI) | Former use, weighted % (95% CI) | Past 30-day use, weigh ted % (95% CI) | P-valuec |
| Venue | ||||||||||
| Inside a school bathroom or locker room | 6, 07 1 |
33.2 (30.9, 35.5) | 8,964 | 17.9 (15.8, 20.0) | 45.3 (42.0, 48.7) | <0.0001 | 25.8 (23.6, 27.9) | 48.1 (44.6, 51.7) | 46.7 (43.6, 49.8) | <0.0001 |
| Inside a classroom | 3, 83 4 |
21.4 (19.4, 23.5) | 5,792 | 8.8 (7.2, 10.5) | 31.4 (28.4, 34.5) | <0.0001 | 15.1 (13.4, 16.8) | 33.1 (29.5, 36.6) | 34.0 (31.0, 36.9) | <0.0001 |
| Inside some other area of the school (e.g, hallway, cafeteria) | 3, 52 3 |
19.8 (18.0, 21.6) | 5,338 | 8.5 (7.2, 9.8) | 28.7 (26.0, 31.5) | <0.0001 | 14.4 (12.7, 16.0) | 29.8 (26.3, 33.3) | 30.2 (27.6, 32.9) | <0.0001 |
| Outside of the schoold | 6, 01 7 |
32.8 (30.6, 34.9) | 8,851 | 20.5 (18.7, 22.4) | 42.5 (39.6, 45.4) | <0.0001 | 26.4 (24.3, 28.5) | 45.8 (42.7, 49.0) | 44.4 (41.6, 47.2) | <0.0001 |
| Somewhe re else not listed here | 5, 26 6 |
28.4 (27.2, 29.5) | 7,661 | 29.5 (27.7, 31.2) | 27.5 (26.0, 29.0) | 0.0877 | 27.5 (26.2, 28.7) | 33.7 (31.5, 36.0) | 27.7 (25.7, 29.7) | <0.0001 |
| Number of locations | ||||||||||
| 0 | 6, 94 2 |
36.1, (34.1, 38.1) | 9,502 | 48.0 (45.3, 50.7) | 26.6 (24.1, 29.0) | <0.0001 | 43.3 (41.2, 45.5) | 22.8 (20.4, 25.2) | 21.7 (19.2, 24.2) | <0.0001 |
| 1 | 6, 21 4 |
33.5 (32.4, 34.6) | 8,818 | 34.5 (32.8, 36.2) | 32.7 (31.2, 34.1) | 33.0 (31.8, 34.2) | 32.8 (30.1, 35.5) | 35.5 (33.5, 37.5) | ||
| 2 | 1, 55 4 |
8.4 (7.9, 8.9) | 2,222 | 7.7 (7.0, 8.4) | 9.0 (8.2, 9.8) | 7.9 (7.2, 8.5) | 9.8 (8.3, 11.3) | 9.2 (8.2, 10.3) | ||
| 3 | 1, 18 9 |
6.7 (6.1, 7.4) | 1,777 | 4.2 (3.6, 4.9) | 8.8 (7.8, 9.7) | 5.8 (5.2, 6.4) | 9.7 (8.0, 11.4) | 7.7 (6.5, 8.9) | ||
| 4 | 1, 44 8 |
8.2 (7.2, 9.1) | 2,148 | 3.0 (2.3, 3.7) | 12.3 (10.9, 13.6) | 5.2 (4.4, 5.9) | 11.8 (10.1, 13.5) | 15.4 (13.8, 17.1) | ||
| 5 | 1, 20 6 |
7.2 (6.2, 8.1) | 1,884 | 2.5 (2.0, 3.1) | 10.8 (9.2, 12.3) | 4.8 (4.1, 5.6) | 13.1 (10.3, 16.0) | 10.4 (8.9, 11.8) | ||
Notes: Boldface indicates statistical significance (p<0.05).
Weighted n based on the weighted total population estimate of 27,011,216 U.S. middle and high school students.
Weighted percentage (95% CI) within the column.
Rao–Scott χ2tests were performed to compare the prevalence by school level and e-cigarette use status.
Outside of the school, such as in the parking lot, on sidewalk, or on other school grounds.
NYTS, National Youth Tobacco Survey.
High school students (versus middle school students) and former or past 30–day e-cigarette users (versus never e-cigarette users) were more likely to report observation of e-cigarette use in all locations except somewhere else. They were also more likely to report observation of e-cigarette use on multiple locations in or around the school than their counterparts.
As shown in Table 3, female students were more likely than male students to report noticing vaping in or around the school (65.7% vs 62.4%, AOR=1.1, 95% CI=1.0, 1.2) and high school students had higher odds of reporting observation of e-cigarette use in schools than middle school students (73.4% vs 52.0%, AOR=2.3, 95% CI=2.0, 2.8). Non-Hispanic Whites (versus other groups), former and past 30–day e-cigarette users (versus never users), students with exposure to tobacco marketing (versus no), and students living with a household member using e-cigarettes (versus no) were associated with higher odds of reporting observation of vaping in or around the school. For instance, 78.3% of past 30–day e-cigarette users reported seeing e-cigarette use on school grounds versus 56.7% of never e-cigarette users (AOR=1.8, 95% CI=1.5, 2.1).
Table 3.
Factors Associated with Youth Observation of E-cigarette Use in or Around School, NYTS, 2019 (n=19,018)
| Youth observation of e-cigarette use in or around school | |||
|---|---|---|---|
| Factor | % (95% CI)a | AOR (95% CI)b | p-valueb |
| Overall | 63.9 (61.9, 65.9) | — | — |
| Sex | |||
| Male | 62.4 (60.2, 64.6) | ref | — |
| Female | 65.7 (63.5, 68.0) | 1.1 (1.0, 1.2) | 0.005 |
| Grade | |||
| Middle school | 52.0 (49.3, 54.7) | ref | — |
| High school | 73.4 (71.0, 75.9) | 2.3 (2.0, 2.8) | <0.0001 |
| Race/ethnicity | |||
| NH White | 67.9 (65.8, 69.9) | ref | — |
| NH Black | 54.7 (50.3, 59.1) | 0.6 (0.5, 0.8) | 0.0001 |
| Hispanic | 62.5 (59.8, 65.2) | 0.9 (0.8, 1.0) | 0.0499 |
| Others | 58.1 (52.9, 63.4) | 0.8 (0.7, 1.0) | 0.0124 |
| E-cigarette use | |||
| Never | 56.7 (54.5, 58.8) | ref | — |
| Former | 77.2 (74.8, 79.6) | 1.9 (1.6, 2.2) | <0.0001 |
| Past 30 days | 78.3 (75.8, 80.8) | 1.8 (1.5, 2.1) | <0.0001 |
| Exposure to cigarette and other tobacco marketing | |||
| No | 49.4 (46.3, 52.4) | ref | |
| 1 | 64.2 (61.8, 66.6) | 1.4 (1.3, 1.7) | <0.0001 |
| ≥2 | 69.8 (67.9, 71.7) | 1.5 (1.3, 1.7) | <0.0001 |
| Exposure to e-cigarette marketing | |||
| No | 49.1 (46.4, 51.8) | ref | |
| 1 | 65.2 (62.8, 67.7) | 1.5 (1.4, 1.8) | <0.0001 |
| ≥2 | 73.9 (71.9, 75.9) | 2.1 (1.8, 2.4) | <0.0001 |
| Tobacco use by household members | |||
| None | 60.4 (58.1, 62.7) | ref | — |
| Other tobacco pro ducts | 65.1 (62.4, 67.7) | 1.1 (0.9, 1.2) | 0.3845 |
| E-cigarettes | 78.2 (75.6, 80.9) | 1.6 (1.4, 1.9) | <0.0001 |
Notes: Boldface indicates statistical significance (p<0.05).
Weighted percentage (95% CI) within the column.
In multivariable logistic regression, youth observation of e-cigarette use in or around the school (yes versus no) was the dependent variable, and all factors listed in the first column were explanatory variables.
NYTS, National Youth Tobacco Survey; NH, non-Hispanic.
Self-reported observation of youth vaping in or around the school was associated with higher odds of susceptibility to smoking cigarettes (AOR=1.2, 95% CI=1.0, 1.3, p=0.008) and using e-cigarettes (AOR=1.7, 95% CI=1.6, 1.9, p<0.0001) (Table 4). Moreover, the associations were more pronounced among middle school students than high school students. For instance, youth observation of vaping in or around the school was significantly associated with being susceptible to smoking cigarettes among middle school students (AOR=1.2, 95% CI=1.1, 1.3, p=0.001), but not among high school students (p=0.53).
Table 4.
Association Between Youth Observation of E-cigarette Use in or Around School and Susceptibility to Use Cigarettes and E-cigarettes Among Never Tobacco Users, NYTS, 2019 (n=11,518)
| Susceptible to e-cigarette use | Susceptible to cigarette smoking | |||||
|---|---|---|---|---|---|---|
| Observation of e-cigarette use in or around School by grade | Weighted % (95% CI) | AOR (95% CI)a | P-value | Weighted % (95% CI) | AOR (95% CI)a | P-value |
| Overall | ||||||
| No | 26.5 (24.9, 28.1) | 24.1 (22.4, 25.8) | ||||
| Yes | 39.5 (38.0, 41.0) | 1.7(1.6, 1.9) | <0.0001 | 26.7 (25.3, 28.1) | 1.2 (1.0, 1.3) | 0.008 |
| Middle schoolb | ||||||
| No | 26.9 (25.0, 28.8) | 24.7 (22.6, 26.8) | ||||
| Yes | 43.8 (41.2, 46.4) | 1.8 (1.6, 2.1) | <0.0001 | 31.8 (29.5, 34.1) | 1.2 (1.1, 1.4) | 0.001 |
| High schoolb | ||||||
| No | 25.7 (22.8, 28.7) | 22.7 (19.8, 25.7) | ||||
| Yes | 35.8 (33.7, 37.9) | 1.6 (1.3, 1.9) | <0.0001 | 22.3 (20.8, 23.9) | 0.9 (0.8, 1.1) | 0.53 |
| Interactionc | 1.2 (1.0, 1.5) | 0.11 | 1.3 (1.1, 1.7) | 0.02 | ||
Notes: Boldface indicates statistical significance (p<0.05).
Multivariable regression models were performed to assess the association between youth observation of e-cigarette use (predictive variable) and susceptibility to tobacco use (dependent variable) among non-tobacco users. Covariates include sex, race/ethnicity, school level, exposure to cigarette and other tobacco marketing, exposure to e-cigarette marketing, and tobacco use by household members.
Separate analyses were performed on two susceptibility variables (e-cigarette use and cigarette smoking) for all students and were further stratified by middle and high school students.
The results of interaction analysis indicate that, as compared to high schools, middle schools have higher odds of initiating cigarette smoking for students who had observation (versus none) of e-cigarette use.
NYTS, National Youth Tobacco Survey.
DISCUSSION
This study used nationally representative data to estimate that nearly two thirds of U.S. middle and high school students reported observing e-cigarette use in or around the school in 2019. Given that students in the U.S. spend an average of 180 days in the school year and 6.64 hours in school during school days6 and there is a strong interplay between school environments and teen health behaviors,18,19 these statistics are concerning. The findings from youth observation of e-cigarette use echo with the high prevalence of e-cigarette use.2,3 As the newer generations of e-cigarette products often contain high concentrations of nicotine,5 adolescent e-cigarette users could quickly develop nicotine addiction and may have to vape in school. Furthermore, the prevalence of exposure to secondhand aerosol among U.S. youth significantly increased from 25.6% in 2017 to 33.2% in 2018.20 Owing to the clustering of students in the school environment, youth vaping on school grounds could lead to exposure to secondhand aerosol among other students, including never tobacco users.21
The findings of this study indicate an urgent need to enforce vape-free campus policies and implement evidence-based programs to prevent and reduce youth vaping on school grounds. Some school districts have taken actions to counteract the surge in e-cigarette use in the school. For instance, some districts have installed vaping detectors or camera surveillance near restrooms, some others have tried limiting the number of students allowed in the restroom at once or assigning teachers to restroom duty for surveillance, and a few schools have even tried to remove stall doors.22 These actions are consistent with the finding that inside a school bathroom or locker room is the most common location where youth noticed vaping (33.2%). However, a large number of students also reported observation of youth vaping inside the classroom (21.4%) and inside some other areas of the school (hallway or cafeteria, 19.8%). This brings additional challenges for school educators to track youth vaping behaviors as these pod-mod style vaping products have a sleek design to look like school supplies, such as pens, highlighters, and USB drives, and provide emissions that are hard to detect.5 Thus, students can take quick whiffs undetected while sitting inside the classroom or walking down the hallway. A previous study also reported that less than half of middle and high school teachers and administrators could accurately identify a photo of JUUL as a vaping device.23 As e-cigarette products evolve quickly,24 ongoing training for school personnel and parents about new generations of vaping products and their harmfulness is warranted to curb e-cigarette use in schools.
Youth have a more positive norm toward vaping than smoking.25 Social norms, including friends’ e-cigarette use, are strongly associated with initiation and frequent use of e-cigarettes among adolescents.26 Previous studies have also shown that the school-level prevalence of vaping was significantly associated with student-level e-cigarette use.27,28 This study found that youth observation of vaping on school grounds was associated with significantly higher odds of being susceptible to smoking cigarettes (AOR=1.2) and using e-cigarettes (AOR=1.7). The Ecological Systems Theory29 posits that youth development is influenced by factors near to adolescents such as family and friends and more distal factors such as school environments. Students who have seen vaping in or around the school may develop curiosity about vaping, perceive vaping as a school norm, and model peers to initiate e-cigarette use. Past studies have demonstrated that some influencing factors could lead to higher risks of substance initiation among younger (versus older) adolescents.10,30 Consistently, this study found heterogeneity in the association of youth observation of vaping and susceptibility to tobacco use by school level with more pronounced effects among middle school students than high school students. As younger adolescents (versus older) are more likely to be influenced by their peers,31 findings from this study highlight the importance of starting prevention efforts on vaping at an earlier age.
To the best of the author’s knowledge, this is the first study to report that vaping is prevalent in or around the school, with 16.8 million U.S. middle and high school students reporting observation of vaping behaviors on school grounds in 2019. Furthermore, female (versus male) students, high school (versus middle school) students, non-Hispanic Whites (versus other groups), and past 30–day tobacco users were more likely to report the notice of youth vaping. The disparities may reflect vaping norms and clustering of e-cigarette use among these vulnerable students, and thus tailored education and messages are needed to reduce youth e-cigarette use in or around the school.
This study also identified heterogeneity in the prevalence of self-reported observation of vaping among never (57%), former (77%), and current e-cigarette users (78%). A previous study has found similar disparities in reporting exposure to e-cigarette advertising promotions with a higher prevalence among current and former e-cigarette users than never users.15 There may be several plausible explanations. First, former or current e-cigarette users are more prone to observe this potentially surreptitious behavior on school grounds because they are more familiar with e-cigarette products than never users. They may over-report the occurrence of e-cigarette use as a confirmation of vaping as indicative of their own identity. Second, never users may under-report the observation of vaping behaviors in or around the school owing to their unfamiliarity of e-cigarette devices, especially given the ease of concealment for the new generation of vaping products.8 Thus, caution needs to be placed in the interpretation of these self-reported data.
Recently, some institutes have started to develop evidence-based programs to address the vaping behaviors in or around the school. For instance, a pilot study of “CATCH My Breath,” an e-cigarette prevention program, has shown positive effects in improving youth knowledge on e-cigarette use and preventing e-cigarette ever use among Texas middle school students.32 The U.S. Food and Drug Administration has included e-cigarette products in the “The Real Cost” campaign to educate youth that e-cigarettes, just like cigarettes, put them at risk for addiction.33 The Stanford Tobacco Prevention Toolkit also provides lecture-based materials on e-cigarette use.34 However, the adoption and dissemination of evidence-based vaping prevention in school settings is limited. Schools also lack clear and consistent guidelines for restricting vaping behaviors. For instance, >80% of schools reported that they had an e-cigarette policy. Still, less than half indicated that their policies specifically included JUUL in a survey of 1,420 middle and high school teachers and administrators.23 Moreover, studies have found little or no evidence on the long-term effectiveness of school-based anti-tobacco programs.35 More research is needed to evaluate each of these programs and increase the reach, effectiveness, adaption, implementation, and maintenance36 of these programs to simultaneously target prevention, cessation, and denormalization of youth vaping behaviors.
Limitations
This study is subject to limitations. First, the 2019 NYTS data are cross-sectional; thus, causal inference cannot be established. Second, tobacco use behaviors were self-reported, subject to recall and social desirability biases, especially for younger respondents.37 However, the test–retest reliability of self-reported behaviors related to tobacco use among adolescents is high.37 Third, youth observation of e-cigarette use on school grounds was measured by the question with check-all-that-apply options, which may be biased downward in estimating the true prevalence.38 Future surveys should consider using an alternative design with forced-choice questions. Finally, given that a majority of study participants were never tobacco users, they may not be able to accurately recognize an e-cigarette as a wide range of devices fall under the umbrella term “e-cigarettes.”39 Furthermore, e-cigarette use in youth may be underestimated when it was assessed with the term “e-cigarette” rather than with brand names.39 However, the 2019 NYTS provided brand names including JUUL, Vuse, Mark Ten, and blu in the instructions to reduce bias in estimating e-cigarette use prevalence.
CONCLUSIONS
Despite these limitations, this study demonstrated that e-cigarette use is common in or around schools, and youth observation of vaping in school may increase the risk of initiating cigarettes or e-cigarettes in the future. Evidence-based vaping programs are needed to prevent and reduce youth e-cigarette use.
ACKNOWLEDGMENTS
Research reported in this publication was supported by grant number R03CA228909 (Principal Investigator: Dai) from the National Cancer Institute and U.S. Food and Drug Administration Center for Tobacco Products. The content is solely the responsibility of the authors and does not necessarily represent the official views of NIH or the Food and Drug Administration. The funding agency had no role in the design and conduct of the study; collection, management, analysis, or interpretation of the data; preparation, review, or approval of the manuscript; or decision to submit the manuscript for publication.
Footnotes
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No financial disclosures were reported by the author of this paper.
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