Abstract
Objective:
Nicotine exposure among adolescent e-cigarette users remains a public health concern. JUUL, a popular e-cigarette brand among youth, is particularly alarming given the high nicotine delivery (59 mg/mL). This study compares e-cigarette use frequency and symptoms of nicotine dependence among adolescent JUUL and non-JUUL users.
Methods:
We analyzed data from the 2020 National Youth Tobacco Survey. Participants were n=1,713 U.S. middle and high school students who reported past 30-day e-cigarette use. We compared adolescent e-cigarette users who reported JUUL use to those who did not. Outcomes were: (1) symptoms of nicotine dependence (i.e. nicotine cravings; use within 30 minutes of waking); (2) past 30-day e-cigarette use frequency, categorized as 1–5 days, 6–19 days, and 20–30 days. Covariates were sex, race/ethnicity, other tobacco product use, primary e-cigarette device type (i.e., disposable; pod; mod/tank).
Results:
Overall, 49.5% of adolescent e-cigarette users reported using JUUL in the past 30 days, 40.1% reported symptoms of nicotine dependence, and 36.2% reported using an e-cigarette on 20–30 days. JUUL users were 1.77 (95% CI: 1.36 – 2.31) times as likely to report symptoms of nicotine dependence and 1.43 (95% CI: 1.02 – 2.01) time as likely to report using e-cigarettes on 20–30 days, compared to 1–5 days, relative to non-JUUL users, controlling for covariates.
Conclusion:
JUUL use was associated with greater odds of nicotine dependence and more frequent e-cigarette use among adolescents. Greater prevention and regulatory efforts should be made to prevent adolescent use of high dose nicotine devices such as JUUL.
Keywords: Youth, JUUL, Nicotine Dependence, Electronic Cigarettes, NYTS
INTRODUCTION
In 2020, approximately 3.58 million adolescents (13.1%) reported using an electronic cigarette (e-cigarette) in the past 30-days.1 Prefilled pod/cartridge devices are the most commonly used e-cigarette device among youth,2 with the JUUL brand dominating the market share.3 JUUL delivers nicotine at rates similar to combustible cigarettes;4 substantially greater than most e-cigarette brands,3 although other brands (e.g., Puff Bar) are adopting similar technology to deliver equivalent or more nicotine as JUUL.
A study of n=185 youth in the US shows that JUUL users report greater symptoms of nicotine dependence relative to those who use other e-cigarette products;5 similar findings were observed by Boykan and colleagues (2019) among a convenience sample of youth and young adults.6 Further, Monitoring the Future (MTF) data of a nationally representative sample of 8th, 10th, and 12th grade students found that nearly 42% of JUUL users reported at least one symptom of nicotine dependence, with nicotine cravings being the most prevalent symptom of nicotine dependence.7 Nicotine dependence among adolescent e-cigarette users is a significant public health concern,8 underscoring an urgent need to monitor and assess the implications of JUUL on adolescent nicotine dependence.
Using nationally representative data of middle and high school e-cigarette users in the United States, we examined the association between using JUUL and (1) symptoms of nicotine dependence; and (2) e-cigarette use frequency. This study examined the previously observed relationship between JUUL use and two symptoms of nicotine dependence among a nationally representative sample of middle and high school students (6th through 12th grade), thereby extending prior studies that found a relationship between JUUL and nicotine dependence in a convenience sample of young people5,6 and another study using nationally representative data of 8th, 10th, and 12th grade students.7
METHODS
Study Sample & Population
This is a secondary data analysis of the 2020 National Youth Tobacco Survey (NYTS). NYTS is an annual, cross-sectional survey conducted by the Centers for Disease Control and Prevention (CDC). NYTS uses a stratified, three-stage cluster sample design to obtain a representative sample of 6th–12th grade students in the United States in order to assess adolescent tobacco use behaviors.
This study examined adolescents who reported using an e-cigarette in the past 30 days (n=1,769). However, n=56 were excluded due to missing data on study variables, resulting in a final sample size of n=1,713.
Measures
JUUL Use.
The primary independent variable was any JUUL use in the past 30 days. Participants were asked “During the past 30 days, what e-cigarette brands did you use?” and were allowed to check all that applied. Participants who selected JUUL were considered JUUL users, regardless of what other products they also reported using in the past 30 days. Participants who selected any other brand(s) (e.g., Blu; Vuse; Suorin) but did not select JUUL were considered non-JUUL users (referent group).
Nicotine Dependence.
The first outcome variable was symptoms of nicotine dependence, assessed by two validated measures: (1) Participants were asked “During the past 30 days, have you had a strong craving or felt like you really needed to use a tobacco product of any kind?” Nicotine dependence was defined as reporting “yes” to this question;9 (2) Participants were asked “How soon after you wake up do you want to use a tobacco product?” Symptom of nicotine dependence was measured as reporting using a tobacco product within 30 minutes of waking.10 These are the only two measures of nicotine dependence assessed by the NYTS questionnaire; thus, a more comprehensive diagnosis of nicotine dependence could not be ascertained. As the two measures of nicotine dependence were highly correlated (Cronbach alpha: 0.613) a single measure reflecting any symptoms of nicotine dependence was created. This decision was made based on the facts that alpha scores are sensitive to the number of items11 and that an alpha score over 0.6 indicates the items are unidimensional.12 Hence, the high alpha score for only two items along a consistent construct (i.e., symptoms of nicotine dependence) was the basis for analyzing symptoms of nicotine dependence as a single, unidimensional outcome. Participants with neither symptom of dependence were categorized as the referent outcome (0) while participants with either symptoms of nicotine dependence were coded as 1.
E-Cigarette Use Frequency.
The second outcome was frequency of e-cigarette use. Participants were asked “During the past 30-days, on how many days did you use e-cigarettes?” To our knowledge, there is no established methodology for categorizing non-daily tobacco use;13–16 thus, we elected to categorize e-cigarettes use into three groups: (1) 1–5 days per month (referent outcome); (2) 6–19 days (coded as 1); and (3) 20–30 days (coded as 2). This coding reflects light, moderate, and heavy use, respectively.
Covariates.
Sex was coded as a binary variable (male as referent). Race/ethnicity was categorized as: non-Hispanic white (referent); non-Hispanic black; Hispanic/Latino; and “other” (i.e., non-Hispanic Asian; multiracial; and any other race). Grade level was categorized as middle school (6th – 8th grade; referent) and high school (9th – 12th grade).
To account for variance in device preference among JUUL users, this study controlled for device type most often used. Participants were asked “which of the following best describes the type of e-cigarette you have used in the past 30 days? If you have used more than one type, please think about the one you use most often.” Participants were categorized as “pod/cartridge users” if they responded with “An e-cigarette that uses pre-filled pods or cartridges (e.g. JUUL).” Participants who reported using disposable e-cigarettes, tanks, mod systems, or responded “I don’t know” were categorized as “non-pod/cartridge users.”
This study also controlled for a binary measure of any use of other tobacco products in the past 30 days. These products included: cigarettes, cigars/cigarillos/little cigars, chewing tobacco, pipe, bidis, hookah, snus, dissolvable and roll-your-own tobacco. Those who reported using one or more products were considered other tobacco product users.
Statistical Analyses
Weighted frequencies for descriptive statistics were computed. A multivariable logistic regression was utilized to examine the association between JUUL use and any symptoms of nicotine dependence. Next, a multivariable multinomial logistic regression was conducted to examine the associations between JUUL use and e-cigarette use frequency. For the multinomial logistic regression, light use (i.e., 1–5 days) served as the referent outcome and was compared to moderate (i.e., 6–19 days) and heavy (i.e., 20–30 days) e-cigarette use in the past 30 days. Multinomial logit coefficients for the multinomial logistic regression were exponentiated and reported as Relative Risk Ratios (RRR). All models controlled for sex, race/ethnicity, grade level, other tobacco use, and device type preference. Data were weighted to be representative of adolescent e-cigarette users in the United States. All analyses were conducted using STATA 14.2 (College Station, TX).
RESULTS
Descriptive Statistics
Overall, 49.5% of adolescent e-cigarette users reported using JUUL in the past 30-days. Approximately 40.1% of adolescent e-cigarette users reported symptoms of nicotine dependence and 36.2% reported heavy e-cigarette use (i.e., use on 20–30 days in the past month). Participants used an average of 1.94 e-cigarette devices. The number of devices used was greater for JUUL users (mean: 2.67) than non-JUUL users (mean 1.21); however, as these measures are not independent of each other, statistical differences could not be calculated. Descriptive statistics including study sample demographics are available in Table 1.
Table 1:
Descriptive Statistics of Adolescent E-Cigarette Users by Nicotine Dependence and E-Cigarette Use Frequency (NYTS, 2020; n=1,713)
| Full Sample (Column %) | Nicotine Diependencea | E-Cigarette Use, Days Per Monthc | ||||
|---|---|---|---|---|---|---|
|
| ||||||
| No | Yes | 1–5 Days | 6–19 Days | 20–30 Days | ||
| Full Sample | 100% | 59.9% (56.9 – 62.8) | 40.1% (37.2 – 43.1) | 44.1% (40.6 – 47.7) | 19.7% (17.5 – 22.0) | 36.2% (32.6 – 40.0) |
| E-Cigarette Brand d | ||||||
| Non-JUUL | 50.5% (44.4 – 56.6) | 67.5% (63.0 – 71.6) | 32.5% (28.4 – 37.0) | 47.9% (42.6 – 53.2) | 19.1% (15.7 – 23.1) | 33.0% (28.4 – 37.9) |
| JUUL | 49.5% (43.4 – 55.7) | 52.1% (48.7 – 55.5) | 47.9% (44.5 – 51.3) | 40.3% (36.2 – 44.5) | 20.2% (17.6 – 23.1) | 39.5% (34.6 – 44.5) |
| Sex | ||||||
| Males | 48.2% (45.0 – 51.4) | 58.2% (53.2 – 63.0) | 41.8% (37.0 – 46.8) | 47.1% (42.0 – 52.3) | 20.5% (17.5 – 23.8) | 32.4% (27.3 – 38.0) |
| Females | 51.9% (48.6 – 55.1) | 61.4% (58.0 – 64.8) | 38.6% (35.2 – 42.0) | 41.4% (37.6 – 45.2) | 18.9% (16.4 – 21.8) | 39.7% (35.7 – 43.9) |
| Grade Level | ||||||
| Middle School | 15.2% (10.6 – 21.3) | 62.3% (55.9 – 68.4) | 37.7% (31.6 – 44.1) | 59.1% (51.6 – 66.2) | 20.3% (15.1 – 26.8) | 20.6% (16.4 – 25.5) |
| High School | 84.8% (78.7 – 89.4) | 59.4% (56.1 – 62.7) | 40.6% (37.3 – 43.9) | 41.5% (38.0 – 45.0) | 19.6% (17.8 – 22.2) | 39.0% (35.2 – 42.9) |
| Race/Ethnicity | ||||||
| Non-Hispanic White | 57.4% (51.8 – 62.8) | 55.3% (51.1 – 59.4) | 44.7% (40.7 – 48.9) | 38.3% (35.3 – 41.3) | 20.3% (17.9 – 23.1) | 41.4% (37.8 – 45.1) |
| Hispanic/Latino | 26.8% (21.1 – 33.5) | 70.0% (56.7 – 73.9) | 30.0% (26.1 – 34.1) | 57.0% (50.2 – 63.6) | 17.2% (13.3 – 22.0) | 25.8% (19.8 – 32.9) |
| Non-Hispanic, Black | 5.0% (3.4 – 6.7) | 58.4% (42.0 – 73.2) | 41.6% (26.8 – 58.0) | 46.6% (33.6 – 60.1) | 22.6% (12.6 – 37.2) | 30.8% (18.5 – 46.6) |
| Othere | 10.8% (8.5 – 13.7) | 59.9% (47.6 – 71.1) | 40.1% (28.9 – 52.4) | 42.2% (31.8 – 53.4) | 20.8% (13.2 – 31.1) | 37.0% (28.1 – 46.9) |
| Other Tobacco Use f,g | ||||||
| No | 62.2% (57.8 – 66.5) | 68.5% (65.6 – 71.3) | 31.5% (28.7 – 34.4) | 50.0% (46.0 – 53.9) | 18.0% (15.4 – 21.0) | 32.0% (28.7 – 35.5) |
| Yes | 37.8% (33.5 – 42.20 | 45.6% (41.0 – 50.4) | 54.4% (49.6 – 59.0) | 34.5% (29.8 – 39.6) | 22.4% (19.0 – 26.1) | 43.1% (37.2 – 49.2) |
| Primary Device Type h | ||||||
| Not Pod/Cartridge | 52.6% (47.2 – 58.0) | 60.3% (56.2 – 64.3) | 39.7% (35.7 – 43.8) | 42.1% (37.9 – 46.3) | 21.6% (17.8 – 25.9) | 36.4% (31.4 – 41.6) |
| Pod/Cartridge | 47.4% (42.0 – 52.8) | 59.4% (55.3 – 63.3) | 40.7% (36.7 – 44.7) | 46.4% (41.1 – 51.9) | 17.5% (15.2 – 20.1) | 36.0% (30.6 – 41.9) |
NOTE: Percentages may not add up to 100% due to rounding.
Self-Report craving tobacco or using tobacco within 30-minutes of waking up.
Past 30-day use of any of the following: cigarettes, cigars, cigarillos, little cigars, pipe tobacco, bidis, and/or hookah.
Self-reported days using an e-cigarette in the past 30-days
Self-Report using JUUL in the past 30-days
“Other” is where a response was “Asian, non-Hispanic”, “American Indian/Alaska Native, non-Hispanic;” or “native Hawaiian and other Pacific Islanders, non-Hispanic”
For Nicotine Dependence and E-Cigarette Use Frequency, “other tobacco use” reflects past 30-day use of any of the following: cigarettes, cigars, cigarillos, little cigars, pipe tobacco, bidis, snus, dissolvable, hookah.
For combustible tobacco use, “other tobacco use” reflects past 30-day use of any of the following: chewing tobacco, snus, or dissolvables
Self-reported type of e-cigarette most often used. JUUL is a pod/cartridge device. Non pod/cartridge devices include using disposable e-cigarettes, tanks, mod systems, and “I don’t know”
Analytic Statistics
As seen in Table 2, JUUL users were 1.77 (95% CI: 1.36 – 2.31) times as likely to report symptoms of nicotine dependence compared to non-JUUL users, controlling for covariates. Similarly, JUUL users were 1.43 (95% CI: 1.02 – 2.01) times as likely to report heavy e-cigarette use compared to light e-cigarette use, relative to non-JUUL users, controlling covariates. There were no statistically significant differences in moderate versus light e-cigarette use by JUUL use status after controlling for covariates.
Table 2:
Association of JUUL Use with Nicotine Dependence and E-Cigarette Use Frequency (NYTS, 2020; n=1,713))
| Nicotine Dependencea | E-Cigarette Use Frequencyb 1 to 5 Days (Referent) |
||
|---|---|---|---|
|
| |||
| Adjusted Odds Ratio 95% Confidence Interval |
Relative Risk Ratio 95% Confidence Interval |
||
| Yes | 6 to 19 Days | 20 to 30 Days | |
| E-Cigarette Type c | |||
| Non-JUUL | 1.00 (Referent) | 1.00 (Referent) | 1.00 (Referent) |
| JUUL | 1.77 (1.36 – 2.31) *** | 1.34 (0.98 – 1.83) | 1.68** (1.13 – 2.49) |
| Sex | |||
| Males | 1.00 (Referent) | 1.00 (Referent) | 1.00 (Referent) |
| Females | 0.80 (0.60 – 1.05) | 01.01 (0.79 – 1.29) | 0.51** (0.31 – 0.83) |
| Grade Level | |||
| Middle School | 1.00 (Referent) | 1.00 (Referent) | 1.00 (Referent) |
| High School | 1.18 (0.85 – 1.61) | 1.46 (0.94 – 2.25) | 1.46 (0.83 – 2.58) |
| Race/Ethnicity | |||
| Non-Hispanic White | 1.00 (Referent) | 1.00 (Referent) | 1.00 (Referent) |
| Hispanic/Latino | 0.50 (0.38 – 0.65) *** | 0.55 (0.38 – 0.79) ** | 0.43 (0.31 – 0.60) *** |
| Non-Hispanic, Black | 0.81 (0.35 – 1.85) | 0.82 (0.40 – 1.68) | 0.57 (0.29 – 1.12) |
| Otherd | 0.80 (0.47 – 1.35) | 0.96 (0.51 – 1.80) | 0.89 (0.55 – 1.42) |
| Other Tobacco Use e | |||
| No | 1.00 (Referent) | 1.00 (Referent) | 1.00 (Referent) |
| Yes | 2.64 (2.04 – 3.41) *** | 1.86 (1.41 – 2.45) *** | 2.06 (1.52 – 2.80) *** |
| Primary Device Type f | |||
| Not Pod/Cartridge | 1.00 (Referent) | 1.00 (Referent) | 1.00 (Referent) |
| Pod/Cartridge | 0.83 (0.62 – 1.11) | 0.64 (0.47 – 0.87) ** | 0.75 (0.51 – 1.10) |
NOTE:
p<0.05
p<0.01
p<0.001
Self-Report craving tobacco or using tobacco within 30-minutes of waking up.
Self-reported days using an e-cigarette in the past 30-days.
Self-Report using JUUL in the past 30-days
“Other” is where a response was “Asian, non-Hispanic”, “American Indian/Alaska Native, non-Hispanic;” or “native Hawaiian and other Pacific Islanders, non-Hispanic”
“ther tobacco use” reflects past 30-day use of any of the following: cigarettes, cigars, cigarillos, little cigars, pipe tobacco, bidis, snus, dissolvable, hookah.
Self-reported type of e-cigarette most often used. JUUL is a pod/cartridge device. Non pod/cartridge devices include using disposable e-cigarettes, tanks, mod systems, and “I don’t know”
DISCUSSION
Among a nationally representative sample of U.S. adolescents, JUUL users had increased odds of nicotine dependence and heavy e-cigarette use compared to non-JUUL users. Descriptive findings reinforce prior study that shows adolescent e-cigarette users experience nicotine dependence5–8 and prefer JUUL devices over other e-cigarette brands.3,17–20 This study also found a comparable prevalence of nicotine dependence symptoms among adolescent JUUL users (47.9%) as a study using a nationally representative sample of 8th, 10th, and 12th grade students who used JUUL (41.3%).7 Our study reinforces research showing a relationship between JUUL and nicotine dependence among young people,5–7 extending this prior work by observing such a relationship among a nationally representative sample of adolescents from 6th through 12th grade. As such, the precautionary principle should be used to guide interventions aimed at reducing the prevalence of e-cigarette use among youth, in line with the recommendations made by the United States Surgeon General21 and the National Academy of Sciences.22
Study results have implications for public health interventions including communication campaigns. Given our findings, compounded by emerging research demonstrating a desire to quit among young JUUL users,23 strategies are needed not only to encourage cessation, but to reduce initiation of e-cigarette use. Interventions are most effective when they are multitiered and comprehensive (i.e. a multilevel interventions); incorporating home, school, and community-based approaches. The Substance Abuse and Mental Health Services Administration (SAMHSA) recently released a report on e-cigarette prevention and cessation, detailing successful strategies with an emphasis on multilevel interventions.24 E-cigarette interventions aimed at prevention for youth (e.g., CATCH My Breath)25 and cessation for young adults26 have been developed and validated. Similarly, ‘The Real Cost’, a youth tobacco prevention mass media campaign has been expanded to include e-cigarettes.27 Given the elevated risk for nicotine dependence and increased frequency of e-cigarette use among JUUL users, e-cigarette interventions should consider incorporating messages and modules specific to JUUL (and other popular high-dose nicotine pod/cartridge devices).
Findings from the study also have regulatory implications. In the United States, JUUL-pods are available in nicotine concentrations (5% nicotine; 59 mg/mL)3 on par with a pack of combustible cigarettes.4 Conversely, the maximum nicotine concentration for JUUL in the retail setting is 1.5% (18 mg/mL) in the European Union and the United Kingdom;28 higher doses are available through prescription.28 As a method of reducing nicotine exposure during adolescence, particularly from high-dose devices like JUUL, the US should consider enacting similar safeguards against the sale of high-dose nicotine devices. Additionally, state and local action can and should be taken to restrict access to e-cigarettes among those under 21 years of age as retail access is an important contributor to heavy e-cigarette use among adolescents.29 Thus, greater enforcement of age restriction laws may be an effective regulatory approach for local governments.
This study also notes that 33.5% of JUUL users selected non-pod/cartridge devices as their primary e-cigarette device indicating that adolescent e-cigarette users are not only using one brand or device type exclusively, but may be doing so for different reasons. Additionally, high nicotine concentration and concealability are commonly cited reasons for using JUUL while high cost of JUUL is a reason for using other devices.19,20 In essence, disposable e-cigarettes users may supplement with JUUL to satisfy nicotine cravings while users of mod/tank devices may use JUUL in places where concealability is a necessity (e.g., at school). While the finding that JUUL users also use other e-cigarettes has been found previously, among adults,30 more study is needed on the diversity of products used by adolescent e-cigarette users.
This study has limitations. First, this study is subject to recall and response bias as data are self-reported. Second, this study could not control for a number of e-cigarette brands used which may be a confounder for the study outcomes. As the question used to calculate number of brands used was also used to categorize users as JUUL and non-JUUL users (i.e., not independent of each other), our statistical models could not control for number of brands selected. Models included ‘primary device type’ as a covariate to control for use of JUUL as a supplement to other e-cigarette use, but research is still needed to explore number of devices used as a potential mediator or confounder for nicotine dependence and e-cigarette use frequency. Third, this study did not account for nicotine concentration in e-cigarette devices. Some studies suggest a sizable proportion of adolescent e-cigarette users report using 0% nicotine e-liquid,31 and non-nicotine e-cigarette use is associated with lower use frequency.32 However, studies show less knowledge of e-cigarettes and nicotine content among youth who report using non-nicotine devices.33,34 Research tailored to examine the complexities of e-cigarette device types, brand preferences, and product label policy (nicotine content) is needed.
This study adds to the scant research on e-cigarette brands like JUUL and their social and behavioral effects like nicotine dependence and e-cigarette use frequency among a nationally representative sample of adolescents in the United States. Study results inform e-cigarette prevention efforts and tobacco regulatory policy; however, further investigation that includes longitudinal research is crucial to examine the temporal relationship between JUUL use and nicotine dependence.
Highlights.
Nearly half (49.5%) of adolescent e-cigarette users reported using JUUL.
JUUL users had nearly doubled (aOR: 1.77) odds of nicotine dependence
JUUL users had 1.43 times greater odds of using an e-cigarette on 20–30 days per month
Role of funding sources
Research reported in this presentation was supported by grant number [1 R01 CA242171-01] from the National Institutes of Health (NIH). Additional funding was provided via the University of Texas Health Science Center at Houston School of Public Health Cancer Education and Career Development Program – National Cancer Institute/NIH Grant – National Cancer Institute/NIH Grant T32/CA057712. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Cancer Institute or the National Institutes of Health.
Footnotes
Conflict of Interest
SHK is a consultant in litigation against the vaping industry. This does not alter our adherence to Drug and Alcohol Dependence’s policies on sharing data and materials.
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