Abstract
Introduction
Identifying predictors of electronic nicotine product (ENP) cessation can inform ENP cessation interventions. High rates of cooccurring ENP and cigarette (dual) use and transitions between these products underscore the importance of considering cigarette smoking status when assessing and addressing ENP cessation.
Aims and Methods
We analyzed waves 3 (W3) and 4 (W4) of the Population Assessment of Tobacco and Health (PATH) study to identify (1) W3 socio-demographics, tobacco and ENP use characteristics, and psychosocial correlates of W3 cigarette smoking status (non-smoker, former, and current) among W3 adult ENP users, and (2) W3 predictors of W4 combined ENP and cigarette smoking abstinence relative to use of one or both products.
Results
At W3, 65.6% of ENP users concurrently smoked cigarettes. Adjusted multinomial regression results indicated that different W3 socio-demographics, tobacco and ENP use characteristics, and psychosocial correlates were significantly associated with distinct W3 cigarette use profiles. At W4, 9.9% of individuals were abstinent from both products. These individuals were less likely to: (1) be current smokers (vs. non-smokers) or be advised to quit using tobacco, compared with cigarette only or dual users, and (2) use ENPs daily or live in a household allowing ENP use, compared with ENP only or dual users (p < .05).
Conclusions
ENP cessation approaches need to be tailored to the distinct cigarette use profiles of ENP users. Dual users and daily ENP users may require more intensive interventions to achieve the cessation of both products. Supportive physical environments, such as home vape-free policies, may facilitate ENP cessation.
Implications
This analysis contributes to advancing the nascent literature on predictors of electronic nicotine product (ENP) cessation, which can guide the development of ENP cessation interventions by indicating which populations, psychosocial and environmental constructs, and cooccurring behaviors interventions should target. This research also highlights the importance of considering cigarette smoking status when designing ENP cessation interventions and defining intervention outcomes.
Introduction
The use of electronic nicotine products (ENPs) has emerged as a major public health problem in the United States. ENPs are the second most commonly used tobacco product among U.S. adults, with an estimated 10.9 million current users.1 Particularly concerning is the dramatic increase in the use of these products in young adults. For instance, among young adults, the prevalence of current (every day or someday) ENP use increased from 2.4% in 20142 to 9.3% in 2019.1 Although ENPs are considered less harmful than traditional cigarettes3,4 and may be effective in supporting cessation efforts,5,6 there is much unknown about their long-term health effects.7–9 Additionally, recent reports of health complications from COVID-19 among youth and young adult ENP users10 and evidence linking ENP use to initiation of cigarette smoking11 demonstrate the potential harms of these products. As a result, medical and public health experts have called for urgent action to curb the ENP epidemic.12
Addressing both ENP prevention and cessation is critical; however, relatively few efforts have focused on ENP cessation. Identifying factors associated with quitting ENPs can inform ENP cessation approaches by indicating which populations are most in need of help and which intervention targets might optimize intervention outcomes. Social Cognitive Theory (SCT) is a widely used framework for informing health behavior change interventions, including smoking cessation interventions, and thus may have utility in informing ENP cessation interventions. According to SCT, such interventions must take into account individual factors (eg, socio-demographics), psychosocial constructs (eg, social influences, risk perception, motivation), and cooccurring risk behaviors, among other factors.13
A primary consideration for ENP cessation is the co-use of other tobacco products, particularly cigarettes. Over 50% of ENP users are estimated to also smoke cigarettes (also referred to as dual users),14 and a number of analyses using PATH data15 have shown that transitions between ENPs and cigarettes are common.16–18 For instance, two studies found that approximately 12% of exclusive ENP users at wave (W) 1 transitioned to exclusive cigarette smoking at W2.16,17 Additionally, these studies as well as another study found that, among dual users at W1, a substantial proportion quit using ENPs but became exclusive cigarette smokers at W216,17 or W3.18 Thus, failing to consider cigarette smoking status when assessing ENP cessation can misleadingly indicate a positive outcome (quitting ENPs) when it may in fact represent a harmful state (smoking cigarettes).
The above studies also indicate that several tobacco and ENP use characteristics are associated with ENP cessation. One analysis of ENP users (exclusive and dual users) found that being a long-term former smoker (vs. never smoker), using ENPs daily, and using other combustible products at W1 were associated with a lower likelihood of discontinuing ENPs at W2.16 Another study among dual users found that younger age of first exposure to tobacco products and greater nicotine dependence at W1 were associated with a reduced risk of quitting both products (vs. remaining dual users) at W3.18 Thus, ENP cessation intervention research must address the broader context of tobacco use behaviors in driving intervention messages and in defining intervention outcomes.
With regard to socio-demographic characteristics, higher education has been shown to correlate with a higher likelihood of ENP cessation.19 Psychosocial characteristics associated with the likelihood of quitting ENPs include reasons for using ENPs. One study found that those who used ENPs for non-goal oriented reasons such as curiosity were more likely to quit than those who used it for goal oriented reasons such as quitting smoking.19 However, reasons for discontinuing ENPs vary based on smoking status, further underscoring the need to address cigarette smoking when developing ENP cessation interventions.20–24 Never or non-smokers most commonly cite health concerns and cost for discontinuing ENPs.20,21 Former smokers commonly cite health concerns and not needing ENPs to stay quit as the main reasons for discontinuation.20–22,24 For dual users, the primary reason for quitting ENPs is because they are perceived to be less satisfying than cigarettes.20–22,24
As cigarette smoking status plays a prominent role in ENP cessation, understanding how distinct cigarette use groups differ in terms of socio-demographics, tobacco and ENP use, and psychosocial characteristics can inform tailored ENP cessation approaches. Additionally, given the limited research on ENP cessation, and transitions between ENP and cigarette use, further research, particularly longitudinal research, is needed to identify a range of factors predicting combined ENP and cigarette smoking abstinence that might indicate promising targets for ENP cessation interventions. To date, a handful of studies have examined factors associated with ENP cessation,16,18,19 but several gaps remain. Two of these studies included cigarette smoking as a covariate and not as part of the outcome measure16,19 and only one study examined predictors of transitions to complete tobacco/nicotine product cessation.18 These studies have also largely focused on socio-demographics and tobacco use characteristics and there is limited research on the association between psychosocial and environmental characteristics, and ENP cessation in a nationally representative sample. Finally, while two of these studies analyzed data from earlier waves of the PATH study (W1–W216 and W1–W318), the landscape of ENPs underwent significant changes around this period. W2 data collection ended and W3 data collection began in 2015, just as novel fourth-generation ENPs such as JUUL entered the market.25 Therefore, cigarette use patterns among ENP users and predictors of ENP cessation could have changed. Additionally, there were changes to the PATH study methodology across W1, W2, and later waves. For instance, in W1 and W2, some questions such as plans to quit ENPs were asked only to dual and poly users of tobacco who also used ENPs. However, in W3 and W4, these questions were asked to all current established ENP users. Similarly, W1 and W2 did not specifically assess household rules about using ENPs, but subsequent waves did. Thus, the current analysis builds on previous analyses of PATH data16,18 and leverages the most recent waves (W3 and W4) to: (1) identify W3 socio-demographics, tobacco and ENP use characteristics, and psychosocial correlates of distinct W3 cigarette use profiles (ie, current, former, and non-smokers) among W3 ENP users, and (2) identify W3 predictors of combined ENP and cigarette smoking abstinence relative to use of one or both products at W4 among W3 ENP users.
Methods
Data Source
PATH is a nationally representative longitudinal cohort study of tobacco use in the U.S. civilian, non-institutionalized population. Details of the design and methodology of the PATH study have been published elsewhere.15 Briefly, the PATH survey used a four-stage stratified area probability sampling design whereby smaller geographic segments were sampled from a stratified sample of geographical primary sampling units (PSUs). Within each geographic segment, residential addresses were sampled and adults were included from households corresponding to the selected residential addresses. Sampling rates varied by age, race, and tobacco-use status. W3 data was collected between October 2015 and 2016 and W4 data was collected between December 2016 and January 2018.
Sample
The analytic sample for aim 1 included current established ENP users at W3 with complete data on all W3 variables. The PATH study defines (1) ENPs to include e-cigarettes, vape pens, personal vaporizers and mods, e-cigars, e-pipes, e-hookahs and hookah pens, and (2) current established ENP users as those who have ever used ENPs fairly regularly and currently use them every day or some days. The W3 sample consisted of 28 148 adults, of whom 26 316 were not current established ENP users and 61 were missing data on one or more variables used to define current established ENP use. Of the 1771 ENP users, 32 were missing data on one or more variables used to define cigarette smoking status and 203 were missing data on one or more W3 covariates, resulting in a sample size of 1536.
An additional criterion for the aim 2 analytic sample was non-missing W4 ENP and cigarette use status. Of the 1536 adults in the aim 1 sample, 228 were missing data on W4 ENP and or cigarette use, resulting in a sample size of 1308 for aim 2. This analysis was determined to be non-human subjects research by the George Washington University IRB.
Measures
Aim 1 Outcome: W3 cigarette smoking status among W3 ENP users. This was treated as a three-level categorical variable: (1) current smokers (ie, those who reported smoking at least one cigarette in the past 30 days), (2) former smokers (ie, those who reported no smoking in the past 30 days but smoking 100 cigarettes or more in their lifetime), and (3) non-smokers (ie, those reporting no smoking in the past 30 days and smoking less than 100 cigarettes in their lifetime). The 100-cigarette lifetime threshold was used to discriminate between former established and casual smokers26 and has been used in previous analyses of PATH data16,17 as well as large national surveys such as the National Health Interview Survey.27
Aim 2 Outcome: W4 combined ENP and cigarette use status among W3 ENP users. The dependent variable for Aim 2 was categorized as none (ie, abstinent from both ENPs and cigarettes), use of ENPs only, use of cigarettes only, and use of both products within the past 30 days.
Independent Variables at W3
Socio-demographics: included age (18–24, 25–44, and 45 years or older), gender (male/female), race-ethnicity (non-Hispanic White and other), household income (<$10 000, $10 000–49 999, and $50 000 or more), education (less than high school, completed GED or high school and completed some college or higher), employment (don’t currently work, work part-time and work full time), and marital status (never married, married, widowed/divorced/separated).
Other tobacco products and substance use: were operationalized as past 30-day use (yes/no) of combustible and non-combustible tobacco products (cigars, cigarillos, pipes, hookah, smokeless tobacco, snus) and marijuana. Combustible and non-combustible tobacco products were combined owing to small sample sizes for the latter.
ENP use characteristics: included frequency of use (daily vs. non-daily) and whether the device was rechargeable (yes vs. no/don’t know).
Psychosocial and physical factors: psychosocial factors included (1) home rules about using ENPs (not allowed, allowed in some places or at some times, and not allowed anywhere or anytime), (2) whether important referents used ENPs (yes vs. no/unsure), (3) perceived harm of using ENPs to health, which was measured on a five-point Likert scale, with response options ranging from not at all harmful to extremely harmful and higher scores indicative of greater perceived harm, (4) readiness to quit using ENPs, defined as planning to quit using ENPs within the next six months (yes/no), and (5) receipt of advice to quit using tobacco from a healthcare provider (yes/no). Physical factors included the presence of respiratory difficulties, that is wheezing and/or dry cough in the past 12 months (yes/no).
Data Analysis
We first examined bivariate associations between the independent variables and both dependent variables (W3 cigarette smoking status and W4 dual product use status) using chi-square tests for categorical variables and Student’s t-test for continuous variables. We also examined bivariate associations among independent variables to assess correlations between predictors and determine which predictors to include in the regression models. Because of high correlations, we chose to omit marital status (correlated with age), employment, and education (correlated with income) in the regression models. The variable indicating whether important referents used ENPs was also excluded from the regression models, as it was not significantly associated with either of the dependent variables at the bivariate level. To identify W3 correlates of W3 cigarette smoking status, we conducted a multinomial logistic regression analysis to estimate adjusted relative risk ratios for all combinations of smoking status (non-smoker vs. former smoker, current smoker vs. former smoker, current smoker vs. non-smoker). Similarly, to identify W3 predictors of W4 combined ENP and cigarette smoking abstinence, we used multinomial logistic regression to estimate adjusted relative risk ratios comparing those abstinent from both products to those using ENPs only, cigarettes only, and both products. Due to the complex survey design, analyses of PATH data require the use of sample weights to account for differential probabilities of selection, non-response rates, and deficiencies in the sampling frame, and replicate weights to correctly calculate standard errors of statistics. W3 single wave weights were used for cross-sectional W3 analyses (aim 1) and W4 all wave weights were used for longitudinal (aim 2) analyses. All analyses used the balanced repeated replications method for variance estimation with Fay’s adjustment of 0.3. For descriptive analyses, weighted percentages and logit transformed confidence intervals were calculated. A p-value of .05 was considered statistically significant. No adjustments were made for multiple comparisons. All analyses were conducted using Stata version 14.
Results
Characteristics of the aim 1 sample are presented in Table 1. Among this sample of 1536 ENP users at W3, the majority was male (56.1%), non-Hispanic White (76.8%), had completed some college or more (56.6%), and worked full time (50.9%). A sizeable proportion was between the ages of 25–44 years (45.4%), had a household income between $10 000 and $49 999 (49.7%), and was never married (42.6%). At W3, 6.8% of ENP users were non-smokers, 27.6% were former smokers, and 65.6% were current smokers (dual users). The majority did not use other combustible or non-combustible tobacco products (70.1%) or marijuana (73.5%). A slight majority (52%) were non-daily users of ENPs, and most (89.7%) used rechargeable devices.
Table 1.
Weighted Sample Characteristics of ENP Users by Cigarette Smoking Status, PATH Study Wave 3: 2015–2016
| W3 cigarette smoking status | |||||
|---|---|---|---|---|---|
| Variable | Total (unweighted N = 1536) | Non-smoker (unweighted N = 128) | Former smoker (unweighted N = 370) | Current smoker (unweighted N = 1038) | |
| Weighted % (95% CI) | Weighted % (95% CI) | Weighted % (95% CI) | Weighted % (95% CI) | p | |
| 6.8 (5.5, 8.4) | 27.6 (25.1, 30.3) | 65.6 (62.8, 68.3) | |||
| Socio-demographic factors | |||||
| Age | |||||
| 18–24 years | 23.8 (21.5, 26.3) | 72.6 (59.8 82.6) | 10.6 (8.0, 13.9) | 24.3 (21.7, 27.1) | |
| 25–44 years | 45.4 (42.6, 48.3) | 17.7 (10.1, 29.0) | 46.9 (40.7, 53.1) | 47.7 (44.2, 51.2) | |
| 45 years or older | 30.8 (28.1, 33.6) | 9.7 (3.8, 22.6) | 42.5 (36.2, 49.0) | 28.0 (25.1, 31.2) | <.0001 |
| Male | 56.1 (53.1, 59.1) | 56.2 (45.1, 66.6) | 57.2 (50.7, 63.5) | 55.6 (52.5, 58.7) | .8872 |
| Non-Hispanic White | 76.8 (74.3, 79.1) | 55.3 (44.7, 65.5) | 82.8 (77.9, 86.7) | 76.5 (73.5, 79.2) | <.0001 |
| Household income | |||||
| <$10 000 | 15.0 (13.3, 16.8) | 21.8 (13.8, 32.6) | 6.7 (4.5, 9.8) | 17.8 (15.6, 20.3) | |
| $10 000–49 999 | 49.7 (46.9, 52.5) | 45.4 (35.1, 56.1) | 46.3 (40.5, 52.2) | 51.5 (48.1, 54.9) | |
| $50 000+ | 35.3 (32.6, 38.2) | 32.8 (23.6, 43.6) | 47.0 (41.5, 52.7) | 30.7 (27.3, 34.3) | <.0001 |
| Education | |||||
| Less than high school | 10.3 (8.8, 12.1) | 10.1 (5.5, 17.8) | 8.6 (6.1, 12.0) | 11.1 (9.2, 13.4) | |
| GED or high school | 33.1 (30.3, 36.0) | 36.2 (26.1, 47.8) | 30.1 (25.1, 35.8) | 34.0 (30.4, 37.9) | |
| Some college or more | 56.6 (53.5, 59.6) | 53.7 (42.8, 64.2) | 61.3 (55.7, 66.5) | 54.9 (51.0, 58.7) | .3353 |
| Employment | |||||
| Don’t work | 30.7 (27.9, 33.6) | 21.7 (14.6, 31.0) | 29.6 (25.0, 34.6) | 32.1 (28.8, 35.5) | |
| Work part time | 18.4 (16.4, 20.6) | 34.7 (26.1, 44.4) | 12.9 (9.5, 17.3) | 19.1 (16.78 21.7) | |
| Work full time | 50.9 (48.0, 53.8) | 43.7 (33.8, 54.0) | 57.5 (52.0, 62.8) | 48.8 (45.3, 52.4) | <.0001 |
| Marital status | |||||
| Never married | 42.6 (39.7, 45.7) | 76.9 (66.1, 85.1) | 29.8 (24.0, 36.4) | 44.4 (41.2, 47.7) | |
| Married | 35.4 (32.6, 38.3) | 17.1 (10.6, 26.5) | 49.2 (42.6, 55.8) | 31.6 (28.4, 35.0) | |
| Widowed/divorced/separated | 22.0 (19.5, 24.6) | 6.0 (1.7, 18.6) | 21.0 (16.6, 26.2) | 24.0 (21.0, 27.3) | <.0001 |
| Tobacco and substance use characteristics | |||||
| Use other tobacco products | 29.9 (27.4, 32.6) | 37.3 (29.1, 46.4) | 13.1 (9.6, 17.7) | 36.2 (33.3, 39.2) | <.0001 |
| Use marijuana | 26.5 (23.9, 29.3) | 32.7 (23.5, 43.5) | 16.9 (12.8, 22.0) | 29.9 (26.8, 33.1) | .0001 |
| ENP use characteristics | |||||
| Use ENPs daily | 48.0 (44.8, 51.3) | 23.9 (16.2, 34.0) | 78.8 (73.3, 83.3) | 37.5 (33.8, 41.4) | <.0001 |
| ENP is rechargeable | 89.7 (87.6, 91.4) | 84.6 (75.2, 90.9) | 94.9 (91.6, 97.0) | 87.9 (85.3, 90.2) | .0011 |
| Psychosocial and physical factors | |||||
| ENP home rules | |||||
| Not allowed | 28.3 (25.5, 31.2) | 48.8 (37.6, 60.1) | 22.4 (18.1, 27.4) | 28.6 (25.3, 32.2) | |
| Partially allowed | 24.3 (21.6, 27.2) | 25.6 (17.2, 36.3) | 23.7 (18.9, 29.3) | 24.5 (21.3, 27.9) | |
| Fully allowed | 47.4 (44.6, 50.3) | 25.6 (17.9, 35.2) | 53.9 (48.1, 59.7) | 47.0 (43.8, 50.2) | <.0001 |
| Important others use ENPs | 47.8 (44.6, 50.9) | 44.1 (33.6, 55.2) | 52.1 (45.8, 58.3) | 46.3 (42.4, 50.2) | .2258 |
| Perceived harm of ENPs, M (95% CI) | 2.55 (2.50, 2.60) | 2.43 (2.18, 2.68) | 2.40 (2.31, 2.49) | 2.63 (2.57, 2.68) | .0002 |
| Readiness to quit ENPs | 17.6 (15.4, 20.1) | 21.5 (13.8, 31.9) | 11.3 (8.6, 14.8) | 19.9 (17.1, 23.0) | .0010 |
| Advised to quit tobacco | 28.5 (26.0, 31.1) | 5.6 (3.1, 9.8) | 15.5 (12.1, 19.7) | 36.3 (32.9, 39.8) | <.0001 |
| Respiratory symptoms in last 12 months | 41.5 (38.4, 44.6) | 29.6 (19.9, 41.7) | 30.4 (24.1, 37.6) | 47.3 (44.0, 50.7) | <.0001 |
Bold values indicate p < .05.
W3 Smoking Status Among W3 ENP Users
Table 1 also provides bivariate analyses results regarding W3 correlates of smoking status (ie, non-smoker, former, current) among W3 ENP users.
In the adjusted multivariable multinomial logistic regression model examining correlates of W3 smoking status among W3 ENP users (Table 2), compared with former smokers, current smokers were more likely to be younger, use other tobacco products (aRRR = 2.46), use marijuana (aRRR = 1.47), received advice to quit using tobacco (aRRR = 3.24), and experienced respiratory symptoms in the last 12 months (aRRR = 1.76); however, current smokers were less likely than former smokers to have a household income ≥$10 000, use ENPs daily (vs. non-daily; aRRR = 0.22), and use a rechargeable ENP (aRRR = 0.47).
Table 2.
Adjusted Multinomial Logistic Regression Results of Cigarette Use Profiles for ENP Users, PATH Study Wave 3: 2015–2016 (Unweighted N = 1536)
| Variable | Current smoker vs. former smoker | Current smoker vs. non-smoker | Non-smoker vs. former smoker | |||
|---|---|---|---|---|---|---|
| aRRR (95% CI) | p | aRRR (95% CI) | p | aRRR (95% CI) | p | |
| Socio-demographic factors | ||||||
| Age (vs. ≥45 years) | Ref | Ref | Ref | |||
| 25–44 years | 1.70 (1.13, 2.56) | .011 | 1.24 (0.36, 4.20) | .732 | 1.38 (0.38, 4.96) | .621 |
| 18–24 years | 3.18 (1.93, 5.24) | <.0001 |
0.14 (0.04, 0.48) |
.002 | 22.21 (5.99, 82.40) | <.0001 |
| Male (vs. female) | 0.89 (0.64, 1.24) | .481 | 1.68 (0.99, 2.86) | .054 | 0.53 (0.29, 0.97) | .039 |
| Non-Hispanic White (vs. other) | 0.89 (0.58, 1.35) | .567 | 2.31 (1.37, 3.90) | .002 | 0.38 (0.19, 0.77) | .008 |
| Household income (vs. <$10 000) | Ref | Ref | Ref | |||
| $10 000–49 999 | 0.48 (0.29, 0.80) | .005 | 1.12 (0.52, 2.41) | .769 | 0.43 (0.17, 1.10) | .078 |
| $50 000+ | 0.34 (0.20, 0.58) | <.0001 | 0.68 (0.30, 1.57) | .366 | 0.50 (0.19, 1.29) | .147 |
| Tobacco and substance use characteristics | ||||||
| Use other tobacco products | 2.46 (1.55, 3.90) | <.0001 | 1.70 (1.05, 2.75) | .032 | 1.45 (0.80, 2.61) | .214 |
| Use marijuana | 1.47 (1.00, 2.17) | .05 | 1.24 (0.71, 2.17) | .441 | 1.19 (0.61, 2.31) | .612 |
| ENP use characteristics | ||||||
| Daily (vs. nondaily user) | 0.22 (0.15, 0.31) | <.0001 | 1.90 (1.02, 3.53) | .044 | 0.11 (0.06, 0.22) | <.0001 |
| Rechargeable device | 0.47 (0.26, 0.86) | .015 | 1.23 (0.51, 2.97) | .646 | 0.38 (0.14, 1.07) | .067 |
| Psychosocial and physical factors | ||||||
| ENP home rules (vs. not allowed) | Ref | Ref | Ref | |||
| Partially allowed | 0.97 (0.62, 1.52) | .893 | 1.21 (0.60, 2.45) | .593 | 0.80 (0.36, 1.77) | .579 |
| Fully allowed | 1.07 (0.70, 1.62) | .753 | 2.01 (1.06, 3.80) | .033 | 0.53 (0.25, 1.12) | .097 |
| Perceived harm of ENPs | 1.02 (0.88, 1.18) | .834 | 1.43 (1.01, 2.02) | .044 | 0.71 (0.50, 1.02) | .064 |
| Readiness to quit ENPs | 1.35 (0.90, 2.02) | .147 | 0.91 (0.46, 1.80) | .780 | 1.49 (0.69, 3.20) | .308 |
| Advised to quit tobacco | 3.24 (2.19, 4.80) | <.0001 | 6.23 (3.00, 12.92) | <.0001 | 0.52 (0.23, 1.17) | .113 |
| Respiratory symptoms in last 12 months | 1.76 (1.19, 2.60) | .005 | 1.21 (0.67, 2.19) | .516 | 1.45 (0.70, 3.02) | .318 |
Bold values indicate p < .05.
Compared with non-smokers, current smokers were more likely to be non-Hispanic White (vs. other; aRRR = 2.31), use other tobacco products (aRRR = 1.70), use ENPs daily (vs. non-daily; aRRR = 1.90), live in a home where ENP use was fully allowed (vs. not allowed; aRRR = 2.01), perceive ENPs to be more harmful (aRRR = 1.43), and received advice to quit using tobacco (aRRR = 6.23), but less likely to be between 18 and 24 years (vs. 45 years or older; aRRR = 0.14).
Finally, relative to former smokers, non-smokers were more likely to be between 18 and 24 years (vs. 45 years or older; aRRR = 22.21) but less likely to be male (vs. female; aRRR = 0.53), non-Hispanic White (vs. other; aRRR = 0.38), and use ENPs daily (vs. non-daily; aRRR = 0.11).
W4 Combined ENP and Cigarette Smoking Abstinence Among W3 ENP Users
Characteristics of the W4 sample were largely similar to that of the W3 sample (Table 3). Comparisons of characteristics of W3 and W4 participants indicated that those lost to follow-up at W4 were significantly younger, more likely to live in a home where ENP use was not allowed at all, and less likely to be interested in quitting ENPs (results not shown). Table 3 provides bivariate analyses results regarding W3 correlates of W4 combined ENP and cigarette use status (ie, none, ENPs only, cigarettes only, both) among W3 ENP users.
Table 3.
Weighted Sample Characteristics of Wave 3 ENP Users by Wave 4 Combined ENP and Cigarette Use Status, PATH Study Waves 3 and 4: 2015–2018
| W4 combined ENP and cigarette use status | ||||||
|---|---|---|---|---|---|---|
| Variable | Total (unweighted N = 1308) | None (unweighted N = 136) | ENPs only (unweighted N = 333) | Cigarettes only (unweighted N = 400) | Both (unweighted N = 439) | |
| Weighted % (95% CI) | Weighted % (95% CI) | Weighted % (95% CI) | Weighted % (95% CI) | Weighted % (95% CI) | p | |
| 9.9 (7.9, 12.5) | 27.7 (25.0, 30.5) | 30.0 (27.0, 33.1) | 32.4 (29.4, 35.6) | |||
| Socio-demographic factors | ||||||
| Age | ||||||
| 18–24 years | 23.0 (20.5, 25.6) | 29.0 (21.1, 38.5) | 19.8 (16.0, 24.4) | 24.5 (20.0, 29.6) | 22.4 (18.8, 26.4) | |
| 25–44 years | 47.0 (43.7, 50.3) | 43.9 (34.3, 54.1) | 43.9 (37.3, 50.6) | 50.2 (43.8, 56.6) | 47.6 (41.8, 53.5) | |
| 45 years or older | 30.0 (27.2, 33.1) | 27.0 (17.9, 38.7) | 36.3 (30.1, 43.0) | 25.3 (20.6, 30.7) | 30.0 (25.2, 35.3) | .1250 |
| Male | 56.1 (52.8, 59.3) | 48.9 (36.9, 61.1) | 60.8 (54.0, 67.1) | 57.2 (51.9, 62.4) | 53.2 (48.1, 58.2) | .1690 |
| Non-Hispanic White | 77.3 (74.6, 79.7) | 68.5 (58.3, 77.2) | 83.0 (78.5, 86.7) | 74.6 (69.8, 78.9) | 77.5 (72.3, 81.9) | .0121 |
| Household income | ||||||
| <$10 000 | 15.3 (13.3, 17.6) | 16.3 (10.7, 24.1) | 9.0 (6.2, 12.7) | 21.2 (17.3, 25.6) | 15.0 (11.8, 18.9) | |
| $10 000–49 999 | 50.2 (47.1, 53.4) | 50.2 (40.2, 60.1) | 48.1 (41.7, 54.6) | 55.7 (50.7, 60.5) | 47.0 (41.7, 52.4) | |
| $50 000+ | 34.5 (31.2, 37.9) | 33.5 (24.8, 43.5) | 42.9 (36.3, 49.7) | 23.1 (18.6, 28.4) | 38.0 (32.8, 43.5) | <.0001 |
| Education | ||||||
| Less than high school | 10.0 (8.3, 12.0) | 6.6 (3.0, 13.9) | 7.6 (4.9, 11.5) | 11.9 (8.9, 15.8) | 11.4 (8.3, 15.4) | |
| GED or high school | 33.0 (30.0, 36.2) | 31.4 (21.9, 42.9) | 30.5 (24.2, 37.7) | 34.8 (29.7, 40.3) | 33.9 (28.4, 40.0) | |
| Some college or more | 57.0 (53.9, 60.0) | 62.0 (51.9, 71.2) | 61.9 (54.8, 68.6) | 53.3 (47.6, 58.9) | 54.7 (49.1, 60.2) | .3228 |
| Employment | ||||||
| Don't work | 30.9 (28.0, 34.0) | 29.4 (21.5, 38.8) | 26.5 (21.2, 32.7) | 34.8 (29.2, 40.7) | 31.5 (27.0, 36.4) | |
| Work part time | 19.1 (16.6, 21.9) | 19.9 (12.7, 29.7) | 18.7 (14.2, 24.1) | 17.0 (13.3, 21.4) | 21.3 (17.0, 26.4) | |
| Work full time | 50.0 (46.5, 53.4) | 50.7 (41.2, 60.1) | 54.8 (47.8, 61.6) | 48.3 (42.6, 54.1) | 47.2 (42.7, 51.7) | .3229 |
| Marital status | ||||||
| Never married | 42.7 (39.5, 46.0) | 44.3 (35.1, 53.9) | 38.5 (32.6, 44.8) | 43.9 (39.1, 48.8) | 44.8 (39.6, 50.1) | |
| Married | 35.2 (32.3, 38.2) | 34.5 (26.1, 44.1) | 41.7 (35.8, 47.8) | 34.4 (29.3, 39.8) | 30.6 (26.3, 35.3) | |
| Widowed/divorced/separated | 22.1 (19.5, 24.9) | 21.2 (13.0, 32.6) | 19.8 (15.2, 25.4) | 21.8 (17.6, 26.6) | 24.6 (20.5, 29.2) | .1908 |
| Tobacco and substance use characteristics | ||||||
| Smoking status | ||||||
| Non-smoker | 6.7 (5.3, 8.4) | 19.6 (13.1, 28.4) | 11.2 (8.0, 15.5) | 1.9 (1.1, 3.5) | 3.2 (1.9, 5.3) | |
| Former smoker | 28.3 (25.7, 31.0) | 44.3 (33.4, 55.8) | 64.0 (58.0, 69.6) | 5.5 (3.4, 8.8) | 13.9 (10.3, 18.4) | |
| Current smoker | 65.1 (62.2, 67.8) | 36.1 (26.8, 46.6) | 24.8 (19.9, 30.4) | 92.6 (89.4, 94.8) | 83.0 (78.5, 86.7) | <.0001 |
| Use other tobacco products | 29.4 (26.6, 32.3) | 29.3 (21.4, 38.7) | 17.7 (12.9, 23.9) | 35.8 (31.0, 41.1) | 33.5 (29.1, 38.2) | <.0001 |
| Use marijuana | 26.2 (23.3, 29.3) | 25.8 (17.0, 37.1) | 17.7 (13.5, 22.8) | 30.1 (25.1, 35.6) | 30.0 (24.9, 35.6) | .0040 |
| ENP use characteristics | ||||||
| Use ENPs daily | 48.8 (45.4, 52.2) | 29.5 (21.3, 39.2) | 76.7 (70.8, 81.7) | 25.5 (20.3, 31.5) | 52.5 (46.9, 58.0) | <.0001 |
| ENP is rechargeable | 90.0 (87.7, 91.9) | 85.1 (76.6, 90.9) | 94.4 (90.9, 96.6) | 85.2 (80.8, 88.7) | 92.1 (87.9, 95.0) | .0008 |
| Psychosocial and physical factors | ||||||
| ENP home rules | ||||||
| Not allowed | 27.3 (24.4, 30.4) | 47.2 (37.3, 57.3) | 19.2 (15.1, 24.1) | 31.5 (25.8, 37.8) | 24.2 (19.4, 29.7) | |
| Partially allowed | 24.6 (21.8, 27.7) | 20.4 (13.3, 30.1) | 24.6 (20.3, 29.6) | 28.1 (22.8, 34.0) | 22.7 (19.0, 27.0) | |
| Fully allowed | 48.1 (45.0, 51.2) | 32.4 (22.7, 43.8) | 56.2 (49.7, 62.4) | 40.4 (34.9, 46.2) | 53.1 (48.4, 57.7) | <.0001 |
| Important others use ENPs | 48.4 (44.8, 51.9) | 44.7 (33.4, 56.5) | 50.0 (43.8, 56.2) | 43.8 (38.0, 49.8) | 52.3 (46.6, 57.9) | .1926 |
| Perceived harm of ENPs, M (95% CI) | 2.54 (2.48, 2.60) | 2.57 (2.37, 2.78) | 2.32 (2.20, 2.44) | 2.82 (2.70, 2.94) | 2.48 (2.36, 2.59) | <.0001 |
| Readiness to quit ENPs | 16.1 (14.0, 18.5) | 22.6 (15.9, 31.1) | 9.2 (6.3, 13.1) | 23.6 (18.9, 29.2) | 13.1 (10.2, 16.8) | <.0001 |
| Advised to quit tobacco | 28.4 (25.7, 31.3) | 12.9 (7.4, 21.4) | 15.1 (11.2, 20.0) | 39.6 (34.5, 44.9) | 34.2 (29.2, 39.5) | <.0001 |
| Respiratory symptoms in last 12 months | 41.3 (38.0, 44.6) | 35.0 (24.9, 46.6) | 31.7 (25.4, 38.8) | 49.4 (44.6, 54.3) | 43.8 (38.8, 48.8) | .0003 |
Bold values indicate p < .05.
A greater proportion of W3 non-smokers were more likely to be abstinent from both products at W4 (29.3%) than W3 former (15.6%) and current (5.5%) smokers. In adjusted multivariable analyses of W4 combined ENP and cigarette smoking abstinence (Table 4), compared with those abstinent from both products: those using ENPs only were more likely to have used ENPs daily (vs. nondaily; aRRR = 5.81) and lived in a home where the use of ENPs was partially or fully allowed at W3. Compared with those abstinent from both products, those using cigarettes only were more likely to have been current smokers (vs. non-smokers; aRRR = 16.77) and been advised to quit using tobacco (aRRR = 2.83) at W3. Finally, compared with those abstinent from both products, those using both products were also more likely to have been current smokers (vs. non-smokers; aRRR = 8.15), used ENPs daily (vs. non-daily; aRRR = 3.30), lived in a home were ENP use was fully allowed (vs. not allowed; aRRR = 2.16), and been advised to quit using tobacco (aRRR = 2.52), but were less likely to have been ready to quit using ENPs (aRRR = 0.53) at W3.
Table 4.
Adjusted Multinomial Logistic Regression Results of Wave 4 Combined ENP and Cigarette Smoking Abstinence for Wave 3 ENP Users, PATH Study Waves 3 and 4: 2015–2018 (Unweighted N = 1308)
| Variable | ENPs only vs. none | Cigarettes only vs. none | Both vs. none | |||
|---|---|---|---|---|---|---|
| aRRR (95% CI) | p | aRRR (95% CI) | p | aRRR (95% CI) | p | |
| Socio-demographic factors | ||||||
| Age (vs. ≥45 years) | Ref | Ref | Ref | |||
| 25–44 years | 0.78 (0.38, 1.63) | .514 | 1.14 (0.54, 2.40) | .738 | 0.85 (0.40, 1.77) | .655 |
| 18–24 years | 0.85 (0.36, 2.01) | .710 | 1.08 (0.46, 2.52) | .865 | 0.83 (0.38, 1.81) | .633 |
| Male (vs. female) | 1.98 (0.98, 3.99) | .056 | 1.75 (0.89, 3.42) | .102 | 1.35 (0.70, 2.62) | .371 |
| Non-Hispanic White (vs. other) | 1.36 (0.73, 2.53) | .328 | 1.11 (0.63, 1.96) | .722 | 1.00 (0.54, 1.84) | .992 |
| Household income (vs. <$10 000) | Ref | Ref | Ref | |||
| $10 000–49 999 | 1.42 (0.65, 3.14) | .376 | 0.90 (0.43, 1.86) | .770 | 0.99 (0.48, 2.07) | .986 |
| $50 000+ | 1.49 (0.60, 3.68) | .383 | 0.68 (0.28, 1.64) | .387 | 1.44 (0.59, 3.50) | .414 |
| Tobacco and substance use characteristics | ||||||
| Smoking status (vs. non-smoker) | Ref | Ref | Ref | |||
| Former smoker | 0.63 (0.26, 1.51) | .295 | 0.90 (0.32, 2.52) | .839 | 0.73 (0.27, 1.96) | .531 |
| Current smoker | 0.63 (0.27, 1.50) | .297 | 16.77 (7.25, 38.77) | <.0001 | 8.15 (3.69, 18.02) | <.0001 |
| Use other tobacco products | 0.82 (0.42, 1.61) | .565 | 1.00 (0.54, 1.84) | .998 | 1.18 (0.65, 2.13) | .589 |
| Use marijuana | 0.67 (0.34, 1.30) | .232 | 1.02 (0.56, 1.87) | .942 | 1.11 (0.57, 2.17) | .755 |
| ENP use characteristics | ||||||
| Daily (vs. nondaily user) | 5.81 (3.17, 10.64) | <.0001 | 1.30 (0.66, 2.56) | .449 | 3.30 (1.76, 6.21) | <.0001 |
| Rechargeable device | 1.99 (0.99, 4.02) | .054 | 1.24 (0.62, 2.48) | .544 | 1.91 (0.97, 3.74) | .060 |
| Psychosocial and physical factors | ||||||
| ENP home rules (vs. not allowed) | Ref | Ref | Ref | |||
| Partially allowed | 2.48 (1.26, 4.91) | .009 | 1.90 (0.95, 3.78) | .069 | 1.86 (0.98, 3.53) | .056 |
| Fully allowed | 2.48 (1.22, 5.04) | .013 | 1.74 (0.83, 3.61) | .138 | 2.16 (1.06, 4.44) | .035 |
| Perceived harm of ENPs | 0.98 (0.71, 1.34) | .889 | 1.30 (0.98, 1.72) | .066 | 1.04 (0.76, 1.43) | .795 |
| Readiness to quit ENPs | 0.57 (0.30, 1.11) | .097 | 0.82 (0.43, 1.57) | .551 | 0.53 (0.29, 0.96) | .037 |
| Advised to quit tobacco | 1.35 (0.63, 2.90) | .435 | 2.83 (1.39, 5.78) | .005 | 2.52 (1.27, 5.01) | .009 |
| Respiratory symptoms in last 12 months | 0.83 (0.46, 1.51) | .541 | 1.15 (0.62, 2.12) | .653 | 0.96 (0.56, 1.67) | .894 |
Bold values indicate p < .05.
Discussion
By using data from the most recent waves of the PATH study (W3 and W4), this analysis offers the most current evidence regarding a wide range of predictors of combined ENP and cigarette smoking abstinence, and correlates of cigarette smoking status in a large, nationally representative sample of U.S. adult ENP users. Similar to previous analyses, we found that the majority of ENP users (65.6%) concurrently smoked cigarettes (ie, were dual users).14,16 We also found that ENP users differed in socio-demographics, tobacco and substance use patterns, and psychosocial characteristics based on their cigarette smoking status.
Socio-demographic correlates of W3 cigarette smoking status included age, race/ethnicity, gender and household income, and the patterns of associations we found are consistent with findings from previous studies. For instance, former smokers were more likely to be older than current smokers and non-smokers,20,24,28–30 current and former smokers were more likely to be non-Hispanic White,20,29 and former smokers and non-smokers were more likely to have a higher income than current smokers.24,28,29
W3 current smokers were more likely to use other combustible or non-combustible tobacco products than W3 former or non-smokers, and W3 current smokers were more likely than W3 former smokers to use marijuana, similar to results from other analyses.20,29 ENP use characteristics also differed markedly by smoking status. W3 former smokers were more likely than W3 non-smokers or current smokers to use ENPs daily and were also more likely than W3 current smokers to use a rechargeable device. This is likely due to the fact that among former smokers, a primary reason for using ENPs is to quit smoking.20–22,24 Therefore, former smokers might invest in a rechargeable device as a cessation aid and may perceive the need to use ENPs more frequently to remain abstinent from cigarette smoking.24
W3 current smokers were also more likely to receive advice to quit using tobacco products than W3 former or non-smokers. This is similar to results from another study, which found that cigarette smokers were more likely to receive advice to quit compared with non-cigarette tobacco product users.31 Several factors could account for this difference, including lack of routine screening for other tobacco products in clinical settings, lack of guidance for providers on ENP cessation, and ambivalence among healthcare providers about the efficacy of ENPs as a smoking cessation aid.32,33 Similar to other studies, we also found that dual users were more likely than former smokers to experience respiratory difficulties such as wheezing and/or dry cough.34–36
Longitudinal predictors of combined ENP and cigarette smoking abstinence largely mirrored findings from previous analyses of PATH data on predictors of ENP discontinuation.16–18 We also found that socio-demographic characteristics did not predict combined ENP and cigarette smoking abstinence but some tobacco and ENP use characteristics did. Thus, the introduction of newer ENPs such as JUUL does not appear to have changed predictors of ENP cessation. Given that W3 dual users were more likely than W3 non-smokers to use cigarettes only or both products (vs. be abstinent from both products) at W4, and W3 dual users were also more likely than W3 former or non-smokers to use other combustible or non-combustible tobacco products, dual users merit particular attention for interventions, specifically around quitting all tobacco products, because of their high-risk status. This also implies that interventions that successfully promote ENP cessation without attention to smoking or other tobacco product use may not substantially change a user’s risk. In terms of ENP use characteristics, daily users at W3 were more likely to use ENPs only or both products (vs. be abstinent from both products) at W4. ENP cessation interventions could encourage and assist daily ENP users with cutting down their frequency to facilitate ENP cessation.
Among psychosocial factors, living in a home freely allowing ENP use at W3 was associated with a greater likelihood of using ENPs only or both products (vs. being abstinent from both products) at W4. Household vaping restrictions are associated with lower vaping prevalence and frequency.37 Therefore, more efforts are needed to encourage vape-free homes, for instance by emphasizing the potential harms associated with secondhand exposure to aerosols from ENPs.38 Receiving advice to quit tobacco products at W3 was associated with a greater likelihood of using cigarettes only or both products (vs. being abstinent from both products) at W4. However, this could possibly reflect confounding by smoking status, as current smokers are more likely to receive advice to quit using tobacco and less likely to be abstinent from both products. Finally, readiness to quit using ENPs at W3 was associated with a greater likelihood of abstinence from both products (vs. using both products) at W4, and could serve as a potential target for behavioral ENP cessation interventions for dual users.
These findings illustrate the utility of an SCT framework to inform ENP cessation interventions. Interventions need to be tailored to the complex and heterogeneous profiles of cooccurring risk behaviors and substance use patterns among ENP users. Interventions targeting dual users will need to address cigarette smoking as well as other combustible and non-combustible tobacco product and marijuana use. As a result, dual or poly users might require more intensive behavioral support and pharmacotherapy. Psychosocial intervention targets may also differ across different cigarette use groups. For instance, former smokers use ENPs more frequently to remain abstinent from cigarette smoking, and common reasons for quitting ENPs among former smokers include safety concerns and not needing ENPs to stay quit.20,21,24 Thus, ENP cessation approaches tailored to former smokers could emphasize the risks of ENPs, encourage them to cut down on the frequency of use, and build self-efficacy to stay quit, while interventions for dual users may need to increase readiness to quit both products. Supportive social and physical environments, such as vape-free environments could potentially facilitate ENP cessation.
Strengths and Limitations
Limitations of this analysis include self-report of ENP and cigarette use and small sample sizes for some groups, which is reflected in the wide confidence intervals for some estimates. Additionally, observations that were excluded for missing data may have been associated with the outcomes of ENP and cigarette use, resulting in reduced statistical power and potentially biased estimates. The observational nature of the data precludes us from making any causal conclusions, particularly for W3 analyses, which are cross-sectional. However, strengths of this analysis are the inclusion of a wider range of variables than previous analyses, including psychosocial and environmental variables, and the use of a nationally representative sample, which enhances the generalizability of findings. Given the dearth of research on ENP cessation, these findings can inform the development of ENP cessation interventions.
Conclusions
Current, former, and non-smoking ENP users differ in socio-demographic, tobacco use, and psychosocial characteristics. Therefore, ENP cessation approaches need to be tailored to the distinct cigarette use profiles of ENP users. Dual users and daily ENP users may require intensive approaches to support abstinence from both products. Promoting the adoption of vape-free policies in homes could create supportive environments that facilitate ENP and cigarette smoking abstinence.
Supplementary Material
A Contributorship Form detailing each author’s specific involvement with this content, as well as any supplementary data, are available online at https://academic.oup.com/ntr.
Funding
Dr. Berg is supported by National Institutes of Health funding, specifically the US National Cancer Institute (R01CA179422-01; PI: Berg; R01CA215155-01A1; PI: Berg; R01CA239178-01A1; MPIs: Berg, Levine), the Fogarty International Center/National Institutes of Health (1R01TW010664-01; MPIs: Berg, Kegler), and the National Institute of Environmental Health Sciences/Fogarty (D43ES030927-01; MPIs: Berg, Marsit, Sturua).
Declaration of Interests
None declared.
Supplementary Material
References
- 1. Cornelius ME, Wang TW, Jamal A, Loretan CG, Neff LJ. Tobacco product use among adults—United States, 2019. MMWR Morb Mortal Wkly Rep. 2020;69(46):1736–1742. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2. Hu SS, Neff L, Agaku IT, et al. . Tobacco product use among adults - United States, 2013–2014. MMWR Morb Mortal Wkly Rep. 2016;65(27):685–691. [DOI] [PubMed] [Google Scholar]
- 3. Czekala L, Simms L, Stevenson M, Tschierske N, Maione AG, Walele T. Toxicological comparison of cigarette smoke and e-cigarette aerosol using a 3D in vitro human respiratory model. Regul Toxicol Pharmacol. 2019;103:314–324. [DOI] [PubMed] [Google Scholar]
- 4. St Helen G, Liakoni E, Nardone N, Addo N, Jacob P III, Benowitz NL. Comparison of systemic exposure to toxic and/or carcinogenic volatile organic compounds (VOC) during vaping, smoking, and abstention. Cancer Prev Res (Phila). 2020;13(2):153–162. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5. Hajek P, Phillips-Waller A, Przulj D, et al. . A randomized trial of e-cigarettes versus nicotine-replacement therapy. N Engl J Med. 2019;380(7): 629–637. [DOI] [PubMed] [Google Scholar]
- 6. Masiero M, Lucchiari C, Mazzocco K, VeronesiG, et al. . Corrigendum: e-cigarettes may support smokers with high smoking-related risk awareness to stop smoking in the short run: preliminary results by randomized controlled trial. Nicotine Tob Res. 2020;22(4):594–595. [DOI] [PubMed] [Google Scholar]
- 7. Gotts JE, Jordt SE, McConnell R, Tarran R. What are the respiratory effects of e-cigarettes? BMJ. 2019;366:l5275. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8. Walley SC, Wilson KM, Winickoff JP, Groner J. A public health crisis: electronic cigarettes, vape, and JUUL. Pediatrics. 2019;143(6):2018–2741. [DOI] [PubMed] [Google Scholar]
- 9. Zhang G, Wang Z, Zhang K, et al. . Safety assessment of electronic cigarettes and their relationship with cardiovascular disease. Int J Environ Res Public Health. 2018;15(1):E75. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10. Gaiha SM, Cheng J, Halpern-Felsher B. Association between youth smoking, electronic cigarette use, and COVID-19. J Adolesc Health. 2020;67(4):519–523. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11. Soneji S, Barrington-Trimis JL, Wills TA, et al. . Association between initial use of e-cigarettes and subsequent cigarette smoking among adolescents and young adults: a systematic review and meta-analysis. JAMA Pediatr. 2017;171(8):788–797. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12. Surgeon General’s Advisory on E-cigarette Use Among Youth. Centers for Disease Control and Prevention (CDC). Updated April 9, 2019. https://www.cdc.gov/tobacco/basic_information/e-cigarettes/surgeon-general-advisory/index.html. Accessed October 27, 2020. [Google Scholar]
- 13. Bandura A. Social Foundations of Thought and Action: A Social Cognitive Theory. Englewood Cliffs, NJ: Prentice-Hall; 1986. [Google Scholar]
- 14. Rosen RL, Steinberg ML. Interest in quitting e-cigarettes among adults in the United States. Nicotine Tob Res. 2020;22(5):857–858. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15. Hyland A, Ambrose BK, Conway KP, et al. . Design and methods of the Population Assessment of Tobacco and Health (PATH) Study. Tob Control. 2017;26(4):371–378. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16. Coleman B, Rostron B, Johnson SE, et al. . Transitions in electronic cigarette use among adults in the Population Assessment of Tobacco and Health (PATH) Study, Waves 1 and 2 (2013–2015). Tob Control. 2019;28(1):50–59. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17. Wei L, Muhammad-Kah RS, Hannel T, et al. . The impact of cigarette and e-cigarette use history on transition patterns: a longitudinal analysis of the population assessment of tobacco and health (PATH) study, 2013–2015. Harm Reduct J. 2020;17(1):45-020-00386-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18. Osibogun O, Bursac Z, Mckee M, Li T, Maziak W. Cessation outcomes in adult dual users of e-cigarettes and cigarettes: the Population Assessment of Tobacco and Health cohort study, USA, 2013–2016. Int J Public Health. 2020;65(6):923–936. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19. Pepper JK, Ribisl KM, Emery SL, Brewer NT. Reasons for starting and stopping electronic cigarette use. Int J Environ Res Public Health. 2014;11(10):10345–10361. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20. Berg CJ. Preferred flavors and reasons for e-cigarette use and discontinued use among never, current, and former smokers. Int J Public Health. 2016;61(2):225–236. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21. Biener L, Song E, Sutfin EL, Spangler J, Wolfson M. Electronic cigarette trial and use among young adults: reasons for trial and cessation of vaping. Int J Environ Res Public Health. 2015;12(12):16019–16026. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22. Boyle RG, Richter S, Helgertz S. Who is using and why: prevalence and perceptions of using and not using electronic cigarettes in a statewide survey of adults. Addict Behav Rep. 2019;10:100227. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23. Kong G, Morean ME, Cavallo DA, Camenga DR, Krishnan-Sarin S. Reasons for electronic cigarette experimentation and discontinuation among adolescents and young adults. Nicotine Tob Res. 2015;17(7): 847–854. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24. Yong HH, Borland R, Cummings KM, et al. . Reasons for regular vaping and for its discontinuation among smokers and recent ex-smokers: findings from the 2016 ITC Four Country Smoking and Vaping Survey. Addiction. 2019;114(suppl 1):35–48. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25. Huang J, Duan Z, Kwok J, et al. . Vaping versus JUULing: how the extraordinary growth and marketing of JUUL transformed the US retail e-cigarette market. Tob Control. 2019;28(2):146–151. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26. Bondy SJ, Victor JC, Diemert LM. Origin and use of the 100 cigarette criterion in tobacco surveys. Tob Control. 2009;18(4):317–323. [DOI] [PubMed] [Google Scholar]
- 27. Hitchman SC, Pearson JL, Villanti AC. The need for more nuance in headline adult cigarette smoking prevalence estimates. Addiction. 2017;112(8):1327–1328. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28. Harrell PT, Simmons VN, Piñeiro B, et al. . E-cigarettes and expectancies: why do some users keep smoking? Addiction. 2015;110(11):1833–1843. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29. Jaber RM, Mirbolouk M, DeFilippis AP, et al. . Electronic cigarette use prevalence, associated factors, and pattern by cigarette smoking status in the United States From NHANES (National Health and Nutrition Examination Survey) 2013–2014. J Am Heart Assoc. 2018;7(14):e008178. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30. Ma JZ, Hart JL, Walker KL, et al. . Perceived health risks of electronic nicotine delivery systems (ENDS) users: the role of cigarette smoking status. Addict Behav. 2019;91:156–163. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31. Keith DR, Stanton CA, Gaalema DE, et al. . Disparities in US healthcare provider screening and advice for cessation across chronic medical conditions and tobacco products. J Gen Intern Med. 2017;32(9): 974–980. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32. Kollath-Cattano C, Dorman T, Albano AW Jr, Jindal M, Strayer SM, Thrasher JF. E-cigarettes and the clinical encounter: physician perspectives on e-cigarette safety, effectiveness, and patient educational needs. J Eval Clin Pract. 2019;25(5):761–768. [DOI] [PubMed] [Google Scholar]
- 33. Singh B, Hrywna M, Wackowski OA, Delnevo CD, Jane Lewis M, Steinberg MB. Knowledge, recommendation, and beliefs of e-cigarettes among physicians involved in tobacco cessation: a qualitative study. Prev Med Rep. 2017;8:25–29. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34. Cassidy RN, Tidey JW, Colby SM. Exclusive e-cigarette users report lower levels of respiratory symptoms relative to dual e-cigarette and cigarette users. Nicotine Tob Res. 2020;22(suppl 1):S54–S60. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35. Bhatta DN, Glantz SA. Association of e-cigarette use with respiratory disease among adults: a longitudinal analysis. Am J Prev Med. 2020;58(2):182–190. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36. Hedman L, Backman H, Stridsman C, et al. . Association of electronic cigarette use with smoking habits, demographic factors, and respiratory symptoms. JAMA Netw Open. 2018;1(3):e180789. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37. Azagba S, Shan L, Manzione L. Associations of home and workplace vaping restrictions with e-cigarette use among U.S. adults. Prev Med. 2020;139:106196. [DOI] [PubMed] [Google Scholar]
- 38. Bayly JE, Bernat D, Porter L, Choi K. Secondhand exposure to aerosols from electronic nicotine delivery systems and asthma exacerbations among youth with asthma. Chest. 2019;155(1):88–93. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.