Hypothetical flavor ban and intention to vape among vape shop customers: The role of flavor preference and e-cigarette dependence

Abstract

Introduction:

E-cigarette users typically initiate vaping with flavored e-liquids. People who vape flavors tend to underestimate the harm of vaping. We examined the interrelationship between flavor preference, vaping for cessation purposes, e-cigarette dependence, e-cigarette harm perception and purchase/use intention, given a hypothetical flavor ban. We hypothesized that non-tobacco flavor preference and vaping for cessation would be negatively associated with harm perception of e-cigarettes and intention to continue vaping if a flavor ban occurred and that these effects would be mediated by e-cigarette dependence.

Methods:

From July 2019 to March 2020, we conducted intercept interviews with 276 customers at 44 vape shops in California. The predictor variables were flavor preference and vaping for cessation. The outcome variables were harm perception of e-cigarettes and intention to purchase/use given a hypothetical flavor ban. Multilevel structural equation modeling tested whether e-cigarette dependence mediates the effects of flavor preference on hypothetical continued vaping and purchase.

Results:

Those who preferred flavors showed significantly lower intention to purchase e-liquids (β=−.28, p<.001) and to continue vaping (β=−.17, p=.001), given a hypothetical flavor ban. Those who vaped for smoking cessation indicated greater intention to purchase e-liquid (β=.10, p=.016) and to continue vaping (β=.17, p=.001) given a hypothetical flavor ban. E-cigarette dependence significantly mediated these effects (p’s<.04).

Discussion:

Flavor preference was negatively related to intention to continue to vape within a hypothetical flavor ban. Our results also highlight the importance of e-cigarette dependence and use of e-cigarettes as smoking cessation methods. Implications for future flavor bans are discussed.

Introduction

E-cigarette vaping prevalence increased dramatically over the past decade [1–5]. While vaping might lead to harm reduction among combustible tobacco users who are unable or unwilling to quit nicotine, the drastic increase in prevalence of vaping accompanied by the emergence of vape shop retailers [6–8] may undermine decades of anti-tobacco efforts and policies in de-normalizing tobacco use [9]. Marketing strategies employed by the industry promote a rapid evolution of products, including numerous flavors [10, 11].

Systematic reviews have found that most vapers prefer flavors [10, 11]. Sweet and fruity flavors contribute to reduced harm perception of e-cigarettes [10], increased willingness to initiate vaping [10], and subsequent escalation in vaping frequency [12]; however, tobacco-flavor is associated with increased harm perception [11]. Non-nicotine, flavor-only vaping is associated with approval of vaping [13]. Vaping nontraditional, “trendy” flavors (e.g., fruit, dessert or combinations) was prospectively related to continued vaping and taking more puffs per vaping session, relative to vaping tobacco- or menthol flavors [14].

Most adult vapers report that their first e-cigarette purchases were flavored products [15–18]. Compared to adult users ages ≥ 25 years, the appeal of the variety of flavors is a salient reason for vaping for younger adults (aged 18–24), who are more likely to use fruit-, candy- or concurrent multi-flavors [19]. While older adults often indicate vaping as a way to quit smoking [20, 21], younger adults tend to vape for socialization [22] and enjoyment/recreation [23], citing flavors as a reason [21–23]. Findings on whether flavored vaping help with smoking cessation are inconclusive [11].

Given the role of flavor in vaping, laws to ban or restrict flavors have been discussed by FDA [24] and cities/states (e.g., MA [25], MI [26], NY [27], CA [28]) with varying success. However, little is known regarding the impact of flavor bans on vapers’ opinions or behaviors [29]. The levels of vaping-specific dependence could influence vapers’ reactions to such bans because people with higher nicotine dependence might continue vaping even if flavors were banned. Research is needed to elucidate the role of vaping-specific dependence as well as preference for flavors (vs. tobacco-only flavor) in shaping vapers’ willingness to continue product use in the case of flavor bans.

E-cigarette users typically report lower levels of nicotine dependence compared with cigarette smokers [30]. Vaping-specific dependence is negatively associated with willingness to quit vaping among current e-cigarette youth users [31]. Unlike adolescents typically preferring flavors other than tobacco [12, 13], young adult poly-device users (i.e., using multiple devices concurrently) frequently used tobacco flavored products as well as other flavors [32], implying that banning flavors might not deter vape behavior among young adults. Little is known regarding the relationship between flavor preference and vaping-specific dependence, as well as the role of dependence in conjunction with harm perception when considering hypothetical flavor bans.

This study examines the interrelationships between (a) flavor preference, (b) vaping for cessation purposes, (c) e-cigarette dependence, (d) e-cigarette harm perception and (e) purchase/use intention given enactment of a hypothetical flavor ban among in-person vape shop customers. We hypothesized that non-tobacco flavor preference and vaping for smoking cessation would be negatively associated with e-cigarette harm perception and intention to continue vaping after a hypothetical flavor ban. We also hypothesized that these direct effects would be mediated by e-cigarette dependence.

Methods

Participants and Procedures

From July 2019 to March 2020, trained teams of 2–3 data collectors visited vape shops in Southern California and received permission to recruit customers from shop owners (15.4% shop refusal rate). Prior to data collection, all data collectors completed extensive training and piloting of protocols and survey measures adapted from previous work [33–37]. Data collectors followed scripts and verbally administered structured survey questions. All vape shop customers present at the time of data collection were approached as they exited the vape shop. Participants were eligible if they had vaped in the last 30 days. Customers were invited to participate in a 15-minute intercept interview survey. Customers were assured that the data would be collected anonymously. Out of 431 eligible customers, 28.1% (n=121, average age 35; 77% male; 52% white) declined to participate and 7.8% (n=34) were not surveyed as interviews with other customers were in progress. Participants provided verbal consent and received a $35 gift card. A total of 276 customer interviews from 44 vape shops from diverse neighborhoods were included in this sample. The study was approved by the USC Institutional Review Board.

Measures

Demographics:

Participants reported their age, ethnicity, and gender.

Past 30-day use:

Days of cigarette/e-cigarette use in the past 30 days (1–30) were assessed.

Quit status:

Participants indicated whether they “quit all combustible tobacco products by using e-cigarettes instead” (0=No/1=Yes).

Nicotine level of e-cigarette:

Participants indicated how many mg/ml of nicotine their favorite brand/flavor contains.

Dependence:

A 4-item scale [33] measured e-cigarette dependence (e.g., “I find myself reaching for my e-cigarette without thinking about it”; (0=Never to 4=Almost always).

Harm perception of e-cigarettes:

Participants responded to “How harmful to your health do you think e-cigarettes are on a scale of 1-to-10?” [35] (1=No danger/quite safe to 10=dangerous/not safe at all).

Intention for tobacco-flavored e-liquid purchase for hypothetical flavor ban:

“Hypothetically, let’s say that there was a regulation such that only tobacco flavored e-juices were allowed, and all other flavors were banned, how likely would you purchase tobacco flavored e-juices?” (1=Not at all to 4=Extremely)

Intention for continued vaping after a hypothetical flavor ban:

Immediately after the previous question, participants responded to how likely it is that they would continue to vape (1=Not at all to 4=Extremely).

Non-tobacco flavor preference:

Participants “checked all that apply” to indicate their preferred flavors: fruity, dessert, minty, menthol and tobacco. We reverse coded preference for tobacco flavor (i.e., prefer tobacco flavor=0; prefer non-tobacco flavors=1).

Statistical Analysis

We derived a single factor structure of e-cigarette dependence through multilevel confirmatory factor analysis (CFA). We used multilevel structural equation modeling (SEM) to include the e-cigarette dependence factor and simultaneously test the mediational model (1-1-1) [38, 39] while accounting for potential clustering by vape shops. The outcome variables in our mediational model were harm perception and intention to purchase and continued use of e-cigarettes in a hypothetical flavor ban. The final model adjusted for gender, age, and nicotine level of e-cigarettes. All analyses were conducted in Mplus V8.3.

Results

Descriptive Statistics

The sample was largely white (41.7%; Hispanic 25.0%), male (76.4%), and young adult (M=31.8 years of age). Most had used 100+ cigarettes in lifetime (75.7%), quit combustible tobacco products by vaping instead (71.7%) and were daily vapers (M=26.6 days in the past month). All participants had used e-cigarettes 1+ day in the past month; 77.9% had vaped 30 days in the past month; 22.1% were current dual users (i.e., 1+ day of cigarette use in the past month).

Although the estimates reported here are the results of multilevel modeling, the estimates produced by multilevel modeling were similar as those in single-level models (endogenous variables ICCs<.01; average cluster size 6.3).

Multilevel CFA

The one-factor CFA for e-cigarette dependence showed good fit, with individual loadings ranging from .54 to .70 (RMSEA=.07; CFI=.98; SRMR=.03), controlling for clustering by shops.

Multilevel SEM

Direct effects of flavor preference and quit by vaping on dependence

The dependence factor was used in our subsequent mediation model (Figure 1; RMSEA=.07; CFI=.87; SRMR=.06). Current cigarette and e-cigarette use were positively related to the dependence factor (β=.13, p=.008; β=.31, p<.001, respectively), controlling for gender, ethnicity, age, and e-cigarette nicotine concentration. Non-tobacco flavor preference was negatively related to e-cigarette dependence (β= −.19, p=.002). Vaping to quit smoking was positively associated with e-cigarette dependence (β=.13, p=.029).

Figure 1. Multilevel mediational model.

The mediation model is adjusted for age, ethnicity, gender and nicotine level (in mg/ml) used in e-cigarettes. Standardized coefficients are shown.

Direct effects of flavor preference and quit by vaping on perceived harm and intentions

Non-tobacco flavor preference was not associated with perceived harm of e-cigarettes (β=−.06, p=.236). Those who preferred non-tobacco flavors showed significantly lower intention for continued purchase (β=−.28, p<.001) and use of e-cigarettes (β=−.17, p=.001) in case of a hypothetical flavor ban. Those who reported vaping to quit indicated greater intention for continued purchase (β=.10, p=.016) and use of e-cigarettes (β=.17, p=.001) in case of a hypothetical flavor ban. With respect to perceived harm of e-cigarettes, those who vape to quit did not significantly differ from those who vape for other reasons (β=−.13, p=.054).

E-cigarette dependence, in turn, was positively associated with harmful perception (β=.14, p=.033), greater intention for continued purchase (β=.29, p<.001) and use of e-cigarettes (β=.25, p<.001) in a hypothetical flavor ban.

Indirect Effects

E-cigarette dependence partially mediated the association between preferred flavor and harm perception (p=.047). It also mediated the relationship between preferred flavor and intention for continued purchase (p=.013) and use of e-cigarettes (p=.039) in a hypothetical flavor ban (Table 2).

Table 2.

Direct effect, indirect effect and total effect of the model

	Direct effect	Indirect effect	Total effect
Flavor→Dep→Harm	−.06	−.03*	−.01
Flavor→Dep→HypoPurchase	−.28***	−.06*	−.33***
Flavor→Dep→HypoVape	−.17**	−.05*	−.22***
QuitEC→Dep→Harm	−.13	.02	−.11
QuitEC →Dep→HypoPurchase	.10*	.04*	.14**
QuitEC →Dep→HypoVape	.17**	.03*	.20***

^*p<.05;

^**p<.01;

^***p<.001

Flavor: Preference for non-tobacco flavor; Dep: E-cigarette dependence factor; Harm: Perceived harmful of e-cigarettes to health; HypoPurchase: Intention to purchase tobacco-flavored e-juice in hypothetical flavor ban; HypoVape: Intention to continue vaping in hypothetical flavor ban; QuitEC: Quit combustible products by using e-cigarettes instead

Discussion

Vape shop customers who preferred non-tobacco flavors reported lower intentions to continue to purchase and use e-cigarettes in the case of a flavor ban. E-cigarette dependence mediated this association; non-tobacco flavor preference is related to lower dependence, which, in turn, is related to lower usage/purchase intention in the case of a flavor ban. However, our results did not support the hypothesis that flavor preference would be associated with harm perception. This may be because vape shop customers are generally older than the participants in past studies [10, 11]. An additional analysis revealed that flavor preference was not related to intention to switch to combustible tobacco products in the case of a flavor ban (p=.71, results not shown), suggesting that flavor bans could deter users with flavor preference from using combustible products.

Limitations.

Data were self-reports and findings might not generalize to vapers who purchase online and do not visit vape shops. It is also unclear whether vapers who prefer flavors would switch to other flavored tobacco produces after a flavor ban. Future studies should investigate the role of flavor preference and e-cigarette dependence for vapers in other states and countries. Our data collection halted because of Covid-19 restrictions; thus, the effect of Covid-19 on the observed associations remains to be seen.

Conclusion.

Our findings provide valuable insights about vape shop customers and the potential effects of e-cigarette flavor bans. Customers who preferred flavors were less likely to intend to continue vaping in the case of a flavor ban, suggesting that flavor bans could reduce vaping among experimental tobacco users, without preventing highly nicotine dependent users from switching from cigarettes to e-cigarettes for harm reduction.

Table 1.

Sample characteristics of vape shop customers (N=276)

	M(SD)	N(%)
Demographics
Male		211(76.4)
Age	31.8(10.5)
Race/Ethnicity
Hispanic		69(25.0)
White		115(41.7)
Black		35(12.7)
Asian		46(16.7)
Other		31(11.2)
Use Characteristics
Ever smoked 100 cigarettes in lifetime		209(75.7)
Days of e-cig use in the past 30-day	26.6(7.4)
Days of cigarette use in the past 30-day	2.5(7.2)
Nicotine level (mg/ml)	17.0(18.7)
Quit smokable tobacco products by using e-cigs instead		198(71.7)
Dependence to E-Cigarettes
I find myself reaching for my e-cig without thinking about it	3.4(1.3)
I drop everything to go out and buy e-cig or e-juice	1.8(1.0)
I vape more before going into a situation where vaping is not allowed	3.0(1.5)
When I haven’t been able to vape for a few hours, the craving gets intolerable	2.1(1.2)
Harm Perception
How harmful is e-cig to your health (1=No danger/quite safe to 10=dangerous/not safe at all)	4.4(2.3)
Intention in case of a Hypothetical Ban
If there was a regulation such that only tobacco flavored e-juices are allowed and all other flavors are banned (1=Not at all to 4=Extremely):
How likely you would purchase tobacco flavored e-juices?	1.9(1.1)
How likely you would continue to vape?	2.3(1.2)