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. Author manuscript; available in PMC: 2025 Jan 1.
Published in final edited form as: Am J Prev Med. 2023 Sep 4;66(1):55–63. doi: 10.1016/j.amepre.2023.09.001

Cumulative exposure to e-cigarette coupons and changes in e-cigarette use among US adults

Zongshuan Duan 1, Kristen R Hamilton-Moseley 2, Timothy S McNeel 3, Carla J Berg 4,5, Kelvin Choi 2
PMCID: PMC10840717  NIHMSID: NIHMS1929187  PMID: 37673195

Abstract

Introduction:

Coupons are an effective, frequently-used tobacco marketing strategy. This study examined prospective associations between cumulative exposure to e-cigarette coupons and changes in e-cigarette use among US adults.

Methods:

Data were from a representative US adult cohort (n=19,824) in the Population Assessment of Tobacco and Health Study (waves [W] 2, 3, 4, and 5), collected from October 2014 to November 2019. Analysis was conducted in 2022. Four logistic regression models examined associations of number of waves for which participants received e-cigarette coupons during W2-W4 with changes in e-cigarette use: W2 never use to W5 current use (initiation); W2 current non-daily use to W5 daily use (progression); W2 current use to W5 former use (cessation), and W2 former use to W5 current use (return-to-use).

Results:

Overall, 66.1% of US adults never used e-cigarettes, 10.6% currently used e-cigarettes, and 23.4% formerly used e-cigarettes at W2. The average number of waves for which participants received e-cigarette coupons during W2-W4 was 0.13: 0.10 among W2 individuals who never used e-cigarettes, 0.30 among individuals who currently used e-cigarettes on a non-daily basis, 0.50 among individuals who currently used e-cigarettes, and 0.17 among individuals who formerly used e-cigarettes. Receiving coupons at increased waves was associated with 1) greater odds of initiation (aOR=1.58, 95%CI=1.26–1.97); 2) lower odds of cessation (aOR=0.78, 95%CI=0.67–0.91); and 3) increased odds of return-to-use (aOR=1.39, 95%CI=1.14–1.69). Findings did not differ by W2 cigarette smoking status.

Conclusions:

E-cigarette coupons may encourage and sustain e-cigarette use. Policies restricting e-cigarette coupons may curb e-cigarette use.

Introduction

Despite e-cigarettes being widely promoted as smoking cessation aids,1,2 evidence on the effects of e-cigarettes on quitting cigarette smoking remains mixed.3 While some clinical trials have indicated that e-cigarettes are effective in helping adults quit smoking,4-7 a recent meta-analysis of observational population-based studies indicated no significant association.3 As of 2023, no e-cigarettes have been approved as smoking cessation aids by the U.S. Food and Drug Administration (FDA).

Tobacco marketing significantly impacts individuals’ use behaviors.8-11 Pricing strategies, such as discounts and coupons, are heavily utilized to engage existing and potential customers and ultimately influence use behaviors.12,13 Tobacco companies distribute coupons directly to existing and potential consumers.14 A study examining various mobile tobacco websites associated with prominent US tobacco brands indicated widespread and varying coupon practices across different product categories and that the majority of cigarette and smokeless tobacco websites offered coupons.15 Some e-cigarette and cigar websites also provided similar incentives.15 In addition, 2013-2014 data from the nationally-representative Population Assessment of Tobacco and Health (PATH) Study reported past 6-month receipt of direct mail/email tobacco coupons among 37.1% of people who currently smoked cigarettes, 16.5% of people who formerly smoked cigarettes, and 10.7% of people who had never smoked cigarettes.16 Notably, the receipt of tobacco coupons encourages and sustains cigarette smoking behaviors.16-18 One cohort study showed that receipt of cigarette coupons was negatively associated with both short- and long-term cigarette smoking cessation.19 An analysis of 2013-2014 PATH data found that, among US adults, receipt of direct mail/email tobacco coupons was prospectively associated with progression of cigarette smoking at 12-month follow-up.16

E-cigarette manufacturers employ pricing strategies to engage customers,20 but data on the impact of e-cigarette coupon reception is scarce. A study using 2016-2018 PATH data showed that 5.3% of people who currently smoked cigarettes with intention to quit reported receiving e-cigarette coupons.19 Other research suggested that receipt of tobacco coupons was significantly related to e-cigarette susceptibility among people who did not use e-cigarettes.21 More generally, reduced e-cigarette prices have been associated with increased e-cigarette sales,22,23 indicating that e-cigarette coupons likely impact use. Despite these findings, there is no nationally representative study documenting the exposure to e-cigarette coupons, by e-cigarette using status (i.e., current, former, never use), and there is limited literature regarding their impact on use behaviors within these subgroups.

Other gaps in literature also exist. First, previous studies estimating the effects of tobacco coupons primarily operationalized coupon receipt as a dichotomous variable and at a single timepoint,16-18 which fails to capture the incremental impact of e-cigarette coupon reception over a longer period and the potential dose-response relationships. One study found a dose-response relationship that cumulative exposure to cigarette discount coupons was associated with increased smoking and decreased quitting.24 Second, previous studies focused primarily on short-term (6-month or 1-year) associations and did not examine whether such relationships were sustained over longer periods. It is conceivable that the impact of e-cigarette coupons on e-cigarette use behaviors may be stronger for those with higher and/or longer incremental exposure to e-cigarette coupons. Third, little research has examined the extent to which the e-cigarette industry targets populations disproportionately impacted by tobacco use (e.g., low socioeconomic status [SES], racial/ethnic minorities).25 This is critical given that the tobacco industry has a documented history of targeted marketing to such subpopulations18 and that conventional tobacco coupons may disproportionally impact low-SES subpopulations.16,19

This study aimed to examine incremental exposure to e-cigarette coupons across individuals representing different e-cigarette use statuses and its association with long-term changes in e-cigarette use behaviors, accounting for sociodemographic characteristics that potentially reflect disproportionately-impacted subpopulations. Specifically, this study analyzed data from a nationally representative adult cohort from the PATH study to examine: (1) the number of waves for which participants reported exposure to e-cigarette coupons across three waves (2014-2018) by e-cigarette use status; (2) associations between e-cigarette coupon exposure over time and changes in e-cigarette use status at follow-up (2018-2019); and (3) interactions between number of waves for which participants received e-cigarette coupons and baseline cigarette smoking status on e-cigarette behavioral change outcomes. This study hypothesized that cumulative exposure to e-cigarette coupons would be significantly associated with progression of e-cigarette use behaviors, and these associations would be stronger among those who used cigarettes at baseline.

Methods

Study Sample

This study analyzed data from the US PATH Study Adult Surveys (n=19,824) Public Use Files. The PATH study is a nationally representative, longitudinal cohort study examining tobacco use among US youth and adults. The study utilized a four-stage stratified area probability sample design, in conjunction with a two-phase design for sampling adults at the final stage.26 Audio computer-assisted self-interviewing was used to administer interviews. Additional details of the PATH Study are documented elsewhere.26

Data analyzed in the current study were from Wave 2 (W2; 2014-2015), W3 (2015-2016), W4 (2016-2018), and W5 (2018-2019). Because response rates for W2 through W5 differed across groups with respect to W1 age, sex, race/ethnicity and tobacco use, weighting adjustments were used to account for differential response rates across groups.26 The weighted response rates for W2 through W5 were 83.2%, 78.4%, 73.5%, and 69.4%, respectively. This study used deidentified data and does not require review or approval from the Institutional Review Board.

Measures

E-cigarette use behaviors were assessed at W2 and W5 by asking, “In the past 30 days, have you used an e-cigarette, even one or two puffs?”; “In the past 12 months, have you used an e-cigarette, even one or two puffs?”; and “Do you now use e-cigarettes: every day, some days, or not at all?”. At W1, participants also reported lifetime e-cigarette use. Based on W2 responses, participants were classified into three mutually exclusive groups: people who never used e-cigarettes (reported never use at W1 and no use in the past 30 days or 12 months at W2); people who currently used e-cigarettes (reported e-cigarette use in the past 30 days or 12 months, and indicated using “some days” or “every day”); and people who formerly used e-cigarettes (reported ever using e-cigarettes but reported “not at all” about current e-cigarette use). Additionally, people who used e-cigarettes on a non-daily basis (reported e-cigarette use in the past 30 days or 12 months and indicated using “some days” regarding current e-cigarette use) were identified.

The primary outcome was W5 e-cigarette use status. W5 outcomes differed depending on the W2 group assignment. For people who never used e-cigarettes at W2, the outcome was initiation, defined as reporting currently using e-cigarettes “some days” or “every day” at W5 (vs. other responses). For people who currently used e-cigarettes at W2, the outcome was cessation, defined as reporting “not at all” when asked about current e-cigarette use at W5 (vs. other responses). For people who formerly used e-cigarettes at W2, the outcome was return to e-cigarette use, defined as reporting currently using e-cigarettes “some days” or “every day” (vs. other responses). Lastly, for people who used e-cigarettes on a non-daily basis at W2, the outcome was progression to current daily e-cigarette use (reported currently using e-cigarettes “every day” at W5 vs. other responses).

The primary predictor was receipt of e-cigarette coupons (W2-W4). At W2-W4, participants were asked about receipt of coupons for e-cigarettes. At W2, two separate items were used to assess if in the past 12 months, participants had received coupons for tobacco products including cigarettes, e-cigarettes, cigars, smokeless tobacco, or other tobacco products either directly in the mail or in an email message, with each item referring to one delivery mode (i.e., direct mail, email). Participants who responded “yes” to either item were then asked for which tobacco products they received discounts (i.e., cigarettes, cigars, smokeless tobacco, or other tobacco products). Participants who reported receiving e-cigarette coupons via either the mail or email were categorized as receiving e-cigarette coupons. At W3 and W4, participants were asked if they had received coupons for a list of tobacco products (including e-cigarettes) in the past 12 months. For each wave, participants who reported e-cigarette coupon receipt were classified accordingly (vs. those who reported no coupon receipt or receipt of a coupon for a different tobacco product). The number of waves for which participants received e-cigarette coupons during W2-W4 was counted (0-3).

Covariates included W2 age, gender, race/ethnicity (non-Hispanic Black, non-Hispanic White, other/missing), education level (<high school, general equivalency diploma (GED) holder, high school graduate, some college or associate degree, and bachelor’s degree or above), and household income (<$50,000, $50,000-$99,999, $100,000 or more, missing). Additionally, participants were asked, “In the past 30 days, have you noticed cigarettes or other tobacco products being advertised in any of the following places? On posters or billboards; in newspapers or magazines; on websites or social media sites; on radio; on television; at events like fairs, festivals, or sporting events.” Participants who dichotomized as noticing ads in any place versus not noticing. This study also adjusted for W2 cigarette smoking status: never, current non-daily, current daily, and former.

Statistical Analysis

First, W2 correlates of number of waves for which participants received e-cigarette coupons during W2-W4 were examined. This study used two logistic regression models: the first included only sociodemographic variables, while the second also included e-cigarette use status and whether participants had noticed tobacco ads.

This study then fit four separate logistic regression models to investigate the associations between the number of waves for which participants were exposed to e-cigarette coupons and changes in e-cigarette use status between W2 and W5, adjusting for sociodemographic variables, W2 cigarette smoking status, and whether participants noticed tobacco ads at W2. Specifically, this study examined the relationship between number of waves for which participants received e-cigarette coupons and W5 outcomes. In each model, this study also tested the interaction between number of waves for which participants received e-cigarette coupons and W2 cigarette smoking status on the e-cigarette use outcome.

Analyses were conducted in 2022, using SUDAAN 11.0.3 to employ W5 balanced repeated replicate weights with Fay’s adjustment (f=0.3). This study used W5 adult all-waves longitudinal weights for the W1 cohort, which were adjusted for nonresponse, trimming, and raking to control totals.26

Results

Overall weighted characteristics and characteristics by W2 e-cigarette use status are presented in Table 1. This analytic sample (n=19,824) included 66.1% (n=13,094) who never used e-cigarettes, 10.6% (n=2,094) who currently used e-cigarettes (including 7.9% who currently used e-cigarettes non-daily [n=1,560]), and 23.4% (n=4,636) who formerly used e-cigarettes at W2. Overall, 89.9% did not receive any e-cigarette coupons, 8.0% received them for one wave, 1.7% for two waves, and 0.4% for three waves. The mean number of waves for which the sample reported receiving e-cigarette coupons was 0.13 waves (95% Confidence Interval [CI]=0.11-0.13). These estimates varied by W2 e-cigarette use status: 0.10 waves (95%CI=0.09-0.11) among adults who never used e-cigarettes, 0.35 waves (95%CI=0.32-0.40) among adults who currently used e-cigarettes, and 0.17 waves (95%CI=0.15-0.18) among adults who formerly used e-cigarettes. Additionally, adults who currently used e-cigarettes on a non-daily basis received e-cigarette coupons for 0.30 waves (95%CI=0.26-0.35).

Table 1.

Weighted characteristics in all individuals and by e-cigarette use status.

Characteristics All Never Current Former Current non-daily
N (%) N (%) N (%) N (%) N (%)
All 19,824 (100) 13,094 (100) 2,094 (100) 4,636 (100) 1,560 (100)
Race / ethnicity
 Non-Hispanic Black 2,928 (11.0) 2,296 (11.5) 186 (8.6) 446 (8.6) 157 (9.8)
 Hispanic 3,563 (15.0) 2,508 (15.5) 293 (10.9) 762 (13.6) 242 (12.3)
 Other / missing 1,711 (9.1) 1,099 (9.2) 183 (8.1) 429 (8.7) 142 (9.0)
 Non-Hispanic White 11,622 (65.0) 7,191 (63.8) 1,432 (72.3) 2,999 (69.1) 1,019 (68.9)
Gender
 Male 9,360 (47.7) 6,107 (46.4) 1,039 (54.6) 2,214 (52.7) 741 (52.7)
 Female 10,464 (52.3) 6,987 (53.6) 1,055 (45.4) 2,422 (47.3) 819 (47.3)
Age
 18-24 5,509 (12.9) 3,343 (10.4) 629 (22.5) 1,537 (24.8) 496 (23.9)
 25-34 4,049 (18.1) 2,272 (15.7) 500 (26.7) 1,277 (30.0) 362 (26.4)
 35-44 3,010 (16.7) 1,939 (16.3) 386 (20.5) 685 (17.2) 289 (20.9)
 45-54 2,952 (17.3) 2,047 (18.0) 305 (15.0) 600 (14.3) 221 (14.5)
 55-64 2,569 (17.4) 1,959 (19.1) 209 (11.0) 401 (10.0) 147 (10.4)
 65+ 1,735 (17.5) 1,534 (20.6) 65 (4.3) 136 (3.8) 45 (3.8)
Education
 Less than High School 2,540 (10.6) 1,715 (10.6) 303 (12.6) 522 (9.8) 247 (13.7)
 General equivalency diploma 1,257 (5.0) 670 (4.3) 205 (9.3) 382 (7.8) 150 (9.1)
 High school graduate 4,436 (22.4) 2,931 (22.3) 480 (24.2) 1,025 (22.1) 364 (24.4)
 Some college or associate degree 7,106 (32.8) 4,293 (30.9) 858 (40.6) 1,955 (41.8) 613 (39.0)
 Bachelor’s degree or more 4,485 (29.1) 3,485 (31.9) 248 (13.3) 752 (18.5) 186 (13.8)
Household income
 <$50,000 11,686 (50.4) 7,318 (47.9) 1,421 (64.9) 2,947 (59.9) 1,092 (67.6)
 $50,000-$99,999 4,153 (24.5) 2,814 (25.2) 399 (20.5) 940 (22.1) 283 (19.2)
 $100,000 or more 2,750 (17.8) 2,078 (19.1) 164 (9.3) 508 (12.8) 100 (7.5)
 Missing 1,235 (7.3) 884 (7.8) 110 (5.4) 241 (5.2) 85 (5.7)
Currently smokes cigarettes
 Yes 7,195 (20.0) 2,897 (10.4) 1,528 (71.7) 2,770 (57.9) 1,263 (80.8)
 No 12,629 (80.0) 10,197 (89.6) 566 (28.3) 1,866 (42.1) 297 (19.2)
Noticed ads in past 30 days
 Missing 18 (0.1) 8 (0.1) 6 (0.3) 4 (0.1) 5 (0.4)
 Yes 11,249 (54.4) 7,404 (54.0) 1,164 (53.9) 2,681 (57.2) 897 (55.6)
 No 8,557 (45.5) 5,682 (46.0) 924 (45.8) 1,951 (42.7) 658 (44.0)
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Shown in Table 2, non-Hispanic White adults received e-cigarette coupons in a higher number of waves compared to Hispanic, non-Hispanic Black, and adults of other race or who were missing race/ethnicity information (p<0.05). Adults aged 25-34 received e-cigarette coupons in more waves than those aged 18-24 (p<0.05). Adults with some college or associate degree, as well as those who did not graduate from high school, received coupons in more waves than those with a bachelor’s degree or more (p<0.05). Lastly, adults who had noticed tobacco advertisements in the previous 30 days and those who currently used e-cigarettes at W2 received e-cigarette coupons in more waves compared to those who did not notice tobacco advertisements and did not use e-cigarettes at W2 (p<0.05).

Table 2.

Weighted estimates of correlates of number of waves exposed to e-Cigarette coupons.

Characteristics Point Estimate
(95% CI)		 Predicted Marginal Mean
(95% CI)
Race/ethnicity
 Non-Hispanic Black −0.05 (−0.07, −0.03) 0.09 (0.07, 0.11)
 Hispanic −0.03 (−0.05, −0.01) 0.11 (0.09, 0.13)
 Other/missing −0.04 (−0.06, −0.01) 0.10 (0.08, 0.13)
 Non-Hispanic White Reference 0.14 (0.13, 0.15)
Sex
 Male 0.01 (−0.00, 0.03) 0.13 (0.12, 0.14)
 Female Reference 0.12 (0.11, 0.13)
Age in years
 18-24 Reference 0.12 (0.11, 0.14)
 25-34 0.04 (0.02, 0.07) 0.16 (0.14, 0.18)
 35-44 0.02 (−0.01, 0.05) 0.14 (0.12, 0.16)
 45-54 0.02 (−0.01, 0.05) 0.14 (0.12, 0.16)
 55+ −0.02 (−0.04, −0.00) 0.10 (0.08, 0.11)
Education
 Less than high school −0.06 (−0.08, −0.03) 0.07 (0.06, 0.09)
 General equivalency diploma 0.01 (−0.03, 0.05) 0.14 (0.10, 0.17)
 High school graduate −0.03 (−0.06, −0.00) 0.10 (0.08, 0.12)
 Some college or associate degree 0.03 (0.01, 0.05) 0.16 (0.14, 0.18)
 Bachelor’s degree or more Reference 0.13 (0.11, 0.14)
Household income
 <$50,000 0.03 (−0.00, 0.06) 0.14 (0.13, 0.15)
 $50,000-$99,000 0.03 (−0.00, 0.05) 0.13 (0.12, 0.15)
 Missing −0.02 (−0.06, 0.01) 0.08 (0.06, 0.11)
 $100,000 or more Reference 0.11 (0.08, 0.13)
Noticed tobacco ads at W2
 Yes 0.13 (0.12, 0.14) 0.17 (0.16, 0.18)
 No Reference 0.04 (0.03, 0.05)
Used e-cigarettes at W2
 Yes 0.23 (0.20, 0.27) 0.35 (0.31, 0.38)
 No Reference 0.11 (0.11, 0.12)
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Note: Boldface indicates statistical significance (p<0.05).

Among adults who never used e-cigarettes at W2, each incremental wave of exposure to e-cigarette coupons was associated with greater odds of W5 current e-cigarette use (Adjusted Odds Ratio [aOR]=1.58, 95%CI=1.26–1.97). Among people who currently used e-cigarettes at W2, each wave of coupon exposure was associated with lower odds of cessation at W5 (aOR=0.78, 95%CI=0.67–0.91). Among adults who formerly used e-cigarettes at W2, each wave of coupon exposure was associated with W5 current e-cigarette use (aOR=1.39, 95%CI=1.14–1.69). The association of each wave of coupon exposure with W5 current daily e-cigarette use was not significant in adults who had used e-cigarettes on a non-daily basis at W2 (aOR=1.11, 95%CI=0.83–1.48). Figure 1 shows the predicted marginal probability of W5 outcomes by number of waves for which participants received e-cigarette coupons and W2 e-cigarette use status. In all models, interactions between number of waves for which participants received e-cigarette coupons and W2 cigarette smoking status were not statistically significant (p>0.25).

Figure 1.

Figure 1

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a. Among people who never used e-cigarettes at Wave 2, the predicted marginal probability of using e-cigarettes at Wave 5 by waves of exposure to e-cigarette coupons (adjusted for age, sex, race/ethnicity, and noticing e-cigarette advertisements); b. Among people who used e-cigarettes on a non-daily basis at Wave 2, the predicted marginal probability of currently using e-cigarettes at Wave 5 by Waves of exposure to e-cigarette coupons (adjusted for age, sex, race/ethnicity, and noticing e-cigarette advertisements); c. Among people who used e-cigarettes at Wave 2, the predicted marginal probability of having quit e-cigarette use by wave 5, by waves of exposure to e-cigarette coupons (adjusted for age, sex, race/ethnicity, and noticing e-cigarette advertisements); d. Among people who had quit using e-cigarettes by Wave 2, the predicted marginal probability of having returned to using e-cigarettes by wave 5, by waves of exposure to e-cigarette coupons (adjusted for age, sex, race/ethnicity, and noticing e-cigarette advertisements).

Discussion

This study examines the exposure to e-cigarette coupons among US adults and changes in e-cigarette use behaviors over a 4-year period. The findings support the hypothesis that increased e-cigarette coupon receipt was prospectively related to progression and continuation of e-cigarette use, demonstrating a dose-response relationship. These findings, consistent with literature documenting cigarette manufactures’ pricing strategies,12,13 show that the e-cigarette industry utilizes discount coupons to establish relationships with existing, returning, and/or potential customers, and these strategies influence use behaviors.

Current findings align with previous studies that receipt of tobacco discount coupons predicts cigarette smoking initiation, cessation, and relapse.16-18,24 Incremental exposure to e-cigarette coupons over time may increase the likelihood of utilizing these coupons to reduce prices, which in turn may encourage use and discourage quitting.27-29 Therefore, incremental coupon receipt may potentially promote and sustain nicotine addiction and related health risks.30,31 The non-significant finding related to progression from non-daily to daily e-cigarette use could be due to the small number of individuals using e-cigarettes daily at W5.

Contrary to the initial hypothesis, this study found no statistically significant interactions between number of waves for which participants received e-cigarette coupons and W2 cigarette smoking status on all four e-cigarette use outcomes. The initial hypothesis was based on the fact that despite the FDA not approving e-cigarettes as quit smoking aids,32 e-cigarettes were widely promoted as cigarette smoking cessation tools.3,33 Therefore, this study hypothesized that compared with people who don’t smoke cigarettes, e-cigarette companies would be more likely to distribute e-cigarette coupons to people who smoke cigarettes. This study also expected that people who smoke cigarettes would be more likely than those who do not smoke to redeem these coupons for e-cigarettes. The non-significant interactions for all associations may indicate that e-cigarette discount coupons are influencing adults regardless of their cigarette smoking status. Given the population-based studies have largely shown e-cigarettes as an ineffective smoking cessation aid,3 e-cigarette coupons are likely to worsen public health at the population level. The finding support that incremental receipt of e-cigarette coupons was associated with unfavorable e-cigarette use progression, highlighting an urgent need for comprehensive policies regulating coupons and other pricing strategies of e-cigarettes.34

Additionally, this study highlighted the correlation of e-cigarette coupon exposure with demographic characteristics. Individuals who were non-Hispanic White, aged 25-34 years, with some college or associate degree are more likely to be incrementally exposed to e-cigarette discount coupons. These groups of individuals have consistently lower prevalence of cigarette smoking than racial/ethnic minorities and individuals with lower educational attainment.35 Thus, the findings suggest that e-cigarette companies may use e-cigarette discount coupons to recruit new consumers into nicotine use instead of promoting smoking cessation as claimed.3,33

This study has important policy implications. Consistent with what has been reported in previous studies,16-18,36,37 findings of this study support the regulatory efforts to restrict or ban the distribution of e-cigarette coupons. In addition, increasing e-cigarette taxes may strengthen the effectiveness of coupon regulations to counter e-cigarette companies’ pricing strategies,34 given that previous studies on cigarette taxes have consistently documented that raising tobacco tax is effective in preventing cigarette smoking initiation and promoting cessation.38,39 In addition, policies restricting e-cigarette coupons may have the potential to prevent e-cigarette initiation, promote e-cigarette cessation, and sustain e-cigarette abstinence among those with no history of cigarette use. Furthermore, previous studies imply that prohibiting redemption of e-cigarette coupons at retailers may be a feasible approach.16,17,36,37 Additionally, e-cigarette marketing strategies are getting increasingly diversified, shifting from traditional media channels to digital media channels,40 which may influence e-cigarette use behaviors among adults.41-45 To effectively guide intervention regulatory efforts, future longitudinal studies are needed to explore exposure to e-cigarette promotion across different media channels and assess its impact on tobacco use trajectories.

Limitations

This study has limitations. First, self-reported measures may introduce recall error and social desirability bias, although e-cigarette use is not stigmatized.46 Second, despite using nationally representative longitudinal data, being an observational study limits establishing causal relationships. Third, despite controlling for various covariates, unknown confounders are possible. Relatedly, for parsimony, nicotine dependence wasn’t included as it didn’t significantly alter results. In addition, participants’ urbanicity was not accounted for due to limitation of the PATH Study Public Use Files. Fourth, the current analysis did not account for the time-varying effect of e-cigarette coupons on use behaviors. It is possible that recent exposure to e-cigarette coupons is more impactful than earlier exposure on e-cigarette use behaviors. Therefore, future studies are warranted to examine time-varying effect of e-cigarette coupon exposure. Furthermore, this study used an “other” category to represent racial and ethnic minorities and missing data. It does not fully capture the diversity within this category and is essential for future research to examine how e-cigarette coupons may impact racial minority groups that are not specified in this study.

Conclusions

This study used nationally representative longitudinal data to document the correlates of number of waves for which participants were exposed to e-cigarette coupons among US adults, and estimated prospective, and more importantly, dose-response associations between number of waves for which participants received e-cigarette coupons and progression of e-cigarette use behaviors. The results indicated that e-cigarette coupons encouraged e-cigarette use initiation, hindered e-cigarette use cessation, and promoted e-cigarette relapse, regardless of the individuals’ cigarette use status. These findings highlight an urgent need to implement stronger and more comprehensive policies regulating e-cigarette coupons.

Acknowledgements

The authors are grateful to National Addiction & HIV Data Archive Program (NAHDAP) for providing access to the Population Assessment of Tobacco and Health (PATH) Study Public-Use Files. Opinions and comments expressed are the authors’ own and do not necessarily reflect those of the funding agencies.

Drs. Hamilton-Moseley and Choi are supported by the Division of Intramural Research, National Institute on Minority Health and Health Disparities. Dr. Berg is supported by funding from the National Cancer Institute [grant numbers R01CA215155-01A1 to C.J.B., grant numbers R01CA239178-01A1 to C.J.B., R01CA179422-01 to C.J.B, R21CA261884-01A1 to C.J.B.); the Fogarty International Center [grant number R01TW010664-01 to C.J.B.]; the National Institute of Environmental Health Sciences/Fogarty [grant number D43ES030927-01 to C.J.B.]; and the National Institute on Drug Abuse [grant number R01DA054751-01A1 to C.J.B.]. Opinions and comments expressed are the authors’ own and do not necessarily reflect those of the funding agencies.

Footnotes

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Credit author statement

Zongshuan Duan: Writing-original draft, Writing – review & editing; Kristen R. Hamilton-Moseley: Conceptualization, Data curation, Formal Analysis, Validation, Writing- original draft, Writing – review & editing; Timothy S. McNeel: Methodology, Writing – review & editing; Carla J. Berg: Conceptualization, Supervision, Writing – review & editing; Kelvin Choi: Conceptualization, Methodology, Supervision, Writing – review & editing.

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