Abstract

Introduction

Electronic cigarettes (e-cigarettes) could benefit public health if they help current smokers to stop smoking long term, but evidence that they do so is limited. We aimed to determine the association between e-cigarette use and subsequent smoking cessation in a nationally representative cohort of US smokers followed for 2 years.

Methods

We analyzed data from adult cigarette smokers in Waves 1 through 3 of the Population Assessment of Tobacco and Health study. The primary exposure was e-cigarette use at Wave 1. The primary outcome was prolonged cigarette abstinence, defined as past 30-day cigarette abstinence at Waves 2 and 3 (1- and 2-year follow-up).

Results

Among Wave 1 cigarette smokers, 3.6% were current daily e-cigarette users, 18% were current non-daily e-cigarette users, and 78% reported no current e-cigarette use. In multivariable-adjusted analyses, daily e-cigarette use at Wave 1 was associated with higher odds of prolonged cigarette smoking abstinence at Waves 2 and 3 compared to nonuse of e-cigarettes (11% vs. 6%, adjusted odds ratio [AOR] = 1.77, 95% confidence interval [CI] = 1.08 to 2.89). Non-daily e-cigarette use was not associated with prolonged cigarette smoking abstinence. Among Wave 1 daily e-cigarette users who were abstinent from cigarette smoking at Wave 3, 63% were using e-cigarettes at Wave 3.

Conclusions

In this longitudinal cohort study of US adult cigarette smokers, daily but not non-daily e-cigarette use was associated with higher odds of prolonged cigarette smoking abstinence over 2 years, compared to no e-cigarette use. Daily use of e-cigarettes may help some smokers to stop smoking combustible cigarettes.

Implications

In this nationally representative longitudinal cohort study of US adult cigarette smokers, daily e-cigarette use, compared to no e-cigarette use, was associated with a 77% increased odds of prolonged cigarette smoking abstinence over the subsequent 2 years. Regular use of e-cigarettes may help some smokers to stop smoking combustible cigarettes.

Introduction

Electronic cigarettes (e-cigarettes) are novel nicotine-delivery devices that heat a nicotine-containing liquid, producing an aerosol that users inhale. Although e-cigarettes expose users to nicotine, they do not burn tobacco. Consequently, they expose users to fewer and lower levels of the many other chemicals found in tobacco smoke.1 It is these combustion products, rather than nicotine, that are the primary source of smoking-related morbidity and mortality.2 National evidence reviews from England and the United States have concluded that although e-cigarette use is not harmless, cigarette smokers who switch to e-cigarettes will likely reduce their smoking-attributable health risks.1,3

E-cigarettes therefore have the potential for substantial public health benefit if cigarette smokers, especially those who are unwilling or unable to quit using current treatments, switch to e-cigarettes and stop smoking combustible cigarettes. This potential benefit must be balanced against two potential harms. First, the long-term health effects of e-cigarette use are not known.1 Second, nonsmoking youths and young adults who would not otherwise have become cigarette smokers might try e-cigarettes, develop nicotine dependence, and transition to smoking combustible cigarettes. Modeling studies indicate that, under likely scenarios, e-cigarette use in the US population is likely to produce a net public health benefit.1,4 However, definitive information about the magnitude of the effect of e-cigarettes on cessation, initiation, and human health is not yet available. Recently, two national surveys reported a dramatic increase in e-cigarette use among US high school students in 2018.5,6 Whether this will lead to an increase in adolescent cigarette smoking is not yet known, but this concern makes even more urgent the need to better define both the potential public health benefits and risks of e-cigarette use.

A critical unanswered question about e-cigarettes’ potential public health benefit is whether the devices help smokers to stop smoking combustible cigarettes. Cigarette smokers commonly report using e-cigarettes in their attempts to quit smoking.7–9 In 2016, 52.5% of current smokers in the United States reported ever using e-cigarettes and 10.8% were current e-cigarette users.10 Clinical trial evidence that e-cigarettes promote smoking cessation is limited to three randomized trials,11–13 all of which were conducted outside of the United States. A Cochrane meta-analysis of two of these trials12,13 concluded that nicotine-containing e-cigarettes produced more smoking cessation than e-cigarettes without nicotine.14 In comparing the effectiveness of e-cigarettes to evidence-based cessation treatment, one trial found no difference in quitting between the two groups,12 whereas the other found significantly more cessation in the group receiving e-cigarettes compared to the group receiving nicotine replacement therapy.11

In the absence of clinical trials, nonexperimental observational studies provide the strongest available epidemiological evidence and have the advantage of demonstrating the effect of e-cigarettes under real-world conditions of use as widely available consumer products. Observational studies have had mixed results, in part because of variability in how current e-cigarette use was defined, in what devices were used, and in smokers’ motivation to quit.1 Among observational trials, those analyzing large population-based surveys provide the most generalizable evidence. Two nationally representative US surveys have found e-cigarette use to be associated with quit attempts and smoking cessation.8,15 These studies analyzed data from repeated cross-sectional samples of US adults rather than analyzing data from a cohort of individuals followed over time. In contrast, a prospective cohort study using a US population-based web-panel found that smokers who used e-cigarettes had a lower odds of having quit smoking at 1-year follow-up.16 These discrepant findings highlight the need for further research to explore the association of e-cigarettes and smoking cessation, ideally in larger samples and with longer follow-up.

The Population Assessment of Tobacco and Health (PATH) study provides a unique opportunity to assess whether e-cigarette use is associated with subsequent smoking cessation in a large nationally representative cohort of smokers being followed over time.17 Data from the third year of data collection, allowing for 2 years of follow-up, were recently released. We analyzed PATH data to assess the association between e-cigarette use at baseline and cigarette smoking abstinence after 2 years of follow-up. Specifically, we evaluated whether different frequencies of e-cigarette use at Wave 1 were associated with prolonged cigarette abstinence at Waves 2 and 3. In secondary analyses, we evaluated whether e-cigarette use at Wave 1 was associated with abstinence from Waves 1 to 2 and Waves 1 to 3. We hypothesized that more frequent e-cigarette use would be associated with prolonged cigarette abstinence.

Methods

Study Population

Data from Waves 1 through 3 of the PATH study, which has followed a longitudinal cohort of US adults and youth since 2013, were used for this study.17,18 Wave 1 data were collected from September 2013 to September 2014, Wave 2 data were collected from October 2014 to October 2015, and Wave 3 data were collected from October 2015 to October 2016. Participants identified through address-based sampling were surveyed about tobacco use using audio computer-assisted self-interviews. Although the PATH study collects data on both adults and youth, this analysis included only data from adults age 18 and older who were current cigarette smokers at Wave 1. We defined Wave 1 current cigarette smokers as adults who reported (1) smoking 100 or more cigarettes in their lifetime and (2) now using cigarettes every day or some days. The institutional review board of Westat approved the parent study. Only de-identified publicly available data were used for this study, and this study was deemed exempt by the institutional review board at Partners Healthcare.

Measures

Baseline demographics (measured at Wave 1) included age, sex, race/ethnicity, education, and income as a percentage of the federal poverty level.

To assess e-cigarette use, participants at Wave 1 were asked “Have you ever heard of an electronic cigarette or e-cigarette before this study?” and those who reported “yes” were asked “Have you ever used an e-cigarette, such as NJOY, Blu, or Smoking Everywhere, even one or two times?” Respondents who said yes were asked “Do you now use e-cigarettes…” with potential response options of “every day,” “some days,” or “not at all.” Current e-cigarette use was defined as reporting now using e-cigarettes every day or some days. Some-day e-cigarette users were further asked, “On how many of the past 30 days did you use an e-cigarette?” For analysis, we first dichotomized current e-cigarette users into non-daily (use on 0–29 days of the past 30 days) and daily users. In subsequent exploratory analyses, we recategorized frequency of past-month e-cigarette use into three groups based on the distribution of e-cigarette use frequency found at Wave 1: less than or equal to 9 days, 10–19 days, and 20–30 days.

Abstinence from cigarette smoking, the outcome measure, was defined by a “no” response to this question asked at both Waves 2 and 3, “In the past 30 days, have you smoked a cigarette, even one or two puffs?” The primary outcome measure was prolonged cigarette abstinence, assessed at both Waves 2 and 3. Secondary outcomes measures were cigarette abstinence at Wave 2 and cigarette abstinence at Wave 3. Relapse was defined as cigarette abstinence at Wave 2, but no abstinence at Wave 3.

Other covariates used in analyses included mean number of cigarettes per day, which we censored at the 99th percentile to reduce the impact of extreme outliers, and nicotine dependence, which was measured as smoking the first cigarette of the day within 30 minutes of waking.19 To examine the pattern of e-cigarette use over time, current e-cigarette use at Waves 2 and 3 was defined as now using any electronic nicotine delivery product (specifically e-cigarette, e-cigar, e-hookah, e-pipe, or other electronic nicotine product) every day or some days.

Statistical Analysis

We used complex survey procedures and replicate weights in Stata, version 14 for all analyses (StataCorp LLC, College Station, TX). The weighting accounted for selection probabilities and nonresponse rates. For the primary outcome, the study population was limited to adult respondents available at all three waves (unweighted n = 8218). For the secondary outcomes of abstinence at one wave, the study population of adult smokers was limited to respondents available at both Waves 1 and 2 (unweighted n = 9264) or at Waves 1 and 3 (unweighted n = 8575).

Multivariable logistic regression was used to evaluate the association between Wave 1 e-cigarette use and follow-up smoking abstinence. These analyses controlled for age (18–34 years, 35–54 years, and ≥55 years), sex, race/ethnicity (non-Hispanic white, Hispanic, non-Hispanic black, and non-Hispanic other), education (less than high school, high school diploma or General Education Diploma [GED], or some college, or 4 year college degree or more), income as a percentage of the federal poverty level (<100%, 100%–199%, or ≥200%), mean cigarettes per day, and nicotine dependence (first cigarette of the day ≤ or >30 minutes after waking). Only participants with complete data on study variables were included in the multivariable models.

Results

Among all adult current cigarette smokers at Wave 1, the weighted percentage of current e-cigarette use was 22% (95% confidence interval [CI] = 20% to 23%) Current daily e-cigarette use was reported by 3.6% (95% CI = 3.1% to 4.2%) and current non-daily e-cigarette use was reported by 18% (95% CI = 17% to 19%). The percentage reporting no current e-cigarette use was 78% (95% CI = 77% to 79%).

Characteristics of the sample by e-cigarette use at Wave 1 are shown in Table 1. Smokers who reported current daily or non-daily e-cigarette use were younger than smokers who reported not currently using e-cigarettes (Table 1). A higher percentage of current daily e-cigarette users had non-Hispanic white race/ethnicity. Current daily and non-daily e-cigarette users had higher education than smokers not currently using e-cigarettes. Groups also differed in cigarettes smoked per day, with current daily e-cigarette users reporting the lowest number of cigarettes per day.

Table 1.

Study Sample Characteristics by E-cigarette Use at Wave 1

Daily e-cig use
(N = 299)
% (95% CI)
Non-daily e-cig use
(N = 1523)
% (95% CI)
No current e-cig use
(N = 6379)
% (95% CI)
p
Age<.001
 18–3443 (37 to 50)46 (44 to 49)37 (36 to 38)
 45–5436 (29 to 43)39 (36 to 42)39 (38 to 41)
 ≥5521 (16 to 27)14 (12 to 17)24 (22 to 25)
Male sex59 (52 to 66)52 (50 to 55)55 (54 to 56).07
Race/ethnicity<.001
 Hispanic7 (4 to 10)11 (10 to 13)11 (10 to 12)
 Non-Hispanic white82 (77 to 86)74 (71 to 77)68 (67 to 70)
 Non-Hispanic black6 (4 to 10)8 (6 to 10)15 (14 to 16)
 Non-Hispanic other5 (3 to 8)7 (5 to 9)6 (5 to 6)
Education<.001
 Less than HS14 (11 to 19)12 (10 to 14)17 (16 to 18)
 HS or GED38 (31 to 45)35 (32 to 38)39 (38 to 41)
 Some college36 (29 to 43)39 (37 to 42)33 (32 to 34)
 4-year college degree or higher12 (9 to 17)14 (12 to 15)11 (10 to 12)
Income as percentage of federal poverty level.32
 <100%36 (30 to 42)35 (33 to 38)38 (36 to 40)
 100%–199%26 (21 to 33)27 (25 to 30)28 (26 to 29)
 ≥200%38 (30 to 45)37 (34 to 40)34 (33 to 36)
Cigarettes per day, mean (SE)11.2 (0.7)14.2 (0.3)13.6 (0.2)<.001 (daily vs. non-daily and daily vs. no current use)
First cigarette within 30 mins of waking67 (60 to 72)62 (59 to 65)60 (58 to 61).06
Daily e-cig use
(N = 299)
% (95% CI)
Non-daily e-cig use
(N = 1523)
% (95% CI)
No current e-cig use
(N = 6379)
% (95% CI)
p
Age<.001
 18–3443 (37 to 50)46 (44 to 49)37 (36 to 38)
 45–5436 (29 to 43)39 (36 to 42)39 (38 to 41)
 ≥5521 (16 to 27)14 (12 to 17)24 (22 to 25)
Male sex59 (52 to 66)52 (50 to 55)55 (54 to 56).07
Race/ethnicity<.001
 Hispanic7 (4 to 10)11 (10 to 13)11 (10 to 12)
 Non-Hispanic white82 (77 to 86)74 (71 to 77)68 (67 to 70)
 Non-Hispanic black6 (4 to 10)8 (6 to 10)15 (14 to 16)
 Non-Hispanic other5 (3 to 8)7 (5 to 9)6 (5 to 6)
Education<.001
 Less than HS14 (11 to 19)12 (10 to 14)17 (16 to 18)
 HS or GED38 (31 to 45)35 (32 to 38)39 (38 to 41)
 Some college36 (29 to 43)39 (37 to 42)33 (32 to 34)
 4-year college degree or higher12 (9 to 17)14 (12 to 15)11 (10 to 12)
Income as percentage of federal poverty level.32
 <100%36 (30 to 42)35 (33 to 38)38 (36 to 40)
 100%–199%26 (21 to 33)27 (25 to 30)28 (26 to 29)
 ≥200%38 (30 to 45)37 (34 to 40)34 (33 to 36)
Cigarettes per day, mean (SE)11.2 (0.7)14.2 (0.3)13.6 (0.2)<.001 (daily vs. non-daily and daily vs. no current use)
First cigarette within 30 mins of waking67 (60 to 72)62 (59 to 65)60 (58 to 61).06

Missing data were 2% or fewer for all variables except income, for which 7% of data were missing. CI = confidence interval; GED = General Education Diploma; HS = high school.

Table 1.

Study Sample Characteristics by E-cigarette Use at Wave 1

Daily e-cig use
(N = 299)
% (95% CI)
Non-daily e-cig use
(N = 1523)
% (95% CI)
No current e-cig use
(N = 6379)
% (95% CI)
p
Age<.001
 18–3443 (37 to 50)46 (44 to 49)37 (36 to 38)
 45–5436 (29 to 43)39 (36 to 42)39 (38 to 41)
 ≥5521 (16 to 27)14 (12 to 17)24 (22 to 25)
Male sex59 (52 to 66)52 (50 to 55)55 (54 to 56).07
Race/ethnicity<.001
 Hispanic7 (4 to 10)11 (10 to 13)11 (10 to 12)
 Non-Hispanic white82 (77 to 86)74 (71 to 77)68 (67 to 70)
 Non-Hispanic black6 (4 to 10)8 (6 to 10)15 (14 to 16)
 Non-Hispanic other5 (3 to 8)7 (5 to 9)6 (5 to 6)
Education<.001
 Less than HS14 (11 to 19)12 (10 to 14)17 (16 to 18)
 HS or GED38 (31 to 45)35 (32 to 38)39 (38 to 41)
 Some college36 (29 to 43)39 (37 to 42)33 (32 to 34)
 4-year college degree or higher12 (9 to 17)14 (12 to 15)11 (10 to 12)
Income as percentage of federal poverty level.32
 <100%36 (30 to 42)35 (33 to 38)38 (36 to 40)
 100%–199%26 (21 to 33)27 (25 to 30)28 (26 to 29)
 ≥200%38 (30 to 45)37 (34 to 40)34 (33 to 36)
Cigarettes per day, mean (SE)11.2 (0.7)14.2 (0.3)13.6 (0.2)<.001 (daily vs. non-daily and daily vs. no current use)
First cigarette within 30 mins of waking67 (60 to 72)62 (59 to 65)60 (58 to 61).06
Daily e-cig use
(N = 299)
% (95% CI)
Non-daily e-cig use
(N = 1523)
% (95% CI)
No current e-cig use
(N = 6379)
% (95% CI)
p
Age<.001
 18–3443 (37 to 50)46 (44 to 49)37 (36 to 38)
 45–5436 (29 to 43)39 (36 to 42)39 (38 to 41)
 ≥5521 (16 to 27)14 (12 to 17)24 (22 to 25)
Male sex59 (52 to 66)52 (50 to 55)55 (54 to 56).07
Race/ethnicity<.001
 Hispanic7 (4 to 10)11 (10 to 13)11 (10 to 12)
 Non-Hispanic white82 (77 to 86)74 (71 to 77)68 (67 to 70)
 Non-Hispanic black6 (4 to 10)8 (6 to 10)15 (14 to 16)
 Non-Hispanic other5 (3 to 8)7 (5 to 9)6 (5 to 6)
Education<.001
 Less than HS14 (11 to 19)12 (10 to 14)17 (16 to 18)
 HS or GED38 (31 to 45)35 (32 to 38)39 (38 to 41)
 Some college36 (29 to 43)39 (37 to 42)33 (32 to 34)
 4-year college degree or higher12 (9 to 17)14 (12 to 15)11 (10 to 12)
Income as percentage of federal poverty level.32
 <100%36 (30 to 42)35 (33 to 38)38 (36 to 40)
 100%–199%26 (21 to 33)27 (25 to 30)28 (26 to 29)
 ≥200%38 (30 to 45)37 (34 to 40)34 (33 to 36)
Cigarettes per day, mean (SE)11.2 (0.7)14.2 (0.3)13.6 (0.2)<.001 (daily vs. non-daily and daily vs. no current use)
First cigarette within 30 mins of waking67 (60 to 72)62 (59 to 65)60 (58 to 61).06

Missing data were 2% or fewer for all variables except income, for which 7% of data were missing. CI = confidence interval; GED = General Education Diploma; HS = high school.

Among smokers, current daily e-cigarette use at Wave 1 was associated with higher odds of prolonged cigarette smoking abstinence at both Waves 2 and 3 compared to no current e-cigarette use (11% vs. 6%, adjusted odds ratio [AOR] = 1.77, 95% CI = 1.08 to 2.89, p = .02; Tables 2 and 3). There was no statistically significant association between non-daily e-cigarette use and prolonged cigarette smoking abstinence. Income below the federal poverty level, a higher number of cigarettes per day, and high nicotine dependence were all negatively associated with prolonged cigarette smoking abstinence (Table 3).

Table 2.

Cigarette Abstinence at Follow-up by E-cigarette Use at Wave 1

Prolonged cigarette abstinence at Waves 2 and 3Cigarette abstinence at Wave 2Cigarette abstinence at Wave 3
Wave 1 e-cigarette use statusNWeighted %NWeighted %NWeighted %
No current e-cigarette use3666 (5–7)67210 (9–11)85213 (12–14)
Current non-daily e-cigarette use816 (5–7)15010 (8–11)19212 (10–14)
Current daily e-cigarette use3111 (7–16)5114 (11–20)6121 (17–27)
Prolonged cigarette abstinence at Waves 2 and 3Cigarette abstinence at Wave 2Cigarette abstinence at Wave 3
Wave 1 e-cigarette use statusNWeighted %NWeighted %NWeighted %
No current e-cigarette use3666 (5–7)67210 (9–11)85213 (12–14)
Current non-daily e-cigarette use816 (5–7)15010 (8–11)19212 (10–14)
Current daily e-cigarette use3111 (7–16)5114 (11–20)6121 (17–27)
Table 2.

Cigarette Abstinence at Follow-up by E-cigarette Use at Wave 1

Prolonged cigarette abstinence at Waves 2 and 3Cigarette abstinence at Wave 2Cigarette abstinence at Wave 3
Wave 1 e-cigarette use statusNWeighted %NWeighted %NWeighted %
No current e-cigarette use3666 (5–7)67210 (9–11)85213 (12–14)
Current non-daily e-cigarette use816 (5–7)15010 (8–11)19212 (10–14)
Current daily e-cigarette use3111 (7–16)5114 (11–20)6121 (17–27)
Prolonged cigarette abstinence at Waves 2 and 3Cigarette abstinence at Wave 2Cigarette abstinence at Wave 3
Wave 1 e-cigarette use statusNWeighted %NWeighted %NWeighted %
No current e-cigarette use3666 (5–7)67210 (9–11)85213 (12–14)
Current non-daily e-cigarette use816 (5–7)15010 (8–11)19212 (10–14)
Current daily e-cigarette use3111 (7–16)5114 (11–20)6121 (17–27)
Table 3.

Factors Associated with Cigarette Abstinence at Follow-up

Prolonged cigarette abstinence at Waves 2 and 3
AOR (95% CI)
Cigarette abstinence at Wave 2
AOR (95% CI)
Cigarette abstinence at Wave 3
AOR (95% CI)
Current e-cigarette use at Wave 1
 NoneRefRefRef
 Non-daily1.16 (0.84 to 1.61)1.07 (0.84 to 1.37)1.02 (0.80 to 1.28)
 Daily1.77 (1.08 to 2.89)*1.53 (1.04 to 2.23)*1.57 (1.12 to 2.21)*
Age
 18–340.69 (0.50 to 0.95)*0.86 (0.68 to 1.09)0.97 (0.78 to 1.21)
 45–540.74 (0.53 to 1.04)0.80 (0.60 to 1.06)0.90 (0.72 to 1.12)
 ≥55RefRefRef
Male sex1.19 (0.96 to 1.47)1.05 (0.90 to 1.23)1.33 (1.14 to 1.55)***
Race/ethnicity
 Non-Hispanic whiteRefRefRef
 Hispanic1.24 (0.87 to 1.78)1.23 (0.95 to 1.59)1.05 (0.81 to 1.35)
 Non-Hispanic black0.87 (0.57 to 1.31)0.83 (0.63 to 1.11)0.86 (0.65 to 1.14)
 Non-Hispanic other1.51 (0.92 to 2.49)1.12 (0.74 to 1.68)1.19 (0.87 to 1.65)
Education
 Less than HS1.05 (0.61 to 1.81)1.03 (0.72 to 1.47)0.83 (0.57 to 1.19)
 HS or GED1.10 (0.74 to 1.63)0.91 (0.68 to 1.21)0.84 (0.63 to 1.11)
 Some college1.07 (0.72 to 1.58)0.98 (0.77 to 1.23)1.00 (0.77 to 1.29)
 4-year college degree or higherRefRefRef
Income as percentage of federal poverty level
 <100%0.53 (0.40 to to 0.70)***0.68 (0.54 to 0.85)**0.71 (0.58 to 0.86)**
 100–199%0.72 (0.56 to 0.93)*0.85 (0.70 to 1.04)0.84 (0.68 to 1.04)
 ≥200%RefRefRef
Cigarettes per day0.93 (0.90 to 0.95)***0.94 (0.93 to 0.96)***0.95 (0.93 to 0.96)***
First cigarette within 30 mins of waking0.73 (0.55 to 0.98)*0.69 (0.57 to 0.85)***0.72 (0.59 to 0.87)**
Prolonged cigarette abstinence at Waves 2 and 3
AOR (95% CI)
Cigarette abstinence at Wave 2
AOR (95% CI)
Cigarette abstinence at Wave 3
AOR (95% CI)
Current e-cigarette use at Wave 1
 NoneRefRefRef
 Non-daily1.16 (0.84 to 1.61)1.07 (0.84 to 1.37)1.02 (0.80 to 1.28)
 Daily1.77 (1.08 to 2.89)*1.53 (1.04 to 2.23)*1.57 (1.12 to 2.21)*
Age
 18–340.69 (0.50 to 0.95)*0.86 (0.68 to 1.09)0.97 (0.78 to 1.21)
 45–540.74 (0.53 to 1.04)0.80 (0.60 to 1.06)0.90 (0.72 to 1.12)
 ≥55RefRefRef
Male sex1.19 (0.96 to 1.47)1.05 (0.90 to 1.23)1.33 (1.14 to 1.55)***
Race/ethnicity
 Non-Hispanic whiteRefRefRef
 Hispanic1.24 (0.87 to 1.78)1.23 (0.95 to 1.59)1.05 (0.81 to 1.35)
 Non-Hispanic black0.87 (0.57 to 1.31)0.83 (0.63 to 1.11)0.86 (0.65 to 1.14)
 Non-Hispanic other1.51 (0.92 to 2.49)1.12 (0.74 to 1.68)1.19 (0.87 to 1.65)
Education
 Less than HS1.05 (0.61 to 1.81)1.03 (0.72 to 1.47)0.83 (0.57 to 1.19)
 HS or GED1.10 (0.74 to 1.63)0.91 (0.68 to 1.21)0.84 (0.63 to 1.11)
 Some college1.07 (0.72 to 1.58)0.98 (0.77 to 1.23)1.00 (0.77 to 1.29)
 4-year college degree or higherRefRefRef
Income as percentage of federal poverty level
 <100%0.53 (0.40 to to 0.70)***0.68 (0.54 to 0.85)**0.71 (0.58 to 0.86)**
 100–199%0.72 (0.56 to 0.93)*0.85 (0.70 to 1.04)0.84 (0.68 to 1.04)
 ≥200%RefRefRef
Cigarettes per day0.93 (0.90 to 0.95)***0.94 (0.93 to 0.96)***0.95 (0.93 to 0.96)***
First cigarette within 30 mins of waking0.73 (0.55 to 0.98)*0.69 (0.57 to 0.85)***0.72 (0.59 to 0.87)**

Boldface indicates statistical significance. Multivariable logistic regression models controlled for age, race/ethnicity, sex, education, income, cigarettes per day, and time to first morning cigarette. CI = confidence interval; GED = General Education Diploma; HS = high school.

*p < .05, **p < .01, ***p < .001.

Table 3.

Factors Associated with Cigarette Abstinence at Follow-up

Prolonged cigarette abstinence at Waves 2 and 3
AOR (95% CI)
Cigarette abstinence at Wave 2
AOR (95% CI)
Cigarette abstinence at Wave 3
AOR (95% CI)
Current e-cigarette use at Wave 1
 NoneRefRefRef
 Non-daily1.16 (0.84 to 1.61)1.07 (0.84 to 1.37)1.02 (0.80 to 1.28)
 Daily1.77 (1.08 to 2.89)*1.53 (1.04 to 2.23)*1.57 (1.12 to 2.21)*
Age
 18–340.69 (0.50 to 0.95)*0.86 (0.68 to 1.09)0.97 (0.78 to 1.21)
 45–540.74 (0.53 to 1.04)0.80 (0.60 to 1.06)0.90 (0.72 to 1.12)
 ≥55RefRefRef
Male sex1.19 (0.96 to 1.47)1.05 (0.90 to 1.23)1.33 (1.14 to 1.55)***
Race/ethnicity
 Non-Hispanic whiteRefRefRef
 Hispanic1.24 (0.87 to 1.78)1.23 (0.95 to 1.59)1.05 (0.81 to 1.35)
 Non-Hispanic black0.87 (0.57 to 1.31)0.83 (0.63 to 1.11)0.86 (0.65 to 1.14)
 Non-Hispanic other1.51 (0.92 to 2.49)1.12 (0.74 to 1.68)1.19 (0.87 to 1.65)
Education
 Less than HS1.05 (0.61 to 1.81)1.03 (0.72 to 1.47)0.83 (0.57 to 1.19)
 HS or GED1.10 (0.74 to 1.63)0.91 (0.68 to 1.21)0.84 (0.63 to 1.11)
 Some college1.07 (0.72 to 1.58)0.98 (0.77 to 1.23)1.00 (0.77 to 1.29)
 4-year college degree or higherRefRefRef
Income as percentage of federal poverty level
 <100%0.53 (0.40 to to 0.70)***0.68 (0.54 to 0.85)**0.71 (0.58 to 0.86)**
 100–199%0.72 (0.56 to 0.93)*0.85 (0.70 to 1.04)0.84 (0.68 to 1.04)
 ≥200%RefRefRef
Cigarettes per day0.93 (0.90 to 0.95)***0.94 (0.93 to 0.96)***0.95 (0.93 to 0.96)***
First cigarette within 30 mins of waking0.73 (0.55 to 0.98)*0.69 (0.57 to 0.85)***0.72 (0.59 to 0.87)**
Prolonged cigarette abstinence at Waves 2 and 3
AOR (95% CI)
Cigarette abstinence at Wave 2
AOR (95% CI)
Cigarette abstinence at Wave 3
AOR (95% CI)
Current e-cigarette use at Wave 1
 NoneRefRefRef
 Non-daily1.16 (0.84 to 1.61)1.07 (0.84 to 1.37)1.02 (0.80 to 1.28)
 Daily1.77 (1.08 to 2.89)*1.53 (1.04 to 2.23)*1.57 (1.12 to 2.21)*
Age
 18–340.69 (0.50 to 0.95)*0.86 (0.68 to 1.09)0.97 (0.78 to 1.21)
 45–540.74 (0.53 to 1.04)0.80 (0.60 to 1.06)0.90 (0.72 to 1.12)
 ≥55RefRefRef
Male sex1.19 (0.96 to 1.47)1.05 (0.90 to 1.23)1.33 (1.14 to 1.55)***
Race/ethnicity
 Non-Hispanic whiteRefRefRef
 Hispanic1.24 (0.87 to 1.78)1.23 (0.95 to 1.59)1.05 (0.81 to 1.35)
 Non-Hispanic black0.87 (0.57 to 1.31)0.83 (0.63 to 1.11)0.86 (0.65 to 1.14)
 Non-Hispanic other1.51 (0.92 to 2.49)1.12 (0.74 to 1.68)1.19 (0.87 to 1.65)
Education
 Less than HS1.05 (0.61 to 1.81)1.03 (0.72 to 1.47)0.83 (0.57 to 1.19)
 HS or GED1.10 (0.74 to 1.63)0.91 (0.68 to 1.21)0.84 (0.63 to 1.11)
 Some college1.07 (0.72 to 1.58)0.98 (0.77 to 1.23)1.00 (0.77 to 1.29)
 4-year college degree or higherRefRefRef
Income as percentage of federal poverty level
 <100%0.53 (0.40 to to 0.70)***0.68 (0.54 to 0.85)**0.71 (0.58 to 0.86)**
 100–199%0.72 (0.56 to 0.93)*0.85 (0.70 to 1.04)0.84 (0.68 to 1.04)
 ≥200%RefRefRef
Cigarettes per day0.93 (0.90 to 0.95)***0.94 (0.93 to 0.96)***0.95 (0.93 to 0.96)***
First cigarette within 30 mins of waking0.73 (0.55 to 0.98)*0.69 (0.57 to 0.85)***0.72 (0.59 to 0.87)**

Boldface indicates statistical significance. Multivariable logistic regression models controlled for age, race/ethnicity, sex, education, income, cigarettes per day, and time to first morning cigarette. CI = confidence interval; GED = General Education Diploma; HS = high school.

*p < .05, **p < .01, ***p < .001.

The association of e-cigarette use at Wave 1 with secondary outcomes was similar. Current daily e-cigarette use at Wave 1, compared to nonuse of e-cigarettes, was associated with higher odds of abstinence from cigarette smoking at both Wave 2 (p = .03) and Wave 3 (p = .01; Table 3). Non-daily e-cigarette use did not significantly increase odds of cigarette smoking abstinence compared to nonuse of e-cigarettes. Males had higher odds of abstinence from cigarettes at Wave 3 (Table 3). Income below the federal poverty level, high nicotine dependence, and a higher number of cigarettes smoked per day at Wave 1 were negatively associated with cigarette abstinence at Waves 2 and 3.

Smoking relapse between Waves 2 and 3 was seen in 4.4% of current daily e-cigarette users at Wave 1, 3.2% of non-daily e-cigarette users at Wave 1, and 3.3% of nonusers of e-cigarettes Wave 1 (p = .62, data not shown in tables). Neither daily nor non-daily e-cigarette use associated with cigarette smoking relapse between Waves 2 and 3 in multivariable logistic regression models (AOR = 1.41, 95% CI = 0.76 to 2.61 for daily use; AOR = 1.07, 95% CI = 0.73 to 1.58 for non-daily use).

In exploratory analyses that categorized current e-cigarette use into three groups, current e-cigarette use on 20 or more days per month at Wave 1 was associated with a higher odds of prolonged cigarette smoking abstinence at both Waves 2 and 3 (AOR = 1.60, 95% CI = 1.05 to 2.43, data not shown in tables). Less frequent e-cigarette use at Wave 1 was not significantly associated with prolonged abstinence (AOR = 1.07, 95% CI = 0.74 to 1.55 for ≤9 days of e-cigarette use; AOR = 1.84, 95% CI = 0.88 to 3.83 for 10–19 days of e-cigarette use; data not shown in tables).

Among Wave 1 current daily e-cigarette users who were abstinent from cigarette smoking at Wave 3, 63% were using e-cigarettes at Wave 3. Among Wave 1 current non-daily e-cigarette users who were abstinent from cigarette smoking at Wave 3, 31% were using e-cigarettes at Wave 3. Among Wave 1 current nonusers of e-cigarettes who were abstinent from cigarette smoking at Wave 3, 13% were using e-cigarettes at Wave 3.

Discussion

In this nationally representative longitudinal cohort study of US adult cigarette smokers, daily e-cigarette use, compared to no e-cigarette use, was associated with a 77% increased odds of prolonged cigarette smoking abstinence over the subsequent 2 years. Non-daily e-cigarette use was not associated with subsequent abstinence. These are the first nationally representative cohort study data to show an association between e-cigarette use and sustained combustible cigarette abstinence rates over 2 years. These results are consistent with the hypothesis that when used daily, e-cigarettes may help smokers to stop smoking combustible cigarettes, but that less frequent e-cigarette use may not do so.

The study results are consistent with findings of previous cross-sectional studies that also found an association between more frequent e-cigarette use and smoking cessation. For example, a population-based study using cross-sectional data from the 2014–2015 Tobacco Use Supplement-Current Population Survey found that a higher number of days of e-cigarette use in the last 30 days was associated with higher odds of both making a cigarette quit attempt and successfully quitting among attempters.20 In another study using data from two US cities, daily e-cigarette use for at least 1 month was associated with a higher odds of quitting smoking 2–3 years later.21 Two longitudinal studies using cohort data from only Waves 1 and 2 of the PATH study found results similar to ours.22,23 One study found daily e-cigarette use at Wave 1 to be associated with smoking cessation after 1 year.23 Another found that initiation of e-cigarette use by Wave 2 among nonusers at Wave 1 was associated with smoking cessation at Wave 2.22 This study expands on these findings by including data from Wave 3 of the PATH study and showing an association between daily e-cigarette use and prolonged cigarette abstinence over 2 years. This is a key observation because of concerns that former smokers using e-cigarettes may be more likely to relapse.23,24

One explanation for the difference in cigarette smoking abstinence among daily and non-daily e-cigarette users may be that these groups differ in their reasons for e-cigarette use,25 such that cessation may be a less common reason for use among non-daily e-cigarette users. They may be aiming to reduce harm from cigarettes without committing to total abstinence. Another explanation may be that non-daily e-cigarette use is unlikely to completely control symptoms of nicotine withdrawal in daily cigarette users with high levels of nicotine dependence, and therefore these smokers will continue cigarette use to manage cravings and withdrawal.

In contrast to our findings, several prior observational studies examining the relationship between e-cigarette use and cigarette abstinence found that e-cigarette use was associated with a lower likelihood of successful cessation.26 This is likely because of heterogeneity in the way that these prior studies defined current e-cigarette use. Our findings suggest that combining daily and non-daily e-cigarette users is likely to underestimate the association between e-cigarette use and subsequent cigarette abstinence and may miss differences in smoking abstinence among subgroups of e-cigarette users. Observational studies should account for the frequency of e-cigarette use when evaluating the association between e-cigarette use and cigarette smoking abstinence. A recent longitudinal cohort study conducted during the same years as Wave 3 of the PATH study reported different findings from ours.16 In that study, smokers who used e-cigarettes at baseline had a lower adjusted odds of cigarette abstinence 1 year later than baseline e-cigarette nonusers. The smaller sample size of this study compared to PATH may have limited the statistical power to find an effect. It also differed from PATH in obtaining data from a web-based panel.16

Nearly 40% of the current smokers at Wave 1 who used e-cigarettes (and 63% of the smokers who used e-cigarettes daily) and were abstinent from combustible cigarettes at Wave 3 were still using e-cigarettes at Wave 3. This may explain why other nationally representative surveys have found that daily e-cigarette use is most prevalent among former smokers who quit smoking within the past year.27 A cross-sectional study in the United Kingdom found that former smokers who used e-cigarettes for at least 6 months significantly reduced their exposure to many of the toxins and carcinogens in combustible cigarettes.28 Smokers who transition completely from combustible cigarettes and maintain e-cigarette use likely reduce their tobacco-related health risks.1,3 Because the long-term health effects of using e-cigarettes remain unknown, to minimize potential harms from e-cigarette use, smokers who use e-cigarettes to successfully quit smoking might be encouraged to aim to quit e-cigarette use as well, but only when they are confident that they can do so without returning to smoking.29

This study has several limitations. First, bias from unmeasured confounders is a limitation in any observational study. Self-selection bias is a potential limitation of this study if the smokers who chose to use e-cigarettes daily were more likely to quit for another reason. Our analyses controlled for multiple demographic factors and for nicotine dependence but could not adjust for factors such as motivation to quit or confidence in ability to quit because of the PATH survey question structure. Second, all data, including those on cigarette abstinence, were obtained by participant self-report and were not biochemically verified, introducing the possibility of social desirability bias. However, guidelines do not consider biochemical validation needed for large population or observational studies that do not include smoking cessation interventions.30 Third, Wave 1 of the PATH study only asked about use of e-cigarettes and may have underestimated the total prevalence of other electronic nicotine delivery system use if respondents did not know that a product they were using was an e-cigarette. This has been shown in studies of youth.31 Whether the same is true in adults is not known, but misclassification should bias results toward accepting the null hypothesis. Fourth, the exact timing of e-cigarette use in relation to stopping smoking is not known. Participants who were both smoking and using e-cigarettes at Wave 1 may have stopped using e-cigarettes before quitting cigarette smoking. Finally, smokers who used e-cigarettes at baseline might also have used smoking cessation pharmacotherapies approved by the US Food and Drug Administration, such as nicotine replacement therapy, varenicline, or bupropion. In our analyses, we were not able to adjust for use of these products because of limitations in the way in which these questions were asked on the PATH survey.

Conclusions

Smokers in this large nationally representative longitudinal study who used e-cigarettes daily were more likely to be abstinent from combustible cigarettes after 2 years compared to smokers who did not use e-cigarettes. Further defining the potential public health benefit that e-cigarettes could offer in terms of smoking cessation will require randomized controlled trials, but these observational data suggest that frequent e-cigarette use is associated with subsequent abstinence from combustible tobacco products.

Funding

This study was supported by the National Heart, Lung, and Blood Institute (NHLBI) of the National Institutes of Health (K23HL136854 to Dr. Kalkhoran). The funding source had no role in the study design; in the collection, analysis, and interpretation of the data; in the writing of the report; and in the decision to submit the manuscript for publication.

Declaration of Interests

Drs. Rigotti and Kalkhoran receive royalties from UpToDate, Dr. Rigotti has been an unpaid consultant to Pfizer, and a paid consultant to Achieve Life Sciences. Dr. Chang has no conflicts of interest to disclose.

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Comments

1 Comment
The effect of daily e-cigarette use on smoking abstinence: Smoking out exaggerated statistics
8 August 2019
James D Sargent MD1; Steven Woloshin MD2
1 C Everett Koop Institute at Dartmouth; 2 Lisa Schwartz Foundation for Truth in Medicine
In their study entitled, Electronic Cigarette Use and Cigarette Abstinence Over 2 Years Among US Smokers in the Population Assessment of Tobacco and Health Study, Kalkhoran and co-authors concluded, “daily e-cigarette use, compared to no e-cigarette use, was associated with a 77% increased odds of prolonged cigarette smoking abstinence over the subsequent 2 years.” The statement was based on an odds ratio of 1.77, comparing the chances a cigarette smoker who used e-cigarettes daily would achieve prolonged abstinence compared to one who does not use e-cigarettes at all.

Seventy seven percent increase—sounds big—so much so that this was one of the studies cited when e-cigarette proponents testified recently on Capitol Hill to argue against more stringent regulation of the industry. Unfortunately, this conclusion greatly overstates the public health implications of e-cigarettes on smoking abstinence documented by this study.

Why is the conclusion overstated? Because the “77% increased odds” is a relative measure. The “77%” is only meaningful if you know the answer to, “77% of what?” It is like a sale in a store. “77% off” sounds good. But understanding whether this sale translates into meaningful savings depends on how much the items cost to begin with (consider 77% off a $100 item vs. off a $0.50 item).
In this case, the absolute difference1 was just 5 percentage points (the two-year abstinence rate was 11% among daily e-cigarette users vs. 6% for cigarette smokers who did not use e-cigarettes). Moreover, that 5 percentage point absolute difference should be interpreted with caution, since daily e-cigarette users are probably more motivated to quit smoking anyway.

The public health implications of the findings seem quite modest. Only 3.6% of smokers in the study were daily e-cigarette users, suggesting a very limited appeal of these products among current adult cigarette smokers, most of whom were using e-cigarettes to get some nicotine in places they couldn’t smoke. At the population level, low prevalence of daily e-cigarette use means that, even under the most optimistic of assumptions (i.e., e-cigarettes caused all 5% difference), e-cigarettes helped just 18 out of 1000 smokers achieve prolonged abstinence over 2 years (3.6%*5%=0.18%).

In summary, it is hard to imagine how this 77% increase will affect population rates of cigarette smoking or make up for the harm these products are causing in the adolescent-young adult population. One wonders how the number of smokers who benefitted from e-cigarette use compares to the number who achieved prolonged abstinence through use of nicotine replacement—products which have little appeal among youth.

1.   Woloshin S, Schwartz LM, Welch HG. Know Your Chances. Understanding Health Statistics. University of California Press, Berkley CA. www.ncbi.nlm.nih.gov/books/NBK115435. 
Submitted on 08/08/2019 2:34 PM GMT
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