Public Health Consequences of E-Cigarettes (2018) / Chapter Skim
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16 Combustible Tobacco Cigarette Smoking Among Youth and Young Adults
16 Combustible Tobacco Cigarette Smoking Among Youth and Young Adults
Pages 493-540
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From page 493... ...
. About one-third to one-half of youth and young adult e-cigarette users report no history of regular combustible tobacco product use (CDC, 2016; HHS, 2016)
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CONCEPTUAL FRAMEWORK: PATTERNS OF USE AMONG YOUTH AND YOUNG ADULTS Among the population of teens and young adults with no history of smoking, several possible transitions in combustible tobacco use behavior may occur as a result of e-cigarette use. To illustrate this, the overarching tobacco product transitions conceptual model posed in Figure 16-1 has been adapted to address the possible effects of e-cigarette use on combustible tobacco cigarette use among adolescents and young adults with no history of cigarette smoking.
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From page 495... ...
. Transition 1: Among Adolescents and Young Adults with No History of Combustible Tobacco Use, Does E-Cigarette Use Affect Risk of Combustible Tobacco Cigarette Ever Use?
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From page 496... ...
These ways are discussed in the paragraphs below. Preventive Effect E-cigarette use could have a preventive effect that deters ever combustible tobacco cigarette use (i.e., probability of transition is lower for Path 2a than 2b, holding all external confounds constant)
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Second, the exposure to e-cigarettes in this group is suspected to increase proclivity to try combustible tobacco cigarettes (Schneider and Diehl, 2016) for several reasons: (1)
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The "common liability" hypothesis proposes that youth who use e-cigarettes and then transition to combustible tobacco cigarettes are overrepresented by teens with a preference for exploring novel experiences (Etter, 2017; Kozlowski and Warner, 2017)
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due to nicotine-induced neurobiological changes (Lydon et al., 2014) , which would enhance the first few combustible tobacco cigarette smoking experiences.
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If these factors are associated with both e-cigarette use and combustible tobacco cigarette smoking initiation and are not in the causal pathway, they could statistically bias the study results and create a spurious effect of e-cigarette use on a combustible tobacco cigarette use outcome. For example, if e-cigarettes attract youth who already have a strong interest in smoking, then e-cigarette use may serve as an indicator of an underlying proclivity to smoke rather than playing a causal role in cigarette initiation.
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Among observational study designs, longitudinal studies were considered stronger evidence compared with cross-sectional studies. Given the high plausibility of reverse causality such that combustible tobacco cigarette smoking may also impact e-cigarette use, longitudinal cohort studies that assessed e-cigarette use at baseline and smoking at a future follow-up assessment would provide the strongest evidence to rule out potential reverse causality.
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502 PUBLIC HEALTH CONSEQUENCES OF E-CIGARETTES TABLE 16-1 INITIATION: Summary of Prospective Cohort Studies of the Association Between Ever Use of E-Cigarettes (Versus Never Use) and Subsequent Risk of Ever Smoking of Combustible Tobacco Cigarettes Among Youth/Young Adults Who Were Non-Smokers at Baseline Cohort Age Follow-Up Reference Location Cohort Size at Baseline Duration Barrington- Southern 298 Median = Mean = Trimis et al., California, 17.4 years 16 months 2016a USA Best et al., 2017 Scotland, UK 2,125 11–18 years 12 months Conner et al., England, UK 1,726 13–14 years 12 months 2017 Leventhal et al., Los Angeles, CA, 2,530 never Mean = 12 months 2015 USA users of any 14 years combustible tobacco product at baseline Loukas et al., Texas, USA 2,558 Mean = 18 months 2018 (24 colleges)
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COMBUSTIBLE TOBACCO CIGARETTE SMOKING AMONG YOUTH 503 Measurement Tobacco OR; 95% E-Cigarettea Cigaretteb CIc,d Adjustments Ever use Ever use 5.48; Sex, ethnicity, grade, parental 2.69–11.2 education, and use of hookah, cigar, or pipe at baseline Ever use Ever use 2.42; Age, sex, SES, ethnic group, school, 1.63–3.60 smoking susceptibility, peer and family smoking status Ever use Ever use 4.06; Age, sex, SES, ethnic group, school, 2.94–5.60 smoking susceptibility, peer and family smoking status Ever use Past 6-month 1.75; Age, sex, ethnicity, parental use at 1.10–2.77 education, family living situation, 6-month and peer and family smoking, smoking 12-month susceptibility, smoking expectancies, follow-ups impulsivity, depression, substance use, delinquent behavior Ever use Ever use Overall Age, sex, race/ethnicity, school, sample: 1.36; smoking susceptibility, peer smoking, 1.01–1.83. family-of-origin tobacco use, other Among tobacco use baseline never users of any tobacco product: 2.26; CI = 1.35–3.76 Ever use Past 12 4.78; 1.91– Sex, race, baseline marijuana use and months 11.96 binge drinking Ever use Ever use 8.3; 1.2–58.6 Age, sex, race/ethnicity, maternal education, peer and parental smoking, sensation-seeking tendency Ever use Ever use 6.8; 1.2–58.6 Age, sex, race/ethnicity, relationship status, living situation, education, self-esteem, sensation seeking, rebelliousness continued
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c Comparing incidence of combustible tobacco cigarette smoking in baseline users of e cigarettes compared with the referent category of baseline non-users of e-cigarettes (OR = 1.0)
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NOTE: OR = odds ratio; SES = socioeconomic status. Measurement Tobacco OR, IRR, β; E-Cigarettea Cigaretteb 95% CIc,d Adjustments Ever use Past 30-day use OR = 7.50; Sex, ethnicity, grade, parental 2.41–23.4 education, and use of hookah, cigar, or pipe at baseline Ever use Increased use OR = 1.89; Age, sex, SES, ethnic group, of cigarettes 0.82–4.33 school, smoking susceptibility, at follow-up peer and family smoking status among baseline ever users Frequency Total cigarettes At first A propensity score accounting in past 6 smoked follow-up: for sex, race/ethnicity, student months IRR = 1.13; status, significant other who 1.06–1.21 smoked, smokers in participant's Interaction household, intent to quit with time: IRR = 1.16; 1.09–1.23 continued
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b Dependent variable. c Extent of tobacco cigarette smoking in baseline users of e-cigarettes conditional on e cigarette use.
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1.31 expectancies, ever use of alcohol or Prior = ever Smoking Intensity drugs, ever use of any combustible use, but no intensity proportional tobacco product, depression, use in past (cigarettes odds: OR = lack of premeditation, sensation 30 days. per day on 1.26; 1.07– seeking, delinquent behavior Infrequent = smoking days)
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c Comparing incidence of tobacco cigarette smoking in baseline users of e-cigarettes com pared with the referent category of baseline non-users of e-cigarettes (OR = 1.0)
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frequency in smoking frequency household structure, Prior = ever past 30 days: level versus never use parental education, peer use, but no 0 days, of e-cigarettes: and family smoking, use in past 1–2 days, 3 or Prior user = 1.51; 95% smoking susceptibility, 30 days. more days.
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Instead, studies that include more detailed measures of smoking frequency that distinguish among monthly, weekly, and daily use and smoking intensity that identify the number of cigarettes smoked per smoking day were considered to provide stronger evidence to address smoking progression. Among studies including only two time points that addressed smoking progression, those that did not eliminate baseline ever smokers and used an alternate strategy for addressing reverse causation (e.g., statistical adjustment of baseline combustible tobacco use, elimination of baseline current combustible tobacco users without eliminating baseline past combustible tobacco users)
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In such research, results consistent with the diversion hypothesis that e-cigarette use prevents ever smoking and smoking progression would demonstrate that there would be a negative association between e-cigarette use and smoking that becomes stronger in higher (versus lower) risk youth in stratified analyses whereby the e-cigarette– combustible tobacco cigarette association is estimated in subgroups differing in level of liability for smoking captured by other moderator variables outside of the causal pathway (e.g., rebelliousness)
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For instance, evidence that a positive association between baseline e-cigarette use and later combustible tobacco cigarette smoking is mediated by increases in beliefs that smoking is enjoyable would be interpreted as evidence consistent with the catalyst hypothesis and that e-cigarette use increases risk of smoking initiation. Studies demonstrating that e-cigarette use is associated with a subsequent reduction in curiosity or interest in trying cigarettes would support the diversion hypothesis and that e-cigarette use reduces smoking risk.
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Thus, evidence that the (positive or negative) association between e-cigarette use and subsequent combustible tobacco cigarette use is stronger than the corresponding association of e-cigarette use with another risk behavior, such as cannabis use, would suggest specificity of the association and further strengthen the conclusion from the primary review.
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This review included studies of moderators and mediators of the vaping–smoking association that addressed plausibility; ecological evaluations of trends in vaping and smoking over time; effects of age restrictions on e-cigarette sales on smoking that addressed coherence; and studies on the analogous association of non-cigarette tobacco product use with cigarette smoking and e-cigarette use with other tobacco product use. 2 Two studies are abstracts and therefore do not meet the committee's inclusion criteria, but are included here because they were included in the systematic review and meta- analysis by Soneji and colleagues (Hornik et al., 2016; Primack et al., 2016)
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the relation of baseline ever e-cigarette use with subsequent ever use of combustible tobacco cigarettes at follow-up among baseline never users of combustible cigarettes, and (2) the relation of baseline past 30-day e-cigarette use with subsequent past 30-day use of combustible tobacco cigarettes among those reporting no use of combustible tobacco cigarettes in the past 30 days at baseline.
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Each of the seven ever-use studies eliminated ever smokers of combustible tobacco cigarettes at baseline, providing strong evidence of temporal precedence and eliminating some reverse causation explanations (i.e., past smokers seek out e-cigarette use by baseline and then subsequently return to smoking at follow-up)
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The odds ratios (ORs) for the studies are adjusted for a study-specific set of demographic, psychosocial, and behavioral risk factors (see Table 16-1 for covariates)
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Some papers included a more comprehensive set of covariates addressing plausible shared risk factors across demographic, environmental, and intrapersonal/endogenous dispositional domains, providing a more rigorous evaluation of the degree to which an observed association between e-cigarette use and subsequent smoking is direct (i.e., not due to confounding) , whereas some included demographic factors and excluded important environmental or intra personal factors.
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Hence, FIGURE 16-2 Meta-analysis of adjusted odds of current (past 30-day) combustible tobacco cigarette smoking at follow-up among non-current combustible tobacco cigarette smokers at baseline and current e-cigarette users at baseline compared with non-current e-cigarette users at baseline.
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. The study found no significant interactions between e-cigarette ever use and time in the prediction of combustible tobacco cigarette smoking (interaction adjusted OR = 0.74; 95% CI = 0.34–1.61, p = 0.44)
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. The combustible tobacco cigarette use frequency outcome was a threelevel variable based on days used in past 30 (0 versus 1–2 days versus 3 days of use or more)
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Overall, this study provided fairly strong evidence of dose–response associations between e-cigarette use and progression in smoking frequency and intensity for non-smokers at baseline. In a sample of 391 non-daily combustible tobacco cigarette smokers age 18 to 24 in California, Doran and colleagues (2017)
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Because all participants were smokers at baseline, it is possible that most started smoking before using e-cigarettes, leaving the temporal precedence of the association unclear. It is possible that there is a selection bias whereby those most at risk who are likely to escalate their smoking start using e-cigarettes as a means to help with cravings or because of unsuccessful efforts to quit (rather than a causal effect whereby using e-cigarettes intensifies smoking progression)
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In sum, the study methods and results are highly similar to the seven original studies included in the Soneji and colleagues (2017) meta-analysis of initiation and suggests generalization of e-cigarette use–smoking initiation associations to a sample outside the United States.
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The results showed that e-cigarette use was not associated significantly with later increases in combustible tobacco cigarette smoking (β = 0.02, p = 0.08)
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after adjusting for demographics, combustible tobacco cigarette use susceptibility, family-of-origin tobacco use, friend cigarette use, and other tobacco product use. Analyses stratified by other tobacco product use at baseline showed that e-cigarette–ever use was associated with greater odds of combustible tobacco cigarette–ever use during follow-up in baseline never users of cigars, hookah, or smokeless tobacco (OR = 2.26; 95% CI = 1.35–3.76)
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, and have never used other tobacco products (Loukas et al., 2018)
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. Another mediating mechanism proposed by the catalyst model is that youth who enjoy the pharmacological effects of nicotine or develop initial symptoms of nicotine dependence via e-cigarettes may be more inclined to use other tobacco products with nicotine-related pharmacological effects, such as combustible tobacco cigarettes (Schneider and Diehl, 2016)
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Holding all other factors constant, if e-cigarette use increased risk of smoking, then changes in the prevalence of e-cigarette use should parallel changes in the prevalence of smoking. If e-cigarette use prevented combustible tobacco cigarette smoking, changes in the prevalence of e-cigarette use and smoking over time should oppose each other.
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Studies of the Association of E-Cigarette Use Policy Change and Youth Smoking Three studies have examined whether changes in the prevalence of combustible tobacco cigarette use differ among youth who reside across
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Analogous Studies Involving Other Tobacco Products and Studies of Associations of E-Cigarette Use with Other Risk Behaviors Given that the catalyst model hypothesizes that e-cigarette use may increase smoking in youth by sensitizing youth to nicotine in a form that is more palatable and lacks aversive qualities of cigarettes (Schneider and Diehl, 2016) , other products that share properties with e-cigarettes would also be expected to be associated with increased risk of smoking.
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From page 532... ...
Youth who have a liability to experiment with multiple tobacco products would show indiscriminate forms of poly-tobacco product use involving the use of multiple non-cigarette and cigarette products in various sequences. However, evidence showing that e-cigarette use is associated with later combustible tobacco cigarette use in samples excluding users of other tobacco products suggests that indiscriminate patterns of polytobacco product use are unlikely to explain the association (Leventhal et al., 2015; Loukas et al., 2018)
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, which the committee considered a comprehensive selection of confounding factors. Use of tobacco products other than e-cigarettes and combustible tobacco cigarettes was adjusted for in several of the studies, and two studies reported positive associations of e-cigarette use and subsequent transition to ever smoking among baseline never users of any tobacco product.
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. Different regions of the United States and other countries have unique tobacco product policies and socioultural backdrops that may alter the avail c ability and population-level risk of e-cigarette use or combustible tobacco cigarette use in each location.
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Among youth and young adult e-cigarette users who ever use combustible tobacco cigarettes, there is moderate evidence that e-cigarette use increases the frequency and intensity of subsequent combustible tobacco cigarette smoking.
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Primary review of the observational literature yielded several studies showing a positive association between e-cigarette–ever use and past 30-day smoking status, which is a weak proxy for patterns of smoking indicative of progression in frequency and intensity. Among studies better positioned to address progression in frequency and intensity, the evidence supported a positive association of more frequent e-cigarette use with progression in smoking frequency and intensity.5 Dose–response associations were evident or suggestive across most analyses among those four studies.
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2016. Quickstats: Cigarette smoking status among current adult e-cigarette users, age group -- National Health Interview Survey, United States, 2015.
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2016. Current cigarette smoking among adults -- United States, 2005–2015.
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2015. Progression to traditional cigarette smoking after electronic cigarette use among U.S.
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2016b. Lon gitudinal study of e-cigarette use and onset of cigarette smoking among high school students in Hawaii.
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