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. Author manuscript; available in PMC: 2024 Feb 27.
Published in final edited form as: Subst Use Misuse. 2023 Feb 27;58(5):618–628. doi: 10.1080/10826084.2023.2177961

Nicotine Dependence Among Current Cigarette Smokers Who Use E-Cigarettes and Cannabis

Dina M Jones a, Mignonne C Guy b,c, Brian J Fairman d, Eric Soule b,e, Thomas Eissenberg b, Pebbles Fagan a
PMCID: PMC10249428  NIHMSID: NIHMS1875449  PMID: 36852436

Abstract

Background.

Co-use of tobacco and cannabis and dual use of cigarettes and e-cigarettes are very common among young adults. However, it is unclear whether co-use of cigarettes, e-cigarettes, and/or cannabis is associated with higher levels of nicotine dependence than cigarette-only use. We investigated the relationship between cigarette/nicotine dependence and co-use of tobacco and cannabis among 4 groups of cigarette smokers aged 18–35: cigarette-only smokers, cigarette-e-cigarette (CIG-ECIG) co-users, cigarette-cannabis (CIG-CAN) co-users, and cigarette-e-cigarette-cannabis (CIG-ECIG-CAN) co-users.

Methods.

Data were from a 2018 cross-sectional survey based on a national convenience sample of smokers aged 18–35 (n = 315). Cigarette/nicotine dependence was measured by the Fagerstrom Test of Nicotine Dependence (FTND) and e-cigarette dependence was measured by the Penn State E-cigarette Dependence Index. Bivariate analyses examined sociodemographic and tobacco/other substance use characteristics by co-use status and multivariable linear regression assessed the relationship between co-use and nicotine dependence.

Results.

In the sample, 27.6% were cigarette-only smokers, 24.8% were CIG-ECIG, 27.6% were CIG-CAN, and 20.0% were CIG-ECIG-CAN co-users. Significant differences were observed in sociodemographic and tobacco/other substance use characteristics by co-use status. E-cigarette co-users had low e-cigarette dependence, but moderate FTND scores. In adjusted analyses, only CIG-ECIG co-use was associated with higher FTND scores compared to cigarette-only smoking. However, CIG-ECIG and CIG-ECIG-CAN co-use were associated with higher FTND scores compared to CIG-CAN co-use.

Conclusions.

Co-use of cigarettes and e-cigarettes was associated with greater nicotine dependence among smokers aged 18–35. Additional research is needed to understand the underlying mechanisms of these relationships and inform prevention efforts.

Keywords: marijuana, cannabis, cigarette, electronic cigarette, co-use, poly-tobacco use, nicotine dependence, young adults, e-cigarette, tobacco use

1. Introduction

The prevalence of cigarette smoking has declined over the past decade, but co-use of tobacco and cannabis is common and increasing, especially among young adults (Dai, 2020; Strong et al., 2018; Tucker et al., 2019). In 2018, 36.4% of past-month cigarette smokers aged 18–34 reported using cannabis in the past month (SAMHSA, 2020) and in 2020, 42.6% of past-month cigarette smokers aged 18–34 reported using cannabis in the past month (SAMHSA, 2022). Research shows that current tobacco users, especially those who use multiple tobacco products, have a higher likelihood of currently using cannabis compared to non-tobacco users (Agrawal & Lynskey, 2009; Strong et al., 2018).

The growing popularity of novel tobacco products like e-cigarettes has introduced new ways to co-use tobacco and cannabis. In 2020, 50.1% of adults aged 18–34 who reported vaping nicotine or tobacco in the past month also reported using cannabis in the past month (SAMHSA, 2022). A recent meta-analysis found that young adults who used e-cigarettes had 2.3 times higher odds of using cannabis than young adults who did not use e-cigarettes (Chadi et al., 2019). Moreover, many young adult cigarette smokers report currently using e-cigarettes (Spears et al., 2019) and in 2020, the prevalence of dual/co-use of cigarettes and e-cigarettes was highest among adults aged 18–35 and lower among older adults (Boakye et al., 2022). Research also shows that co-users of cigarettes and e-cigarettes are more likely to use cannabis (Kristjansson et al., 2015) and have higher levels of nicotine dependence (Jankowski et al., 2019; Rüther et al., 2016; Strong et al., 2017) than cigarette-only smokers.

The increased risk of nicotine dependence among co-users of tobacco and cannabis is a major concern. Cannabis use has been linked to increased nicotine dependence, progression to nicotine dependence (Ford et al., 2002; Schauer et al., 2017), and lower rates of cigarette smoking cessation (Voci et al., 2020; Vogel et al., 2018; Weinberger et al., 2020). Prior studies have shown that co-users of cigarettes and cannabis (Agrawal et al., 2008; Rubinstein et al., 2014; Strong et al., 2018) have greater nicotine dependence than cigarette-only smokers. Research also suggests that differences in nicotine content, puff topography, and use frequency of tobacco or cannabis could contribute to higher levels of nicotine dependence among co-users compared to cigarette-only smokers (DeVito & Krishnan-Sarin, 2018; Martínez et al., 2020; Talih et al., 2015; Weinberger et al., 2021). However, Tucker et al. (2019) found that tobacco/nicotine-only users had no difference in cigarette or e-cigarette dependence compared to those who co-used cannabis and tobacco sequentially or administered them together. Although the literature is mixed, co-users of cigarettes, e-cigarettes, and/or cannabis may be more likely to have sustained tobacco use, thereby increasing their risk for tobacco-related diseases compared to cigarette-only smokers. Additional research is needed to clarify the relationship between co-use of cigarettes, e-cigarettes, and cannabis and nicotine dependence especially among young adults.

Despite the popularity of cannabis use among cigarette and e-cigarette users aged 18–34, few co-use studies have assessed levels of nicotine dependence or specifically focused on co-use of cigarettes, e-cigarettes, and cannabis; current co-use behaviors; co-use of cigarettes and cannabis, and even fewer have examined co-use of e-cigarettes and cannabis. Instead, some studies on co-use of tobacco and cannabis have examined the prevalence or factors associated with co-use among youth (Dai, 2020; Miech et al., 2019; Smith et al., 2020). Moreover, most prior co-use studies have focused on general tobacco-cannabis co-use (Montgomery, 2015; Ramo et al., 2012; Tucker et al., 2019), cigar-cannabis co-use (Cohn et al., 2016; Montgomery & Mantey, 2017; Schauer et al., 2017), or ever/past year co-use behaviors (Seaman et al., 2020; Trivers et al., 2019), and very few considered nicotine dependence. Some co-use studies have reported on specific routes/modes of cannabis consumption like vaping cannabis (Dai, 2020; Miech et al., 2019; Schulenberg et al., 2019; Seaman et al., 2020; Smith et al., 2020) or certain patterns of co-use like co-administration (i.e., blunting or removing all or part of the tobacco inside of a cigar and replacing it with cannabis [Sterling et al, 2016a; Yerger et al., 2001]) (Cohn et al., 2016; Montgomery & Mantey, 2017; Schauer et al., 2017; Seaman et al., 2020; Smith et al., 2020; Trivers et al., 2019; Tucker et al., 2019). Few have reported the prevalence of vaping cannabis or blunting among current/past 30-day co-users overall or in the context of nicotine dependence.

The purpose of this study was to examine the relationship between nicotine dependence and current co-use of cigarettes, e-cigarettes, and cannabis among a national, convenience sample of current cigarette smokers aged 18–35. We hypothesized that cigarette-only smokers would have lower nicotine dependence compared to 3 groups of co-users: cigarette and e-cigarette (CIG-ECIG) co-users, cigarette and cannabis (CIG-CAN) co-users, and cigarette, e-cigarette, and cannabis (CIG-ECIG-CAN) co-users. Secondary aims were to 1) describe the sociodemographic, tobacco, and other substance use characteristics of the sample by co-use status, 2) examine e-cigarette dependence and the prevalence of cannabis vaping among e-cigarette users, and 3) examine the prevalence of blunting among cannabis users. Identifying the levels of nicotine dependence among co-users may provide new information to help us understand chronic use behaviors among tobacco and cannabis users and to inform prevention efforts.

2. Methods

2.1. Procedure and sample

This study was conducted by the Center for the Study of Tobacco Products (CSTP), Virginia Commonwealth University (VCU). We analyzed cross-sectional survey data from an online study [Fagan et al., 2019] designed to evaluate the reliability and validity of an e-cigarette flavor outcome expectancy scale among current established cigarette and cigar smokers who do and do not use e-cigarettes. In August 2018, research staff posted study advertisements on Craigslist. To obtain a national sample, staff posted advertisements in five randomly selected Craigslist localities (i.e., US cities and regions in each census tract (e.g., Northeast, Midwest, South, West) using an online statistical computing program. Overall, our sampling frame included 20 Craigslist localities or 4.8% of the 417 Craigslist localities at the time of randomization (June 2018). At the time of randomization, none of the localities in our sampling frame restricted flavored tobacco product sales.

2.2. Participant screening and eligibility

Respondents who clicked the study advertisement link were directed to a description of the study’s purpose on the VCU CSTP website. Interested respondents were directed to more detailed information and an online screening questionnaire. Overall, 1,767 respondents consented to the screening questionnaire, 1,620 (91.7%) of whom completed a 2-minute, online eligibility screener about sociodemographic characteristics; current cigarette, cigar, and e-cigarette use behaviors; ability to read and write in English; and contact information. Of those who completed the online screener, 968 (59.8%) were eligible for the survey. Respondents were eligible for the study if they were aged 18–35 and met standard definitions for current established cigarette or cigar use (i.e., smoked at least 100 cigarettes or 50 cigars in lifetime, now smoke cigarettes or cigars “every day” or “some days”) and used cigarettes or cigars in the past 30 days (National Center for Health Statistics). We sought to recruit an equivalent number of current cigarette/cigar smokers who did and did not currently use e-cigarettes every day or some days. To do so, we tracked the number of eligible respondents by e-cigarette use status to achieve equivalent numbers in each group and stopped recruiting participants in each group once we met the group’s recruitment goal. Those who were not proficient in English or did not have a working phone, email, and home address were ineligible. Two research staff reviewed the online screening data to confirm respondent’s eligibility and then forwarded respondents a unique code and link to complete the survey consent form and survey. Of the 968 eligible respondents, 355 (36.7%) consented to the survey, 320 of whom (90.1%) completed the survey. All 320 participants were current cigarette smokers and half (n = 160) currently used e-cigarettes. Participants who completed the survey were sent a $25 electronic VISA gift card to compensate them for their time. This study was approved by the VCU Institutional Review Board.

2.3. Measures

2.3.1. Nicotine dependence

Nicotine dependence was assessed using the Fagerström Test for Nicotine Dependence (FTND), a standard, 6-item assessment used to determine the intensity of a physical addiction to nicotine in cigarettes (Heatherton et al., 1991). FTND scores range from 0 to 10 with higher scores indicating greater nicotine dependence. Two FTND items, time to first cigarette use and number of cigarettes smoked per day, are important single indicators of nicotine dependence and were also reported. Time to first cigarette use was assessed by asking, “How soon after you wake up do you smoke your first cigarette?” Responses included “within 5 minutes,” “6 to 30 minutes,” “31 to 60 minutes,” and “after 60 minutes” and were dichotomized to “≤5 minutes” versus “>5 minutes” of waking. The number of cigarettes smoked per day was assessed by asking, “On average, when you smoked during the past 30 days (month), about how many cigarettes did you smoke each day?” Categorical responses ranged from “I did not smoke cigarettes in the past 30 days” and “1 cigarette” up to “100 cigarettes” but the variable was treated as a continuous in analyses. E-cigarette dependence was assessed using the 10-item, Penn State Nicotine Dependence Index for e-cigarettes (Foulds et al., 2015), although response options/scores were changed from the original index for the item, “On days that you can use your electronic cigarette freely, how soon after you wake up do you first use your electronic cigarette?” Responses included, “within 5 minutes” (score of 4), “6 to 30 minutes” (score of 3), “31 to 60 minutes” (score of 2), and “after 60 minutes” (score of 1). Overall scores ranged from 0 to 19 with higher scores indicating greater e-cigarette dependence.

2.3.2. Co-use status

We used a standard, widely used current cigarette smoking definition (Bondy et al., 2009). Those who smoked at least 100 cigarettes in their lifetime and now smoked cigarettes “every day” or “some days” and in the past 30 days were considered current cigarette smokers. Participants reported whether they now used e-cigarettes or cannabis “every day,” “some days,” or “not at all” and the number of days they used e-cigarettes and cannabis in the past 30 days. Those who reported using e-cigarettes at least 1 day in the past 30 days were considered current e-cigarette users and those who reported using cannabis at least 1 day in the past 30 days were considered current cannabis users. Current e-cigarette and cannabis use is commonly defined as past 30-day use in national surveys, but has also been assessed using every day/some day use definitions (Brouwer et al., 2022; Coleman et al., 2017; Patrick et al., 2022; Schluter & Hodgins, 2022; Substance Abuse and Mental Health Services Administration, 2021). We utilized past 30 day e-cigarette and cannabis use definitions to be consistent with national surveys and because we found greater reliability using past 30-day use compared to every day/some day use, (i.e., 20.8% of those who reported using cannabis every day and 17.8% of those who reported using e-cigarettes every day reported use less than 30 days in the past 30 days and 15.7% of those who reported using e-cigarettes some days and 9.2% of those who reported using cannabis some days did not report any past 30 day use).

We created a 4-level measure of current co-use status based on participants’ current use of cigarettes, e-cigarettes, and cannabis: 1) Cigarette-only smokers reported current cigarette use, but did not report current e-cigarette or cannabis use; 2) CIG-ECIG co-users reported current cigarette and e-cigarette use, but did not report current cannabis use or usually using cannabis in their e-cigarette device; 3) CIG-CAN co-users reported current cigarette and cannabis use, but not current e-cigarette use; 4) CIG-ECIG-CAN co-users reported current use of cigarettes, e-cigarettes, and cannabis.

2.3.3. Tobacco use characteristics

We assessed the age that participants first tried any nicotine containing product; frequency of cigarette smoking (daily/nondaily), usual cigarette flavor (menthol/non-menthol/no usual type), and current other tobacco product use “every day” or “some days” (use of at least 1 other tobacco product [e.g., large/regular/premium cigars, little cigars and cigarillos, hookah, pipes, smokeless tobacco, or dissolvable tobacco]). Current e-cigarette users also reported the type of substance they usually used in their e-cigarette device. Response options included “nicotine,” “non-nicotine,” “marijuana,” “other drugs,” and “don’t know.” Lastly, we reported past 30-day blunt use among current cannabis users. Past 30-day blunt use was assessed by asking, “In the past 30 days, have you smoked [large/regular/premium cigars] or [little cigars/cigarillos] of any kind as a blunt, even one or two puffs?”. Response options included, “Yes, smoked as blunt”, “No, did not smoke blunt”, “Yes, smoked as a blunt and as a cigar without marijuana in the past 30 days”, and “Don’t know” and those who responded yes were considered past 30-day blunt users.

2.3.4. Other substance use behaviors

Participants reported past 30-day use of alcohol and “other drugs (i.e., cocaine, heroin/opioids, ecstasy, methamphetamines, etc.).”

2.3.5. Sociodemographic characteristics

Data collected included sex/gender (female, male, transgender), age, race (Black/African America, White, Other), Hispanic ethnicity (yes/no), sexual orientation (heterosexual or straight, lesbian/gay/ bisexual/don’t know), marital status (married, living with partner, never married, and widowed/separated/divorced), educational attainment (less than high school, high school or general education diploma (GED), some college, associate degree and bachelor’s degree or more), current degree enrollment status (yes/no), and annual household income (< $10,000, $10,000–$29,999, $30,000–$49,999), and ≥$50,000).

2.4. Data analysis

Five participants were excluded due to missing data on e-cigarette use (n = 4) or FTND items (n = 1) resulting in an analytical sample of 315 participants. Number of cigarettes smoked per day was treated as a continuous variable in analyses given the continuous range of response options. We compared measures of nicotine dependence, sociodemographic, and tobacco/other substance use characteristics by co-use status. Univariate analyses, bivariate analyses (Pearson χ2, Fishers exact, F, t, Mann Whitney-U tests), and multivariable linear regression were conducted in SAS 9.4 (Cary, NC) for comparisons. Pair-wise comparisons by co-use status were conducted when global bivariate tests were statistically significant at the p<.05 to identify differences between specific groups.

We conducted several linear regression models to test our hypothesis that cigarette-only smokers would have lower nicotine dependence compared to CIG-ECIG, CIG-CAN, and CIG-ECIG-CAN co-users. A general linear regression model was first used to regress co-use status (primary predictor, ref = cigarette-only smoking) on FTND score (outcome). Subsequent regression models included Model 1, adjusted for all sociodemographic characteristics; Model 2, adjusted for tobacco/substance use characteristics (cigarette smoking frequency, menthol smoking status, current other tobacco product use, past 30-day alcohol and other drug use); and Model 3, adjusted for sociodemographic and tobacco/substance use characteristics. Given the lack of information on nicotine dependence and co-use status, including the influence of cannabis use, we conducted Model 3 with CIG-CAN co-use as the reference group. We also conducted a sensitivity regression analysis with co-use status defined/based on current use of e-cigarettes and cannabis “every day” or “some days” instead of past 30 day use. For regression analyses, standard errors (SE) and 95% confidence intervals (CIs) were computed, and a p-value < .05 was considered statistically significant in all analyses.

3. Results

3.1. Sociodemographic characteristics by co-use status

Table 1 reports sociodemographic characteristics by co-use status. Overall, 27.6% of participants reported current cigarette-only smoking, 24.8% reported CIG-ECIG co-use, 27.6% reported CIG-CAN co-use, and 20.0% reported CIG-ECIG-CAN co-use. The average participant age was 28.4 years, and more than half of participants were female, White, non-Hispanic, heterosexual, not married, had some college education or greater, and had an annual household income less than $50,000. There were statistically significant differences in co-use status by sexual orientation, marital status, and current degree enrollment status. A significantly higher proportion of CIG-ECIG-CAN co-users (28.6%) identified as gay, lesbian, bisexual or did not know their sexual orientation compared to CIG-ECIG co-users (12.8%, p=.0198) and cigarette-only smokers (12.8%, p=.0162), but no difference was found with CIG-CAN co-users (23.0%). A significantly higher proportion of CIG-ECIG co-users (42.3%) were married compared to CIG-CAN co-users (23.0%, p=.0100), but no difference was found with CIG-ECIG-CAN co-users (23.8%), and cigarette-only smokers (28.7%). A significantly higher proportion of cigarette-only smokers (24.1%) were currently enrolled in a degree program compared to CIG-ECIG (7.7%, p=.0044) and CIG-CAN (11.5%, p=.0293) co-users and a significantly higher proportion of CIG-ECIG-CAN co-users (22.2%) were currently enrolled in a degree program compared to CIG-ECIG-co-users (p=.0139). No associations were found with co-use status by sex/gender, age, race, ethnicity, educational attainment, and annual household income (Table 1).

Table 1.

Sociodemographic characteristics by co-use status among cigarette smokers aged 18–35

Participant characteristics Total sample Cigarette-only smoker CIG-ECIG co-users CIG-CAN co-users CIG-ECIG-CAN co-user test p
N = 315 (n = 87) 27.6% (n = 78) 24.8% (n = 87) 27.6% (n = 63) 20.0%
% (n) % (n) % (n) % (n) % (n)
Sex/gender f .09
 Female 74.2 (233) 76.7 (66) 84.6 (66) 66.7 (58) 68.3 (43)
 Male 24.5 (77) 22.1 (19) 15.4 (12) 31.0 (27) 30.2 (19)
 Transgender 1.3 (4) 1.2 (1) 0 2.3 (2) 1.6 (1)
Age, M (SD) 28.4 (4.1) 28.4 (3.9) 29.4 (3.7) 28.1 (4.1) 27.7 (4.6) an .08
Race c .78
 Black/African American 8.9 (28) 8.1 (7) 6.4 (5) 10.3 (9) 11.1 (7)
 White 80.0 (252) 78.2 (68) 85.9 (67) 79.3 (69) 76.2 (48)
 Other 11.1 (35) 13.8 (12) 7.7 (6) 10.3 (9) 12.7 (8)
Ethnicity
 Hispanic 8.6 (27) 5.8 (5) 7.7 (156) 8.1 (7) 14.3 (9) c .31
Sexual orientation c .0320
 LGB/other/don’t know 18.8 (59) 12.8 (11)a 12.8 (10)a 23.0 (20)ab 28.6 (18)b
Marital status c .0426
 Married 29.5 (93) 28.7 (25)ab 42.3 (33)ab 23.0 (20)a 23.8 (15)ab
 Living with partner 27.6 (87) 25.3 (22) 25.6 (20) 25.3 (22) 36.5 (23)
 Never married 36.5 (115) 39.1 (34) 25.6 (20) 48.3 (42) 30.2 (19)
Widowed/separated/divorced 6.4 (20) 6.9 (6) 6.4 (5) 3.5 (3) 9.5 (6)
Educational Attainment c .73
 Less than high school 5.4 (17) 5.8 (5) 7.7 (6) 3.5 (3) 4.8 (3)
 High school or GED 25.7 (81) 28.7 (25) 25.6 (20) 20.7 (18) 28.6 (18)
 Some college 40.6 (128) 41.4 (36) 33.3 (26) 48.3 (42) 38.1 (24)
 Associate degree 12.4 (39) 12.6 (11) 16.7 (13) 9.2 (8) 11.1 (7)
 ≥ Bachelor’s degree 15.9 (50) 11.5 (10) 16.7 (13) 18.4 (16) 17.5 (11)
Currently enrolled in degree program c .0102
 Yes 16.2 (51) 24.1 (21)a 7.7 (6)b 11.5 (10)bc 22.2 (14)ac
Annual household income c .98
 < $10,000 9.2 (29) 8.1 (7) 6.4 (5) 11.5 (10) 11.1 (7)
 $10,000–$29,999 29.5 (93) 32.2 (28) 26.9 (21) 29.9 (26) 28.6 (18)
 $30,000–$49,999 26.0 (82) 25.3 (22) 28.2 (22) 25.3 (22) 25.4 (16)
 ≥ $50,000 35.2 (111) 34.5 (30) 38.5 (30) 33.3 (29) 34.9 (22)
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Abbreviations: CIG-ECIG, cigarette and e-cigarette; CIG-CAN, cigarette and cannabis; CIG-ECIG-CAN, cigarette, e-cigarette, and cannabis; GED, General Education Diploma; LGB, lesbian, gay, bisexual; M, mean; SD, standard deviation; c, Pearson χ2; f, Fishers; an, F/ANOVA. Cigarette only smokers were those who reported current cigarette use but no past 30 day e-cigarette or cannabis use. CIG-ECIG co-users were those who reported current cigarette use and past 30 day e-cigarette use but no past 30 day cannabis use. CIG-CAN co-users were those who reported current cigarette use and past 30 day cannabis use but no past 30 day cannabis use. CIG-ECIG-CAN co-users were those who reported current cigarette use and past 30 day use of e-cigarettes and cannabis. Sample sizes and percentages may not add up to total sample size due to missingness or rounding. Within a row/participant characteristic, values without a common superscript differ in pair-wise comparisons (p<.05) of co-use status categories.

3.2. Nicotine dependence by co-use status

Table 2 reports tobacco and other substance use characteristics by co-use status. The average FTND score was 4.3 indicating moderate nicotine dependence, only 31.8% of participants smoked their first cigarette within 5 minutes of waking, and the median number of cigarettes smoked per day was 10. Among past 30-day e-cigarette users, the average e-cigarette dependence score was 7.3, indicating low dependence. There were statistically significant differences in FTND scores and time to first cigarette use by co-use status. Specifically, CIG-ECIG co-users had significantly higher FTND scores (5.1) compared to CIG-ECIG-CAN co-users (4.2, p=.0350), cigarette-only smokers (4.3, p=.0316), and CIG-CAN co-users (3.6, p=.0002). A significantly higher proportion of CIG-ECIG co-users (41%) smoked their first cigarette within 5 minutes of waking compared to CIG-CAN (25.3%, p=.0315) and CIG-ECIG-CAN (22.2%, p=.0179) co-users, but no difference was found with cigarette-only smokers (36.8%).

Table 2.

Tobacco and other substance use characteristics by co-use status among cigarette smokers aged 18–35

Substance use characteristics Total sample Cigarette-only smokers CIG-ECIG co-users CIG-CAN co-users CIG-ECIG-CAN co-users test p
N = 315 n = 87 n = 78 n = 87 n = 63
FTND†, M (SD) 4.3 (2.5) 4.3 (2.4)a 5.1 (2.4)b 3.6 (2.6)a 4.2 (2.4)a an .0021
Time to first cigarette use
< 5 min, % (n)		 31.8 (100) 36.8 (32)ab 41.0 (32)b 25.3 (22)a 22.2 (14)a c .0379
M (SD) M (SD) M (SD) M (SD) M (SD)
E-cigarette dependence† 7.3 (4.9) - 7.6 (4.7) - 7.0 (5.1) t .47
Age first tried any nicotine containing product 15.1 (3.5) 15.0 (3.7) 15.8 (3.2) 14.8 (3.9) 14.8 (2.7) an .20
Cigarettes smoked per day
 Median (IQR) 10.0 (13.0) 10.0 (14.0) 10.0 (11.0) 10.0 (11.0) 10.0 (15.0) mw .58
 M (SD) 13.1 (14.2) 14.4 (14.3) 13.5 (16.4) 11.8 (12.0) 12.6 (14.0) an .67
Cigarette smoking frequency
 Daily, % (n) 73.7 (232) 75.9 (66)ab 66.7 (52)a 86.2 (75)b 61.9 (39)a c .0033
Days used e-cigarettes in past 30 days 16.3 (10.3) - 16.4 (10.4) - 16.2 (10.1) t .90
Days used cannabis in past 30 days 20.2 (10.8) - - 19.9 (11.1) 20.6 (10.5) t .68
% (n) % (n) % (n) % (n) % (n)
Usual cigarette flavor f .0077
 Menthol 54.3 (171) 57.5 (50)a 61.5 (48)a 37.9 (33)b 63.5 (40)a
 Non-menthol 44.1 (139) 41.4 (36) 35.9 (28) 60.9 (53) 34.9 (22)
 No usual flavor 1.6 (5) 1.2 (1) 2.6 (2) 1.2 (1) 1.6 (1)
Current other tobacco use‡ c <.0001
 Yes 47.9 (147) 22.9 (19)a 42.1 (32)b 55.2 (48)b 78.7 (48)c
Past 30-day alcohol use c .0003
 Yes 71.4 (225) 55.2 (48)a 70.5 (55)b 80.5 (70)b 82.5 (52)b
Past 30-day other-drug use§ c <.0001
 Yes 14.6 (46) 5.8 (5)a 2.6 (2)a 27.6 (24)b 23.8 (15)b
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Abbreviations: CIG-ECIG, cigarette and e-cigarette; CIG-CAN, cigarette and cannabis; CIG-ECIG-CAN, cigarette, e-cigarette, and cannabis; FTND, Fagerstrom Test for Nicotine Dependence; IQR, interquartile range; M, mean; SD, standard deviation; c, Pearson χ2; f, Fishers; an, F/ANOVA; t, t test; mw, Mann-Whitney U. Cigarette only smokers were those who reported current cigarette use but no past 30 day e-cigarette or cannabis use. CIG-ECIG co-users were those who reported current cigarette use and past 30 day e-cigarette use but no past 30 day cannabis use. CIG-CAN co-users were those who reported current cigarette use and past 30 day cannabis use but no past 30 day cannabis use. CIG-ECIG-CAN co-users were those who reported current cigarette use and past 30 day use of e-cigarettes and cannabis. Sample sizes and percentages may not add up to total sample size due to missingness or rounding. Within a row/substance use characteristic, values without a common superscript differ in pair-wise comparisons (p<.05) of co-use status categories.

†

FTND scores range from 0–10. E-cigarette dependence was assessed using a modified version of the Penn State Nicotine Dependence Index and scores range from 0–19.

‡

Based on ‘every day’ or ‘some days’ use of at least 1 other tobacco product including little cigars and cigarillos, large/regular/premium cigars, hookah, pipe tobacco, smokeless tobacco, and dissolvable tobacco.

§

Based on past 30-day use of ‘cocaine, heroin/opioids, ecstasy, methamphetamines/meth, etc.

3.3. Tobacco and other substance use characteristics by co-use status

Significant differences were also found with co-use status and the prevalence of daily cigarette smoking, usual/menthol cigarette flavor, current other tobacco product use, and past 30-day alcohol and other drug use. A significantly higher proportion of CIG-CAN co-users (86.2%) reported daily cigarette smoking compared to CIG-ECIG-CAN (61.9%, p=.0006) and CIG-ECIG (66.7%, p=.0029) co-users, but no difference was found with cigarette-only smokers (75.9%). A significantly lower proportion of CIG-CAN co-users (37.9%) reported that they usually smoked menthol cigarettes compared to CIG-ECIG-CAN co-users (63.5%, p=.0030), CIG-ECIG co-users (61.5%, p=.0024), and cigarette-only smokers (57.5%, p=.0181). A significantly higher proportion of CIG-ECIG-CAN co-users (78.7%) reported current other tobacco product use compared to cigarette-only smokers (22.9%, p<.0001), CIG-ECIG co-users (42.1%, p<.0001), and CIG-CAN co-users (55.2%, p=.0032) and a significantly lower proportion of cigarette-only smokers currently used other tobacco products compared to CIG-ECIG (p=.0095) and CIG-CAN (p<.0001) co-users. Additionally, a significantly lower proportion of cigarette-only smokers (55.2%) reported past 30-day alcohol use compared to CIG-ECIG-CAN (82.5%, p=.0004), CIG-CAN (80.5%, p=.0004), and CIG-ECIG (70.5%, p=.0422) co-users. Lastly, a significantly higher proportion of CIG-CAN (27.6%) and CIG-ECIG-CAN (23.8%) co-users reported past 30-day other-drug use compared to CIG-ECIG (2.6%, pCIG-CAN<.001 and pCIG-ECIG-CAN=.0001) and cigarette-only smokers (5.8%, pCIG-CAN=.0001 and pCIG-ECIG-CAN=.0013). No differences were found between co-use status and number of cigarettes smoked per day, e-cigarette dependence, age first tried any nicotine containing product, or frequency of e-cigarette or cannabis use (Table 2).

3.4. Substance usually used in e-cigarette and blunt use

Past 30-day e-cigarette users also reported the substance usually used in their e-cigarette and past 30-day cannabis users reported past 30-day blunt use (data not shown). Overall, 79.4% of e-cigarette users reported that they usually vape a nicotine-based substance, 12.1% usually vaped non-nicotine-based substances, 6.4% usually vaped cannabis, and 2.1% reported “don’t know.” Compared to CIG-ECIG co-users, a lower proportion of CIG-ECIG-CAN co-users reported that they usually vape a nicotine-based substance (CIG-ECIG-CAN: 71.4% vs. CIG-ECIG: 85.9%), but a similar proportion reported that they usually vape non-nicotine-based substances (CIG-ECIG-CAN: 11.1% vs. CIG-ECIG: 12.8%) and responded “don’t know” (CIG-ECIG-CAN: 3.2% vs. CIG-ECIG: 1.3%). Moreover, 14.3% of CIG-ECIG-CAN co-users reported that they usually vape cannabis. Overall, 62.7% of cannabis users reported smoking a large/regular/premium cigar or little cigar/cigarillo as a blunt in the past 30 days. No difference was found in the prevalence of past 30-day blunt use between CIG-ECIG-CAN co-users (68.3%) and CIG-CAN co-users (58.6%).

3.5. Regression analyses

Table 3 shows results from multivariable linear regression models that examined the relationship between co-use status and nicotine dependence. In unadjusted analyses, CIG-ECIG co-use was associated with higher FTND scores compared to cigarette-only smoking (B = 0.75 [95% CI: 0.01, 1.50], SE: 0.38, t = 1.99, p = .0480). After adjusting for sociodemographic and smoker characteristics (Model 3), CIG-ECIG co-use remained associated with FTND scores (B = 0.78 [95% CI: 0.05, 1.51], SE: 0.37, t = 2.11, p = .0361) compared to cigarette-only smoking. CIG-CAN co-use was associated with lower FTND scores compared to cigarette-only smoking following adjustment for tobacco/substance use characteristics (Model 2, B = −0.82 [95% CI: −1.56, −0.08], SE: 0.37, t = −2.19, p = .0290), but this association was no longer significant following adjustment for both sociodemographic and tobacco/substance use characteristics. No association was found between nicotine dependence and CIG-ECIG-CAN co-use relative to cigarette-only smoking in unadjusted or adjusted analyses (Table 3). Following adjustment for sociodemographic and tobacco/other substance use characteristics, CIG-ECIG-CAN co-use (B = 0.87 [95% CI: 0.09, 1.65], SE: 0.39, t = 2.21, p = .0280, data not shown) and CIG-ECIG co-use (B = 1.42 [95% CI: 0.67, 2.16], SE: 0.38, t = 3.75, p = .0002, data not shown) were associated with higher FTND scores compared to CIG-CAN co-use.

Table 3.

Unadjusted and adjusted regression results predicting nicotine dependence from co-use status among cigarette smokers aged 18–35a

Co-use status Outcome: FTND Score
Unadjusted Model 1b Model 2c Model 3d
B (SE), [95% CI] B (SE), [95% CI] B (SE), [95% CI] B (SE), [95% CI]
Cigarette-only smoker, reference
CIG-ECIG co-user 0.75 (0.38), [0.01, 1.50] 0.60 (0.37), [−0.14, 1.34] 0.93 (0.36), [0.22, 1.64] 0.78 (0.37), [0.05, 1.51]
CIG-CAN co-user −0.65 (0.37), [−1.39, 0.08] −0.35 (0.37), [−1.08, 0.38] −0.82 (0.37), [−1.56, −0.08] −0.64 (0.38), [−1.39, 0.11]
CIG-ECIG-CAN co-user −0.12 (0.40) [−0.92, 0.67] 0.08 (0.40), [−0.70, 0.87] 0.21 (0.42), [−0.61, 1.03] 0.23 (0.42), [−0.60, 1.06]
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Abbreviations: B, unstandardized beta; CIG-ECIG, cigarette and e-cigarette; CIG-CAN, cigarette and cannabis; CIG-ECIG-CAN, cigarette, e-cigarette, and cannabis; FTND, Fagerstrom Test for Nicotine Dependence; SE, standard error, CI, confidence interval. Boldface indicates statistical significance at the α = .05 level.

a

Transgender participants were excluded from regression analyses due to insufficient sample size.

b

Model 1 only controlled for sociodemographic characteristics (age, sex/gender, race, ethnicity, sexual orientation, marital status, educational attainment, degree enrollment status, and annual household income).

c

Model 2 only controlled for tobacco/substance use characteristics (cigarette smoking frequency, menthol smoking status, current other tobacco product use, past 30-day alcohol and other drug use).

d

Model 3 adjusted for both sociodemographic and tobacco/substance use characteristics.

3.6. Sensitivity regression analyses

Table S1 shows results from the sensitivity regression analysis that defined co-use status based on use of e-cigarettes and cannabis “every day” or “some days”. Under the “every day”/”some days” co-use status definition, there were 72 cigarette-only smokers, 91 CIG-ECIG co-users, 84 CIG-CAN co-users, and 67 CIG-ECIG-CAN co-users. In unadjusted analyses, CIG-ECIG co-use remained associated with higher FTND scores compared to cigarette-only smoking (B = 0.91 [95% CI: 0.16, 1.66], SE: 0.38, t = 2.38, p = .0178). However, after adjusting for sociodemographic characteristics (Model 1) we found a new association wherein CIG-ECIG co-use was associated with higher FTND scores compared to cigarette-only smoking (B = 0.79 [95% CI: 0.05, 1.53], SE: 0.38, t = 2.10, p = .0369). After adjusting for sociodemographic and smoker characteristics (Model 3), CIG-ECIG co-use remained associated with FTND scores (B = 0.83 [95% CI: 0.08, 1.57], SE: 0.38, t = 2.19, p = .0291) compared to cigarette-only smoking. However, CIG-CAN co-use was no longer associated with lower FTND scores compared to cigarette-only smoking following adjustment for tobacco/substance use characteristics (Model 2, B = −0.70 [95% CI: −1.48, 0.08], SE: 0.40, t = −1.76, p = .0792). Following adjustment for sociodemographic and tobacco/other substance use characteristics, CIG-ECIG co-use (B = 1.37 [95% CI: 0.64, 2.10], SE: 0.37, t = 3.69, p = .0003, data not shown) remained associated with higher FTND scores compared to CIG-CAN co-use. However, CIG-ECIG-CAN co-use was no longer associated with higher FTND scores compared to CIG-CAN co-use (B = 0.73 [95% CI: −0.05, 1.51], SE: 0.39, t = 1.84, p = .0665, data not shown).

4. Discussion

In sum, we found that cigarette-only smoking was associated with lower nicotine dependence as measured by FTND compared to current CIG-ECIG co-use. However, we did not find differences in FTND scores between cigarette-only smokers and CIG-CAN or CIG-ECIG-CAN co-users in adjusted analyses. Current CIG-ECIG and CIG-ECIG-CAN co-use was associated with higher FTND scores compared to CIG-CAN co-use. We also found that a greater proportion of CIG-ECIG co-users smoked their first cigarette within 5 minutes of waking compared to CIG-CAN and CIG-ECIG-CAN co-users. Overall, our primary hypothesis was partly supported and the present study provides novel information that suggests that levels of nicotine dependence vary based on the type of products co-used among cigarette smokers.

Our results that show that CIG-ECIG co-users have greater nicotine dependence than cigarette-only smokers are consistent with several studies, but the literature is mixed. Rüther et al. (2016) found that CIG-ECIG co-users had greater modified FTND scores than cigarette-only smokers. Similarly, Strong et al. (2017), found that CIG-ECIG co-users had slightly higher standardized tobacco dependence scores than cigarette-only smokers. In contrast, other studies (González-Roz & MacKillop, 2021; [Kaplan et al., 2020]; Rostron et al., 2016) found no difference in cigarette/nicotine dependence between CIG-ECIG co-users and cigarette-only smokers. One possible explanation for the mixed findings is that cigarette smokers who use e-cigarettes have high levels of nicotine dependence and may co-use with e-cigarettes to reduce their cigarette consumption. Although not statistically significantly different, CIG-ECIG co-users smoked fewer cigarettes per day on average and a lower proportion smoked daily compared to cigarette-only smokers. Alternatively, CIG-ECIG co-users could have greater nicotine dependence than cigarette-only smokers considering that they consume an additional source of nicotine and engage in dual/poly-tobacco use behavior, which may increase their nicotine dependence overall (Leavens et al., 2022; [Martínez et al., 2020]; Sung et al., 2018). Given these mixed findings and the limited number of available studies, further research is needed to clarify the relationship between CIG-ECIG co-use and nicotine dependence.

Contrary to our expectations, we did not find that co-use of cigarettes and cannabis (with or without e-cigarette use) was associated with different levels of nicotine dependence compared to cigarette-only smoking. Despite limited research, our lack of observed differences is somewhat consistent with prior studies. A systematic review (Peters et al., 2012a) and a brain imaging study (Brody et al., 2016) found no difference in nicotine dependence between CIG-CAN co-users and cigarette-only smokers. It is possible that cannabis may help to promote or maintain tobacco/nicotine use instead of serving as a tobacco substitute. For example, CIG-CAN and CIG-ECIG-CAN co-users were more likely to currently use other tobacco products than cigarette-only smokers, around 60% consumed cannabis in the form of a blunt, which contain tobacco [Sterling et al., 2016b], and 14.8% of CIG-ECIG-CAN co-users reported usually vaping cannabis. Moreover, the present study did not assess cannabis dependence and it is unclear the extent to which cannabis dependence contributes to maintenance of co-use behaviors and nicotine dependence. However, these findings are especially curious given that CIG-ECIG-CAN co-users also had similar e-cigarette use frequency and levels of e-cigarette dependence compared to CIG-ECIG co-users, who had higher levels of nicotine dependence than cigarette-only smokers. Notably, cigarette-only smokers, CIG-CAN co-users, and CIG-ECIG-CAN co-users had no difference in their cigarette consumption or age at nicotine initiation which could have contributed to the lack of differences observed between these groups. Future studies should seek to compare levels of nicotine dependence among cigarette-only and CIG-CAN co-users.

Interestingly, we also found that CIG-CAN co-users had significantly lower FTND scores compared to CIG-ECIG and CIG-ECIG-CAN co-users. Similar to other studies (Etter & Eissenberg, 2015; Kaplan et al,. 2020; Morean et al., 2018) CIG-ECIG and CIG-ECIG-CAN co-users in the present study had moderate levels of nicotine/cigarette dependence and low e-cigarette dependence. Few studies have examined the effect of cannabis on tobacco/nicotine dependence, especially among ECIG-CAN co-users or relative to CIG-ECIG co-use. Thus, it is unclear the extent to which e-cigarette use contributed to the observed differences in nicotine dependence. Nevertheless, research has linked cannabis use to increased nicotine dependence and progression to nicotine dependence (Agrawal et al., 2008; Ford et al., 2002; Patton et al., 2005; Rubinstein et al., 2014; Schauer et al., 2017) and underlying biological and pharmacological mechanisms likely influence the relationship between cannabis use and nicotine dependence.

The effect of cannabis and tobacco co-use on the brain cannot be easily explained despite evidence that the effects of co-use are different from the effects of cannabis or tobacco use alone (Vergara et al., 2018). For example, prior studies have shown that compared to cigarette-only smoking, CIG-CAN co-use is associated with increased nicotinic acetylcholine receptor availability (Brody et al., 2016; Brody et al., 2013) and reduced volume (Filbey et al., 2015) in areas of the brain associated with tobacco addiction. Review articles (Peters et al., 2012b; Rabin & George, 2015) also note overlap in neurobiological, pharmacological, and genetic mechanisms associated with tobacco and cannabis addiction. Future studies should seek to further clarify the influence of cannabis use on nicotine dependence among cigarette and/or e-cigarette users. Given the risk of sustained tobacco use with co-use of cigarettes, e-cigarettes, and/or cannabis there is a great need for research on dependence and co-use behaviors to inform prevention efforts.

4.1. Limitations and strengths

This study has several limitations. The data are based on a cross-sectional national convenience sample, and we cannot make causal inferences or assess temporality. Like other surveys, the data are self-report and there is potential for recall bias. Due to the small sample size and purpose of the survey, we were unable to examine cannabis dependence or differences with exclusive e-cigarette users. Some findings in our sensitivity analysis, especially for CIG-CAN co-use, were different when co-use status considered current e-cigarette and cannabis use as “every day”/”some days” instead of past 30 day use. As such, our findings related to CIG-CAN co-use should be interpreted with caution. Although current e-cigarette and cannabis users in our study reported use most days in the past 30 days (e-cigarette, M: 16.3/30 days; cannabis, M: 20.2 days/30 days), our findings may have been impacted because we did not differentiate between less frequent and more frequent co-users. Larger samples will allow for the assessment of different co-use status definitions on findings related to nicotine dependence. While we assessed past 30-day blunt use and the type of substance usually vaped, including marijuana/cannabis, we did not assess other routes/modes of cannabis administration such as oral ingestion (i.e., edible cannabis) or inhalation of cannabis oil, wax, or dabs. Future co-use studies may benefit from assessing the influence of cannabis consumption routes/modes on levels of nicotine dependence.

Despite these limitations, our study has several strengths. This is one of the few national samples to capture data that helps us understand nicotine dependence and co-use of cigarettes, e-cigarettes, and cannabis among cigarette smokers aged 18–35. Our results related to CIG-ECIG co-use were consistent in our sensitivity analyses which further bolsters our findings. This study provides new data that can inform larger studies that help us better understand the relationship between nicotine dependence and co-use of tobacco and cannabis.

5. Conclusions

Use of tobacco, including e-cigarettes, and cannabis is very common among cigarette smokers, but larger studies are needed to further clarify whether co-use of cigarettes, e-cigarettes, and/or cannabis is associated with varying levels or increased nicotine dependence. We found that CIG-ECIG co-use is associated with greater nicotine dependence compared to cigarette-only smoking among current smokers aged 18–35. Additionally, CIG-ECIG-CAN co-use and CIG-ECIG co-use is associated with greater nicotine dependence compared to CIG-CAN co-use, although the underlying reasons for these differences are not clear. Studies on CIG-ECIG-CAN co-use are rare, and ongoing surveillance of nicotine dependence among co-users are needed to better inform prevention efforts.

Supplementary Material

Table S1

Disclosure of interest

Thomas Eissenberg is a paid consultant in litigation against the tobacco industry and also the electronic cigarette industry and is named on one patent for a device that measures the puffing behavior of electronic cigarette users, on another patent application for a smartphone app that determines electronic cigarette device and liquid characteristics, and a third patent application for a smoking cessation intervention. Eric Soule is named on a patent application for a smartphone app that determines electronic cigarette device and liquid characteristics.. All other authors report no conflict of interest. This research is supported by grant number U54DA036105 from the National Institute on Drug Abuse of the National Institutes of Health and the Center for Tobacco Products of the U.S. Food and Drug Administration. The content is solely the responsibility of the authors and does not necessarily represent the views of the NIH or the FDA.

Funding

This research is supported by grant number U54DA036105 from the National Institute on Drug Abuse of the National Institutes of Health and the Center for Tobacco Products of the U.S. Food and Drug Administration. DMJ’s effort is also supported by grant number K01DA055088 from the National Institute on Drug Abuse of the National Institutes of Health. The content is solely the responsibility of the authors and does not necessarily represent the views of the NIH or the FDA.

Footnotes

Conflict of Interest

Thomas Eissenberg is a paid consultant in litigation against the tobacco industry and also the electronic cigarette industry and is named on one patent for a device that measures the puffing behavior of electronic cigarette users, on another patent application for a smartphone app that determines electronic cigarette device and liquid characteristics, and a third patent application for a smoking cessation intervention. Eric Soule is named on a patent application for a smartphone app that determines electronic cigarette device and liquid characteristics. The other authors declare they have no conflicts of interest.

Data availability statement

The data are available upon request from the senior author.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Table S1
NIHMS1875449-supplement-Table_S1.docx (17.5KB, docx)

Data Availability Statement

The data are available upon request from the senior author.

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