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. Author manuscript; available in PMC: 2023 Aug 1.
Published in final edited form as: Eat Behav. 2022 Jul 5;46:101652. doi: 10.1016/j.eatbeh.2022.101652

Associations between Eating Disorder Symptoms and Smoking and Vaping Use and Motives in College Students

Kathrin M Hennigan 1,*, Kathleen R Olson 1,*, Jessica H Baker 1, Melissa A Munn-Chernoff 1
PMCID: PMC9679963  NIHMSID: NIHMS1848438  PMID: 35839570

Abstract

A positive association between eating disorder (ED) symptoms and cigarette use exists. However, little is known about the association between ED symptoms and e-cigarette use, as well as how these symptoms are related to motives for using cigarettes and e-cigarettes. In this study, 716 college students (M age=19.23, SD=1.65; 61% female) completed an online survey that included the Eating Pathology Symptoms Inventory, smoking and vaping questionnaires, and the Drinking Motives Questionnaire-Revised, which was modified for smoking and vaping. We examined mean differences in ED symptoms in lifetime (and past-month) cigarette and e-cigarette users versus non-users, and investigated correlations between ED symptoms and smoking and vaping motives. Finally, we evaluated whether biological sex influenced the results. Overall, 30.4% of students reported lifetime smoking, 10.5% reported past-month smoking, 23% reported lifetime vaping, and 9.5% reported past-month vaping. With the exception of higher mean scores for negative attitudes toward obesity in students reporting lifetime smoking versus never smoking after adjusting for sex (M=5.97 vs. M=4.52, t[713]=−3.76, q=0.004), no significant mean differences emerged between those who used nicotine and those who did not, which reflected small to moderate effect sizes. Few associations were observed between ED symptoms and nicotine use motives. These findings suggest that the comorbidity between ED symptoms and smoking and vaping in a non-clinical sample is minimal, although additional research with larger sample sizes of males and females is needed.

Keywords: eating disorders, disordered eating, smoking, vaping, smoking motives, vaping motives

1. Introduction

Eating disorders (EDs) and nicotine use are major public health concerns. The prevalence of EDs in the general population is 1%-3.5% (Hudson, Hiripi, Pope, & Kessler, 2007). The prevalence of traditional cigarette use (herein referred to as smoking) has decreased, from 20.9% in 2005 to 15.5% in 2016 (Jamal et al., 2018), whereas the prevalence of electronic cigarette (e-cigarette) use (herein referred to as vaping) has increased (US Department of Health and Human Services, 2016), particularly among young adults. Individuals with a lifetime ED report a higher prevalence of smoking than individuals without an ED (Anzengruber et al., 2006; Solmi et al., 2016), with specific ED symptoms—binge eating, purging, and intense fear of gaining weight—being more strongly associated with nicotine dependence than others (Anzengruber et al., 2006; Munn-Chernoff et al., 2020; Solmi et al., 2016). Numerous somatic conditions are associated with EDs and smoking, including osteoporosis, fractures, esophageal cancer, and obesity (Solmi et al., 2016). Thus, individuals who report both ED symptoms and smoking could be at greater risk for the presence of these somatic conditions.

Despite the increase in vaping, little information is known about associations between EDs and vaping and if findings between EDs and smoking generalize to vaping. Understanding the relation between ED symptoms and vaping is critical because the harmful effects of vaping, such as oxidative stress and acute endothelial dysfunction (Betteridge, 2000; Sassano et al., 2018), may compound the physical harm caused by EDs and their symptoms. To our knowledge, only one study examined the association between nicotine use and ED symptoms. In adolescents, all unhealthy weight control behaviors increased as smoking and vaping increased (Lee & Lee, 2019). By specifically focusing on ED symptoms rather than diagnoses, we may identify individuals who are at high-risk for developing co-occurring EDs and nicotine misuse, pinpoint key symptoms for this association, and inform prevention and treatment approaches.

Another important component of this research includes smoking and vaping motives. Nicotine is an appetite suppressant, and some individuals believe smoking helps control eating behaviors (Copeland, Spears, Baillie, & McVay, 2016). Smoking is a perceived method for weight control (Anzengruber et al., 2006). Smoking motives may differ by sex, with smoking behavior in women being more heavily influenced by non-nicotine factors than smoking behaviors in men (Perkins, 2009).1 Regardless of sex, vaping to control appetite is positively associated with body concerns in college students (Napolitano, Lynch, & Stanton, 2020). E-cigarettes are available in many flavors, and individuals with EDs may choose sweet e-liquid flavors to curb cravings or stop binges (Morean & L'Insalata, 2018). Although this suggests that weight-related motives for vaping in individuals with EDs exist, the research surrounding this is limited. It is also unknown if more common smoking and vaping motives, including enhancement (i.e., heightening positive affect) and coping (i.e., managing negative mood; Cooper, 1994), are related to ED symptoms. College students and adults often report vaping for enjoyment or enhancement (Saddleson et al., 2016), and enhancement motives are associated with binge eating in students (Boggiano et al., 2014). Coping is a commonly identified smoking motive among adults (Fidler & West, 2009) and is the strongest smoking motive in individuals with EDs (George & Waller, 2005). Because both motives relate to more chronic smoking behavior (Tate, Pomerleau, & Pomerleau, 1994), they may influence vaping behavior, particularly among individuals with ED symptoms. Examining a range of ED symptoms and their relation to motives for smoking and vaping may reveal key symptoms to evaluate in clinical settings for more precise treatment of individuals with this comorbid presentation.

College students are an ideal population to investigate ED symptoms and nicotine use because they are at high-risk for both traits (Hudson et al., 2007; Kenne, Mix, Banks, & Fischbein, 2016). Up to 50% of college students report ED symptoms (Lipson & Sonneville, 2017), and 36% of young adults (US Department of Health and Human Services, 2016) and 28%-40% of college students (Kenne et al., 2016; Lanza, Pittman, & Batshoun, 2017) report lifetime vaping versus 16% of adults over 25 years old (US Department of Health and Human Services, 2016). Over half of young adults who use e-cigarettes have never smoked cigarettes (Cornelius, Wang, Jamal, Loretan, & Neff, 2020). Notable sex differences exist, with the prevalence of ED symptoms greater in women than men (Eisenberg, Nicklett, Roeder, & Kirz, 2011). Moreover, men are more likely to report smoking than women, and male college students are more likely to report vaping than female college students (Choi & Forster, 2013; Jamal et al., 2018; Kenne et al., 2016). Thus, college students are especially vulnerable to ED symptoms and nicotine use, particularly vaping, emphasizing the importance of including this population in research investigating associations between ED symptoms and nicotine use.

We examined associations between multiple transdiagnostic ED symptoms and nicotine use. First, we assessed differences in ED symptoms among college students 1) reporting lifetime versus never smoking, 2) past-month versus no past-month smoking, 3) lifetime versus never vaping, and 4) past-month versus no past-month vaping. Given prior studies on associations of EDs and their symptoms with smoking traits (Anzengruber et al., 2006; Munn-Chernoff et al., 2020; Solmi et al., 2016), we hypothesized that cigarette and e-cigarette users would exhibit higher levels of binge eating, purging, and fear of weight gain than individuals who never used these nicotine methods. Second, we investigated smoking and vaping motives in college students reporting lifetime smoking or lifetime vaping and their association with ED symptoms. Consistent with findings on enhancement motives and binge eating (Boggiano et al., 2014), we predicted stronger associations between binge eating and enhancement motives for smoking and vaping. Given sex differences in ED symptoms and nicotine use, we also evaluated whether biological sex influenced any significant findings. Understanding associations between these traits and motivations behind smoking and vaping could provide critical information for prevention and treatment, in turn decreasing risk for additional medical conditions.

2. Methods

2.1. Participants and Procedure

Participants included 716 students aged ≥18 years old (Mage=19.23, SD=1.65, age range: 18-35 years) recruited via a psychology subject pool for the Carolina College Assessment for Research and Education in Science (Carolina C.A.R.E.S.) study in 2016-2017. Participants, who received course credit for participating, provided consent online and then completed an online self-report survey via Qualtrics. The local institutional review board approved the study.

Four hundred thirty-seven (61.03%) students were female.2 Overall, 477 (66.62%) participants identified as Caucasian, 114 (15.92%) as Asian, 66 (9.22%) as African American, 30 (4.19%) as Multiracial, 28 (3.91%) as Other, and 1 (0.14%) as Pacific Islander. Fifty-two (7.27%) individuals reported being Hispanic. Most (n=336; 46.93%) were first-year students, with 202 (28.21%) sophomores, 127 (17.74%) juniors, 50 (6.98%) seniors, and 1 (0.14%) graduate student. At the time of the study, these statistics were representative of the University of North Carolina at Chapel Hill as a whole.

2.2. Measures

2.2.1. Eating Pathology Symptoms Inventory (EPSI)

The EPSI (Forbush et al., 2013), a 45-item self-report questionnaire, assessed ED symptoms in the past month through eight subscales: body dissatisfaction, binge eating, cognitive restraint, purging, restricting, excessive exercise, negative attitudes toward obesity, and muscle building. Item responses ranged from 0 (never) to 4 (very often), and relevant scores were summed for each subscale. Higher scores indicated greater disordered eating. In a college-aged sample, the EPSI had Cronbach’s α ranging from 0.66 to 0.95 (Forbush et al., 2013). The Cronbach’s α of each subscale in this sample was 0.90 (body dissatisfaction), 0.88 (binge eating), 0.77 (cognitive restraint), 0.85 (purging), 0.87 (restricting), 0.89 (excessive exercise), 0.89 (negative attitudes toward obesity), and 0.78 (muscle building).

2.2.2. Smoking and Vaping Questionnaires

Two yes/no questions assessed smoking. “Have you ever tried a cigarette?” assessed lifetime smoking. “In the past month, have you smoked a cigarette?” reflected past month smoking. These two yes/no questions also assessed vaping, with “cigarette” being changed to “e-cigarette”.

2.2.3. Smoking and Vaping Motives Questionnaires

We modified the Drinking Motives Questionnaire-Revised (DMQ-R; Cooper, 1994), as recommended in the PhenX Toolkit (Hamilton et al., 2011), to evaluate lifetime smoking and vaping motives by replacing the phrase “drink alcohol” with “smoke cigarettes” or “smoke e-cigarettes.” We included two subscales: enhancement (i.e., using a substance to heighten positive affect) and coping (i.e., using a substance to manage negative mood). Considering their lifetime cigarette and e-cigarette use, participants rated how often each item reflected their motives for smoking or vaping on a scale ranging from 1 (almost never/never) to 5 (almost always/always), and relevant items were summed to create each motive. Higher scores indicated greater motive for cigarette or e-cigarette use. When used to assess alcohol motives, the DMQ-R enhancement and coping scales showed good validity in adolescents and adults, with alphas ranging from 0.84 to 0.88 (Cooper, 1994). When modified to assess smoking motives, the enhancement (α=0.79) and coping (α=0.70) subscales showed adequate internal consistency across individuals aged 15-65 years (Glavak Tkalić, Sučić, & Dević, 2013). To our knowledge, no other studies have reported on the reliability or validity of the DMQ-R modified for vaping. In our sample, Cronbach’s α for the smoking questionnaire was 0.72 and 0.62 for the enhancement and coping subscales, respectively. The Cronbach’s α for the vaping questionnaire was 0.80 and 0.83 for the enhancement and coping subscales, respectively.

2.3. Statistical Analyses

We used SAS version 9.4 (SAS Institute Inc, 2019) for data analysis. Missing data were only present for one individual for each of the ED symptoms, lifetime cigarette use, and lifetime e-cigarette use; thus, no adjustments were made to account for missing data. Purging was the only ED symptom that was positively skewed and was therefore log-transformed before analyses. Using independent samples t-tests, we first evaluated mean differences in ED symptoms between students reporting lifetime smoking versus no lifetime smoking and lifetime vaping versus no lifetime vaping. We repeated analyses based on past-month nicotine use. Cohen’s d (Cohen, 1988) was calculated to determine the effect size of the association, where 0.20, 0.50, and 0.80 indicate small, medium, and large effect sizes, respectively. To explore associations between ED symptoms and nicotine use motives, we then assessed Pearson correlations between the eight ED symptoms and two motives subscales for both smoking and vaping in individuals with a lifetime history of reporting these nicotine use methods. Finally, we examined the effect of biological sex on any significant results in post-hoc analyses via linear regression or partial correlations. False Discovery Rate (FDR) correction (Benjamini & Hochberg, 1995) was performed to control for multiple testing (q<0.05; n=72).

3. Results

Overall, 217 individuals (30.35%) reported lifetime smoking, 75 (10.47%) reported past-month smoking, 165 (23.08%) reported lifetime vaping, and 68 (9.50%) reported past-month vaping. Additionally, Table 1 shows a breakdown of participants who reported one or both nicotine use methods in their lifetime and in the past month.

Table 1.

Lifetime and past-month nicotine use.

Lifetime Nicotine Use Past-Month Nicotine Use
Nicotine Use Group Frequency (%) Frequency (%)
Neither 457 (63.92) 44 (35.48)
Smoking Only 93 (13.01) 27 (21.77)
Vaping Only 41 (5.73) 24 (19.35)
Smoking and Vaping 124 (17.34) 29 (23.39)
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With three exceptions, no significant mean differences in ED symptoms between individuals who did and did not endorse lifetime or past-month smoking or vaping emerged (Table 2). Students reporting lifetime smoking endorsed higher mean scores of negative attitudes toward obesity and muscle building than those who reported never smoking (negative attitudes toward obesity: M=5.97, SD=5.08 vs. M=4.52, SD=4.58, t[713]=−3.76, q=0.004; muscle building: M=3.65, SD=3.99 vs. M=2.51, SD=3.43, t[361.22]=−3.63, q=0.004; Table 2). Students who reported lifetime vaping endorsed higher muscle building mean scores than those who reported never vaping (M=3.62, SD=4.11 vs. M=2.63, SD=3.47; t[238.18]=−2.83, q=0.04; Table 2). Effect sizes for these mean differences were small to moderate (0.01 to 0.31). Post-hoc analyses revealed that more males (n=119, 42.81%) than females (n=98, 22.43%) reported ever smoking (χ2(1)=33.39, q=0.003), and more males (n=93, 33.45%) than females (n=72, 16.48%) reported ever vaping (χ2(1)=27.59, q=0.003). After adjusting for sex, the association between lifetime smoking and negative attitudes toward obesity remained significant (β=1.33, SE=0.39, t=3.38, q=0.008), whereas associations between lifetime smoking and muscle building (β=0.39, SE=0.27, t=1.42, q=0.31) and lifetime vaping and muscle building (β=0.25, SE=0.30, t=0.85, q=0.65) were not.

Table 2.

Mean differences (and standard deviations) in eating disorder symptoms between cigarette and e-cigarette users versus never users.

Lifetime Cigarette Use Past-Month Cigarette Use
Eating Disorder Symptom Use
(n=217)		 No Use
(n=498)		 t(df) q d Use
(n=75)		 No Use
(n=142)		 t(df) q d
Body dissatisfaction 8.00 (7.07) 9.15 (7.07) 2.00 (713) .15 .16 6.81 (6.77) 8.62 (7.17) 1.80 (215) .19 .26
Binge eating 7.35 (6.43) 6.45 (5.63) −1.80 (366.78) .19 .15 7.80 (6.64) 7.12 (6.33) −.74 (215) .68 .10
Cognitive restraint 4.41 (3.18) 4.65 (3.13) .94 (713) .58 .08 3.88 (2.95) 4.68 (3.28) 1.78 (215) .19 .26
Purging* .67 (1.89) .78 (2.35) .05 (713) .98 .05 .72 (2.13) .65 (1.75) .70 (215) .68 .04
Restricting 4.15 (4.83) 4.00 (4.62) −.38 (713) .85 .03 4.48 (4.95) 3.97 (4.77) −.74 (215) .68 .10
Excessive exercise 6.41 (5.58) 5.64 (5.35) −1.77 (713) .19 .14 6.07 (4.53) 6.60 (6.07) .73 (190.84) .68 .10
Negative attitudes toward obesity 5.97 (5.08) 4.52 (4.58) −3.76 (713) .004 .30 5.92 (4.68) 6.00 (5.30) .11 (215) .98 .02
Muscle building 3.65 (3.99) 2.51 (3.43) −3.63 (361.22) .005 .31 4.12 (4.13) 3.39 (3.91) −1.27 (215) .37 .18
Lifetime E-Cigarette Use Past-Month E-Cigarette Use
Eating Disorder Symptom Use
(n=165)		 No Use
(n=550)		 t(df) q d Use
(n=68)		 No Use
(n=97)		 t(df) q d
Body dissatisfaction 7.97 (6.83) 9.05 (7.14) 1.71 (713) .20 .15 7.26 (6.79) 8.46 (6.85) 1.11 (163) .47 .18
Binge eating 6.96 (5.90) 6.65 (5.90) −.60 (713) .74 .05 7.32 (6.75) 6.71 (5.24) −.63 (120.48) .74 .10
Cognitive restraint 4.47 (3.21) 4.60 (3.12) .47 (713) .83 .04 4.72 (3.39) 4.30 (3.09) −.83 (163) .65 .13
Purging* .82 (2.29) .73 (2.20) −.21 (713) .98 .04 .74 (1.94) .88 (2.51) .42 (163) .83 .06
Restricting 4.24 (4.62) 3.99 (4.70) −.59 (713) .74 .05 3.65 (4.25) 4.65 (4.85) 1.37 (163) .33 .22
Excessive exercise 6.53 (5.34) 5.67 (5.44) −1.79 (713) .19 .16 6.60 (5.28) 6.48 (5.40) −.14 (163) .98 .02
Negative attitudes toward obesity 5.76 (4.82) 4.72 (4.75) −2.45 (713) .07 .22 5.78 (4.65) 5.74 (4.97) −.05 (163) .98 .01
Muscle building 3.62 (4.11) 2.63 (3.47) −2.83 (238.18) .04 .26 4.12 (4.56) 3.28 (3.75) −1.29 (163) .37 .20
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Note:

*

Symptom was log-transformed, though raw means and standard deviations are shown for ease of interpretation. False discovery rate q-values were calculated to adjust for multiple comparisons (n=72). Significant q-values (<0.05) are in bold-type. Cohen’s d effect sizes are classified as small (d = 0.20), medium (d = 0.50), and large (d = 0.80; Cohen, 1988).

Next, we examined correlations between ED symptoms and lifetime smoking (or vaping) motives among individuals who had ever reported smoking (n=217) or vaping (n=165) (Table 3). We did not examine correlations between ED symptoms and past-month smoking or vaping due to the small sample size (n=75 and n=68, respectively). Regarding smoking motives, students who reported lifetime smoking had mean scores of 1.72 (SD=0.92, range: 1.00-5.00) on the enhancement subscale and 1.27 (SD=0.59, range: 1.00-4.20) on the coping subscale. With few exceptions, no significant correlations between ED symptoms and smoking motives were observed. Two significant positive correlations emerged for body dissatisfaction (r=0.24, q=0.009) and purging (r=0.21, q=0.03) with smoking as a coping mechanism. After adjusting for sex, both correlations remained significant (body dissatisfaction: r=0.30, q=0.003; purging: r=0.26, q=0.005).

Table 3.

Correlations between enhancement and coping motives subscales with eating disorder symptoms among individuals who ever reported smoking (n=217) or vaping (n=165) in their lifetime.

Lifetime Enhancement
Smoking		 Lifetime Coping
Smoking		 Lifetime Enhancement
Vaping		 Lifetime Coping
Vaping
Eating Disorder
Symptom		 r p q r p q r p q r p q
Body dissatisfaction .00 .96 .98 .24 .0007 .009 −.01 .87 .98 .18 .03 .11
Binge eating .03 .67 .83 .18 .01 .07 .20 .02 .07 .13 .10 .22
Cognitive restraint .00 1.0 1.0 .12 .10 .21 .13 .12 .24 .15 .07 .19
Purging* −.01 .92 .98 .21 .0003 .03 −.03 .76 .90 .17 .03 .12
Restricting .00 .96 .98 .18 .02 .07 .01 .95 .98 .14 .09 .20
Excessive exercise .03 .68 .83 .04 .56 .74 .07 .42 .65 −.01 .86 .98
Negative attitudes toward obesity .12 .10 .21 .18 .01 .07 .08 .33 .56 .18 .03 .12
Muscle building .18 .01 .07 .09 .22 .39 .22 .01 .05 .06 .48 .68
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Note:

*

Symptom was log-transformed. False discovery rate q-values were calculated to adjust for multiple comparisons (n=72). Significant q-values (<0.05) are in bold-type.

Students who reported lifetime vaping had a mean score of 1.76 (SD=0.90, range: 1.00-4.40) on the enhancement subscale and a mean score of 1.18 (SD=0.44, range: 1.00-3.60) on the coping subscale. No significant correlations between ED symptoms and vaping motives emerged (Table 3).

4. Discussion

We investigated associations between specific ED symptoms and nicotine use by examining a range of transdiagnostic ED symptoms among collegiate cigarette and e-cigarette users. Nearly 30% of students reported lifetime smoking, which is higher than the 15.5% reported previously (Jamal et al., 2018). Corroborating prior studies (Kenne et al., 2016; Lanza et al., 2017), we also found that approximately 23% of students reported lifetime vaping, demonstrating the commonality of e-cigarette experimentation among college students. Few mean differences in ED symptoms between individuals who did and did not use nicotine—lifetime or past-month—were observed. The small to moderate effect sizes indicated that any mean difference in ED symptom scores between both nicotine use groups was minimal in this sample. Finally, we found little evidence for significant associations between ED symptoms and nicotine use motives.

In contrast to existing studies demonstrating significant associations of binge eating and purging with nicotine misuse (Anzengruber et al., 2006; Munn-Chernoff et al., 2020; Solmi et al., 2016), the majority of associations between ED symptoms and nicotine use in this study were not significant. Two primary reasons for this difference exist. First, prior studies included individuals with a diagnosis of an ED or of more regular/problematic nicotine users, whereas our study likely captured both occasional and regular users. We were unable to assess frequency and quantity of smoking and vaping in this study, which could have limited our ability to detect significant association. Thus, this association may only appear in regular nicotine users or the desire to binge eat and/or purge may increase as individuals become more regular nicotine users. Second, prior studies included samples comprised primarily or exclusively of women/females (Anzengruber et al., 2006; Munn-Chernoff et al., 2020; Solmi et al., 2016), whereas 40% (n=279) of the participants in our study were male. It is possible that sex differences in a portion of these associations do exist, but we were underpowered to detect them. This is especially salient since the prevalence of ED symptoms higher in women than men (Eisenberg et al., 2011), and males are more likely to report smoking and vaping than females (Choi & Forster, 2013; Jamal et al., 2018; Kenne et al., 2016). Additional research should directly compare whether associations are indeed strongest in individuals with an ED diagnosis versus ED symptoms, strongest among problematic users or those who use with greater frequency and quantity, and if sex differences do exist within well-powered samples of males and females.

Only the association between negative attitudes toward obesity and lifetime smoking was significant after adjusting for sex and had an effect size equal to 0.30. This finding supported our hypothesis. Research indicates that nicotine is an appetite suppressant (Solmi et al., 2016). Fear of fatness refers to an intense fear of gaining weight (Copeland et al., 2016), which resembles the EPSI subscale ‘negative attitudes toward obesity’. An avoidance coping style is associated with many types of substance use, including smoking (Bricker, Schiff, & Comstock, 2011), and fear of fatness may fall into this avoidant tendency (Levitt, 2003). In a community sample, the prevalence of intense fear of gaining weight was higher among individuals with nicotine dependence than controls (Munn-Chernoff et al., 2020). Thus, individuals with EDs who smoke may use cigarettes to cope with their fear of gaining weight and avoid their negative attitudes toward obesity. Still, most associations were null, differences between nicotine use groups were of small to medium effect, and the pattern of significance for negative attitudes toward obesity was inconsistent across past month smoking and vaping. Further, we were unable to examine the frequency and quantity of smoking and vaping, which may have contributed to our null results. Finally, negative attitudes toward obesity are common in the general population, with nearly one-quarter of Americans reporting stigmatizing attitudes toward obesity (Hilbert, Rief, & Braehler, 2008). Therefore, additional research is needed before drawing firm conclusions.

With respect to nicotine use motives, most of the associations were also not significant, which could be due to our inclusion of college student sample rather than a clinical sample or the lack of a frequency and quantity assessment of smoking and vaping. However, two notable findings emerged with respect to smoking. Because purging is a symptom of bulimia nervosa and the binge-eating/purging subtype of anorexia nervosa, the significant positive association between purging and coping motives for smoking partially supported our hypothesis and suggests that purging may be a key ED symptom contributing to use of coping motives for smoking. For instance, prior research found that individuals with a history of bulimia nervosa were more likely to endorse coping as a substance use motive (Luce, Engler, & Crowther, 2007). Women with bulimia nervosa or binge-eating disorder more often endorsed coping as a drinking motive than individuals reporting an ED not otherwise specified and healthy controls (Luce et al., 2007). Purging may be one coping strategy for women, providing negative reinforcement and regulating negative affect (Smyth et al., 2007; Wedig & Nock, 2010). Additionally, although we did not hypothesize this, we did find a significant positive association between body dissatisfaction and coping motives for lifetime smoking. This positive association supports past findings that smoking is associated with weight control (Copeland et al., 2016), whereby individuals may smoke to cope with their body dissatisfaction. That we did not find a significant association between these two ED symptoms and vaping could reflect the smaller sample size for lifetime vaping (n=165) than lifetime smoking (n=217). Further, associations that exist may only be seen or may be the strongest among individuals with an ED diagnosis or those who engage in heavier or more problematic nicotine use.

Study strengths include the large sample and assessment of multiple transdiagnostic ED symptoms pertinent across sex that relate to nicotine use and motives. College students—a group at high risk of ED symptoms (Lipson & Sonneville, 2017) and vaping (Kenne et al., 2016; Lanza et al., 2017)—exclusively comprised our sample. Although this specificity is a strength, it could also be a limitation because our findings may not generalize to non-college populations. A second limitation is that the lifetime and past-month smoking and vaping questions did not assess frequency and quantity of these behaviors. It is likely that our assessment of lifetime users included both occasional and regular users, which could lead to a low resolution to detect significant associations. Third, despite assessing enhancement and coping motives for smoking and vaping, we did not examine other prominent motives (e.g., weight loss/control, curiosity, social) in the Carolina C.A.R.E.S. survey for brevity. Fourth, due to small sample size, we were unable to compare sex differences among those who smoked and those who vaped on mean scores for ED symptoms. Fifth, to the best of our knowledge, the vaping motives questionnaire created for this study has not been used in previous research. Finally, Cronbach’s alphas for the smoking motives questionnaire were lower than for the other questionnaires; thus, these results should be interpreted with caution.

Overall, we examined mean differences in ED symptoms between cigarette and e-cigarette users and non-users and demonstrated how smoking and vaping motives relate to ED symptoms. In general, we found few significant associations for both smoking and vaping. Additional research should clarify the significant difference in mean scores for negative attitudes toward obesity between lifetime cigarette users and non-users using alternative questions, as well as significant positive associations for body dissatisfaction and purging with coping motives for smoking after adjusting for sex. Future research in larger samples of males and females should examine ED symptoms related to nicotine use, as well as multiple smoking and vaping motives, among problematic nicotine users. The latter could elucidate possible ED-specific motives for smoking or vaping. Ecological momentary assessments could explore purging and smoking/vaping in real-time to assess the temporality of these coping behaviors among regular cigarette and e-cigarette users. As one of the first studies to examine multiple transdiagnostic ED symptoms related to cigarette/e-cigarettes use and motives, these findings could inform future research and clinical practice for individuals experiencing comorbid EDs and nicotine use.

Highlights.

  • Few studies have examined eating disorder symptoms and nicotine use associations

  • Eating disorder symptoms and nicotine use are prevalent among college students

  • Few significant findings emerged, which showed small to moderate effect sizes

  • Eating disorder symptoms were generally not correlated with smoking and vaping

Role of Funding Sources

This work was supported by funding from the Department of Psychology and Neuroscience at the University of North Carolina at Chapel Hill, the National Institute of Mental Health under grant K01 MH106675 to Dr. Baker, and the National Institute on Alcohol Abuse and Alcoholism under grant K01 AA025113 to Dr. Munn-Chernoff. NIH had no role in the study design, collection, analysis, or interpretation of the data, writing the manuscript, or the decision to submit the paper for publication.

Footnotes

Conflict of Interest

All authors declare that they have no conflicts of interest.

1

We recognize and appreciate the importance of correctly using the terms for biological sex (e.g., male and female) and gender/gender identity (e.g., man, woman). Here, we use terms for both biological sex and gender/gender identity to reflect the terms used to describe participants in the prior research studies.

2

Although we used a question on biological sex to determine if someone was male or female, the results of other studies may be based on biological sex or gender, so caution should be used when comparing our results to prior work.

References

  1. Anzengruber D, Klump KL, Thornton L, Brandt H, Crawford S, Fichter MM, … Bulik CM (2006). Smoking in eating disorders. Eating Behaviors, 7(4), 291–299. [DOI] [PubMed] [Google Scholar]
  2. Benjamini Y, & Hochberg Y (1995). Controlling the false discovery rate: A practical and powerful approach to multiple testing. Journal of the Royal Statistical Society. Series B (Methodological), 57(1), 449–518. [Google Scholar]
  3. Betteridge DJ (2000). What is oxidative stress? Metabolism, 49(2 Suppl 1), 3–8. doi: 10.1016/s0026-0495(00)80077-3 [DOI] [PubMed] [Google Scholar]
  4. Boggiano MM, Burgess EE, Turan B, Soleymani T, Daniel S, Vinson LD, … Morse A (2014). Motives for eating tasty foods associated with binge-eating. Results from a student and a weight-loss seeking population. Appetite, 83, 160–166. doi: 10.1016/j.appet.2014.08.026 [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Bricker JB, Schiff L, & Comstock BA (2011). Does avoidant coping influence young adults' smoking?: A ten-year longitudinal study. Nicotine & Tobacco Research, 13(10), 998–1002. doi: 10.1093/ntr/ntr074 [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Choi K, & Forster J (2013). Characteristics associated with awareness, perceptions, and use of electronic nicotine delivery systems among young US Midwestern adults. American Journal of Public Health, 103(3), 556–561. doi: 10.2105/AJPH.2012.300947 [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Cohen J (1988). Statistical power analysis for the behavioral sciences (Vol. 2nd). Hillsdale, NJ: Lawrence Earlbaum Associates. [Google Scholar]
  8. Cooper ML (1994). Motivations for alcohol use among adolescents: Development and validation of a four-factor model. Psychological Assessment, 6(2), 117–128. doi:https://doi.apa.org/doiLanding?doi=10.1037%2F1040-3590.6.2.117 [Google Scholar]
  9. Copeland AL, Spears CA, Baillie LE, & McVay MA (2016). Fear of fatness and drive for thinness in predicting smoking status in college women. Addictive Behaviors, 54, 1–6. doi: 10.1016/j.addbeh.2015.11.010 [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Cornelius ME, Wang TW, Jamal A, Loretan CG, & Neff LJ (2020). Tobacco product use among adults - United States, 2019. Morbidity and Mortality Weekly Report, 69(46), 1736–1742. doi: 10.15585/mmwr.mm6946a4 [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Eisenberg D, Nicklett EJ, Roeder K, & Kirz NE (2011). Eating disorder symptoms among college students: Prevalence, persistence, correlates, and treatment-seeking. Journal of American College Health, 59(8), 700–707. doi: 10.1080/07448481.2010.546461 [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Fidler JA, & West R (2009). Self-perceived smoking motives and their correlates in a general population sample. Nicotine & Tobacco Research, 11(10), 1182–1188. doi: 10.1093/ntr/ntp120 [DOI] [PubMed] [Google Scholar]
  13. Forbush KT, Wildes JE, Pollack LO, Dunbar D, Luo J, Patterson K, … Watson D (2013). Development and validation of the Eating Pathology Symptoms Inventory (EPSI). Psychological Assessment, 25(3), 859–878. doi: 10.1037/a0032639 [DOI] [PubMed] [Google Scholar]
  14. George A, & Waller G (2005). Motivators for smoking in women with eating disorders. European Eating Disorders Review, 13(6), 417–423. doi: 10.1002/erv.62 [DOI] [Google Scholar]
  15. Glavak Tkalić R, Sučić I, & Dević I (2013). Motivation for substance use: Why do people use alcohol, tobacco and marijuana? Društvena Istraživanja, 22(4), 601–625. doi: 10.5559/di.22.4.03 [DOI] [Google Scholar]
  16. Hamilton CM, Strader LC, Pratt JG, Maiese D, Hendershot T, Kwok RK, … Haines J (2011). The PhenX Toolkit: Get the most from your measures. Am J Epidemiol, 174(3), 253–260. doi: 10.1093/aje/kwr193 [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Hilbert A, Rief W, & Braehler E (2008). Stigmatizing attitudes toward obesity in a representative population-based sample. Obesity (Silver Spring), 16(7), 1529–1534. doi: 10.1038/oby.2008.263 [DOI] [PubMed] [Google Scholar]
  18. Hudson JI, Hiripi E, Pope HG Jr., & Kessler RC (2007). The prevalence and correlates of eating disorders in the National Comorbidity Survey Replication. Biological Psychiatry, 61(3), 348–358. [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Jamal A, Phillips E, Gentzke AS, Homa DM, Babb SD, King BA, & Neff LJ (2018). Current cigarette smoking among adults - United States, 2016. Morbidity and Mortality Weekly Report, 67(2), 53–59. doi: 10.15585/mmwr.mm6702a1 [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Kenne DR, Mix D, Banks M, & Fischbein R (2016). Electronic cigarette initiation and correlates of use among never, former, and current tobacco cigarette smoking college students. Journal of Substance Use, 21(5), 491–494. [Google Scholar]
  21. Lanza HI, Pittman P, & Batshoun J (2017). Obesity and cigarette smoking: Extending the link to e-cigarette/vaping use. Am J Health Behav, 41(3), 338–347. doi: 10.5993/AJHB.41.3.13 [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Lee Y, & Lee KS (2019). Relationship between unhealthy weight control behaviors and substance use patterns among Korean adolescents: Results from the 2017 national youth risk behavior survey. Public Health, 174, 56–64. doi: 10.1016/j.puhe.2019.06.005 [DOI] [PubMed] [Google Scholar]
  23. Levitt DH (2003). Drive for thinness and fear of fat: Separate yet related constructs? Eating Disorders, 11(3), 221–234. doi: 10.1080/10640260390218729 [DOI] [PubMed] [Google Scholar]
  24. Lipson SK, & Sonneville KR (2017). Eating disorder symptoms among undergraduate and graduate students at 12 U.S. colleges and universities. Eating Behaviors, 24, 81–88. doi: 10.1016/j.eatbeh.2016.12.003 [DOI] [PubMed] [Google Scholar]
  25. Luce KH, Engler PA, & Crowther JH (2007). Eating disorders and alcohol use: Group differences in consumption rates and drinking motives. Eating Behaviors, 8(2), 177–184. doi: 10.1016/j.eatbeh.2006.04.003 [DOI] [PubMed] [Google Scholar]
  26. Morean ME, & L'Insalata A (2018). Electronic cigarette use among individuals with a self-reported eating disorder diagnosis. International Journal of Eating Disorders, 51(1), 77–81. doi: 10.1002/eat.22793 [DOI] [PubMed] [Google Scholar]
  27. Munn-Chernoff MA, Few LR, Matherne CE, Baker JH, Men VY, McCutcheon VV, … Duncan AE (2020). Eating disorders in a community-based sample of women with alcohol use disorder and nicotine dependence. Drug and Alcohol Dependence, 212, 107981. doi: 10.1016/j.drugalcdep.2020.107981 [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Napolitano MA, Lynch SB, & Stanton CA (2020). Young adult e-cigarette users: Perceptions of stress, body image, and weight control. Eating and Weight Disorders, 25(2), 487–495. doi: 10.1007/s40519-018-0627-6 [DOI] [PubMed] [Google Scholar]
  29. Perkins KA (2009). Sex differences in nicotine reinforcement and reward: Influences on the persistence of tobacco smoking. Nebraska Symposium on Motivation, 55, 143–169. doi: 10.1007/978-0-387-78748-0_9 [DOI] [PubMed] [Google Scholar]
  30. Saddleson ML, Kozlowski LT, Giovino GA, Goniewicz ML, Mahoney MC, Homish GG, & Arora A (2016). Enjoyment and other reasons for electronic cigarette use: Results from college students in New York. Addictive Behaviors, 54, 33–39. doi: 10.1016/j.addbeh.2015.11.012 [DOI] [PubMed] [Google Scholar]
  31. SAS Institute Inc. (2019). SAS/OR 9.4 User's Guide. Cary, NC: SAS Institute. [Google Scholar]
  32. Sassano MF, Davis ES, Keating JE, Zorn BT, Kochar TK, Wolfgang MC, … Tarran R (2018). Evaluation of e-liquid toxicity using an open-source high-throughput screening assay. PLoS Biology, 16(3), e2003904. doi: 10.1371/journal.pbio.2003904 [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Smyth JM, Wonderlich SA, Heron KE, Sliwinski MJ, Crosby RD, Mitchell JE, & Engel SG (2007). Daily and momentary mood and stress are associated with binge eating and vomiting in bulimia nervosa patients in the natural environment. Journal of Consulting and Clinical Psychology, 75(4), 629–638. doi: 10.1037/0022-006X.75.4.629 [DOI] [PubMed] [Google Scholar]
  34. Solmi M, Veronese N, Sergi G, Luchini C, Favaro A, Santonastaso P, … Stubbs B (2016). The association between smoking prevalence and eating disorders: A systematic review and meta-analysis. Addiction, 111(11), 1914–1922. doi: 10.1111/add.13457 [DOI] [PubMed] [Google Scholar]
  35. Tate JC, Pomerleau CS, & Pomerleau OF (1994). Pharmacological and non-pharmacological smoking motives: A replication and extension. Addiction, 89(3), 321–330. doi: 10.1111/j.1360-0443.1994.tb00899.x [DOI] [PubMed] [Google Scholar]
  36. US Department of Health and Human Services. (2016). E-cigarette use among youth and young adults: A report of the Surgeon General. Retrieved from https://www.cdc.gov/tobacco/data_statistics/sgr/e-cigarettes/pdfs/2016_sgr_entire_report_508.pdf
  37. Wedig MM, & Nock MK (2010). The functional assessment of maladaptive behaviors: A preliminary evaluation of binge eating and purging among women. Psychiatry Research, 178(3), 518–524. doi: 10.1016/j.psychres.2009.05.010 [DOI] [PubMed] [Google Scholar]

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