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Vaping to lose weight: Predictors of adult e-cigarette use for weight loss or control
Addictive Behaviors 66 (2017) 55–59
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Addictive Behaviors journal homepage: www.elsevier.com/locate/addictbeh
Vaping to lose weight: Predictors of adult e-cigarette use for weight loss or control Meghan E. Morean a,b,⁎, Amelia V. Wedel a a b
Oberlin College, Department of Psychology, 120 West Lorain Street Oberlin, OH 44074, USA Yale School of Medicine, Department of Psychiatry, 34 Park St. New Haven, CT 06519, USA
H I G H L I G H T S • • • •
13.5% of a sample of adult e-cigarette users reported vaping to lose/control weight. These adults were heavier vapers, overweight, and reported restricting calories. These adults also preferred coffee or vanilla-flavored e-cigarettes. These adults also reported poor impulse control.
a r t i c l e
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Article history: Received 17 June 2016 Received in revised form 13 October 2016 Accepted 22 October 2016 Available online 24 October 2016 Keywords: Electronic cigarettes E-cigarettes Vaping Eating disorder Weight loss Weight
a b s t r a c t Introduction: Some traditional cigarette smokers are motivated to smoke to lose weight or control their weight. The current study evaluated whether a subset of adult e-cigarette users reported vaping to lose or control their weight and examined potential predictors of vaping for weight management. Methods: Adult e-cigarette users (n = 459) who reported wanting to lose weight or maintain their weight completed an anonymous online survey. Participants reported on demographics, vaping frequency, e-cigarette nicotine content, cigarette smoking status, preferred e-cigarette/e-liquid flavors, current weight status (i.e., overweight, underweight), use of dieting strategies associated with anorexia and bulimia, lifetime history of binge eating, self-discipline, and impulse control. Binary logistic regression was used to examine whether vaping for weight loss/control was associated with the aforementioned variables. Results: Participants who reported vaping for weight loss/control (13.5%) were more likely to vape frequently (adjOR = 1.15; 95% CI [1.00, 1.31]); be overweight (adjOR = 2.80; [1.33, 5.90]); restrict calories (adjOR = 2.23; [1.13, 4.42]); have poor impulse control (adjOR = 0.59; [0.41, 0.86]); and prefer coffee- (adjOR = 2.92; [1.47, 5.80]) or vanilla-flavored e-liquid (adjOR = 7.44; [1.56, 36.08]). Conclusions: A subset of adult e-cigarette users reported vaping for weight loss/control, raising concerns about expanded, scientifically unsubstantiated uses of e-cigarettes. Identifying where individuals obtain information about vaping for weight loss (e.g., e-cigarette ads, Internet) and whether weight-related motives promote e-cigarette initiation among e-cigarette naïve individuals is important to informing regulatory efforts. Further research also is needed to better understand the link between e-liquid flavors and weight loss motivations. © 2016 Elsevier Ltd. All rights reserved.
1. Introduction Current e-cigarette use among American adults rose from 0.3% in 2010 to 6.8% in 2013 (McMillen, Gottlieb, Shaefer, Winickoff, & Klein, 2015). Research attempting to understand these increases in vaping largely has focused on vaping motivations that are relevant to smokers (e.g., vaping helps users quit/reduce smoking) (Berg, Barr, Stratton,
⁎ Corresponding author. E-mail addresses: [email protected] (M.E. Morean), [email protected] (A.V. Wedel).
http://dx.doi.org/10.1016/j.addbeh.2016.10.022 0306-4603/© 2016 Elsevier Ltd. All rights reserved.
Escoffery, & Kegler, 2014; Rutten, Blanke, Agunwamba, et al., 2015). However, vaping motivations that are relevant to nonsmokers have received less research attention (Schoenborn & Gindi, 2015). This study focuses on an established motive for smoking that also may be applicable to both smokers and non-smokers who vape: weight loss or control. Although there is considerable evidence linking smoking to weight loss motives, (Granner, Black, & Abood, 2002; White, McKee, & O'Malley, 2007) to our knowledge, no scientific data have been published on vaping for weight loss/control. However, there are several reasons to believe that some individuals are vaping for weight-related reasons. First, nicotine, which is contained in cigarettes and in many e-cigarettes, has appetite suppressant effects and can help curb cravings for
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M.E. Morean, A.V. Wedel / Addictive Behaviors 66 (2017) 55–59
sweet foods (Chiolero, Faeh, Paccaud, & Cornuz, 2008; Kluger, 1996). Further promoting weight loss, nicotine increases resting metabolic rate, leading to an increased daily caloric expenditure of approximately 200 calories (Audrain-McGovern & Benowitz, 2011). Second, the behavior of smoking a cigarette (and presumably of vaping) can serve as a distractor from or substitute for eating (Kovacs, Correa, & Brandon, 2014). Third, e-cigarettes uniquely are available in a plethora of appealing flavors, (Kong, Morean, Cavallo, Camenga, & Krishnan-Sarin, 2015; Shiffman, Sembower, Pillitteri, Gerlach, & Gitchell, 2015) many of which mimic high calorie/fat foods or beverages (e.g., candy, desserts, alcohol) that may be avoided during attempts to lose weight or control weight. Fourth, anecdotal evidence obtained via sources like YouTube and online message boards suggests some e-cigarette users rely on flavors to help manage cravings for high calorie/fat foods or are vaping as a food substitute. For example, e-cigarette forum users posted that vaping stops a “hand-to-mouth habit”, “curbs appetite”, “tricks my body into thinking I'm munching”, and “stops cravings” (Unforgiven1222, 2014; Panther, 2015; JLC, 2014). Based on prior evidence linking eating disorders like anorexia or bulimia to smoking for weight-related reasons, (Clark, Hurt, Croghan, et al., 2006; Meyers et al., 1997; White, 2012) forums on several pro-eating disorders websites also were examined. Individuals posting on pro-anorexia websites reported that vaping helps curb cravings for food and/or reduces the frequency of binge episodes. For example, one user posted that, “When I feel like binging, I just [vape] a flavor close to my craving.”. Posters also touted vaping as healthier than smoking and noted the added “benefit” of nicotine's appetite suppressant effects (Kiminokokoro & Electronic cigarettes and appetite?, 2015; Tidbit, 2015; Andrea). Finally, vaping companies have attempted to capitalize on the potential link between vaping and weight loss. For example, Vapor Diet advertises itself as the “USA's hottest diet” and entices potential customers to purchase e-juices like pizza, cupcakes, and cocktails with phrases such as “zero calories, zero guilt, tastes like you are eating your favorite foods” (VaporDiet.com). The defunct company VaporTrim used similar marketing tactics: “inhale flavor, curb cravings, lose weight” (Spooky, 2012). Thus, in the current study we aimed to identify whether a subset of adult e-cigarette users reported vaping for weight loss/control within an online sample. Potential predictors for vaping for weight loss/control subsequently were examined. We anticipated that e-cigarette users who were vaping for weight loss/control would vape more frequently, use nicotine e-cigarettes, report being overweight, and prefer flavors that are analogous to high calorie/fat foods or beverages. Based on smoking research, we expected that smokers, females, and individuals who evidenced symptoms of eating disorders also would be more likely to report vaping to lose/control weight (Meyers et al., 1997; White, 2012). Finally, given that behavioral loss of control and impulsivity have been associated both with eating pathology and with cigarette smoking, we anticipated that individuals with high levels of trait impulsivity or poor self-control would be more likely to report vaping to lose/ control weight (Latner, Mond, Kelly, Haynes, & Hay, 2014; Morean, DeMartini, Leeman, et al., 2014; Em, Grilo, & Gearhardt, 2016). 2. Materials & methods 2.1. Participants Six hundred adult e-cigarette users completed an anonymous, online survey. As described below, the analytic sample comprised 459 participants (51.2% male, 73.0% White; mean age 34.42 [SD = 9.69] years) who had complete data for all study variables.
2015, participants were recruited to complete the 15–20-minute survey via Amazon Mechanical Turk (i.e., MTurk), a crowdsourcing data collection site that produces valid scientific survey data (Mason & Suri, 2012). To ensure data quality, only MTurk workers age 18 years and older who had completed at least 5000 previous MTurk jobs (demonstrating platform familiarity) and had an approval rating of 98% or higher (demonstrating quality work) could view the study advertisement. 2344 of these individuals provided consent to complete a series of screening questions that ultimately were used to determine study eligibility. To be eligible, participants had to report: 1) past-month vaping (1460 participants were deemed ineligible based on this question); 2) currently trying to lose or maintain weight (101 additional participants were deemed ineligible based on this question); and 3) residing in the United States (156 additional participants were deemed ineligible on the final screener question). In total, 627 participants were eligible to complete the survey. Twenty-seven individuals never began the survey and 141 were missing data on a central study variable. This resulted in an analytic sample of 459 participants. Participants were compensated $2.00 for their time. 2.3. Measures 2.3.1. Demographics Participants reported their age, biological sex, and race. 2.3.2. Cigarette smoking status Participants reported their current cigarette smoking status as “never-smoker, former smoker, occasional smoker, or regular smoker”. 2.3.3. Vaping to lose/control weight Participants reported whether they currently were “vaping to lose or control [their] weight” (no/yes). 2.3.4. Frequency of vaping Participants reported on how much time they spent vaping each day. Responses included: 1–10, 11–20, 21–30, 31–40, 41–50, 51–60, 61–90, 91–120, and +120 min. 2.3.5. Nicotine content of e-cigarettes Participants reported whether they typically use nicotine or nicotine-free e-cigarettes. 2.3.6. Flavor preferences Participants reported which e-cigarette flavor categories they preferred: tobacco, menthol, mint, vanilla, fruit (like strawberry, blueberry, or peach), candy or dessert (like apple pie, chocolate, or Jolly Rancher), spice (like clove, cinnamon, or nutmeg), alcohol (like piña colada, strawberry daiquiri, or bourbon), and coffee (like espresso, latte, or cappuccino). These flavor categories were included in the current study based on their inclusion in prior research (Kong et al., 2015; Krishnan-Sarin, Morean, Camenga, Cavallo, & Kong, 2015). 2.3.7. Weight perceptions Participants indicated whether they currently are overweight, underweight, or have no current weight problem. 2.3.8. Weight control strategies (Malinauskas, Raedeke, Aeby, Smith, & Dallas, 2006) Participants reported whether they had engaged in three weight control strategies that are associated with eating disorders: calorie restriction, using laxatives after eating, and vomiting after eating.
2.2. Procedure The Institutional Review Board of Oberlin College reviewed all study procedures and materials and confirmed they were in compliance with ethical standards of conducting human research. During September of
2.3.9. Binge eating Binge eating was defined as, “eating what others would consider an unusually large amount of food for the circumstances, accompanied by a sense of losing control over your eating” (Fairburn & Beglin, 2008).
M.E. Morean, A.V. Wedel / Addictive Behaviors 66 (2017) 55–59
Based on this definition, participants reported lifetime engagement in binge eating (no/yes). 2.3.10. Impulse control and self-discipline Participants completed the Abbreviated Self-Control Scale (Morean et al., 2014), a 7-item scale that assesses impulse control (Cronbach's α = 0.82; example item: “Sometimes I can't stop myself from doing something, even if I know it is wrong” [reverse scored]) and self-discipline (Cronbach's α = 0.70; example item: “People say that I have iron self-discipline”). This version of the measure was chosen based on prior research demonstrating that it evidences stronger psychometric properties than prior versions when used to assess self-control in smokers (Morean et al., 2014). 2.4. Data analytic plan We first conducted independent samples t-tests and chi-squares to examine potential differences between the analytic sample and participants who were excluded from the analyses on the basis of having missing data.1 Next, we conducted descriptive analyses on the analytic sample. We then conducted a binary logistic regression predicting vaping to lose/control weight based on the following variables: sex, age, race, cigarette smoking status, e-cigarette nicotine content, flavor preferences, having a weight problem, binge eating, restricting food intake, using laxatives, and vomiting after eating. Prior to interpreting the model results, collinearity diagnostics were examined. 3. Results 3.1. Differences between the analytic sample and excluded participants The analytic sample differed from the participants who were excluded for having missing data in several ways that indicated the analytic sample likely represented a higher risk group. Specifically, the analytic sample comprised heavier vapers, more females, White participants, smokers, individuals who use nicotine e-liquid, individuals who reported calorie restriction, and individuals who were overweight (results not presented). 3.2. Analytic sample demographics In total, 13.5% of the analytic sample reported vaping to lose/control weight. Participants reported vaping between 21 and 40 min per day, on average. Preferences for e-cigarette flavors included fruit (41.4%), tobacco (31.4%), menthol (27.9%), mint (27.2%), dessert (22.0%), coffee (17.2%), vanilla (14.2%), spices (12.6%), and alcohol (6.5%). 57.3% of the sample reported being overweight and 7.5% reported being underweight. Regarding dieting strategies, 52.5% reported restricting calories, 6.5% reported vomiting after eating, and 5.9% reported laxative use. In total, 37.7% reported engaging in a binge-eating episode at some point during their lives. 3.3. Predictors of using e-cigarettes to lose weight With regard to assessing collinearity, variance inflation indices for each predictor were all b 1.38, which indicates only modest correlations among independent variables. Additionally, condition indices were smaller than 20 and none was associated with two or more variables with large variance proportions (≥0.50; results not depicted). As such multicollinearity was deemed not to be a significant concern, and the 1 Initially, we planned to impute missing data. However, the majority of individuals appear to have terminated the survey early, as 62% were missing data on all weight-related variables and 88% were missing data on the impulsivity variables. Given the amount and non-random nature of the missing data, imputation was not appropriate. Hence, we chose to include only participants with complete data in the analytic sample.
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model was interpreted. The binary logistic regression model accounted for 20.6% of the variance in vaping for weight loss/control (p b 0.001, classification accuracy = 87.4%). Participants who reported vaping to lose/control weight vaped more frequently (adjOR = 1.15); were currently overweight (adjOR = 2.80); reported engaging in calorie restriction (adjOR = 2.23); reported poor impulse control (OR = 0.59); and reported preferences for coffee (adjOR = 2.92) and vanilla-flavored eliquid (adjOR = 7.44); all p values b 0.05, see Table 1. 4. Discussion In our sample of adult e-cigarette users, 13.5% reported vaping to lose/control weight. Frequent vapers who reported being overweight, currently engaging in calorie restriction as a weight loss strategy, and/ or having poor impulse control were more likely to report currently vaping to lose/control weight than were their respective counterparts. These findings suggest that vaping could be considered a novel “fad diet”, especially given that vaping for weight loss/control was endorsed by individuals to whom “fad diets” traditionally appeal. Ongoing efforts to inform the public about the potential harms associated with vaping should notify consumers that e-cigarettes have not been approved for weight loss and that frequent vaping may increase the risk of experiencing negative health effects from e-cigarette use. Contrary to study hypotheses, preferences for dessert/candy-flavored e-liquids, specifically, were not associated significantly with vaping to lose/control weight. However, preferences for vanilla and coffee-flavored e-liquids were significantly associated with vaping to lose/ control weight. Of note, vanilla-flavored e-liquids are among the most popular e-liquids and are readily available even in the disposable e-cigarette market. Given the popularity and availability of this inherently sweet flavor, it is possible that vanilla e-liquid may serve as a generic distractor from or substitute for a wide array of foods that would be Table 1 Predictors of current use of e-cigarettes to lose or control weight.
Males Age Whites Time spent vaping per day Current smoking status (Former) Occasional smoker Daily smoker Nicotine-free e-juice Current weight problem (None) Underweight Overweight Dieting strategies Calorie restriction Laxative use Vomiting after eating Binge eating (None) Self-discipline Impulse control Flavor preferences Tobacco Menthol Mint Spices Fruit Dessert Alcohol Coffee Vanilla
B
S.E.
−0.21 0.00 −0.24 0.14
0.33 0.02 0.38 0.07
Adjusted odds Wald ratio 0.39 0.00 0.40 4.11 4.17
95% confidence interval
0.82 1.00 0.79 1.15⁎
0.43 0.97 0.37 1.00
0.66 0.37 3.20 0.05 0.43 0.01 −0.25 0.46 0.29 7.36
1.93 1.05 0.78
0.94 3.96 0.45 2.41 0.32 1.93
0.70 1.03
0.63 1.21 0.38 7.36
2.01 2.80⁎⁎
0.58 6.96 1.33 5.90
0.80 0.95 0.00 −0.23 0.19 −0.52
0.35 0.83 0.64 0.33 0.21 0.19
5.27 1.32 0.00 0.46 0.76 7.70
2.23⁎ 2.58 1.00 0.80 1.20 0.59⁎⁎
1.13 0.51 0.28 0.41 0.79 0.41
4.42 13.02 3.52 1.54 1.82 0.86
0.46 0.51 0.20 −0.03 0.22 0.52 2.10 1.07 2.01
0.36 0.34 0.36 0.47 0.33 0.41 1.10 0.35 0.81
1.63 2.23 0.32 0.00 0.42 1.57 3.63 9.42 6.21
1.59 1.66 1.22 0.97 1.24 1.68 8.16 2.92⁎⁎ 7.44⁎⁎
0.78 0.85 0.61 0.39 0.65 0.75 0.94 1.47 1.54
3.24 3.23 2.45 2.46 2.38 3.76 70.63 5.80 16.08
Note. Sample size for the binary logistic regression model = 459. ⁎ p b 0.05. ⁎⁎ p b 0.01.
1.55 1.04 1.65 1.31
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prohibited on a diet. Furthermore, while it is possible to purchase plain “vanilla” e-liquid, many e-liquid flavors that contain vanilla flavoring are more complex and demonstrate overlap with the dessert category (e.g., vanilla cupcake; vanilla frosting; vanilla crème brulee; vanilla custard). Given the overlap with the candy/dessert category, the fact that preferences for vanilla were associated with more frequent vaping is consistent with study hypotheses. The findings regarding preferences for coffee-flavored e-liquid being linked to vaping for weight loss/control are somewhat more perplexing, but several plausible explanations may help to explain the link. First, while black coffee is neither high in calories nor fat, the coffee flavors described to participants as examples of the category (i.e., latte, cappuccino, mocha) often are high in calories and fat content. For example, a 12-ounce Starbucks latte contains 200 cal and 9 g of fat (Starbucks). Therefore, it is possible that individuals who indicated preferences for coffee flavors were indeed endorsing preferences for sweet flavors that mimic high calorie, high fat beverages. If this were the case, it would be consistent with our general hypothesis. A second possibility is that some participants who use coffee-flavored e-juice for weight loss/control may associate coffee with caffeine and, subsequently with weight loss/control. Although most coffee-flavored e-juices do not contain caffeine, it is possible to purchase caffeinated coffee-flavored e-liquids (and other flavors as well). While we did not assess it in the current study, some participants who reported preferences for coffee-flavored e-liquids and vaping to lose/control may have been using caffeinated e-liquids to increase the effectiveness of vaping for weight loss/management. Future research is needed on this topic. It is worth discussing several ways in which our results did not support our hypotheses. While we anticipated that women would be more likely than men to vape for weight loss, 50% of participants who endorsed vaping for weight management were men. If replication indicates that men use e-cigarettes for weight loss/control at comparable rates to women, this would reflect a departure from the smoking literature. Of note, this finding was supported anecdotally by the fact that many of the YouTube videos we found endorsing e-cigarettes for weight loss were posted by men (CasualKkyle, 2014; Vapor, 2013; Genious, 2014). It also is important to note that neither binge eating, using laxatives, nor vomiting after eating were associated with vaping to lose/control weight in this sample. However, it is possible that relationships would emerge in a clinical sample of individuals with eating disorders. Also, there were no differences in vaping to lose/control weight based on e-cigarette nicotine content, suggesting that perhaps the flavors are sufficient to manage cravings. Finally, there were no differences in vaping to lose/control weight based on cigarette smoking status, indicating that theses constructs may operate independently. However, data were not collected on smoking to lose weight, so it is possible that some dual e-cigarette/cigarette users rely on smoking for weight loss/control. Additional research is needed on these topics. The study findings should be considered in light of several limitations. First, the data were self-report and relied on participants' willingness and ability to respond accurately. Second, the sample comprised adult MTurk workers who reported current vaping and a desire to lose or maintain weight, which may not be representative of the general population of e-cigarette users. Third, it was not possible to determine if any of our participants met DSM-5 criteria for an eating disorder, and further research is needed to determine if vaping for weight loss/ control is more prevalent in clinical populations or if it has any impact on treatment response. Fourth, because the sample comprised adults, future research should explore whether vaping for weight loss/control is prevalent in adolescents, for whom flavors may be more important motivators of vaping (Kong et al., 2015). Fifth, a limited number of e-cigarette flavors were assessed in this study. Currently, thousands of e-cigarette flavors are available for purchase, so assessing a broader range of flavors may have utility in discovering links between flavor preference and vaping for weight management. Sixth, we only assessed a single motive related to weight loss in the current study (i.e., do you currently
vape to lose weight or control your weight?). Future research should be more specific in evaluating factors that are related to weight loss versus weight maintenance. In addition, future research should examine how factors such as flavor preferences and impulsivity relate to other motivations for using e-cigarettes (e.g., to quit smoking). Finally, the current data do not speak to how vaping for weight loss is related to vaping frequency, specifically. Future research examining main effects and interactions between independent variables similar to those included in the current study is warranted. It is possible, for example, that individuals who engage in calorie restriction as a general dieting strategy may vape more frequently only if they are impulsive and specifically are using vaping as a means of reducing calories. In addition, interactions between study variables and flavor preferences could relate differentially to vaping frequency. For example, smokers who are vaping frequently for weight loss may be more likely to vape tobacco flavored e-liquid than non-smokers. In spite of its limitations, the current study is the first to demonstrate that some e-cigarette users vape for weight loss/control and that these users are more likely to vape frequently, be overweight, restrict calories, and having poor impulse control. The findings also suggest that the unique flavors associated with e-cigarettes (relative to cigarettes) may play an important role when considering vaping motivations related to weight. Future studies that assess the use of a wider array e-liquid flavors in samples in which rates of vaping to lose/control weight may be elevated (e.g., adolescents, individuals with eating disorders) are needed and may provide additional support for a link between e-cigarette flavors and vaping to lose/control weight. Role of funding source None. Contributors Dr. Morean conceptualized the study and developed study hypotheses. Dr. Morean and Ms. Wedel developed the self-report survey, ran the statistical analyses, and collaborated on the draft of the manuscript. Both authors have approved the final version of the manuscript. Conflict of interest No conflicts declared. Acknowledgements None.
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Panther. Has vaping helped you lose weight? Vaping underground website. http:// vapingunderground.com/threads/has-vaping-helped-you-lose-weight.48905/. Posted 2015, January 19. (Accessed May 24, 2016). Rutten, L. J., Blanke, K. D., Agunwamba, A. A., et al. (2015). Use of e-cigarettes among current smokers: Associations among reasons for use, quit intentions, and current tobacco use. Nicotine & Tobacco Research, 7(10), 1228–1234. Schoenborn, C. A., & Gindi, R. M. (2015). Electronic cigarette use among adults: United States, 2014. NCHS data brief, no. 217. Hyattsville, MD: National Center for Health Statistics. Shiffman, S., Sembower, M. A., Pillitteri, J. L., Gerlach, K. K., & Gitchell, J. G. (2015). The impact of flavor descriptors on nonsmoking teens' and adult smokers' interest in electronic cigarettes. Nicotine & Tobacco Research, 17(10), 1255–1262. Spooky (2012, March 13). Vaportrim makes cupcakes inhalable, cuts calories to zero. Oddity Central Website. http://www.odditycentral.com/news/vaportrim-makescupcakes-inhalable-cuts-calories-to-zero.html (Accessed May 24, 2016) Starbucks (d). Explore our menu. http://www.starbucks.com/menu/catalog/nutrition? drink=all#view_control=nutritiion Accessed May 24, 2016 Tidbit (2015, January 22). Thinking about getting an e-cig. MyProAna website. http:// www.myproana.com/index.php/topic/347006-thinking-about-getting-an-e-cig/ (Accessed May 24, 2016) Unforgiven1222 (2014). Vaping as appetite suppressant. Reddit website. https://www. reddit.com/r/electronic_cigarette/comments/1jvrhv/vaping_as_appetite_supressant/ (Accessed May 24, 2016) Johnny Vapor. Lose weight & diet by using e-cigs & vaping!!! (Dekang Mint Choco Review). [Video]. YouTube. https://www.youtube.com/watch?v=vrJIexl8VTI. Published 2013, October 24. (Accessed May 24, 2016). VaporDiet.com Website. (Accessed 2016, May 24) White, M. A. (2012). Smoking for weight control and its associations with eating disorder symptomatology. Comprehensive Psychiatry, 53(4), 403–407. White, M. A., McKee, S. A., & O'Malley, S. S. (2007). Smoke and mirrors: Magnified belief that cigarette smoking suppresses weight. Addictive Behaviors, 32(10), 2200–2210.
Contents lists available at ScienceDirect
Addictive Behaviors journal homepage: www.elsevier.com/locate/addictbeh
Vaping to lose weight: Predictors of adult e-cigarette use for weight loss or control Meghan E. Morean a,b,⁎, Amelia V. Wedel a a b
Oberlin College, Department of Psychology, 120 West Lorain Street Oberlin, OH 44074, USA Yale School of Medicine, Department of Psychiatry, 34 Park St. New Haven, CT 06519, USA
H I G H L I G H T S • • • •
13.5% of a sample of adult e-cigarette users reported vaping to lose/control weight. These adults were heavier vapers, overweight, and reported restricting calories. These adults also preferred coffee or vanilla-flavored e-cigarettes. These adults also reported poor impulse control.
a r t i c l e
i n f o
Article history: Received 17 June 2016 Received in revised form 13 October 2016 Accepted 22 October 2016 Available online 24 October 2016 Keywords: Electronic cigarettes E-cigarettes Vaping Eating disorder Weight loss Weight
a b s t r a c t Introduction: Some traditional cigarette smokers are motivated to smoke to lose weight or control their weight. The current study evaluated whether a subset of adult e-cigarette users reported vaping to lose or control their weight and examined potential predictors of vaping for weight management. Methods: Adult e-cigarette users (n = 459) who reported wanting to lose weight or maintain their weight completed an anonymous online survey. Participants reported on demographics, vaping frequency, e-cigarette nicotine content, cigarette smoking status, preferred e-cigarette/e-liquid flavors, current weight status (i.e., overweight, underweight), use of dieting strategies associated with anorexia and bulimia, lifetime history of binge eating, self-discipline, and impulse control. Binary logistic regression was used to examine whether vaping for weight loss/control was associated with the aforementioned variables. Results: Participants who reported vaping for weight loss/control (13.5%) were more likely to vape frequently (adjOR = 1.15; 95% CI [1.00, 1.31]); be overweight (adjOR = 2.80; [1.33, 5.90]); restrict calories (adjOR = 2.23; [1.13, 4.42]); have poor impulse control (adjOR = 0.59; [0.41, 0.86]); and prefer coffee- (adjOR = 2.92; [1.47, 5.80]) or vanilla-flavored e-liquid (adjOR = 7.44; [1.56, 36.08]). Conclusions: A subset of adult e-cigarette users reported vaping for weight loss/control, raising concerns about expanded, scientifically unsubstantiated uses of e-cigarettes. Identifying where individuals obtain information about vaping for weight loss (e.g., e-cigarette ads, Internet) and whether weight-related motives promote e-cigarette initiation among e-cigarette naïve individuals is important to informing regulatory efforts. Further research also is needed to better understand the link between e-liquid flavors and weight loss motivations. © 2016 Elsevier Ltd. All rights reserved.
1. Introduction Current e-cigarette use among American adults rose from 0.3% in 2010 to 6.8% in 2013 (McMillen, Gottlieb, Shaefer, Winickoff, & Klein, 2015). Research attempting to understand these increases in vaping largely has focused on vaping motivations that are relevant to smokers (e.g., vaping helps users quit/reduce smoking) (Berg, Barr, Stratton,
⁎ Corresponding author. E-mail addresses: [email protected] (M.E. Morean), [email protected] (A.V. Wedel).
http://dx.doi.org/10.1016/j.addbeh.2016.10.022 0306-4603/© 2016 Elsevier Ltd. All rights reserved.
Escoffery, & Kegler, 2014; Rutten, Blanke, Agunwamba, et al., 2015). However, vaping motivations that are relevant to nonsmokers have received less research attention (Schoenborn & Gindi, 2015). This study focuses on an established motive for smoking that also may be applicable to both smokers and non-smokers who vape: weight loss or control. Although there is considerable evidence linking smoking to weight loss motives, (Granner, Black, & Abood, 2002; White, McKee, & O'Malley, 2007) to our knowledge, no scientific data have been published on vaping for weight loss/control. However, there are several reasons to believe that some individuals are vaping for weight-related reasons. First, nicotine, which is contained in cigarettes and in many e-cigarettes, has appetite suppressant effects and can help curb cravings for
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sweet foods (Chiolero, Faeh, Paccaud, & Cornuz, 2008; Kluger, 1996). Further promoting weight loss, nicotine increases resting metabolic rate, leading to an increased daily caloric expenditure of approximately 200 calories (Audrain-McGovern & Benowitz, 2011). Second, the behavior of smoking a cigarette (and presumably of vaping) can serve as a distractor from or substitute for eating (Kovacs, Correa, & Brandon, 2014). Third, e-cigarettes uniquely are available in a plethora of appealing flavors, (Kong, Morean, Cavallo, Camenga, & Krishnan-Sarin, 2015; Shiffman, Sembower, Pillitteri, Gerlach, & Gitchell, 2015) many of which mimic high calorie/fat foods or beverages (e.g., candy, desserts, alcohol) that may be avoided during attempts to lose weight or control weight. Fourth, anecdotal evidence obtained via sources like YouTube and online message boards suggests some e-cigarette users rely on flavors to help manage cravings for high calorie/fat foods or are vaping as a food substitute. For example, e-cigarette forum users posted that vaping stops a “hand-to-mouth habit”, “curbs appetite”, “tricks my body into thinking I'm munching”, and “stops cravings” (Unforgiven1222, 2014; Panther, 2015; JLC, 2014). Based on prior evidence linking eating disorders like anorexia or bulimia to smoking for weight-related reasons, (Clark, Hurt, Croghan, et al., 2006; Meyers et al., 1997; White, 2012) forums on several pro-eating disorders websites also were examined. Individuals posting on pro-anorexia websites reported that vaping helps curb cravings for food and/or reduces the frequency of binge episodes. For example, one user posted that, “When I feel like binging, I just [vape] a flavor close to my craving.”. Posters also touted vaping as healthier than smoking and noted the added “benefit” of nicotine's appetite suppressant effects (Kiminokokoro & Electronic cigarettes and appetite?, 2015; Tidbit, 2015; Andrea). Finally, vaping companies have attempted to capitalize on the potential link between vaping and weight loss. For example, Vapor Diet advertises itself as the “USA's hottest diet” and entices potential customers to purchase e-juices like pizza, cupcakes, and cocktails with phrases such as “zero calories, zero guilt, tastes like you are eating your favorite foods” (VaporDiet.com). The defunct company VaporTrim used similar marketing tactics: “inhale flavor, curb cravings, lose weight” (Spooky, 2012). Thus, in the current study we aimed to identify whether a subset of adult e-cigarette users reported vaping for weight loss/control within an online sample. Potential predictors for vaping for weight loss/control subsequently were examined. We anticipated that e-cigarette users who were vaping for weight loss/control would vape more frequently, use nicotine e-cigarettes, report being overweight, and prefer flavors that are analogous to high calorie/fat foods or beverages. Based on smoking research, we expected that smokers, females, and individuals who evidenced symptoms of eating disorders also would be more likely to report vaping to lose/control weight (Meyers et al., 1997; White, 2012). Finally, given that behavioral loss of control and impulsivity have been associated both with eating pathology and with cigarette smoking, we anticipated that individuals with high levels of trait impulsivity or poor self-control would be more likely to report vaping to lose/ control weight (Latner, Mond, Kelly, Haynes, & Hay, 2014; Morean, DeMartini, Leeman, et al., 2014; Em, Grilo, & Gearhardt, 2016). 2. Materials & methods 2.1. Participants Six hundred adult e-cigarette users completed an anonymous, online survey. As described below, the analytic sample comprised 459 participants (51.2% male, 73.0% White; mean age 34.42 [SD = 9.69] years) who had complete data for all study variables.
2015, participants were recruited to complete the 15–20-minute survey via Amazon Mechanical Turk (i.e., MTurk), a crowdsourcing data collection site that produces valid scientific survey data (Mason & Suri, 2012). To ensure data quality, only MTurk workers age 18 years and older who had completed at least 5000 previous MTurk jobs (demonstrating platform familiarity) and had an approval rating of 98% or higher (demonstrating quality work) could view the study advertisement. 2344 of these individuals provided consent to complete a series of screening questions that ultimately were used to determine study eligibility. To be eligible, participants had to report: 1) past-month vaping (1460 participants were deemed ineligible based on this question); 2) currently trying to lose or maintain weight (101 additional participants were deemed ineligible based on this question); and 3) residing in the United States (156 additional participants were deemed ineligible on the final screener question). In total, 627 participants were eligible to complete the survey. Twenty-seven individuals never began the survey and 141 were missing data on a central study variable. This resulted in an analytic sample of 459 participants. Participants were compensated $2.00 for their time. 2.3. Measures 2.3.1. Demographics Participants reported their age, biological sex, and race. 2.3.2. Cigarette smoking status Participants reported their current cigarette smoking status as “never-smoker, former smoker, occasional smoker, or regular smoker”. 2.3.3. Vaping to lose/control weight Participants reported whether they currently were “vaping to lose or control [their] weight” (no/yes). 2.3.4. Frequency of vaping Participants reported on how much time they spent vaping each day. Responses included: 1–10, 11–20, 21–30, 31–40, 41–50, 51–60, 61–90, 91–120, and +120 min. 2.3.5. Nicotine content of e-cigarettes Participants reported whether they typically use nicotine or nicotine-free e-cigarettes. 2.3.6. Flavor preferences Participants reported which e-cigarette flavor categories they preferred: tobacco, menthol, mint, vanilla, fruit (like strawberry, blueberry, or peach), candy or dessert (like apple pie, chocolate, or Jolly Rancher), spice (like clove, cinnamon, or nutmeg), alcohol (like piña colada, strawberry daiquiri, or bourbon), and coffee (like espresso, latte, or cappuccino). These flavor categories were included in the current study based on their inclusion in prior research (Kong et al., 2015; Krishnan-Sarin, Morean, Camenga, Cavallo, & Kong, 2015). 2.3.7. Weight perceptions Participants indicated whether they currently are overweight, underweight, or have no current weight problem. 2.3.8. Weight control strategies (Malinauskas, Raedeke, Aeby, Smith, & Dallas, 2006) Participants reported whether they had engaged in three weight control strategies that are associated with eating disorders: calorie restriction, using laxatives after eating, and vomiting after eating.
2.2. Procedure The Institutional Review Board of Oberlin College reviewed all study procedures and materials and confirmed they were in compliance with ethical standards of conducting human research. During September of
2.3.9. Binge eating Binge eating was defined as, “eating what others would consider an unusually large amount of food for the circumstances, accompanied by a sense of losing control over your eating” (Fairburn & Beglin, 2008).
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Based on this definition, participants reported lifetime engagement in binge eating (no/yes). 2.3.10. Impulse control and self-discipline Participants completed the Abbreviated Self-Control Scale (Morean et al., 2014), a 7-item scale that assesses impulse control (Cronbach's α = 0.82; example item: “Sometimes I can't stop myself from doing something, even if I know it is wrong” [reverse scored]) and self-discipline (Cronbach's α = 0.70; example item: “People say that I have iron self-discipline”). This version of the measure was chosen based on prior research demonstrating that it evidences stronger psychometric properties than prior versions when used to assess self-control in smokers (Morean et al., 2014). 2.4. Data analytic plan We first conducted independent samples t-tests and chi-squares to examine potential differences between the analytic sample and participants who were excluded from the analyses on the basis of having missing data.1 Next, we conducted descriptive analyses on the analytic sample. We then conducted a binary logistic regression predicting vaping to lose/control weight based on the following variables: sex, age, race, cigarette smoking status, e-cigarette nicotine content, flavor preferences, having a weight problem, binge eating, restricting food intake, using laxatives, and vomiting after eating. Prior to interpreting the model results, collinearity diagnostics were examined. 3. Results 3.1. Differences between the analytic sample and excluded participants The analytic sample differed from the participants who were excluded for having missing data in several ways that indicated the analytic sample likely represented a higher risk group. Specifically, the analytic sample comprised heavier vapers, more females, White participants, smokers, individuals who use nicotine e-liquid, individuals who reported calorie restriction, and individuals who were overweight (results not presented). 3.2. Analytic sample demographics In total, 13.5% of the analytic sample reported vaping to lose/control weight. Participants reported vaping between 21 and 40 min per day, on average. Preferences for e-cigarette flavors included fruit (41.4%), tobacco (31.4%), menthol (27.9%), mint (27.2%), dessert (22.0%), coffee (17.2%), vanilla (14.2%), spices (12.6%), and alcohol (6.5%). 57.3% of the sample reported being overweight and 7.5% reported being underweight. Regarding dieting strategies, 52.5% reported restricting calories, 6.5% reported vomiting after eating, and 5.9% reported laxative use. In total, 37.7% reported engaging in a binge-eating episode at some point during their lives. 3.3. Predictors of using e-cigarettes to lose weight With regard to assessing collinearity, variance inflation indices for each predictor were all b 1.38, which indicates only modest correlations among independent variables. Additionally, condition indices were smaller than 20 and none was associated with two or more variables with large variance proportions (≥0.50; results not depicted). As such multicollinearity was deemed not to be a significant concern, and the 1 Initially, we planned to impute missing data. However, the majority of individuals appear to have terminated the survey early, as 62% were missing data on all weight-related variables and 88% were missing data on the impulsivity variables. Given the amount and non-random nature of the missing data, imputation was not appropriate. Hence, we chose to include only participants with complete data in the analytic sample.
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model was interpreted. The binary logistic regression model accounted for 20.6% of the variance in vaping for weight loss/control (p b 0.001, classification accuracy = 87.4%). Participants who reported vaping to lose/control weight vaped more frequently (adjOR = 1.15); were currently overweight (adjOR = 2.80); reported engaging in calorie restriction (adjOR = 2.23); reported poor impulse control (OR = 0.59); and reported preferences for coffee (adjOR = 2.92) and vanilla-flavored eliquid (adjOR = 7.44); all p values b 0.05, see Table 1. 4. Discussion In our sample of adult e-cigarette users, 13.5% reported vaping to lose/control weight. Frequent vapers who reported being overweight, currently engaging in calorie restriction as a weight loss strategy, and/ or having poor impulse control were more likely to report currently vaping to lose/control weight than were their respective counterparts. These findings suggest that vaping could be considered a novel “fad diet”, especially given that vaping for weight loss/control was endorsed by individuals to whom “fad diets” traditionally appeal. Ongoing efforts to inform the public about the potential harms associated with vaping should notify consumers that e-cigarettes have not been approved for weight loss and that frequent vaping may increase the risk of experiencing negative health effects from e-cigarette use. Contrary to study hypotheses, preferences for dessert/candy-flavored e-liquids, specifically, were not associated significantly with vaping to lose/control weight. However, preferences for vanilla and coffee-flavored e-liquids were significantly associated with vaping to lose/ control weight. Of note, vanilla-flavored e-liquids are among the most popular e-liquids and are readily available even in the disposable e-cigarette market. Given the popularity and availability of this inherently sweet flavor, it is possible that vanilla e-liquid may serve as a generic distractor from or substitute for a wide array of foods that would be Table 1 Predictors of current use of e-cigarettes to lose or control weight.
Males Age Whites Time spent vaping per day Current smoking status (Former) Occasional smoker Daily smoker Nicotine-free e-juice Current weight problem (None) Underweight Overweight Dieting strategies Calorie restriction Laxative use Vomiting after eating Binge eating (None) Self-discipline Impulse control Flavor preferences Tobacco Menthol Mint Spices Fruit Dessert Alcohol Coffee Vanilla
B
S.E.
−0.21 0.00 −0.24 0.14
0.33 0.02 0.38 0.07
Adjusted odds Wald ratio 0.39 0.00 0.40 4.11 4.17
95% confidence interval
0.82 1.00 0.79 1.15⁎
0.43 0.97 0.37 1.00
0.66 0.37 3.20 0.05 0.43 0.01 −0.25 0.46 0.29 7.36
1.93 1.05 0.78
0.94 3.96 0.45 2.41 0.32 1.93
0.70 1.03
0.63 1.21 0.38 7.36
2.01 2.80⁎⁎
0.58 6.96 1.33 5.90
0.80 0.95 0.00 −0.23 0.19 −0.52
0.35 0.83 0.64 0.33 0.21 0.19
5.27 1.32 0.00 0.46 0.76 7.70
2.23⁎ 2.58 1.00 0.80 1.20 0.59⁎⁎
1.13 0.51 0.28 0.41 0.79 0.41
4.42 13.02 3.52 1.54 1.82 0.86
0.46 0.51 0.20 −0.03 0.22 0.52 2.10 1.07 2.01
0.36 0.34 0.36 0.47 0.33 0.41 1.10 0.35 0.81
1.63 2.23 0.32 0.00 0.42 1.57 3.63 9.42 6.21
1.59 1.66 1.22 0.97 1.24 1.68 8.16 2.92⁎⁎ 7.44⁎⁎
0.78 0.85 0.61 0.39 0.65 0.75 0.94 1.47 1.54
3.24 3.23 2.45 2.46 2.38 3.76 70.63 5.80 16.08
Note. Sample size for the binary logistic regression model = 459. ⁎ p b 0.05. ⁎⁎ p b 0.01.
1.55 1.04 1.65 1.31
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prohibited on a diet. Furthermore, while it is possible to purchase plain “vanilla” e-liquid, many e-liquid flavors that contain vanilla flavoring are more complex and demonstrate overlap with the dessert category (e.g., vanilla cupcake; vanilla frosting; vanilla crème brulee; vanilla custard). Given the overlap with the candy/dessert category, the fact that preferences for vanilla were associated with more frequent vaping is consistent with study hypotheses. The findings regarding preferences for coffee-flavored e-liquid being linked to vaping for weight loss/control are somewhat more perplexing, but several plausible explanations may help to explain the link. First, while black coffee is neither high in calories nor fat, the coffee flavors described to participants as examples of the category (i.e., latte, cappuccino, mocha) often are high in calories and fat content. For example, a 12-ounce Starbucks latte contains 200 cal and 9 g of fat (Starbucks). Therefore, it is possible that individuals who indicated preferences for coffee flavors were indeed endorsing preferences for sweet flavors that mimic high calorie, high fat beverages. If this were the case, it would be consistent with our general hypothesis. A second possibility is that some participants who use coffee-flavored e-juice for weight loss/control may associate coffee with caffeine and, subsequently with weight loss/control. Although most coffee-flavored e-juices do not contain caffeine, it is possible to purchase caffeinated coffee-flavored e-liquids (and other flavors as well). While we did not assess it in the current study, some participants who reported preferences for coffee-flavored e-liquids and vaping to lose/control may have been using caffeinated e-liquids to increase the effectiveness of vaping for weight loss/management. Future research is needed on this topic. It is worth discussing several ways in which our results did not support our hypotheses. While we anticipated that women would be more likely than men to vape for weight loss, 50% of participants who endorsed vaping for weight management were men. If replication indicates that men use e-cigarettes for weight loss/control at comparable rates to women, this would reflect a departure from the smoking literature. Of note, this finding was supported anecdotally by the fact that many of the YouTube videos we found endorsing e-cigarettes for weight loss were posted by men (CasualKkyle, 2014; Vapor, 2013; Genious, 2014). It also is important to note that neither binge eating, using laxatives, nor vomiting after eating were associated with vaping to lose/control weight in this sample. However, it is possible that relationships would emerge in a clinical sample of individuals with eating disorders. Also, there were no differences in vaping to lose/control weight based on e-cigarette nicotine content, suggesting that perhaps the flavors are sufficient to manage cravings. Finally, there were no differences in vaping to lose/control weight based on cigarette smoking status, indicating that theses constructs may operate independently. However, data were not collected on smoking to lose weight, so it is possible that some dual e-cigarette/cigarette users rely on smoking for weight loss/control. Additional research is needed on these topics. The study findings should be considered in light of several limitations. First, the data were self-report and relied on participants' willingness and ability to respond accurately. Second, the sample comprised adult MTurk workers who reported current vaping and a desire to lose or maintain weight, which may not be representative of the general population of e-cigarette users. Third, it was not possible to determine if any of our participants met DSM-5 criteria for an eating disorder, and further research is needed to determine if vaping for weight loss/ control is more prevalent in clinical populations or if it has any impact on treatment response. Fourth, because the sample comprised adults, future research should explore whether vaping for weight loss/control is prevalent in adolescents, for whom flavors may be more important motivators of vaping (Kong et al., 2015). Fifth, a limited number of e-cigarette flavors were assessed in this study. Currently, thousands of e-cigarette flavors are available for purchase, so assessing a broader range of flavors may have utility in discovering links between flavor preference and vaping for weight management. Sixth, we only assessed a single motive related to weight loss in the current study (i.e., do you currently
vape to lose weight or control your weight?). Future research should be more specific in evaluating factors that are related to weight loss versus weight maintenance. In addition, future research should examine how factors such as flavor preferences and impulsivity relate to other motivations for using e-cigarettes (e.g., to quit smoking). Finally, the current data do not speak to how vaping for weight loss is related to vaping frequency, specifically. Future research examining main effects and interactions between independent variables similar to those included in the current study is warranted. It is possible, for example, that individuals who engage in calorie restriction as a general dieting strategy may vape more frequently only if they are impulsive and specifically are using vaping as a means of reducing calories. In addition, interactions between study variables and flavor preferences could relate differentially to vaping frequency. For example, smokers who are vaping frequently for weight loss may be more likely to vape tobacco flavored e-liquid than non-smokers. In spite of its limitations, the current study is the first to demonstrate that some e-cigarette users vape for weight loss/control and that these users are more likely to vape frequently, be overweight, restrict calories, and having poor impulse control. The findings also suggest that the unique flavors associated with e-cigarettes (relative to cigarettes) may play an important role when considering vaping motivations related to weight. Future studies that assess the use of a wider array e-liquid flavors in samples in which rates of vaping to lose/control weight may be elevated (e.g., adolescents, individuals with eating disorders) are needed and may provide additional support for a link between e-cigarette flavors and vaping to lose/control weight. Role of funding source None. Contributors Dr. Morean conceptualized the study and developed study hypotheses. Dr. Morean and Ms. Wedel developed the self-report survey, ran the statistical analyses, and collaborated on the draft of the manuscript. Both authors have approved the final version of the manuscript. Conflict of interest No conflicts declared. Acknowledgements None.
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