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. Author manuscript; available in PMC: 2020 Apr 1.
Published in final edited form as: Addict Behav. 2018 Oct 29;91:21–29. doi: 10.1016/j.addbeh.2018.10.043

Flavored electronic cigarette use, preferences, and perceptions in pregnant mothers: A correspondence analysis approach

Laura R Stroud a,b, George D Papandonatos c, Katelyn Borba b, Tessa Kehoe b, Lori AJ Scott-Sheldon a,b
PMCID: PMC6358514  NIHMSID: NIHMS1512619  PMID: 30446262

Abstract

Use, preferences, and perceptions of flavored electronic cigarettes (e-cigarettes) were investigated in an ethnically diverse sample of pregnant mothers (N = 100; 50% smokers, Mage = 26; 66% low income; 65% minorities) via detailed interviews. Fruit and mint were the most commonly used flavors. Pregnant women endorsed increased use of fruit flavored e-cigarettes in pregnancy and greater preferences and intentions to use sweet flavors (fruit and candy) and lowest preferences for tobacco flavors. No differences in perceptions of general, pregnancy, or fetal-related health risks emerged across flavors. Latent factor mapping (biplots) based on correspondence analyses of contingency tables revealed clustering of more-preferred fruit and candy flavors versus least-preferred tobacco flavored e-cigarettes, with other sweet flavors— mint and alcohol—clustering more closely with fruit and candy flavors, and more pungent flavors—spice, coffee, chocolate—clustering near tobacco. Correspondence analysis also revealed uncorrelated clustering of preferences and harm perceptions, with intentions showing associations with both preferences and harm perceptions. Preference for fruit and mint flavored e-cigarettes and decreased harm perceptions significantly differentiated lifetime e-cigarette users from non-users. Results highlight preferences for fruit and mint flavored e-cigarettes, and links between preferences for fruit and mint flavors and lifetime use of e-cigarettes in women assessed during pregnancy. These findings also highlight the utility of correspondence analysis for elucidating clustering of flavor perceptions and preferences for novel tobacco products.

Keywords: pregnancy, e-cigarette, flavor, tobacco, perceptions, preferences

1. Introduction

Electronic cigarettes (E-cigarettes) are designed to deliver nicotine and mimic sensations of conventional cigarettes without combusting tobacco. E-cigarettes generate an aerosol or “vapor” by heating an e-liquid typically composed of nicotine, propylene glycol/glycerin, and flavorings (Benowitz & Fraiman, 2017; Brown & Cheng, 2014). Although e-cigarettes deliver nicotine (the primary addictive agent in cigarettes), they do not involve combustion of tobacco, which has been linked to adverse health effects of conventional cigarettes in adults (Benowitz & Fraiman, 2017; J. Chen, Bullen, & Dirks, 2017). Thus, e-cigarettes were initially marketed as healthier, safer alternatives to conventional cigarettes for smoking cessation and to allow smokers to circumvent smoke-free laws (Collins, Glasser, Abudayyeh, Pearson, & Villanti, 2018). Assertions regarding the health benefits of e-cigarettes have diminished over time based on emerging evidence showing that e-cigarettes may increase cardiovascular and other health risks (Glantz & Bareham, 2018). Furthermore, e-cigarettes have attracted new tobacco users such as youth which has prompted action by the United States Food and Drug Administration (FDA) to enact regulations restricting the sale and distribution of e-cigarettes to children and youth (U.S. Food and Drug Administration, 2016).

Use of e-cigarettes has rapidly increased since their introduction to the United States in 2007. Rates of use doubled annually between 2008 and 2014 (Carroll Chapman & Wu, 2014; Grana, Benowitz, & Glantz, 2014). Recent studies have also highlighted e-cigarette use in pregnant women (Bhandari et al., 2018; McCubbin, Fallin-Bennett, Barnett, & Ashford, 2017; Wagner, Camerota, & Propper, 2017). These studies show prevalence rates of e-cigarette use in pregnancy ranging from 4-15%. Further, data from the first wave of the Population Assessment of Tobacco and Health (PATH) study revealed prevalence rates of 4.9% e-cigarette use in all pregnant women—second in prevalence only to cigarettes—and prevalence rates of 28.5% e-cigarette use among pregnant tobacco users (Kurti et al., 2017).

Perceptions that e-cigarettes are less harmful than convention cigarettes have decreased over time among U.S. adults (Huerta, Walker, Mullen, Johnson, & Ford, 2017; Majeed et al., 2017). However, the specific risks associated with the use of e-cigarettes are not yet clear, especially as e-cigarettes and alternative nicotine delivery systems continue to evolve (Gentry, Forouhi, & Notley, 2018; Murthy, 2017; Smith et al., 2018). The issue of risks from e-cigarettes is even more salient during pregnancy due to impact of maternal use on both mother and fetus and evidence for fetal toxicity from both nicotine and tobacco combustion products (England, Bunnell, Pechacek, Tong, & McAfee, 2015). In non-pregnant adults, tobacco combustion products are considered more harmful than nicotine; however, during pregnancy, nicotine is a well-established developmental toxicant, characterized by the FDA as having teratogenic effects on human fetuses (U.S. Department of Health and Human Services, 2016a). Although, to date, no studies have documented the impact of maternal e-cigarette use on offspring development, decades of research have supported links between maternal cigarette use and infant morbidity (e.g., low birth weight) and mortality (sudden infant death syndrome). These links have now been deemed sufficient to infer causality by the Surgeon General (U.S. Department of Health and Human Services, 2004, 2014).

Flavors may increase the appeal of e-cigarettes particularly in attracting new users, women, and vulnerable populations. Prior research shows preferences for sweet flavored e-cigarettes among youth, women, and cigarette smokers trying to quit (Krishnan-Sarin, Morean, Camenga, Cavallo, & Kong, 2015; Piñeiro et al., 2016; Shiffman, Sembower, Pillitteri, Gerlach, & Gitchell, 2015). Pregnant women may also be vulnerable to the appeal of flavorings due to alterations in taste, cravings, and nausea during pregnancy, and variable patterning of tobacco use over gestation (Faas, Melgert, & de Vos, 2010). For example, pregnant women have an increased sensitivity to bitter tastes during pregnancy (Ochsenbein-Kolble, von Mering, Zimmermann, & Hummel, 2005). Pregnant women with an increased sensitivity to bitter tastes were more likely to use menthol cigarettes (Oncken et al., 2015). Pregnant mothers also show an increase in nausea and vomiting, which may lead to altered preferences for flavors (Bayley, Dye, Jones, DeBono, & Hill, 2002; Koren, Madjunkova, & Maltepe, 2014). Finally, pregnant mothers have shown highly variable patterning in both quantity and frequency of cigarette use over pregnancy, potentially making them more vulnerable to the appeal of flavors and novel tobacco products (Eiden et al., 2013; Pickett, Wakschlag, Dai, & Leventhal, 2003). Despite evidence for increased preferences for flavored e-cigarettes in vulnerable populations (Garrison, O'Malley, Gueorguieva, & Krishnan-Sarin, 2018; Zare, Nemati, & Zheng, 2018a), and potential increased susceptibility of pregnant women to flavored products, little is known regarding use, preferences, or perceptions of e-cigarette flavors in pregnant women.

1.1. The Present Study

To address this gap, we conducted detailed interviews regarding use, preferences, and perceptions of e-cigarette flavorings in a diverse sample of pregnant tobacco users and non-users. Correspondence analysis (Greenacre, 1984), a latent factor mapping technique widely employed in consumer marketing research to identify clustering of perception measures by flavors, and flavors by perception measures (e.g., Lee and Chambers (2010)) was used. To our knowledge, this is the first application of this technique to identify flavor preferences and perceptions in novel tobacco products. The aims of this study were to: (1) investigate patterns of e-cigarette flavor use over the peripartum period (i.e., the period shortly before, during, and immediately following pregnancy), (2) characterize preferences and perceptions of e-cigarette flavors in pregnant women, (3) identify clustering of perception measures by flavors and flavors by perception measures using correspondence analysis, and (4) investigate links between flavors preferences and perceptions and use of e-cigarettes. We hypothesized that sweet and mint flavors would be most used, most preferred, and perceived as less harmful than less sweet and tobacco flavored e-cigarettes. We further hypothesized that preference for sweet and mint flavors would be associated with increased use. To our knowledge, the present study is the first to investigate patterns of e-cigarette flavor use in pregnant mothers as well as preferences, intentions, and harm perceptions regarding e-cigarette flavors.

2. Material and Methods

2.1. Participants

Participants were 100 English-speaking, primarily low-income, and racially and ethnically diverse pregnant mothers drawn from a larger study of smoking during pregnancy and fetal development. Participants were recruited from obstetrical offices, health centers, and community postings in southern New England. Eligible participants were over-sampled for prenatal cigarette use, and were enrolled if they were ages 18-40, had no current/prior involvement with child protective services, and no history of serious gestational medical conditions (e.g., pre-eclampsia). Participants in the parent study agreed to participate in a substudy focused on use, preferences, and perceptions of tobacco product flavors during pregnancy or after delivery. All study procedures were reviewed and approved by local Institutional Review Boards; all participants provided written informed consent. The final analytic sample included 50 pregnant women who endorsed cigarette use over pregnancy and 50 controls, who denied cigarette use over pregnancy.

2.2. Procedures

2.2.1. Recruitment.

Participants who were confirmed to be pregnant were enrolled during the second trimester (M = 21 weeks gestation; SD = 1) following on-site recruitment efforts targeting first and second trimester pregnant women at obstetric clinics serving a large maternal hospital in Southern New England. Our recruitment approach was supplemented by posting flyers at local obstetric clinics, health centers, and in the community.

2.2.2. Maternal Interviews.

Participants completed four interview sessions across second and third trimesters of pregnancy and one month postpartum as part of the parent study. Specifically, interview sessions took place at 21±1, 27±1, and 33±1 weeks gestation and at 31±1 days postpartum. The Timeline Follow Back (TLFB) was completed at each interview session. The TLFB is a structured assessment of daily tobacco and other substance use that uses a calendar marked with key dates (e.g., holidays, personal events) to cue memory and increase accuracy of recall for tobacco and other substance use (Robinson, Sobell, Sobell, & Leo, 2014; Sobell & Sobell, 1992, 1995). The first interview session covered three months prior to conception through 21±1 weeks. Each subsequent session covered the period from the prior session to the current session. The TLFB was adapted to also query mothers regarding their use of e-cigarettes and other tobacco products (e.g., hookah, cigars) over pregnancy, preconception, and one month postpartum. In addition, mothers were queried regarding their choice of flavors for each episode of e-cigarette use. Pregnant mothers also completed the Tobacco Flavors Interview (below) during third trimester (M = 34 weeks, SD = 1). Finally, mothers were asked questions about their demographics (e.g., income) as well as their health and pregnancy history.

2.2.3. Tobacco Flavors Interview

Developed by our group, the Tobacco Flavors Interview uses a portable flip chart presentation easel binder (Scott-Sheldon & Stroud, 2015). The interview includes a series of questions regarding use, perceptions, preferences, and intentions to use flavored tobacco products across eight flavor categories (menthol/mint, clove/spice, fruit, chocolate, alcohol [e.g., margarita], coffee and other beverages, candy or other sweets [e.g., cotton candy, butterscotch], and tobacco/unflavored) consistent with the flavor categories from the PATH study (U.S. Department of Health and Human Services, 2016b). Participants are queried sequentially regarding four tobacco products: (1) cigarettes (menthol and tobacco only), (2) electronic cigarettes, (3) hookah, and shisha, (4) cigars/little cigars. The present study focused on e-cigarettes, with data from cigarette harm perceptions questions included for comparison. The presentation easel binder includes photos of products (e.g., electronic cigarette brands such as Blu), flavor images (e.g., fruit, alcohol), and response choices (e.g., 1-7 scale with anchors of extremely dislike to extremely like). The interview lasts approximately one hour.

2.2.4. Flavors Interview Measures

All measures were pilot tested with a sample of reproductive-aged woman (N = 630) (Scott-Sheldon & Stroud, 2018).

Lifetime use.

Participants were asked whether they had (1) ever heard (yes/no) or (2) ever tried (yes/no) each tobacco product (cigarettes, e-cigarettes, hookah, cigars). (Those who had never heard of the tobacco product were coded as never users.) Participants were also asked about which flavors of each tobacco product they had used. These measures were adapted from published e-cigarette measures (Krishnan-Sarin et al., 2015).

Preferences for e-cigarette tobacco flavorings.

Preferences for e-cigarette flavors were measured using 3 items reported on a 7-point scale (extremely dislike—extremely like, extremely unattractive—extremely attractive, not at all interested—very interested). Higher ratings indicate more positive preferences for the specific e-cigarette flavor. Preferences (i.e., attitudes) for e-cigarette flavorings were developed based on guidelines for the construction of behavior-change theory measures (Fishbein & Aizen, 2011).

Perceptions of e-cigarette and cigarette harm.

Participants were asked about their perceptions of general (“harmful for your health”) and pregnancy-related (“harmful for pregnant women to use,” “harmful to the fetus”) health risks of e-cigarette flavors using 3 items reported on a 7-point scale (not at all harmful—very harmful) adapted from published measures (Baeza-Loya et al., 2014; Popova & Ling 2013). Higher ratings indicate greater perceptions about the harmfulness (general, pregnancy-related) of e-cigarette flavors. The same questions were asked about cigarette flavors (menthol, tobacco) to allow for comparisons of harm perceptions between e-cigarettes and conventional cigarettes.

Intentions to use flavored e-cigarettes.

Participants were asked to report the likelihood that they would use flavored e-cigarettes after the baby is born using a 7-point scale (extremely unlikely—very likely). Higher scores indicate a greater likelihood of using flavored e-cigarettes. Behavioral intentions for e-cigarette flavorings were developed based on guidelines for the construction of behavior-change theory measures (Fishbein & Aizen, 2011).

2.3. Statistical Analysis.

2.3.1. Sample Characteristics and Patterns of Use

Two-sample t and chi-square tests were used to assess differences between lifetime e-cigarette exposure groups (e-cigarette users vs. non-users, regardless of flavors used) (Table 1). Patterns of use involved counts of individual e-cigarette flavor use from the TLFB. Measures of preferences, perceptions, and intentions toward e-cigarette flavors were significantly skewed. Thus, differences in overall preferences, perceptions, and intentions for each e-cigarette flavor were evaluated using Kruskal-Wallis analysis of variance, a non-parametric rank-based method that does not rely on normality assumptions (Table 2). Differences between flavors preferences, perceptions, and intentions by lifetime e-cigarette use vs. lifetime e-cigarette non-use (regardless of flavor used) were assessed using a two-sample Wilcoxon test (Table 3).

Table 1.

Sample Characteristics by Lifetime E-Cigarette Use (N = 100).

Total Sample E-Cig User Non-User
(N = 100)
% (n)		 (n = 45)
% (n)		 (n = 55)
% (n)		 p-value
Maternal Characteristics
 Age (years) M (SD) 26 (4) 27 (5) 26(4) .283
 Non-White Race 56% (56) 51% (23) 60% (33) .373
 Hispanic Ethnicity 31% (31) 20% (9) 40% (22) .031
 ≤ HS education 48% (48) 49% (22) 47% (26) .872
 Income <$30,000/year 64% (64) 59% (26) 70% (38) .243
 Unemployed 33% (33) 38% (17) 29% (16) .358
 Gravida M (SD) 3(2) 3(2) 2(2) .932
 Parity M (SD) 1(1) 2(1) 1(1) .100
Pregnancy Tobacco & Substance Use/Exposure
 Any Cigarette 50% (50) 82% (37) 24% (13) < .001
 Any Hookah 11% (11) 11% (5) 10% (6) .974
 Any Cigar 14% (14) 13% (6) 16% (8) .862
 Any Alcohol 64% (64) 67% (30) 62% (34) .615
 Any Marijuana 46% (46) 51% (23) 42% (23) .354
 Secondhand smoke exposure 52% (52) 67% (30) 40% (22) .008
Lifetime Tobacco Use
 Any cigarette 74% (74) 96% (43) 56% (31) < .001
 Any hookah 83% (83) 93% (42) 75% (41) .013
 Any cigar 63% (63) 76% (34) 53% (29) .019
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NOTE: E-Cig = E-cigarette. Because of the N = 100 sample size, all prevalence/count variables are equivalent to percentages for the total sample column.

Table 2.

Preferences and perceptions of e-cigarette flavors in pregnant women (N = 100)

Preference Scale Fruit
M (SD) 		Candy
M (SD) 		Mint/Menthol
M (SD) 		Alcohol
M (SD) 		Coffee
M (SD) 		Chocolate
M (SD) 		Spice
M (SD) 		Tobacco
M (SD) 		Kruskal -
Wallis (X2) 		p
Liking 3.56 (2.13) 3.29 (2.25) 2.80 (2.08) 2.55 (1.99) 1.91 (1.49) 2.19 (1.79) 1.58 (1.22) 1.61 (1.42) 101.09 <.001
Attractiveness 3.02 (2.02) 3.02 (2.05) 2.46 (1.89) 2.55 (1.96) 2.07 (1.51) 2.28 (1.72) 1.77 (1.32) 1.74 (1.34) 51.82 <.001
Interest 2.67 (2.16) 2.45 (2.01) 2.01 (1.83) 2.01 (1.84) 1.57 (1.18) 1.71 (1.41) 1.33 (0.91) 1.34 (1.08) 52.28 <.001
Intentions 1.54 (1.30) 1.45 (1.15) 1.38 (1.06) 1.36 (1.11) 1.27 (0.80) 1.17 (0.64) 1.18 (0.72) 1.10 (0.52) 16.97 .018
General Health Risks 5.52 (1.62) 5.50 (1.67) 5.65 (1.55) 5.65 (1.59) 5.57 (1.61) 5.55 (1.61) 5.58 (1.57) 5.74 (1.58) 1.83 .969
Pregnancy Health Risks 6.46 (1.19) 6.51 (1.09) 6.49 (1.18) 6.56 (1.04) 6.52 (1.07) 6.47 (1.16) 6.50 (1.10) 6.58 (1.02) 0.50 .999
Fetal Health Risks 6.37 (1.27) 6.40 (1.22) 6.43 (1.17) 6.45 (1.16) 6.40 (1.17) 6.40 (1.22) 6.42 (1.17) 6.48 (1.09) 0.38 .999
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Note. All preferences and perception scales are 1-7 scales, with 1 being lowest appeal or risk. Intentions indicates intentions to use flavor after the baby is born. Statistically significant p values denote differences across all flavors for a given preference or perception based on Kruskal-Wallis X2 tests.

Table 3.

Mean flavor perceptions by lifetime use of e-cigarettes among pregnant women (N = 100).

Flavors
Preference Scale e-Cig Use Fruit Candy Mint/
Menthol		 Alcohol Coffee Chocolate Spice Tobacco
Liking User 4.40*** 3.69 3.69*** 2.76 1.91 2.22 1.67 2.00**
Non-User 2.87*** 2.96 2.07*** 2.38 1.91 2.16 1.51 1.29**
Attractiveness User 3.36 3.20 2.96* 2.71 2.00 2.36 1.82 1.96
Non-User 2.75 2.87 2.05* 2.42 2.13 2.22 1.73 1.56
Interest User 3.29* 2.82 2.76*** 2.22 1.51 1.82 1.44 1.58
Non-User 2.16* 2.15 1.40*** 1.84 1.62 1.62 1.24 1.15
Intentions User 1.82* 1.56 1.51 1.44 1.33 1.18 1.24 1.07
Non-User 1.31* 1.36 1.44 1.29 1.22 1.16 1.13 1.13
General Harm User 5.22* 5.22* 5.27** 5.31* 5.29* 5.24* 5.27* 5.40**
Non-User 5.76* 5.73* 5.96** 5.93* 5.80* 5.80* 5.84* 6.02**
Pregnancy Harm User 6.20* 6.29* 6.22* 6.36* 6.31* 6.24* 6.27* 6.40*
Non-User 6.67* 6.69* 6.71* 6.73* 6.69* 6.65* 6.69* 6.73*
Fetal Harm User 6.04* 6.11* 6.13* 6.18* 6.11* 6.11* 6.13* 6.24*
Non-User 6.64* 6.64* 6.67* 6.67* 6.64* 6.64* 6.65* 6.67*
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Note. E-Cig = e-Cigarettes. Use groups are based on lifetime e-cigarette use regardless of flavor (n=45 lifetime e-cigarette users; n=55 lifetime e-cigarette non-users). All preference and perception scales are 1-7 scales, with 1 being lowest appeal or risk. Intentions indicates intentions to use flavor after the baby is born. Bold font indicates statistically significant differences between lifetime e-cigarette users and non-users by Wilcoxon test.

*

p<.05

**

p<.01

***

p<.001.

2.3.2. Correspondence Analysis

The final set of ratings was organized in two complementary sets of contingency tables: (a) Flavors by preferences, perceptions, and intentions comprising seven 8 × 7 tables whose rows were the eight flavor categories, and whose columns were the response categories on the seven scales measuring e-cigarette preferences, perceptions, and intentions, and (b) Preferences, perceptions, and intentions by flavors: eight 7 × 8 tables, whose rows were the seven scales measuring e-cigarette preferences, perceptions, and intentions, and whose columns were the eight flavors. In both cases, table entries corresponded to frequency counts for a specific preference, perception, or intention by flavor combination (e.g. the number of participants endorsing the strongest intention to use fruit-flavored e-cigarettes). These tables were analyzed using correspondence analysis (Gabriel, 1971; Greenacre, 1984), a mapping technique that enables the simultaneous display of the rows and columns of a contingency table as points in a latent factor space, with inter-point distances defined by the χ2 metric. Correspondence analysis allows for the identification of clusters of rows and columns with similar distributional characteristics, as well as to graphically depict row-column associations, based on row-column proximity in factor space.

Row-principal biplots (Gabriel, 1971; Gower & Hand, 2006) were used to present graphical output from correspondence analyses of both sets of contingency tables. These plots use arrows to represent (a) flavors or (b) preferences/perceptions/intentions and dots to identify study participants. The tip of each arrow corresponds to the highest rating on a given scale; its base corresponds to the lowest rating. Arrows pointing in similar directions indicate positively-correlated scales; uncorrelated scales appear at right angles. All three harm perception scales were reverse scored, so that high ratings on these scales correspond to low perceptions of harm. With this recoding, we expect that all preferences, perceptions, and intentions towards flavored e-cigarettes to be positively correlated. Longer arrows reflect skewness in the ratings distribution, typical of less preferred flavors (e.g., tobacco) or harm perception scales; shorter arrows indicate that the entire range of the 7-point scale has been used by participants. As the origin intersects each arrow at the sample mean of each rating scale, arrows for symmetrically distributed rating scales are bisected by the origin, while they are cut into uneven line segments when skewness is present. Because of the discrete nature of the rating scales, response patterns can overlap and the same dot may represent the factor score of more than one study participant.

3. Results

3.1. Sample Characteristics

The sample included 100 pregnant mothers (M age = 26, range = 18-38). Table 1 provides descriptive statistics for the overall sample (N = 100) and by lifetime e-cigarette use (n = 45 e-cigarette users, n = 55 e-cigarette non-users). The sample was primarily of low socioeconomic status (48% had a high school education or less; 33% were unemployed; 64% had an annual household income <$30,000), and ethnically diverse (65% minorities). Eighty-three percent of mothers were unmarried; most pregnancies (62%) were unplanned. The sample reported using alcohol (64%), marijuana (46%), and other tobacco products (50% cigarettes, 11% hookah, 14% cigars) at least once during pregnancy. Fewer Hispanics reported ever using e-cigarettes, p = .031; otherwise, no significant demographic differences emerged between e-cigarette users and non-users. E-cigarette users were also significantly more likely to smoke cigarettes during pregnancy (p < .001), to be exposed to second-hand smoke during pregnancy (p < .01), and to endorse lifetime use of cigarettes, hookah, and cigars (ps ≤ .02).

3.1.2. Prevalence and patterns of use of flavored e-cigarettes

Prevalence of any lifetime e-cigarette use was 45%. Of these, 69% (n = 31) reported using mint/menthol, 64% (n = 29) fruit, 20% (n = 9) tobacco, 18% (n = 8) candy, 11% (n = 5) chocolate, 9% (n = 4) coffee or spice, 7% (n = 3) alcohol, and 4% (n = 3) other/mixed flavors. Prevalence of any e-cigarette use across the peripartum period was 16%, with 9% endorsing e-cigarette use (regardless of flavor) in preconception (3 months prior to pregnancy), 9% endorsing use during pregnancy, and 3% endorsing use within one month postpartum. Of these, 63% (n = 10) endorsed more than one-time use (Med = 133; range = 2-85); 38% (n = 6) endorsed one-time use. Sixty-nine percent (n = 11) reported using fruit, 19% (n = 3) candy, 19% (n = 3) mint, 13% (n = 2) tobacco, 6% (n = 1) spice, and 6% (n = 1) coffee (or other beverage) flavors. No mothers endorsed use of chocolate or alcohol flavors in the peripartum period. Twenty-five percent (n = 4) endorsed use of multiple flavors over the peripartum period (e.g., fruit and candy). Figure 1 shows days of use of each flavor by each of the 16 peripartum e-cigarette users. Overall, participants endorsed using fruit-flavored e-cigarette the most during the preconception and pregnancy periods, but more days of use of candy, spice, and coffee flavors in the postpartum period.

Figure 1.

Figure 1.

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Frequency of use of individual e-cigarette flavors over preconception, pregnancy and postpartum by 16 peripartum e-cigarette users.

3.2. Preferences, perceptions, and intentions to use e-cigarette flavors.

Preferences, perceptions, and intentions for each e-cigarette flavor are shown in Table 2. Sweet-flavored e-cigarettes (fruit and candy) were the most preferred, followed by mint and alcohol, and coffee, chocolate and spice. Variability in mean preference ratings across flavors was widest for liking, more moderate for attractiveness, and narrowest for interest. Significant between-flavor differences emerged for all 3 preference scales (ps <.001). Differences in intentions were also significant (p <.02), anchored by the contrasts between sweet (fruit and candy) and tobacco flavors. We found little influence of e-cigarette flavors on harm perceptions (ps >.96). The average risk of harm was perceived as very high (>5.5 on 7-point scale) for general health, and as extremely high (>6.3 on 7-point scale) for both pregnancy and fetal health. Although average risks of harm were perceived as high, they were lower across all perceptions versus either tobacco or menthol cigarettes (>6.4, >6.8, and >6.7, respectively for general, pregnancy, and fetal harm; ps<.001).

3.3. Clustering of flavors by preferences, perceptions, and intentions.

Biplots for preferences and intentions for the eight flavors are shown in Figure 2, and confirm our hypotheses regarding the polarity of fruit and candy vs. tobacco but also clarify the relative positions of the remaining flavors, with mint and alcohol depicted as being closest to the fruit and candy pole, and spice, coffee and chocolate shown closest to the tobacco pole in terms of liking, attractiveness, and intentions. The interest biplot differed from the other three biplots, revealing close associations between the ratings of all flavors other than mint and tobacco. In all preference biplots, participant ratings converged on the origin for tobacco, but showed more variability for fruit and candy, suggesting a low preference for tobacco-flavored e-cigarettes, but increased preference for sweet flavors. Total variance explained by the first two latent factors was 64% for liking, 75% for attractiveness, 69% for interest, and 83% for intentions, suggesting that factor scores for the first two latent dimensions from the correspondence analysis provide an adequate 2-dimensional representation of the original scores across the eight flavors.

Figure 2.

Figure 2.

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Biplots of e-cigarette flavors by: (a) liking, (b) attractiveness, (c) interest, and (d) intentions scales.

Note: Arrows represent e-cigarette flavor ratings and dots represent identify individual study participants. The tip of each arrow corresponds to the highest rating on each Likert scale; the base corresponds to the lowest rating. Arrows pointing in similar directions indicate positively-correlated scales; uncorrelated scales appear at right angles. Longer arrows reflect skewness in the ratings distribution; shorter arrows indicate that the entire range of the 7-point scale has been used. Because of the discrete nature of the rating scales, the same dot may represent more than one study participant.

Biplots for the three harm perception measures for the eight flavors are shown in Figure 3, and are also dominated by a sweet vs. tobacco flavors contrast consistent with biplots for preferences and intentions. Increased variability between participants in harm perceptions was evident along the spice/chocolate/coffee pole, driven by a small number of participants who endorsed lower harm ratings for spice/coffee/chocolate, despite elevated harm ratings for the remaining flavors. However, this small number of participants did not significantly affect overall mean harm ratings. As the first latent factor explains 95-97% of the variance for the three health risk scales, dimension reduction appears remarkably successful.

Figure 3.

Figure 3.

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Biplots of e-cigarette flavors by harm perceptions: (a) risks to general health, (b) risks during pregnancy, (c) risks to the fetus.

Note: Arrows represent e-cigarette flavors and dots represent identify individual study participants. Harm perceptions were reverse scored for simplicity of visualization.

3.4. Clustering of preferences, perceptions, and intentions by flavor.

Biplots for the 7 preference, perception, and intentions scales across 3 representative flavors (fruit, candy, tobacco) are shown in Figure 4. In all three biplots, preferences (liking, attractiveness, interest) for e-cigarettes were nearly orthogonal to the 3 harm perception scales, indicating little association between these two sets of preferences/perceptions. Clustering of the arrows for the three preferences and three harm perceptions scales indicated strong and positive within-cluster correlations. Within the harm perceptions cluster, the pregnancy and fetal harm arrows were longer and were tightly clustered around the origin versus the general harm scale, indicating elevated health concerns in the perinatal periods. The intention pole differed by flavor, showing closer alignment with preferences for fruit, mint, and alcohol favors, but with harm perceptions for tobacco, and between the two clusters for candy, chocolate, coffee, and spice.

Figure 4.

Figure 4.

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Biplots of preference and perception scales by e-cigarettes with (a) fruit, (b) candy, and (c) tobacco flavors.

Note: Arrows represent e-cigarette preferences, perceptions, and intentions, and dots represent identify individual study participants. Harm perceptions were reverse scored for simplicity of visualization.

3.5. Association between e-cigarette flavor preferences, perceptions, and intentions and use.

Table 3 documents the associations between preference, perceptions, and intentions towards e-cigarette flavors and lifetime use of e-cigarettes. Higher preferences for fruit and mint flavors significantly differentiated lifetime e-cigarette users from non-users (ps <05); differences between users and non-users were especially large for the liking scale (ps <.001). Lifetime users also reported significantly higher liking for tobacco flavor vs non-users (p <.01), Only fruit flavors significantly differentiated users from non-users for the intentions scale (p <.05). In contrast to preferences and intentions, harm perceptions appear uniformly elevated for e-cigarette non-users versus e-cigarette users for all three health scales (general, pregnancy, fetal), with few differences by flavor.

4. Discussion

We investigated patterns of use, preferences, and perceptions of flavored e-cigarettes in a diverse, low-income sample of pregnant tobacco users and non-users. Pregnant women endorsed greatest use of fruit flavored e-cigarettes in the preconception and pregnancy periods and showed strongest preferences for sweet flavors (fruit and candy) and weakest preferences for tobacco flavors. Our correspondence analyses revealed clustering of more-preferred fruit and candy flavors versus least-preferred tobacco flavored e-cigarettes, with other sweet flavors—mint and alcohol—clustering more closely together with fruit and candy flavors, and with more pungent flavors—spice, coffee, and chocolate—clustering with tobacco. Correspondence analysis also revealed uncorrelated clustering of preferences (liking, attractiveness, and interest) and harm perceptions (general, pregnancy, and fetal harms), with intentions showing associations with both preferences and perceptions. Finally, preferences for fruit and mint flavors, intentions to use fruit flavors, and decreased harm perceptions across flavors distinguished lifetime e-cigarette users from lifetime e-cigarette non-users in this vulnerable population.

To our knowledge, the present study is the first to assess patterns of use, preferences, and perceptions of e-cigarette flavors in pregnant women and the first to apply a correspondence analysis, a latent factor mapping technique typically used in consumer marketing research, to new tobacco product. Additional strengths of the study are: (a) detailed characterization of flavor preferences and perceptions by in-person interview, (b) detailed characterization of tobacco product and flavor use via Timeline Followback methodology (Robinson et al., 2014), (c) focus on an a highly vulnerable population, and (d) underserved, low-income, ethnically diverse (65% minorities) sample.

High rates of use of fruit and mint flavors as well as preferences for and intentions to use sweet and mint flavors versus tobacco and more bitter flavors are consistent with our hypotheses and with prior studies of use and preferences for flavored e-cigarettes in adults, young adults, and youth (Zare, Nemati, & Zheng, 2018b). For example, order of prevalence for use of e-cigarette flavors in a sample of 75,233 US adults was fruit (45%), mint (44%), and candy/chocolate/other sweet flavors (26%) (Bonhomme et al., 2016). Similarly, a laboratory vaping study revealed that liking was highest for e-cigarette flavors perceived as sweet and cool, but lowest for flavors perceived as bitter or harsh (Kim et al., 2016). Similar findings are evident for young adults, who have been shown to prefer fruit and mint flavors (Czoli, Goniewicz, Islam, Kotnowski, & Hammond, 2016), and who showed greater “liking/wanting” for e-cigarettes with higher concentrations of menthol in a laboratory study (Krishnan-Sarin et al., 2017). Therefore, our results extend findings from adults as well as another vulnerable population—youth—to pregnant women (Zare et al., 2018b).

In contrast to preferences and intentions, we did not find differences in harm perceptions by sweet or mint flavors. Instead, harm perceptions were high across flavors and were not correlated with preferences in the correspondence analyses. Results contrast with prior studies of harm perceptions across flavors in youth, where fruit and sweet-flavored e-cigarettes were perceived as less harmful than tobacco flavored e-cigarettes (Dai & Hao, 2016; Ford, MacKintosh, Bauld, Moodie, & Hastings, 2016; Pepper, Ribisl, & Brewer, 2016). Lack of differences in harm perceptions across flavors may relate to public health and education campaigns regarding dangers of tobacco use during pregnancy. Indeed, perceptions of pregnancy and fetal harm were uniformly high (average of >6.3 on 7-point scale); perceptions of “general” health risks were also high, but showed more variability than pregnancy and fetal health risks. Across all harm perceptions (general, pregnancy, and fetal), however, e-cigarettes were perceived as less harmful than cigarettes. These findings complement prior research showing decreased risk perceptions for e-cigarettes vs. conventional cigarettes in pregnant women (Ashford et al., 2016; McCubbin et al., 2017).

We acknowledge several limitations of our study. First, pregnant mothers in our study were queried once during third trimester regarding their preferences and perceptions of e-cigarette flavors. Given changes in taste, cravings, and nausea over gestation, future studies involving prospective assessment of flavors preferences over pregnancy would be informative. Second, although we assessed preferences for multiple broad categories of e-cigarette flavors (e.g., fruit, candy), we did not assess preference for specific flavors within each category. Given the popularity of fruit flavors, investigating specific fruit-flavored e-cigarettes would be informative. Third, data were not available to determine lifetime smoking status of study participants; thus, the extent to which e-cigarettes are used for smoking cessation or as product substitution in this sample is unknown. Finally, our study sampled a small number (N = 100) of low-income, diverse pregnant mothers. In addition, only nine mothers endorsed e-cigarette use during pregnancy; thus, estimates for flavor use and preferences during pregnancy may not be reliable or generalizable. Future large-scale prospective studies of pregnant e-cigarette users are needed to further investigate preferences for flavors during pregnancy as well as links between flavor preferences and use of e-cigarettes in pregnancy, preconception and postpartum periods.

Findings from the present study have several methodological, clinical, and regulatory implications: (1) Methodological: The present study highlights the utility of correspondence analysis for identifying clustering of both flavors and perceptions/preferences in relation to novel tobacco products. Future research might apply these techniques to additional tobacco products (e.g., hookah, cigars), attributes (e.g., design characteristics), and perceptions (e.g., sensory perceptions). Correspondence analysis and latent factor mapping might also be used to display differences between participant characteristics (e.g., race, other substance use) in relation to flavors and perceptions. (2) Clinical: Flavored e-cigarettes were perceived as harmful for the fetus, for pregnant women, and for general health, although they were perceived as less harmful than cigarettes. Additional research is needed to determine whether pregnant women are using e-cigarettes to help quit cigarettes in pregnancy or as a substitute or alternative to cigarettes during pregnancy (England et al., 2016; Oncken et al., 2017). Also needed is research on the impact (and relative impact vs. cigarettes) of e-cigarettes on human fetal development (Suter, Mastrobattista, Sachs, & Aagaard, 2015). Complementing prior research showing associations between e-cigarette use and decreased harm perceptions (Bernat, Gasquet, Wilson, Porter, & Choi, 2018; J. C. Chen, Green, Arria, & Borzekowski, 2018; Cooper, Harrell, Perez, Delk, & Perry, 2016; Nguyen, Tong, Marynak, & King, 2016), pregnant women who endorsed lifetime use of e-cigarettes showed lower harm perceptions than pregnant women who did not endorse lifetime e-cigarette use. Results highlight the importance of screening for current and lifetime e-cigarette use during prenatal care and counseling around potential risks of e-cigarette use during pregnancy (Ashford et al., 2016; Kurti et al., 2017; McCubbin et al., 2017; Wagner et al., 2017). (3) Regulatory: Similar to other adult populations, sweet flavors were preferred relative to tobacco flavor and were important in differentiating lifetime e-cigarette users and e-cigarette non-users. Although the impact of e-cigarettes and e-cigarette flavorings on fetal and child development is unknown, both nicotine and combustion products are known developmental toxicants in human and animal models. As regulatory policies regarding flavors in e-cigarettes and other tobacco products are being crafted (U.S. Food and Drug Administration, 2018), it may be relevant to consider that pregnant women are another population who shows preference for sweet-flavored e-cigarettes and that preferences for sweet flavors (especially fruit and mint) were associated with lifetime e-cigarette use prior to pregnancy. Continued research on e-cigarette perceptions and e-cigarette use over the course pregnancy is needed to further inform the development and impact of regulatory policies regarding e-cigarette flavors.

4.1. Conclusions.

Results highlight the utility of correspondence analysis for investigating flavor preferences and perceptions in new tobacco products. Results also suggest that similar to other adult populations and youth, pregnant women show greatest preference for sweet flavored e-cigarettes, and that preferences for sweet flavors were associated with lifetime use prior to pregnancy. Flavors preferences among pregnant women may inform tobacco product regulatory policy.

HIGHLIGHTS.

  • Fruit flavored e-cigarettes were most commonly used during pregnancy.

  • Sweet and mint flavors were most preferred; tobacco flavor was least preferred.

  • Preference for sweet flavors distinguished lifetime e-cigarette users and non-users.

  • Correspondence analysis is a useful tool to examine flavor preferences.

  • Results may inform regulatory policy regarding flavored tobacco products.

Acknowledgements

We gratefully acknowledge the women who contributed to this study. We are also grateful to the Maternal-Infant Studies Laboratory staff, especially Jennifer Caetano and Jillian Roche, for their assistance with data collection, and Geidy Nolasco with study administration. We thank Pamela Borek for administrative assistance with this manuscript.

Role of Funding Sources

Funding for this study and manuscript preparation was supported by the National Institute on Drug Abuse (NIDA) of the National Institutes of Health and the Center for Tobacco Products of the U.S. Food and Drug Administration (FDA) under grant 5R01DA036999-02S2 to Laura R. Stroud, PhD, as well as grants NIDA grants 5R01DA036999 and 5R01DA045492 to Laura R. Stroud, PhD. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health or the Food and Drug Administration. NIDA, CTP, and FDA 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.

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